UvA-DARE (Digital Academic Repository) Interactions between circadian clocks and feeding behaviour Sen, S.K. Publication date 2018 Document Version Final published version License Other Link to publication Citation for published version (APA): Sen, S. K. (2018). Interactions between circadian clocks and feeding behaviour. General rights It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. UvA-DARE is a service provided by the library of the University of Amsterdam (https://dare.uva.nl) Download date:17 Oct 2022 Interactions between circadian clocks and feeding behaviour Interactions between circadian clocks and feeding behaviour REV-ERB PER BMAL1 CLOCK 2 CRY AVP ROR Satish Kumar Sen Satish Kumar Sen Interactions between circadian clocks and feeding behaviour. Satish Kumar Sen        2 UNIVERSITE DE STRASBOURG France UNIVERSITE D'AMSTERDAM PAYS-BAS ÉCOLE DOCTORALE Sciences de la Vie et de la Santé Institut des Neurosciences Cellulaires et Intégratives de Strasbourg THÈSE EN COTUTELLE présentée par : SATISH KUMAR SEN Soutenue le : 09 July 2018 Pour obtenir le grade de : Docteur de l’université de Strasbourg & Docteur de l'université d'Amsterdam Discipline/Spécialité : Sciences du vivant / Neurosciences Interactions between circadian clocks and feeding behaviour THÈSE dirigée par: Dr. CHALLET E. Prof. KALSBEEK A. Docteur, Université de Strasbourg Professeur, Université d'Amsterdam RAPPORTEURS: Prof. OSTER H. Prof. SCHLICHTER R. Dr. FELDER-SCHMITTBUHL M.P. Prof. LA FLEUR S. Dr. YI C.X. Professeur, Université de Lübeck Professeur, Université de Strasbourg Docteur, Université de Strasbourg Professeur, Université d'Amsterdam Docteur, Université d'Amsterdam 3 Interactions between circadian clocks and feeding behaviour ACADEMISCH PROEFSCHRIFT ter verkrijging van de graad van doctor aan de Universiteit van Amsterdam op gezag van de Rector Magnificus prof. dr. ir. K.I.J. Maex ten overstaan van een door het college voor promoties ingestelde commissie in het openbaar te verdedigen in het Institut des Neurosciences Cellulaires et Intégratives de Strasbourg op maandag 9 Juli 2018, te 14:00 uur door SATISH KUMAR SEN geboren te Bina, India 4 PROMOTIECOMMISSIE: Promotores : Overige leden : Prof. Dr. A. Kalsbeek Universiteit van Amsterdam Dr. E. Challet Universiteit van Straatsburg Prof. Dr. H. Oster Universiteit van Lübeck Prof. Dr. R. Schlichter Universiteit van Straatsburg Dr. M.P. Felder-Schmittbuhl Universiteit van Straatsburg Prof. Dr. S.E. la Fleur Universiteit van Amsterdam Dr. C.X. Yi Universiteit van Amsterdam Faculteit der Geneeskunde Dit proefschrift is tot stand gekomen in het kader van het NeuroTime programma, een Erasmus Mundus Joint Doctorate, met als doel het behalen van een gezamenlijk doctoraat. Het proefschrift is voorbereid in: het Nederlands Herseninstituut en in het Academisch Medisch Centrum (AMC), Faculteit der Geneeskunde, van de Universiteit van Amsterdam; en in het Institut des Neurosciences Cellulaires et Intégratives van de Université de Strasbourg. This thesis has been written within the framework of the NeuroTime program, an Erasmus Mundus Joint Doctorate, with the purpose of obtaining a joint doctorate degree. The thesis was prepared in: the Netherlands Institute for Neuroscience (NIN) and in the Academic Medical Centre (AMC), Faculty of Medicine at the University of Amsterdam; and in the Institut des Neurosciences Cellulaires et Intégratives of the Université de Strasbourg. 5 6 Contents Chapter 1 ........................................................................................................................... 9 General introduction Chapter 2 ......................................................................................................................... 63 Ultradian feeding in mice not only affects the peripheral clock in the liver, but also the master clock in the brain .................................................................................................. 63 Chapter 3 ......................................................................................................................... 99 An ultradian feeding schedule in rats differentially affects peripheral clocks in liver, brown adipose tissue and skeletal muscle and lipid metabolism, but not the central clock in SCN ............................................................................................................................... 99 Chapter 4 ....................................................................................................................... 137 Differential effects of diet composition and timing of feeding behavior on rat Brown adipose tissue and skeletal muscle peripheral clocks. .................................................... 137 Chapter 5 ....................................................................................................................... 167 Expression of the clock gene Rev-erbα in the brain controls the circadian organization of food intake and locomotor activity, but not daily variations of energy metabolism ...... 167 Chapter 6 ....................................................................................................................... 195 Discussion and perspectives ........................................................................................... 195 Summary ......................................................................................................................... 209 Samenvatting .................................................................................................................. 216 Résumé............................................................................................................................ 220 PhD Portfolio .................................................................................................................. 231 7 8 Chapter 1 General Introduction Chapter 1 ............................................................................................................................. 9 General Introduction ........................................................................................................... 9 1. Introduction of rhythms ......................................................................................... 10 1.1. Circadian rhythms .......................................................................................................... 11 1.2. Infradian rhythms ........................................................................................................... 12 1.3. Ultradian rhythms ........................................................................................................... 13 2. 3. Molecular mechanism underlying generation of circadian rhythms ..................... 13 Circadian clocks: A multi-oscillatory system ........................................................ 15 3.1 Master clock in the suprachiasmatic nucleus (SCN) ................................................. 15 3.2 Peripheral clocks ............................................................................................................. 21 4. 5. Circadian control of plasma metabolites and hormones ........................................ 24 Interactions between the circadian clock system, feeding and metabolism. ......... 30 5.1 Restricted feeding and calorie restriction .............................................................. 30 5.2 Diet and its impact on circadian clocks. ..................................................................... 33 5.3 Clock genes in relation to metabolic genes ................................................................. 34 5.4 The nuclear receptor REV-ERBα in relation to circadian clock and metabolism .............................................................................................................................. 36 6. Aim of my thesis ........................................................................................................... 41 Chapter 2 Effects of ultradian feeding on central and peripheral clocks in mice ......................................................................................................................................... 41 Chapter 3 Effects of ultradian feeding on central and peripheral clocks in rats ........... 42 Chapter 4 Differential effects of diet composition and timing of feeding behaviour on rat brown adipose tissue and skeletal muscle peripheral clocks .............. 42 Chapter 5 Role of the clock gene Rev-erbα in feeding and energy metabolism ............................................................................................................................. 42 9 1. Introduction of rhythms The sun and moon are important for the existence of life on earth. The sun gives energy in the form of light, the moon reflects light from the sun and makes tidal waves. Life on our terrestrial planet originated nearly about 3.8 billion years ago from the transition of nonliving to living systems through the process of biogenesis. The moon orbits around the earth and the earth moves around the sun. The rotation of the earth around its own axis gives rise to day and night cycles, according to which the physiology of most living organisms responds. Most living organisms, whether they are uni- or multi-cellular, express day and night cycles. Daily rhythms were first described in a written report by Androsthenes of Thasos around 4th century B.C.E. (mentioned in (Bretzl, 1903) after observing the daily periodic movement of the leaves of the tamarind tree, Tamarindus indica. In 1729, the French astronomer Jean-Jacques d’Ortous de Mairan observed that every day the leaves of the Mimosa pudica opened during the day and closed at night. To confirm whether this opening and closing of the leaves was due to sunrise and sunset, he kept a plant in constant darkness and observed that the leaves still opened and closed at the usual time of day. Through this experiment he demonstrated the existence of an internal timing system in Mimosa pudica. Thirty years later, Henri-Louis Duhamel du Moceau, a French botanist, showed that the movement of leaves in constant darkness was independent of the environmental temperature changes, thus providing further evidence for the internal origin of this rhythm (McClung, 2006). In the 1930’s Erwin Bünning, a German biologist, evidenced the genetic origin of circadian rhythms by crossing bean plants with different endogenous periods. In the daily life of animal species, daily rhythms are expressed in a wide range of biological processes, such as their rest-activity cycle, hormone release and body temperature rhythm. Daily rhythms can be defined as sequences of events having a defined period of 24 hours and specific phase and amplitude for that particular event (Figure 1). In the human physiological system many events are organized in time, with most (locomotor) activity occurring during daytime and sleep and rest during the night. Also other events take place at specific times of day, like body temperature reaching its nadir level at the beginning of the night and melatonin being released from the pineal gland only during the night. 10 Figure 1: Parameters used to describe a biological rhythm: The period is defined as the time required to complete one cycle. Mesor is the average value around which the variable measured oscillates. The amplitude of the rhythms is defined as the difference between the mesor and the acrophase (or bathyphase). Acrophase and bathyphase represent the time points when the parameter measured shows the highest or the lowest values, respectively. 1.1. Circadian rhythms The daily rhythmicity of the external behavior of an organism is due to its internal circadian clock (Pittendrigh, 1993). The term “circadian”, which was first used by Franz Halberg in 1950s, arises from the Latin words circa which means “around” and dies for “day”. The circadian rhythms comprise biological processes with a period length of about 24 h (20-28 h), thus completing their cycle in approximately one day. Circadian rhythms are endogenous in nature. These self-sustained circadian rhythms can be investigated by measuring external behavioural and physiological parameters like locomotor activity and body temperature under constant (lightening) conditions. In 1960, Jürgen Aschoff observed lengthening and shortening of period length, in respectively nocturnal and diurnal animals, under constant light conditions, in response to an increase in light intensity. When there are no external environmental cues such as light, i.e., under constant dark (DD) conditions, with food ad libitum, circadian rhythms in rats and mice persist and show so-called free-running (Figure 2) (Aschoff, 1965). A similar observation was made in humans, i.e., the existence of free-running rhythms in constant conditions, by Michel Siffre, a French explorer and scientist, staying voluntarily in an isolated cave for two months with no external time cues (Siffre, 1963). A process known as entrainment allows 11 circadian rhythms to be synchronized to the external environment by setting the endogenous period to exactly 24 h. Hence circadian entrainment is important for living organisms to be in phase with the daily variations in the environment. The light-dark (LD) cycle is the primary external entraining cue for the synchronization of circadian rhythms. All mammalian species respond to LD cycles by timing their body physiology and metabolism to a specific phase of the LD cycle, like eating during the dark phase and sleeping during the light phase in nocturnal species. Figure 2: Schematic representation of rodent single plotted actogram. The above activity plot, or so-called actogram, represents a rhythm of locomotor activity initially entrained to the 24-h light-dark (LD) cycle. Upon transfer to constant darkness (DD), a free-running circadian rhythm resumes with its endogenous period. The circadian clock drives the daily rhythm in body temperature, but also the sleep-wake cycle and level of motor activity affect this rhythm (Tokura and Aschoff, 1983; Refinetti and Menaker, 1992). The rhythm in body temperature is due to the difference in circadian variation of heat loss and production (Aschoff, 1983). Likewise, there are daily variations in many hormones, such as leptin from white adipose tissue, insulin from the endocrine pancreas and melatonin from the pineal gland. 1.2. Infradian rhythms Rhythms with a period (much) longer than 24 h are known as “infradian rhythms". These rhythms include 4-5 day rhythms to monthly rhythms, such as the estrous cycle in rodents and the menstrual cycle in humans, respectively. This category also includes lunar 12 rhythms, and seasonal rhythms like the shedding of leaves, reproduction in seasonal animals and migration of birds, among many others. 1.3. Ultradian rhythms Rhythms that occur with a period much shorter than 24 h are called “ultradian rhythms” (Halberg and Reinberg, 1967). These rhythms are known to be associated with feeding behaviour and various physiological processes, like pulsatile hormonal secretion, cardiovascular function, like heartbeat and blood pressure, and respiratory exchange of gases. 2. Molecular mechanism underlying generation of circadian rhythms In the early 1970s Seymour Benzer and his student Ron Konopka were the first to identify the mutation affecting circadian behaviour in Drosophila melanogaster in a gene they called Period (Konopka and Benzer, 1971). Later in the 1980s the molecular clock research work in Drosophila melanogaster was continued by the scientists Jeffrey Hall, Michael Rosbash and Michael Young who were honoured the Nobel prize for medicine or physiology in 2017 for deciphering the principles of the molecular mechanism of the circadian clock, i.e., the transcriptional-translational feedback loop (TTFL). The identification of clock genes in Drosophila helped in cloning mammalian clock genes. The molecular machinery of the circadian clock involves a collection of clock genes which are expressed rhythmically and control the clock oscillations. The complete core clock mechanism relies on positive and negative transcriptional, post-transcriptional, translational and post-translational feedback loops (Shearman et al., 2000; Reppert and Weaver, 2001) (Figure 3). In mammals, the two key elements involved in the molecular clock machinery are the basic helix-loop-helix (bHLH)/PAS-containing transcription factors BMAL1 and CLOCK (King et al., 1997; Gekakis et al., 1998; Hogenesch et al., 1998; Griffin et al., 1999; Bunger et al., 2000). BMAL1 and CLOCK heterodimerize and activate via E-box sequences the rhythmic transcription of other clock genes, like the Period genes (Per1, Per2 and Per3), the Cryptochrome genes (Cry1 and Cry2) (Griffin et al., 1999; Kume et al., 1999; van der Horst et al., 1999; Vitaterna et al., 1999; Shearman et al., 2000), Reverbα and Rorα (Preitner et al., 2002; Sato et al., 2004; Triqueneaux et al., 2004; Akashi and Takumi, 2005), and various clock-controlled genes like Vasopressin 13 (Avp), D site albumin promoter binding protein (Dbp) (Jin et al., 1999; Ripperger et al., 2000) and many others. These transcripts are translated in the cytoplasm. Figure 3: Molecular mechanism of mammalian circadian clock. Transcriptional-translational feedback loops of core clock genes. CLOCK and BMAL1 dimerize and activate the transcription of other clock genes such Per1&2, Cry1&2, Rorα, Rev-erbα by binding to E-boxes in their promoter region. After transcription of these clock genes they are translationally released in the cytoplasm. Translated PER and CRY proteins heterodimerize and translocate back to the nucleus to inhibit the transcription of their own genes by binding to BMAL1 and CLOCK. Clock proteins undergo post-translational modifications and ubiquitination for proteosomal degradation. Another loop involves the translocation of REV-ERBs and RORs into the nucleus to modulate transcription after binding to RORE sequences in the promoters of Bmal1 and Clock genes to activate or repress their transcription. From the cytoplasm, some of the clock proteins are translocated back to the nucleus to regulate their expression by interacting with the CLOCK/BMAL1 complex and interfering with its transcriptional activity. These proteins also regulate themselves through another loop by binding to the RORE sequences in the promoter region of CLOCK and BMAL1. The circadian expression of CLOCK and BMAL1 is regulated both positively and negatively by RORs and REV-ERBs, respectively. Many clock proteins also undergo post-translational modifications. This is an important mechanism for regulating more precisely the phase, amplitude and period of the circadian clocks, by modulating the stability and turnover of various clock proteins (Bellet and Sassone-Corsi, 2010). Important post-translational modifications are phosphorylation, sumoylation, acetylation, and ubiquitination. Phosphorylation regulates the cellular 14 localization and stability of various clock proteins and maintains the circadian period close to 24 h (Lee et al., 2001). Phosphorylation occurs at the phosphor-acceptor site on its substrate by kinases. Casine kinase Iε (CKIε) is one of the kinases which phosphorylate the PER proteins. A mutation in the gene encoding for CKIε, characterized as tau mutation, shortens the period of circadian rhythmicity in the Syrian hamster (Lowrey et al., 2000). Phosphorylation can also cause the recruitment of ubiquitin ligase adapter Fbox protein bTrC and target the clock proteins for ubiquitination-mediated proteasomal degradation (Eide et al., 2005; Shirogane et al., 2005; Bellet and Sassone-Corsi, 2010). There are various kinases which phosphorylate other clock proteins, including CKIε (Eide et al., 2002), mitogen-activated protein kinases (MAPKs) (Sanada et al., 2002), and CK2α (Tamaru et al., 2009) and glycogen synthase kinase 3β (GSK3 β) that all phosphorylate BMAL1 (Sahar et al., 2010). Furthermore, GSK3 β on its turn phosphorylates other clock proteins, such as CRY2 (Harada et al., 2005), PER2 (Iitaka et al., 2005), REV-ERBα (Yin et al., 2006) and CLOCK (Spengler et al., 2009). In addition to phosphorylation, sumoylation also controls the turnover of the clock proteins. The small ubiquitin-related modifier 1 (SUMO 1) protein, which regulates the process of SUMOylation in clock proteins (Cardone et al., 2005), sumoylates BMAL1 at a conserved lysine (K259) residue present in the PAS domain linker. Mutation of genes encoding for ubiquitin ligases can also abolish circadian rhythmicity. The F-box-type E3 ligase FBXL3 ubiquitinates the CRY1/2 proteins (Busino et al., 2007; Godinho et al., 2007; Siepka et al., 2007). Ovine CRY1 degradation can be reduced by FBXL3 and its homologue FBXL21 (Dardente et al., 2008). REV-ERBα undergoes degradation by the E3 ligases HUWE1/ARF-BP1 and PAM/MYC-BP2 and also by lithium which is an inhibitor of GSK3 β (Yin et al., 2010; Stojkovic et al., 2014). Another E3 ligase UBE3A binds and destabilizes BMAL1 (Gossan et al., 2014). Moreover, another pathway through which REV-ERBα is targeted for ubiquitination involves degradation by F-box protein FBXW7, resulting in an increased circadian amplitude (Zhao et al., 2016a). 3. Circadian clocks: A multi-oscillatory system 3.1 Master clock in the suprachiasmatic nucleus (SCN) The lesion studies by Richter in 1967 provided the evidence for the involvement of the anterior hypothalamus in the regulation of daily rhythms of locomotor activity. In 1972 15 Moore and Lenn identified that the SCN (Figure 4) in the anterior hypothalamus receive direct input from the retina. Figure 4: Localisation of the suprachiasmatic nucleus (SCN) in mice. Coronal section of a mouse brain showing the localization of the SCN above the OC. The below cresyl violet staining shows the cellular density in the SCN. OC: optic chiasma; 3V: third ventricle. Adapted from the Franklin-Paxinos atlas (Paxinos, 2004). Later that same year, Stephan and Zucker observed that bilateral electrolytic lesions of the SCN resulted in loss of daily rhythms of drinking behaviour and locomotor activity. Moreover, in the same year, Moore and Eichler found also that the daily rhythm in the adrenal amount of corticosterone was abolished in SCN-ablated rats (Moore and Eichler, 1972; Stephan and Zucker, 1972) (Figure 5). Not only behavioural responses, but also physiological responses, like body temperature, turned out to be SCN dependent. Lesions of the SCN eliminated the circadian rhythm of body temperature, although a few studies suggested a weak but significant circadian rhythmicity in body temperature after SCN lesions (Dunn et al., 1977; Fuller et al., 1981; Satinoff and Prosser, 1988), which may have been due to incomplete SCN lesions. In vivo electrical recordings in rats displayed the rhythmic firing rate of SCN neurons (Inouye and Kawamura, 1979) and in vitro electrical recording of cultured neonatal rat SCN cells provided the evidence for an endogenous pacemaker and single-cell circadian oscillators (Welsh et al., 1995). These 16 findings indicate that this circadian clock in the SCN is composed of multiple single-cell oscillators (Liu et al., 1997). Figure 5: Abolition of locomotor activity and drinking rhythms by SCN lesions in rats. Simultaneously recorded activity (A) and drinking (D) rhythms from an un-operated control rat (No. 226, top) and a rat with a bilateral suprachiasmatic lesion (No.9, bottom) during a 50-day period about 2 months after surgery. The control rat’s drinking activity is entrained to the light-dark cycle. There is no entrainment or circadian periodicity in the record of the rat with the lesion. Adapted from (Stephan and Zucker, 1972). The SCN was finally accepted as the central or master clock after the transplantation of fetal SCN tissue in SCN-lesioned animals and restoration of daily behavioural rhythms of locomotor activity (Drucker-Colin et al., 1984; Lehman et al., 1987; DeCoursey and Buggy, 1989; Ralph et al., 1990; LeSauter et al., 1996; Silver et al., 1996), although these transplants did not restore neuroendocrine rhythms (Meyer-Bernstein et al., 1999). Daily rhythms in body temperature, rest-activity and hormone release are controlled via neuroendocrine and autonomic nervous output pathways of the SCN (LeSauter et al., 1996; Ueyama et al., 1999; Kalsbeek et al., 2011). Light or photic cues are detected and integrated by the retina, and conveyed from the retina to the ventrolateral region of the SCN via the retinohypothalamic tract (Hendrickson et al., 1972; Moore and Lenn, 1972; Moore and Card, 1985; Moore, 1995). A small subpopulation of the retinal ganglion cells are intrinsically photosensitive because they contain the photopigment melanopsin. Many of these melanopsin-containing ganglion cells innervate the SCN (Provencio et al., 2000; Gooley et al., 2001; Hannibal et al., 2002; Hattar et al., 2002). Anterograde and retrograde tracing studies revealed the detailed topography of the SCN efferents (Watts and Swanson, 1987; Watts et al., 1987; Kalsbeek et al., 1993). The central SCN clock sends direct projections to secondary clocks of the 17 hypothalamus in the paraventricular nuclei (PVN), the ventromedial hypothalamic nuclei (VMH), the dorsomedial hypothalamic nuclei (DMH), the arcuate nuclei (ARC) and the retrochiasmatic area, whose daily timing is thus synchronized to the SCN clock. In addition, the SCN also sends its efferents directly to a few extra-hypothalamic areas such as the paraventricular nucleus of the thalamus (PVT), habenula and amygdala (AMY) (Kalsbeek and Buijs, 2002; Saper et al., 2005; Dibner et al., 2010) (Figure 6). Figure 6: Efferent pathways from the SCN SCN projections (red) to hypothalamic (yellow), thalamic (green) and sub-cortical (pink) brain regions. AMY, amygdala; ARC, arcuate nucleus; BNST, bed nucleus of the stria terminalis; DMH, dorsomedial hypothalamic nucleus; HB, habenula; IGL, intergeniculate leaflet; LS, lateral septum; POA, preoptic area; PVN, paraventricular nucleus of the hypothalamus; PVT, paraventricular nucleus of the thalamus; SCN, suprachiasmatic nuclei; sPVZ, subparaventricular zone. Modified from (Dibner et al., 2010). In turn, several hypothalamic nuclei, including the ARC and DMH, convey feeding and metabolic signals to the SCN clock (Challet and Mendoza, 2010). The ARC and DMH are involved in the regulation of feeding and energy metabolism (Guilding and Piggins, 2007; Williams and Elmquist, 2012). The ARC contains two populations of neurons which behave opposite with regard to their control of feeding behaviour. One population of neurons synthesizes Neuropeptide Y (NPY) and Agouti-related peptide (AgRP), which are both orexigenic. The other group of neurons synthesizes Pro-opiomelanocortin (POMC) and Cocaine and amphetamine regulated transcript (CART), which are both anorexigenic (Akabayashi et al., 1994; Steiner et al., 1994; Xu et al., 1999). Loss or destruction of leptin-sensitive and NPY-sensitive neurons in the ARC nucleus results in disturbed daily rhythms in food intake (Wiater et al., 2011; Li et al., 2012). Like the arcuate nucleus, DMH neurons are also sensitive to feeding-related hormones such as leptin (Elmquist et al., 1997). The DMH has been suggested to play a critical role in the regulation of a wide 18 range of behavioural rhythms. Excitotoxic lesions of the DMH disrupt circadian rhythms of wakefulness, feeding, locomotor activity and plasma corticosterone. Additionally, the DMH connects with several hypothalamic nuclei including the lateral hypothalamic area and PVN. The afferent neurons of DMH innervating the ventrolateral preoptic nucleus are largely GABAergic, while those innervating the lateral hypothalamic area are mainly glutamatergic (Chou et al., 2003; Saper et al., 2005). The DMH also appears to be involved in food entrainment (Mistlberger, 2006). During restricted feeding the DMH exhibits a robust oscillation of mPer expression and this oscillation persist for a few days after the food deprivation (Mieda et al., 2006). Thus the DMH could be an important area that mediates the effects of SCN output on several behavioural and physiological rhythms and may play a role in daily rhythm of feeding/fasting. Anatomy and cell types of the SCN. Anatomically and functionally, the SCN contains at least two major subdivisions: a ventral "core" region and a dorsal "shell" region based on afferent and efferent projections and neuropeptide expression (Ibata et al., 1989; Antle and Silver, 2005; Gamble et al., 2007; Kiss et al., 2008). On the one hand, the ventral core of the SCN expresses Gastrinreleasing peptide (GRP) and Vasoactive intestinal polypeptide (VIP) (Abrahamson and Moore, 2001; Antle and Silver, 2005). GRP levels in the rat SCN reach peak levels during the resting phase and gradually decrease during the dark phase, while VIP remains low during the light phase and gradually reaches peak levels during the dark period (Shinohara et al., 1993). On the other hand, the dorsal shell contains mainly neurons that express Arginine vasopressin (AVP) along with calretinin (CAR) (Moore et al., 2002) (Figure 7). Figure 7: Distribution of principal neuropeptides in the SCN SCN neurons expressing the neuropeptides VIP, GRP, AVP and the neurotransmitter GABA. Many of the SCN neurons within the dorsal shell express AVP and GABA. The SCN neurons in the ventral core contain VIP and GRP. AVP: arginine vasopressin; GABA: Gamma amino-butyric acid; VIP: vasoactive intestinal polypeptide; GRP: gastrin-releasing peptide. 19 mRNA expression of Avp is highest during daytime under light-dark conditions, in both nocturnal and diurnal rodents, and this rhythm persists in constant darkness (Dardente et al., 2004). Moreover, also the rhythmic release of AVP is higher during the daytime (Kalsbeek et al., 1998). Additionally, SCN neurons also contain many other neuropeptides (Cheng et al., 2002), such as for instance prokineticin 2 (PK2), a multifunctional secretory protein (Zhou and Cheng, 2005; Negri et al., 2007), which plays a role in transmission of the circadian signals from the SCN (Zhou and Cheng, 2005; Zhang et al., 2009). Photic entrainment of SCN clock In order to maintain its daily rhythmicity synchronized with the outside world, the SCN clock requires a synchronizing signal with a 24-h period, for instance the environmental light-dark (LD) cycle. In the absence of such a synchronizing input, the SCN clock starts to free-run with a period different from, although still close to 24 h. Photic entrainment of the SCN clock occurs via retinal ganglion cells which project to the SCN through the retinohypothalamic tract (RHT) (Panda et al., 2002; Foster et al., 2007; Panda, 2007) and is dependent on the timing of the light exposure. In response to photic stimulation, RHT terminals release glutamate and pituitary adenylate cyclase activating peptide (PACAP) in the SCN, which stimulate their receptors on SCN neurons and cause the transcription of the clock genes Per1 and Per2 (Albrecht et al., 1997; Shearman et al., 1997; Shigeyoshi et al., 1997; Reppert and Weaver, 2002). Figure 8: Photic input signal transduction pathways in the SCN neuron. Solid and dashed lines indicate the direct and indirect phase-shifting pathways, respectively. BIT, brain immunoglobulin-like molecules with tyrosine-based activation motifs; CaMKII, calcium/calmodulin kinase II; CRE, cAMP response element; CREB, CRE-binding protein; PACAP, pituitary adenylate cyclaseactivating peptide; PKGII, cGMP-dependent protein kinase II. Adapted from (Hirota and Fukada, 2004). 20 In most of the nocturnal and diurnal animals, exposure to light pulses during the early night causes a phase delay, while a light pulse in the late night results in a phase advance. By contrast, exposure to a light pulse around midday does not have any resetting effect on the master clock. Light exposure activates a series of pathways with induction of early and immediate responses, such as transcription of c-fos and phosphorylation of ERK (Morris et al., 1998; Obrietan et al., 1998).Light-induced phase delays are associated with upregulated expression of Per1 and Per2 in the SCN core and later with Per2 expression in the SCN shell (Hamada et al., 2001; Yan and Okamura, 2002; Hamada et al., 2004). By contrast, light-induced phase advances are associated only with increased expression of Per1 in the core SCN, but not Per2 (Antle and Silver, 2005) (Figure 8). 3.2 Peripheral clocks Each cell and organ have their own clock. These clocks are entrained by the master clock in the SCN and remain synchronized under regular laboratory conditions (i.e., stable LD cycle, food and water ad libitum, constant ambient temperature). The master clock sends its output signals to almost each peripheral tissue of the body via neuroendocrine and autonomic nervous pathways. The entrainment of peripheral clocks by the master clock, the light-dark cycle, feeding-fasting cycle, and diet composition had been studied extensively (Figure 9). Figure 9: Organization of circadian timing system. The master clock, located in the suprachiasmatic nuclei (SCN) of the hypothalamus, adjusts the timing of many secondary clocks/oscillations in the brain and peripheral organs, in part via nervous pathways (dotted red lines). Light perceived by the retina is the potent synchronizer of the SCN clock (dashed yellow arrow), while meal time can synchronize peripheral clocks (blue arrows). Modified from (Delezie and Challet, 2011). Liver clock The liver is an important organ in the control of energy homeostasis. In particular, the liver is an important organ for glucose uptake, storage, and production. Hepatic glycogen 21 anabolism and catabolism show daily rhythms (Kida et al., 1980; Roesler et al., 1985; Roesler and Khandelwal, 1985). Many genes encoding enzymes involved in hepatic glucose metabolism display a circadian expression pattern (Lamia et al., 2008). Some of these metabolic genes lose their rhythmicity in mice with a liver-specific knock-out of the Bmal1 gene, while others remain rhythmic, probably through systemic cues. Glucose transporter (Glut2) in the liver is critical for exporting glucose from the liver. Its maximal expression is found during fasting, while during the feeding phase its expression is lower, then limiting glucose exported from the liver (Schmutz et al., 2012). Under an LD cycle temporal restricted feeding can shift the phase of clock gene expression in the liver, for up to 12h. These changes in the liver clock are much faster than any other peripheral clocks, such as kidney, pancreas and heart (Damiola et al., 2000; Stokkan et al., 2001). The changes in phase and amplitude of rhythmic genes in the liver involve feeding/fasting cues (Atger et al., 2017). Entrainment of the liver clock induced by a restricted feeding cycle is independent of the SCN clock and the light-dark cycle (Hara et al., 2001; Stokkan et al., 2001; Bae and Androulakis, 2017), but does involve temperature cues as shown with experiments using dampened temperature cycles (Damiola et al., 2000; Brown et al., 2002). Feeding/fasting cycles trigger the secretion of various hormones, many metabolites and affect the intracellular redox state by changing the NADH/NAD+ ratio. The hepatic clock is also altered by the amount of food and the interval between feeding time-points, but it remains unaffected by the frequency of feeding as long as the interval remains fixed (Kuroda et al., 2012). Skeletal muscle clock Nearly 45% of the body mass is composed of skeletal muscle (Goodpaster et al., 2000; Hoppeler and Fluck, 2002), making skeletal muscle one of the largest tissues of the body. Skeletal muscle is strongly implicated in the maintenance of glucose homeostasis as it takes up 80% of postprandial glucose (DeFronzo et al., 1981b; Ferrannini et al., 1988). In skeletal muscle, over 2300 genes involved in myogenesis, transcription and metabolism, are expressed rhythmically (McCarthy et al., 2007; Pizarro et al., 2013; Harfmann et al., 2015). Muscle physiology is entrained either directly by the molecular clock (Yamazaki et al., 2000) or indirectly by other rhythmic factors such as feeding time, neuro-humoral signals, and locomotor activity that are controlled by the SCN clock. The communication of the SCN molecular clock to the skeletal muscle is mediated through neuro-humoral and 22 temperature signals (Balsalobre et al., 2000; Brown et al., 2002; Abraham et al., 2010; Saini et al., 2012). The muscle clock gets desynchronized from the SCN clock when external stimuli, such as feeding and exercise, are out of phase with the regular LD cycle (Mayeuf-Louchart et al., 2015). Feeding/fasting cycles can synchronize the muscle clock, as shown by the restricted feeding schedule (Damiola et al., 2000; Opperhuizen et al., 2016). In mice, fasting for 24h does not disturb the muscle clock (Dudek and Meng, 2014). In addition to the feeding/fasting cycle, also activity cues, such as scheduled physical exercise, may act as a Zeitgeber for the muscle clock (Yamazaki et al., 2000; Yamanaka et al., 2008; Wolff and Esser, 2012). Disruption of circadian rhythms in skeletal muscle results in impaired glucose tolerance and insulin sensitivity (Yoo et al., 2004; Harfmann et al., 2015). Restricted feeding and scheduled activity in PER2:LUC mice results in a shift in gene expression of the muscle molecular clock (Wolff and Esser, 2012). Restricted feeding limiting food access to the light/resting phase desynchronizes the skeletal muscle clock from the liver clock of rats, as clock genes in muscle lose their rhythmicity when rats are fed with a chow diet during the resting phase (Reznick et al., 2013; Opperhuizen et al., 2016), but remain rhythmic with an unchanged phase when fed a high-fat diet during the resting phase (Reznick et al., 2013). Brown adipose tissue clock Like the liver and skeletal muscle, brown adipose tissue (BAT) is another metabolically active organ, but in this case specifically involved in non-shivering thermogenesis. BAT is highly enriched in capillaries that supply oxygen and lipid as a substrate to generate heat through its endogenous thermogenic process. BAT contains numerous small-sized lipid droplets, as well as iron-rich mitochondria expressing uncoupling protein-1 (UCP1, thermogenin). Mice deficient in UCP1 (Enerback et al., 1997) and BAT (Lowell et al., 1993) helped to demonstrate the functionality of UCP1 and BAT for the generation of heat through non-shivering thermogenesis (Matthias et al., 2000; Golozoubova et al., 2001). BAT is also a major organ for glucose uptake (Cawthorne, 1989), through glucose transporters GLUT1 and GLUT4, which are activated by cold exposure and noradrenergic signalling (Nikami et al., 1992; Dallner et al., 2006; Bartelt et al., 2011). Due to its plasma lipids and plasma glucose lowering and insulin sensitivity increasing effect, increased BAT activity helps in reducing metabolic disorders related to obesity and diabetes 23 (Nedergaard et al., 2011). Various genetic models of clock gene mutants provided evidence for the involvement of the BAT clock in thermogenesis (Chappuis et al., 2013; Gerhart-Hines et al., 2013; Nam et al., 2016). The activation of BAT by various highcalorie diets, such as high fat or high sugar diets, is likely through increased UCP1 levels, thereby providing a potential mechanism to limit weight/fat gain (Rothwell and Stock, 1979; Bukowiecki et al., 1983; Mercer and Trayhurn, 1987; Moriya, 1994; LeBlanc and Labrie, 1997). 4. Circadian control of plasma metabolites and hormones Daily variations in plasma hormones and metabolites are under the control of the circadian timing system, but also affected by the feeding-fasting and rest-activity cycles. Dysregulation of these plasma metabolites may result in various metabolic disorders such obesity, dyslipidemia, type 2 diabetes, and hypertension. In this thesis we concentrated especially on the following metabolites and hormones: glucose, free fatty acids, corticosterone, insulin, leptin, and melatonin (Figure 10). Glucose metabolism Glucose, the major energy reservoir of the cell, is required for normal functioning. Body uptake of glucose occurs mostly from carbohydrate-rich diets via the systemic circulation. The liver stores glucose in the form of glycogen. Plasma glucose concentrations show a daily rhythm, as reported both in animals and humans. The daily rhythm of basal glucose concentrations is SCN-dependent and gets abolished after bilateral lesions of SCN, while the rhythm still persists when rats are fasted or fed a 6-meals-a-day feeding schedule (Nagai et al., 1994; Kalsbeek et al., 1998; La Fleur et al., 1999). The plasma glucose concentration depends on influx of glucose from gut and liver and efflux of glucose mostly to brain, muscle and adipose tissues (Kalsbeek et al., 2006). Glucagon produced by pancreatic α-cells acts on the liver for stimulating the synthesis of hepatic glucose through the process of glycogenolysis and gluconeogenesis (Pilkis and Granner, 1992; Kurukulasuriya et al., 2003). In rats, the daily rhythm of plasma glucose concentrations peaks prior to the onset of activity (La Fleur et al., 1999; Challet et al., 2004; Cailotto et al., 2005b). The stimulation of sympathetic fibers that innervate the liver increases glucose production through glycogen phosphorylase activation (Shimazu and Fukuda, 1965), while activation of the parasympathetic pathway to the liver decreases hepatic glucose production through an inhibitory action on glycogen synthase (Shimazu, 1967). Hepatic 24 denervation studies in rats provided the evidence for a critical role of the SCN, mediated through the autonomic nervous system, in the daily rhythm of plasma glucose concentrations (Kalsbeek et al., 2004; Cailotto et al., 2005b). Apart from the SCN, this pathway involves other hypothalamic nuclei such as the PVN. Injections of a GABA-A antagonist or an NMDA agonist in the vicinity of the PVN resulted in activation of PVN neurons and caused hyperglycemia independent of insulin and corticosterone release (Kalsbeek et al., 2004), but possibly involving increased release of glucagon. Figure10: Schematic representation of the circadian timing system in a nocturnal rodent. The suprachiasmatic nuclei (SCN), site of the master clock, are mostly reset by light cues (in yellow) perceived by the retina. Secondary clocks in the brain and peripheral tissue (only a few are shown) are phase controlled in part by temporal cues from the master clock, via the autonomic nervous system (blue arrows). Peripheral glands release rhythmically hormones. Brain-controlled feeding/fasting, sleep/wake cycles and changes in body temperature (not shown) are also modulators of peripheral rhythmicity. WAT, white adipose tissue. Modified from (Challet, 2015). The circadian clock and clock components also play an important role in the regulation of glucose metabolism at other levels. Various clock gene mutants presented a number of metabolic disorders, including hyperglycemia, dyslipidemia, hepatic steatosis and reduced gluconeogenesis. More specifically, mutation of the Clock gene has a major impact on glucose metabolism, such as reduced gluconeogenesis and increased insulin sensitivity, hyperglycemia, decreased glucose tolerance and dampened oscillations of hepatic glycogen and glycogen synthase 2 (Rudic et al., 2004; Turek et al., 2005; Kennaway et al., 2007; Doi et al., 2010; Marcheva et al., 2010). Similarly, knock-out of Bmal1 leads to altered glucose metabolism. Global and liver-specific Bmal1 knockout mice develop glucose intolerance (Lamia et al., 2008). A pancreas-specific knockout of Bmal1 also induces impaired glucose tolerance, as well as hypoinsulinemia (Marcheva et al., 2010). 25 Also mutations in other clock genes such as Per2, Cry1/Cry2, and Rev-erbα impact on glucose metabolism with differential effects on glycemia, glycogen storage, and glucose tolerance (Schmutz et al., 2010; Delezie et al., 2012; Zhao et al., 2012; Zani et al., 2013). Lipid metabolism The liver also plays a pivotal role in lipid metabolism. It is the major site for converting carbohydrates into fatty acids and triglycerides which are than exported and stored in adipose tissue. Free fatty acids are derived from the circulation, as well as from de novo synthesis from acetyl Co-A or malonyl-CoA. The free fatty acids are converted into triglycerides (TGs) in hepatocytes which are than further used for the production of VLDL particles for export (Bradbury, 2006). Lipids are the major source of stored energy in the white adipose tissues (WAT) of mammals. When energy requirements of the body cannot be full-filled by circulating energy metabolites such as carbohydrates, a breakdown of lipids occurs through the process of lipolysis from WAT. Lipolysis involves hydrolysis of TGs into glycerol and free fatty acids via activation of the hormone sensitive lipase. Plasma free fatty acids show a daily rhythm which is dependent on the SCN (Yamamoto et al., 1984, 1987; Dallman et al., 1999). Plasma apolipoproteins help in the transportation of other lipids such as TG and cholesterol (Pan and Hussain, 2009; Challet, 2013). Intestinal production of lipoproteins may cause a rise in plasma TGs and cholesterol in nocturnal rodents during their active phase (Pan and Hussain, 2007). Diurnal variations of plasma lipids in mice are under circadian control, and are altered under constant lightening and restricted feeding conditions (Pan and Hussain, 2007). Most of the genes in the intestine such apolipoprotein B, apolipoprotein AIV, intestinal triglycerides transport protein and intestinal fatty acid binding protein show diurnal variations during lipid uptake and metabolism (Pan and Hussain, 2007, 2009; Pan et al., 2010). Mutations or circadian disruptions of the molecular clock machinery have a pronounced influence on lipid rhythms. Clock mutant mice lose the day-night rhythmicity in the absorption of macronutrients due to loss of rhythm in the intestinal absorption (Pan and Hussain, 2009). Similarly, clock mutant mice also express altered circadian rhythmicity of the genes involved in TG synthesis and lipolysis ((Kudo et al., 2007; Tsai et al., 2010; Shostak et al., 2013) and are characterized by hypertriglyceridemia (Turek et al., 2005). Pparα is well known for its involvement in the regulation of lipid metabolism. Bmal1 knock-out mice display down26 regulation of Pparα in liver suggesting a close connection between Pparα and Bmal1 (Canaple et al., 2006). Knock-down of Bmal 1 in 3T3-L1 adipocytes results in decreased adipocyte differentiation and lipogenesis gene expression, while Bmal1 knock out mice have high levels of circulating fatty acids resulting in an unusual accumulation of fat in liver and muscle (Shimba et al., 2011). Embryonic fibroblast cells of the Bmal 1 knockout mice failed to differentiate into adipocytes (Shimba et al., 2005). Daily oscillations of plasma TGs are disrupted in the Bmal1 knock-out mice (Rudic et al., 2004; Bunger et al., 2005). Per2 knock-out mice have altered lipid metabolism (Grimaldi et al., 2010) et al. 2010). Liver lipidomic analysis of Per1/2 null mice fed under ad libitum or night time restricted feeding still shows oscillation in TGs in an anti-phasic manner suggesting oscillation of TGs in the absence of a functional clock. Night time restricted feeding reduces hepatic triglycerides levels in wild-type mice (Adamovich et al., 2014). Like the other clock genes, also Rev-erbα plays an important role in lipid metabolism, more precisely in adipogenesis (Fontaine et al., 2003; Duez and Staels, 2008b; Delezie et al., 2012). In addition, it also regulates TGs and TG rich lipoprotein metabolism (Raspe et al., 2002). It has been shown in rats that Rev-erbα represses various apolipoproteins A-I which are the major protein constituents of high-density lipoproteins (HDL) (Vu-Dac et al., 1998). Rev-erbα-deficient mice display high levels of hepatic apoC-III expression, plasma TGs and TG-rich very low density lipoproteins (VLDL) (Raspe et al., 2001; Raspe et al., 2002). Under regular chow-feeding conditions these mice display increased adiposity, and a period of 24 h fasting increases more fatty acid mobilization in the knockout mice as compared to wild-type littermates. When fed with a high-fat diet, the Rev-erbα knockout mice are more prone to metabolic disturbances and lipogenic factors are more activated compared to wild-type animals (Delezie et al., 2012). Corticosterone rhythm Plasma corticosterone levels peak prior to the onset of activity, which is just before lights off in nocturnal animals (Cheifetz, 1971; Ixart et al., 1977; Carnes et al., 1989). The SCN clock in the hypothalamus regulates the adrenal production and secretion of glucocorticoids. The circadian regulation of glucocorticoid release is mediated via the hypothalamic-pituitary-adrenal axis and the autonomic nervous system. AVP, one of the principal neuropeptides of the SCN projections towards the PVN/DMH area, presents a diurnal release in the cerebrospinal fluid and in the PVN/DMH and SCN region (Reppert 27 et al., 1981; Kalsbeek et al., 1995; Buijs et al., 1999). Micro-infusion of AVP in PVN and DMH inhibits corticosterone release (Kalsbeek et al., 1992), while infusion of an AVP antagonist in PVN and DMH at the time of highest AVP release has a stimulatory effect on corticosterone release (Kalsbeek et al., 1992; Kalsbeek et al., 1996a). The circadian release of corticosterone in both nocturnal (rats) and diurnal (Arvicanthis) animals are in phase with the onset of daily activity. The administration of AVP in the PVN of diurnal animals stimulates corticosterone release, that is, it has opposite effects to those in nocturnal animals (Kalsbeek et al., 2008). The feeding-fasting cycle also strongly influences the activity of the hypothalamicpituitary-adrenal axis. In mice and rats, daytime restricted feeding provokes a bimodal pattern of corticosterone secretion, the first peak corresponding to feeding time while the second peak occurs at dusk at a similar phase to ad libitum feeding conditions (Le Minh et al., 2001). However, the first, feeding driven peak is independent of the SCN (Krieger et al., 1977). The circadian rhythm of circulating glucocorticoids is thought to synchronize a number of peripheral clocks (Dickmeis, 2009). Melatonin rhythm In mammals, the pineal gland secretes melatonin, a lipophilic hormone, only in the night. The rhythmic release of melatonin is under control of the SCN, but is also highly influenced by the presence or absence of light (Pevet and Challet, 2011). In the absence of light, melatonin is synthesized during the subjective night phase, while in the presence of light, either during the regular day or at night, melatonin synthesis is inhibited. The secretion of melatonin from the pineal gland always takes place at night in both nocturnal and diurnal animals. Therefore, it has been considered as a phase marker of the SCN clock (Cajochen et al., 2003; Arendt and Skene, 2005). Kalsbeek et al. demonstrated that the daily rhythm of melatonin synthesis is caused by a rhythmic alternation of glutamatergic and GABAergic outputs from the SCN (Perreau-Lenz et al., 2004). These glutamatergic and GABAergic signals control the activity of pre-autonomic PVN neurons that are in control of the sympathetic inputs to the pineal gland. During the light period GABAergic neurons in the SCN provide inhibitory signals onto these pre-autonomic neurons in the PVN, whereas in the dark period glutamatergic inputs from the SCN stimulate these preautonomic neurons to start the secretion of pineal melatonin (Kalsbeek and Fliers, 2013). 28 Plasma melatonin also provides feedback signals to the SCN clock (Pevet and Challet, 2011). In rodents, melatonin has phase resetting properties on SCN oscillations (Armstrong and Redman, 1985). Restricted feeding combined with calorie restriction in rats causes a small but significant phase advance of the daily rhythm of pineal melatonin (Challet et al., 1997a). In SCN-lesioned rats, restricted feeding restores the rhythmic transcription of the rate limiting enzyme arylalkylamine-N-acetyltransferase, possibly via sympathetic fibers (Feillet et al., 2008a). Melatonin is known to influence other hormone rhythms such as leptin, corticosterone and insulin (Peschke and Peschke, 1998; Gunduz, 2002; Alonso-Vale et al., 2008; Chakir et al., 2015). Leptin rhythm Leptin is a hormone which is secreted from adipocytes in the white adipose tissue and plays a major role in the regulation of food intake and energy homeostasis by exerting its effect on hypothalamic neurons. Leptin acts on the NPY and POMC neurons in the arcuate nucleus by binding to the LEPR-B. More precisely, leptin inhibits the orexigenic NPY/AgRP neurons, while it activates the anorexigenic POMC- and CART-expressing neurons as a result of which food intake is decreased (Schwartz et al., 2000; Kalra and Kalra, 2003; Sobrino Crespo et al., 2014). Circulating leptin concentrations are related to fat mass and adiposity in humans and rodents (Ahima et al., 1996; Considine and Caro, 1996; Havel et al., 1996; Kolaczynski et al., 1996; Elimam and Marcus, 2002). During food restriction, leptin levels decrease, leading to increased appetite and reduced energy expenditure (Velkoska et al., 2003). Leptin signals probably also modulate peripheral clocks as indicated by the alteration of clock gene expression in liver and adipose tissue of leptin-deficient (ob/ob) and leptin-resistant (KK-Ay) mice and Zucker rats (Motosugi et al., 2011). Plasma leptin levels in mice and rats show a diurnal rhythm with a nocturnal peak. This rhythm is sex dependent (i.e., with much higher amplitude in females as compared to male mice) and is abolished under 24-fasting conditions (Ahren, 2000). Complete destruction of the SCN in rats results in a loss of the diurnal rhythmicity, while a 6-meals-a-day feeding schedule has no major effect on its rhythmicity. Furthermore, the rhythm of plasma leptin is controlled by the SCN via the sympathetic fibers innervating WAT (Kalsbeek et al., 2001). Rhythmic secretion of leptin is also modulated by the circadian clock within the adipocytes (Otway et al., 2009). Plasma leptin may give feedback to the SCN as SCN cells express leptin receptors and an in vitro study in rats showed leptin-induced phase advances of the SCN clock (Prosser and Bergeron, 2003). 29 Hence leptin may play an important role in connecting circadian clocks and energy metabolism. Insulin rhythm Alike to the hormones cited above, insulin also shows daily variations in plasma concentrations, which are under control of the SCN (la Fleur et al., 2001; Rudic et al., 2004; Shi et al., 2013). Of note, insulin sensitivity also displays daily rhythmicity (la Fleur et al., 2001). Insulin, which is secreted by pancreatic β-cells in response to a meal, regulates blood glucose by favouring the entry of glucose into metabolically active tissues, thus reducing glycemia (Patton and Mistlberger, 2013). The secretion of insulin after a meal results in acute changes in Per2 and Rev-erbα expression in the liver (Tahara et al., 2011; Yamajuku et al., 2012). Mice with a global deletion of the clock genes Cry1 and Cry2 present hyperinsulinemia (Barclay et al., 2013), whereas specific ablation of the clock genes Clock and Bmal1 in the pancreas results in hypoinsulinemia (Marcheva et al., 2010; Sadacca et al., 2011). The 6-meals-a-day feeding schedule nicely demonstrates the stimulatory effect of the SCN on insulin release during night time meals (Kalsbeek et al., 1998). SCN-lesioned mice lose their daily insulin rhythm and display hyperinsulinemia (Coomans et al., 2013). In diabetic rats, the phase of the circadian clock in the heart is shifted, suggesting a role for hyperglycaemia and/or altered insulin signalling on the cardiac clock (Young et al., 2002). 5. Interactions between the circadian clock system, feeding and metabolism. 5.1 Restricted feeding and calorie restriction Limiting food access in rodents to either the active or resting phase, with no caloric restriction, is known as restricted feeding. Rodents under restricted feeding conditions adjust and adapt to their new feeding-fasting schedule within a few days (Honma et al., 1983; Froy et al., 2006). Feeding restricted every day for a single, short period of time entrains various food-entrainable oscillators (FEO) and synchronizes the physiological and behavioural rhythms to the feeding opportunity, for instance, a period of increased locomotor activity prior to every day access to food. This robust increase in locomotor activity is known as food-anticipatory activity. Restricted feeding also leads to anticipatory increases in body temperature, several metabolic cues, heart rate and 30 secretion of glucocorticoids (Saito et al., 1976; Comperatore and Stephan, 1987; Mistlberger, 1994; Hara et al., 2001; Boulamery-Velly et al., 2005; Saper et al., 2005; Hirao et al., 2006). When rats are entrained to a restricted feeding opportunity during the middle of the resting phase, c-FOS protein expression in the DMH is shifted to the daytime, indicating that the timing of the activation of the DMH is linked to meal time (Angeles-Castellanos et al., 2004). The food-anticipatory activity persists in SCN-lesioned animals which indicates that the FEOs are located outside the master clock, likely in neural structures from the hypothalamus to brainstem that regulate feeding behaviour (Mistlberger and Antle, 2011). Restricting food access to the resting phase also inverses or shifts clock gene expression in peripheral tissues such as liver, lungs, and kidneys, but not in the SCN clock, thereby uncoupling central and peripheral clocks (Figure 11) (Damiola et al., 2000; Hara et al., 2001; Stokkan et al., 2001; Cassone and Stephan, 2002; Schibler et al., 2003; Hirota and Fukada, 2004). The restricted feeding paradigm also phase shifts the peak expression of the clock genes in several brain areas outside of the SCN, such as cerebral cortex and striatum, compared to animals fed ad libitum (Wakamatsu et al., 2001; Feillet et al., 2008a). A high fat diet in combination with the time restricted feeding prevents mice from developing metabolic disorder such as obesity, hyperinsulinemia, and hepatic steatosis if the high fat diet is provided during the usual active period (Mendoza et al., 2008a; Hatori et al., 2012). Figure 11: Daytime feeding changes the phase of clock gene expression in the liver but not in the suprachiasmatic nucleus (SCN). (A) Circadian accumulation of Per1 and Per2 mRNA levels in liver. (B) Circadian accumulation of Per1 and Per2 in SCN. Adapted from (Damiola et al., 2000). 31 Figure 12: Immunoreactive expression of AVP and PER2 in the SCN of caloric restricted (T-CR) and control (AL) mice. (A) AVP-ir nuclei and (B) PER2-ir nuclei in the SCN from mice under a 12-h LD cycle and AL (black symbols) or T-CR (White symbols) at different Zeitgeber times (ZT-0, lights on; ZT-12, lights off. (C) Schematic presentation showing that daily hypocaloric feeding affects the SCN clock. Black and White top bars indicate the LD cycle. Vertical arrows indicate the meal time. Adapted and modified from (Mendoza et al., 2007a). When rats that are housed under a regular LD cycle are exposed to restricted feeding coupled with caloric restriction (hypocaloric diet), they display phase advances in their locomotor activity rhythm, body temperature cycle, and the daily rhythm of plasma melatonin (Challet et al., 1997a; Wakamatsu et al., 2001; Feillet et al., 2008a). Caloric restriction is elicited by reducing the total caloric intake to 60-70% of ad libitum values without malnutrition. Animals under caloric restriction fed either one or two daily meals or exposed to intermittent daily fasting displayed an increased lifespan (Masoro, 1995; Masoro et al., 1995; Froy and Miskin, 2010), and delayed onset of age-related diseases such as cancer, diabetes, kidney disease, and cataract (Weindruch et al., 1997; Roth et al., 2002; Koubova and Guarente, 2003; Roth et al., 2004; Masoro, 2005). Caloric restriction can entrain the SCN clock and modulate photic entrainment (Challet et al., 1997b; Challet et al., 2003; Mendoza et al., 2005; Resuehr and Olcese, 2005). Caloric restricted mice express a rise in body temperature in anticipation of the scheduled food access (Duffy et al., 1989). A hypocaloric meal provided during daytime also affects the temporal organization of the SCN clock in mice, with a shifted SCN clock and clock outputs (Figure 12) (Mendoza et al., 2005; Mendoza et al., 2007a). Rats on a six-meals-a-day feeding schedule coupled with hypocaloric meals also showed a phase advance of their locomotor activity and body temperature rhythms (Mendoza J et al. 2008). In conclusion, 32 caloric restriction affects the peripheral clock in liver similar to restricted feeding (Damiola et al., 2000; Hara et al., 2001; Stokkan et al., 2001), but contrary to timerestricted feeding it affects the central SCN clock as well (Mendoza et al., 2007a) via additional, as yet unknown mechanisms. 5.2 Diet and its impact on circadian clocks. Eating behavior is not only about “how much we eat”, but also about “what and when we eat”. The daily life style of humans nowadays is highly influenced by late evening activities, shift work, and high-caloric feeding. A high-caloric diet has a major impact on body physiology and metabolism, leading to obesity, diabetes, and other features of the metabolic syndrome. A high energy diet also leads to circadian disruption. Mice fed on a high-fat diet present disruption of behavioral rhythms with a dampened rhythm of locomotor activity and increased feeding duration together with alterations of circadian clock and metabolic gene expression in metabolically active tissues such as hypothalamus, liver, muscle and adipose tissue (Kohsaka et al., 2007; Barnea et al., 2009, 2010). High-fat feeding also affects the plasma levels of hormones involved in fuel utilization such leptin, insulin, corticosterone, prolactin, luteinizing hormone, thyroid stimulating hormone, testosterone and also pineal melatonin in rats, mice and humans (Havel et al., 1999; Cha et al., 2000; Cano et al., 2008; Honma et al., 2016). Mice on a high-fat diet display increased body mass index, and increased plasma metabolite concentrations such as glucose, and free fatty acids. High-fat feeding in mice also impairs circadian re-entrainment after a jetlag (Mendoza et al., 2008a). Furthermore, decreased light-induced phase shifts of mice fed with a high-fat diet correlate with a reduction of light-induced c-FOS and P-ERK in the SCN (Mendoza et al., 2008a). Mice fed with a high-fat, high-sugar diet (fcHFHS) in combination with short-term daytime feeding display desynchronized peripheral clocks, leading to the metabolic syndrome through leptin resistance, physical inactivity and fatty liver and adiposity (Yasumoto et al., 2016). Rats on fcHFHS for five weeks gain body weight over the control group, while those rats fed with either high-fat or high-sugar do not show an increase of body weight. The rise in body weight in the fcHFHS group is due to increased abdominal fat (la Fleur et al., 2010). Moreover, feeding behavior is modified, as characterized by increased meal numbers due to sugar intake without reducing meal size (la Fleur et al., 2007; la Fleur et al., 2014). Of note, rats fed on fcHFHS diet display no change in rhythms of body temperature or locomotor activity (la Fleur et al., 2007). 33 5.3 Clock genes in relation to metabolic genes Metabolic pathways are regulated by numerous metabolic genes involved in lipid and glucose metabolism and are tightly connected with the molecular mechanism of the circadian clock. The transcription factors peroxisome proliferator-activated receptors (PPARs) play an important role in linking metabolism to circadian clocks. PPAR expression is found to be rhythmic in mouse liver, skeletal muscle, white and brown adipose tissues (Lemberger et al., 1996b; Yang et al., 2006), which gives a clue of the tight interconnectivity between these two systems (Figure 11). PPARs belong to a superfamily of ligand-activated nuclear receptors. After binding to ligands such as free fatty acids and eicosanoids, PPARs heterodimerize with retinoid X receptors (RXRs). Then these complexes bind to PPAR responsive elements (PPRE) and activate the transcription of their target genes. There are three PPAR isoforms: PPARα, PPARβ/δ and PPARγ (Berger and Moller, 2002), each of them differs from each other by tissue-specific distribution, specificity toward particular ligands and functionality (Willson et al., 2000). PPARα, a metabolic sensor and lipid metabolizing gene in the liver, makes a direct link between the circadian clock and metabolism by binding a PPRE in the promoter of Bmal1 and regulating its expression positively (Lemberger et al., 1996a; Oishi et al., 2005; Canaple et al., 2006). PPARγ, the paralog of PPARα, is expressed highly in white and brown adipose tissues in which it regulates adipogenesis and lipid biosynthesis (Kliewer et al., 1997; Sheu et al., 2005; Medina-Gomez et al., 2007). Genetic ablation of PPARγ in mice is associated with behavioral changes by abolishing or dampening circadian rhythmicity, which affects body metabolism (Yang et al., 2012). It plays an important role in the regulation of heart rate and blood pressure by forming a feedback loop with BMAL1. Conditional knockout of PPARγ in the vascular system dampens the heart rate and blood pressure (Wang et al., 2008). PPARγ and its partner PPARα positively regulate expression of the clock gene Rev-erbα in the liver and PPARγ also promotes adipocyte differentiation (Gervois et al., 1999; Fontaine et al., 2003). The PPARγ coactivator 1α (PGC1α) is expressed rhythmically in mouse liver and muscle, thereby it is involved in connecting the molecular clock and energy metabolism. Its main function is the regulation of oxidative phosphorylation by mitochondrial biogenesis (Bellet and Sassone-Corsi, 2010). Genetic deletion of PGC-1α in mice leads to an abnormal locomotor activity pattern, disrupted body temperature rhythms, and disturbed energy metabolism (Lin et al., 2005; Feige and 34 Auwerx, 2007; Liu et al., 2007). PPARβ/δ is highly ubiquitous and expressed in most tissues of the body (Braissant et al., 1996). It has a role in the control of energy homeostasis (Coll et al., 2009; Asher and Schibler, 2011). A recent study demonstrated PPARβ/δ expression in the hamster SCN, and showed that a PPARβ/δ agonist amplifies phase delays of the locomotor activity rhythm in response to a light pulse (Challet et al., 2013). This possible direct link to the circadian clock needs to be investigated further. Sirtuin1 (SIRT1), a NAD+ dependent deacetylase, acts as a cellular nutrient sensor (Sahar and Corsi 2012). An increased NAD+/NADH ratio activates SIRT1 which links it to cellular energy metabolism (Bordone and Guarente, 2005). Previous reports showed that during caloric restriction SIRT1 activates PGC-1α via its deacetylation (Rodgers et al., 2005). SIRT1 is an important modulator of the circadian machinery (Asher et al., 2008; Nakahata et al., 2008). SIRT1 regulates circadian rhythms by deacetylation of histones at the promoter of clock genes, and non-histone proteins BMAL1 and PER2 display a circadian pattern of expression (Nakahata et al., 2009; Ramsey et al., 2009). This 24-h expression of NAD+ may be dependent on the rate limiting enzyme nicotinamide phosphoribosyl transferase (NAMPT), suggesting a close connection of the circadian clock and metabolic processes within the peripheral clock. Figure 13: The mammalian circadian clock and its link to energy metabolism . Expression of Bmal1 and Rev‐erbα genes are controlled by PPARα and binding of RORs to RORE sequences. RORs need a co‐activator, PGC‐1α, which is phosphorylated by activated AMPK. In parallel, AMPK activation leads to an increase in NAD+ levels, which, in turn activate SIRT1. SIRT1 activation leads to PGC‐1α deacetylation and activation. Acetyl adenosine diphosphate ribose (Ac‐ADP‐r) and nicotinamide (NAM) are released after deacetylation by SIRT1. Adapted from (Froy and Miskin, 2010). Energy metabolism also impacts the cellular redox status (Figure 13). A study by Rutter et al. showed that the cellular redox has an impact on the circadian clock such that the level 35 of pyridine nucleotides can modulate DNA binding of CLOCK-BMAL1 or Neuronal PAS Domain Protein 2 (NPAS2)-BMAL1 heterodimers (Rutter et al., 2001). Daily rhythms in the cellular redox state are observed in the liver by daily changes in the rate-limiting enzyme in the NAD+ salvage pathways and circadian-dependent regulation of the nicotinamide phosphoribosyl transferase (NAMPT) (Nakahata et al., 2009; Ramsey et al., 2009). The NAD+ levels in cells Poly (ADP-ribose) polymerase 1 (PARP-1) binds to the CLOCK-BMAL1 heterodimer and poly-ADP-ribosylates CLOCK during the early light phase. Knock-out of PARP-1 has been shown to affect the clock machinery in the liver in response to a change in feeding time and impair the food entrainment of peripheral circadian clocks. Daytime restricted feeding shifts the expression of clock genes and the auto-ADP-ribosylation of PARP-1 in liver. Hence feeding regulates the circadian expression of the PARP-1, and may thus via the poly-ADP-ribosylation of CLOCK also affect the molecular clock (Asher et al., 2010). Adenosine monophosphate (AMP) activates the protein kinase AMPK, thereby AMPK activity provides information about the cellular energy state via the AMP to ATP ratio (Davies et al., 1992). In particular, AMPK phosphorylates and destabilizes one of the core clock proteins, CRY1. In this way, AMPK sends timing signals about the cellular energy state directly to the molecular clock via CRY1 (Lamia et al., 2009). 5.4 The nuclear receptor REV-ERBα in relation to circadian clock and metabolism The nuclear receptor (NR) REV-ERBα is also known as NR1D1. REV-ERBα is a transcriptional repressor, encoded by the reverse strand of the thyroid hormone receptor cErbα, as well as its isoform which was discovered later on as REV-ERBβ (Lazar et al., 1989; Dumas et al., 1994; Forman et al., 1994). Until 2007 REV-ERBα was considered as an orphan nuclear receptor. Then, heme was discovered as the physiological ligand, which regulates the activity of REV-ERBα (Yin et al., 2007; Meng et al., 2008). Unlike other NRs, REV-ERBα lacks the carboxy-terminal activation function 2 (AF2) region in its ligand binding domain (LBD) (Dumas et al., 1994; Forman et al., 1994). The AF2 region identifies co-activators required for the transcription. Therefore, due to the lack of an AF2 region, REV-ERBα cannot activate transcription. It acts as a transcriptional repressor due to the binding of co-repressors such as the nuclear receptor co-repressor (NCoR) in the hydrophobic region (Renaud et al., 2000; Yin and Lazar, 2005). REV-ERBα binds to its response element called Rev-erbα response element (RRE, or RORE) containing six base 36 pair core motifs (A/G) GGTCA flanked by an A/T rich 5’ (Solt et al., 2012). REV-ERBα can also repress its own transcription via a RevDR2 binding site in its promotor (Adelmant et al., 1996). REV-ERBα binds either as a monomer or as a homodimer to the RevDR2/ROREs elements which consist of direct repeats of the core motif separated by two nucleotides (Harding and Lazar, 1993; Dumas et al., 1994; Retnakaran et al., 1994; Harding and Lazar, 1995). The binding competitor of REV-ERBα is Retinoic Acid Receptor-Related Orphan receptor α (RORα). Both transcription factors share the same DNA binding site, ROR response elements (RREs or ROREs), but behave in an opposite manner, REV-ERBα acting as a transcriptional repressor while RORα is a transcriptional activator (Duez and Staels, 2008b; Zhao et al., 2014). REV-ERBα members of NR family have diverse roles in different biological processes, such as circadian system, sleep regulation, reproduction, development, inflammation and energy metabolism. They also participate in various metabolic pathways, such as gluconeogenesis, adipocyte differentiation, bile acid synthesis, heme, cholesterol homeostasis and thermogenesis (Yin et al., 2007; Duez and Staels, 2008b; Le Martelot et al., 2009; Delezie et al., 2012; Nam et al., 2016). REV-ERBα was the first NR shown as a link between cellular metabolism and the circadian clock by acting as a circadian transcriptional repressor that regulates the expression of core clock genes and increases the robustness of clock oscillation, besides its involvement in intracellular metabolic pathways. REV-ERBα can also be considered as a clock-controlled gene, because it somehow mediates output pathways of the molecular clock in the SCN and peripheral tissues (Lazar et al., 1989; Balsalobre et al., 1998; Torra et al., 2000). The promoter sequence of Bmal1, a key positive limb element of core clock, contains RORE sequences to which REV-ERBα binds to inhibit its transcription (Preitner et al., 2002; Bugge et al., 2012; Cho et al., 2012). Mice with a knock-out for Rev-erbα show elevated expression of Bmal1, highlighting the repressive effect of REV-ERBα (Preitner et al., 2002). The transcription of Npas2 and Clock is also under the control of REV-ERBα because both of these genes contain RORE sequences in their promoter (Crumbley et al., 2010; Crumbley and Burris, 2011). An in vitro study showed that the E-box binding sites of BMAL1/CLOCK are present in the Rev-erbα promoter, thus suggesting a bidirectional transcriptional regulation of Rev-erbα though BMAL1/CLOCK transactivation (Triqueneaux et al., 2004). These studies collectively indicate the transcriptional relationship between BMAL1/CLOCK and REV-ERB/ROR. REV-ERBα binds to the 37 corepressor N-CoR to repress transcription (Harding and Lazar, 1995; Hu and Lazar, 1999; Ishizuka and Lazar, 2003). The N-CoR/REV-ERBα complex interacts with multiprotein complex Histone deacetylase 3 (HDAC3) which deacetylates histone, causes chromatin compaction and represses Bmal1 transcription (Guenther et al., 2000; Guenther et al., 2001; Ishizuka and Lazar, 2003; Yin and Lazar, 2005). Glycogen synthase kinase 3β (GSK3β) phosphorylates and stabilizes REV-ERBα, while its stability can be modified with lithium (Yin et al., 2006). The cyclin-dependent kinase 1 (CDK1) phosphorylates REV-ERBα at its T275 site, and recognizes/recruits F-box protein, FBXW7α, for proteasome degradation, suggesting that the amplitude of rhythmic expression of REVERBα is dependent on CDK1-FBXW7 axis (Zhao et al., 2016a). 5.4.1 Role of REV-ERBα in behavioural responses. Global Rev-erbα knock-out mice show a shorter period length of locomotor activity (-0.5 h) compared to wild-type mice under constant light (LL) or constant dark (DD) conditions. Global Rev-erbα knock-out mice exposed to light pulses of 2 h in the late night display larger phase advances in locomotor activity rhythm (Preitner et al., 2002). Brainspecific Rev-erbα knock-out mice kept under a regular light dark cycle show a drastic reduction in the day-night amplitude of general locomotor activity. Furthermore, general locomotor activity is highly disturbed, showing either arrhythmicity or heterogeneity among individual free-running periods under DD condition. (Delezie et al., 2016). Food entrainment activity is impaired in global Rev-erbα knock-out mice with decreased anticipatory bouts of locomotor activity and body temperature whether animals are under light-dark or DD conditions, whereas brain deletion of Rev-erbα prevents foodanticipatory behaviour and thermogenesis (Delezie et al., 2016). Mice with global deletion of Rev-erbα with chow available ad libitum do not differ in food intake, general locomotor activity, and body temperature as compared to wild-type mice, while their respiratory quotient rhythm is altered during both day and night. Besides its role in feeding and metabolism, REV-ERBα also plays an important role in vascular inflammation (Sato et al., 2014b), sleep homeostasis, sleep-wake cycle and sleep architecture, emotional behavior (Banerjee et al., 2014; Amador et al., 2016; Mang et al., 2016), and mood regulation (Kishi et al., 2008; Chung et al., 2014). 38 5.4.2 Role of REV-ERBα in peripheral tissues. The clock gene Rev-erbα also plays a significant role in various metabolic pathways. Reverbα is required for adipocyte differentiation (Chawla and Lazar, 1993; Fontaine et al., 2003; Wang and Lazar, 2008). Rev-erbα knock-out mice show increased adipose tissue mass and increased lipoprotein lipase (Lpl) expression in white adipose tissue, skeletal muscle and liver (Delezie et al., 2012). In vivo experiments in rat adipose tissues and in vitro experiments in 3T3-L1 cell lines show that rosiglitazone treatment activates PPARγ which further induces Rev-erbα expression through binding to the DR2 element in its promoter region (Fontaine et al., 2003; Laitinen et al., 2005). Brown adipose tissue (BAT) is a metabolically active tissue that participates in bodily thermogenesis. Thermogenesis is linked to the circadian clock mechanism via Rev-erbα. In 2013, Gerhart-Hines and colleagues demonstrated the role of Rev-erbα in BAT (Gerhart-Hines et al., 2013). REV-ERBα also promotes adipogenesis in BAT (Nam et al., 2015). Global Rev-erbα knock-out mice show increased tolerance to 4°C cold with increased Ucp1 expression in BAT (Delezie et al., 2012; Gerhart-Hines et al., 2013). In Bmal1 knock-out mice, 4°C cold exposure suppresses Rev-erbα expression in BAT (Li et al., 2013). In vivo studies in human subjects using 18-fluorodeoxyglucose (glucose analogue) show a diurnal rhythm of glucose uptake by BAT (Cypess et al., 2009; Virtanen et al., 2009). In mice, such a rhythm is abolished after deletion of Rev-erbα resulting in increased glucose uptake during daytime, but not at night (Gerhart-Hines et al., 2013). Skeletal muscles are metabolically active organs that participate in the homeostasis of glucose uptake and insulin sensitivity (Dyar et al., 2014). Rhythmic functioning in skeletal muscle is under the control of the skeletal molecular clock. Rev-erbα is expressed rhythmically in mouse skeletal muscle with a similar phase as in other peripheral clocks, such as liver and adipose tissues (Yang et al., 2006). REV-ERBα in the muscle represses a key gene, myoD which is essential for muscle cell differentiation as first shown in vitro in C2Cl2 cells (Downes et al., 1995). In addition, it represses the transcription of Bmal1 and Clock genes in muscle (Delezie et al., 2012). Rev-erbα knock-out mice displayed higher Lpl mRNA levels in skeletal muscle (Delezie et al., 2012), decreased oxidative function and decreased exercise, and increased autophagy (Woldt et al., 2013). Administration of the REV-ERBα agonist (SR9011) leads to an amplification in the circadian expression of genes involved in fatty acid oxidation and glycolysis in skeletal muscle (Solt et al., 2012). 39 The liver is the major organ for glucose and lipid metabolism and maintenance of whole body homeostasis. In the liver clock, REV-ERBα regulates expression of BMAL1 and CLOCK (Preitner et al., 2002; Delezie et al., 2012) and modulates body metabolism by regulating lipid, cholesterol and bile acid metabolism, liver gluconeogenesis, hepatic glycogen and circulating glucose, triglycerides and free fatty acids (Duez et al., 2008; Le Martelot et al., 2009; Delezie et al., 2012). REV-ERBα participates in regulation of the rhythmic expression of the rate limiting enzyme cholesterol-7α-hydroxylase (CYP7A1) required for cholesterol to bile acid metabolism. As discussed previously, REV-ERBα recruits the NCoR/HDAC3 complex for suppressing Bmal1 expression in the liver. REVERBα co-localizes with hepatic HDAC3 to regulate lipid metabolism and rhythmic histone acetylation. Accordingly, loss of Rev-erbα disturbs hepatic lipid homeostasis and causes hepatic steatosis (Feng et al., 2011; Bugge et al., 2012; Sun et al., 2012; Sun et al., 2013). REV-ERBα also may regulate the secretion of various endocrine hormones like insulin production by β cells and glucagon production by α cells in pancreatic islets, although conflicting results have been reported (Delezie et al., 2012; Vieira et al., 2012; Vieira et al., 2013). 40 6. Aim of my thesis The aim of my thesis project was to focus on the relation between circadian clocks and clock genes on the one hand and feeding behaviour and diet composition on the other hand. Changes in feeding behaviour either due to an equal distribution of the daily meals over the 24-hour day/night cycle or a change in diet composition may result in disturbances of the circadian clock mechanism. Alternatively, mutations in clock genes may disturb feeding behaviour and, as a consequence, may alter energy metabolism. By investigating the central clock in the SCN and peripheral clocks in the liver, skeletal muscle, and brown adipose tissue under these different conditions we provided new insights into how the central and peripheral clocks of the body may affect whole body metabolism. Figure (14). Figure 14: Schematic representation of the chapters representing the interactions between circadian clocks and feeding behaviour in a nocturnal rodent. Chapter 2 Effects of ultradian feeding on central and peripheral clocks in mice In Chapter 2 we studied in mice the impact of an ultradian 6-meals-a-day feeding schedule on the regulation of the peripheral clock in the liver and the function of the central clock in the SCN, as well as on physiology and metabolism. As already discussed in the Introduction, restricted feeding has a major impact on the peripheral clocks, while caloric restriction also affects the SCN clock. Here in mice, we combined the two approaches, that is, ultradian restricted feeding associated or not with caloric restriction. The aim of this study was to differentiate the effects of timing and caloric restriction on the central and peripheral clocks of mice. 41 Chapter 3 Effects of ultradian feeding on central and peripheral clocks in rats In Chapter 3 we continued the experiment described in Chapter 2 by performing a similar study in rats by exposing them to the 6-meals-a-day feeding schedule and focusing on the regulation of the central clock in the SCN and peripheral clocks in the liver, skeletal muscle, and brown adipose tissue. The aim of this study was to assess the effect of the 6meals-a-day feeding schedule in another species, the rat, and its impact on other peripheral tissues such as muscle and brown adipose tissue along with the liver in relation to circadian rhythmicity and metabolism. Chapter 4 Differential effects of diet composition and timing of feeding behaviour on rat brown adipose tissue and skeletal muscle peripheral clocks In this chapter, we focused on the consequences of a high caloric free choice high-fat high-sugar (fcHFHS) diet along with time-restricted feeding on the daily expression of clock and metabolic genes in rats. The effects of restricted feeding along with a chow or hypercaloric diet have been studied extensively in the liver, but to a lesser extend in skeletal muscle (SM) and brown adipose tissue (BAT), in spite of their critical role in energy metabolism. The aim of this study was to understand the interactive effects of TRF and diet on whole body energy metabolism as well on the clock and metabolic gene expression in overlooked metabolically active tissues such as SM and BAT. Chapter 5 Role of the clock gene Rev-erbα in feeding and energy metabolism The circadian control of feeding behaviour is still not fully understood. 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FEBS letters 586:1306-1311. 371. Zhou QY, Cheng MY (2005) Prokineticin 2 and circadian clock output. The FEBS journal 272:57035709. 60 61 62 Chapter 2 Ultradian feeding in mice not only affects the peripheral clock in the liver, but also the master clock in the brain Satish Sen1,3,4, Hélène Raingard1, Stéphanie Dumont1, Andries Kalsbeek2,3,4, Patrick Vuillez1,4, Etienne Challet1,4 1 Regulation of Circadian Clocks team, Institute of Cellular and Integrative Neurosciences, UPR3212, Centre National de la Recherche Scientifique (CNRS), University of Strasbourg, France. 2 Department of Endocrinology and Metabolism, Academic Medical Center (AMC), University of Amsterdam, The Netherlands. 3 Hypothalamic Integration Mechanisms, Netherlands Institute for Neuroscience (NIN), Amsterdam, The Netherlands. 4 International Associated Laboratory LIA1061 Understanding the Neural Basis of Diurnality, CNRS, France and the Netherlands. Corresponding author: Etienne Challet, INCI, CNRS UPR3212, 5 rue Blaise Pascal, 67084 Strasbourg, France. Tel: +33 388456693, e-mail: challet@inci-cnrs.unistra.fr 63 Abstract Restricted feeding during the resting period causes pronounced shifts in a number of peripheral clocks, but not the central clock in the suprachiasmatic nucleus (SCN). By contrast, daily caloric restriction impacts also the light-entrained SCN clock, as indicated by shifted oscillations of clock (PER1) and clock-controlled (vasopressin) proteins. To determine if these SCN changes are due to the metabolic or timing cues of the restricted feeding, mice were challenged with an ultradian 6-meals schedule (1 food access every 4 h) to abolish the daily periodicity of feeding. Mice fed with ultradian feeding that lost <10% body mass (i.e., isocaloric) displayed 1.5-h phase-advance of body temperature rhythm, but remained mostly nocturnal, together with up-regulated vasopressin and downregulated PER1 and PER2 levels in the SCN. Hepatic expression of clock genes (Per2, Rev-erbα, and Clock) and Fgf21 was respectively, phase-advanced and up-regulated by ultradian feeding. Mice fed with ultradian feeding that lost >10% body mass (i.e., hypocaloric) became more diurnal, hypothermic in late night, and displayed larger (3.5-h) advance of body temperature rhythm, more reduced PER1 expression in the SCN, and further modified gene expression in the liver (e.g., larger phase-advance of Per2 and upregulated levels of Pgc-1α). While glucose rhythmicity was lost under ultradian feeding, the phase of daily rhythms in liver glycogen and plasma corticosterone (albeit increased in amplitude) remained unchanged. In conclusion, the additional impact of hypocaloric conditions on the SCN are mainly due to the metabolic and not the timing effects of restricted daytime feeding. Keywords: Circadian rhythm, feeding, 6-meal schedule, clock gene, suprachiasmatic nucleus. 64 INTRODUCTION Biological rhythms are under the control of circadian oscillators, including a master circadian clock located in the suprachiasmatic nucleus (SCN) of the anterior hypothalamus and peripheral oscillators present in almost every cell of the body (Bray and Young, 2009). The underlying molecular mechanism of the clock is based on transcriptional and translational feedback loops consisting of positive and negative elements (Reppert and Weaver, 2001). When heterodimerized, the positive limb elements BMAL1 and CLOCK activate transcription of the negative elements (Period (Per)1, 2, 3, and Cryptochrome (Cry)1, 2) that in turn inhibit BMAL1/CLOCK transactivation. In parallel, other clock genes such as Rev-erbα, β and Ror α, β, whose transcription is also activated by BMAL1/CLOCK, modulate Bmal1 and Clock transcription (Preitner et al., 2002; Crumbley and Burris, 2011; Cho et al., 2012). Light perceived by the retina is the most potent synchronizer of the circadian rhythm produced by the molecular clock mechanism within the SCN. The molecular clockwork regulates the rhythmic transcription of clock-controlled genes, such as the gene coding for neuropeptide Arginine Vasopressin (Avp) (Jin et al., 1999). The output of the SCN controls the timing of peripheral clocks via nervous, hormonal and behavioral cues (Froy, 2011). Food access restricted to the usual resting period can phase-shift circadian oscillations in a number of peripheral organs and brain regions outside the SCN, while the SCN master clock remains synchronized to the light-dark cycle (Damiola et al., 2000; Stokkan et al., 2001; Feillet et al., 2008b). However, when daytime restricted feeding is combined with caloric restriction, the master clock is affected, as assessed by phase-advances in daily rhythms of body temperature, activity rhythm, and pineal melatonin, as well as by altered photic resetting (Challet, 2010). Moreover, daily caloric restriction leads to phase-shifts in daily oscillations of clock (PER1) and clock-controlled (AVP) proteins in the SCN (Mendoza et al., 2007b). To avoid the synchronizing effects of daily restricted feeding, a protocol has been developed using a feeding regimen of six 10-min food accesses equally distributed over 24 h (i.e., one 10-min meal every 4 h) (Kalsbeek and Strubbe, 1998). In nocturnal rats under light-dark conditions, this ultradian 6-meals-a-day feeding schedule does not modify the phase of locomotor activity rhythm, but if food access to the 6-meals is shortened to cause body mass loss, rats become partially active during daytime due to a phase-advance of the rest/activity rhythm (Mendoza et al., 2008b). 65 One recent rat study showed that peripheral clock gene rhythms are still present during ultradian 6-meals-a-day feeding, despite changes in amplitude and phase (Su et al., 2016a). Another study suggested that in mice, the peripheral clocks remain unaffected by meal timing when each meal is given equally spaced either 2, 3, 4 or 6 times per day. However, if meal frequency is unevenly distributed, i.e., with unequal intervals between the meals, then the phase of peripheral clock genes changes, especially in the kidney. Moreover, that study also showed that ultradian 6-meal feeding coupled to caloric restriction was able to produce phase-advances of peripheral clocks inversely proportional to the degree of energy intake (Kuroda et al., 2012). In the present study, we aimed at investigating further whether it is the daily timing of feeding and fasting or metabolic cues associated with caloric restriction that affects the central and peripheral clocks. For that purpose, we challenged mice with a 6-meals-a-day feeding schedule (combined with isocaloric or hypocaloric conditions) and studied their behavioural and physiological changes, as well as expression of clock and clockcontrolled genes in the master clock and liver. MATERIALS AND METHODS Animals and housing Seventy-six 5-week old male C57BL/6J mice (Janvier labs, Le Genest-Saint-Isle, France) were used for this study. The animals were housed in individual cages equipped with a wheel, at an ambient temperature of 23 ± 2°C under 12:12 h light-dark conditions (lights on at 7:00 AM (defining Zeitgeber Time (ZT) 0) and off at 19:00 PM (=ZT12)). In a group of 46 animals, access to food was automatically controlled by electronic timers for six cages at a time. Thirty animals served as controls and had ad libitum access to food. All experiments were performed in accordance with the U.S. National Institutes of Health Guide for the Care and Use of Laboratory Animals (1996), the French National Law (implementing the European Communities Council Directive 86/609/EEC) and approved in advance by the Regional Ethical Committee of Strasbourg for Animal Experimentation (AL/50/57/02/13) and in compliance with the ethical standards of the journal (Portaluppi et al., 2010). 66 Surgery Mice were anesthetized with isoflurane (Vetflurane, Virbac 3% powered by 0.2 l/ min O2) to implant a transponder (Minimitter, Vitalview, Sunriver, OR, USA) in the abdominal cavity to record body temperature and general cage activity. The abdomen was shaved and sprayed with antiseptic (DermaSpray, Bayer) before an incision in the skin and muscle (810 mm) was made. Once the transponder was inserted into the abdominal cavity, the muscle layer was stitched with surgical sutures (Filapeau, 3.0) and anti-inflammatory medication was provided in drinking water (Metacam, 0.2 mg/ml, 0.1ml) for 2 days. Experimental procedure After surgery, the animals were placed in experimental cages for 2 weeks with drinking water and food ad libitum. After this, mice were habituated to an ultradian schedule of six meals each day with one food access every 4 h (ZT2, ZT6, ZT10, ZT14, ZT18 and ZT22). Access to food during restricted feeding was set automatically by the Food Planning system based on a food basket allowing and preventing food access in the low and upper position, respectively (Intellibio, Seichamps, France). Lifting and fall of the food basket being associated with a brief motor noise, these auditory cues may have signaled food availability to the mice. The smaller mesh size of the trough compared to the size of the food pellets prevented any food hoarding in the cage. Duration of food access was reduced every 4 days gradually from 6 x 1 h, via 6 x 30 min, 6 x 20 min to 6 x 15 min. This protocol was based on previous studies in rats (Kalsbeek and Strubbe, 1998; Mendoza et al., 2008b). The fact that mice were fed every day at the same times has probably improved their ability to adjust to ultradian feeding, as opposed to irregular meal times (Valle, 1981). Food intake during daytime and nighttime was measured twice (at the steps of 6 x 1 h and 6 x 15 min) to evaluate the day-night pattern of food intake. Body mass was measured weekly. At the end of two weeks of feeding according to the 6 x 15 min protocol, two groups were categorized according to individual adaptation to the paradigm, eventually leading to body mass loss. A cut-off at 10% body mass loss allowed to distinguish an isocaloric group including animals with less than 10% of body mass loss (mean: 5.4 ± 0.5%; n total=24; n=4 per ZT) and a hypocaloric group in which animals lost 10% or more (up to 25%) body mass (mean: 15.5 ± 1.1%; n total=22; n=3-4 per ZT). Animals of the control group were kept with food and water ad libitum (n=5 per ZT). 67 Immunohistochemistry At the end of the experiment, animals were sacrificed with an overdose of pentobarbital. Mice fed with ultradian 6-meals schedule were sampled every 4 h between food accesses (i.e., ZT0, ZT4, ZT8, ZT12, ZT16 and ZT20) to limit direct effects of feeding while avoiding prolonged fasting. Control mice fed ad libitum were sacrificed at the same times. Blood was sampled by intracardiac puncture, liver was sampled in the right lobe, and the heart was perfused with 50 mL of 0.9% saline followed by 50 mL of 4% paraformaldehyde in phosphate buffer (0.1 M, pH 7.4). Brains were removed, postfixed overnight in 4% paraformaldehyde (4°C) and transferred to a cryoprotectant buffered sucrose solution (30% at 4°C) for at least 24 h till brains sank to the bottom due to the sucrose density gradient. Brains were then frozen in isopentane around -50°C and stored at -80°C. Five series of 30-μm coronal SCN sections were prepared on a cryostat and collected in Phosphate-Buffered Saline (0.1 M PBS, 1x) and washed with 1x Tris Buffer Saline pH 7.6 (0.1 M TBS 1x). Then sections were incubated in 3% H2O2 in TBS (30 min) to suppress endogenous peroxidase activity, thereby reducing background staining. Again brain sections were rinsed in TBS 1x. Brain sections were then transferred in a solution containing 10% normal serum (either goat or horse according to the host species of the primary antibody) and Triton X-100 (0.1 %) in TBS for 2 h, followed by incubation in the primary antibody (48 h at 4°C). We used rabbit polyclonal anti arginine-vasopressin (AVP) (1:20000, Truus, a gift from Dr. Ruud Buijs, Netherlands Institute for Brain Research, Amsterdam, the Netherlands), goat polyclonal anti-PER1 (1:750; SC-7724, Santa Cruz Biotechnologies, Santa Cruz, CA, USA) and rabbit polyclonal anti-PER2 (1:3000, #PER-21A; Alpha Diagnostic International, San Antonio TX, USA; note that for anti-PER2 immunohistochemistry, PBS indicated below was always replaced with TBS). The sections were washed in PBS 1x, then incubated (2 h at 4°C) with biotinylated goat anti-rabbit IgG (1:500, PK6101; Vectastain Standard Elite ABC Kit Vector Laboratories, Inc., Burlingame, CA, USA) for AVP and PER2 and with biotinylated anti-goat IgG made in horse (1:500, BA-9500; Vector labs) for PER1 immunostaining. After this, sections were rinsed in PBS 1x and incubated (2 h) in a solution containing avidin–biotin peroxidase complex (Vectastain Elite ABC kit; Vector Laboratories Inc.). Following incubation with ABC reagents, sections were rinsed 4 times in PBS, and incubated with H2O2 (0.015%, Sigma-Aldrich, St Louis, MO, USA) and 3,3’diaminobenzidine 68 tetrahydrochloride (0.5 mg/ml, Sigma-Aldrich) diluted in water. Thereafter, sections were rinsed with PBS, wet mounted on slides coated with gelatin, dehydrated through a series of alcohols, soaked in xylene, and cover slipped. Photomicrographs were taken on Leica DMRB microscope (Leica Microsystems) with an Olympus DP50 digital camera (Olympus France). The number of immunopositive cells was counted on one section in both SCN’s and averaged. mRNA extraction and quantitative real-time PCR RNA was extracted from frozen liver samples by homogenizing liver samples in lysis buffer supplemented with β-mercaptoethanol and using absolutely RNA miniprep kit (Agilent Technologies, USA. The samples were purified by precipitation with sodium acetate and isopropyl alcohol. The quality of RNA was measured on NanoDrop ND-100 spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA; A260/A280, and A260/A230 values were > 1.8) RNA integrity was assessed using (Agilent RNA 6000 Nano Kit) on Aligent 2100 bio-analyzer for all the liver samples (RIN Value were >7) bio-analyzer. cDNA was synthesized with the High Capacity RNA to cDNA kit (Applied Biosystem, Foster city CA, USA) using 1µg of RNA. Measurement of relative abundance was performed by real-time PCR analysis using 1X of TaqMan Gene Expression Master Mix (Life Technologies, Foster city, CA, USA). The following TaqMan probes (Per2: Mm00478113_m1, Clock: Mm00455950_m1, Sirt1: Mm00490758_m1, Fgf21: Mm00840165_g1, Nr1d1 (Rev-erb α): Mm00520708_m1, Pparα: Mm01208835 m1 and Pgc-1α: Mm00440939_m1) were used for all the genes with 1µl of cDNA in the reaction mixture of 20 μl. Each reaction PCR was done in duplicate. A dilution curve was prepared of pooled cDNA samples using log10 standards to calculate the amplification efficiency for each primer set (values were between 1.85-1.99). Data were normalized to Tbp (Mm00446971_m1) and analysed the comparative cycle threshold (Ct) method RQ= 2∆∆Ct. ∆∆Ct =∆Ct sample- ∆Ct reference (Pfaffl, 2001) with efficiency corrections. Transcript levels were calculated relative to the mean of ZT 0 samples. Plasma metabolic parameters Plasma samples were obtained after centrifugation of fresh blood collected with 4% EDTA 69 (10 µL for 1 mL of blood) and centrifuged for 10 min (5000 rpm at 4°C). Plasma glucose was evaluated with GOD-PAP kit (Biolabo, Maizy, France). The ACS-ACOD method (NEFA-HR2; Wako, Osaka, Japan) was used for assaying plasma non-esterified fatty acids (NEFA). Plasma concentrations of corticosterone were determined by a Rat/Mouse Corticosterone EIA kit (AC-14F1, IDS EURL, Paris, FRANCE). The limit of sensitivity of the assay was 0.55 ng/mL. Hepatic glycogen assay Samples of fresh liver were flash-frozen in liquid nitrogen. Hepatic glycogen was quantified according to the method developed by Murat and Serfaty (Murat and Serfaty, 1974). Statistical analysis Data are presented as mean ± standard error of the mean (SEM). Statistical analysis was performed by SigmaPlot (version 12, SPSS Inc, Chicago, IL, USA). Significance was defined at p<0.05. Two-way analysis of variance (ANOVA) with or without repeated measures (RM) were performed to assess the effect of Feeding conditions (food ad libitum, ultradian iso- or ultradian hypo-caloric feeding) and the effect of Time (either baseline versus experimental condition, or time of day), and the Interaction between these factors. One-way analysis of variance (ANOVA) was performed to assess the effect of Time in the separate feeding groups. When appropriate, post-hoc analysis was performed using Fisher LSD method. For assessing daily rhythmicity, we used a cosinor analysis to determine mean level, amplitude and acrophase of the considered parameter with SigmaPlot software (Jandel Scientific,Chicago, IL). Data were fitted to the following regression: [y=A+B·cos(2π(xC)/24)], where A is the mean level, B the amplitude and C the acrophase of the rhythm. RESULTS Food intake When mice were fed with 6 meals of 1 h each, they ate most of their food during their active period (night time) and less during their resting period (p<0.001). Post-hoc analysis showed a significant effect of Time (night vs. day; Fisher LSD test, p<0.05) (Figure 1A). Mice on the 15-min 6-meals-a-day feeding schedule, both the hypocaloric and isocaloric 70 group, ate equal amounts of food during day and night. However, the amount of food ingested by the hypocaloric group was significantly lower (~20%) than that by the isocaloric mice, both during day and night (Group: isocaloric vs. hypocaloric, p<0.001; Time: night vs. day, p=0.056; Interaction: p=0.88) (Figure 1B). Activity levels being similar in both groups (see below), the reduced food intake and larger loss of body mass in the hypocaloric group seem to be due to a poorer adaptation of these mice to six 10-min meals schedule per day (e.g., less efficient feeding strategy or capacity) compared to isocaloric mice. FIGURE 1. Food intake in mice fed with ultradian 6-meal schedules. (A) Day and night food intake during 6 x 1 h ultradian schedules in isocaloric and hypocaloric groups. (B) Day and night food intake during 6 x 15 min ultradian schedules for isocaloric and hypocaloric groups. Means (± SEM) lacking common letters are significantly different (Post-hoc test after ANOVA; p<0.05). Behavioral and physiological outputs of the central clock Wheel-running activity Two-way ANOVA-RM revealed that during the 6 meals-a-day feeding schedule, daytime activity was more enhanced in hypocaloric animals than in isocaloric mice as compared to ad libitum baseline conditions (Feeding: baseline with food ad libitum vs. 6-meal schedule, p<0.001; effect of Group: isocaloric vs. hypocaloric, p<0.001 and Interaction, p<0.001; Figures 2 and 3A). The proportion of nocturnal activity was lower in the 6 meals-a-day as compared to ad libitum feeding conditions, and the decrease during 6meals feeding was more marked in the hypocaloric group compared to the isocaloric group (Feeding effect: p<0.001; Group effect: p<0.001 and Interaction: p<0.001; Figure 3B). Total wheel-running activity was increased during ultradian 15-min 6-meal feeding as compared to ad libitum baseline conditions (Feeding: baseline with food ad libitum vs. 71 6-meal schedule, p <0.001), while there was no difference between the isocaloric and hypocaloric groups (Group: p=0.27; Figure 3C). FIGURE 2. Daily wheel-running activity in two mice submitted to ultradian 6-meal schedules, belonging either to the isocaloric (panel A) or hypocaloric groups (panel B). The horizontal lines show the successive shortening in duration of food access and the vertical lines show the imposed timing of the 6 meals every 4 h, starting at ZT2 (Zeitgeber 2, i.e. 2 h after lights on). The white area on the 4th day of 6 x 15 min feeding schedule is due to a failure in data acquisition (~12 h). Note the increase in daytime activity, and decrease in nocturnal activity of the mouse of the hypocaloric group (panel B). Body temperature Two-way ANOVA-RM performed on mean body temperature showed a significant effect of Feeding (p<0.001), a significant effect of Group (p<0.001) and a significant Interaction (p<0.001). Post-hoc analysis (Fisher LSD test, p<0.05) showed that in mice fed with the ultradian 6-meal schedule mean body temperature decreased with a deeper drop in the hypocaloric group (-1.2°C) than in the isocaloric group (-0.2°C), compared to baseline values (Figures 4 and 5A). The amplitude of the body temperature rhythm was increased by the ultradian 6-meal schedule, both in hypo- or isocaloric conditions (Feeding: p<0.001; Group: p=0.81; Interaction, p=0.019) (Figure 5B). The acrophase of the body temperature rhythm showed a phase-advance during the ultradian 6-meals schedule, with earlier values in the hypocaloric group (i.e., +3.5 h compared to baseline peak) compared to the isocaloric group (i.e., +1.5 h compared to baseline; Feeding: p<0.001; Group: p<0.006; and Interaction, p<0.001) (Figure 5C). 72 FIGURE 3. Changes in the levels of wheel-running activity between baseline conditions with with food ad libitum and 6 x 15 min ultradian schedules for isocaloric and hypocaloric groups. (A) Daytime wheel-running activity, expressed in % of total activity (B) Nocturnal wheel-running activity, expressed in % of total activity. (C) Total wheel-running activity (per 24 h), expressed in numbers of wheel revolutions. Means (± SEM) lacking common letters are significantly different (Post-hoc test after 2-way ANOVA-RM; p<0.05). Daily expression of clock and clock-controlled proteins in the SCN PER1 The expression level of the clock protein PER1 was assessed in the SCN of mice fed ad libitum and in animals fed according the ultradian 6-meal schedule (hypocaloric and isocaloric groups; Figure 6). There were significant effects of Time of day and Feeding, and a significant Interaction between the two parameters (p<0.001 for the three factors, Table1). The significant Feeding effect was caused by a reduction in mean levels of PER1 in the isocaloric and hypocaloric groups, as compared to ad libitum fed controls. One-way ANOVA analysis showed a significant effect of Time in mice fed ad libitum and in the animals fed with ultradian 6-meal schedule (Table 1). Cosinor analysis confirmed the daily rhythmicity of PER1 levels in the SCN of all three groups (peak around ZT14) (Figure 7A, Table 2), as well as the down-regulated expression in mice fed with the ultradian 6-meals schedule, with the most reduced levels in the hypocaloric group (Table 2). In addition, the ultradian 6-meals schedule reduced the amplitude of PER1 expression rhythm in the SCN. Together these results clearly show that the 6 meal feeding conditions affect the master clock. 73 FIGURE 4. Daily body temperature in two mice submitted to ultradian 6-meal schedules, belonging either to the isocaloric (panel A) or hypocaloric groups (panel B; same mice as in Figure 2). The horizontal lines show the successive shortening in duration of food access and the vertical lines show the imposed timing of the 6 meals every 4 h, starting at ZT2 (Zeitgeber 2, i.e. 2 h after lights on). The white area on the 4th day of 6 x 15 min feeding schedule is due to a failure in data acquisition (~12 h). Note the increase in daytime thermogenesis, and decrease in nocturnal thermogenesis of the mouse of the hypocaloric group (panel B). The mean daily profiles of body temperature rhythm are during food ad libitum (panel C) and 6 x 15 min ultradian schedules (panel D) for isocaloric (black squares) and hypocaloric groups (grey triangles). During 6-meals schedule (panel D) rectangle boxes indicate the time of food access. Note the diet-induced thermogenesis after each meal in panel D. Rectangle boxes are also drawn in panel C for visual comparison. PER2 Expression of PER2, another core clock protein, was also investigated in the SCN of control mice and those fed according the ultradian 6-meals schedule (Figure 6). Two-way ANOVA revealed significant effects of Time of day and Feeding (p<0.001 for the two factors Table 1). The One-way ANOVA analysis showed a significant effect of Time in mice fed ad libitum and the animals fed with the ultradian 6-meal schedule (Table 1). Mean levels of PER2 were reduced in both groups of animals fed with the 6-meal schedule, as compared to control mice fed ad libitum (Table 2). Cosinor analysis showed a significant rhythmic expression of PER2 in all three experimental groups, with a peak expression in early night (around ZT13-14) (Figure 7B, Table 2). Vasopressin (AVP) Expression of AVP, a clock-controlled protein, was examined in the SCN of ad libitum fed mice, and animals fed according to the ultradian 6-meal schedule (Figure 6). Two-way ANOVA showed a significant effect of Feeding condition (p<0.001) and a significant 74 Interaction (p=0.005; Table 1). One-way ANOVA analysis showed a significant effect of Time in mice fed ad libitum, but not in animals fed with the ultradian 6-meal schedule (Table 1). Mean levels of AVP expression in the SCN were up-regulated by 30% throughout the 24 h cycle in both the isocaloric and hypocaloric group, compared to the control group fed ad libitum (Table 2). Cosinor analysis detected a significant rhythm in the ad libitum fed group, with an acrophase at dusk, around ZT11, but not in the isocaloric and hypocaloric groups (Figure 7C, Table 2). The lack of rhythmicity in the isocaloric 6meals schedule groups indicates that the ultradian feeding schedule may have a major impact on SCN functioning. FIGURE 5. Changes in body temperature between baseline conditions with food ad libitum and 6 x 15 min ultradian schedules for isocaloric and hypocaloric groups, including mean body temperature (A), amplitude rhythm (B), and acrophase (C). Means (± SEM) lacking common letters are significantly different (Posthoc test after 2-way ANOVA-RM; p<0.05). Rhythms of plasma metabolites Plasma glucose While the main effect of Time of day was not significant for plasma glucose (Table 1), significant differences among groups did occur (Feeding (p<0.001) and Interaction (p<0.01)). The one-way ANOVA analysis showed a significant effect of Time in mice fed ad libitum, but no effect of Time in the animals fed with ultradian 6-meal schedule (Table 1). Cosinor analysis detected a significant rhythm in plasma glucose only in ad libitum group (Table 3). As compared to ad libitum control values, the mean levels of plasma glucose were unchanged and reduced in isocaloric and hypocaloric groups, respectively (Figure 8A, Table 3). These results indicate that the ultradian 6-meal schedule causes 75 arrhythmicity of the plasma glucose rhythm in both the isocaloric and hypocaloric group and an additional hypoglycemia in the hypocaloric group. Non-esterified fatty acids (NEFA) Two-way ANOVA showed a significant effect of Time of Day (p=0.034) and Feeding condition (p=0.020), but no Interaction (Table 1). One-way ANOVA analysis showed a significant effect of Time only in the isocaloric group, but not in the animals fed ad libitum (Table 1). Cosinor analysis showed no significant daily rhythms for plasma NEFA levels (Figure 8B, Table 3). Plasma corticosterone The daily corticosterone rhythm was significantly affected by the different feeding conditions Feeding (p<0.001) and Interaction (p<0.003; Table 1). The one-way ANOVA analysis showed a significant effect of Time in all 3 feeding groups (Table 1), as did the cosinor regression (Table 3). Remarkably, the ultradian 6-meal schedule did not modify its basal levels at dawn. By contrast, ultradian feeding caused an increase of the daily amplitude of corticosterone variations, especially in the hypocaloric group (Figure 8C, Table 3). Liver glycogen Two-way ANOVA showed significant effects of Time (p<0.001), but not of Feeding or Interaction (Table 1). One-way ANOVA analysis showed a significant effect of Time in fed ad libitum control, isocaloric and hypocaloric groups (Table 1). Cosinor regression showed a significant rhythm in all 3 groups (Table 3; Figure 8D). Of note, in contrast to plasma glucose, neither the phase, nor the levels of liver glycogen were affected by the ultradian 6-meal feeding. Daily expression of clock and metabolic genes in the liver Per2 The One-way ANOVA analysis showed a significant effect of Time in all 3 feeding groups (Table 1) and so did the cosinor regressions (Table 4). However, the significant effects of Feeding (p<0.001) and Interaction (p<0.001); Table 1) indicate that these rhythms differed between groups. Indeed, Per2 expression was down-regulated and 76 markedly phase-advanced by the ultradian 6-meal feeding in both hypocaloric (7 h) and isocaloric groups (4 h), as compared to control mice fed ad libitum ( Figure 9A, Table 4). Clock Expression of the circadian gene Clock in the liver was still rhythmic in mice fed according to the ultradian 6-meal schedule (Time of day, p<0.001; Tables 1 and 4). The significant effects of Feeding (p<0.001) and Interaction (p<0.001) indicated a downregulated Clock expression only in isocaloric 6-meal fed mice (Figure 9B, Tables 1 and 4). Moreover, hepatic expression of Clock was phase-advanced respectively by 3.5 and 1.2 h in the isocaloric and hypocaloric groups, as compared to control mice fed ad libitum ( Figure 9B, Table 4) Rev-erbα The hepatic expression of Rev-erbα (also known as Nr1d1) showed rhythmic expression for all feeding conditions (Time of day, p<0.001; Feeding (p=0.03) and Interaction (p<0.001); Tables 1 and 4). Rev-erbα expression was phase-advanced respectively by ~3.5 and 4.7 h in the hypocaloric and isocaloric groups, as compared to control mice fed ad libitum (Figure 9C, Table 4). Pparα The expression of the metabolic gene peroxisome-proliferative-activated-receptor alpha (Pparα) in the liver was rhythmic only in the isocaloric group and the ad libitum fed animals as indicated by the one-way ANOVA (Table 1). Moreover there was a significant effect of Feeding (p<0.002) and Interaction (p<0.007) (Table 1). Cosinor regression indicated significant rhythms in the ad libitum and isocaloric groups (Table 5). Pparα expression was down-regulated in isocaloric 6-meal fed group (Figure 9E, Table 5). 77 FIGURE 6. Photomicrographs of PER1, PER2 and AVP immunostaining in the SCN of ad libitum fed, Isocaloric and Hypocaloric groups. Frames indicate the time points with largest differences among groups. Scale bar, 200 μm. ZT, Zeitgeber time (ZT0 and ZT12 defining lights on and off, respectively). 78 Table 1. P values for the effects of time, feeding and interaction (Two-way ANOVA) and effect of time for each feeding condition (One-way ANOVA). Two-way ANOVA (Time x Feeding) Proteins PER1 PER2 AVP Plasma metabolites Glucose NEFA Corticosterone Liver Glycogen Clock genes Per2 Clock Rev-erbα Metabolic genes Sirt1 Pparα Pgc-1α Fgf21 One-way ANOVA (Time) Time Feeding Interaction Ad libitum Isocaloric Hypocaloric < 0.001 < 0.001 = 0.247 < 0.001 < 0.001 < 0.001 < 0.001 = 0.209 = 0.005 < 0.001 < 0.001 = 0.007 = 0.014 < 0.001 = 0.776 = 0.031 < 0.001 = 0.129 = 0.985 = 0.034 < 0.001 < 0.001 = 0.001 = 0.020 < 0.001 = 0.229 = 0.008 = 0.344 = 0.003 = 0.144 = 0.041 = 0.795 < 0.001 < 0.001 = 0.069 = 0.026 = 0.002 = 0.004 = 0.500 = 0.285 = 0.001 = 0.016 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 = 0.030 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.010 = 0.044 = 0.003 < 0.001 = 0.159 = 0.007 = 0.005 = 0.080 = 0.002 < 0.001 < 0.001 = 0.448 = 0.007 = 0.162 = 0.017 = 0.151 < 0.001 < 0.002 = 0.076 = 0.061 = 0.002 = 0.229 = 0.293 = 0.049 = 0.416 = 0.176 = 0.015 FIGURE 7. Daily profiles of expression of clock and clock-controlled proteins in the SCN of fed ad libitum (white circle), ultradian isocaloric (black square) and hypocaloric (dark grey triangle) groups. (A) PER1 expression; (B) PER2 expression; (C) AVP expression. Fitted lines show significant cosine regressions (see methods). ~ effect of time of day (p<0.05), # effect of feeding (p<0.05) and x interaction between feeding and time of day (p<0.05). 79 Table 2. Parameters of cosinor regressions of daily expression of clock and clock- controlled proteins in the SCN. SCN PER1 (n cells) Mean SEM Ad libitum (n=30) Isocaloric (n=24) Hypocaloric (n=22) a b * 191.06 111.14* 9.17 13.03 c a b 13.43 117.79^ 47.27 0.44 11.08 15.67 c a 13.69 84.93 1.26 8.04 b 39.18 c 15.14 P < 0.001 SCN PER2 (n cells) Mean SEM 114.92 85.96 * 3.81 5.40 P < 0.001 Mean SCN AVP (n cells) SEM * 1.92 2.70 = 0.040 10.60 55.37 - 1.42 1.45 - = 0.799 53.56 1.57 42.43 7.32 13.44 83.79 70.08 0.23 8.53 11.75 14.22 68.00 0.67 7.61 11.58 68.48 10.99 - - 1.08 14.34 0.58 - - < 0.001 < 0.001 < 0.001 < 0.001 P # = 0.135 Table 2. Shows the three parameters of cosinor regressions, including a) the mean level, b) the amplitude, and c) the acrophase of the rhythm (see Methods for details). For the acrophase, the reference time is Zeitgeber 0 (i.e., lights on).*Ad libitum group is significantly different from Isocaloric and Hypocaloric groups (P < 0.05). ^ Isocaloric group is significantly different from Hypocaloric group (P < 0.05). #Ad libitum group is significantly different from Hypocaloric group (P < 0.05). P values in the right columns indicate the significance of the cosinor fit. Figure 8. Daily profiles of plasma glucose, non-esterified fatty acids, corticosterone, and hepatic glycogen in fed ad libitum (white circle), ultradian isocaloric (black square) and hypocaloric (dark grey triangle) groups. (A) Plasma glucose, (B) Plasma non-esterified fatty acids (NEFA) (C) Plasma corticosterone (D) Hepatic glycogen. Fitted lines show significant cosine regressions (see methods). ~ effect of time of day (p<0.05), # effect of feeding (p<0.05) and x interaction between feeding and time of day (p<0.05).parameters are not shown (-). 80 Table 3. Parameters of cosinor regressions of daily variation of plasma glucose, non-esterified fatty acids, liver glycogen, and plasma corticosterone. Plasma Glucose (mmol/L) Mean SEM P Ad libitum (n=30) Isocaloric (n=24) # a b 12.02 0.49 2.05 0.69 c a 3.23 1.29 11.59^ 0.42 b c Hypocaloric a b (n=22) c = 0.022 Plasma NEFA (mmol/L) Mean SEM 0.13 - = 0.124 = 0.601 3.95 - 3.22 - 1.28 = 0.706 § < 0.001 114.49* 8.53 0.38 70.93 11.88 0.44 11.55 0.66 3.32 0.24 96.71 18.015 - - 1.84 0.36 127.98 25.48 8.82 0.59 - - 0.80 0.69 10.09 0.76 0.14 0.01 4.00 0.34 = 0.131 0.01 0.26 Plasma Corticosterone (ng/mL) Mean SEM P - - 0.18 € 0.013 P Liver Glycogen (mg/100mg) Mean SEM P = 0.587 = 0.003 < 0.001 203.03 19.90 £ 27.87 - - - - - 2.18 0.48 201.20 - - - - - 2.93 0.85 11.37 < 0.001 < 0.001 < 0.001 0.54 Table 3. Shows the three parameters of cosinor regressions, including a) the mean level, b) the amplitude, and c) the acrophase of the rhythm (see Methods for details). For the acrophase, the reference time is Zeitgeber 0 (i.e., lights on). *Ad libitum group is significantly different from Isocaloric and Hypocaloric groups (P < 0.05). ^Isocaloric group is significantly different from Hypocaloric group (P < 0.05). # Ad libitum group is significantly different from Hypocaloric group (P < 0.05). £Hypocaloric group is different from Isocaloric and Ad libitum fed groups (P < 0.05). §Ad libitum group is different from Isocaloric group (P < 0.05). € Isocaloric is different from Ad libitum. NEFA, non-esterified fatty acids and glucose mmol/L, Millimoles per Litre. Liver glycogen mg/100mg, Milligram per 100 Milligram. Plasma corticosterone ng/ml, Nanogram per Milliliter. P values on the right columns indicate significance of the cosinor fit. Non-significant parameters are not shown (-). 81 Table 4. Parameters of cosinor regressions of daily expression of clock genes in the liver Ad libitum a b (n=30) c Isocaloric a b (n=24) c Hypocaloric a b (n=22) c Liver Per2 Liver Clock Liver Rev-erb (a.u.) (a.u.) (a.u.) Mean SEM P Mean SEM P Mean SEM P * § 2.18 0.11 < 0.001 0.76 0.02 < 0.001 9.51 1.24 < 0.001 * 2.09 0.16 0.30 0.03 13.40 1.81 * * 15.75 0.28 22.66 0.45 7.10* 0.49 1.41 0.14 < 0.001 0.55^ 0.02 < 0.001 6.53 0.99 < 0.001 1.06 0.20 0.21 0.03 8.37 1.40 ^ ^ 11.81 0.71 19.19 0.59 3.56 0.64 1.70 0.17 < 0.001 0.75 0.03 = 0.004 9.47 1.35 < 0.001 1.08 0.24 0.21 0.05 9.60 1.95 8.71 1.88 21.42 0.99 2.37 0.74 Table 4 shows the three parameters of cosinor regressions, including a) the mean level, b) the amplitude, and c) the acrophase of the rhythm (see Methods for details). For the acrophase, the reference time is Zeitgeber 0 (i.e., lights on).*Ad libitum group is significantly different from Isocaloric and Hypocaloric groups (P<0.05). ^Isocaloric group is significantly different from Hypocaloric group (P<0.05). §Ad libitum group is different from Isocaloric group (P<0.05). a.u., arbitrary units. P values on the right columns indicate significance of the cosinor analysis. Pgc-1α The hepatic expression of Pgc-1α showed significant effects of Time (p=0.007; Table 1) and Feeding (p<0.001). The effect of Feeding was caused by the up-regulated Pgc-1α expression during ultradian 6-meal feeding, especially in the hypocaloric group, as compared to control mice fed ad libitum ( Figure 9F, Table 1). One-way ANOVA analysis showed a significant effect of Time only in the mice fed ad libitum, but not in the animals fed with ultradian 6meal schedule (Table 1) and significant cosinor regressions in all the groups (Table 5). Fgf21 The significant effect of Feeding (p<0.001) and Interaction (p=0.017) was caused by Fgf21 expression being up-regulated by the ultradian 6-meal schedule ( Figure 9G, Table 1). Fgf21 in liver showed rhythmic expression in ad libitum and hypocaloric group (Table 5). One-way ANOVA analysis showed a significant effect of Time only in hypocaloric group of mice fed under ultradian 6 meal schedule (Table 1). 82 Figure 9. Daily profiles of hepatic expression of clock and metabolic genes in fed ad libitum (white circle), ultradian isocaloric (black square) and hypocaloric (dark grey triangle) groups. (A) Per2, (B) Clock, (C) Reverbα, (D) Sirt1, (E) Pparα, (F) Pgc-1α and (G) Fgf21. Fitted lines show significant cosine regressions (see methods). ~ effect of time of day (p < 0.05), # effect of feeding (p < 0.05) and x interaction between feeding and time of day (p < 0.05). 83 DISCUSSION Challenging mice with a 6-meals-a-day feeding schedule (i.e., one food access every 4 h throughout the 24-h light-dark cycle) markedly disrupts the circadian organization in the SCN and the liver, thus demonstrating that the daily rhythm of feeding and fasting profoundly affects the functioning of the peripheral and master clock system. Therefore, the 6-meals-aday feeding schedule, i.e., the absence of a clear daily rhythm of feeding and fasting, results in a partial desynchronization (uncoupling) within the multi-oscillatory network, with stronger changes occurring when ultradian feeding was combined with caloric restriction. In addition, caloric restriction results in a strong phase-advance of the nocturnal pattern of wheel-running activity, thereby leading to a more diurnal phenotype in locomotor activity. Hence we concluded that ultradian periodicity of the meals and hypocaloric condition cause significant changes in the SCN and peripheral clocks, and that metabolic cues associated with caloric restriction modulate the temporal niche of activity. Physiological and behavioural changes Mice fed according to the ultradian feeding schedule were initially given food access for 1 h every 4 h (6 x 1 h per 24 h). During this stage of the 6 meals-a-day feeding protocol, animals show a normal pattern of food intake characterized by high nocturnal intake, but when each food access was shortened to 15 min (6 x 15 min per 24 h) the mice eat equal amounts of food during day and night. Similar adaptations to such unusual feeding schedules have been initially demonstrated in rats fed with an ultradian 6-meals schedule of 6 x 10 min each (Kalsbeek and Strubbe, 1998). More recently, another team applied this protocol in mice (Kuroda et al., 2012). In the present study, the fact that about half of the mice on the ultradian feeding schedule lost body mass led us to subdivide them into two groups, isocaloric and hypocaloric mice (with a cut-off for 10% of body mass loss). The similar levels of wheelrunning activity between the two groups indicate that the differences observed in the hypocaloric group are likely due to reduced energy intake and related metabolic changes. 84 Table 5. Parameters of cosinor regressions of daily expression of metabolic genes in the liver. Liver Sirt1 (a.u.) Ad libitum a b (n=30) c Isocaloric a b (n=24) c Hypocaloric a b (n=22) c Mean 1.27 0.18 12.23 1.33 1.45 0.35 14.41 Liver Pparα (a.u.) SEM P Mean SEM P § 0.05 = 0.050 1.24 0.05 < 0.001 0.07 0.37 0.07 1.55 12.09§ 0.76 0.04 = 0.066 0.88 0.04 = 0.015 0.20 0.06 7.43 1.20 0.06 = 0.003 1.15 0.12 = 0.364 0.09 0.94 - Liver Pgc-1α (a.u.) Mean 2.08* 0.61 10.88 3.27^ 0.98 11.23 5.25 2.97£ 9.09 Liver Fgf21 (a.u.) SEM P Mean 0.11 = 0.002 1.61 0.16 1.13# 1.01 6.93# 0.26 = 0.042 6.14€ 0.36 1.4 0.75 = 0.033 5.57¥ 1.04 3.99 1.39 23.44 SEM 0.23 0.33 0.65 0.74 0.71 1.01 0.95 P = 0.009 = 0.326 = 0.003 Table 5 shows the three parameters of cosinor regressions, including a) the mean level, b) the amplitude, and c) the acrophase of the rhythm (see Methods for details). For the acrophase, the reference time is Zeitgeber 0 (i.e., lights on).*Ad libitum group is significantly different from Isocaloric and Hypocaloric groups (P < 0.05). ^Isocaloric group is significantly different from Hypocaloric group (P<0.05). #Ad libitum group is significantly different from Hypocaloric group (P < 0.05). §Ad libitum group is different from Isocaloric group (P < 0.05). £ Hypocaloric group is different from Isocaloric and Ad libitum fed groups (P < 0.05). € Isocaloric is different from Ad libitum. ¥ Hypocaloric is different from Ad libitum. a.u., arbitrary units. P values on the right columns indicate significance of the cosinor analysis. Non-significant parameters are not shown (-). 85 While the isocaloric group of mice maintained essentially a nocturnal pattern of wheelrunning activity under the ultradian feeding schedule, the behavioral pattern is very different in the hypocaloric group. These mice became partially diurnal, being inactive during late night and shifting their activity onsets towards daytime. These data suggest that the SCN is affected by hypocaloric feeding. A daily hypocaloric single meal has previously been shown to induce phase-advances of the rest-activity rhythm in both rats and mice, independent of the time of hypocaloric feeding (Challet et al., 1997a; Challet et al., 1998). Also, energetic constraints associated with the so-called work for food paradigm lead to shifts of the nocturnal activity pattern of mice to diurnality (Hut et al., 2011; van der Vinne et al., 2014). When diurnal grass rats (Arvicanthis ansorgei) are fed with daily hypocaloric feeding at night, they become partially nocturnal (Mendoza et al., 2012a). In addition to the dramatic reorganization of rest-activity rhythm in the hypocaloric mice, it is worth mentioning that these mice also display some anticipatory activity prior to food access at ZT6 (Fig. 2B) that is not seen in the isocaloric group (Fig. 2A). A previous work studied behavioral changes of calorie restricted mice fed with a daily amount equal to 60% of ad libitum conditions using automatic feeders that delivered food pellets every 4 h. Compared to control mice (i.e., fed ad libitum in addition to the food pellets supplied by the feeders), calorie restricted mice displayed increased daytime activity, as in our hypocaloric group, and anticipation to the meals, especially those occurring during daytime (Luby et al., 2012). A drop in the mean body temperature was detected when mice were fed according to the ultradian feeding rhythm. Such drops in body temperature are also seen when rats and mice are fasted (Nagashima et al., 2003; Tokizawa et al., 2015) and other conditions with energetic challenges (e.g., (Hut et al., 2011)), likely helping these animals to minimize their energy expenditure. Previously a drop in mean body temperature and a phase-advance was also observed in rats challenged with ultradian 6-meal schedules combined with caloric restriction (Mendoza et al., 2008b). In the current study the acrophase of the body temperature rhythm was shifted towards daytime during the 6-meals-a-day feeding schedule, with a larger phaseadvance in the hypocaloric fed mice compared to the isocaloric group. The sensitivity of the SCN clock to temperature cues has been a subject of recent debate because some studies found that the SCN may be shifted or not by temperature cycles (Herzog and Huckfeldt, 2003; Buhr et al., 2010). The fact that the rest-activity rhythm was only phase-advanced in the 86 hypocaloric group may be due to the deeper hypothermia in the calorie-restricted mice, i.e. the SCN and/or its downstream structures (e.g., secondary brain clocks) would be sensitive to the shifting effects of this deeper hypothermia. Glucose metabolism In contrast to the daily profiles of plasma NEFA, the daily rhythm of plasma glucose was highly altered by the 6-meal feeding schedule, with differential effects depending on whether the mice belonged to the hypocaloric or isocaloric group. In mice with ad libitum access to food, plasma glucose levels rise during daytime, as previously observed in other studies (e.g., (Ahren, 2000; Grosbellet et al., 2015)). While rats fed with the 6-meal schedule maintain their daily rhythm in plasma glucose at the same phase as rats fed ad libitum (La Fleur et al., 1999), in mice fed with 6-meal schedule daily plasma glucose levels became arrhythmic. In the hypocaloric group, in addition a relative hypoglycaemia occurred, most likely due to the caloric restriction (Mahoney et al., 2006). Liver glycogen is crucial for maintaining blood glucose homeostasis. However, contrary to plasma glucose levels, the daily profiles in hepatic glycogen content remained unaltered, whatever the feeding condition of the mice. These findings suggest that daily rhythmicity of glycogen synthesis in these animals is dependent on SCN outputs (other than AVP) and/or light signals, most likely conveyed by autonomic inputs (Cailotto et al., 2008). Daytime restricted feeding in rats, however, results not only in increased gluconeogenesis, but also in a 12-h shift in the daily variations of hepatic glycogen content (Perez-Mendoza et al., 2014), thus indicating that daily restricted feeding can impact timing of glycogen synthesis. In the present study, the unaltered daily rhythm of glycogen content in the liver as opposed to the altered rhythms of plasma glucose suggest that changes in glycemia during ultradian feeding are mainly due to an altered timing in glucose utilization (e.g., by the skeletal muscles and/or the brain). Plasma corticosterone Contrary to the restricted-feeding paradigm, the ultradian 6-meal feeding schedule does not induce any pre-feeding rise of corticosterone, but increases the amplitude of daily rhythm of plasma corticosterone in rats (La Fleur et al., 1999). In the present study performed in mice, 87 the daily rhythm of plasma corticosterone also showed a profound increase in amplitude during ultradian feeding conditions, but no shift of its acrophase. As for liver glycogen content, these findings suggest that daily rhythmicity of corticosterone concentrations during 6-meal schedule is controlled by SCN outputs (that would be different in that situation from the classical involvement of SCN AVP; (Kalsbeek et al., 2012)) and/or light signals probably conveyed by autonomic inputs (Ishida et al., 2005; Husse et al., 2014). A disappearance of the circadian trough of circulating glucocorticoids is a hallmark of chronic stress (Dallman et al., 2000). The low morning levels of plasma corticosterone during 6-meals schedule (both the iso- and hypo-caloric groups) indicate that the basal activity of the hypothalamic-pituitaryadrenal (HPA) axis is unaltered. By contrast, mice challenged with work for food display a large increase of corticosterone levels throughout daytime (van der Vinne et al., 2014), suggesting hyperactivity of the HPA axis. Thus, 6-meals schedule and work for food paradigms differentially affect the HPA axis. The body mass loss may explain the increased evening peak of corticosterone during the ultradian feeding schedule, as mildly foodrestricted rats fed at dusk also show an increased amplitude of the plasma corticosterone rhythm that seems to result from an increased sensitivity of ACTH to CRH (Garcia-Belenguer et al., 1993). Clock and metabolic gene expression in the liver In food-restricted animals fed during the resting phase, meal feeding is well known to phaseshift peripheral clocks, especially those in the liver (Damiola et al., 2000; Stokkan et al., 2001). By contrast, in response to ultradian feeding, the liver clock is not affected as a whole (Kuroda et al., 2012; Su et al., 2016c). Instead, as confirmed in the present study, distinct transcriptional changes are detected according to the clock gene considered (i.e., Clock, Reverbα, and Per2). First, the phase of oscillations of the circadian gene Clock was only slightly phase-advanced (+1-3 h) by the 6-meal feeding schedule. As CLOCK controls rhythmic synthesis of hepatic glycogen via transcriptional activation of Glycogen synthase 2 (Doi et al., 2010), it is worth noting that hepatic variations in glycogen content and Clock expression do not keep exactly the same phase-relationship according to feeding conditions, suggesting that rhythmic 88 expression of Glycogen synthase 2 is also controlled by transcriptional factors other than CLOCK. Second, diurnal expression of Rev-erbα in the liver was more phase-advanced (+3-5 h) by the 6-meals schedule, independent of the metabolic (iso- or hypocaloric) status of the mice. Rhythmic transcription of Clock being controlled by REV-ERBα (Crumbley and Burris, 2011), the smaller phase-advance of liver Clock oscillations than those of Rev-erbα raise the possibility of post-translational modifications delaying transcriptional activity of REV-ERBα. A daily hypocaloric meal also induces a phase-advanced hepatic expression of Rev-erbα (Feillet et al., 2006), suggesting that this common effect with ultradian feeding is unrelated to daily feeding signals, but may result from other cues (e.g., shifted metabolic or thermic cues; see below). Furthermore, an apparent ~4-h phase-advance of this gene has also been reported in voles fed according to an ultradian rhythm (one meal every 2.5 h; (van der Veen et al., 2006)). Previous reports showed that liver expression of Rev-erbα is downregulated by refeeding after overnight fasting (Oike et al., 2011; Tahara et al., 2011). This modulatory effect does not readily explain the observed pattern of Rev-erbα expression under 6-meal schedule, probably due to the short period of fasting (~4 h) between each food access). Together, these results indicate daily and ultradian feeding cues modulate the diurnal expression of Rev-erbα in the liver. Third, the 6-meals schedule (isocaloric group) lead to prominent phase-advances (+4 h) of Per2 expression in the liver, thus confirming previous data in PER2::LUC mice challenged with ultradian 6-meal feeding (Kuroda et al., 2012). An earlier rise of liver Per2 mRNA levels has also been reported in rats under 6-meal schedule (Cailotto et al., 2005a) as well as in mice challenged with work for food (van der Vinne et al., 2014). Oxyntomodulin released by the gut after food intake up-regulates Per2 expression in the liver (Landgraf et al., 2015). This modulatory effect could partly explain the dampened amplitude of hepatic expression of Per2 during 6-meal schedule, though it did not abolish the daily rhythmicity (as would be expected if oxyntomodulin was the sole factor involved because food intake would trigger Per2 transcription every 4 h, leading to constitutive levels throughout 24 h). The larger shift in the hypocaloric group (+7 h) is also in accordance with previous findings in PER2::LUC mice challenged with ultradian 6-meal feeding combined to caloric restriction (Kuroda et al., 2012). These results show that hepatic oscillations of Per2 are regulated not only by meal89 timing cues, but also by metabolic cues associated with a reduction in total energy intake. Among these cues, thermic signals due to phase-advanced body temperature (and deeper hypothermia in the case of ultradian hypocaloric feeding) may directly modulate liver expression of Per2 (Kornmann et al., 2007) which may, in turn, phase-advance the whole liver clock. Several metabolic genes in the liver are regulated by the molecular clock, such as Sirt1, Pparα, Pgc-1α and Fgf21. In turn, SIRT1 causes deacetylation and degradation of PER2 and modulates transcription of clock genes (such as Bmal1, Per2 and Cry1) due to NAD+ dependent protein deacetylase activity (Asher et al., 2008). SIRT1 also regulates Pparα expression (Purushotham et al., 2009) and interacts with Pgc-1α in the liver (Rodgers et al., 2005). The hepatic expression of these metabolic genes was affected by ultradian feeding. However, the precise changes (mean, phase and/or amplitude) markedly differ according to the genes, suggesting a combination of direct effects of 6-meal schedule conditions and modulation of phase-control by the liver clock (that was phase-advanced by ultradian feeding). Regarding Pgc-1α transcription, it was increased during 6-meals schedule in the isocaloric group, and even more in the hypocaloric group, confirming previous data in mice challenged with another hypocaloric condition without daily feeding cues (i.e., alternate days of fasting for 3 months; (Ranhotra, 2010)). Levels of Sirt1 mRNA levels tended to be increased in the hypocaloric group during ultradian feeding, an effect possibly linked to negative energy balance as up-regulated expression of Sirt1 is clearly observed in 24-h fasted mice (Hayashida et al., 2010). In addition, the phase of diurnal expression of Sirt1 and Pgc-1α in the mouse liver was not affected by ultradian feeding, suggesting some uncoupling with the liver clockwork. Hepatic expression of Pparα was globally down-regulated by the isocaloric 6-meals schedule in contrast to the fasting-induced up-regulation of this gene (Hayashida et al., 2010), indicating that the duration of fasting is a critical parameter for transactivation of this gene. Fgf21 expression is highly induced in the liver of mice fasted over 24 h (Lundasen et al., 2007). Here Fgf21 expression was also increased during the 6-meals schedule, without a positive correlation with Pparα, one of its transcriptional regulators (Lundasen et al., 2007; Oishi et al., 2008). Because FGF21 can be released in the bloodstream and act on the central clock (Bookout et al., 2013), we assayed plasma FGF21 in mice challenged with the ultradian 90 6-meal schedule. In spite of higher hepatic expression, plasma levels of FGF21 were not increased during ultradian feeding (data not shown). This suggests that the ~4-h duration of fasting between 2 meals during ultradian feeding was too short to allow FGF21 synthesis and/or release. In any case, these findings seem to rule out a critical role of FGF21 as a hepatokine that would convey temporal cues associated with ultradian feeding to the brain. Clock and clock-controlled proteins in the SCN In contrast to the high sensitivity of peripheral clocks to the synchronizing effects of meal time, the SCN clock remains synchronized to the light-dark cycle in food-restricted rodents fed during daytime (Damiola et al., 2000; Stokkan et al., 2001), leading to the current view that the SCN is insensitive to feeding cues. The present study challenges this concept by highlighting molecular changes in the SCN of mice fed with an ultradian feeding schedule. These changes, including up-regulated daily expression of the clock-controlled protein AVP and dampened oscillations of the two clock proteins PER1 and PER2, reveal that the daily alternation of feeding and fasting also participates in the normal functioning of the SCN. For AVP and PER2, the reducing effects of ultradian feeding on the amplitude of their oscillations were comparable between the isocaloric and hypocaloric groups, while the magnitude of the downregulation of PER1 was more pronounced in the hypocaloric group. Of note, ultradian feeding combined with hypocaloric conditions does not produce the same temporal alterations in the SCN as those observed after daily caloric restriction (i.e., phaseadvances in daily oscillations of PER1 and AVP, (Mendoza et al., 2007b); or non-significant increased oscillations of PER2, (van der Vinne et al., 2014)), suggesting that caloric restriction is able to shift the SCN clock only when it is combined with a timed daily feeding cue. The effects of ultradian feeding under hypocaloric conditions, however, led to phaseadvances of rest/activity rhythm comparable to those induced by daily caloric restriction (Mendoza et al., 2005) or by work for food (van der Vinne et al., 2014). This finding confirms that the behavioral phase-advances do not rely on the diurnal timing of a daily feeding cue (absent under ultradian feeding; (Mendoza et al., 2008b)) and suggests that the neural changes leading to a more diurnal temporal niche of activity under food shortage occur in SCN pathways downstream to the clockwork (e.g., transforming growth factor α or prokineticin 2 signaling) and/or its downstream structures (i.e., secondary brain clocks). 91 Common voles often display ultradian rhythms of rest-activity and feeding-fasting. Furthermore, the number of SCN cells containing AVP has been negatively correlated with robustness of circadian rhythmicity in this species (Gerkema et al., 1994). Our data actually suggest that in mice, ultradian feeding may trigger up-regulated levels of AVP in the SCN. Previous studies have already shown that daytime restricted feeding in rats modifies the daily pattern of AVP release from the SCN (i.e., delayed onset and earlier offset; (Kalsbeek et al., 1998)). Furthermore, daily caloric restriction also resulted in a phase-advance of the AVP rhythm in the SCN of mice fed at midday (Mendoza et al., 2007b). When vasopressin signalling is altered, interneuronal coupling and the daily amplitude of transcriptional activity in the SCN is compromised (e.g., (Li et al., 2009; Yamaguchi et al., 2013)). The weaker oscillations of AVP during ultradian feeding may thus feedback within the SCN to the molecular clockwork and participate in dampened SCN oscillations, as observed here for a reduced amplitude of PER1 and PER2 expression. AVP released from the SCN terminals modulates the daily timing of glucocorticoid secretion by the adrenal glands, via inhibitory effects in the dorsomedial hypothalamic nuclei and the sub-paraventricular hypothalamic region (Kalsbeek et al., 1996b). In mice fed according to the ultradian feeding schedule, the daily rhythm of plasma corticosterone is increased in amplitude and not shifted, while AVP protein expression is markedly increased. This apparent discrepancy raises the intriguing possibility that AVP in the SCN is actually synthesized, but not released as usual, in response to the 6-meal feeding schedule. In fact, a similar conclusion was drawn by the group of Gerkema because they showed that the increased levels of AVP in the SCN of arrhythmic voles are due to a decreased synaptic release of AVP (Jansen et al., 2000). To sum up, this study highlights that when the daily feeding rhythm is abolished by introducing an ultradian periodicity of food intake, SCN function and daily rhythmicity of clock and metabolic genes in the liver are modified, glucose arrhythmicity occurs and amplitude of corticosterone rhythm increases. The additional impact of hypocaloric conditions under ultradian feeding highlights specific changes (not dependent on daily feeding cues or overnight fasting), including phase-advances of rest/activity and body temperature rhythms, more marked reduction of PER1 in the SCN and modified gene 92 expression in the liver (e.g., larger shift of Per2 and up-regulated levels of Pgc-1α). Thus, not only the timing of feeding and fasting, but also metabolic cues associated with hypocaloric conditions may affect the central and peripheral clocks. ACKNOWLEDGEMENTS We thank Sylviane Gourmelen and Dr. Dominique Sage-Ciocca for their expert assistance with animal care and actimetry, respectively. 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Science. 342:85-90. 97 98 Chapter 3 An ultradian feeding schedule in rats differentially affects peripheral clocks in liver, brown adipose tissue and skeletal muscle and lipid metabolism, but not the central clock in SCN Paul de Goede‡1, Satish Sen‡1,3,4, Yan Su3, Ewout Foppen1, Vincent-Joseph Poirel5, Etienne Challet4, Andries Kalsbeek*1,2,3 ‡ 1 These authors contributed equally Laboratory of Endocrinology, Department of Clinical Chemistry, Academic Medical Center (AMC), University of Amsterdam, Amsterdam, The Netherlands. 2 Department of Endocrinology and Metabolism, Academic Medical Center (AMC), University of Amsterdam, Amsterdam, The Netherlands 3 Hypothalamic Integration Mechanisms group, Netherlands Institute for Neuroscience (NIN), Amsterdam, The Netherlands 4 Regulation of Circadian Clocks team, Institute of Cellular and Integrative Neurosciences, UPR3212, Centre National de la Recherche Scientifique (CNRS), University of Strasbourg, Strasbourg, France 5 Melatonin and seasonal rhythms team, Institute of Cellular and Integrative Neurosciences, UPR3212, Centre National de la Recherche Scientifique (CNRS), University of Strasbourg, Strasbourg, France * Corresponding address: Andries Kalsbeek, Hypothalamic Integration Mechanisms group, Netherlands Institute for Neuroscience (NIN), Amsterdam, The Netherlands E-mail: a.kalsbeek@nin.knaw.nl 99 Abstract Restricted feeding is well known to affect both core clock gene as well as metabolic gene expression profiles. However, it is not known whether the changes in metabolic gene expression result from the changes in the molecular clock or directly from the feeding behavior itself. Here we eliminated the daily rhythm in feeding behavior, but not that in locomotor activity, by giving animals 6 meals evenly distributed throughout the day (1 meal every 4 hours). Importantly, whilst on the 6-meals-a-day feeding regimen animals were not hypocaloric as they retained normal body temperature regulation and a continuous increase in body weight. Animals on the 6-meals-a-day feeding schedule also retained the normal day/night difference in physiological parameters such as body temperature, locomotor activity and heat production. The natural rhythm in RER, however, was blunted with the ultradian feeding behavior as a result of increased utilization of carbohydrates during the light- and lipids during the dark phase, respectively. The 6-meals-a-day feeding schedule without caloric restriction did not have a major impact on the SCN clock and clock controlled mRNA and protein expression rhythms. The results of the 6-meals-a-day feeding regimen clearly showed that feeding behavior is not the only regulator of the peripheral clocks in liver, skeletal muscle (SM) and brown adipose tissue (BAT). Despite the largely intact clock gene expression several genes involved in glucose and lipid metabolism showed differential expression profiles in these metabolically active peripheral tissues whilst on the 6-meal feeding schedule. Key metabolic genes such as Pdk4 were differently affected between these 3 tissue types. In summary, eliminating the daily rhythm in feeding behavior in rats without caloric restriction does not affect the SCN clock, but does disturb metabolic rhythms in liver, SM and BAT in a tissue-dependent manner. Thereby the absence of a clear daily rhythm in feeding activity results in a further desynchronization between the central clock in the brain and metabolically active tissues such as SM, BAT and liver. Keywords: Soleus Muscle (SM), Brown adipose tissue (BAT), liver, 6-meal feeding. 100 1. Introduction Daily recurring biological events of the mammalian behavioral system such as the sleepwake, feeding-fasting and rest-activity cycles are under the control of the master or central clock. The central clock, located in the suprachiasmatic nucleus (SCN), is an endogenous pacemaker located in the anterior hypothalamus of the brain. This central pacemaker controls and coordinates peripheral clocks in the brain and virtually every other tissue in the body through neural, humoral and behavioral rhythms and subsequently also regulates bodily rhythms in metabolism (Reppert and Weaver, 2002; Hastings et al., 2003; Bray and Young, 2009; Dibner et al., 2010). The molecular mechanism underlying the generation of these daily rhythms involves a set of clock genes forming transcriptional and (post-)translational feedback circuits (Shearman et al., 2000; Reppert and Weaver, 2001; Ko and Takahashi, 2006). The positive limb of this molecular clock consists of the core clock elements BMAL1 and CLOCK. Heterodimerization of these core clock elements drives transcription of the Period (Per1, Per2, and Per3) and Cryptochrome genes (Cry1 and Cry2) (Gekakis et al., 1998; Hogenesch et al., 1998; Jin et al., 1999; Kume et al., 1999). The protein isoforms of PER and CRY act as negative components in the feedback loop that inhibit their own transcription (Ramsey et al., 2007). An auxiliary loop which is also induced by CLOCK:BMAL1 heterodimerization activates transcription of Rev-erbα and Rorα. In turn, REV-ERBα represses whilst RORα activates the transcription of Bmal1 and Clock (Preitner et al., 2002; Sato et al., 2004; Triqueneaux et al., 2004; Akashi and Takumi, 2005; Guillaumond et al., 2005). The daily rhythm produced by this molecular clock mechanism has a period of approx. 24-hours (i.e., circadian) and is entrained to the exact 24-hour rhythm of the outside world by environmental light. The molecular clock uses clock-controlled genes such as DBP as well as other transcription factors as an output to regulate a wide variety of cellular processes, of which many involve metabolic processes (Eckel-Mahan and Sassone-Corsi, 2013; Marcheva et al., 2013). As such, the biological clock plays a major role in metabolism, on a whole body level, but also on a tissue/cellular level. Disturbing the biological clock, for example by performing shift work, thus can be expected to have detrimental effects on the regulation of metabolism. Indeed, shift work in humans as well as animal models of shift work show disturbances in metabolism and increased risks of 101 metabolic disorders such as type 2 diabetes (T2DM) (e.g. (Scheer et al., 2009; Arble et al., 2010; Barclay et al., 2012; Opperhuizen et al., 2015; Morris et al., 2016). The exact mechanisms that lead from shift-work and disturbing the normal circadian behavior to these metabolic disorders are not fully understood, but there is a likely role for erratic eating patterns. As a result of the disturbed clock mechanisms, metabolic substrate availability and demand may be out of balance and this imbalance will eventually result in metabolic diseases. Changes in feeding behavior are well known to affect peripheral clocks (Damiola et al., 2000; Stokkan et al., 2001; Opperhuizen et al., 2016; de Goede P, 2018). An often used paradigm to study the effects of food intake on metabolism and the circadian clock mechanism is timerestricted feeding (TRF), during which animals are allowed to eat only during a restricted period of the 24-hour day, e.g. only during the active or inactive phase. TRF to the inactive phase is often linked with negative effects on health and metabolism, whilst TRF to the active phase is linked to positive effects (Manoogian and Panda, 2017). Many studies, including several from our own group, have found that both core clock genes as well as metabolic genes are clearly affected by TRF in metabolically active tissues such as BAT, WAT, SM and liver (Damiola et al., 2000; Hatori et al., 2012; Reznick et al., 2013; Dyar et al., 2015; Opperhuizen et al., 2016; de Goede P, 2018). Unfortunately, as the metabolic genes are often controlled by the biological clock, it is difficult to identify whether the changes in metabolic gene expression upon TRF are caused by the altered feeding behavior itself or by the feedinginduced changes in the molecular clock mechanism. To disentangle the effects of the daily rhythm in feeding behavior on rhythms in metabolic gene expression in the SCN and various peripheral tissues such as liver, SM and BAT, from those of the endogenous molecular clock, we eliminated the daily rhythm in feeding behavior. To accomplish this, we used the 6-mealsa-day feeding paradigm. In this paradigm animals have access to food 6 times a day, spread evenly across the day, i.e., one meal every 4 hours, for a short period of time (generally 11-14 minutes). This well-established paradigm forces the animals to eat similar amounts of food in each of the 6 sessions of food availability, thereby eliminating the natural day/night difference in food intake (Kalsbeek and Strubbe, 1998; Su et al., 2016a). In mice six-meals-a-day feeding alters rhythms in behavior such as locomotor activity and body temperature, but also changes gene expression profiles in peripheral tissues such as WAT and liver (Mendoza et al., 2008b; Kuroda et al., 2012; Su et al., 2016a; Sen et al., 2017). Furthermore, 6-meals-a-day 102 feeding combined with caloric restriction also affects the central clock in the mouse SCN (Mendoza et al., 2007a; Sen et al., 2017). To better characterize the effects of the 6-meals-aday feeding regimen on metabolism, we placed rats in metabolic cages where we measured several physiological parameters, including RER, body temperature and locomotor activity, whilst remaining on the 6-meals-a-day feeding schedule. Additionally, we investigated changes in daily mRNA and protein expression profiles in the SCN as well as mRNA expression profiles in metabolically active peripheral tissues: liver, BAT and SM. Our results indicate that whilst locomotor activity and body temperature rhythms are largely unchanged, RER and peripheral gene expression profiles of animals on the 6-meals-a-day feeding regimen are clearly affected. Interestingly, 6-meals-a-day feeding in rats did not affect the SCN clock and clock controlled protein expression at either the transcriptional or translational level. Furthermore, the effects of ultradian feeding were different for the 3 peripheral tissues investigated here: BAT, SM and liver. Clearly, this differential effect of feeding behavior on the different clocks may result in desynchronization between the central and peripheral clocks as well as between the peripheral clocks themselves and thus likely results in a metabolic imbalance. 2. Materials & Methods 2.1 Animal experiments Sixty four male Wistar rats were housed under 12:12 light:dark conditions for the entire experiment, with Zeitgeber time (ZT) 0 being the time of lights on and ZT12 being the time of lights off. Animals only received chow food. Animals were habituated to the 6-meals-aday feeding regimen by having access to their food bin 6 times a day, temporally spaced equally over the 24h light/dark (L/D)-cycle once every 4 hours. In this way there were three feeding opportunities (i.e., meals) during the light period at ZT2, ZT6 and ZT10, each meal consisting of 12 minutes of food access and three feeding opportunities during the dark period at ZT14, ZT18, and ZT22 each consisting of 11 minutes of food access, as the animals eat at a slightly higher pace during the dark period. All rats learned within two weeks to eat equal amounts of food in the light and dark period under this feeding regimen. Animals in the control group under ad libitum conditions had free access to food 24h/day. After 4 weeks, a subset of animals from both the 6-meal schedule (n=15) and the ad libitum group (n=16) were 103 placed individually in metabolic cages during 4 days in order to measure several physiological and metabolic parameters, whilst remaining on their assigned feeding conditions. After 6 weeks, the rats were sacrificed at ZT2, ZT8, ZT14 or ZT20 and soleus muscle, liver and BAT tissues were carefully collected, snap frozen in liquid nitrogen and stored at -80 °C until RNA isolation was performed. Brain tissue was collected from two independent experiments with identical experimental procedures. This way we could store brain tissue both freshly frozen for use with in situ hybridization as well as store brain tissue post-fixed with paraformaldehyde for immunohistochemistry (IHC). Liver tissue and frozen brain tissue came from one set of animals (n=33), soleus muscle, BAT, PFA fixed brain tissue and metabolic measurements came from the other set of animals (n=31). 2.2 Activity and respirometry Metabolic PhenoCages (TSE systems) were used to measure several metabolic parameters, whilst animals remained on their ad libitum or 6-meals-a-day feeding schedule conditions. Animals were individually housed in these cages. After a day of acclimatization to this new environment, the parameters for food intake, locomotor activity, respiratory exchange ratio (RER) and heat production were measured for three consecutive days (72 hours). 2.3 Body temperature In a subset of animals from both groups a temperature logger (DST nano-T, STAR ODDI) was placed subcutaneously during a short anesthesia. After a recovery period of 9 days body temperature was measured every 15 minutes for three consecutive days. 2.4 RNA isolation Soleus muscle tissue was mechanically homogenized while kept on dry ice. The BAT tissue and liver were crushed in Trizol by using a homogenizer machine. For all the tissues, RNA isolation was done using the NucleoSpin RNA isolation kit (Machery-Nagel). For muscle RNA isolation, three additional washing steps with 75% ethanol were performed. RNA was eluted from the spin column using 40μl of H2O and RNA concentration and quality of the RNA were determined using a DS-11 (DeNovix) spectrophotometer and a nanochip using 104 Agilent 2100 Bioanalyzer (Agilent Technologies), respectively. Although RNA integrity number (RIN) values above 5 were considered acceptable, all samples had a RIN above 8. 2.5 Muscle, BAT, and liver cDNA synthesis Two hundred ng from both muscle and liver, 350 ng from BAT of isolated RNA were used as input template for cDNA synthesis. The Transcriptor First Strand cDNA synthesis kit (Roche) was used with oligo-dT primers (30 min at 55°C, 5 min at 85°C and an additional sample without reverse transcriptase (-RT) was used as negative control to check for genomic DNA contamination during the RT-qPCRs. RT-PCRs were run using an UNO-Thermoblock (Biometra). 2.6 RT-qPCR One to nineteen (1:19) diluted cDNA was used for all qPCRs to detect muscle, BAT and liver gene expression profiles. Expression levels of all genes were standardized by dividing over the geometric mean of two or three housekeeping genes: TBP, GAPDH and Cyclophilin for muscle; TBP, HPRT1 and GAPDH for BAT and HPRT and GAPDH for liver. RT-qPCR was performed using a LightCycler 480 (Roche). Different housekeeping genes were used for the different tissues as feeding rhythms are known to affect commonly used housekeeping genes in a tissue-dependent manner and thus need to be tested for each different tissue to determine their suitability (Nakao et al., 2017). Expression levels were calculated using dedicated software for linear regression of qPCR data (LinRegPCR). All used primers are listed in Table S1. Melting curves of the RT-qPCR and fragment length of the DNA amplicons were inspected as a means of quality control. Liver clock gene expression data were replotted from a previous study (Su et al., 2016b), but this time using the cosinor representation. 2.7 In situ hybridization: After decapitation fresh brains were stored in -80°C before cryo-sectioning was performed. The transverse sections (20μm) covering the rostro-caudal axis to the SCN were cut and collected on frosted slides without gelatin coating in series of 6 sections. Slides were stored at -20°C until experiments were performed. Antisense and sense RNA probes were generated with an in vitro transcription kit (Maxiscript, Ambion, Austin TX, USA). Here we used 105 riboprobes of rPer1, rPer2 (plasmids kindly provided by Dr H.Okamura, University of Kyoto, Japan) and rAvp (Dardente et al., 2004). Hybridization was performed following the protocol described previously (Tournier et al., 2003). Slides along with a radioactive standard were exposed for 3 days for Avp and 5 days for Per1 and Per2 to an autographic film (Biomax MR Kodak). Standards were included in each cassette to verify that the measured values of optical densities were in the linear response range of the film. Densitometric analysis of hybridization signals was performed with a computerized analysis system (Biocom RAG200, Les Ulis France). The optical density of a specific signal was calculated by subtracting the intensity of staining background area measured in an area above the SCN. Measures were taken from the bilateral SCN on five consecutive slices and averaged for the given brain and particular ZT for both feeding conditions. Data were expressed as relative optical density values. 2.8 Immunohistochemistry After decapitation brains were dissected and post fixed in 4% paraformaldehyde for 24 hr in a 4°C cold room. Following the 24 hr post fixation the brain tissue was transferred again to fresh 4% paraformaldehyde for the next 48 hr followed by cryoprotection in 30% sucrose solution in a 4°C cold room until sectioning was performed. Five series of 30 μm coronal SCN sections were prepared on a cryostat and collected in the cryoprotectant and washed with 1× Tris Buffer Saline pH 7.6 (0.1 M TBS). Subsequently, sections were incubated in 3% H2O2 in TBS (30 min) to suppress endogenous peroxidase activity, thereby reducing background staining. Again brain sections were rinsed in TBS. Brain sections were then transferred in a solution containing 10% normal serum goat according to the host species of the primary antibody) and Triton X-100 (0.1 %) in TBS for 2 h, followed by incubation in the primary antibody (24 h at 4°C). We used rabbit polyclonal anti arginine-vasopressin (AVP) (1:8000, Truus, a gift from Dr. Ruud Buijs, Netherlands Institute for Brain Research, Amsterdam, The Netherlands). The sections were washed in TBS, then incubated (2 h at 4°C) with biotinylated goat anti-rabbit IgG (1:500, PK6101; Vectastain Standard Elite ABC Kit Vector Laboratories, Inc., Burlingame, CA, USA) for AVP immunostaining. After this, sections were rinsed in TBS and incubated (2 h) in a solution containing avidin–biotin peroxidase complex (Vectastain Elite ABC kit; Vector Laboratories Inc.). Following 106 incubation with ABC reagents, sections were rinsed 4 times in PBS, and incubated with H2O2 (0.015%, Sigma-Aldrich, St Louis, MO, USA) and 3,3’-diaminobenzidine tetrahydrochloride (0.5 mg/ml, Sigma-Aldrich) diluted in water. Thereafter, sections were rinsed with TBS, wet mounted on slides coated with gelatin, dehydrated through a series of alcohols, soaked in xylene, and cover slipped. Photomicrographs were taken on a Leica DMRB microscope (Leica Microsystems) with an Olympus DP50 digital camera (Olympus France). The number of immune-positive cells was counted on one medial section in both SCN’s and averaged. 2.9 Statistics All data are presented as means ± SEM. Daily rhythmicity of gene and protein expression profiles were assessed using cosinor analysis determining mean, amplitude and acrophase of the considered measures with SigmaPlot 13 software (SPSS Inc, Chicago, IL). Data were fitted to the following regression: y = A + B·cos(2π(x − C)/24), where A is the mean level, B the amplitude and C the acrophase of the rhythm. Statistical analysis for t-tests, one-way and two-way ANOVAs, as well as Fisher LSD method post-hoc analysis were also executed by SigmaPlot 13 software. Two-way analyses of variance (ANOVA) were performed to assess the effect of Feeding (food ad libitum and 6-meals-a-day feeding) and Time (time of the day) and the Interaction between these factors. 3. Results 3.1 Caloric intake and body weight gain Daily caloric intake was lower for the 6-meal group as compared to the ad libitum fed group (18.1g and 22.4g per day, respectively; independent t-test, n=15-16 per group, p<0.0001). Importantly, the L/D difference of food intake seen in ad libitum fed animals (73% of food intake during the dark phase; paired t-test, p<0.0001) was abolished in the 6-meal group (52% of food intake during the dark phase; paired t-test, p=0.075). Food intake was also not different between the 6 different feeding opportunities in the 6-meal group (one-way RMANOVA, p=0.13). Body weight gain after 6 weeks was lower for the 6-meal group as compared to the ad libitum fed group (146.1g and 102.2g, respectively; independent t-test, n=20 per group, p<0.0001). However, all animals in the 6-meal group continued to gain weight throughout the experiment (Fig. 1). 107 FIGURE 1. Analysis of the daily food intake and body weight of the animals. (A) Difference in daily food intake between light and dark phase for the ad libitum and 6M fed animals. (B) Average 24 hour food intake for both groups of animals. (C) Weekly body weight growth curve for both groups of animals. (D) Body weight at time of sacrifice (left) and absolute body weight gain during the experiment (right) for both groups of animals. Data are depicted as means ± SEM. ns=non significant, **=p<0.01, ****=p<0.0001, n=20 per group. ad lib= ad libitum fed animals (black lines and bars), 6M=animals fed according to the 6 meals a day feeding regimen (grey lines and bars). 3.2 RER The daily pattern of RER was altered in the 6-meal group, not showing a clear L/D difference alike the ad libitum group, but instead 6 peaks in RER throughout the day (Fig. 2a). These 6 peaks in RER clearly followed upon the access to food for the 6-meals-a-day group (dotted vertical lines). Further analysis showed that there was a significant L/D difference in RER in the ad libitum (paired t-test, p<0.001), but not in the 6-meal animals (paired t-test, p=0.354) (Fig. 2b). This difference between ad libitum and the 6-meals-a-day animals is partly explained by a phase-advance of the daily RER rhythm, because cosinor analysis showed a significant phase-advance of the acrophase (~ZT20 vs. ZT10; p<0.001) (Table S2). The average 24h RER did not differ between the ad libitum and 6 meal groups (unpaired t-test, p=0.0581) (Fig. 2c). Two-way ANOVA showed significant effects of Time as well as Interaction (two way RM-ANOVA; Feeding p=0.055, L/D p=0.008 and Feeding*L/D p<0.001). 108 3.3 Locomotor activity The daily pattern of locomotor activity for the 6-meal group was very similar to that of the ad libitum group, showing a clear L/D difference, although the 6-meal group also showed 6 peaks in activity over 24 hours (Fig. 2a). These 6 peaks in locomotor activity mostly followed the access to food for the 6-meal group (dotted vertical lines). Importantly, two-way RMANOVA showed that locomotor activity was significantly different between the light and dark period in both ad libitum and 6-meal groups, although the significant interaction indicated that this difference was smaller in the 6 meals-a-day group (L/D, p<0.001; Feeding*L/D, p=0.016). A paired t-test confirmed the significant effects of L/D in both the ad libitum and 6-meal group (p<0.001 for both groups), with higher locomotor activity during the dark period in both groups (Fig. 2b). Cosinor analysis revealed a significant difference in acrophase (2 hours) and amplitude of the locomotor activity rhythm between ad libitum and 6-meals-a-day feeding, again confirming the larger day/night difference seen in ad libitum animals (p<0.001 and p=0.02, respectively) (Table S2). Total locomotor activity per 24 hour did not differ between ad libitum and the 6 meals-a-day fed rats (independent t-test, p=0.538) (Fig. 2c). Two-way RM-ANOVA again confirmed that locomotor activity per 24 hour was not different between ad libitum and 6-meals-a-day fed groups (Feeding, p=0.609). 3.4 Heat production The daily pattern of heat production for the 6-meals-a-day group was similar to the ad libitum group, showing a clear L/D difference, although the 6-meals-a-day group had 6 clear peaks in heat production throughout the day (Fig. 2a). These 6 peaks in heat production were very similar to the peaks in locomotor activity. A subsequent paired t-test revealed a statistically significant effect of L/D on heat production in both ad libitum and 6-meals-a-day fed rats (p<0.001), although again with a somewhat smaller amplitude in the 6-meals-a-day animals (Fig. 2b). Additionally, the cosinor analysis showed significant differences in the acrophase (2.2 hours) and amplitude of heat production between ad libitum and 6-meal feeding (p<0.001 and p<0.001, respectively) (Table S2). Heat production per 24 hour did not differ between ad libitum and 6 meals-a-day fed rats (p=0.136) (Fig. 2c). Two-way RM-ANOVA showed a significant effect of Time (p<0.001) and Feeding*Time (p<0.001), but no effect of Feeding (p=0.165). 109 FIGURE 2. Analysis of the metabolic parameters RER, locomotor activity, heat production and subcutaneous body temperature (from left to right respectively) of the animals inside the metabolic cages. Whilst in the metabolic cages animals remained on their assigned feeding regimen. (A) 24 hour traces of the metabolic parameters, averaged per group. The timing of the meal for the 6M group are indicated along the x-axis. (B) Difference within metabolic parameters between light and dark phase for the ad libitum and 6M fed animals. (C) Average 24 hour values of the metabolic parameters for both groups of animals. Data are depicted as means ± SEM. ns = non-significant, ****=p<0.0001, n=15-16 per group, except for subcutaneous body temperature (n=3-5 per group). Locomotor activity is presented as arbitrary units (AU). ad lib= ad libitum fed animals (black lines and bars), 6M = animals fed according to the 6 meals a day feeding regimen (grey lines and bars). Shaded areas represent the dark phase. 3.5 Body temperature The daily pattern of body temperature for the 6-meals-a-day group was very similar to that of the ad libitum group, showing a clear L/D difference (Fig. 2a). Importantly, there were significant differences between the light and dark period, but there was no interaction between Feeding and Time, nor a main effect of Feeding (Feeding, p=0.214; Time, p=0.0003; Feeding*Time, p=0.787; Two-way RM-ANOVA). Cosinor analysis further revealed that there were no significant differences in amplitude or acrophase between the two groups (Table S2). As already confirmed by the two-way RM-ANOVA, total body temperature per 110 24 hour did not differ between ad libitum and 6 meals-a-day fed rats (independent t-test, p=0.214) (Fig. 2c). 3.6 Clock and clock-controlled gene expression in the SCN The daily pattern of Per1 and Per2 mRNA expression in the SCN was measured under both ad libitum and 6-meals-a-day feeding conditions. Two-way ANOVA analysis showed a significant effect of Time for both Per1 and Per2 (p<0.001). Cosinor analysis confirmed the rhythmicity of both clock genes (Fig. 3a,b). Both genes maintained a significant rhythm irrespective of feeding conditions with no significant changes in mean, amplitude or acrophase for any of the two genes. The mRNA expression of Avp, a clock controlled gene, was also examined in the SCN of the ad libitum and 6-meals-a-day feeding groups (Fig. 3c). Two-way ANOVA showed no significant effects of Time or Feeding (Table S4). The cosinor analysis detected a significant rhythm in the 6-meals-a-day (p=0.045), but not in the ad libitum (p=0.313) group. Also AVP protein expression in the SCN was measured by counting the number of immunepositive cells in the SCN of rats under ad libitum and 6-meals-a-day feeding conditions. Twoway ANOVA showed a significant effect of Time (p<0.001). However, cosinor analysis detected no significant rhythmicity in either the 6-meals-a-day or ad libitum groups (p=0.139, and p=0.054, respectively; Fig. 3d). 3.7 Clock gene expression in soleus muscle All clock genes tested (Bmal1, Per1, Per2, Cry1, Cry2, Rev-erbα and Dbp) (Fig. 4A-H, Table 2; cosinor analysis) showed a significant rhythmic expression in the ad libitum fed group except Cry2. Eliminating the daily rhythm in feeding behavior with the 6-meals-a-day schedule resulted in a loss of rhythmicity for Per1, while Cry2 remained non rhythmic in both the feeding groups. A ~1.5 hour shift was observed in Dbp expression, but no other significant changes in mean level or amplitude were observed in the 6-meals-a-day feeding groups (Table 2). Two-way ANOVA analysis showed no significant effect of Feeding for any of the clock genes, but showed a significant effect of Time (p<0.001) for all clock genes 111 except Cry2. A significant interaction between Time and Feeding was found for Per2, Reverbα and Dbp (Table 1). FIGURE 3. Daily profiles of clock and clock-controlled genes and clock-controlled protein expression in the SCN of fed ad libitum (Black circle), 6-meal feeding (Gray triangle) groups. (A) Per1 expression; (B) Per2 expression; (C) Avp expression (D) AVP protein expression Fitted lines show significant cosine regressions (see methods). ~ effect of time of day (p < 0.05). 3.8 Metabolic genes in soleus muscle Both Pdk4 and Ucp3 showed a shift in peak expression when subjected to the 6-meals-a-day feeding regimen as compared to ad libitum. For both genes this shift was in the same direction and of roughly the same magnitude (Figs. 5I & 5K, Table 2). On the other hand, Pgc-1β expression lost rhythmicity under the 6-meal feeding regimen (data not shown). Most of the other metabolic genes studied did not show rhythmicity in either of the feeding conditions except for Srebp1c that lost rhythmicity upon 6-meals-a-day feeding. Pgc1α gained rhythmicity upon 6-meals-a-day feeding (Table 2). Furthermore, two-way ANOVA analysis showed a significant effect of Time for several metabolic genes in soleus muscle 112 (Ucp3, Pgc1α, Pdk4, Srebp1c and Sirt3). No significant effect of Feeding or Interaction was observed for any of the metabolic genes in soleus muscle (Table 1). 3.9 Clock gene expression in BAT All tested clock genes in BAT remained rhythmic in the 6-meals-a-day group (Fig. 4, Table 3). Two-way ANOVA showed a significant effect of Time for Bmal1, Cry1, Per2, Dbp and Reverbα. No significant effects of Feeding were found for any of the clock genes studied except for Cry1. A significant Interaction effect for Time and Feeding was found for Bmal1 and Dbp expression (p<0.001). Cosinor analysis revealed no shift in expression for any of the clock genes when comparing ad libitum with 6-meals-a-day feeding except for Bmal1 (1.9 hours; Table 3). 3.10 Metabolic genes in BAT Cosinor analysis showed loss of rhythmicity for the lipid metabolizing genes such as Pgc-1α, Lpl and Srebp1c during 6-meals-a-day feeding, whilst other genes like Ucp1, Glut4, Pparα, Hsl1 were not rhythmically expressed in either of the two feeding conditions (Fig. 5, Table 3). Interestingly, Pdk4, Fas and Fgf21 gained rhythmicity in the 6-meals-a-day fed group as compared to the ad libitum group. Two-way ANOVA showed that in most of the tested metabolic genes, no effect of Time was found, except for Lpl, Pdk4, Ucp1, Sirt3, Fas, and Fgf21. No significant effect of Feeding and Interaction was found for any of the tested metabolic genes in BAT (Table 1). 3.11 Clock gene expression in Liver All studied clock genes in the liver remained rhythmic in the 6-meals-a-day feeding conditions, except for Cry2. In addition, no significant phase changes were observed except for Rev-erbα (1.9 hours; p=0.005). Mean expression levels were affected for Bmal1 and Cry1 and the amplitude was dampened for Bmal1, Cry1, Per2 and Rev-erbα (Table 4). Two-way ANOVA showed an effect of Feeding for Bmal1 and Cry1 (p=0.008 and P<0.001, respectively). Additionally, a significant effect of Time was found for all the studied clock genes as well as an Interaction for Cry1, Per2, and Rev-erbα (Table 1). 113 3.12 Metabolic genes in Liver Cosinor analysis of the metabolic genes tested in the liver showed that upon 6-meals-a-day feeding Glut2 and Fas remained rhythmic. A large phase shift was observed in Fas expression upon 6-meal feeding (8.4 hours; p=0.001). Pdk4 and Fgf21 lost rhythmicity, but Lpl and Srebp1c gained rhythmicity. The other metabolic genes tested (Pparα, Pgc-1α, Hsl and Sirt1) were not rhythmic in either condition (Table 4). Two-way ANOVA analysis showed a significant effect of Time for Glut2, Pdk4, Lpl, Fas, and Fgf21. There was no significant effect of Feeding, however, there was a significant Interaction effect for Fas (Table 1). FIGURE 4. Daily profiles of clock and metabolic genes expression in Liver, Muscle and BAT in animals fed ad libitum (Black circle), 6-meal feeding (Gray triangle) groups. (A) Bmal1, (B) Cry1, (C) Cry2 (D) Per1, (E) Per2, (F) Rev-erbα, (G) Dbp. Fitted lines show significant cosine regressions (see methods). ~ effect of time of day (p < 0.05), # effect of feeding (p < 0.05) and x interaction between feeding and time of day (p < 0.05). 114 4. Discussion Many studies have investigated the effects of time restricted feeding (TRF) on energy metabolism by focusing on (clock) gene expression in liver, skeletal muscle, BAT and WAT (Salgado-Delgado et al., 2010; Hatori et al., 2012; Reznick et al., 2013). Since in these studies clock gene expression profiles were strongly affected by TRF, it was not possible to determine whether the changes in the expression profiles of metabolic genes were driven by the altered rhythms in feeding behavior itself or the altered clock gene expression. Additionally, in these studies the animals were fasted for 10-14 hours a day which might also affect metabolism independently of the altered rhythm in feeding behavior. Moreover, disturbed feeding rhythms in humans, including those of shift workers, usually are not characterized by a complete shift of the feeding rhythm, but instead by a more widespread distribution of small “meals” throughout the 24-hour day (Panda et al.). Here we for the first time reported the disruptive effects of an equidistant 6-meals-a-day feeding pattern in rats on SCN, muscle and BAT gene expression rhythms, as well as on several physiological parameters including body temperature, locomotor activity, heat production and RER. This ultradian feeding pattern mainly affected daily rhythms in RER and lipid metabolism, while leaving daily rhythms in clock gene expression, locomotor activity and body temperature relatively intact. Abolishing the daily feeding-fasting cycle with an ultradian 6-meals-a-day feeding schedule (1 meal every 4 hours) without caloric restriction did not affect the SCN clock, and only slightly affected peripheral clock gene expression rhythms in liver, BAT, and SM with small changes in acrophase, mesor and amplitude levels for some clock genes in a tissue and gene dependent manner. On a whole body level minor changes in the daily rhythms in locomotor activity, heat production and body temperature were found, but the daily rhythm in RER was severely disturbed in the animals on the 6-meals-a-day feeding schedule. Additionally, eating according to the 6-meals-a-day schedule gave rise to disturbances in lipid metabolism in liver, BAT and SM. Hence in rats 6-meals-a-day feeding without caloric restriction does not severely impact the molecular clock, but does abolish the daily rhythmicity of the respiratory quotient, i.e., metabolic flexibility. 115 FIGURE 5. Daily profiles of metabolic genes expression in Liver, Muscle and BAT in animals fed ad libitum (Black circle), 6-meal feeding (Gray triangle) groups. (A) Srebp1c, (B) Hsl, (C) Lpl (D) Fas, (E) Pgc-1α, (F) Pparα, (G) Sirt1 and Sirt3, (H) Glut2 and Glut4, (I) Pdk4, (J) Fgf21 (K) Ucp3 and Ucp1. Fitted lines show significant cosine regressions (see methods). ~ effect of time of day (p < 0.05). 116 4.1 Rhythms in feeding behavior affect whole body metabolism To successfully eliminate the daily rhythm in feeding behavior we reduced the time of food access and rats could eat approx. 1.3 hours each day evenly spread across the 24 hour period. An important issue that arises with this experimental design, especially when investigating metabolism, is that the experimental group eats less and potentially becomes hypocaloric (i.e., losing or not gaining body weight). Importantly, although in our experiments the animals on the 6-meal regimen eat less compared to the ad libitum conditions they are not under hypocaloric conditions as they continuously gained weight throughout the experiment, although at the end of the experiment body weight was slightly lower when compared to ad libitum conditions. This is similar to what was observed in previous studies using the 6meals-a-day feeding schedule in rats (Mendoza et al., 2008b; Su et al., 2016a). Contrasting, in mice most of the animals lost weight during such an ultradian 6-meals-a-day feeding regimen (Sen et al., 2017). Additionally, during our experiments the persisting daily patterns in body temperature indicated that the 6-meals-a-day fed animals still are able to control their body temperature at normal levels, again indicating that these animals are not in a hypometabolic condition (Mendoza et al., 2008b). During the 6-meals-a-day feeding regimen, the animals largely maintained the day-night rhythm in locomotor activity that is often lost or even inverted to the inactive phase during light phase TRF (de Goede P, 2018). Despite a small shift in acrophase, rats maintained the normal day-night pattern of locomotor activity even when they are forced to eat during their resting phase, which is consistent with a previous report of 6-meals-a-day feeding in rats (Mendoza et al., 2008b), while daytime restricted feeding coupled to caloric restriction in rats phase advances the locomotor activity rhythm (Challet et al., 1997a). Rats in the present 6meals-a-day feeding study did not show any anticipatory activity prior to meal access, but a sudden rise in activity was observed during each meal access, especially during the light period. It is known that the SCN controls the daily rhythm in locomotor activity. Since there was no effect of the 6-meals-a-day feeding schedule on the SCN clock, it is not surprising the animals maintained their regular day-night pattern of locomotor activity. However, ultradian feeding combined with caloric restriction can affect the SCN clock. For example, alterations in the SCN clock together with changes in locomotor activity were found in both rats 117 (Mendoza et al., 2008b) and mice (Sen et al., 2017) subjected to a hypocaloric diet with ultradian 6-meals-a-day feeding. The daily RER pattern in the 6-meals-a-day feeding rats did not show the alterations previously observed during daytime TRF (Reznick et al., 2013; de Goede P, 2018). In both conditions the daily RER rhythm showed a profound shift, but in the daytime TRF condition its amplitude was enhanced whereas in the 6-meals-a-day feeding condition its amplitude was reduced. This indicates the length of the daily fasting period may be an important determinant of the daily rhythm in RER, with TRF the length of this daily fasting period is increased, whereas with the 6-meals-a-day feeding schedule it is reduced. Heat production in 6-meals-a-day feeding rats showed a sudden rise in heat production during each meal access, especially during the light period. This rise in heat production during each meal may be due to meal induced thermogenesis, but it is also strongly correlated to the rise in locomotor activity during each meal access. As 6-meals-a-day fed rats had to be active (i.e., not be asleep) during every meal opportunity in order to obtain a sufficient amount of chow, this gives to a sudden rise in locomotor activity during each meal opportunity. Inherently, this paradigm also could potentially alter the sleep/wake cycles of the animals, but this remains to be tested. 4.2 Ultradian rhythms in feeding behavior do not affect the central SCN clock The SCN clock synchronizes the other peripheral clocks of the body. Time-restricted feeding entrains the peripheral clocks but not the SCN clock. Intriguingly, restricted feeding coupled to caloric restriction does shift the SCN clock in mice and also ultradian feeding coupled with caloric restriction alters in mice the clock controlled protein AVP in the SCN and down regulates some clock proteins (Sen et al., 2017). Here, 6-meal feeding in rats did not affect the SCN clock at either the transcriptional or translational level and these findings are consistent with previous behavioral data in 6-meal fed rats (Mendoza et al., 2008b) and other (timerestricted) feeding paradigms (Stokkan et al., 2001) In the present study the 6-meals-a-day feeding paradigm was not coupled with caloric restriction, it seems likely that only when the 6-meals-a-day feeding paradigm is combined with caloric restriction it will alter the SCN clock (Mendoza et al., 2005; Mendoza et al., 2007a; Sen et al., 2017). 118 4.3 Rhythms in feeding behavior do not dictate peripheral clocks Peripheral clocks were affected by the 6-meals-a-day feeding paradigm in a tissue-dependent as well as a clock gene dependent manner. For example, rhythmic expression of Per1 in SM and Cry2 in liver was lost under the 6-meals-a-day regimen, whilst Dbp in BAT showed a strong reduction in the amplitude of its rhythmic expression (Fig. 3). However, most clock genes in liver, SM and BAT remained rhythmic under the 6-meals-a-day feeding regimen, clearly indicating that the daily feeding-fasting rhythm is not the only regulator of peripheral clock gene expression. Likely the central pacemaker in the SCN, which was found not to be not affected by the 6-meals-a-day regimen (Fig. 2), also plays a role in the persisting rhythms of these peripheral clocks. Most of the clock genes tested in peripheral tissues, except for Dbp (muscle), Bmal1 (BAT) and Rev-erbα (liver) showed no phase changes which is consistent with the previously reported effect of 6-meals-a-day feeding on the liver (Cailotto et al., 2005b; Kuroda et al., 2012) and eWat (Su et al., 2016a). This implies that without clear day/night difference in food intake the phase of peripheral clock gene expression is not necessarily affected. Contrasting, it has been shown recently that changes in the lighting conditions do affect the phase of clock gene expression in the liver when combined with 6meals-a-day feeding (Ikeda et al., 2015). As rhythms in feeding behavior do not seem to be the only factor dictating daily rhythms in peripheral clock gene expression, clearly other factors such as body temperature, locomotor activity and the corticosterone and melatonin rhythm, which were still found to be rhythmic under the 6-meals-a-day regimen, likely also play a role. These results seem to contradict experiments using TRF paradigms to study the influence of feeding behavior on peripheral clock gene expression, including experiments by our own group (Reznick et al., 2013; Dyar et al., 2015; Opperhuizen et al., 2016). Rats that could only feed themselves during the light (inactive) phase lost rhythmic expression for all tested clock genes in muscle, shifted acrophases for all tested clock genes in BAT and showed almost complete anti-phasic expression patterns of tested clock genes in liver (Opperhuizen et al., 2016; de Goede P, 2018). These data indicate that feeding behavior is a strong Zeitgeber for peripheral clocks, which seems to contrast with the current results. One possible explanation for these findings is that also daily light-dark patterns in locomotor activity were drastically changed in these rats. In line with this is a previous study in mice where TRF to 119 the light phase eliminated the rhythm in Per2 expression in the gastrocnemius muscle, but other clock genes tested only showed small shifts in acrophase (3.5 ± 1.4 hours compared to dark fed animals) (Bray et al., 2013). Contrasting to other TRF experiments the locomotor activity of rats studied in Bray et al. was found to be mainly nocturnal. Perhaps this persisting nocturnal activity pattern retains the rhythmic expression of clock genes in SM. It thus might well be possible that locomotor activity and not feeding behavior is the main regulator of the muscle peripheral clock. Future experiments using time-restricted activity could provide more insight on this matter. The effects of locomotor activity on the peripheral clocks in liver and BAT seem less likely, but also cannot be ruled out by the present experiments. Another important difference between TRF experiments and 6-meals-a-day feeding is that during the 6-meals-a-day regimen food deprivation never lasts longer than 4 hours, whilst in TRF studies food access usually is limited to 10-12 hours during the light phase, resulting in a daily 12-14 hours fasting period. Under the 6-meals-a-day feeding regimen Srebp1c lost its rhythmic expression, while Pgc1α gained rhythmicity upon 6-meals-a-day feeding. Several metabolic genes also showed a trend for changes in average expression levels as a result of the 6-meal feeding regimen (Glut4, Lpl and Sirt3) or showed a significant phase shift of their acrophase (Pdk4 and Ucp3). This effect of 6-meals-a-day feeding on genes involved in lipid metabolism seems in line with our previous observation of increased plasma leptin levels (Kalsbeek et al., 2001). Finally, the 6meal feeding regimen appears to affect gene expression profiles in SM less as compared to TRF to the light phase, especially concerning the clock genes. Another interesting notion is that the expression of Sirt3 remained unchanged in muscle indicating that the 6-meals-a-day feeding schedule did not make the rats calorie restricted. Clock gene expression profiles in BAT and the daily rhythm in RER closely follow the rhythm in feeding behavior during TRF but not with the 6-meals-a-day feeding regimen. Contrasting, several metabolic genes in BAT either lost or gained rhythmicity or had their expression levels altered with 6-meal feeding, including Pdk4, Lpl and Srebp1c, suggesting that glucose and lipid metabolism in BAT is also modulated by 6-meals-a-day feeding schedule. The loss of rhythmicity of Srebp1c, Pgc-1α and Lpl and gain of rhythmicity of Pdk4, Fgf21 and Fas in BAT during 6-meals-a-day feeding probably is necessary to conserve 120 glucose and lipid metabolism during the active and inactive phase, respectively. Accordingly, when abolishing the day/night rhythm in feeding behavior no L/D difference was observed in RER, although there was a large phase advance resulting in lower RER during the dark phase, suggesting an enhanced utilization of lipids during the dark phase during which the 6-mealsa-day animals were eating less food as compared to the ad libitum fed group. As expected, a peak in RER occurred almost immediately after each feeding session in the 6-meals-a-day experiment, regardless of the time of day (Fig. 4a). Similar to skeletal muscle, also in BAT Sirt3 did not show any change in level of expression suggesting that during 6-meals-a-day feeding animals were not caloric restricted. Fgf21 is upregulated upon prolonged fasting and stimulates glucose uptake in adipocytes (Itoh, 2010; Oishi et al., 2011; Markan et al., 2014). Interestingly average Fgf21 and Pdk4 expression levels remained unchanged during the 6meals-a-day feeding regimen, but gained rhythmicity. This could suggest that the fasting period is not long enough to induce Fgf21 expression, but still played a role in disturbed glucose uptake as is observed with the gain of rhythmicity of Pdk4 after 6-meals-a-day feeding regimen. Taken together our 6-meals-a-day data show that in BAT metabolic gene expression is, at least in part, regulated by feeding behavior. However, clock gene expression in BAT may be more affected by the fasting period, which is prolonged and more profound in the traditional TRF experiments, but reduced to less than 4 hours during our 6-meals-a-day feeding regimen. In the liver several, but not all, of the metabolic genes were affected by the 6-meals-a-day feeding regimen, but often with opposite effects compared to muscle and BAT. For instance Srebp1c and Lpl gained rhythmicity with the 6-meals-a-day feeding regimen. Contrasting Pdk4 and Fgf21 lost rhythmicity after 6-meals-a-day feeding and in these genes the mean expression levels remained unchanged, suggesting that 4h fasting is not long enough to activate the expression of Fgf21 and other metabolic genes in the liver (Pparα, Pgc1α, Hsl, and Glut2) that are found to be activated by prolonged fasting (Lundasen et al., 2007; Hayashida et al., 2010). Interestingly, also in the liver Sirt1, similar to muscle and BAT, remained unaffected with 6-meals-a-day feeding suggesting again that in the present 6-meal feeding paradigm the rats were not calorie restricted. Another interesting observation is that Fas expression was completely altered after 6-meal feeding. The different effects on 121 metabolic gene expression in liver when compared to muscle and BAT once more confirms the differential effects of feeding behavior on peripheral metabolically active tissues. In all three tissue types investigated here an apparent gain of rhythmicity was found for one or more metabolic genes in the 6-meal group. Although this might seem counter-intuitive, as the rhythm in feeding behavior was abolished, there are several possible explanations for these findings. The natural fasting period of ad libitum fed animals during the daytime might disturb the rhythmic expression of these metabolic genes. Elimination of this fasting period through the 6-meal paradigm potentially unmasks this disturbance. In line with this, eliminating the rhythm in feeding behavior only marginally affected the peripheral clocks but did lead to altered expression of metabolic genes. It thus might be possible that the feeding behavior (specifically the daytime fasting period) itself suppressed the rhythmic control of the peripheral clock on these peripheral metabolic genes. This would thus imply that some metabolic genes are mainly regulated by the feeding behavior whilst other metabolic genes are controlled by the combination of the peripheral clock and feeding/fasting behavior. Finally, the group sizes and the specific ZTs here chosen might lead to insufficient statistical power to detect a significant rhythm in the ad libitum group whilst for the 6-meal group this rhythm is found. Lastly, we do not believe that the duration of our intervention is too short to notice more substantial changes in gene expression profiles and metabolic phenotype. Our study protocol lasted for 6 weeks and therefore exceeds the duration of most TRF protocols that generally last between 1-4 weeks. 4.4 Clinical relevance of ultradian and other TRF interventions An increasing amount of evidence suggests that not only diet composition, but also the timing of food intake can both improve or deteriorate energy homeostasis. Recently, several studies in humans have tried to identify potential mechanisms that can explain these links between rhythmic aspects of (feeding) behavior and metabolic diseases, such as obesity and T2DM. One such study found a positive correlation between the fragmentation of daytime activity rhythms and occurrence of obesity and central adiposity in European adolescents (Garaulet et al., 2016). Similar results were found in Spanish obese adult women (Corbalan-Tutau et al., 122 2011) and Dutch middle-aged and elderly persons (Luik et al., 2013). It was hypothesized that this fragmentation of activity was due to circadian disruption, since daily patterns of melatonin, a main output of the SCN, showed a decreased amplitude related to an increase in rhythm fragmentation (Corbalan-Tutau et al., 2011). When abolishing the feeding-fasting rhythm with our 6-meals-a-day paradigm, the day-night difference in RER was less pronounced or even abolished in the 6-meals-a-day group. On the other hand, during TRF the amplitude of the daily RER rhythm was enhanced (Opperhuizen et al., 2016; de Goede P, 2018). It is therefore tempting to speculate that the beneficial effects that are seen during TRF to the active phase result from a clearer distinction between the rest and active phase for several physiological parameters such as feeding behavior, energy metabolism and locomotor activity and that this beneficial effect of TRF could also protect against the consequences of an “unhealthy” hypercaloric diet. In a different experimental design mice had access to food twice a day: at the beginning and end of the active period and several measures of metabolic health were studied (MartinezLopez et al., 2017). Importantly, in this study mice in the experimental group consumed equal amounts of food as the ad libitum control group. They found that mice that consumed isocaloric meals twice a day had lower lipid levels, suppressed gluconeogenesis, increased leptin sensitivity, increased muscle mass and decreased adiposity, all suggesting that consuming multiple distinct meals with an equal interval of intermeal fasting, without caloric restriction, can prevent metabolic disorders such as T2DM and obesity. A possible explanation for these findings is the clear fasting period in the experimental group. Several studies show clear beneficial effects of (prolonged) fasting on metabolism and health in both humans and rodents (reviewed in (Longo and Panda, 2016)). One such study had overweight, healthy individuals whom had erratic eating patterns (spread throughout the day and night) limit their food intake during a 10-12h period for 16 weeks without reducing caloric intake (Gill and Panda, 2015). After the 16 weeks intervention period subjects had reduced body weight as well as self-reported improved sleep and an improved sense of being energetic. Similarly, mice fed a high fat diet that were TRF to 8 hours during the dark phase were protected against obesity, hyperinsulinemia, hepatic steatosis and inflammation as compared to ad libitum fed mice that consumed equivalent calories from this high fat diet (Hatori et al., 123 2012). In respect to these fasting studies the 6-meals-a-day feeding protocol has exactly the opposite effect, i.e., it reduces the fasting period to maximal 4 hours and the animals are continuously in a post-prandial state. Thus, our experimental design not only serves as a valuable tool to study the effects of rhythms in feeding behavior independently of changes in the peripheral clocks, but also to study the effects of an absence of a clear fasting period. 5. Conclusion Using our 6-meals-a-day feeding regimen to eliminate the daily rhythm in feeding behavior, we observed several changes in behavior, physiology and metabolism, including body temperature, RER and locomotor activity. Additionally, we found that this ultradian feeding behavior has no effect on the SCN clock, and has limited effects on peripheral clock (clock) gene rhythms in liver, BAT and SM. These results indicate that other, environmental or endogenous cues clearly also are involved in the control of these peripheral rhythms. On the other hand, the changes in gene expression often were regulated in a tissue-dependent manner, stressing the importance of multi-tissue investigations when studying the effects of TRF or other models that disturb the normal functioning of biological rhythms and rhythmic behavior on metabolism. Furthermore, since the central pacemaker in the SCN was not affected by the 6-meals-a-day feeding paradigm, we confirm its rigidity, although clearly this does not prevent misalignment between peripheral clocks and the central clock. 6. Acknowledgements and funding We acknowledge Unga A. Unmehopa and Bernadine Snell for their assistance on the quality control of RNA isolation and RT-qPCR. PdG was supported by a ZonMW TOP grant (#91214047). SS was supported by doctoral fellowships from “NeuroTime” Erasmus Mundus Program, European Doctoral College of University of Strasbourg and Eurometropolis of Strasbourg. 7. Declaration of interest Conflicts of interest: none 124 References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. Hastings, M.H., Reddy, A.B. and Maywood, E.S., 2003. A clockwork web: circadian timing in brain and periphery, in health and disease, Nat Rev Neurosci. 4, 649-61. Reppert, S.M. and Weaver, D.R., 2002. 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Fasting, Circadian Rhythms, and Time-Restricted Feeding in Healthy Lifespan, Cell Metab. 23, 1048-1059. 59. Gill, S. and Panda, S., 2015. A Smartphone App Reveals Erratic Diurnal Eating Patterns in Humans that Can Be Modulated for Health Benefits, Cell Metab. 22, 789-98. 128 Table 1: Two-way ANOVA analysis of all clock- and metabolic genes tested in liver, muscle and BAT. Genes Bmal1 Cry1 Cry 2 Per1 Per2 Dbp Rev-erbα Ucp1 Ucp3 Pparα Pgc-1α Glut2 Glut4 Pdk4 Hsl Lpl Srebp1c Sirt1 Sirt3 Fas Fgf21 Feeding =0.008 <0.001 =0.270 =0.765 =0.072 =0.141 =0.122 Liver Time <0.001 <0.001 =0.021 <0.001 <0.001 <0.001 <0.001 =0.644 =0.526 =0.505 =0.122 =0.927 <0.001 =0.459 =0.848 =0.234 =0.063 =0.803 =0.624 =0.840 =0.194 =0.004 =0.954 <0.001 =0.282 =0.718 =0.082 =0.359 =0.495 =0.026 =0.318 =0.053 =0.098 =0.006 <0.001 <0.001 =0.181 Interaction =0.057 <0.001 =0.516 =0.178 =0.021 =0.105 <0.001 Two Way ANOVA table (P values) Muscle Feeding Time Interaction =0.758 =0.830 <0.001 =0.345 =0.637 <0.001 =0.342 =0.353 =0.670 =0.466 =0.563 <0.001 =0.888 <0.001 =0.003 =0.969 <0.001 <0.001 =0.583 <0.001 =0.049 Feeding =0.199 =0.003 =0.051 =0.117 =0.262 =0.002 =0.360 =0.166 BAT Time <0.001 <0.001 =0.178 <0.001 <0.001 <0.001 <0.001 =0.039 Interaction =0.002 =0.074 =0.684 =0.991 =0.175 <0.001 =0.865 =0.654 =0.299 =0.002 =0.110 =0.340 =0.031 =0.271 =0.252 =0.311 =0.870 =0.079 =0.471 =0.121 =0.093 =0.161 =0.559 =0.077 =0.379 =0.066 =0.023 =0.427 =0.144 =0.015 =0.684 =0.115 =0.776 =0.965 =0.997 =0.415 =0.248 =0.485 =0.065 =0.224 =0.126 =0.027 =0.187 =0.010 =0.110 =0.531 =0.348 =0.546 =0.252 =0.287 =0.104 =0.459 =0.045 =0.101 =0.606 =0.832 =0.818 =0.836 =0.298 =0.023 =0.027 =0.024 =0.341 =0.581 =0.281 129 Genes Bmal1 Cry1 Cry2 Per1 Per2 Dbp Rev-erbα Ucp3 Pgc-1α Glut4 Pdk4 Hsl Lpl Srebp1c Sirt3 Fas a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c Mean 0.12 0.12 0.7 0.21 0.08 21.2 0.10 --0.03 0.03 14.0 0.09 0.06 14.8 1.29 1.33 12.1α 0.54 0.50 8.6 0.10 0.07 3.3α 0.25 --6.33 --1.86 0.90 3.8α 0.06 --7.80 --0.09 0.05 23.2 0.58 --0.17 --- Ad libitum SEM 0.01 0.01 0.32 0.01 0.01 0.71 0.01 --0.00 0.01 0.75 0.01 0.01 0.86 0.09 0.13 0.37 0.04 0.06 0.44 0.01 0.02 0.80 0.02 --0.27 --0.16 0.22 0.95 0.01 --0.24 --0.01 0.01 0.92 0.02 --0.02 --- Mean 0.11 0.13 0.3 0.22 0.07 21.1 0.12 --0.04 --0.09 0.03 12.7 1.28 1.22 10.4 0.51 0.42 7.2 0.14 0.15 23.8 0.27 0.07 16.4 7.04 --2.78 2.48 23.5 0.07 --8.72 --0.11 --0.63 --0.20 --- 6-meal SEM 0.01 0.02 0.60 0.01 0.02 1.28 0.01 --0.01 --0.01 0.01 1.28 0.08 0.12 0.38 0.04 0.06 0.50 0.03 0.04 1.10 0.01 0.02 1.19 0.33 --0.60 0.85 1.30 0.01 --0.42 --0.02 --0.02 --0.03 --- P value =0.767 =0.719 =0.595 =0.351 =0.788 =0.953 =0.335 =0.463 =0.899 =0.074 =0.169 =0.973 =0.548 =0.002 =0.658 =0.340 =0.055 =0.286 =0.122 <0.001 =0.355 =0.112 =0.148 =0.077 <0.001 =0.549 =0.065 =0.364 =0.096 =0.451 Table 2. Muscle Cosinor analysis of clock and metabolic genes showing the three fitted parameters of the cosinor regression analysis, including a (the mean level), b (the amplitude), and c (the acrophase of the rhythm; see Methods for details). For the acrophase, the reference time is Zeitgeber 0 (i.e., lights on) and can be any number between 0-24 only. p values in the right column indicate a significant difference between Ad libitum and the 6-meals-a-day group. Non-significant parameters are not shown (--) Genes Bmal1 Cry1 Cry2 Per1 Per2 Dbp Rev-erbα Ucp1 Pparα Pgc-1α Glut4 Pdk4 Hsl Lpl Srebp1c Sirt3 Fas Fgf21 a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c Mean 0.01 0.01α 22.1α 0.02α 0.01 20.1 0.01α --0.00 0.00 3.0 0.01 0.01 14.3 0.13 0.11α 9.5α 0.04 0.02 10.3 9.80 --0.01 --0.04 0.02 12.7 0.74 --0.66 --0.13 --2.05 0.80 14.4 0.05 0.02 17.1 0.12 --5.75 --0.01 --- Ad libitum SEM 0.00 0.00 0.57 0.01 0.00 0.89 0.00 --0.00 0.00 1.44 0.00 0.00 1.12 0.01 0.02 0.55 0.00 0.01 1.22 0.96 --0.01 --0.00 0.01 1.47 0.07 --0.07 --0.01 --0.20 0.28 1.35 0.01 0.01 1.44 0.00 --0.29 --0.01 --- Mean 0.01 0.00 0.0 0.01 0.01 20.1 0.01 --0.00 0.00 2.5 0.00 0.00 14.8 0.09 0.03 13.1β 0.03 0.02 11.1 8.24 --0.05 --0.03 --0.67 --0.77 0.27 16.5 0.12 --1.63 --0.04 --0.12 --5.67 0.85 14.5 0.01 0.00 8.1 6-meal SEM 0.00 0.00 1.41 0.00 0.00 0.48 0.00 --0.00 0.00 0.96 0.00 0.00 0.86 0.10 0.00 0.46 0.00 0.00 0.62 0.50 --0.00 --0.00 --0.04 --0.06 0.08 1.13 0.01 --0.10 --0.00 --0.00 --0.18 0.26 1.15 0.00 0.00 1.28 P value =0.193 <0.001 <0.001 <0.001 =0.608 =0.978 =0.041 =0.113 =0.890 =0.801 =0.286 =0.103 =0.732 =0.741 <0.001 <0.001 =0.359 =0.885 =0.553 =0.159 =0.247 =0.313 =0.41 =0.250 =0.485 =0.064 =0.219 =0.826 =0.833 =0.352 Table 3. BAT Cosinor analysis of clock and metabolic genes showing the three fitted parameters of the cosinor regression analysis, including a (the mean level), b (the amplitude), and c (the acrophase of the rhythm; see Methods for details). For the acrophase, the reference time is Zeitgeber 0 (i.e., lights on) and can be any number between 0-24 only. p values in the right column indicate a significant difference between Ad libitum and the 6-meals-a-day group. Non-significant parameters are not shown (--) 131 Genes Bmal1 Cry1 Cry2 Per1 Per2 Dbp Rev-erbα Pparα Pgc-1α Glut2 Pdk4 Hsl Lpl Srebp1c Sirt1 Fas Fgf21 a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c a b c Mean 0.04α 0.40α 1.0 0.05α 0.03α 21.3 0.09 0.03 20.3 0.03 0.03 15.2 0.10 0.07α 17.6 0.23 0.30 12.0 0.19 0.25α 9.4α 0.18 --0.01 --0.39 0.09 14.1 0.09 0.04 3.9 0.01 --0.01 --0.64 --0.02 --1.08 0.40 17.7α 0.04 0.01 6.4 Ad libitum SEM 0.00 0.01 0.50 0.00 0.00 0.26 0.01 0.01 1.40 0.00 0.00 0.62 0.01 0.01 0.50 0.03 0.04 0.56 0.03 0.04 0.56 0.01 --0.00 --0.02 0.02 1.30 0.01 0.01 0.96 0.00 --0.00 --0.05 --0.00 --0.08 0.11 1.13 0.00 0.00 0.99 Mean 0.03 0.02 1.5 0.03 0.02 21.7 0.08 --0.04 0.01 14.1 0.08 0.04 17.0 0.18 0.20 13.1 0.15 0.16 11.2 0.19 --0.01 --0.40 0.09 13.1 0.07 --0.01 --0.01 0.00 7.2 0.63 0.22 7.9 0.02 --1.31 0.53 9.2 0.03 --- 6-meal SEM 0.00 0.00 0.52 0.00 0.00 0.62 0.01 --0.00 0.01 1.25 0.01 0.01 0.95 0.01 0.02 0.40 0.01 0.01 0.32 0.01 --0.00 --0.02 0.03 1.07 0.01 --0.00 --0.00 0.00 0.80 0.05 0.07 1.10 0.00 --0.10 0.13 0.97 0.00 --- P value <0.001 =0.015 =0.402 <0.001 <0.001 =0.505 =0.271 =0.762 =0.092 =0.449 =0.070 =0.001 =0.602 =0.158 =0.087 =0.100 =0.184 =0.021 =0.005 =0.636 =0.444 =0.512 =0.951 =0.533 =0.056 =0.815 =0.646 =0.841 =0.178 =0.068 =0.482 =0.001 =0.103 Table 4. Liver Cosinor analysis of clock and metabolic genes showing the three fitted parameters of the cosinor regression analysis, including a (the mean level), b (the amplitude), and c (the acrophase of the rhythm; see Methods for details). For the acrophase, the reference time is Zeitgeber 0 (i.e., lights on) and can be any number between 0-24 only. p values in the right column indicate a significant difference between Ad libitum and the 6-meals-a-day group. Non-significant parameters are not shown (--) 132 Table S1 Primer list Genes Housekeeping Cyclophillin GAPDH HPRT1 TBP Clock Bmal1 Cry1 Cry2 DBP Per1 Per2 Reverbα Metabolic Fas Glut2 Glut4 HSL LPL Pdk4 Pgc1α Pgc1β Pparα Srebp1c Ucp1 Ucp3 Sirt1 Sirt3 Fgf21 Forward primer Reverse primer ATGTGGTCTTTGGGAAGGTG TGAACGGGAAGCTCACTGG GCAGTACAGCCCCAAAATGG TTCGTGCCAGAAATGCTGAA GAAGGAATGGTTTGATGGGT TCCACCACCCTGTTG CTGTA AACAAAGTCTGGCCTGTATCCAA TGCACACCATTTTCCCAGAAC CCGATGACGAACTGAAACACCT AAGTCATCGTGCGCATTTCA TGGATAAGCACTTGGAACGGAA CCTTTGAACCTGATCCGGCT CGCACTTCGGGAGCTCAAACTTC CACCCTGAAAAGAAAGTGCGA ACAGCTGACACCACCCAGATC TGCAGTGTCCGAGGAAGATAGC TCATCATGGTCGTCGGACAGA TGTACAAGTCCCACAGGCGGTA TGCCTTCTTCATGATTGGCTG GTCCATGGCACAGGGCTCACC CAACGCCAAGGAGCTCAAGT CATGGGCATAGGTGAAGATTTCT CTTGGGTGCCGATTACAACC GTCCAGAAAGCCCCAGATACC GGGCTGTGAGTGAGTGCTTTC CACACAGCATGGATTTACGCA CAAAACAACCAGGCCTTCGA TGGTTTTGGTTACGGCTTGC TGCCATTGTTAAGACCGAG AAAAGGCCATCGGTGAAGGT TCACACAATGCAATCCGTTT ACAAGATTGTGGAGCTCAAGG AATCAGCTTTGCTTCCCTCA GCACTGCAGCCTGTTTTGCTGA TGTTTCCTGTGGGATACCTGA GACATACGGGCTGACGTGAT ACCGCAGTCCAGAAAGTCTC GCCCTCCCGTACACTCACTC TGCCCCTTAGTCTTTTCAAGCT CAGCGAGGCAAGGCTAGA ACCTGCAAAGACGTTGGACAG AGCAATTCCCCGATGTCCA TGCCAGTTTCTCCTTCGACA GGTCATTTGGTGACTCTGG AGGAGGGCTCATTGCGTTTT GGCCTTGACCTTGTTCATGT TGCGCAAGACAGCAGATTTA GCTTTGTGCTTGCATTCTGA ATAGTCAGGATGGTACCGAGCA TGAAGAATGGTCTTGGGTCTTT AGTCGGGGCACTGATTTCTG GGCCTCAGACTGGTACACAT 133 Table S2: t-test analysis for behavioral and physiological parameters. a b c a b c a b c a b c Locomotor Activity Respiratory exchange ratio Temperature Heat production SEM 37.9 7.1 0.2 0.00 0.00 0.1 0.1 0.1 0.3 0.04 0.05 0.1 Ad libitum 379.7 221.5 19.3 (ZT) 0.95 0.02 19.9 (ZT) 36.8 0.48 17.8 (ZT) 5.3 1.1 19.1 (ZT) 6-meal 358.6 193.4 17.3 (ZT) 0.93 0.02 10.1 (ZT) 36.25 0.34 17.4 (ZT) 5.1 0.6 16.8 (ZT) SEM 8.9 9.7 0.4 0.01 0.00 0.8 0.07 0.02 0.5 0.14 0.01 0.4 P value =0.60 =0.02 <0.001 =0.054 =0.73 <0.001 =0.02 =0.46 =0.56 =0.16 <0.001 <0.001 Shift ~ 2h ~ 10h ~2h Table S3: t-test analysis on significant cosinor parameters for the clock and clock-controlled genes and protein in SCN. Genes SCN Avp Per1 Per2 Protein SCN AVP 6-meal P value a b c a b c a b c Mean 42.03 --7.70 4.12 6.6 7.82 3.24 10.4 Ad libitum SEM 3.85 --0.70 0.99 0.9 0.72 1.02 1.2 Mean 42.79 11.31 12.6 8.94 4.74 5.6 7.94 3.75 10.7 SEM 2.94 4.15 1.40 0.45 0.70 0.56 0.65 0.92 0.93 a b c 65.25 --- 4.45 --- 64.54 --- 5.65 --- =0.879 =0.15 =0.61 =0.35 =0.90 =0.70 =0.80 =0.92 Table S4: Two-way ANOVA analysis for gene expression in SCN. Genes SCN Avp 2 Way ANOVA Table (P value) Feeding Time Interaction =0.880 =0.069 =0.587 Per1 =0.164 <0.001 =0.767 Per2 =0.909 <0.001 =0.878 =0.791 <0.001 =0.876 Protein SCN AVP 134 135 136 Chapter 4 Differential effects of diet composition and timing of feeding behavior on rat Brown adipose tissue and Skeletal muscle peripheral clocks. Paul de Goede‡1, Satish Sen‡1,3,4, Johanneke E Oosterman1,2, 3, 5, Ewout Foppen1, Remi Jansen3, Susanne E la Fleur1,2,5, Etienne Challet4, Andries Kalsbeek*1,2,3 ‡ These authors contributed equally 1 Laboratory of Endocrinology, Department of Clinical Chemistry, Academic Medical Center (AMC), University of Amsterdam, Amsterdam, The Netherlands. 2 Department of Endocrinology and Metabolism, Academic Medical Center (AMC), University of Amsterdam, Amsterdam, The Netherlands 3 Hypothalamic Integration Mechanisms group, Netherlands Institute for Neuroscience (NIN), Amsterdam, the Netherlands 4 Regulation of Circadian Clocks team, Institute of Cellular and Integrative Neurosciences, UPR3212, Centre National de la Recherche Scientifique (CNRS), University of Strasbourg, Strasbourg, France 5 Metabolism and Reward, Netherlands Institute for Neuroscience, Amsterdam, the Netherlands * Corresponding address: Andries Kalsbeek Ph.d, Hypothalamic Integration Mechanisms group, Netherlands Institute for Neuroscience (NIN), Amsterdam, the Netherlands E-mail: a.kalsbeek@nin.knaw.nl 137 Abstract The effects of feeding behavior and diet composition, as well as their possible interactions, on daily (clock) gene expression rhythms have mainly been studied in the liver, and to a lesser degree in white adipose tissue (WAT), but hardly in other metabolic tissues such as skeletal muscle (SM) and brown adipose tissues (BAT). We therefore subjected male Wistar rats to a regular chow or free choice high-fat-high sugar (fcHFHS) diet in combination with time restricted feeding (TRF) to either the light or dark phase. In SM, all tested clock genes lost their rhythmic expression in the chow light fed group. In the fcHFHS light fed group rhythmic expression for some, but not all, clock genes was maintained, but shifted by several hours. In BAT the daily rhythmicity of clock genes was maintained for the light fed groups, but expression patterns were shifted as compared with ad libitum and dark fed groups, whilst the fcHFHS diet made the rhythmicity of clock genes become more pronounced. Most of the metabolic genes in BAT tissue tested did not show any rhythmic expression in either the chow or fcHFHS groups. In SM Pdk4 and Ucp3 were phase-shifted, but remained rhythmically expressed in the chow light fed groups. Rhythmic expression was lost for Ucp3 whilst on the fcHFHS diet during the light phase. In summary, both feeding at the wrong time of day and diet composition disturb the peripheral clocks in SM and BAT, but to different degrees and thereby result in a further desynchronization between metabolically active tissues such as SM, BAT, WAT and liver. Keywords: Soleus Muscle (SM), Brown adipose tissue (BAT), free choice High-Fat HighSugar (fcHFHS), Time-restricted feeding (TRF), desynchronization. 138 1. Introduction Many studies support the idea that both food consumption and energy metabolism are under strong influence of the biological clock (Bray and Young, 2009; Summa and Turek, 2014). It is therefore not surprising that recent epidemiological studies have found a correlation between conditions that disturb the biological clock, such as shift work, and metabolic diseases, such as obesity and type 2 diabetes mellitus (T2DM). The molecular mechanism of the biological clock is made up of a transcriptional-translational feedback loop consisting of various clock genes, such as Clock, Bmal1, Per1/2/3, Cry1/2, Rev-erbα and clock controlled genes (CCGs). CLOCK and BMAL1 are part of the core clock mechanism and form the positive limb through hetero-dimerization. The Per and Cry genes form the negative limb of the core clock mechanism and bind over the promoter regions of Bmal1 and Clock genes (Gekakis et al., 1998; Hogenesch and Hahn, 1998; Yoo et al., 2005; Ohno et al., 2007). When the PER and CRY proteins are present at sufficiently high levels in the cytoplasm they translocate back to the nucleus to inhibit their own transcription (Ramsey et al., 2007). REVERBα/β and RORα//β show competitive binding to promoters of Bmal1 and Clock with binding of Reverbα/β inhibiting and binding of Rorα/β promoting the transcription of Bmal1 and Clock. The transcriptional-translational feedback loop is set to revolve roughly every 24 hours (i.e., with a circadian period), but can be adjusted and synchronized by several environmental cues, so called Zeitgebers. In mammals the master, or central, clock is located in the suprachiasmatic nucleus (SCN) in the hypothalamus and is mainly synchronized by the environmental light/dark cycle. The strongest known Zeitgeber for peripheral clocks such as those in liver, white and brown adipose tissues and skeletal muscle is food or energy availability (Froy, 2010). The biological clocks use CCGs as an output mechanism to regulate a broad range of processes, including many metabolic processes. A number of CCGs are metabolic genes that are involved in lipogenesis, fatty-acid oxidation and glucose metabolism (e.g. Pparα, Pgc-1α, Srebp1c, several glucose transporters, Fas and Lpl and many more). Strikingly, the exact effects of the biological clocks on these metabolic processes differ in a tissue-dependent 139 manner (Eckel-Mahan and Sassone-Corsi, 2013; Marcheva et al., 2013), indicating the importance of timely orchestrated metabolic processes, both within and between different tissues. As a result, there is a need to investigate the interplay between the biological clocks and metabolic processes for the major tissue types involved in energy metabolism. Thus, most studies concentrated on the liver and, to a lesser extent, on WAT. Two peripheral tissues that until recently have often been overlooked in studies on circadian rhythms and metabolism are brown adipose tissue (BAT) and skeletal muscle (SM), despite their clear importance for whole body energy metabolism. SM is the organ with the highest overall metabolic rate (Wang et al., 2010) and is important for glucose homeostasis. SM alone is responsible for 6080% of insulin-mediated glucose uptake (Wilcox, 2005; de Lange et al., 2007) and 80% of postprandial glucose uptake (DeFronzo et al., 1981a; DeFronzo et al., 1985; Ferrannini et al., 1988; Shulman et al., 1990). SM is also responsible for a major proportion of fatty acid oxidation and the ability to oxidize this metabolic substrate is reduced in obese and T2DM patients (Mensink et al., 2001; Berggren et al., 2008). SM genes involved in carbohydrate catabolism show peak expression early in the active phase, whilst genes involved in the storage of carbohydrate substrates peak in the middle of the active phase. Conversely, genes involved in lipid metabolism peak in the middle of the inactive phase, whilst genes involved in lipogenesis and storage of lipids peak at the end of the active phase (Hodge et al., 2015). More interestingly, the 7 highest enriched gene ontology sets of mRNA found to be oscillating with a 24-h periodicity in SM, were all involved in the regulation of metabolic processes. Combined, these metabolic transcripts represented approximately 62% of the circadian transcriptome of mouse SM (Hodge et al., 2015). BAT is a metabolically highly active tissue important for heat production. Activation of BAT for thermogenesis results in increased energy expenditure via the uncoupling protein UCP1. BAT maintains thermogenesis through oxidation of lipids and glucose and its activation results in oxidative phosphorylation as well as heat production (Cannon and Nedergaard, 2004; Bartelt et al., 2011; Stanford and Goodyear, 2013; Mulya and Kirwan, 2016). BAT has been long known to be activated by various high-calorie diets, such as high-fat and highsucrose diets, likely through the increased UCP1 levels seen during these diets, thereby providing a potential mechanism to limit weight/fat gain (Rothwell and Stock, 1979; Bukowiecki et al., 1983; Mercer and Trayhurn, 1987; LeBlanc and Labrie, 1997). 140 The catabolism and storage of different substrates (i.e., carbohydrates and lipids) in metabolically active tissues is thus regulated in a time-dependent manner, which coincides with the natural daily rhythm of food intake during the active phase and resting during the inactive phase. Disturbing this biological rhythm of feeding behavior by restricting access to food to the inactive phase is a widely accepted animal model for shift-work in humans (Opperhuizen et al., 2015). Several studies, including from our own group, have investigated the effects of time-restricted feeding (TRF) (Vollmers et al., 2009; Salgado-Delgado et al., 2010; Hatori et al., 2012; Reznick et al., 2013; Zarrinpar et al., 2014; Dyar et al., 2015; Oosterman et al., 2015; Opperhuizen et al., 2016; Yasumoto et al., 2016), some of these studies even compared different diets in combination with TRF (Hatori et al., 2012; Reznick et al., 2013; Oosterman et al., 2015). Earlier we found that the combination of eating at the wrong time-of-day and diet composition (i.e., with a high-fat or high-sugar content) affects substrate metabolism on a whole body level. However, the independent contributions of TRF and diet composition could not be established in that study (Oosterman et al., 2015). Here we show the effects of different combinations of TRF and diet composition in male Wistar rats, both on a whole body level as well as in two peripheral organs: SM and BAT. We focused on these two metabolically active tissues since they are critical for glucose and lipid metabolism and they have not been investigated as thoroughly as other tissues (e.g. liver and WAT). In these tissues, we specifically targeted genes of the core clock mechanism and genes involved in glucose and lipid metabolism. The present study shows that expression patterns of the BAT and SM molecular clocks, as well as several metabolic genes, are clearly affected by changes in the daily timing of food intake as well as by diet composition. 2. Materials & Methods 2.1 Animal experiments 2.1.1 Influence of diet composition and TRF One hundred and ninety three male Wistar rats were housed under 12:12 light:dark conditions for the entire experiment, with Zeitgeber Time (ZT) 0 being the time of lights on and ZT12 141 the time of lights off. The animals were divided over 5 different batches. Animals were randomly assigned to either a standard chow or free-choice high-fat high-sugar (fcHFHS) diet group and to one of the TRF groups: ad libitum, Dark or Light. The fcHFHS diet animals could freely choose between pelleted chow, a bottle of tap water, a bottle with a 30% sugar solution (Kristalsuiker; Van Gilse) and a dish with saturated fat (Ossewit Blanc de Boeuf; Vandemoortele Lipids NV). The chow diet animals had access to pelleted chow and tap water only. The ad libitum group had free access to food and water for 24h/day, the Dark and Light TRF groups had free access to food for 10h/day between ZT 1323 and between ZT1-11, respectively. After 3 weeks of diet and TRF, a randomized subset of 63 animals was placed in metabolic cages for 4 days to measure the respiratory exchange ratio, locomotor activity and heat production whilst remaining on their assigned diet and TRF conditions. After 5 weeks of diet and TRF conditions animals were sacrificed at 3 hour intervals throughout a 24 hour period (at ZT 0, 3, 6, 9, 12, 15, 18, 21) and soleus muscle and BAT tissues were carefully collected, snap frozen in liquid nitrogen and stored at -80 °C until RNA isolation was performed. 2.2 Activity and respirometry Metabolic PhenoCages (TSE systems) were used to measure several metabolic parameters, whilst animals remained on their diet and TRF conditions. Animals were individually housed in these cages. After a day of acclimatization to this new environment, the parameters for food intake, locomotor activity, respiratory exchange ratio (RER) and heat production were measured for three consecutive days (72 hours). 2.3 RNA isolation Soleus muscle tissue was mechanically homogenized while kept on dry ice. The BAT tissue was crushed in Trizol by using the homogenizer machine. For both tissues, RNA isolation was done using the NucleoSpin RNA isolation kit (Machery-Nagel). For muscle RNA isolation, three additional washing steps with 75% ethanol were performed. RNA was eluted from the spin column using 40μl of H2O and RNA concentration and quality of the RNA were determined using a DS-11 (DeNovix) spectrophotometer and a nanochip using Agilent 142 2100 Bioanalyzer (Agilent Technologies), respectively. Although RNA integrity number (RIN) values above 5 were considered acceptable, samples had a RIN above 8. 2.4 Muscle and BAT cDNA synthesis Two hundred ng from muscle and 350 ng from BAT isolated RNA were used as input template for cDNA synthesis. The Transcriptor First Strand cDNA synthesis kit (Roche) was used. RT-PCRs were run using an UNO-Thermoblock (Biometra). 2.5 RT-qPCR One to nineteen (1:19) diluted cDNA was used for all qPCRs to detect muscle and BAT gene expression profiles. Expression levels of all genes were standardized by dividing over the geometric mean of three housekeeping genes: TBP, GAPDH and Cyclophilin for muscle; TBP, HPRT1 and GAPDH for BAT. RT-qPCR was performed using a LightCycler 480 (Roche). Expression levels were calculated using dedicated software for linear regression of qPCR data (LinRegPCR). All used primers are listed in Table S4 Melting curves of the RTqPCR and fragment length of the DNA amplicons were inspected as a means of quality control. 3. Statistics Rhythmicity of gene expression profiles was determined by the non-parametric algorithm JTK_CYCLE version 3.1 which was run under R version 3.3.1. T-tests, one-way and twoway ANOVAs, as well as Tukey’s Multiple Comparison post-hoc tests were executed by GraphPad Prism 7. All graphs were plotted by GraphPad Prism 7. 4. Results A detailed description of the physiological and metabolic results from the metabolic cages is provided elsewhere (Oosterman et al.), below is a short description of the most important results. 143 4.1 Caloric intake and body weight gain Caloric intake was not different between the TRF groups, but caloric intake was about 20% higher for the fcHFHS animals as compared to chow fed groups (two-way ANOVA: Diet p<0.001, TRF p>0.05, Diet*TRF p>0.05). Similar to previous experiments animals on the fcHFHS diet consumed about 37.5% of their calories from fat, 15% from sugar and 47.5% from chow (la Fleur et al., 2007). Similarly, body weight gain after 5 weeks was not different between the TRF groups, but body weight gain was higher for the fcHFHS fed animals as compared to chow fed groups (105 grams and 90 grams, respectively; two-way ANOVA: Diet p<0.001, TRF p>0.05, Diet*TRF p>0.05). 4.2 Respiratory exchange ratio (RER) Animals fed ad libitum showed a clear day/night rhythm in their RER, with highest levels found during the active phase for both the chow and fcHFHS fed groups (Fig: 1a & b). TRF to either the dark or light phase greatly increased the amplitude of the RER for both diet groups. The RER for groups restricted to feeding during the light phase was strikingly antiphasic as compared to both the ad libitum and dark fed groups. The L/D difference in RER of all groups clearly follows the daily feeding pattern, with highest RER levels being reached during the feeding period, independent of the time of day (Fig: 1a & b). Analysis of the average RER values per 24 hour period (Fig: 1c) revealed significant differences between the different diet and TRF conditions (two-way ANOVA: Diet p<0.001, TRF p<0.001, Diet*TRF p<0.001). Closer inspection of the individual diet and TRF combinations revealed that the different chow fed groups did not significantly differ in their average 24h RER, but that the RER of both the light and dark fed groups on the fcHFHS diet was significantly lower than that of the ad libitum group on a fcHFHS diet as well as that of the chow ad libitum and light fed groups (one-way ANOVA, p<0.0001) (Fig: 1c). Aside from this, the RER of the light fed fcHFHS group was also significantly lower than the RER of the dark fed chow group (p<0.0001). 4.3 Locomotor activity Animals fed ad libitum showed a clear day/night rhythm in their locomotor activity with most activity occurring during the dark phase (71% of total activity; Fig: 1a & b). During TRF in 144 Fig 1. Analysis of the metabolic parameters RER (left), locomotor activity (middle) and heat production (right) of the animals inside the metabolic cages during TRF. Whilst in the metabolic cages animals remained on their assigned diet composition and TRF conditions. (a) Difference within metabolic parameters between light and dark phase for the chow fed groups. (b) Difference within metabolic parameters between light and dark phase for the fcHFHS fed groups. (c) Average 24 hour values of the metabolic parameters for all diet composition and TRF groups. Data are depicted as means±SEM. ns = non significant, ** = p<0.01, *** = p<0.001, **** = p<0.0001, n = 10–11 per group. Identical letters indicate similar mean values, Tukey’s Multiple Comparison post-hoc test was performed to correct for multiple testing. Locomotor activity is presented as arbitrary units (AU). ad lib=ad libitum fed animals, L = light fed animals, D = dark fed animals. the dark phase this L/D difference in locomotor activity is strengthened due to the increased activity during the dark phase (79% of total activity; Fig: 1a & b). Diet composition does not seem to affect the locomotor activity for ad libitum and dark fed groups (71% and 79% of total activity during the dark phase, respectively). TRF to the light phase, however, does alter the daily pattern of locomotor activity. Animals fed chow during the light phase showed an inverted activity pattern, with most locomotor activity during the light phase (61% of total activity), i.e., in their feeding period (Fig: 1a). Interestingly, light fed animals on a fcHFHS 145 diet lost the day/night rhythm in locomotor activity and showed equal activity during the light (49% activity) and dark period (51% activity; Fig: 1b). Analysis of the total locomotor activity per 24 hour period (Fig: 1c) revealed significant differences between the different diet and TRF conditions (two-way ANOVA: Diet p<0.018, TRF p<0.0005, Diet*TRF p=0.721). Total locomotor activity for the combination of chow diet and TRF to the dark phase was significantly higher compared to the chow ad libitum, fcHFHS ad libitum and fcHFHS light fed groups, but no other diet or TRF combination differed (one-way ANOVA, p=0.0002). 4.4 Heat production Similar to locomotor activity, heat production was highest during the feeding phase for all groups, including the light fed groups (Fig 1a & b). Akin to the locomotor activity data the difference between the light and dark period in heat production was largest in the dark fed animals (Fig 1a & b). Two-way ANOVA showed significant effects of both diet composition and TRF on mean heat production per 24 hours (two-way ANOVA: Diet p<0.0005, TRF p=0.001, Diet*TRF p=0.985) (Fig 1c). Specifically, heat production was lowest in the chow light group and differed significantly from all fcHFHS groups, chow ad libitum differed from fcHFHS ad libitum, and chow dark differed from fcHFHS ad libitum and fcHFHS dark. Interestingly, this result seems to be caused primarily by diet composition and not by TRF, since the three fcHFHS groups did not differ from each other, nor did the 3 chow groups differ from each other, contrasting the results from the two-way ANOVA (Fig: 1c). 4.5 Clock gene expression in soleus muscle and BAT Gene expression analysis using qPCR and JTK_CYCLE analysis confirmed rhythmicity of six of the seven clock genes investigated in both soleus muscle (Bmal1, Cry1, Per1, Per2, Dbp and Rev-erbα) (Fig: 2, Table 1) and BAT (Bmal1, Cry1, Cry2, Per2, Dbp and Rev-erbα) (Fig: 2, Table 2). TRF to the dark phase did not alter the expression patterns of these core clock genes in either tissue type, although it did induce slight phase-shifts for some of the clock genes (Tables 1 & 2). These results were similar for animals on a chow and a fcHFHS diet, although in BAT the fcHFHS diet enhanced the rhythmicity of some of the core clock genes (Fig: 2a,b,c,e & f). The amplitude of the expression rhythm tended to be enlarged for Bmal1, Per2, Cry1, Cry2, Rev-erbα, although this never reached significance (Table S3). 146 In contrast, TRF to the light phase whilst on a chow diet completely abolished the rhythmicity of all 6 rhythmic clock genes in the soleus muscle. Contrasting, in BAT the clock genes still displayed rhythmicity, although with a somewhat altered pattern of expression as compared to that of the ad libitum and dark fed animals. When on a fcHFHS diet, rhythmicity for several core clock genes in the soleus muscle was rescued from the dampening effect of a TRF to the light phase, as seen in animals on a chow diet. In BAT, TRF to the light phase showed similar effects in the fcHFHS and chow groups. 4.6 Metabolic gene expression in soleus muscle and BAT 4.6.1 Soleus muscle Most of the studied metabolic genes in muscle do not show rhythmicity under ad libitum conditions whether fed with chow or fcHFHS diet, except for substrate switch pyruvate dehydrogenase kinase (Pdk4) and the most abundant uncoupling protein in skeletal muscle uncoupling protein 3 (Ucp3) (p<0.001 for both genes) Fatty acid synthase (Fas) was only rhythmically expressed in the dark fed animals on a chow diet (p=0.049). When fed during the light phase, both Pdk4, and Ucp3 and show phase shifts of 7.5 hours as compared to the dark and ad libitum groups, with the exception of Ucp3 for the fcHFHS group that was fed during the light period which was not rhythmically expressed (p=0.45). Interestingly, Srebp1c expression became rhythmic when animals on a chow diet were subjected to TRF to either dark or light phase (Fig: 3e), whilst the ad libitum group did not display rhythmic expression for this gene (p<0.005 for both dark and light phase TRF; acrophase at ZT=0 and ZT=10.5, respectively). None of the fcHFHS groups displayed significant rhythmic expression of Srebp1c. The insulin sensitive glucose transporter Glut4 and the transcription factors Pgc-1α and Pparα were not rhythmically expressed in any of the groups (Fig 3a, c & d). Both Pdk4 and Ucp3 showed a main effect of diet composition for all three TRF groups, due to the higher expression levels in the fcHFHS groups as compared to the chow groups (two way ANOVA, Table S1). Additionally, Pgc-1α had a main effect of diet composition for the ad libitum fed groups, with higher levels for the chow fed group, and for Glut4 an interaction between diet composition and time was found (p=0.011 and p=0.006 respectively, two Way ANOVA, Table S1). 147 Fig 2. Effect of diet composition and TRF on expression profiles of clock genes (a-f) and clock controlled gene Dbp (g) in SM and BAT tissues. Expression profiles are presented as means±SEM. Tissues were collected at 8 different time points across 24 hours. Shaded areas represent the dark phase. 148 Table 1 Effects of diet and timing of food intake on daily rhythms in clock and metabolic gene expression in SM. Data was analyzed by JTK Cycle. The acrophase (in ZT) is only given for genes that are rhythmically expressed (p<0.05). NR = non-rhythmic. JTK cycle analysis for Muscle Genes Muscle Clock Bmal1 Per1 Per2 Rev-erbα Cry1 Cry2 DBP Metabolic Srebp-1c Glut4 Ucp3 PDK4 Pgc1α Pparα Fas CHOW Ad lib 1.5 13.5 16.5 9 21 NR 12 NR NR 4.5 4.5 NR NR NR HFHS Acrophase D 3 15 16.5 9 22.5 NR 13.5 L NR NR NR NR NR NR NR Ad lib 0.001 0.001 0.001 0.001 0.005 1 0.001 P-value D 0.001 0.001 0.001 0.001 0.001 0.110 0.001 1 0.420 1 1 0.380 1 1 Ad lib 3 15 16.5 9 19.5 NR 13.5 0 NR 4.5 6 NR NR 19.5 10.5 NR 21 21 NR NR NR 0.230 1 0.001 0.001 1 1 0.210 0.006 0.140 0.001 0.001 1 0.980 0.049 0.004 1 0.001 0.001 0.38 1 0.300 NR NR 4.5 4.5 NR NR NR L Acrophase D 3 15 16.5 9 22.5 NR 13.5 L 9 NR NR 15 7.5 NR NR Ad lib 0.001 0.001 0.003 0.001 0.001 1 0.001 P-value D 0.001 0.001 0.001 0.001 0.005 1 0.001 L 0.001 0.170 1 0.001 0.001 1 0.078 NR NR 6 6 NR NR NR NR NR NR 22.5 NR NR NR 0.290 1 0.001 0.016 0.890 1 0.24 0.078 0.380 0.001 0.001 0.230 1 0.083 0.078 1 0.450 0.035 1 1 0.086 149 For the light fed groups there was also a main effect of diet composition for Fas expression, with higher levels for the chow fed group (two way ANOVA, Table S1). 4.6.2 Brown adipose tissue Similar to the soleus muscle most of the studied metabolic genes in BAT did not show rhythmicity in both chow and fcHFHS under ad libitum feeding conditions. In contrast to soleus muscle Hsl (Fig not shown), Srebp1c and Pgc-1α expression in BAT showed rhythmicity under ad libitum conditions (p=0.036, p=0.024 and p=0.001, respectively) (Fig 3e & 3c respectively, Table 2). Srebp1c lost rhythmicity in both light and dark chow fed condition while Pgc-1α lost rhythmicity in the chow light fed group (Fig: 3c). Under TRF to either dark or light phase a few genes gained rhythmicity, such as Pparα in both chow and fcHFHS dark fed groups (p=0.016 and p=0.004). Similarly Lpl and Hsl (p=0.002 and p=0.001) both show rhythmicity in the light fed chow group, where the acrophase of Hsl is shifted by almost 12 hours. Additionally some genes upon dark feeding with the fcHFHS diet gained rhythmicity, such as Srebp1c, Glut4 and Ucp1 (p=0.013, p=0.007 and p=0.023, respectively). A significant effect of diet composition as well as a significant interaction between diet composition and time were found for Pgc-1α in the ad libitum fed groups (Diet p=0.028 and Diet*Time p=0.011, two way ANOVA Table S2) and for Pparα dark fed groups (Diet p=0.016 and Diet*Time p<0.001, two way ANOVA, Table S2). Glut4 showed a significant interaction between diet composition and time for the dark fed groups (p<0.001, two way ANOVA Table S2). 5. Discussion Many recent studies have investigated the effects of disturbed rhythms on energy metabolism by focusing on (clock) gene expression in liver and WAT (Salgado-Delgado et al., 2010; Hatori et al., 2012; Reznick et al., 2013). Here we investigated the effects of different TRF paradigms as well as diet composition on (clock) gene expression rhythms in the soleus SM and BAT, two tissue types also important for energy metabolism but often overlooked. 150 Table 2 Effects of diet and timing of food intake on daily rhythms in clock and metabolic gene expression in BAT. Data was analyzed by JTK Cycle. The acrophase (in ZT) is only given for genes that are rhythmically expressed (p<0.05). NR = non-rhythmic. JTK cycle analysis for BAT Genes BAT Clock Bmal1 Per2 Rev-erbα Cry1 Cry2 DBP Metabolic Srebp-1c Glut4 Ucp1 Pgc1α Pparα Fas LPL HSL CHOW Acrophase HFHS P-value Acrophase P-value Ad lib 22.5 13.5 9 21 12 12 D 0 16.5 NR 21 12 12 L 4.5 21 NR 0 21 19.5 Ad lib 0.001 0.001 0.001 0.001 0.001 0.001 D 0.001 0.001 1 0.001 0.034 0.001 L 0.001 0.001 0.092 0.005 0.001 0.001 Ad lib 1.5 16.5 10.5 21 16.5 13.5 D 1.5 16.5 10.5 22.5 13.5 13.5 L 9 0 NR 7.5 NR 21 Ad lib 0.001 0.001 0.001 0.001 0.001 0.001 D 0.001 0.001 0.001 0.001 0.001 0.001 L 0.001 0.001 0.133 0.005 1 0.001 10.5 NR NR 9 NR NR NR 9 NR NR NR 10.5 10.5 NR NR NR NR NR NR NR NR NR 0 22.5 0.024 1 1 0.001 1 0.950 0.264 0.036 1 0.432 1 0.017 0.016 1 0.07 0.253 0.071 0.189 1 0.117 1 1 0.002 0.001 NR NR NR NR NR NR NR NR 13.5 3 7.5 NR 12 NR NR NR NR NR NR NR NR NR NR NR 0.090 1 0.736 1 0.429 1 1 1 0.013 0.007 0.023 0.083 0.004 1 1 1 1 1 0.736 0.844 0.376 1 0.488 0.736 151 Both TRF and diet composition affected daily rhythms in energy metabolism, at the whole body level as well as at the tissue level (SM and BAT).Daily clock gene expression patterns in BAT and SM tissue were strongly affected by TRF and to a lesser extent by diet composition, with clock gene rhythms in SM being completely abolished by daytime TRF whilst shifted in BAT. 5.1 Altered feeding behavior leads to desynchrony within and between peripheral clocks, whilst diet composition mainly affects whole body metabolism The effects of TRF and diet composition on mRNA expression patterns were different between SM and BAT, clearly indicating that these tissues are differently regulated by the same Zeitgebers, feeding behavior and diet composition in this case. These results are in line with previous TRF experiments in rats, as it was shown that TRF has different effects on clock gene rhythms in muscle compared to those in liver (Reznick et al., 2013; Opperhuizen et al., 2016). In the liver, daytime TRF shifts most clock genes by approximately 12 hours (Damiola et al., 2000; Yamajuku et al., 2009; Salgado-Delgado et al., 2013). Clock gene expression rhythms in muscle on the other hand are mostly obliterated by daytime TRF (Reznick et al., 2013; Opperhuizen et al., 2016). Here we confirm the disruptive effects of daytime TRF on muscle clock gene rhythms. On the other hand, clock gene expression rhythms in BAT remained rhythmic (although with a ~12h shift) upon daytime TRF as was also shown in mice (Zvonic et al., 2006; Hatori et al., 2012), further adding to the notion that different tissue types are regulated differently by the same Zeitgeber. Clock gene rhythms in BAT became more pronounced with the fcHFHS diet, which correlates to the larger L/D difference in RER seen in the fcHFHS-fed groups. Consuming the fcHFHS diet also seemed to strengthen the rhythm of several clock genes in SM, in a geneand TRF-dependent manner. For example, in the light fed group on a fcHFHS diet, Bmal1, Cry1 and Rev-erbα remained rhythmic in contrast to those in the chow fed group. This finding implicates that not all components of the molecular clock are regulated similarly within the same tissue. 152 5.2 Different Zeitgebers in skeletal muscle tissue The above data show that metabolic genes in muscle react to changes in feeding behavior to a similar extent as metabolic genes in BAT, but that clock genes in SM clearly are differently affected as compared to BAT. These data again indicated that metabolic genes seem to be controlled more by behavior and hormonal rhythms than the local tissue clock (Su et al., 2016a). It seems plausible that different Zeitgebers affect clock gene expression in a tissuespecific manner. Locomotor activity and exercise have previously been shown to be important Zeitgebers for SM (Dyar et al., 2015). In our study TRF to the light/inactive phase not only changed the timing of food intake, but also caused clear changes in locomotor activity patterns. Therefore, clock gene rhythms in SM could be adjusted less by feeding behavior and putatively more by energy use, e.g., locomotor activity. Of note, although locomotor activity was highest during the light phase, the day/night difference was dampened in the light fed group. This might explain why in SM, unlike in tissues such as liver and BAT, the clock gene rhythms were not inverted by TRF to the light phase. Additionally, entrainment by the SCN or the endogenous peripheral oscillators present in virtually all cells might be differently regulated in different tissues (Yamazaki et al., 2000). Previous experiments by our group have found results consistent with the present study. In an experimental set-up similar to the present study, but with chow fed animals only, a similar loss of rhythmicity of core clock genes in SM was found for animals on a TRF regimen (Opperhuizen et al., 2016). Notably, the muscle examined in Opperhuizen et al. was a different muscle (a mixture of hind leg muscles as opposed to our isolated soleus muscle), indicating that the effects found here are likely not muscle-type specific. A similar result was found in mice in which expression of core clock genes in two different muscle types were directly compared. Expression patterns of core clock genes in the fast tibialis anterior and slow soleus muscle were found to be essentially identical (Dyar et al., 2015). Dyar et al. describe that in both fast tibialis anterior and slow soleus muscles, TRF to the inactive phase shifted the expression peak phase of core genes Bmal1, Per1, and Per2 by around 12h in mice. On the other hand, they report that denervation of the hind limb by sciatic nerve lesions caused relatively minor changes in the expression patterns of most core clock genes, showing that clock gene rhythms are not solely affected by muscle activity. 153 Fig 3. Effect of diet composition and TRF on expression profiles of genes involved in glucose and lipid metabolism (a-g) in SM and BAT tissues. Expression profiles are presented as means±SEM. Tissues were collected at 8 different time points across 24 hours. Shaded areas represent the dark phase. 154 In another study in mice gastrocnemius muscle TRF to the light phase eliminated the rhythm in Per2 expression, but not in other genes, although the amplitude of expression of several clock genes was dampened and only small shifts in acrophase were found (3.46 ± 1.41 hours compared to dark fed animals) (Bray et al., 2013). In their study locomotor activity was found to be mainly nocturnal, in contrast to our experiment. It might well be possible that this persistence of a nocturnal activity pattern acts as a mechanism of retained rhythmic expression in most SM clock genes. Unfortunately, locomotor activity was not reported in the experiments by Dyar et al. Another explanation for the differing results between our study and both Dyar et al. and Bray et al. might be that the duration of the TRF treatment was shorter in those studies, lasting for either 9 days (Bray et al.) or 2 weeks (Dyar et al.) versus 5 weeks in our study. If the arrhythmicity in clock gene expression establishes only after a more prolonged period of TRF, this could also explain the discrepancy between the Dyar and Bray studies. Additionally, in our experimental protocol, the TRF animals only had access to food for 10 hours per day, whilst in both Bray et al. and Dyar et al. the animals had access to food for 12 hours a day. Duration of the fasting period is important as most improvements in metabolic health in rodent studies are seen when food access is limited to 8-12 hours a day (Chaix et al., 2014; Longo and Panda, 2016). Another explanation of the differing results might be a difference between species. In another rat study, chow TRF to the light phase for 3 weeks also resulted in a diminished amplitude of the core clock genes Bmal1 (rhythm lost) and Dbp (still rhythmic) in SM (Reznick et al., 2013). Opposing our activity results, in this study rats maintained a clear nocturnal pattern of activity, albeit with a slight dampening in the normal difference between the light and dark phase, which might explain the differing results in changes in Dbp expression. Interestingly, in the Reznick et al. (2013) study, rats on a HF diet were also subjected to TRF to the light phase. Whilst on a HF diet, the effects of TRF to the light phase on SM core clock expression were less pronounced than whilst on a chow diet. This suggests that increased lipid metabolism resulting from a HF diet in muscles attenuates or rescues the effects of activity at the wrong time of day on the muscle molecular clock and is in line with our results using the fcHFHS diet. Future experiments that can distinguish between the effects of feeding behavior and locomotor activity are needed to reveal the separate contributions of feeding and locomotor 155 activity to the muscle peripheral clock. For example, experiments including a forced mild exercise paradigm could provide more insight into these matters. 5.3 Clinical relevance of diet composition and TRF interventions Total food intake and timing of food intake in relation to TRF and shiftwork have been extensively studied, both in humans and animal models. Several lines of evidence suggest that reinforcing behavioral rhythms, such as through rigid schedules of sleep, exercise or TRF, has beneficial effects on longevity and several parameters of health, including lowered risk of obesity and T2DM (e.g. (Manoogian and Panda, 2016). The exact mechanism of these effects remains to be elucidated, but a prominent role for the circadian clock system can be expected. With respect to the present TRF experiment, it is interesting to note that in both the chow and fcHFHS fed animals, TRF to the dark phase resulted in a more pronounced difference between daytime and nighttime locomotor activity, indicating a less fragmented rhythm. Similar results were seen for RER and heat production, where TRF to the dark phase caused a more pronounced difference between daytime and nighttime RER and heat production, both whilst on the chow and fcHFHS diet. It therefore is tempting to speculate that the beneficial effects that are seen during TRF in animal models result from a more clear distinction between rest and active phase on several physiological parameters such as feeding behavior, metabolism and activity and that this beneficial effect of TRF could also protect against the consequences of an “unhealthy” hypercaloric diet. However, the effects seen could also result from the prolonged (14 hours) periods of fasting, which is also associated with enforcement of stronger behavioral rhythmicity, such as a clearer distinction between the resting and active phase (Manoogian and Panda, 2016). During this prolonged fasting, the body possibly uses up most of its glucose reserves and starts catabolizing more lipids as energy source. Something similar has been shown in mice where TRF during the active phase reduced the fasting glucose level when fed a high caloric diet as well as increased lipid oxidation, proportional with the fasting duration (Chaix et al., 2014). This is also in line with our experiments where the overall 24 hour RER level did not differ between chow groups, whether rats were fed during the light or dark phase or ad libitum. However, in the TRF groups on the fcHFHS diet, the prolonged period of fasting in combination with an increased intake of lipids resulted in 156 an overall lower 24 hour RER. This indicates that regardless of the timing of fasting, fasting has a beneficial effect on overall oxidation of lipids whilst on a high-fat high-sugar diet. 6. Conclusion The interactions found between diet composition and TRF indicate that for rats it matters what they eat and when they eat it. Moreover, these interactions show that the combination of what is eaten and when it is eaten can both attenuate or worsen the effects seen by either diet composition or TRF. This is especially true in skeletal muscle but is not excluded for BAT. Together these data provide further evidence for the occurrence of desynchronization between metabolic tissues as a result of TRF in the light period. Additionally, since the molecular clocks in BAT and SM are differently affected, potentially different mechanisms could be regulating these peripheral clocks. Locomotor activity and (prolonged) fasting are two putative candidates that deserve further studies. 7. Acknowledgements We acknowledge Unga A. Unmehopa and Bernadine Snell for their assistance on the quality control of RNA isolation and RT-qPCR. PdG was supported by a ZonMW TOP grant (#91214047). 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Manoogian, E.N. and Panda, S., 2016. Circadian clock, nutrient quality, and eating pattern tune diurnal rhythms in the mitochondrial proteome, Proc Natl Acad Sci U S A. 113, 3127-9. 160 Table S1: Effect of diet on clock and metabolic gene expression in SM Data was analyzed by two-way ANOVA. Interaction, Time and Diet (chow versus fcHFHS) effects are shown separately for the ad libitum, dark and light fed animals. P is significant (in bold) when p < 0.05. Ad lib Genes (P-value) Two-Way ANOVA (within the TRF ) MUSCLE Dark (P-value) Light (P-value) Time Diet Interaction Time Diet Interaction Time Diet Interaction Bmal1 0.001 0.195 0.488 0.001 0.095 0.699 0.017 0.943 0.082 Per1 0.001 0.316 0.174 0.001 0.284 0.075 0.052 0.106 0.266 Per2 0.001 0.456 0.455 0.001 0.097 0.389 0.982 0.567 0.308 Rev-erbα 0.001 0.949 0.579 0.001 0.907 0.934 0.522 0.161 0.728 Cry1 0.001 0.306 0.012 0.001 0.353 0.847 0.861 0.227 0.005 Cry2 0.101 0.967 0.096 0.123 0.863 0.889 0.673 0.102 0.922 DBP Metabolic 0.001 0.712 0.059 0.001 0.551 0.041 0.024 0.639 0.898 Pgc-1α 0.291 0.011 0.091 0.070 0.436 0.467 0.945 0.338 0.506 PPARα 0.938 0.204 0.470 0.553 0.880 0.666 0.477 0.641 0.631 Fas 0.653 0.654 0.284 0.510 0.393 0.970 0.010 0.005 0.097 PDK4 0.001 0.001 0.275 0.001 0.001 0.001 0.006 0.001 0.594 Srebp-1c 0.053 0.904 0.521 0.004 0.633 0.648 0.019 0.792 0.605 Glut4 0.032 0.552 0.006 0.210 0.268 0.063 0.267 0.895 0.988 Ucp3 0.001 0.006 0.801 0.001 0.001 0.175 0.341 0.001 0.792 Clock 161 Table S2: Effect of diet on clock and metabolic gene expression in BAT. Data was analyzed by two-way ANOVA. Interaction, Time and Diet (chow versus fcHFHS) effects are shown separately for the ad libitum, dark and light fed animals. P is significant (in bold) when p < 0.05. Two-Way ANOVA (within the TRF ) BAT Genes Ad lib (P-value) Time Dark (P-value) Diet Interaction Time Diet 0.001 0.001 0.541 0.956 0.053 Light (P-value) Interaction Time Diet Interaction Clock Bmal1 Per2 0.001 0.001 0.300 0.072 Rev-erbα 0.001 0.419 0.023 0.004 0.189 Cry1 Cry2 0.001 0.001 0.253 0.552 0.004 0.115 0.001 0.008 DBP 0.001 0.191 0.165 0.001 0.011 0.052 Pgc-1α PPARα 0.047 0.233 0.028 0.531 0.011 0.594 0.073 Fas Hsl 0.249 0.234 0.566 0.621 0.351 0.103 0.010 0.189 0.832 Lpl Srebp-1c 0.821 0.174 0.437 0.178 0.543 0.914 Glut4 0.290 0.394 Ucp1 0.612 0.195 0.030 0.069 0.089 0.393 0.001 0.001 0.305 0.003 0.694 0.092 0.001 0.735 0.054 0.060 0.683 0.006 0.294 0.063 0.047 0.071 0.040 0.001 0.096 0.028 0.788 0.080 0.171 0.016 0.784 0.562 0.001 0.493 0.816 0.045 0.230 0.723 0.813 0.303 0.633 0.670 0.060 0.301 0.223 0.253 0.721 0.001 0.113 0.063 0.148 0.006 0.413 0.057 0.408 0.696 0.042 0.691 0.986 0.667 0.979 0.159 0.171 0.009 0.112 0.002 0.001 0.188 0.165 0.344 0.190 0.004 0.490 Metabolic 0.005 162 Table S3. Effects of diet and timing of food intake on Amplitude of clock gene expression in SM. Data was analyzed by JTK Cycle. The amplitude is only given for genes that are rhythmically expressed (p<0.05). NR=non-rhythmic. JTK cycle analysis for BAT CHOW Genes BAT HFHS Amplitude Amplitude Ad lib D L Ad lib D L Bmal1 0.720 0.940 0.430 0.980 1.090 0.660 Per2 0.650 0.670 0.216 0.601 0.702 0.520 Rev-erbα 0.670 NR NR 0.700 0.490 NR Cry1 0.540 0.650 0.255 0.480 0.620 0.320 Cry2 0.180 0.208 0.280 0.206 0.190 NR DBP 0.602 1.275 0.505 0.580 0.980 0.560 163 Table S4 Primer list Genes Forward primer Reverse primer Cyclophillin ATGTGGTCTTTGGGAAGGTG GAAGGAATGGTTTGATGGGT GAPDH TGAACGGGAAGCTCACTGG TCCACCACCCTGTTG CTGTA HPRT1 GCAGTACAGCCCCAAAATGG AACAAAGTCTGGCCTGTATCCAA TBP TTCGTGCCAGAAATGCTGAA TGCACACCATTTTCCCAGAAC Bmal1 CCGATGACGAACTGAAACACCT TGCAGTGTCCGAGGAAGATAGC Cry1 AAGTCATCGTGCGCATTTCA TCATCATGGTCGTCGGACAGA Cry2 TGGATAAGCACTTGGAACGGAA TGTACAAGTCCCACAGGCGGTA DBP CCTTTGAACCTGATCCGGCT TGCCTTCTTCATGATTGGCTG Per1 CGCACTTCGGGAGCTCAAACTTC GTCCATGGCACAGGGCTCACC Per2 CACCCTGAAAAGAAAGTGCGA CAACGCCAAGGAGCTCAAGT Reverbα ACAGCTGACACCACCCAGATC CATGGGCATAGGTGAAGATTTCT Fas CTTGGGTGCCGATTACAACC GCCCTCCCGTACACTCACTC Glut4 GGGCTGTGAGTGAGTGCTTTC CAGCGAGGCAAGGCTAGA LPL CAAAACAACCAGGCCTTCGA AGCAATTCCCCGATGTCCA Pdk4 TGGTTTTGGTTACGGCTTGC TGCCAGTTTCTCCTTCGACA Pgc1α TGCCATTGTTAAGACCGAG GGTCATTTGGTGACTCTGG Pparα TCACACAATGCAATCCGTTT GGCCTTGACCTTGTTCATGT Srebp1c ACAAGATTGTGGAGCTCAAGG TGCGCAAGACAGCAGATTTA Ucp1 AATCAGCTTTGCTTCCCTCA GCTTTGTGCTTGCATTCTGA Ucp3 GCACTGCAGCCTGTTTTGCTGA ATAGTCAGGATGGTACCGAGCA Housekeeping Clock Metabolic 164 165 166 Chapter 5 Expression of the clock gene Rev-erbα in the brain controls the circadian organization of food intake and locomotor activity, but not daily variations of energy metabolism Satish Sen1,3*, Stéphanie Dumont1, Dominique Sage-Ciocca4, Sophie Reibel4, Paul de Goede2, Andries Kalsbeek2,3, Etienne Challet1 1 Regulation of Circadian Clocks team, Institute of Cellular and Integrative Neurosciences, UPR3212, Centre National de la Recherche Scientifique (CNRS), University of Strasbourg, France. 2 Department of Endocrinology and Metabolism, Academic Medical Center (AMC), University of Amsterdam, The Netherlands. 3 Hypothalamic Integration Mechanisms, Netherlands Institute for Neuroscience (NIN), Amsterdam, The Netherlands. 4 Chronobiotron, UMS3415, CNRS, University of Strasbourg, France *Correspondence: ssenbiotech14@gmail.com Running title: Rev-erbα and feeding rhythm Keywords: Nr1d1, circadian rhythm, clock gene, hypothalamus, feeding behavior, energy expenditure. 167 Abstract The nuclear receptor REV-ERBα is part of the molecular clock mechanism and thought to be involved in a variety of biological processes within metabolically active peripheral tissues as well. To investigate whether Rev-erbα (also known as Nr1d1) in the brain plays a role in the daily variations of energy metabolism, feeding behaviour and the sleep-wake cycle, we studied mice with global (GKO) or brain (BKO) deletion of Rev-erbα. Mice were studied both in a light-dark cycle and constant darkness, and 24-h variations of Respiratory quotient (RQ) and energy expenditure, as well as the temporal patterns of rest-activity and feeding behavior were recorded. The RQ increase of GKO mice was not detected in BKO animals, indicating a peripheral origin for this metabolic alteration. Arrhythmic patterns of locomotor activity were only found in BKO mice. By contrast, the circadian rhythm of food intake was lost both in GKO and BKO mice, mostly by increasing the number of daytime meals. These changes in the circadian pattern of feeding behaviour were, to some extent, correlated with a loss of rhythmicity of hypothalamic Hcrt (also named Orx) mRNA levels. Together, these findings highlight that Rev-erbα in the brain is involved in the temporal partitioning of feeding and sleep, whereas its effects on energy metabolism are mainly exerted through its peripheral expression. 168 Introduction Daily variations of behavioral and metabolic processes, such as the sleep-wake cycle and feeding-fasting rhythm, are controlled by a network of circadian clocks in the brain and peripheral tissues. In mammals, the main circadian clock is located in the suprachiasmatic nuclei of the hypothalamus, and is mostly reset by light perceived by the retina (Golombek and Rosenstein, 2010; Brown, 2016). Secondary clocks present in other cerebral regions and peripheral organs (e.g., liver, muscle and pancreas) are adjusted in phase by the suprachiasmatic clock via the autonomic nervous system and endocrine signals (Buijs and Kalsbeek, 2001; Challet, 2015). The secondary clocks can also be shifted by behavioural factors, such as food intake (Schibler et al., 2003; Tahara and Shibata, 2013). The molecular clockwork is based on autoregulatory transcriptional/translational feedback loops that generate rhythmic transcriptional activity with a ~24-h period. In this network, two transcriptional activators, CLOCK and BMAL1, stimulate the expression of Period (Per1-3) and Cryptochrome (Cry1,2) genes, whose proteins in turn can repress the CLOCK-BMAL1 transactivation (Ko and Takahashi, 2006). In addition to these main components, the nuclear receptors Ror(α,β,γ) and Rev-erb(α,β) compete to activate and repress, respectively, the transcription of Bmal1 and Clock, thereby reinforcing the robustness of circadian oscillations (Preitner et al., 2002; Guillaumond et al., 2005; Crumbley and Burris, 2011). The amplitude of the circadian oscillations is further enhanced by targeted degradation of REV-ERBα (Zhao et al., 2016b). Besides its role in the internal timing system, REV-ERBα is also involved in various cellular processes related to lipid metabolism (Feng et al., 2011; Zhang et al., 2016), vascular inflammation (Ma et al., 2013; Sato et al., 2014a) and heme binding (Raghuram et al., 2007; Yin et al., 2007). Together, these results suggest that REV-ERBα is an intracellular integrator of metabolic and circadian pathways (Duez and Staels, 2008a). Mice bearing a global deletion of Rev-erbα display an altered daily balance in fuel partitioning, leading to mistimed alternation between lipogenesis during the active/feeding period and lipolysis during the resting/fasting period (Delezie et al., 2012). However, it is still unclear whether these changes associated with lack of Rev-erbα have a peripheral or central origin. Feeding behavior is strongly organized in time at both ultradian (i.e., meal) and circadian scales (i.e., daily feeding/fasting cycle)(Armstrong, 1980). The regulation of energy balance 169 is based on activation/repression of complex brain circuits controlling energy intake and expenditure. The main components of this neural network include the mediobasal hypothalamus (e.g., arcuate and ventromedial nuclei) and the brainstem (e.g., nucleus of the solitary tract and parabrachial nucleus) (Joly-Amado et al., 2014; Ueno and Nakazato, 2016). These structures are sensitive to circulating metabolic signals from peripheral tissues, such as glucose, non-esterified fatty acids and metabolic hormones (e.g., leptin, insulin and ghrelin) and afferent inputs from the peripheral nervous system. The coupling between the homeostatic regulation of energy metabolism and circadian clocks is not fully understood, but it is thought to involve cellular integrators of metabolic and circadian processes, such as REV-ERBα. Daily changes in food availability elicit rhythmic behavioral, physiological and hormonal changes in anticipation of food access (Patton and Mistlberger, 2013; Tahara and Shibata, 2013). Recent data indicate that brain expression of Rev-erbα largely contributes to the cerebral processes predicting food access because a brain deletion of Rev-erbα prevents these behavioral and thermogenic responses, while a global deletion of Rev-erbα only reduces food-anticipatory behavior and thermogenesis (Delezie et al., 2016). The daily rhythm of food intake and anticipation of food access may share neuronal substrates and functions, raising the possibility that brain REV-ERBα also participates in the temporal organization of the daily feeding pattern. To test whether Rev-erbα expressed in the brain indeed plays a role in the daily variations of energy metabolism and the temporal structure of feeding behaviour, we measured the respiratory quotient, locomotor activity and energy expenditure over 24 hours, and also determined the quantity and organization of spontaneous food intake in mice with either a global or central deletion of Rev-erbα under a light-dark cycle. To establish whether these rhythms are driven by circadian clocks, they were also studied in constant darkness. To further understand the neural substrate underlying the behavioral changes observed qPCRs were performed on several hypothalamic tissues to study clock and metabolic genes. 170 Material and methods Animals and housing conditions The founder heterozygous mice bearing a global deletion of Rev-erbα (GKO) were kindly provided by Prof. Ueli Schibler (University of Geneva, Switzerland) and rederived on a C57BL6J background. The description of the Rev-erbα deletion can be found in (Preitner et al., 2002). Controls of GKO mice were wild-type littermates (WT). The conditional Rev-erbα KO mice were generated at the Mouse Clinical Institute (Strasbourg, France) in the framework of the European EUMODIC consortium (Ayadi et al., 2012). Details for the genesis of this mouse line can be found in (Delezie et al., 2016). To generate brain-specific KO mice, conditional Rev-erbα KO individuals were crossed with NestinCre transgenic mice (Jackson labs, line #003771). To improve the efficiency of brain deletion of Rev-erbα, we generated Rev-erbαfl/gko;Nes-Cre mice, hereafter designated BKO mice, which carry one floxed allele (fl) and one global deleted (gko) allele, so that one Rev-erbα allele is deleted in every cell and in addition, nervous cells do not express Rev-erbα due to Nestin-Cre inactivation of the other Rev-erbα allele (Delezie et al., 2016). Controls of BKO mice were Rev-erbαfl/+;NestinCre littermates (noted CTRL below), which carry one floxed allele (fl) and Cre recombinase transgene under the control of the Nestin promoter, thus impairing expression of only one Rev-erbα allele in nervous cells. Mice were bred within a pathogen-free animal care facility (Chronobiotron platform, UMS 3415, CNRS and University of Strasbourg) in a temperature-controlled room (22 ± 1°C) under 12-h light and 12-h dark (LD 12:12) conditions with lights on at 07:00 (defining Zeitgeber Time (ZT) 0) and lights off at 19:00 (defining ZT12) and 55 ± 5% humidity. Food (Rodent chow, SAFE 105, Augy, France; distribution of metabolizable energy content as percentage: 27% protein, 59% carbohydrate and 14% fat) and UV-treated tap water were provided ad libitum. Two- to 4-month old male mice were individually housed in transparent plastic cages enriched with nest cotton and a piece of wood. Body mass was measured before and after the indirect calorimetry experiment. Body size was measured from snout to beginning of tail. All experiments were performed in accordance with the NIH Guide for the Care and Use of Laboratory Animals (1996), the French National Law (implementing the European Union Directive 2010/63/EU) and approved by the Regional Ethical Committee of 171 Strasbourg for Animal Experimentation (CREMEAS) ) and French Ministry of Higher Education and Research (APAFIS #2533-2015110215078867 v1). Experimental design for indirect calorimetry Mice were kept individually in metabolic cages (floor area: 210 cm2) to measure daily patterns of energy expenditure (EE), respiratory quotient (RQ) by using an open-circuit indirect calorimetry system (Addenfi, Les Cordeliers, France). Concentrations of O2 and CO2 in the outgoing air were successively measured in four different cages. Each cage was sampled every 15 min. The set-up also allowed to study feeding behavior, using an automated weighing system, and locomotor activity, using actimetry plates (i.e., pressure sensors below the cage). In the metabolic cages the same chow pellets and water were provided as in the home cage, but food access was horizontal, instead of vertical, and water was made available in a cup, instead of a bottle. Mice were acclimated to the metabolic cages during 3 consecutive days under LD. Measurements were performed during the 4th and 5th day, the 4th day in LD and the 5th day in constant darkness (DD). Body weight and food left over in the feeder was measured at the end of the experiment. Thereafter, mice were transferred back to their home cages under LD for at least two weeks. Data from animals that lost more than 10% of initial body weight or that ate less than 3 g/day in the metabolic cages were discarded. Final numbers of animals for analysis of calorimetry and feeding behavior were: WT (n=8), GKO (n=4), CTRL (n=8), and BKO (n=6). Tissue and blood collections Groups of WT, GKO, CTRL and BKO mice were sacrificed at ZT5, ZT11, ZT17 and ZT23 (n=4-5 per group and ZT). Mice were injected i.p. with a lethal dose of pentobarbital (200 mg/kg; CEVA, France). An intracardial blood sample was taken with 4% EDTA and brains were sampled and frozen in isopentane at -35°C. Plasma was sampled after blood centrifugation at 4600 g for 10 min at 4°C. The hypothalamus was microdissected from the brain visually, i.e., from the retrochiasmatic level to the hypothalamic posterior region (i.e., excluding the suprachiasmatic region harboring the master clock). According to (Paxinos and Franklin, 2004), the rostrocaudal size of each sample extends from Bregma - 0.9 to -2.5 mm, ± 1.5 mm on each side of the midline (i.e., 3 mm width) and a ventro-dorsal 1.5 mm height 172 from hypothalamic floor. The hypothalamic tissue block, which most likely includes all hypocretin neurons, was immediately frozen in liquid nitrogen and stored at -80°C until mRNA extraction procedure. mRNA extraction and quantitative Real-Time PCR of hypothalamic tissue Frozen hypothalamic tissue blocks from WT, GKO, CTRL and BKO were placed on ice and homogenized in lysis buffer supplemented with β-mercaptoethanol and total RNA was immediately extracted according to the manufacturer’s protocol (RNeasy Mini Kit, Qiagen). RNA quantity and quality were measured using NanoDrop spectrophotometer (ND-1000 Nano0Drop Technologies) and Bioanalyzer (Agilent RNA 6000 Pico kit, Agilent Technologies), respectively. cDNAs were synthesized from 200 ng of total RNA using the SuperScript III Kit (Invitrogen). Quantitative Real-time PCR was performed and analyzed using a Real-time PCR System (7300, Applied Biosystems) with 1X TaqMan Gene Expression Master Mix (Applied Biosystems), 1X TaqMan Gene Expression Assay (Applied Biosystems, see references below) and 1 μL of cDNA in a total volume of 20 μL. PCR conditions were 10 min at 95°C followed by 40 cycles of 15 sec at 95°C, 1 min at 60 °C. PCR reactions were done in duplicate. Relative expression levels were determined using the comparative ΔCT method. Expression levels of all genes of interest were standardized by normalization over the geometric mean of two house-keeping genes, β2-microglobulin and Hypoxanthine-guanine-phosphoribosyl-transferase (Hprt). The following TaqMan Gene Expression Assays (Mm00446968_m1), were used: Rev-erbα (also β2-microglobulin named Nr1d1, (Mm00500226_m1), Mm00520711_g1), Hprt Bmal1 (Mm00500226_m1), Clock (Mm00455950_m1), Period 2 (Per2, Mm00478113_m1), Hypocretin (also named orexin, Hcrt, Mm01964030_s1), Neuropeptide Y (Npy, Mm03048253_m1), Pro-opiomelanocortin (Pomc, Mm00435874_m1), Lipoprotein lipase (Lpl, Mm00434764_m1). Plasma metabolic measurements Plasma glucose was evaluated with GOD-PAP Kit (Biolabo, Maizy, France). Concentrations of plasma non-esterified fatty acids (NEFA) were determined according to the ACS-ACOD Method (NEFA-HR2, Wako, Osaka, Japan). Plasma insulin was assayed with an ultra173 sensitive mouse insulin ELISA kit (CrystalChem, Downers Grove, IL, USA). Levels of plasma leptin were measured with a mouse leptin ELISA Kit (Crystal Chem, Downers Grove, IL, USA). Analysis of feeding pattern and calorimetry For calorimetry analysis, both energy expenditure and respiratory quotient (i.e., ratio of CO2 production over O2 consumption) were calculated using Alab suite program (version 1.55, Addenfi). The same software was used to analyze the microstructure of feeding behavior, including the amount of food consumed, number of eating bouts, number of meals, and meal duration. Meals consisted of one or more eating bouts (i.e., contacts with the feeder comprising at least 0.05 g food intake) separated by an inter-prandial interval of at least 5 min. Thus, a new meal was considered to start if feeding bouts were ≥5 min apart. These criteria are based on (Stengel et al., 2011), except for the minimal amount of dislodged food due to lower precision of the Addenfi scale. Detection thresholds were as follows: 0.05 g for food intake, 5 min for inter-prandial intervals, and 0.1 g/sec for derived detection. Statistical analysis All values are expressed as mean ± SEM. Statistical analysis was performed by SigmaPlot (version 12, Stats software Inc., San Jose, CA, USA). Data were analyzed with one- or two-way analysis of variance (ANOVA) followed by Fisher LSD method and Tukey HSD post-hoc analysis, respectively, when applicable. Significance threshold was at P ≤ 0.05. For assessing daily characteristics of feeding, locomotor activity and respiratory quotient, we used a cosinor analysis to determine mean level, amplitude and acrophase of each rhythm with SigmaPlot. Data were fitted to the following regression:[y = a + b·cos(2π(x − c)/24)] where a is the mean level, b the amplitude, and c the acrophase of the rhythm. Cosinor regressions were considered significant only when the 3 fitted parameters had P ≤ 0.05. 174 Table 1: Mean value data for the Food intake, Body weight, WAT, Body size and WAT /Body weight, comparison between all four genotype. Genotype Food intake (g) Body weight (g) WT GKO CTRL BKO Mean 4.15 4.18 4.20 3.89 Mean 34.69c 33.62a,b 29.85 31.25 SEM 0.41 0.38 0.41 0.14 SEM 0.95 3.85 0.72 1.43 WAT (g) Mean 1.09 1.60 1.11 1.46 SEM 0.15 0.54 0.03 0.23 Body size (mm) Mean 100.37c,d 100.75a,b 92.85 94.50 SEM 0.98 2.01 1.51 1.20 WAT/Body weight Mean SEM 0.031 0.03 0.040 0.01 0.037 0.01 0.046 0.06 Table 1 shows one-way ANOVA comparisons of each parameter (i.e., food intake, body weight, WAT, body size and WAT/Body weight ratio) between WT, GKO, CTRL and BKO mice. a GKO is different from control, b GKO is different from BKO, c WT is different from control and d WT is different from BKO. WAT, white adipose tissue. FIGURE 1. Daily profiles of feeding parameters in mice in light/dark (LD) conditions and constant darkness (DD). Food intake (A, B), number of meals (C, D), meal duration (E, F) and bouts (G, H) in wild-type (WT) mice; mice bearing a global deletion of Rev-erbα (GKO); Control (CTRL) mice; and mice with brain deletion of Rev-erbα (BKO). Black bars represent WT mice; cyan bars represent GKO mice; blue bars represent CTRL mice; and red bars represent BKO mice. Fitted solid and dashed lines represent significant and nonsignificant cosinor regressions, respectively. White and black rectangles on the x-axis represent 12:12-hour LD cycles and dark grey rectangles on the x-axis represent subjective day and subjective night in DD. ~, Effect of time; x, interaction between genotype and time (P < 0.05) 175 Results Temporal feeding pattern in WT and GKO, CTRL and BKO mice Neither body mass, nor daily food intake differed significantly between WT, GKO, control and BKO mice fed ad libitum (Table 1) in keeping with previous reports (Delezie et al., 2012; Delezie et al., 2016). The lower body size in mice expressing NestinCre is in accordance with other studies (Giusti et al., 2014). There was also a trend for increased adiposity in both GKO and BKO mice, as compared to respective controls (Table 1). The daily pattern of food intake (higher at night) was similar with no significant difference in the four genotypes housed under LD, with an acrophase around ZT15. In contrast, after transfer to DD, GKO mice displayed increased food intake during subjective daytime and both GKO and BKO mice lost their circadian rhythm of food intake (Fig 1A & B). Regarding the microstructure of feeding behaviour, the daily rhythm in the number of meals (higher at night) did not differ according to the genotype under LD (Table S1). The peak in the number of daily meals in DD was delayed in BKO compared to CTRL mice, but not in GKO compared to WT mice (Table S2). Meal duration increased at night (peak before midnight) in all genotypes under LD. Both GKO and BKO mice in DD displayed a shift in the daily peak of meal duration (i.e.,~ 2.8 h delay in GKO and ~ 4h delay in BKO, respectively) as compared to their control group (Fig 1E & F, Table S2). The number of eating bouts showed a daily rhythm in the 4 genotypes under LD. After transfer to DD, this rhythm was not markedly changed in GKO mice, but it disappeared in BKO mice (Fig 1G & H, Table S2). Daily variations of energy metabolism The daily pattern of locomotor activity was very similar between WT and GKO mice, except that its amplitude was decreased in GKO under LD, but not in DD. By contrast, BKO mice showed an arrhythmic profile of rest-activity, while CTRL mice displayed a dampened activity pattern, confirming previous observations (Fig 2A & B, Table S3) (Delezie et al., 2016). Mean respiratory quotient (RQ), whose decreased and increased values reflect respectively higher utilization of lipids and carbohydrates, was higher in GKO compared to WT mice under LD, but not in DD. The amplitude of RQ under LD was dampened in BKO as 176 compared to CTRL animals, whereas mean values in DD were increased in BKO mice (Fig 2C & D). Daily variations of energy expenditure were comparable between WT and GKO mice in both LD and DD. By contrast, mean energy expenditure over 24 h and the amplitude of the EE rhythm was consistently reduced in BKO compared to CTRL mice in both LD and DD (Fig 2E & F). FIGURE 2. Daily profiles of physiological parameters in mice in light/dark (LD) conditions and constant darkness (DD). Locomotor activity (A, B), respiratory quotient (C, D) and energy expenditure (E, F). Black bars represent wild-type (WT) mice; cyan bars represent mice bearing a global deletion of Rev-erbα (GKO); blue bars represent Control (CTRL) mice; and red bars represent mice with brain deletion of Rev-erbα (BKO). Fitted solid and dashed lines represent significant and nonsignificant cosinor regressions, respectively. White and black rectangles on the x-axis represent 12:12-hour LD cycles and dark grey rectangles on the x-axis represent subjective day and subjective night in DD. ~, Effect of time (P < .05). AU, arbitrary unit mRNA expression of clock and metabolic genes in brain hypothalamic punches To evaluate the role of Rev-erbα on gene expression in the metabolic hypothalamus, a hypothalamic tissue block was taken excluding the suprachiasmatic nuclei to limit phasedispersion between the master clock and secondary hypothalamic clocks. Daily expression of Rev-erbα was rhythmic with a peak in late daytime in the hypothalamus of both WT and CTR mice, while it was undetectable or at very low levels in GKO and BKO 177 mice, respectively (Fig 3A). As expected by the lack of repressive effects of Rev-erbα on Bmal1 transcription, daily levels of Bmal1 expression were up-regulated in both GKO and BKO animals (P<0.05) as compared to respective controls (WT and CTRL). Rhythmic expression of Bmal1 in WT mice peaked in late night (i.e., ZT22), while Bmal1 expression showed no daily rhythmicity in the other 3 genotypes (namely, GKO, CTRL and BKO) indicating in the case of CTRL that the presence of only one Rev-erbα allele in cells was not sufficient to maintain a rhythmic expression of Bmal1. Daily expression of Clock was rhythmic in WT mice with a peak late night (i.e., ZT21), in phase with that of Bmal1. By contrast, Clock expression lost its rhythmicity in both GKO and BKO mice and tended to show higher daytime values (statistically non-significant). Clock expression was rhythmic in CTRL and WT, although the mean levels of BKO were significantly different from WT and GKO (Table 2). Unexpectedly, a significant rhythmic expression of Per2 was detected in all genotypes without significant changes in the acrophase or amplitude (Tables 2, S4) (Fig 3D). We interpret the rhythmic expression of Per2 as being induced by rhythmic cues from brain clocks outside the sampled tissue block (e.g., suprachiasmatic nuclei) and/or blood. This possibility is supported by the fact that when the liver clock is genetically arrested, hepatic expression of Per2 is still rhythmic due to rhythmic systemic signals (Kornmann et al., 2007). Next, we evaluated the hypothalamic levels of genes coding for orexigenic or anorexigenic peptides. Expression of Hcrt was rhythmic in both control groups (WT and CTRL), albeit the mean levels were down-regulated in CTRL animals. Rhythmicity of Hcrt was lost in both GKO and BKO and expression levels were kept at intermediate values as compared to their respective control groups. Expression of both Npy and Pomc was not rhythmic in any genotype. Mean levels of expression of both Npy and Pomc were higher in WT and GKO, compared to CTRL and BKO mice. Finally, we investigated the hypothalamic levels of Lpl which were found to be constitutively expressed in all genotypes, except in GKO mice that displayed a small-amplitude rhythm with a low mean level of expression (Table 2). Therefore, the up-regulated levels of Lpl mRNA previously observed in the liver, white adipose tissue and skeletal muscle of GKO mice are likely specific of peripheral tissues (Delezie et al., 2012). 178 FIGURE 3. Daily expression of clock, orexigenic, anorexigenic and metabolic genes in the hypothalamus of wild-type (WT) mice; mice bearing a global deletion of Rev-erbα (GKO); Control (CTRL) mice; and mice with brain deletion of Reverbα (BKO) in light/dark (LD) conditions. Expression of clock genes Rev-erbα (A), Bmal1 (B), Clock (C) and Per2 (D); orexigenic genes Npy (E) and Hcrt (G); anorexigenic gene Pomc (F); and metabolic gene Lpl (H). Black circles represent WT mice; a cyan rhombus represents GKO mice; a blue square represents CTRL) mice; and a red triangle represents BKO mice. X, interaction between genotype and time; ~, effect of time; #, effect of genotype (P < .05). Fitted solid and dashed lines represent significant and nonsignificant cosinor regressions, respectively. AU, arbitrary unit Daily pattern in plasma metabolites and hormones The daily pattern of plasma glucose in WT mice, albeit not significantly rhythmic, was comparable to that previously described for ad libitum fed normal mice (e.g., (Ahren et al., 2000; Grosbellet et al., 2015)). Daily levels of plasma glucose in GKO mice were not significantly different from the WT mice, although a trend for increased glycemia was visible in the late night,while 24h glycemia was similarly low during late daytime and early night in both CTRL and BKO mice (Fig 4A; Table S4). A difference in baseline glycemia between Nestin-Cre (CTRL) and mice floxed for another gene has not been reported before (Briancon et al., 2010). 179 Table 2. Cosinor parameters for clock, orexigenic, anorexigenic and metabolic genes in the hypothalamus. WT Gene Bmal1 Reverbα Hcrt Npy Pomc Lpl BKO SEM p Mean SEM p Mean SEM p Mean SEM p a 1.17 0.05 =0.03 1.84αβγ 0.07 =0.600 1.24 0.05 =0.17 1.52δε 0.08 =0.340 b 0.21 0.05 - - - - - - - 22.26 1.07 - - - - - - - 1.02 0.03 1.08 0.02 1.27¥§ 0.03 1.27¥§ 1.31δ£ 0.03 - - 0.13 0.04 - - 1.48γβ 0.07 15.36 1.18 1.01 0.03 1.18 1.13 0.09 a Per2 CTRL Mean c Clock GKO b 0.11 =0.05 0.04 μ =0.63 c a 20.64 1.45€μ b 0.41 0.06 0.28 0.09 0.37 0.08 0.37 0.41 0.14 c a 15.15 0.54 14.57 1.33 14.11 0.88 14.11 17.13 1.03 £ 0.07 0.94 1.58 0.62 1.53 - 0.16 0.30 0.29 0.18 - b c a b c a b c a b c a b c 1.55 0.04 =0.001 &μ 0.05 0.24 9.02 1.56€μ 0.55 21.00 2.53μ 1.42€μ 1.96μ - 0.07 1.18 0.13 0.18 1.30 0.29 0.18 0.15 - 1.05 =0.01 =0.02 =0.20 =0.75 =0.71 - - 1.58γβ 3.88βγα 1.50γβ 1.52βγα - 0.16 0.58 0.23 0.12 - =0.030 - =0.870 =0.380 =0.700 =0.710 §$ 0.05 1.01 0.44 21.87 0.92 0.67 1.38 - 0.10 0.15 1.37 0.12 0.11 0.04 - 1.06 =0.004 =0.030 =0.900 =0.330 =0.090 0.20 =0.11 =0.040 =0.207 Table 2. shows the three fitted parameters of cosinor regressions, including a (the mean level), b (the Amplitude), and c (the acrophase of the rhythm; see Methods for details). For the acrophase, the reference time is Zeitgeber 0 (i.e., lights on). α GKO is different from WT (p< 0.05), β GKO is different from Control, γ GKO is different from BKO, δ BKO is different from WT, ε BKO is different from Control, £ BKO is different from GKO, ¥ Control is different from WT, § Control is different from GKO, μ WT is different from Control, $ Control is different from BKO, & Wt is different from GKO, € Wt is different from BKO (p < 0.05). p values on the right column indicate significance of the cosinor analysis. Nonsignificant parameters are not shown (-). =0.450 =0.300 =0.180 =0.530 180 Plasma levels of NEFA were constant across the day in WT, GKO and BKO mice and rhythmic with a small amplitude in CTRL animals (Fig 4B).Plasma insulin in WT mice showed a significant daily rhythm with increased levels at night, as found in other mouse studies (Kennaway et al., 2013; Grosbellet et al., 2015). In the other 3 genotypes, no significant daily variations were detected for plasma insulin and two-way ANOVA indicates no significant effect of genotype and interaction (p=0.17 and p=0.42, respectively), but did detect an effect of Time (p=0.005) (Table S4). A previous report (Briancon et al., 2010) has suggested a defect in insulin secretion in Nestin-Cre (CTRL) mice that may explain the trend for lower insulinemia at night. Daily levels of plasma leptin were also rhythmic in WT, with a peak around midnight as described previously (Grosbellet et al., 2015), but no significant rhythms were observed in the other 3 genotypes (Fig 4D). A higher daytime leptinemia in Nestin-Cre (CTRL) mice as compared to mice floxed for another gene has also been described previously (Briancon et al., 2010). FIGURE 3. Daily profiles of plasma metabolites in wild-type(WT) mice; mice bearing a global deletion of Rev-erbα (GKO); Control (CTRL) mice; and mice bearing a global deletion of Rev-erbα (GKO) mice in light/dark (LD) conditions. Plasma glucose (A), plasma non-esterified fatty acids (NEFA) (B), plasma insulin (C) and plasma leptin (D). Black circle represents WT mice; a cyan rhombus represents GKO mice; a blue square represents CTRL mice; and a red triangle represent BKO mice. Fitted solid and dashed lines represent significant and nonsignificant cosinor regressions, respectively. White and black rectangles on the x-axis represent 12:12-hour LD cycles. #, Effect of genotype; ~, effect of time (P < .05) 181 Discussion The transcriptional repressor REV-ERBα has been implicated in the molecular basis of circadian clocks and in an array of biological processes within metabolically active peripheral tissues (Zhang et al., 2015). The present study shows that brain Rev-erbα participates in the control of the circadian rhythm in feeding behaviour, as evidenced by the loss of a daily food intake rhythm both in mice lacking Rev-erbα in all cells (GKO) or specifically in neurons (BKO). Loss of the feeding rhythm was detected in constant darkness, but not under a lightdark cycle, demonstrating that constant dark unmasks the inhibitory effect of daytime light on this behavior. The implication of brain Rev-erbα in the sleep/wake activity rhythm was confirmed by the arrhythmic patterns of locomotor activity in BKO mice under both lightdark cycle and constant darkness. The arrhythmic behavior of the BKO animals was also reflected in the reduced amplitude of the rhythms in EE. By contrast, the increase of respiratory quotient (RQ) in GKO mice was not detected in BKO animals, indicative of a peripheral origin for this metabolic change. Daily metabolism Daily variations of energy expenditure were very similar in Rev-erbα GKO and WT mice, while they were reduced in Rev-erbα BKO compared to control mice. The latter most likely is related to the arrhythmic pattern of rest-activity in mice with brain deletion of Rev-erbα. The lack of a clear correlation between the locomotor activity rhythm and energy expenditure may be due to the high sensitivity of the pressure sensors below the cage that we used to detect motor activity. In other words, small movements (e.g. for grooming) will not markedly increase energy expenditure, but will be recorded by the pressure sensors as movements. In terms of rhythmicity, the maintenance of a daily rhythm of RQ in GKO and BKO mice in both LD and DD suggests either that brain REV-ERBα is not critical, or that REV-ERBβ compensates for brain control of RQ rhythm (see below). GKO mice showed higher rhythmic RQ values than those in WT mice, especially under lightdark conditions. This increase reflects a globally lower reliance on fat utilization as an energy source. Previous data indicate that higher RQ values at night in GKO mice may be caused by de novo lipogenesis from dietary carbohydrates (Delezie et al., 2012). A similar effect was 182 not visible in BKO animals, therefore suggesting its peripheral origin. In other words, the RQ change in GKO mice would result from the lack of Rev-erbα in peripheral tissues. Findings comparable to those in GKO mice have been obtained in mice with a global deletion of Bmal1 (Shimba et al., 2011). Given that REV-ERBα is a circadian repressor of Bmal1 transcription, it is surprising that both genotypes lead to analogous metabolic effects, unless they result from an altered clockwork output rather than deletion of a specific circadian gene. The fact that the difference in RQ disappeared in GKO mice transferred to constant dark suggests that light during light-dark cycles exerts direct effects on this outcome. How light would increase RQ during the resting period of GKO mice under light-dark cycles is not clear. Changes in feeding behavior are unlikely to be involved because the lower food intake during the resting phase under light-dark cycles would rather decrease RQ values at that time. Alternatively, putative activation of the sympathetic nervous system by light would rather favour glucose oxidation, thus increasing RQ values. Temporal pattern of rest-activity The circadian control of the rest-activity cycle relies on brain clocks, especially on the master clock in the suprachiasmatic nuclei. Rev-erbα GKO mice display mild alterations in the restactivity rhythm, including a lower amplitude of the activity rhythm under a light-dark cycle (this study) and a shorter free-running period in constant darkness (Preitner et al., 2002). GKO mice also showed altered sleep homeostasis under a light-dark cycle, as evidenced by a slower increase of the homeostatic need of sleep during wakefulness (Mang et al., 2016). In contrast, BKO mice expressed an arrhythmic pattern of rest-activity in both light-dark and constant dark conditions, that is, their circadian behavioral phenotype was much more altered compared to GKO animals, confirming previous observations with another actimetry set-up (Delezie et al., 2016). Previous studies have also noted dissociations between locomotor activity and metabolic rhythms in mice with impaired clocks. In Cry1/2 GKO mice under LD, locomotor activity tends to be arrhythmic, while their daily RQ appears to be rhythmic (Vollmers et al., 2009). Here this distinct effect is probably not due to the differently mutated Rev-erbα and truncated protein products because in both BKO and GKO, the deletion targets the DNA binding domain (i.e., exons 3 and 4) of the Rev-erbα allele (Preitner et al., 2002; 183 Delezie et al., 2016). REV-ERBβ, a transcriptional repressor sharing many properties with REV-ERBα, can compensate some circadian and metabolic functions affected by the knockdown of Rev-erbα, as shown in the liver (Bugge et al., 2012). Therefore, REV-ERBβ in GKO mice may have partly compensated for Rev-erbα deletion during early development. The late ontogenic expression of Nestin in the brain (Dahlstrand et al., 1995) may have precluded compensatory mechanisms in brain structures controlling the rest-activity rhythm in BKO mice, thus explaining their stronger disturbance of the circadian phenotype. Furthermore, behavioral phenotyping of NestinCre mice revealed no changes in levels of locomotion and general exploratory activity during open-field tests (Giusti et al., 2014), or general activity measured in cages with a wheel (Delezie et al., 2016). Here we noted a lower nocturnal activity in control NestinCre mice compared to WT mice, maybe due to the different way locomotion was detected in this study (i.e., pressure sensors instead of infrared beams). At present it cannot be excluded that this behavioral response apparently linked to Nestin-Cre activity may somehow have exacerbated the alteration of rest-activity rhythm in BKO mice. Temporal feeding pattern Normal amounts of food intake were consumed by mice with global or central deletion of Rev-erbα in comparison to respective control littermates. Accordingly, we found no effect of icv injections of the REV-ERBα agonist (GSK4112) on feeding behavior of WT mice (S. Sen and E. Challet, unpublished data). A previous study also reported no change on total daily food intake in mice injected i.p. with REV-ERBα agonists (Solt et al., 2012). Together, these data indicate that Rev-erbα expression in the brain does not play any significant role in the homeostatic regulation of food intake. By contrast, daily patterns of food intake were arrhythmic in Rev-erbα GKO and BKO mice housed in DD, highlighting the involvement of brain REV-ERBα in the circadian control of feeding behavior. Such a behavioral impairment was not detected in light-dark conditions, though. There is a circadian clock in the mouse retina (Besharse and McMahon, 2016) that may also participate in the observed changes. In our opinion, however, this seems unlikely because if the retinal clock was dramatically affected, major effects in behavior and metabolism would be expected not only in DD, but also in LD conditions. In nocturnal 184 rodents, environmental lighting directly modulates food intake, light at night and a dark pulse during daytime being anorexigenic and orexigenic, respectively (Plata-Salaman and Oomura, 1987). A plausible explanation in GKO and BKO mice is thus a masking effect of light during the regular light period in light-dark conditions that will, every day, inhibit food intake during daytime, overwhelming the drive for foraging during the resting period. To date, other strains of mice bearing a mutated clock gene, such as Clock mutation and Staggerer (i.e., mutated Rorα), and those being GKO for clock genes, such as Per1/2 and Cry1/2 KO mice, also show an attenuated diurnal feeding rhythm, arising from almost equal amounts of food eaten during daytime and nighttime (Guastavino et al., 1991; Turek et al., 2005; Adamovich et al., 2014; Kettner et al., 2015). The present data in Rev-erbα BKO further indicate that this behavioral deficit has a central origin that does not rely on impaired peripheral cues. Meal pattern analysis is useful to understand the mechanisms that control feeding behavior. To our knowledge, this study is the first to investigate the microstructure of meal patterns in mice KO for a clock gene. The microstructure data show that the increased food intake of Rev-erbα GKO mice during the subjective day is caused by both an increased number of meals and an increase of their duration, especially during the first halve of the subjective light period. These changes could be related to the orexigenic effect of up-regulated Hcrt mRNA levels in the hypothalamus of GKO mice during daytime. Such diurnal up-regulation fits with the presence of Retinoic acid-related Orphan receptor Response Element (RORE) binding sites for Rev-Erbα in the promoter of the Hcrt gene (Feillet et al., 2017). The arrhythmic pattern of Hcrt expression in both GKO and BKO mice exposed to a light-dark cycle while their feeding pattern is still rhythmic, suggests again that light during daytime may partly have inhibited any increase in eating during daytime, i.e., light is masking the feeding behavior but not hypothalamic neuropeptide expression. Daily expression of mRNA coding for other hypothalamic neuropeptides involved in food intake (i.e., Npy and Pomc) did not display changes that could account for increased daytime food intake, except maybe the trend for enhanced expression of Npy mRNA in GKO mice during late night. The lack of daily fluctuations of Npy and Pomc expression in the hypothalamus has been already reported in rodents (Lu et al., 2002; Ellis et al., 2008; Wang et al., 2017). In BKO mice, the disappearance of the circadian rhythm in food intake is mainly caused by an increased 185 number of meals and eating bouts, during subjective daytime. Additional experiments are needed to investigate the circadian expression of hypothalamic neuropeptides in these mice exposed to constant darkness. Together, these behavioral data suggest that expression of Rev-erbα in the central nervous system is critically involved in the timing of the daily feeding rhythm, probably by affecting the hypothalamic orexin system, but not markedly in the integration of gut-derived satiation signals by the metabolic brainstem. Further investigations will be needed to understand in more detail how and in which brain regions REV-ERBα modulates the circadian timing of feeding behavior and the sleep/wake cycle. Acknowledgements We are indebted to Prof. Ueli Schibler (University of Geneva, Switzerland) for kindly providing the founder Rev-erbα+/- mice, and Prof. Rüdiger Klein (Max Planck Institute of Neurobiology, München, Germany) for his donation of the Nestin-Cre line to Jackson Labs. We also thank the European EUMODIC consortium for having generated the Rev-erbα floxed line, and the Institut Clinique de la Souris (ICS, Illkirch-Graffenstaden, France) for having supplied pairs of these mice. This work was supported by doctoral fellowships from “Neurotime” Erasmus Mundus program, European Doctoral College of University of Strasbourg and Eurometropolis of Strasbourg (S.S.), and recurrent grants from Centre National de la Recherche Scientifique, University of Strasbourg (E.C.), and University of Amsterdam (A.K.). Declaration of interest The authors report no conflict of interest. 186 References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. Adamovich Y, Rousso-Noori L, Zwighaft Z, Neufeld-Cohen A, Golik M, Kraut-Cohen J, Wang M, Han X, Asher G (2014) Circadian clocks and feeding time regulate the oscillations and levels of hepatic triglycerides. Cell Metab 19:319-330. 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Food intake Number of meals Meal duration Bouts Respiratory quotient Locomotor Activity Energy Expenditure Two-way ANOVA (Genotype x Time) LD Genotype Time Interaction Genotype = 0.938 = 0.781 = 0.989 < 0.001 = 0.588 = 0.185 = 0.450 < 0.001 = 0.588 = 0.213 = 0.433 < 0.001 = 0.728 = 0.487 = 0.439 < 0.001 = 0.502 = 0.433 = 0.392 < 0.001 < 0.001 < 0.001 = 0.720 = 0.157 = 0.007 = 0.865 = 0.579 = 0.511 DD Time < 0.001 < 0.001 < 0.001 < 0.001 Interaction = 0.301 = 0.064 = 0.391 = 0.372 < 0.001 < 0.001 < 0.001 = 0.646 = 0.163 = 0.541 Table S2: Two-way ANOVA table with p values for the effect of genotype, time and interaction for the gene expression and plasma metabolites. Two-way ANOVA (Genotype x Time) Genes Bmal1 Clock Rev-erbα Per2 Hcrt Npy Pomc Lpl Plasma metabolites NEFA Glucose Insulin Leptin Genotype Time Interaction < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 = 0.021 = 0.372 = 0.046 =0.008 < 0.001 = 0.005 = 0.601 = 0.646 = 0.173 = 0.100 = 0.066 < 0.001 = 0.284 = 0.192 = 0.567 = 0.908 = 0.879 = 0.006 < 0.001 = 0.174 = 0.112 = 0.140 = 0.880 = 0.005 = 0.031 = 0.157 = 0.371 = 0.424 = 0.096 190 Table S3: Parameters of cosinor regression of 24 h feeding patterns in LD and DD conditions. LD a b Food intake c a b No. of meals c a b Meal duration c a b c Bouts DD a b Food intake c a b No. of meals c a b Meal duration c a b c Bouts WT Mean SEM 0.17 0.01 0.14 0.02 17.48α 0.70 0.57 0.05 0.33 0.06 16.43 0.74 7.76 0.80 6.99 1.14 17.57αδ 0.62 50.15 5.04 41.64 7.13 17.51αδ 0.65 WT Mean SEM 0.16 0.01 0.12 0.02 15.91 0.70 0.60 0.04 0.42 0.06 15.34 0.57 8.02 0.89 7.60 1.26 15.92δ 0.63 46.30 4.87 41.57 6.90 15.92 0.63 GKO p Mean SEM 0.001 0.17 0.02 0.11 0.03 16.83β 0.95 0.001 0.63 0.06 0.37 0.08 16.16 0.90 0.001 7.43 0.93 5.75 1.31 16.41 0.87 0.001 51.60 5.82 39.44 8.23 15.60 0.79 p Mean 0.001 0.29 0.001 0.71 0.32 13.19 0.001 9.13 4.59 13.16 0.001 40.97 33.62 14.30 GKO SEM 0.05 0.07 0.10 1.27 1.23 1.72 1.43 5.50 7.78 0.88 CTRL p Mean SEM 0.005 0.17 0.02 0.14 0.03 15.45 0.81 0.003 0.55 0.04 0.05 0.06 14.61 0.50 0.002 8.22 1.31 9.96 1.85 13.18 0.71 0.001 45.87 6.00 52.81 8.50 13.35 0.61 CTRL p Mean SEM 0.060 0.17 0.02 0.16 0.03 13.71 0.75 0.014 0.57 0.04 0.48 0.06 14.18 0.50 0.033 7.62 1.09 6.98 1.54 12.60 0.84 0.001 42.61 6.12 43.61 8.66 13.47 0.75 BKO p Mean SEM p 0.001 0.16 0.01 0.001 0.13 0.02 13.97 0.74 0.001 0.64 0.05 0.001 0.42 0.08 14.51 0.74 0.001 9.65 1.26 0.001 9.08 1.80 14.34γ 0.75 0.001 55.70 7.62 0.001 40.80 10.78 13.87 1.01 BKO P Mean SEM p 0.001 0.16 0.01 0.001 0.05 0.02 16.08 1.72 0.001 0.71 0.06 0.001 0.31 0.08 16.08 1.04 0.001 11.50 1.68 0.008 7.54 2.38 16.05γ 1.20 0.001 60.10 9.46 0.922 - - - Table S3 shows the three parameters of cosinor regressions, including a (the mean level), b (the amplitude), and c (the acrophase of the rhythm) (see Methods for details). For the acrophase, the reference time is Zeitgeber 0 (i.e., lights on).α WT is different from BKO, β GKO is different from BKO, δ WT is different from control, γ BKO is different control (p < 0.05). p values on the right column indicate significance of the cosinor analysis. Non-significant parameters are not shown (-) 191 Table S4: Parameters of cosinor regression of 24 h locomotor activity and energy metabolism in LD and DD conditions. LD a b Locomotor Activity c a b Respiratory quotient c a b Energy expenditure c DD a b Locomotor Activity c a b Respiratory quotient c a b Energy expenditure c Mean 83.64αδ 65.99δ 16.68 0.91αδ 0.06 14.60 0.72αδ 0.10α 18.96δ Mean 63.91αδ 40.30 17.10 0.88δ 0.07 14.16 0.72αδ 0.09 18.78 WT SEM 13.04 18.44 1.067 0.01 0.01 0.66 0.01 0.01 0.40 p Mean 0.002 56.10θ 45.01 15.85 0.001 0.94βθ€ 0.07 13.77β 0.001 0.72θβ 0.09 18.31 GKO SEM 8.02 11.34 0.96 0.01 0.01 0.63 0.01 0.01 0.54 CTRL p Mean SEM 0.007 15.73 2.37 8.50 3.35 14.22 1.50 0.001 0.88 0.01 0.08 0.01 14.87$ 0.30 0.001 0.68$ 0.01 0.11$ 0.01 17.50 0.25 WT GKO SEM p Mean SEM p Mean 7.73 0.001 59.76β 7.40 0.003 41.98 10.93 36.17 10.46 29.79 1.03 15.82 1.10 16.54 0.01 0.001 0.89θ 0.01 0.001 0.86 0.01 0.09 0.01 0.06 0.40 14.16 0.40 14.48 0.01 0.001 0.75βθ€ 0.01 0.001 0.70 0.01 0.10 0.01 0.09 0.45 18.23 0.57 17.57 p Mean 0.042 42.35 0.001 0.88 0.05 1.80 0.001 0.68 0.06 17.99 CTRL SEM p Mean 8.74 0.050 25.88 12.36 - 1.58 - 0.01 0.001 0.87 0.01 0.08 0.28 13.80 0.01 0.001 0.69 0.01 0.06 0.32 18.09 BKO SEM 6.67 0.01 0.01 0.44 0.01 0.01 0.37 p 0.980 0.001 0.001 BKO SEM p 5.12 0.310 0.01 0.01 0.23 0.01 0.01 0.40 0.001 0.001 Table S4 shows the three parameters of cosinor regressions, including a (the mean level), b (the amplitude), and c (the acrophase of the rhythm) (see Methods for details). For the acrophase, the reference time is Zeitgeber 0 (i.e., lights on).α WT is different from BKO, β GKO is different from BKO, δ WT is different from control, θ GKO is different from control, € GKO different from WT, $ control is different from BKO (p < 0.05). p values on the right column indicate significance of the cosinor analysis. Non-significant parameters are not shown (-). 192 193 194 Chapter 6 Discussion and perspectives 195 Discussion and perspectives There is ample experimental evidence for a number of direct links between circadian clocks and energy metabolism. Many studies also provided arguments that not only disturbances in energy metabolism, but also in the circadian clock system may result in metabolic disorders such as diabetes, obesity, cardiovascular disease, and hypertension. The important role for the circadian timing system in the regulation of energy metabolism is clearly illustrated by the fact that KO or mutations of clock genes lead to a wide array of metabolic dysfunctions. Vice versa many aspects of feeding behavior and diet composition can affect the circadian clock system. One major factor affecting the circadian clocks is the timing of food intake. Restricted feeding at an unusual time of day resets the phase of many peripheral clocks, but not that of the central SCN clock (Damiola et al., 2000). However, when restricted feeding is combined with caloric restriction it may also affect the central SCN clock. The free choice high-fat high-sugar diet has been shown to disturb energy homeostasis as well as the circadian timing system, ultimately resulting in the metabolic syndrome. When mice are offered the high fat diet only during nighttime (i.e., the normal feeding period in mice), this prevents dietinduced metabolic diseases despite an unchanged total caloric intake (Hatori et al., 2012). To further and better understand the relationships between the circadian clock system, feeding behavior and energy metabolism, my PhD work has focused on the following objectives: 1. To study the consequences of the timing of feeding, caloric content and diet composition on the function of the circadian clock system in rats and mice. 2. To assess the impact of a genetic invalidation of the clock gene Rev-erbα on feeding behavior and energy metabolism in mice. We first investigated the effects of an absence of a clear day/night rhythm in feeding behavior on locomotor activity, physiology, and metabolism of both mice and rats by imposing a 6meals-a-day feeding schedule. We found that a 6-meals-a-day feeding schedule led to different effects on the circadian timing system in mice and rats. In mice, the 6-meal feeding schedule affected both the central and peripheral clocks, while in rats this schedule differentially modified the peripheral clocks, but not the central clock in the SCN. These differential effects most likely are due to distinct degrees of caloric restriction. Second, we studied the effects of restricted feeding with or without access to a free choice high-fat high196 sugar diet on two peripheral metabolically active tissues, namely skeletal muscle and brown adipose tissue. In both these tissues, the circadian clocks responded to the light-restricted feeding, but in a different way. Third, we assessed whether and how a genetic disturbance of the molecular clockwork (i.e., KO of the clock gene Rev-erbα) affects feeding behaviour and energy metabolism in the mouse. Our results revealed that the lack of Rev-erbα expression in the brain leads to altered food intake rhythms in constant darkness and arrhythmicity in locomotor activity. By contrast, expression of Rev-erbα in peripheral tissues is involved in the regulation of the respiratory quotient. In the following section, I provide a detailed discussion and perspectives for each chapter. Discussing the effects of a 6-meals-a-day feeding schedule on the central and peripheral clocks The idea to carry out this experiment was based on the effects seen when mice were subjected to a single hypocaloric restricted feeding opportunity, producing a phase shift in the rhythmic expression of the clock output protein AVP within the SCN (Mendoza et al., 2007a). To understand whether this change in the SCN clock of mice was due to the metabolic cues arising from the strong synchronizing effects of the single restricted meal timing or from the hypocaloric condition (i.e., independently of synchronizing effects of meal time), we abolished the daily timing component by offering the mice 6 feeding opportunities equally spaced over the 24-hour light/dark cycle, combined or not with caloric restriction. We then investigated behavioral and physiological rhythmic parameters, together with expression of clock and metabolic genes in the liver as well as expression of clock proteins in the SCN. In chapter 2 we assessed the consequences of the 6-meals-a-day feeding schedule (i.e., one meal every 4 h) in mice. Unexpectedly, the 6-meals-a-day feeding schedule resulted in circadian desynchronization of both the central (i.e., SCN) and peripheral (i.e., liver) clocks. In view of the different individual responses to this feeding paradigm, we categorized the mice into two groups according to their body mass loss: mice having lost less than 10% of their body mass as compared to their initial body mass during ad libitum feeding being called the isocaloric group, and those having lost 10% or more (<25%) being called the hypocaloric group. A clear effect of the 6-meal feeding schedule on the central clock in SCN was seen in both the isocaloric and hypocaloric groups. Expression of the central clock output protein 197 AVP lost its rhythmicity and was upregulated, while expression of the clock proteins PER1 and PER2 was down-regulated. These changes in the SCN clock most likely are due to the ultradian feeding paradigm, since in another study in mice it was shown that timed hypocaloric feeding caused phase advances in the clock protein PER1 and the clockcontrolled protein AVP and increased the amplitude of PER2 in the central clock (Mendoza et al., 2007a). Hence, the ultradian feeding schedule and hypocaloric feeding have a different impact on the SCN. Caloric restriction has a major impact on body physiology resulting in decreased body mass, phase changes in the locomotor activity rhythm and decreased body temperature (Nagashima et al., 2003; Mendoza et al., 2008b; Tokizawa et al., 2015). Mice under hypocaloric ultradian feeding conditions showed similar changes, notably by presenting hypothermia to conserve energy. Restricted feeding also modified the daily pattern of locomotor activity. In diurnal rodents, hypocaloric feeding shifted the behavioral output of SCN clock with a phase delay of locomotor activity pattern (Mendoza et al., 2012b), while nocturnal rats became partially diurnal under both restricted feeding (1 single meal/day) and a hypocaloric 6-meals-a-day feeding schedule (1 meal every 4 h) (Challet et al., 1997a; Mendoza et al., 2008b). These effects are very comparable to those observed in the hypocaloric group of mice on the 6meals-a-day feeding schedule that also became partially diurnal. These findings resemble those found in mice challenged with the work-for-food paradigm (Hut et al., 2011; van der Vinne et al., 2014). Hence restricted feeding combined with caloric restriction shifts the daily locomotor activity rhythm in nocturnal animals in such a way that they become more diurnal. The daily profile of plasma glucose levels was altered in 6-meals fed mice, whereas rats under the 6-meals-a-day feeding schedule maintained their daily rhythm in plasma glucose concentrations (La Fleur et al. 1999). Therefore, also the arrhythmicity in daily plasma glucose concentrations in mice is possibly due to the impact of caloric restriction. Ultradian feeding has not only an impact on the SCN clock and clock output, but it also has an effect on the peripheral clock in the liver. The results of chapter 2 highlight phase changes in the expression of liver clock genes in combination with a dampening of their amplitude in mice under the 6-meals-a-day feeding schedule. The daily expression of liver clock genes followed the timing of feeding resulting in a phase change of the liver oscillator when nocturnal mice are fed during daytime. The interesting fact here is that, unlike daytime 198 restricted feeding in mice, which completely reverses the phase of clock gene expression in the liver, the 6-meal feeding schedule resulted in phase advances or delays in the expression of liver clock genes, but not to arrhythmicity of gene expression. This finding using multiple feeding times across the 24 h cycle clearly indicates that daily meals modulate the phase of the liver clock, but do not directly trigger hepatic oscillations in clock genes. Moreover, there are major effects of the ultradian feeding schedule on the expression of metabolic genes in liver. As compared to conditions of feeding ad libitum, the ultradian feeding schedule led to changes in body mass, body temperature and hepatic expression of metabolic genes in both the isocaloric and hypocaloric groups of mice. This indicates that the ultradian feeding schedule in mice represents a metabolic challenge, even in the so-called isocaloric group. For instance, Fgf21 expression was similarly increased in all mice fed with the 6-meal schedules. Metabolic changes, however, were much more marked in the hypocaloric group, as exemplified by increased levels of Pgc1α gene expression and a trend for up-regulated Sirt1 expression in the hypocaloric mice fed according the 6-meals schedule, Sirt1 being a marker of caloric restriction (Hayashida et al., 2010; Orozco-Solis and SassoneCorsi, 2014; Wang et al., 2014). Another objective of this thesis was to compare the effects of the 6-meals-a-day feeding schedule between two species, mice and rats. Therefore, in the third chapter of this thesis, we investigated the differential effects of a 6-meals-a-day feeding regime on the central and peripheral clocks in rats. In contrast to mice in which the ultradian feeding schedule affected the SCN clock, the expression of clock and clock-controlled proteins in the rat SCN was not affected by the 6-meals-a-day feeding schedule, either at the mRNA or protein level. Moreover, the acrophase of the daily clock gene expression rhythms in the peripheral clocks was modified only for a few clock and clock-controlled genes by the 6-meal feeding schedule in rats. More precisely, only Rev-erbα in the liver, Dbp in skeletal muscle, and Bmal1 in brown adipose tissue (BAT) showed a phase-change. On the other hand, the 6-meals-a-day feeding schedule did clearly affect the mean level and amplitude of a number of clock genes in both liver and BAT. The 6 meals-a-day feeding schedule caused differential effects on the expression of the metabolic genes studied in the three peripheral tissues. Especially genes involved in lipid metabolism were affected by the 6-meals-a-day feeding schedule. Thus, this 199 feeding paradigm in rats differentially affects several peripheral tissues, but these changes mostly concern the regulation of genes involved in lipid metabolism. Abolishing the daily rhythm of feeding with the 6-meals-a-day feeding schedule also modified various physiological parameters. Among others it resulted in phase changes in the RER rhythm (~10h), the locomotor activity rhythm (~2h) and the daily rhythm in heat dissipation (~2h) (Figure 16). Figure 16: Outline of the effect of ultradian feeding on SCN and peripheral clocks in mice and rats. Perspectives of chapters 2 and 3 An important follow-up of the present work will be to investigate how the 6-meals-a-day feeding schedule impacts the circadian clocks and metabolism in diurnal rodents, such as Arvicanthis ansorgei. Diurnal rodents more closely resemble the daily activity and physiology of the humans. Therefore, diurnal rodents are better-fitted translational models to study the links between circadian clocks and metabolism, and understand the metabolic disorders arising due to circadian misalignments such as shift work. The daily lifestyle of shift-workers is characterized by feeding at many different times during the L/D-cycle and light exposure at night. Studying the 6-meals-a-day paradigm in diurnal rodents and its effects on metabolism will help to better understand the causes of meal time-induced metabolic dysfunction and 200 hopefully provide new insights to protect humans from circadian misalignment and metabolic disorders resulting from mis-timed eating. In addition, further studies on nocturnal and diurnal rodents fed according the 6-meals-a-day schedule could be performed in relation to sleep quality, to determine whether such a “round-the-clock” feeding pattern alters the quantity, timing and quality of sleep. Caloric restriction is well known to reduce the chance of developing chronic diseases and improve the metabolic state resulting in increased lifespan (Taormina and Mirisola, 2014). In rodents dietary restriction reduces oxidative stress by reducing the generation of reactive oxygen species (ROS) (Walsh et al., 2014). Caloric restriction also modulates the SCN and peripheral clocks (Kondratov et al., 2006; Mendoza et al., 2007a; Patel et al., 2014; Patel et al., 2016b; Patel et al., 2016a). Interesting question is how caloric restriction, when coupled to the 6-meals-a-day feeding schedule, affects ROS production. In other words, does the beneficial effect of caloric restriction depend on a clear day/night rhythm in feeding activity? Furthermore, the comparative effects of timed feeding using a temporal restricted feeding schedule, and removal of the daily feeding-fasting cycle using a 6-meals-a-day feeding schedule need to be investigated at the level of various neurotransmitters and neuropeptides in the SCN (e.g., GABA, neuropeptide Y, serotonin, orexin) and other hypothalamic clocks (i.e., orexigenic and anorexigenic neuropeptides). This new information would be helpful to understand how feeding behavior plays a role in the daily regulation of neuropeptide expression in the hypothalamus Discussing the differential effects of diet composition and time-restricted feeding on various peripheral clocks Shift workers have to cope with repeated or continuous shifts in their sleep-wake cycle and feeding/fasting rhythm. Does such a lifestyle with daily shifts in multiple rhythms have consequences for the body clock and energy metabolism? To answer this question, many studies have been performed using a time-restricted feeding (TRF) protocol to investigate its effect on the SCN and liver clock, especially in mice. To assess the impact of TRF and diet composition on peripheral clocks and metabolism in rats, we performed a detailed study on two other metabolically important tissues, soleus muscle (SM) and brown adipose tissue (BAT). Physiological and metabolic parameters were studied using metabolic cages. The 201 imposed TRF schedules lead to clear alterations in the respiratory exchange ratio (RER), both in the chow and fcHFHS fed groups. Locomotor activity was most profoundly altered in the light-fed groups. In accordance with the study of Opperhuizen et al. (Opperhuizen et al., 2016) clock gene expression lost its rhythmicity in SM when rats had access to chow only during the light period, but maintained rhythmicity with an inverted phase of expression in BAT tissue. The loss of rhythmicity in SM clock gene expression could be due to the dampening of the day-night difference in locomotor activity. As shown previously, locomotor activity and exercise are non-photic zeitgebers for the SM (Dyar et al., 2015). The different responses of the clock genes in SM and BAT indicate that these two tissues respond differently to the same feeding condition (Figure 17). Together with the published data on the effects of TRF on the liver clock these data clearly show a desynchronization of different metabolic tissues, obviously such a desynchronization may be an important reason for metabolic problems. Figure 17: Outline of the effect of time restricted feeding and diet composition on peripheral clocks. 202 Perspectives of Chapter 4 One of the main results of this chapter is that it clearly highlights a differential response of the peripheral clock in metabolically active tissues, in this case SM and BAT. In addition, this study also shows a clear interaction between the effects of feeding time and diet composition, with the SM clock gaining rhythmicity again when on a fcHFHS diet. Further studies will be needed to understand the mechanisms underlying such a gain in rhythmicity of clock genes that is associated with the presence of high fat and/or high sugar in the fcHFHS diet. Both TRF and diet composition had no strong effects on the profiles of metabolic gene expression in either SM or BAT. Further studies at the post-transcriptional, translational, and posttranslational level are needed to provide an insight on the regulation of metabolic proteins by TRF and different diet compositions. Another approach to better understand the chronobiological consequences and metabolic dysfunction of shift workers, and identify the underlying mechanisms, is to study the effects of diet and TRF in diurnal rodents. Discussing the central and peripheral effects of genetic deletion of Rev-erbα on the control of feeding behavior and energy metabolism. In chapter 5 we investigated whether Rev-erbα expression in the brain is involved in the daily variations of energy metabolism and the temporal structure of feeding behavior. To test this hypothesis, we measured respiratory quotient, locomotor activity and energy expenditure and detailed feeding patterns using metabolic cages in mice with a deletion of the clock gene Reverbα and their respective control animals. Moreover, to differentiate between the central and peripheral effects of Rev-erbα deletion, we studied these parameters in mice with a global (GKO) or a brain-specific deletion (BKO), both under a light-dark cycle and in constant darkness. Under light-dark conditions the temporal feeding pattern of GKO and BKO mice was not modified, while under constant darkness it became arrhythmic in both GKO and BKO animals. GKO mice showed an increase in food intake during the subjective day, which was due to an increase in both number and duration of the meals. The change in food intake might be due to upregulated hypothalamic Hcrt expression in GKO. BKO mice displayed arrhythmicity in locomotor activity in both L/D and D/D conditions. This behavioral change 203 was associated with a reduced amplitude in the daily rhythm in energy expenditure, suggesting that Rev-erbα expression in the brain is involved in the control of locomotor activity and feeding behavior. GKO, but not BKO, mice also displayed alterations in the respiratory quotient, indicating that daily variations in fuel utilization involve the expression of Rev-erbα in peripheral clocks. Perspectives of Chapter 5 A logical follow-up of the present study will be to correlate the changes in the circadian feeding pattern with changes in the expression of orexigenic and anorexigenic neuropeptides. Secondly, we will study the daily variations in clock genes in various brain regions, including the SCN, to better understand the arrhythmic locomotor activity pattern in BKO mice. To rule out a role of Rev-erbβ in feeding behavior and energy metabolism, investigating single KO for Rev-erbβ and double KO models of Rev-erbα/β will be needed to understand the relative importance of both Rev-erbs. Because Rev-erbα acts as a repressor of the core clock, also the KO of RORα, which acts as an activator of the core clock, may help to provide more insight in the role of Rev-erbs in the control of energy metabolism and feeding behavior and, more in general, may also help to better define the role of nuclear receptors in the control of feeding behavior (Figure 18). Figure 18: Outline showing the effect of BKO and GKO mice on SCN clock outputs and hypothalamic clocks, metabolic, orexigenic and anorexigenic genes expression. 204 References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. Challet E, Pevet P, Vivien-Roels B, Malan A (1997) Phase-advanced daily rhythms of melatonin, body temperature, and locomotor activity in food-restricted rats fed during daytime. Journal of biological rhythms 12:65-79. Damiola F, Le Minh N, Preitner N, Kornmann B, Fleury-Olela F, Schibler U (2000) Restricted feeding uncouples circadian oscillators in peripheral tissues from the central pacemaker in the suprachiasmatic nucleus. Genes & development 14:2950-2961. Dyar KA, Ciciliot S, Tagliazucchi GM, Pallafacchina G, Tothova J, Argentini C, Agatea L, Abraham R, Ahdesmaki M, Forcato M, Bicciato S, Schiaffino S, Blaauw B (2015) The calcineurin-NFAT pathway controls activity-dependent circadian gene expression in slow skeletal muscle. Molecular metabolism 4:823-833. Hatori M, Vollmers C, Zarrinpar A, DiTacchio L, Bushong EA, Gill S, Leblanc M, Chaix A, Joens M, Fitzpatrick JA, Ellisman MH, Panda S (2012) Time-restricted feeding without reducing caloric intake prevents metabolic diseases in mice fed a high-fat diet. Cell metabolism 15:848-860. Hayashida S, Arimoto A, Kuramoto Y, Kozako T, Honda S, Shimeno H, Soeda S (2010) Fasting promotes the expression of SIRT1, an NAD+ -dependent protein deacetylase, via activation of PPARalpha in mice. Molecular and cellular biochemistry 339:285-292. Hut RA, Pilorz V, Boerema AS, Strijkstra AM, Daan S (2011) Working for food shifts nocturnal mouse activity into the day. PloS one 6:e17527. Kondratov RV, Kondratova AA, Gorbacheva VY, Vykhovanets OV, Antoch MP (2006) Early aging and age-related pathologies in mice deficient in BMAL1, the core componentof the circadian clock. Genes & development 20:1868-1873. Mendoza J, Pevet P, Challet E (2007) Circadian and photic regulation of clock and clock-controlled proteins in the suprachiasmatic nuclei of calorie-restricted mice. The European journal of neuroscience 25:3691-3701. Mendoza J, Drevet K, Pevet P, Challet E (2008) Daily meal timing is not necessary for resetting the main circadian clock by calorie restriction. Journal of neuroendocrinology 20:251-260. Mendoza J, Gourmelen S, Dumont S, Sage-Ciocca D, Pevet P, Challet E (2012) Setting the main circadian clock of a diurnal mammal by hypocaloric feeding. The Journal of physiology 590:3155-3168. Nagashima K, Nakai S, Matsue K, Konishi M, Tanaka M, Kanosue K (2003) Effects of fasting on thermoregulatory processes and the daily oscillations in rats. American journal of physiology Regulatory, integrative and comparative physiology 284:R1486-1493. Opperhuizen AL, Wang D, Foppen E, Jansen R, Boudzovitch-Surovtseva O, de Vries J, Fliers E, Kalsbeek A (2016) Feeding during the resting phase causes profound changes in physiology and desynchronization between liver and muscle rhythms of rats. The European journal of neuroscience 44:2795-2806. Orozco-Solis R, Sassone-Corsi P (2014) Circadian clock: linking epigenetics to aging. Current opinion in genetics & development 26:66-72. Patel SA, Velingkaar NS, Kondratov RV (2014) Transcriptional control of antioxidant defense by the circadian clock. Antioxidants & redox signaling 20:2997-3006. Patel SA, Chaudhari A, Gupta R, Velingkaar N, Kondratov RV (2016a) Circadian clocks govern calorie restriction-mediated life span extension through BMAL1- and IGF-1-dependent mechanisms. FASEB journal : official publication of the Federation of American Societies for Experimental Biology 30:16341642. Patel SA, Velingkaar N, Makwana K, Chaudhari A, Kondratov R (2016b) Calorie restriction regulates circadian clock gene expression through BMAL1 dependent and independent mechanisms. Scientific reports 6:25970. Taormina G, Mirisola MG (2014) Calorie restriction in mammals and simple model organisms. BioMed research international 2014:308690. 205 18. Tokizawa K, Yoda T, Uchida Y, Kanosue K, Nagashima K (2015) Estimation of the core temperature control during ambient temperature changes and the influence of circadian rhythm and metabolic conditions in mice. J Therm Biol 51:47-54. 19. van der Vinne V, Riede SJ, Gorter JA, Eijer WG, Sellix MT, Menaker M, Daan S, Pilorz V, Hut RA (2014) Cold and hunger induce diurnality in a nocturnal mammal. Proceedings of the National Academy of Sciences of the United States of America 111:15256-15260. 20. Walsh ME, Shi Y, Van Remmen H (2014) The effects of dietary restriction on oxidative stress in rodents. Free radical biology & medicine 66:88-99. 21. Wang C, Huang C, Wei Y, Zhu Q, Tian W, Zhang Q (2014) Short-term exposure to dimethylformamide and the impact on digestive system disease: an outdoor study for volatile organic compound. Environmental pollution 190:133-138. 206 207 208 Summary 209 Summary Energy metabolism and circadian clocks are tightly interconnected. Homeostasis of food intake and energy expenditure is regulated by the brain via a network of nuclei located in the hypothalamus (such as arcuate, paraventricular, dorsomedial and ventromedial nuclei) and brainstem (the nucleus of the solitary tract and parabrachial nucleus). The suprachiasmatic nuclei (SCN) in the hypothalamus function as the master endogenous pacemaker. Its circadian rhythmicity is entrained to the exact 24h rhythm of the outside world via the environmental light/dark cycle. Subsequently, the entrained rhythmicity of the SCN synchronizes daily rhythms in behaviour and physiology, such feeding-fasting, rest-activity, sleep-wake, hormones and metabolites. Moreover, these behavioural and physiological rhythms serve to synchronize all the peripheral clocks to the environmental cues (light and food). The feeding-fasting cycle is one of the most potent synchronizers for the peripheral clocks. Feeding restricted to the resting phase shifts the clock gene expression in various peripheral organs with little or no impact on the central master clock in the SCN. When coupled to caloric restriction restricted feeding (as with a single hypocaloric feeding opportunity in mice) shifts the expression of the clock-controlled protein AVP in the SCN and changes the amplitude of the expression rhythm of several clock genes in the SCN. Even when preventing synchronization to a daily single meal, by using a 6-meals-a-day feeding schedule, hypocaloric restricted feeding in rats results in a phase change of the wheel-running activity and body temperature rhythms. In this thesis, we investigated in mice whether it is the daily timing of the feeding-fasting cycle or the metabolic cues associated with the caloric restriction that impact(s) the central clock in the SCN and peripheral clock in the liver. For this, we challenged the mice with 6-meals-a-day feeding schedule (6 x 15 min, 1 meal every 4 h) abolishing the daily feeding rhythm and studied the behavioural and physiological modifications as well as the changes in expression of clock and clock-controlled genes in both the SCN and liver clock. In the mice challenged with this ultradian feeding schedule we observed different behavioural and physiological responses, depending on their body mass loss (i.e., <10% (isocaloric) or >10% (hypocaloric) of their initial body mass). In both the hypocaloric and isocaloric groups ultradian feeding caused a major impact on the SCN clock, 210 expression of the clock proteins PER1 and PER2 was down-regulated, while expression of the clock-controlled protein vasopressin (AVP) was upregulated and lost its daily rhythmicity. In the hypocaloric group hypothermia was observed concomitant with a phase advance of the locomotor activity rhythm, leading mice to become partially diurnal. By contrast, the isocaloric group maintained its body temperature close to 37 °C and kept a nocturnal pattern in locomotor activity. The daily rhythm in plasma glucose was lost in both the hypocaloric and isocaloric groups. In the hypocaloric group even hypoglycemia was observed. Neither in the hypocaloric nor isocaloric group phase changes were observed in liver glycogen and plasma corticosterone levels when compared with the ad libitum group. Basal corticosterone levels remained unaffected in both the hypocaloric and isocaloric group, while the amplitude in both groups was increased. The higher amplitude of the corticosterone rhythm possibly is due to a lower SCN release of AVP in the hypocaloric and isocaloric groups. Restricted feeding is well known to cause phase-shifts in clock gene expression rhythms in several peripheral tissues. Similarly in our study the ultradian 6-meal-a-day feeding schedule also affected clock gene expression in the liver, as shown by phase advances in the Per2, Reverbα, and Clock expression rhythms. Metabolic genes such as Pparα, Pgc1α, Sirt1 and Fgf21 are closely interconnected and are regulated by the clock. Mean expression level, amplitude and acrophase of studied metabolic genes in the liver were affected by the ultradian 6-meal feeding. Pgc1α expression was upregulated in both the hypocaloric and isocaloric groups while there was a trend for an increased amplitude of Sirt1 expression in the hypocaloric group, similar to what has been observed in fasted mice. Major finding of this chapter is that the lack of a daily feeding rhythm, using the ultradian 6-meal-a-day feeding paradigm, has a major impact not only on the peripheral liver clock but also on the SCN clock. Thus not only the feeding-fasting cycle but also the caloric condition impacts on the peripheral liver clock as well as on the master clock in the SCN. As observed in chapter 2, the ultradian feeding schedule disturbs the SCN and the liver clocks as well as daily rhythms in plasma glucose and other behavioural and physiological functions in mice. Most of these changes were coupled to caloric restriction. Earlier studies showed that the 6-meals-a-day feeding schedule did not affect the daily variation of plasma glucose and insulin rhythms in rats, but increased the plasma corticosterone and triglycerides at certain 211 times of the day. Clock gene expression rhythms in eWAT were maintained with 6 meals feeding whereas many metabolic genes lost their rhythmicity. In chapter 3 we investigated the effect of 6 meals feeding on the central clock in the SCN and on other peripheral clocks along with metabolic gene expression in SM, BAT, and liver in rats. We also measured food intake, body weight, body temperature, and analyzed caloric intake, locomotor activity, respiratory quotient and heat dissipation (metabolic cage). The results of chapter 3 suggest that 6 meals feeding without caloric restriction in rats does not impact the SCN clock machinery at either the transcriptional or translational level. Though the caloric intake and body weight of 6 the meals fed group was lower than ad libitum fed group, the rats continued to increase in body weight, thus indicating they were not hypocaloric. The normal daily RER pattern with oxidation of carbohydrates during feeding (i.e., RER close to 1) and lipids during the resting phase (i.e., RER close to 0.7) was altered in the 6 meals fed group and lost its day-night difference. Clock genes expression rhythms in all three tissues investigated in general remained unaffected by 6-meal feeding, with exception of some clock genes in specific tissues. Most of the studied metabolic genes neither gained nor lost rhythmicity, but some of the lipid metabolizing genes gained or lost rhythmicity upon 6 meals feeding. Lipid metabolizing genes showed differential changes in different metabolically active tissues. Hence, abolition of the daily feeding rhythm with a 6 meals-a-day feeding schedule did not markedly affect clock gene expression rhythms, but did disturb lipid metabolism in various peripheral tissues. Shift-workers show an increased risk for various metabolic diseases such as diabetes, obesity, and cardio-vascular diseases. Feeding is a strong synchronizer of the peripheral clocks, but also working during the resting phase as seen with shift workers may affect the peripheral body clocks. These effects are even worsened when coupled to a high caloric diet such as the high-fat high-sugar diet. To understand the effects of eating at the wrong time-of-day, along with a high caloric diet on the peripheral clock system and energy metabolism, several studies have been performed investigating the effect of diet and time restricted feeding (TRF) on body clocks and metabolism especially in the liver. In chapter 4 we aimed to investigate, in rats, the effects of TRF and diet composition on the brown adipose tissue (BAT) and skeletal muscle (SM) peripheral clocks. During this investigation we subjected the male Wistar rats to 212 a regular chow or free choice high-fat-high sugar (fcHFHS) diet along with TRF during either the light or dark period. In BAT the clock gene rhythms followed the pattern of feeding time during both diets, with the expression patterns shifted in the light fed group as compared with the ad libitum and dark fed groups. Daily rhythms of clock gene expression in BAT were more pronounced with a fcHFHS diet. In SM the studied clock genes lost their rhythmicity in the chow light fed group. During fcHFHS light feeding, some SM clock genes rescued and gained rhythmicity as compared to fcHFHS ad libitum and dark fed groups, though with some phase-shifts. Most of the metabolic genes studied in BAT did not show any effect of diet and TRF, whilst in SM Pdk4 and Ucp3 were expressed rhythmically and phase-shifted in the chow light fed groups. To understand the impact of TRF and diet composition on energy metabolism, we measured caloric intake, level of locomotor activity, heat production and respiratory exchange ratio (RER) using metabolic cages. The caloric intake was not different within the different chow and fcHFHS TRF groups. But the caloric intake was higher in the fcHFHS groups as compared to the chow-fed groups. RER showed a clear day-night difference and TRF during either dark or light phase greatly increased the RER amplitude for both diets. During TRF, RER followed the pattern of feeding in both the chow and fcHFHS groups. A clear day-night difference in locomotor activity was observed in the dark and ad libitum fed groups, but this day-night differences was lost in the light fed group. Heat production also showed clear day-night differences in both the chow and fcHFHS groups. Heat production follows the pattern of feeding, with highest levels during the main period of activity and feeding. During TRF heat production was higher in amplitude during the time of access to food. Hence from this chapter we concluded that BAT and SM, two metabolically active tissues, are affected by both TRF and diet composition. In summary not only eating at the wrong time of day, but also diet differentially affect the peripheral clocks in SM and BAT, leading to desynchronization between these two peripheral clocks. As seen before in chapter 2 and 3, disturbing feeding behaviour by applying ultradian periodicity in food intake affects the central and peripheral clocks. As shown previously, mice with global mutations in clock genes Per1/2 and Cry1/2 displayed no diurnal feeding rhythms. In chapter 5 we investigated the interaction between the circadian clocks and 213 feeding behaviour by using genetically ablated clock gene Rev-erbα mutant mice. For this, we used both the global Rev-erbα (GKO) and conditional brain (BKO) specific Rev-erbα knockout mice and studied the daily pattern of feeding behaviour and energy metabolism under regular light-dark cycles and during constant darkness using metabolic cages. In both GKO and BKO mice, the circadian rhythms of food intake were lost in the constant darkness condition, while daily rhythms were maintained in the light-dark cycle, suggesting a role of brain Rev-erbα in regulating the circadian rhythms of food intake. The implication of brain Rev-erbα in the rest-activity rhythm was shown by the fact that BKO mice displayed arrhythmicity in locomotor activity in both the light-dark and constant dark conditions. The role of Rev-erbα in the control of energy metabolism was shown by the reduced amplitude of energy expenditure in BKO mice and increased respiratory quotient in GKO mice. Thus, expression of the clock gene Rev-erbα in the brain controls the daily rhythms of food intake and locomotor activity, whereas the daily variations in energy metabolism are mainly due to the peripheral expression of Rev-erbα. Conclusion In conclusion, the present thesis shows different aspects of the interactions between circadian clocks, feeding behaviour, diet composition, and metabolism in mice and rats. We investigated the effects of ultradian feeding behaviour on the central and peripheral clocks of rats and mice. We showed that ultradian feeding in mice has major effects on the output of the central SCN clock with an arrest of the release of the clock-controlled protein AVP, as well on the peripheral clocks and energy metabolism. Further studies are needed to see how ultradian feeding will affect daily rhythms in diurnal rodents and their body metabolism. In rats the 6-meals-a-day feeding schedule did not affect the central clock in the SCN at either the transcriptional and translational levels. Expression of clock genes in liver, SM, and BAT was hardly modified by the 6-meal schedule, while expression of genes involved in lipid metabolism was altered in the three peripheral tissues. Thus, this study demonstrated that 6 meals feeding in rats does not affect the SCN clock or peripheral clocks, but has clear effects on lipid metabolism. In will be interesting to investigate whether in rats 6 meals feeding coupled with caloric restriction will also impact the SCN clock. In the 3rd study we found that TRF feeding has a differential effect on clock gene expression in the SM and BAT clocks. 214 The SM clock lost its rhythmicity during chow light feeding, while the BAT clock genes maintained its rhythmicity but shifted its phase as compared to the ad libitum and chow dark feeding groups. The metabolic genes tested in BAT did not show any rhythmic expression with any diet group. In SM Pdk4 and Ucp3 were phase shifted but remained rhythmic in chow light fed. The daily rhythm in locomotor activity followed the pattern of feeding time though with a reduced amplitude in the chow light-fed group and a loss of rhythmicity in the fcHFHS light-fed group. Hence, we conclude that both feeding at the wrong time of day and diet composition affect the peripheral clocks in SM and BAT, but to a different extent and thereby result in desynchronization between various peripheral tissues such as SM, BAT, WAT, and liver. Finally, we investigated the central and peripheral role of the clock gene Rev-erbα in the regulation of food intake and energy metabolism. For that purpose, we analyzed and measured the micro structure of feeding as well as RQ, locomotor activity and energy expenditure in GKO and BKO Rev-erbα mice in light/dark as well as constant dark conditions. We observed that both GKO and BKO lost their daily circadian rhythms of food intake in DD suggesting the involvement of brain Rev-erbα in the circadian control of food intake. An increased RQ was observed in GKO but not in BKO mice, suggesting an involvement of peripheral Rev-erbα in the control of energy metabolism. 215 Samenvatting Energie metabolisme en circadiane klokken zijn nauw met elkaar verweven. De homeostase van voedsel inname en energie verbruik wordt gereguleerd door het brein via een netwerk van kernen in de hypothalamus (zoals de nucleus arcuatus, en de paraventriculaire, dorsomediale en ventromediale hypothalame nuclei) en in de hersenstam (zoals de nucleus van de tractus solitarius en de nucleus parabrachialis). De nucleus suprachiasmaticus (SCN) in de hypothalamus functioneert als de meester of top endogene pacemaker. Zijn endogene circadiane ritme van ongeveer 24 uur wordt gesynchroniseerd met het exacte 24 uurs ritme van de buitenwereld via de licht/donker cyclus in de omgeving. Dit ge-entraineerde SCN ritme synchroniseert vervolgens dagelijkse ritmes in gedrag en fysiologie, zoals de etenvasten, rust-activiteit, en slaap-waak cycli, maar bijvoorbeeld ook ritmes in hormonen, lichaamstemperatuur en metabolieten. Wat licht is voor de centrale pacemaker in de SCN is energie voor de perifere klokken. De eten-vasten cyclus is één van de meest potente synchronisators van de perifere klokken, maar niet van de SCN klok. Wanneer gekoppeld met calorische restrictie kan voedselinname gedurende een beperkte tijd (zoals een eetgelegenheid van een paar uur in muizen) ook de expressie van klok-gecontroleerde eiwitten in de SCN, zoals vasopressine, beïnvloeden, en veranderingen in de amplitude of het expressie niveau van klok genen in de SCN bewerkstellingen. In Hoofdstuk 2 van dit proefschrift hebben we in muizen onderzocht of het de timing van de dagelijkse eten/vasten cyclus is of de metabole verandering geassocieerd met de calorische restrictie, die de centrale klok in de SCN en de perifere klok in de lever verstoord. Hiervoor hebben we muizen onderworpen aan een 6-maaltijden-per-dag voedingsschema om het dag/nacht ritme in eetgedrag uit te schakelen, vervolgens hebben we in deze dieren de gevolgen voor gedrag en fysiologie onderzocht als mede de veranderingen in de expressie van klok- en klok-gecontroleerde genen in zowel de SCN als de lever klok. Het ultradiane 6maaltijden-per-dag eetschema verstoorde zowel de SCN als de lever klok als ook de dagelijkse ritmes in plasma glucose en andere gedrags- en fysiologische functies in de muizen. De meeste van deze veranderingen waren gekoppeld aan de calorische restrictie. De belangrijkste bevinding van dit hoofdstuk is dat het ontbreken van een dag/nacht ritme in 216 eetgedrag, met behulp van het 6-maaltijden-per-dag schema, een sterk effect heeft niet alleen op de lever klok maar ook op de centrale klok in de SCN. In Hoofdstuk 3 hebben we de effecten van het 6-maaltijden-per-dag eetschema op de centrale klok in de SCN en perifere klokken in spier, bruin vet en lever onderzocht in ratten, als mede het effect op een aantal metabole genen. Ook hebben we de effecten op voedsel inname, lichaamsgewicht, lichaamstemperatuur, activiteit, respiratoire quotiënt (RER) en het energie verbruik gemeten in metabole kooien. De resultaten van Hoofdstuk 3 laten zien dat het 6 maaltijden-per-dag schema zonder calorische restrictie in ratten geen impact heeft op het klok mechanisme in de SCN, nog op transcriptie nog op translatie niveau, wel verdween het dag/nacht verschil in het dagelijkse ritme in RER. Klok gen expressie ritmes in alle drie onderzochte weefsels bleven grotendeels intact, met uitzondering van een enkel klok gen in specifieke weefsels. De meeste onderzochte metabole genen verkregen noch verloren hun ritmiciteit, maar vooral een aantal genen betrokken bij het lipiden metabolisme veranderde hun ritmiciteit door het 6-maaltijden-per-dag schema. De afwezigheid van een duidelijk dag/nacht ritme in eetgedrag had dus weinig effect op klok gen expressie in de SCN of perifere klokken, maar veroorzaakte wel een verstoring van het lipidenmetabolisme in verschillende organen. In Hoofdstuk 4 hebben we, in ratten, de effecten van dieet samenstelling voedselinname gedurende een beperkte tijd op de perifere klokken in bruin vet en skelet spier onderzocht. In deze experimenten hadden manlijke Wistar ratten ad libitum dan wel beperkt toegang tot reguliere standaard brokken of een vrije keuze hoog-vet-hoog-suiker (fcHFHS) dieet gedurende alleen de licht of de donker periode. In bruin vet volgden de klok genen het dag/nacht ritme in eetgedrag en verschoof het ritme in de licht groep in vergelijking met de ritmes in de ad libitum en donker gevoerde groepen tijdens beide diëten. In de skelet spier verloren de onderzochte klok genen hun ritmiciteit in de licht gevoerde groep met regulier voer. In de fcHFHS licht groep, behielden of verkregen sommige klok genen hun ritmiciteit in vergelijking met de fcHFHS ad libitum en donker gevoerde groepen, hoewel er wel sprake was van enige verschuiving in de ritmes. De meeste onderzochte metabole genen in het bruin vet werden niet beïnvloed door het dieet of het tijdstip van toegang tot het voer. In de skelet spier vertoonde de expressie van Pdk4 en Ucp3 een duidelijk dag/nacht ritme en een fase217 verschuiving in de licht groepen. Ook RER en energie verbruik vertoonden een duidelijk dagnacht verschil, een beperkte toegang tot het voer overdag of ‘s nachts resulteerde in een sterke toename van deze amplitudes tijdens beide diëten. we vonden ook een duidelijk dag-nacht ritme in algemene activiteit in zowel de donker als ad libitum groepen, maar dit dag-nacht verschil was verdwenen in beide licht groepen. De resultaten van dit hoofdstuk maken duidelijk dat klok gen ritmes in bruin vet en skelet spier, twee metabool actieve weefsels, worden beïnvloedt door zowel het tijdstip van eten als door de dieet samenstelling. Aangezien het tijdstip van eten en dieet samenstelling echter verschillende effecten hebben op de perifere klokken in de spier en het bruin vet, kan eten op het verkeerde moment van de dag resulteren in een desynchronisatie tussen deze twee klokken. In Hoofdstuk 5 onderzochten we de interactie tussen het circadiane systeem en eetgedrag in muizen met een genetische deletie van het klok gen Rev-erbα. We maakten gebruik van zowel globale Rev-erbα knock-out (GKO) muizen als brein specifieke Rev-erbα knock-outs (BKO) en bestudeerden met behulp van metabole kooien in deze muizen het dagelijkse patroon van hun eetgedrag en energie metabolisme in zowel reguliere licht-donker omstandigheden als in continu donker condities. Zowel de GKO als de BKO muizen vertoonden geen circadiaan ritme in eetgedrag meer in de continu donker condities, terwijl deze dag/nacht ritmes in de reguliere licht-donker condities wel aanwezig waren. Deze resultaten suggereren een rol voor Rev-erbα expressie in het brein in het reguleren van het circadiane ritme in eetgedrag. De implicatie van Rev-erbα expressie in het brein in de regulatie van het dag/nacht ritme in algemene activiteit werd duidelijk uit de waarneming dat de activiteit van BKO muizen aritmisch was in zowel de reguliere licht-donker als continu donker omstandigheden. De rol van Rev-erbα in de regulatie van het energie metabolisme bleek uit de afgenomen amplitude van het dag/nacht ritme in energie verbruik in de BKO muizen en de verhoging van de respiratoire quotient in GKO muizen. Expressie van het klok gen Rev-erbα in het brein reguleert dus het dagelijkse ritme in eetgedrag en algemene activiteit, terwijl de dagelijkse variatie in energie metabolisme vooral onder invloed staat van de perifere expressie van Reverbα. Samenvattend, bevestigen de beschreven studies de nauwe relatie tussen het circadiane systeem en eetgedrag, de separate effecten van tijdstip van eten en calorieën op het circadiane 218 systeem en de duidelijke effecten van het circadiane klok systeem op het energie metabolisme. 219 Résumé Le métabolisme énergétique, la prise alimentaire et les horloges circadiennes sont étroitement interconnectés. L’homéostasie de la prise alimentaire et du métabolisme d'énergie est contrôlée par le cerveau via un réseau de noyaux cérébraux situés dans l'hypothalamus basal (comme les noyaux arqués, dorsomédiaux, ventromédiaux et paraventriculaires) et le tronc cérébral (noyaux du tractus solitaire et parabrachiaux). Les noyaux suprachiasmatiques (SCN) de l'hypothalamus contiennent l’horloge circadienne principale, qui synchronise en fonction des facteurs environnementaux (lumière et nourriture) les rythmes journaliers comportementaux et physiologiques (tels que rythme prise alimentaire-jeûne, cycle veillesommeil, rythmes des hormones et des métabolites), ainsi que les horloges périphériques. Le rythme prise alimentaire-jeûne est l’un des synchroniseurs importants des horloges périphériques. La lésion des SCN conduit à une perturbation du rythme de prise alimentaire. Un accès à la nourriture limité à la période habituelle de repos déphase l'expression des gènes d'horloge dans divers organes périphériques sans aucun impact sur l'horloge principale dans les SCN. Cependant, un accès limité à la nourriture, couplé à une restriction calorique (comme dans le cas d’un nourrissage hypocalorique) modifie les profils d'expression des protéines d’horloges et d’une protéine contrôlée par l’horloge (vasopressine, AVP) dans les SCN. En évitant la synchronisation due à un seul repas par jour, la distribution toutes les 4 h d’une ration hypocalorique chez des rats provoque des déphasages des rythmes d’activité locomotrice et de température corporelle. Dans la première étude, nous avons examiné chez des souris si c'était l’effet synchroniseur d’un seul repas hypocalorique ou si c’étaient des facteurs métaboliques liés à la restriction calorique qui affectaient l’horloge principale des SCN. Pour cela, nous avons exposé des souris à un régime de 6 repas de 15 minutes par jour (1 repas tous les 4 h) pour supprimer le rythme journalier de prise alimentaire-jeûne en imposant un rythme ultradien d’alimentation. Nous avons étudié les modifications comportementales et physiologiques, ainsi que les changements d'expression des gènes d'horloge dans l’horloge des SCN et dans l’horloge du foie. Nous avons observé des différences de réponses comportementales et physiologiques en fonction de la perte de masse corporelle des souris (moins de 10 % de perte définissant un 220 groupe isocalorique, et > 10 % définissant un groupe en déficit énergétique, ou hypocalorique). Le rythme ultradien d’alimentation aboutit dans les 2 groupes (hypo- et isocaloriques) à un impact majeur sur l'horloge SCN avec une diminution de l’amplitude des protéines d'horloge PER1 et PER2, et à une surexpression de la vasopressine (AVP) conduisant à une perte de rythmicité journalière. Une hypothermie a été observée dans le groupe hypocalorique, en même temps qu’une avance de phase du rythme d'activité locomotrice, les souris nocturnes devenant partiellement diurnes. En revanche, le groupe isocalorique a maintenu une température corporelle proche de 37 °C et a gardé un patron d'activité locomotrice nocturne. Le rythme de glucose plasmatique a été perdu dans les deux groupes, hypocalorique et isocalorique. Une hypoglycémie a été observée dans le groupe hypocalorique. Par contre, aucun changement de phase n'a été détecté dans les niveaux de glycogène hépatique et de corticostérone plasmatique entre les groupes hypo- et isocalorique comparés au groupe nourri ad libitum. Le niveau basal de corticostérone circulante est resté inchangé tandis que l'amplitude a été augmentée dans les deux groupes, hypocalorique et isocalorique. L’absence de changement du niveau basal de corticostérone pourrait être due à la surexpression de l’AVP dans les SCN des deux groupes expérimentaux. La restriction alimentaire temporelle a provoqué des changements de phase de l'expression des gènes d'horloge dans les horloges périphériques. De la même façon, le régime ultradien d'alimentation à 6 repas a aussi affecté l'expression des gènes d'horloge dans l’horloge du foie, comme le montrent les avances de phase de l’expression de Per2, Rev-erbα et Clock. Les gènes métaboliques comme Pparα, Pgc1α, Sirt1 et Fgf21 étaient étroitement interconnectés et réglés par l'horloge. L'altération des conditions d'alimentation perturbe l'expression des gènes d'horloge, ce qui modifie également l'expression des gènes métaboliques. Le régime ultradien d'alimentation à 6 repas a changé les caractéristiques des oscillations (moyenne, amplitude et/ou 'acrophase) des gènes métaboliques dans le foie. L'expression hépatique de Pgc1α était surexprimée dans les deux groupes, hypocalorique et isocalorique, alors qu'il y avait une tendance à l'augmentation de l'expression de Sirt1 durant l'alimentation ultradienne seulement dans le groupe hypocalorique, suggérant un déficit calorique similaire à celui de souris à jeun. Ainsi, dans ce chapitre, nous avons mis en évidence que l'absence de rythme quotidien d'alimentation, en utilisant un protocole d'alimentation ultradienne à 6 repas, a un impact majeur sur l'horloge SCN et sur la rythmicité 221 quotidienne des gènes d’horloge et des gènes métaboliques dans l'horloge hépatique. Ainsi, les facteurs métaboliques associés à une condition hypocalorique affectent l'horloge principale des SCN et l'horloge secondaire du foie. Comme nous l'avons observé précédemment, une alimentation ultradienne imposée à des souris perturbe l’horloge des SCN et l’horloge hépatique ainsi que les rythmes quotidiens de glucose plasmatique et d'autres fonctions comportementales et physiologiques. La plupart de ces changements ont été associés à la restriction calorique. Des études antérieures ont montré qu’un régime ultradien d'alimentation à 6 repas chez le rat n'affecte pas les rythmes de glycémie plasmatique et d'insulinémie, mais il augmente la corticostérone plasmatique et les triglycérides à certains moments de la journée. Dans le foie et le tissu adipeux blanc, l'expression des gènes d'horloge garde une rythmicité quotidienne avec les 6 repas, tandis que les gènes métaboliques perdent leur rythmicité, indiquant un effet du régime à 6 repas sur le métabolisme lipidique. Fig. 1: Profils journaliers d’expression de protéines d’horloge et d’une protéine contrôlée par l’horloge dans les SCN de souris nourries ad libitum (Cercles blancs), ou avec un régime ultradien isocalorique (Carrés noirs) ou hypocaloriques (Triangles gris foncé). (A) Expression de PER1; (B Expression de PER2; (C) Expression de la vasopressine (AVP). Les courbes en trait continu montrent les régressions sinusoïdales significatives. ~ effet de l’heure du jour (p < 0.05), # effet du nourrissage (p < 0.05) et × interaction entre heure du jour et nourrissage (p < 0.05) Dans la seconde étude, nous avons étudié chez le rat l'effet d’un régime ultradien d'alimentation à 6 repas sur l'horloge centrale et d'autres horloges périphériques (muscle squelettique et tissu adipeux brun), ainsi que l'expression des gènes métaboliques dans ces tissus et dans le foie. Nous avons également mesuré la masse corporelle, la température corporelle et analysé l'apport calorique, l'activité locomotrice, le quotient respiratoire et la perte de chaleur. Les résultats du chapitre 3 suggèrent qu’un régime ultradien d'alimentation 222 Fig. 2 : Profils journaliers d’expression de gènes d’horloge et d’un gène contrôlé par l’horloge dans les SCN de rats nourris ad libitum (Cercles noirs) ou nourris avec un repas ultradien à 6 repas (Triangles gris). (A) Niveaux d’ARNm codant Per1; (B) Niveaux d’ARNm codant Per2; (C) Niveaux d’ARNm codant Avp (D) Niveaux d’expression du neuropeptide vasopressine (AVP). Les courbes en trait continu montrent les régressions sinusoïdales significatives. ~ = effet du Temps (p < 0.05) sans restriction calorique chez les rats n'a pas d'impact sur la machinerie de l'horloge SCN aux niveaux transcriptionnel et traductionnel. Bien que l'apport calorique des rats nourris avec le régime ultradien d'alimentation soit inférieur à celui du groupe nourri ad libitum, les rats en régime ultradien ont continué à augmenter leur masse corporelle, indiquant ainsi que leur balance énergétique est restée positive. Les variations journalières du quotient respiratoire (RER) présentent une avance de phase de 8 h en réponse au régime ultradien d’alimentation, indiquant une augmentation de l’oxydation des glucides et des lipides, respectivement, pendant les périodes habituelles de repos et d’activité. L'expression des gènes d'horloge dans les trois tissus n'a pas été modifiée de façon majeure par le régime ultradien d’alimentation, à l'exception de cas mineurs. Certains des gènes impliqués dans le métabolisme des lipides ont gagné ou perdu de la rythmicité lors de l'alimentation ultradienne à 6 repas. A noter que ces changements étaient différents en fonction des tissus étudiés. Par conséquent, on observe que 223 la perte du rythme journalier d'alimentation n'a pas affecté de manière importante les gènes d'horloge, mais a perturbé le métabolisme des lipides dans les trois tissus périphériques. Fig. 3 : Profils journaliers d’expression de gènes métaboliques dans le foie (Liver), le muscle et le tissue adipeux brun (BAT) chez des rats nourris ad libitum (Cercles noirs) ou nourris avec un repas ultradien à 6 repas (Triangles gris). (A) Srebp1c, Les courbes en trait continu indiquent les régressions sinusoïdales significatives. ~ = effet du Temps (p < 0.05). Comme cela est constaté lors du travail posté, des perturbations de l’horaire des repas affectent les horloges des tissus périphériques, ce qui provoque des dysfonctionnements métaboliques comme le diabète, l'obésité et des maladies cardiovasculaires. L'heure des repas est un puissant synchroniseur des horloges périphériques. Par conséquent, des repas à des horaires inhabituels de même que travailler pendant la phase de repos affectent les horloges secondaires et le métabolisme énergétiques. Ces effets délétères sont même décuplés s’ils sont associés à un régime hypercalorique comme un régime enrichi en sucres et en matières grasses. Plusieurs études de laboratoire ont été menées chez des souris pour comprendre les effets délétères sur l'horloge circadienne et le métabolisme des repas pris à des moments inappropriés (par ex, de jour pour les rongeurs nocturnes) lorsque ces repas sont couplés à un régime hypercalorique. Ces travaux ont surtout été focalisés sur le foie et, dans une moindre mesure, sur le muscle. Nous avons décidé dans la troisième étude d’examiner les effets d’une restriction alimentaire temporelle et de la composition de la nourriture sur les horloges de deux tissus périphériques, le tissu adipeux brun (BAT) et le muscle squelettique chez le rat. Pour cela, nous avons nourri des rats Wistar mâles avec seulement des croquettes standard ou avec un accès au choix à une nourriture enrichie en sucres et en matières grasses (fcHFHS), soit sur 24 h, soit uniquement de jour, soit uniquement de nuit. Dans le BAT, la rythmicité journalière des gènes d'horloge était calée par l’horaire d’accès à la nourriture, car les patrons d’expression ont été décalés chez les animaux nourris de jour par rapport à ceux nourris à 224 volonté ou de nuit. Les rythmes quotidiens des gènes d'horloge sont devenus plus prononcés avec le régime enrichi fcHFHS. Dans le muscle, les gènes d'horloge ont perdu leur rythmicité quand les rats ont été nourris de jour avec des croquettes standard. Quand les rats ingéraient le régime enrichi fcHFHS, quelques gènes d'horloge ont retrouvé une rythmicité qui présentait des changements de phase en comparaison des groupes ayant accès au régime enrichi fcHFHS 24h/24 ou seulement de nuit. Fig. 4 : Analyse de l’activité locomotrice chez des rats placés en cages métaboliques. (a) Différences entre les périodes lumineuses et obscures pour les 3 groupes de rats nourris avec un régime standard (bleu foncé, à gauche : nourriture ad libitum ; bleu clair, au milieu : nourriture de jour ; bleu ciel, à droite : nourriture de nuit). (b) Différences entre les périodes lumineuses et obscures pour les 3 groupes de rats nourris avec un régime enrichi fcHFHS (marron, à gauche : nourriture fcHFHS ad libitum ; rose, au milieu : nourriture fcHFHS de jour ; rouge, à droite : nourriture fcHFHS de nuit). (c) Valeurs moyennes de l’activité locomotrice par 24 h pour tous les groupes (de gauche à droite : bleu foncé, nourriture standard ad libitum ; bleu clair, nourriture standard de jour ; bleu ciel, nourriture standard de nuit ; marron: nourriture fcHFHS ad libitum ; rose: nourriture fcHFHS de jour ; rouge: nourriture fcHFHS de nuit). Les données sont des moyennes ± ET. ns=non significatif, **=p<0.01, ***=p<0.001, ****=p<0.0001, n=10-11 par groupe. Des lettres identiques indiquent des valeurs moyennes similaires. L’activité locomotrice est exprimée en unites arbitraires (AU). ad lib= rats nourris ad libitum, L=rats nourris de jour, D=rats nourris de nuit. Dans le BAT, l’expression de la plupart des gènes métaboliques étudiés n'a été modifiée ni par le régime, ni par la restriction alimentaire temporelle. Au contraire, dans le muscle squelettique, le rythme d’expression des gènes Pdk4 et Ucp3 a été déphasé par l’accès à la nourriture de jour. Pour mieux comprendre l'impact de la restriction alimentaire temporelle et de la composition du régime alimentaire, nous avons mesuré l’apport calorique, le niveau d'activité locomotrice, la production de chaleur et le quotient respiratoire (RER) à l’aide de 225 cages métaboliques. L’ingestion de calories n'était pas significativement modifiée par l’horaire d’accès à la nourriture. En revanche, la consommation calorique était plus élevée dans le groupe ayant accès au régime enrichi fcHFHS en comparaison au groupe nourri seulement avec un régime standard. Les variations de RER montrent clairement des différences jour-nuit. La restriction alimentaire temporelle de jour ou de nuit a considérablement augmenté l'amplitude pour les deux régimes. Pendant la restriction, le RER suit le schéma d'alimentation dans les deux groupes croquettes standard et fcHFHS. La nette différence entre jour et nuit de l'activité locomotrice a été observée chez les groupes nourris avec des croquettes de jour, de nuit ou à volonté ainsi que chez les groupes nourris avec le régime enrichi fcHFHS de nuit ou à volonté En revanche, les différences jour-nuit ont été perdues chez le groupe nourri avec le régime enrichi fcHFHS seulement de jour. Fig. 5: Effet de la composition du régime et de la restriction alimentaire temporelle sur les profils d’exprssion du gène d’horloge Bmal1 dans le muscle squelettique (SM) et le tissu adipeux brun (BAT). Pour chaque tissu, panneau de gauche : courbe bleu foncé, nourriture standard ad libitum (chow ad lib); courbe bleu clair, nourriture standard de jour (chow L); courbe bleu ciel, nourriture standard de nuit (chow D); panneau de droite : courbe marron: nourriture fcHFHS ad libitum (HFHS ad lib); courbe rose: nourriture fcHFHS de jour (HFHS L); courbe rouge: nourriture fcHFHS de nuit (HFHS L). Les données sont des moyennes ± SEM. L’aire grisée représente la phase nocturne. La production de chaleur montre également des différences claires entre le jour et la nuit dans tous les groupes nutritionnels. Pendant la restriction alimentaire, la production de chaleur était plus élevée en amplitude au moment de l'accès des aliments. Autrement dit, la production de chaleur suit le schéma d'alimentation. Par conséquent, à partir de cette étude, nous pouvons conclure que deux tissus métaboliquement actifs, un muscle squelettique et le BAT, sont affectés à la fois par la restriction alimentaire temporelle et la composition du régime alimentaire. En résumé, manger non seulement à des mauvais moments de la journée, mais 226 aussi la composition des aliments affecte différemment les horloges périphériques dans le muscle et le BAT, ce qui conduit à une désynchronisation entre les deux horloges périphériques. Comme nous l'avons vu ci-dessus, les perturbations du comportement alimentaire induites par une périodicité ultradienne des repas affectent les horloges centrales et périphériques. Comme étudié dans des travaux antérieurs, les souris avec des mutations globales des gènes d'horloge Per1/2 et Cry1/2 présentent des altérations des rythmes journaliers d'alimentation. Dans notre quatrième étude, nous avons étudié l'interaction entre les horloges circadiennes et le comportement alimentaire en utilisant une approche génétique avec des souris mutantes pour le gène d'horloge Rev-erbα. Pour cela, nous avons utilisé à la fois les souris knock-out pour Rev-erbα dans tous les tissus (GKO) et d’autres souris présentant une délétion de Rev-erbα seulement dans le système nerveux central (BKO). Fig. 6: Profils journaliers de l’activité locomotrice chez des souris en présence d’un cycle lumière/obscurité (LD) et en obscurité constante (DD). Les histogrammes noirs (panneaux de gauche) représentent les souris sauvages (wild-type: WT); les barres bleu clair représentent les souris porteuses d’une délétion globale de Rev-erbα (GKO); les barres bleu foncé (panneaux de droite) représentent les souris témoins (Contrôles :;CTRL); et les barres rouge représentent les souris porteuses d’une délétion cérébrale de Reverbα (BKO). Les courbes en trait continu indiquent les régressions sinusoïdales significatives. Les rectangles blancs et noirs sur l’axe des X montrent le cycle lumière/obscurité (LD) et les barres grises horizontles figurent l’obscurité constante (DD). ~, Effet du temps (P < .05). AU, unité arbitraire. Puis nous avons étudié le comportement de prise alimentaire quotidienne et le métabolisme énergétique en présence d’un cycle lumière-obscurité et en obscurité constante en utilisant des cages métaboliques. Chez les souris GKO et BKO, les rythmes circadiens de la prise alimentaire ont été perdus en obscurité constante alors qu'ils maintenaient des rythmes quotidiens en présence d’un cycle lumière-obscurité. Ces données suggèrent que Rev-erbα dans le cerveau participe à la régulation des rythmes circadiens de la prise alimentaire. Reverbα dans le cerveau est également impliqué dans le rythme circadien d'activité/repos comme démontré par le fait que les souris BKO ont une arythmie dans l'activité locomotrice dans des 227 conditions de lumière-obscurité et d'obscurité constante. Le rôle de Rev-erbα dans le maintien du métabolisme énergétique est mis en évidence par l'amplitude réduite de la dépense énergétique chez les souris BKO et par l'augmentation du quotient respiratoire chez les souris GKO. Ainsi, l'expression du gène d'horloge Rev-erbα dans le cerveau contrôle les rythmes quotidiens d’alimentation/jeûne et d'activité/repose, mais pas les variations quotidiennes du métabolisme énergétique. Fig. 7: Profils journaliers de la prise alimentaire chez des souris en présence d’un cycle lumière/obscurité (LD) et en obscurité constante ( DD). Les histogrammes noirs (panneaux de gauche) représentent les souris sauvages (wild-type: WT); les barres bleu clair représentent les souris porteuses d’une délétion globale de Rev-erbα (GKO); les barres bleu foncé (panneaux de droite) représentent les souris témoins (Contrôles :;CTRL); et les barres rouge représentent les souris porteuses d’une délétion cérébrale de Reverbα (BKO). Les courbes en trait continu indiquent les régressions sinusoïdales significatives. Les rectangles blancs et noirs sur l’axe des X montrent le cycle lumière/obscurité (LD) et les barres grises horizontles figurent l’obscurité constante (DD). ~, Effet du temps (P < .05); X, interaction entre génotype et temps (P < 0.05). Conclusion En conclusion, la thèse présente montre différents aspects des interactions entre les horloges circadiennes, le comportement alimentaire, la composition du régime alimentaire et le métabolisme chez la souris et le rat. Nous avons étudié les effets du régime alimentaire ultradien sur les horloges centrales et périphériques chez la souris. Nous avons montré que l'alimentation ultradienne chez la souris a des effets majeurs sur le fonctionnement de l'horloge principale avec une altération de l'expression d’AVP, une protéine contrôlée par l'horloge ainsi que sur les horloges périphériques et le métabolisme. Par conséquent, cette étude expérimentale démontre que l'alimentation ultradienne chez la souris affecte à la fois l'horloge principale dans les SCN ainsi que l'horloge périphérique dans le foie. D'autres études seront nécessaires pour établir comment l'alimentation ultradienne 228 affecte les rythmes circadiens et le métabolisme énergétique chez les rongeurs diurnes. Ensuite, nous avons étudié chez le rat les effets possibles de l'alimentation avec 6 repas sur l'horloge principale des SCN et les horloges périphériques dans le foie, un muscle strié et le BAT, ainsi que sur le métabolisme énergétique. Un nourrissage ultradien avec 6 repas chez le rat n'a pas affecté l'horloge centrale des SCN, ni au niveau transcriptionnel, ni au niveau que traductionnel. L'expression des gènes d'horloge dans le foie, le muscle et le BAT a été à peine modifiée par un régime avec 6 repas, tandis que l'expression des gènes impliqués dans le métabolisme des lipides a été altérée dans les trois tissus périphériques. Ainsi, cette étude démontre qu’un régime alimentaire ultradien chez le rat n'affecte pas l'horloge SCN mais a des effets sur les horloges périphériques et le métabolisme des lipides. Dans les expériences à venir, il serait intéressant de coupler un régime à 6 repas avec une restriction calorique chez le rat et d'observer l’impact sur l'horloge des SCN. Ensuite, nous avons étudié les effets différentiels de la composition du régime alimentaire et du moment de l'alimentation sur les horloges périphériques du muscle squelettique et du tissu adipeux brun chez le rat. Diverses études ont fourni la preuve que le régime FcHFHS et la restriction alimentaire temporelle agissent sur les horloges périphériques du foie et des muscles chez la souris. Par conséquent, nous avons étudié l'effet du régime FcHFHS et de la restriction alimentaire temporelle sur les horloges du muscle et du BAT. Nous avons trouvé que la restriction alimentaire temporelle avec des croquettes standard a un effet différentiel sur l'expression des gènes d'horloge dans les horloges du muscle et du BAT. Le muscle a perdu la rythmicité des gènes de l'horloge avec une alimentation de jour, tandis que dans le BAT, la rythmicité des gènes d’horloge était maintenue, mais déphasée par rapport à de la nourriture fournie ad libitum ou seulement de nuit. Les gènes métaboliques ont tous perdu leur expression rythmique dans tous les groupes nutritionnels. Alors que dans le muscle, l’expression de Pdk4 et d’Ucp3 était déphasée, mais restait rythmique avec l’alimentation de jour, Ucp3 perdait sa rythmicité avec le groupe alimenté de jour avec le régime enrichi fcHFHS. L'activité locomotrice des groupes nourris avec des croquettes a suivi le schéma d'alimentation et a maintenu une différence jour-nuit tandis que dans le groupe nourri de jour avec le régime fcHFHS, la différence jour-nuit a été perdue. Par conséquent, nous concluons que l'alimentation au mauvais moment de la journée et la composition du régime perturbent 229 les horloges périphériques dans le muscle et le BAT et conduisent à une désynchronisation entre divers tissus périphériques tels que muscle, BAT, tissu adipeux blanc et foie. Enfin, nous avons étudié le rôle central et périphérique du gène d'horloge Rev-erbα dans la régulation de la prise alimentaire, le schéma d'alimentation et le métabolisme énergétique. Pour ce faire, nous avons analysé et mesuré la prise alimentaire et la microstructure de l'alimentation ainsi que le quotient respiratoire (RER), l'activité locomotrice et la dépense énergétique chez les souris portant une mutation de Rev-erbα dans tous les tissus (GKO) ou restreinte au système nerveux central (BKO). Nous avons conclu que les deux types de mutation GKO et BKO ont perdu les rythmes circadiens de la prise alimentaire en obscurité constante, ce qui suggère que Rev-erbα dans le cerveau joue un rôle dans le contrôle circadien de la prise alimentaire. L’augmentation du RER a été observée chez les souris GKO mais pas chez les souris BKO, suggérant une implication de Rev-erbα dans le contrôle périphérique de cette altération métabolique. 230 SATISH KUMAR SEN Interactions between circadian clocks and feeding behaviour. Résumé Le système circadien muti-oscillant est constitué de l'horloge suprachiasmatique (SCN), l'horloge principale située audessus du chiasma optique dans l'hypothalamus antérieur, et de nombreuses horloges périphériques. L'horloge SCN synchronise les autres oscillateurs périphériques situés dans chaque organe. L'horloge SCN est une horloge circadienne auto-entretenue qui maintient les rythmes quotidiens comportementaux, physiologiques et neuroendocriniens. Les donneurs de temps (zeitgebers), tels que la lumière et la nourriture, sont des synchroniseurs puissants, respectivement pour le SCN et les horloges périphériques. La thèse visait à mieux comprendre les interactions entre les horloges circadiennes et le comportement alimentaire chez les espèces nocturnes. Nous avons montré dans la première et la seconde partie que l'alimentation ultradienne affecte les horloges centrales et périphériques chez la souris et le rat. Dans la première étude, nous avons conclu que l'alimentation ultradienne chez la souris a un impact majeur sur la sortie de l'horloge SCN et sur l'horloge périphérique dans le foie, tandis que dans la seconde étude, l'alimentation ultradienne chez le rat n'a eu pas d'impact sur l'horloge SCN, mais il a modifié les horloges périphériques et le métabolisme des lipides. Dans la troisième partie, nous avons montré des effets différentiels du régime alimentaire et de la restriction alimentaire temporelle sur les horloges périphériques du tissu adipeux brun et du muscle squelettique. Dans la quatrième partie, nous avons démontré un rôle du gène d'horloge Rev-erbα dans le comportement alimentaire et le métabolisme énergétique en comparant des souris porteuses d’une délétion de Rev-erbα, soit globale, soit limitée au système nerveux central. L’ensemble de ces études révèle l'interdépendance des horloges circadiennes et du comportement alimentaire, ainsi que leurs effets sur le métabolisme énergétique. Mots-clefs : Horloge suprachiasmatique, alimentation ultradienne (6 repas), restriction alimentaire, Rev-erbα Abstract The muti-oscillatory circadian system consists of the suprachiasmatic clock (SCN) the master clock, located above the optic chiasm of the anterior hypothalamus, and many peripheral clocks. The SCN clock synchronizes the other peripheral oscillators located in each organ. The SCN clock is a self-sustaining circadian oscillator maintaining the daily behavioural, physiological, and neuroendocrine rhythms. The zeitgebers such as light and food are potent synchronizers for the SCN and other peripheral clocks. The thesis was aimed to understand different aspects of the interactions between circadian clocks and feeding behaviour in nocturnal species. We showed in the first and second parts that the ultradian feeding affects the central and peripheral clocks in mice and rats. In the first part, we concluded that the ultradian feeding in mice has major impacts on the SCN clock output and the peripheral clock in the liver, while in the second part ultradian feeding in rats does not have impact on the SCN clock but it affects peripheral clocks and lipid metabolism. In the third part, we showed the differential effects of diet and time restricted feeding in brown adipose tissue and skeletal muscle peripheral clocks. In the fourth part, we showed the role of clock gene Rev-erbα on feeding behaviour and energy metabolism by comparing between global and brain specific knock-out mice. The present studies reveal the interdependency of the circadian clocks and feeding behaviour, and their effects on whole-body metabolism. Keywords: Suprachiasmatic clock, ultradian (6-meal) feeding, time restricted feeding, Rev-erbα 231 232 Publications Peer reviewed -in thesis  Sen S., Raingard H., Dumont S., Kalsbeek A., Vuillez P., Challet E. (2017). Ultradian feeding in mice not only affects the peripheral clock in the liver, but also the master clock in the brain. Chronobiology International 34: 17-36. doi: 10.1080/07420528.2016.1231689.  Goede P.D.*, Sen S.*, Oosterman J.E., Foppen E., Jansen R., S.E la Fleur., Challet E., Kalsbeek A. (2018). Differential effects of diet composition and timing of feeding behavior on rat brown adipose tissue and skeletal muscle peripheral clocks. Neurobiology of Sleep and Circadian Rhythms 4: 24-33. doi.org/10.1016/j.nbscr.2017.09.002. *Equal contribution  Sen S., Dumont S., Sage-Ciocca D., Reibel S., Goede P.D., Kalsbeek A., Challet E. (2018). Expression of the clock gene Rev-erbα in the brain controls the circadian organization of food intake and locomotor activity, but not daily variation of energy metabolism. Journal of Neuroendocrinology 30: e12557. doi: 10.1111/jne.12557. To be submitted:  Goede P.D.*, Sen S.*, Su Y., Foppen E., Poirel V.J., Challet E., Kalsbeek A. An ultradian feeding schedule in rats differentially affects peripheral clocks in liver, brown adipose tissue and skeletal muscle and lipid metabolism, but not the central clock in SCN. *Equal contribution Peer reviewed -outside thesis  de Vries E. M., Oosterman J.E., Eggink H.M., Goede P.D., Sen S., Foppen E., Surovtseva O.B., Boelen A., Romijin J.A., la Fleur S.E., Kalsbeek A. (2017). Effects of meal composition and meal timing on the expression of genes involved in hepatic drug metabolism in rats. Plos One 12: e0185520. doi: 10.1371/journal.pone.0185520. 233 ACKNOWLEDGEMENTS 234 235