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27 pages, 1592 KiB  
Review
A Glimpse into Humoral Response and Related Therapeutic Approaches of Takayasu’s Arteritis
by Shuning Guo, Yixiao Tian, Jing Li and Xiaofeng Zeng
Int. J. Mol. Sci. 2024, 25(12), 6528; https://doi.org/10.3390/ijms25126528 (registering DOI) - 13 Jun 2024
Viewed by 131
Abstract
Takayasu’s arteritis (TAK) manifests as an insidiously progressive and debilitating form of granulomatous inflammation including the aorta and its major branches. The precise etiology of TAK remains elusive, with current understanding suggesting an autoimmune origin primarily driven by T cells. Notably, a growing [...] Read more.
Takayasu’s arteritis (TAK) manifests as an insidiously progressive and debilitating form of granulomatous inflammation including the aorta and its major branches. The precise etiology of TAK remains elusive, with current understanding suggesting an autoimmune origin primarily driven by T cells. Notably, a growing body of evidence bears testimony to the widespread effects of B cells on disease pathogenesis and progression. Distinct alterations in peripheral B cell subsets have been described in individuals with TAK. Advancements in technology have facilitated the identification of novel autoantibodies in TAK. Moreover, emerging data suggest that dysregulated signaling cascades downstream of B cell receptor families, including interactions with innate pattern recognition receptors such as toll-like receptors, as well as co-stimulatory molecules like CD40, CD80 and CD86, may result in the selection and proliferation of autoreactive B cell clones in TAK. Additionally, ectopic lymphoid neogenesis within the aortic wall of TAK patients exhibits functional characteristics. In recent decades, therapeutic interventions targeting B cells, notably utilizing the anti-CD20 monoclonal antibody rituximab, have demonstrated efficacy in TAK. Despite the importance of the humoral immune response, a systematic understanding of how autoreactive B cells contribute to the pathogenic process is still lacking. This review provides a comprehensive overview of the biological significance of B cell-mediated autoimmunity in TAK pathogenesis, as well as insights into therapeutic strategies targeting the humoral response. Furthermore, it examines the roles of T-helper and T follicular helper cells in humoral immunity and their potential contributions to disease mechanisms. We believe that further identification of the pathogenic role of autoimmune B cells and the underlying regulation system will lead to deeper personalized management of TAK patients. We believe that further elucidation of the pathogenic role of autoimmune B cells and the underlying regulatory mechanisms holds promise for the development of personalized approaches to managing TAK patients. Full article
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<p>Two pathways of naïve B cells into antibody-secreting cells. In the follicular response (<b>left</b>), activated B cells engage in interactions with Th cells and follicle dendritic cells to form GC in secondary lymphoid organs. Following iterative rounds of somatic hypermutation and antigen affinity-driven selection, resting naïve B cells differentiate into antibody secreting cells or switched memory B cells derived from the germinal center. Extrafollicular responses (<b>right</b>) emerge preceding the formation of germinal centers, displaying distinctive phenotypic and transcriptional profiles compared to GC B cells. In healthy individuals, TLR7 and IFN-γ induce resting naïve B cells to differentiate into activated counterparts, DN2 cells and antibody-secreting cells in an IL-21-dependent manner. Neither pathway is T cell-dependent. In particular, the extrafollicular response includes a T cell-independent pathway. In addition, both pathways have mainly been reported in systemic lupus erythematosus. In TAK, the pathogenic role of extrafollicular responses is unknown. Therefore, we have marked a question mark on extrafollicular responses. Th: T helper; FDC: follicle dendritic cell; Mø: macrophage; DN2: double negative 2 cells; Ab: antibody; TLR7: toll-like receptor 7; IFNγ: interferon gamma; IL21: interleukin 21; TAK: Takayasu’s arteritis; GC: germinal center.</p>
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<p>A profile of artery involvement in TAK. In the left part, the color gradient illustrates the typical frequency of arterial segment involvement in TAK, with a predilection for the brachiocephalic arteries, as well as the thoracic and abdominal arterial territories. The right part shows the profile of the peripheral blood and vascular wall of TAK. The pathological process of TAK initiates in the vasa vasorum of the adventitia and is marked by the rupture of elastic laminae and smooth muscle cell migration. Several immune cells including memory B cells, antigen-experienced B cells as well as Tfh cells infiltrate the adventitia. The granulomas are located in the medial layer, and TLOs are distributed deeper within the adventitial layer which involves a dense network of HEVs. TLO: tertiary lymphoid organ; HEV: high endothelial venule; DC: dendritic cell; RBC: red blood cell; Tfh: T follicular helper; TAK: Takayasu’s arteritis.</p>
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<p>Abnormal activation of B cell checkpoints in TAK. The activation of BCRs, TLRs and several co-stimulatory molecules (including CD40, CD80 and CD86) was documented in TAK. Serum APRIL and BAFF levels and cytokines related to humoral immunity, including IL2, IL4, IL6, IL9, IL21, IL23 and IFN-γ, exhibited enhanced levels in TAK patients compared with healthy individuals. IL-5 induces B cell development and Ig secretion, the role of which is unclear in TAK. The bottom half of the figure is the cytokines and their receptors that are involved in B cell activation. The top half of the figure includes BCRs, TLRs and several co-stimulatory molecules. IL: interleukin; IFNγ: interferon-gamma; R: receptor; BAFF: B cell activating factor; BCMA: B cell maturation antigen; APRIL: A proliferation-inducing ligand; TACI: transmembrane activator and calcium modulator and cyclophilin ligand interactor; BCR: B cell receptor; TLR: toll-like receptor; Ig: immunoglobulin; gp130: glycoprotein 130; TAK: Takayasu’s arteritis; PAMP: pathogen-associated molecular pattern; DAMP: damage-associated molecular patterns.</p>
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10 pages, 2145 KiB  
Communication
Calixarene-Based Supramolecular Sensor Array for Pesticide Discrimination
by Yeye Chen, Jia-Hong Tian, Han-Wen Tian, Rong Ma, Ze-Han Wang, Yu-Chen Pan, Xin-Yue Hu and Dong-Sheng Guo
Sensors 2024, 24(12), 3743; https://doi.org/10.3390/s24123743 - 8 Jun 2024
Viewed by 461
Abstract
The identification and detection of pesticides is crucial to protecting both the environment and human health. However, it can be challenging to conveniently and rapidly differentiate between different types of pesticides. We developed a supramolecular fluorescent sensor array, in which calixarenes with broad-spectrum [...] Read more.
The identification and detection of pesticides is crucial to protecting both the environment and human health. However, it can be challenging to conveniently and rapidly differentiate between different types of pesticides. We developed a supramolecular fluorescent sensor array, in which calixarenes with broad-spectrum encapsulation capacity served as recognition receptors. The sensor array exhibits distinct fluorescence change patterns for seven tested pesticides, encompassing herbicides, insecticides, and fungicides. With a reaction time of just three minutes, the sensor array proves to be a rapid and efficient tool for the discrimination of pesticides. Furthermore, this supramolecular sensing approach can be easily extended to enable real-time and on-site visual detection of varying concentrations of imazalil using a smartphone with a color scanning application. This work not only provides a simple and effective method for pesticide identification and quantification, but also offers a versatile and advantageous platform for the recognition of other analytes in relevant fields. Full article
(This article belongs to the Special Issue Sensing in Supramolecular Chemistry)
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<p>(<b>a</b>) Schematic representation of sensor array for pesticide discrimination. (<b>b</b>) Chemical structures of tested pesticides employed calixarenes (SC5A, SAC4A, SAC5A, and QAAC4A) and fluorescent dyes (LCG and AlPcS<sub>4</sub>).</p>
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<p>(<b>a</b>) Fluorescence response patterns of the sensor array ([calixarene] = 2.0 μM, [dye] = 2.0 μM) for different pesticides ([pesticide] = 13.0 μg mL<sup>−1</sup>). (<b>b</b>) Canonical score plot for the fluorescence response patterns determined by LDA with 95% confidence ellipses (<span class="html-italic">n</span> = 6).</p>
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<p>(<b>a</b>) Fluorescence response patterns and (<b>b</b>) canonical score plot for the detection of imazalil from 0–19.6 μg mL<sup>−1</sup>. Addition of solvent without imazalil resulted in an increase in optical path length, leading to a slight fluorescence response. (<b>c</b>) Fluorescence response patterns and (<b>d</b>) canonical score plot for mixtures (1.0 mg mL<sup>−1</sup> for total concentration) of rimsulfuron and nicosulfuron.</p>
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<p>Fluorescence response patterns of the sensor array ([calixarene] = 2.0 μM, [dye] = 2.0 μM) for different pesticides in the presence of 10% (<b>a</b>), 20% soil extract (<b>c</b>). Canonical score plot for the fluorescence response patterns in the presence of 10% (<b>b</b>), 20% (<b>d</b>) soil extract determined by LDA with 95% confidence ellipses (<span class="html-italic">n</span> = 6).</p>
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<p>(<b>a</b>) The image of SAC4A/LCG (2.0/2.0 μM) with various concentrations (up to 3.5 μg mL<sup>−1</sup>) of imazalil taken by iPhone 12. (<b>b</b>) The images recorded by iPhone 12 with a color-scanning app. (<b>c</b>) Plots of G values against imazalil concentrations. G values are green color intensities directly scanned from WizEyes Tech.</p>
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24 pages, 6241 KiB  
Article
Discovery and Characterization of the ddx41 Gene in Atlantic Salmon: Evolutionary Implications, Structural Functions, and Innate Immune Responses to Piscirickettsia salmonis and Renibacterium salmoninarum Infections
by Alejandro J. Yañez, Claudia A. Barrientos, Adolfo Isla, Marcelo Aguilar, Sandra N. Flores-Martin, Yassef Yuivar, Adriana Ojeda, Pablo Ibieta, Mauricio Hernández, Jaime Figueroa, Rubén Avendaño-Herrera and Marcos Mancilla
Int. J. Mol. Sci. 2024, 25(12), 6346; https://doi.org/10.3390/ijms25126346 - 8 Jun 2024
Viewed by 268
Abstract
The innate immune response in Salmo salar, mediated by pattern recognition receptors (PRRs), is crucial for defending against pathogens. This study examined DDX41 protein functions as a cytosolic/nuclear sensor for cyclic dinucleotides, RNA, and DNA from invasive intracellular bacteria. The investigation determined [...] Read more.
The innate immune response in Salmo salar, mediated by pattern recognition receptors (PRRs), is crucial for defending against pathogens. This study examined DDX41 protein functions as a cytosolic/nuclear sensor for cyclic dinucleotides, RNA, and DNA from invasive intracellular bacteria. The investigation determined the existence, conservation, and functional expression of the ddx41 gene in S. salar. In silico predictions and experimental validations identified a single ddx41 gene on chromosome 5 in S. salar, showing 83.92% homology with its human counterpart. Transcriptomic analysis in salmon head kidney confirmed gene transcriptional integrity. Proteomic identification through mass spectrometry characterized three unique peptides with 99.99% statistical confidence. Phylogenetic analysis demonstrated significant evolutionary conservation across species. Functional gene expression analysis in SHK-1 cells infected by Piscirickettsia salmonis and Renibacterium salmoninarum indicated significant upregulation of DDX41, correlated with increased proinflammatory cytokine levels and activation of irf3 and interferon signaling pathways. In vivo studies corroborated DDX41 activation in immune responses, particularly when S. salar was challenged with P. salmonis, underscoring its potential in enhancing disease resistance. This is the first study to identify the DDX41 pathway as a key component in S. salar innate immune response to invading pathogens, establishing a basis for future research in salmonid disease resistance. Full article
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<p>Description of <span class="html-italic">ddx41</span> sequence of <span class="html-italic">S. salar</span>. (<b>A</b>) Nucleotide and amino acid sequence; (<b>B</b>) chromosome localization indicates intron and exons.</p>
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<p>Proteomic identification of DDX41 in head kidney of <span class="html-italic">S. salar</span>. (<b>A</b>) Peptide identification indicates mass and probability of identification; (<b>B</b>) sequence and peptide identify are highlighted in green; (<b>C</b>) fragmentation spectra of each peptide identify; pink background highlight cysteine-alkylation.</p>
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<p>Phylogenetic analysis, conducted with 52 coding sequences from unrelated vertebrates, elucidates the evolutionary relationships of <span class="html-italic">ddx41</span> genes. Using MrBayes and the maximum parsimony method, the bootstrap consensus tree was inferred from 1000 replicates. Bayesian posterior probability and bootstrap support value are indicated at each node, representing common ancestors, as well as branching points where species or sequences diverged during evolution. <span class="html-italic">D. melanogaster</span> was included as an outgroup.</p>
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<p>Multiple alignment of DDX41 deduced amino acid sequence from <span class="html-italic">S. salar</span>, <span class="html-italic">D. rerio</span>, <span class="html-italic">B. bufo</span>, <span class="html-italic">G. gallus</span>, <span class="html-italic">R. norvegicus,</span> and <span class="html-italic">H. sapiens</span>. Identical residues between organisms are highlighted in black color and amino acid with chemical similar characteristic are highlighted in grey color. Numbers on the right indicate the position of the last residue in the alignment relative to the complete amino acid sequence of each species. The conserver domain coiled coil, Q-motif, helicase ATP binding, helicase C-terminal, and ZnF_C2HC are indicated. The basic and acid residues, nuclear signal (NES), and DEAD box are boxed. Asterisk and triangles indicate the important residues in function of DDX41.</p>
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<p>Comparative analysis of predicted DDX41 protein structures between vertebrates, including <span class="html-italic">S. salar</span>, alongside the crystal structure of human DDX41. (<b>A</b>) Principal domain in <span class="html-italic">S. salar</span>, <span class="html-italic">D. rerio</span>, <span class="html-italic">G. gallus</span>, <span class="html-italic">R. norvegicus</span>, and <span class="html-italic">H. sapiens</span>. Domains are color-coded and depicted in box forms. (<b>B</b>) Aligned 3D protein model of DDX41 with <span class="html-italic">H. sapiens</span> (red) and <span class="html-italic">S. salar</span> (blue), with residues labeled at the start and end of the protein chain. (<b>C</b>) Helicase C-terminal domain is highlighted in a green box. (<b>D</b>) Helicase ATP binding domain with DEADc domain is highlighted in a yellow box.</p>
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<p>Immune response kinetics of <span class="html-italic">ddx41</span> gene expression were assessed from 0 (control) to 24 hpi in SHK1 cells following infections with <span class="html-italic">P. salmonis</span> and <span class="html-italic">R. salmoninarum</span>. qPCR quantified <span class="html-italic">ddx41</span> gene expression, normalized to elongation factor-1α (<span class="html-italic">elf1a</span>). Control: non-infected SHK-1 cells. Results, presented as mean ± SE, indicate significance with asterisks: (*) <span class="html-italic">p</span> &lt; 0.05; (**) <span class="html-italic">p</span> &lt; 0.01; (***) <span class="html-italic">p</span> &lt; 0.001; (****) <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Innate immune response against intracellular pathogens in the SHK-1 cell line was assessed by measuring the gene expression levels of inflammatory genes <span class="html-italic">il1b</span> (<b>A</b>), <span class="html-italic">tnfa</span> (<b>B</b>), <span class="html-italic">ifng</span> (<b>C</b>), and <span class="html-italic">irf3</span> (<b>D</b>) during infection kinetics with <span class="html-italic">P. salmonis</span> and <span class="html-italic">R. salmoninarum</span> (0–24 hpi). Gene expression was analyzed using qPCR and normalized to the elongation factor-1a (<span class="html-italic">elf1a</span>) gene level. Control: non-infected SHK-1 cells. Data are presented as mean ± SE, with significance indicated by asterisks: (*) <span class="html-italic">p</span> &lt; 0.05; (**) <span class="html-italic">p</span> &lt; 0.01; (***) <span class="html-italic">p</span> &lt; 0.001; (****) <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Evaluation of innate response in <span class="html-italic">S. salar</span> to natural infection with <span class="html-italic">P. salmonis</span>; the cohabitant (naive) group exhibited mortalities starting from 28 dpc, reaching 70% at 49 dpc. Head kidney samples were collected from <span class="html-italic">S. salar</span> between 0 and 49 days post-<span class="html-italic">P. salmonis</span> challenge. qPCR analysis measured gene expression of <span class="html-italic">ddx41</span> (<b>A</b>), <span class="html-italic">il1b</span> (<b>B</b>), <span class="html-italic">tnfa</span> (<b>C</b>), <span class="html-italic">ifng</span> (<b>D</b>), and <span class="html-italic">irf3</span> (<b>E</b>), normalized to elongation factor-1a (<span class="html-italic">elf1a</span>) levels. Control: non-challenged <span class="html-italic">S. salar.</span> Results are presented as mean ± SE, with significance indicated by asterisks: (*) <span class="html-italic">p</span> &lt; 0.05; (**) <span class="html-italic">p</span> &lt; 0.01; (***) <span class="html-italic">p</span> &lt; 0.001.</p>
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12 pages, 1936 KiB  
Article
Embryonic Mice with Lung-Specific RAGE Upregulation Have Enhanced Mitochondrial Respiration
by Derek M. Clarke, Katrina L. Curtis, Kaden Harward, Jared Scott, Brendan M. Stapley, Madison N. Kirkham, Evan T. Clark, Peter Robertson, Elliot Chambers, Cali E. Warren, Benjamin T. Bikman, Juan A. Arroyo and Paul R. Reynolds
J. Respir. 2024, 4(2), 140-151; https://doi.org/10.3390/jor4020012 - 5 Jun 2024
Viewed by 329
Abstract
RAGE (receptor for advanced glycation end-products) represents a class of multi-ligand pattern recognition receptors highly expressed in the vertebrate lung. Our previous work demonstrated unique patterns of RAGE expression in the developing murine lung and regulation by key transcription factors including NKX2.1 and [...] Read more.
RAGE (receptor for advanced glycation end-products) represents a class of multi-ligand pattern recognition receptors highly expressed in the vertebrate lung. Our previous work demonstrated unique patterns of RAGE expression in the developing murine lung and regulation by key transcription factors including NKX2.1 and FoxA2. The current investigation employed conditional lung-specific upregulation via a TetOn transgenic mouse model (RAGE TG) and nontransgenic controls. RAGE expression was induced in RAGE TG mice throughout gestation (embryonic day, E0-E18.5) or from E15.5-E18.5 and compared to age-matched controls. High-resolution respirometry was used to assess mitochondrial respiration and context was provided by quantifying ATP and reactive oxygen species (ROS) generation. Lung lysates were also screened by immunoblotting for MAPK/PI3K signaling intermediates. RAGE upregulation increased mitochondrial oxygen consumption in the E0-E18.5 and E15.5-E18.5 groups compared to controls. RAGE TG mice also had increased ATP concentrations, which persisted even after controlling for oxygen consumption. In contrast, ROS generation was diminished in RAGE TG animals compared to controls. Lastly, in both RAGE TG groups, pERK and pp38 were significantly decreased, whereas pAKT was significantly elevated, suggesting that RAGE signaling is likely perpetuated via pAKT pathways. Together, these data demonstrate that despite lung hypoplasia in RAGE TG mice, the remaining tissue experiences a favorable shift in mitochondrial bioenergetics without excessive redox assault and a preference for AKT signaling over ERK or p38. Full article
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<p>Altered mitochondrial activity in response to increased expression of RAGE in lung tissue. RAGE upregulation alters mitochondrial bioenergetics in developing lungs. Upregulation of RAGE was induced in RAGE TG pup lung tissue from E15-18.5 and E0-18.5 and compared to dox-fed nontransgenic controls (<span class="html-italic">n</span> = 8 mice per group). Mice were sacrificed on day E18.5 and mitochondrial respiration (<b>A</b>), respiratory P factor (<b>B</b>), and Complex II activity (<b>C</b>) were evaluated. Permeabilized lung tissue samples were sequentially treated with glutamate (10 mM) and malate (GM; 2 mM); +ADP (2.5 mM); +succinate (S; 10 mM); + FCCP (2 mM). Mann–Whitney tests were used, resulting in differences noted as * <span class="html-italic">p</span> ≤ 0.05 or ** <span class="html-italic">p</span> ≤ 0.01.</p>
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<p>Altered levels of ATP or reactive oxygen species (ROS) in response to upregulated expression of RAGE in lung tissue. Following RAGE upregulation from E15-18.5 or E0-18.5, ATP levels were measured in RAGE TG and nontransgenic controls. Levels of ATP were significantly increased in both groups of RAGE TG mice (<b>A</b>). When normalized to ATP synthase activity (ADP), ATP was only significantly increased in E0-18.5 treatment mice compared to controls (<b>B</b>). The DCFDA assay was used to quantify changes in ROS in RAGE TG mice with RAGE upregulation from E15-18.5 or E0-18.5 and compared to nontransgenic controls. ROS was significantly increased in tissue treated from E0-18.5 compared to controls (<b>C</b>). When normalized to complex 2 activity (S), there was a significant decrease in production of ROS in both RAGE TG groups compared to controls (<b>D</b>). Mann–Whitney tests were used, resulting in differences noted as * <span class="html-italic">p</span> ≤ 0.05 or ** <span class="html-italic">p</span> ≤ 0.01.</p>
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<p>Increased pAKT in response to RAGE upregulation in lung tissue. Levels of phosphorylated AKT (pAKT) were screened in lungs from both groups of RAGE TG mice and compared to nontransgenic controls. Active pAKT was significantly increased in RAGE TG lungs treated from E15-18.5 (<b>A</b>) or E0-18.5 (<b>B</b>) compared to controls (<span class="html-italic">n</span> = 4 per group). Representative blots for pAKT and actin are shown and Mann–Whitney tests revealed differences noted as * <span class="html-italic">p</span> ≤ 0.05.</p>
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<p>Decreased pERK in response to RAGE upregulation in lung tissue. Levels of phosphorylated ERK (pERK) were screened in lungs from both groups of RAGE TG mice and compared to nontransgenic controls. Active pERK was significantly decreased in RAGE TG lungs treated from E15-18.5 (<b>A</b>) or E0-18.5 (<b>B</b>) compared to controls (<span class="html-italic">n</span> = 4 per group). Representative blots for pERK and actin are shown and Mann–Whitney tests revealed differences noted as ** <span class="html-italic">p</span> ≤ 0.01.</p>
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<p>Decreased pp38 in response to RAGE upregulation in lung tissue. Levels of phosphorylated p38 (pp38) were screened in lungs from both groups of RAGE TG mice and compared to nontransgenic controls. Active pp38 was significantly decreased in RAGE TG lungs treated from E15-18.5 (<b>A</b>) or E0-18.5 (<b>B</b>) compared to controls (<span class="html-italic">n</span> = 4 per group). Representative blots for pp38 and actin are shown and Mann–Whitney tests revealed differences noted as ** <span class="html-italic">p</span> ≤ 0.01.</p>
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25 pages, 2653 KiB  
Review
Deciphering the Role of Virus Receptors in Plant–Virus–Vector Interactions
by Sumit Jangra, Senthilraja Chinnaiah, Sneha Rashtrapal Patil, Bhavya Shukla, Ragunathan Devendran and Manish Kumar
Receptors 2024, 3(2), 255-279; https://doi.org/10.3390/receptors3020013 - 3 Jun 2024
Viewed by 287
Abstract
Insect-transmitted plant viruses are a major threat to global agricultural crop production. Receptors play a prominent role in the interplay between host-pathogen and vector interaction. The virus–vector relationship involves both viral and vector receptors. Receptors-like kinases (RLKs) and receptor-like proteins play a crucial [...] Read more.
Insect-transmitted plant viruses are a major threat to global agricultural crop production. Receptors play a prominent role in the interplay between host-pathogen and vector interaction. The virus–vector relationship involves both viral and vector receptors. Receptors-like kinases (RLKs) and receptor-like proteins play a crucial role in plant immunity, which acts as a basal defense. Pathogens can evade or block host recognition by their effector proteins to inhibit pathogen recognition receptor (PRR)-mediated signaling. Intriguingly, RLKs are also known to interact with viral proteins and impact plant susceptibility against viruses, while the endocytic receptors in vectors assist in the binding of the virus to the vectors. Unlike other receptors of fungi and bacteria which have three different domains located from extracellular or intracellular to perceive a multitude of molecular patterns, the characterization of viral receptors is quite complex and limited since the virus is directly injected into plant cells by insect vectors. Little is known about these receptors. Unraveling the receptors involved in virus entry and transmission within the vector will provide vital information in virus–vector interactions. This review focuses on efforts undertaken in the identification and characterization of receptors of plant viruses within the host and vector. This will lead to a better understanding of the cellular mechanism of virus transmission and spread, and further suggests new alternative tools for researchers to develop an integrated approach for the management of viral diseases and associated vectors. Full article
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<p>Schematic representation of some of the common techniques used for the identification and functional characterization of proteins associated with plant–virus–vector pathosystem.</p>
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<p>A schematic diagram of an aphid showing the putative proteins corresponding to viral interactive partners. Barley yellow dwarf virus (BYDV), cauliflower mosaic virus (CaMV), zucchini yellow mosaic virus (ZYMV), and tobacco etch virus (TEV) are shown in combination with their putative partners. Host proteins are represented as non-glycosylated proteins (NGPs), Cuticular proteins (CuPs), ribosomal protein S2 (RPS2), and complement component 1Q subcomponent-binding protein (C1QBP). The presence of the viral receptors in aphids is shown with star shapes and different colors.</p>
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<p>A schematic diagram of planthopper showing the putative proteins corresponding to viral interactive partners. Tomato yellow leaf curl virus (TYLCV), rice stripe virus (RSV), and rice ragged stunt oryzavirus (RRSV) are shown in combination with their putative partners. Insect proteins such as vitellogenin (Vg), G-protein Pathway Suppressor 2 (GPS2), oligomycin-sensitivity conferral protein (OSCP), sugar transporter 6 (STP), and flotillin are shown in combination with their respective viruses. The presence of the viral receptors in the planthopper is shown with star shapes and different colors.</p>
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<p>A schematic diagram of thrips showing the putative proteins corresponding to viral interactive partners. Tomato spotted wilt virus (TSWV) with midgut proteins, endocuticle structural glycoprotein (Fo-GN), cyclophilin (Fo-Cyp1), apolipoprotein-D (ApoD), orai-2-like (Orai), and obstructor-E-like isoform X2 (Obst). Major segments like the head, thorax, and abdomen are labeled. The presence of the viral receptors in thrips is shown with different colors and shapes.</p>
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<p>A schematic diagram of a whitefly showing the putative proteins corresponding to viral interactive partners. Tomato yellow leaf curl virus (TYLCV), tomato leaf curl New Delhi virus (ToLCVNDV), cotton leaf curl Rajasthan virus (CLCuV-Ra), cotton leaf curl Multan virus (CLCuMuV), and tomato yellow leaf curl Sardinia virus (TYLCSV). Insect proteins are heat-shock proteins (BtHSP16 and BtHSP70), <span class="html-italic">B. tabaci</span> peptidoglycan recognition protein (BtPGRP), Cyclophilin (Cyp) B, midgut protein (MGP), vesicle-associated membrane protein-associated protein B (VAPB), proliferating cell nuclear antigen (PCNA), cubilin (BtCUBN), aminoless (BtAMN), <span class="html-italic">B. tabaci</span> vesicle-associated membrane protein 2 (BtVAMP2), vacuolar protein (Vps), sorting-associated protein twenty-associated 1 (Vta1), and phosphatidylethanolamine-binding protein (PEBP). Major segments like the head, thorax, and abdomen are labeled.</p>
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<p>A simplified diagram of virus and non-virus-associated receptors in plants. <span class="html-italic">N</span>-gene, <span class="html-italic">Rx</span> gene, <span class="html-italic">Sw-5b</span> gene, <span class="html-italic">RCY1</span> gene, <span class="html-italic">Tm-1</span>, <span class="html-italic">RTM1/RTM2</span> gene show the response against viruses. Tobacco mosaic virus (TMV), potato virus X (PVX), tomato spotted wilt virus (TSWV), cucumber mosaic virus (CMV), tomato mosaic virus (ToMV), and tobacco etch virus (TEV) are interacting with host proteins. Other non-NBS-LRR receptors are also shown in this image.</p>
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17 pages, 2766 KiB  
Article
cGAS-STING-TBK1 Signaling Promotes Valproic Acid-Responsive Human Cytomegalovirus Immediate-Early Transcription during Infection of Incompletely Differentiated Myeloid Cells
by Emily R. Albright and Robert F. Kalejta
Viruses 2024, 16(6), 877; https://doi.org/10.3390/v16060877 - 30 May 2024
Viewed by 268
Abstract
Repression of human cytomegalovirus (HCMV) immediate-early (IE) gene expression is a key regulatory step in the establishment and maintenance of latent reservoirs. Viral IE transcription and protein accumulation can be elevated during latency by treatment with histone deacetylase inhibitors such as valproic acid [...] Read more.
Repression of human cytomegalovirus (HCMV) immediate-early (IE) gene expression is a key regulatory step in the establishment and maintenance of latent reservoirs. Viral IE transcription and protein accumulation can be elevated during latency by treatment with histone deacetylase inhibitors such as valproic acid (VPA), rendering infected cells visible to adaptive immune responses. However, the latency-associated viral protein UL138 inhibits the ability of VPA to enhance IE gene expression during infection of incompletely differentiated myeloid cells that support latency. UL138 also limits the accumulation of IFNβ transcripts by inhibiting the cGAS-STING-TBK1 DNA-sensing pathway. Here, we show that, in the absence of UL138, the cGAS-STING-TBK1 pathway promotes both IFNβ accumulation and VPA-responsive IE gene expression in incompletely differentiated myeloid cells. Inactivation of this pathway by either genetic or pharmacological inhibition phenocopied UL138 expression and reduced VPA-responsive IE transcript and protein accumulation. This work reveals a link between cytoplasmic pathogen sensing and epigenetic control of viral lytic phase transcription and suggests that manipulation of pattern recognition receptor signaling pathways could aid in the refinement of MIEP regulatory strategies to target latent viral reservoirs. Full article
(This article belongs to the Special Issue Epigenetic and Transcriptional Regulation of DNA Virus Infections)
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Figure 1
<p><b>VPA treatment activates an IFN-I response during HCMV infection of incompletely differentiated myeloid cells.</b> (<b>A</b>) Viability of THP1 cells untreated (Ctrl) or treated with 1 mM VPA for 24 h, plotted relative to untreated control cells (Ctrl). (<b>B</b>) Morphology of THP1 cells left untreated (Ctrl) or treated with 1 mM VPA or 100 ng/mL PMA for 24 h. (<b>C</b>–<b>F</b>) THP1 cells treated as in panel B and analyzed by RT-qPCR for GCSFR (<b>C</b>), ID2 (<b>D</b>), CD11B (<b>E</b>), or IFNB1 (<b>F</b>) transcripts. (<b>G</b>,<b>H</b>) THP1 cells pre-treated without (−) or with (+) 1 mM VPA were mock infected or infected with AD169 (AD) or UV-inactivated AD169 (UV) at an MOI of 1 for 18 h and analyzed by RT-qPCR for IFNB1 (<b>G</b>) or viral IE (<b>H</b>) transcripts. (<b>I</b>) THP1 cells treated and infected as in panel G were harvested at 18 h post infection and analyzed by Western blot for the indicated proteins. (<b>J</b>) Quantitation of pIRF3 protein levels from panel I, normalized to total IRF3 levels and plotted relative to VPA treated WT infected samples from the same blot. All bar graphs represent the mean ± SEM from three biological replicates. *: <span class="html-italic">p</span> &lt; 0.05, **: <span class="html-italic">p</span> &lt; 0.01, ***: <span class="html-italic">p</span> &lt; 0.001, ns: <span class="html-italic">p</span> &gt; 0.05 by one-way ANOVA with Tukey’s post hoc test for multiple comparisons.</p>
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<p><b>Knockout of cGAS or STING impairs VPA-responsive IE gene expression during HCMV infection of incompletely differentiated myeloid cells</b>. (<b>A</b>,<b>B</b>) Wild-type (WT) THP1 cells or two independent clones of STING or cGAS knockout (KO) cells were pre-treated without (−) or with (+) 1 mM VPA and infected with AD169 at an MOI of 1 for 18 h and analyzed by RT-qPCR for IFNB1 (<b>A</b>) or viral IE (<b>B</b>) transcripts. n = 3 (<b>C</b>) WT and STING or cGAS knockout THP1s were treated and infected as in panel A and analyzed by Western blot with the indicated antibodies. n = 4. (<b>D</b>) Quantitation of IE1 protein levels from panel C, normalized to Tubulin levels and plotted relative to untreated WT infected samples from the same blot. n = 4. All bar graphs represent the mean ± SEM from the indicated number of biological replicates. *: <span class="html-italic">p</span> &lt; 0.05, **: <span class="html-italic">p</span> &lt; 0.01 by one-way ANOVA with Tukey’s post hoc test for multiple comparisons.</p>
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<p><b>cGAS activity promotes VPA-responsive IE gene expression during HCMV infection of incompletely differentiated myeloid cells</b>. (<b>A</b>) Viability of THP1 cells treated with DMSO or 10 μg/mL Ru.521 for 24 h, plotted relative to DMSO treated controls from the same experiment. n = 3. (<b>B</b>,<b>C</b>) THP1 cells were pre-treated without (−) or with (+) 1 mM VPA and either mock infected or infected with HCMV AD169 at an MOI of 1 in the presence of DMSO or 10 μg/mL Ru.521 for 18 h and analyzed by RT-qPCR for IFNB1 (<b>B</b>) or viral IE (<b>C</b>) transcripts. n = 3. (<b>D</b>) THP1 cells treated and infected as in panel A and analyzed by Western blot with the indicated antibodies n = 4. (<b>E</b>) Quantitation of IE1 protein levels from panel D, normalized to Tubulin levels and plotted relative to DMSO treated WT infected samples from the same blot. n = 4. All bar graphs represent the mean ± SEM from the indicated number of biological replicates. *: <span class="html-italic">p</span> &lt; 0.05, ns: <span class="html-italic">p</span> &gt; 0.05 by Student’s <span class="html-italic">t</span>-test.</p>
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<p><b>Knockout of TBK1 inhibits VPA-responsive IE gene expression during HCMV infection of incompletely differentiated myeloid cells</b>. (<b>A</b>,<b>B</b>) Wild-type (WT), TBK1 knockout (TBK1 KO), or IKKe knockout (IKKe KO) THP1 cells were pre-treated without (−) or with (+) 1 mM VPA and infected with AD169 at an MOI of 1 for 18 h and analyzed by RT-qPCR for IFNB1 (<b>A</b>) or viral IE (<b>B</b>) transcripts. (<b>C</b>) WT and knockout THP1s were treated and infected as in panel A and analyzed by Western blot with the indicated antibodies. (<b>D</b>) Quantitation of IE1 protein levels from panel C, normalized to Tubulin levels and plotted relative to untreated WT infected samples from the same blot. All bar graphs represent the mean ± SEM from four biological replicates. *: <span class="html-italic">p</span> &lt; 0.05, **: <span class="html-italic">p</span> &lt; 0.01, ***: <span class="html-italic">p</span> &lt; 0.001 by one-way ANOVA with Tukey’s post hoc test for multiple comparisons.</p>
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<p><b>TBK1/IKKe activity promotes VPA-responsive IE gene expression during HCMV infection of incompletely differentiated myeloid cells.</b> (<b>A</b>) Viability of THP1 cells treated with DMSO or 10 µM BX795 for 24 h, plotted relative to DMSO-treated controls from the same experiment. n = 3 (<b>B</b>,<b>C</b>) THP1 cells were pre-treated without (−) or with (+) 1 mM VPA and infected with AD169 at an MOI of 1 in the presence of DMSO or 10 µM BX795 for 18 h and analyzed by RT-qPCR for IFNB1 (<b>B</b>) or viral IE (<b>C</b>) transcripts. n = 4. (<b>D</b>) THP1 cells treated and infected as in panel A and analyzed by Western blot with the indicated antibodies. n = 3. (<b>E</b>) Quantitation of IE1 protein levels from panel D, normalized to Tubulin levels and plotted relative to DMSO treated WT infected samples from the same blot. n = 3. All bar graphs represent the mean ± SEM from the indicated number of biological replicates. *: <span class="html-italic">p</span> &lt; 0.05, ***: <span class="html-italic">p</span> &lt; 0.001, ns: <span class="html-italic">p</span> &gt; 0.05 by Student’s <span class="html-italic">t</span>-test.</p>
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<p><b>Activation of STING is sufficient to induce viral IE gene expression in a TBK1-dependent manner.</b> (<b>A</b>) Viability of THP1 cells untreated (Ctrl) or treated with 1 µM diABZI for 24 h, plotted relative to untreated controls from the same experiment. (<b>B</b>,<b>C</b>) Wild-type (WT) or TBK1 knockout (TBK1 KO) THP1 cells were mock infected or infected with AD169 an MOI of 1 in the absence (Ctrl) or presence of 1 µM diABZI for 18 hrs and analyzed by RT-qPCR for IFNB1 (<b>B</b>) or viral IE (<b>C</b>) transcripts. All bar graphs represent the mean ± SEM from three biological replicates. *: <span class="html-italic">p</span> &lt; 0.05, ***: <span class="html-italic">p</span> &lt; 0.001 by one-way ANOVA with Tukey’s post hoc test for multiple comparisons.</p>
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<p><b>Loss of cGAS or expression of UL138 impairs recruitment of NFkB to the viral MIEP and IFNB1 promoter.</b> (<b>A</b>,<b>B</b>) ChIP assays for NFkB p65/RelA (black bars) or matched IgG control (gray bars) at the MIEP (<b>A</b>) or IFNB1 promoter (<b>B</b>) in WT THP1 or two independent clones of cGAS knockout (KO) cells pretreated with 1 mM VPA and infected with wild-type AD169 at an MOI of 1 for 18 hpi. Enrichment relative to WT control from the same experiment is shown. (<b>C</b>,<b>D</b>) ChIP assays for NFkB p65/RelA (black bars) or matched IgG control (gray bars) at the MIEP (<b>C</b>) or IFNB1 promoter (<b>D</b>) in WT THP1 cells pretreated with VPA and infected with either wild-type AD169 (WT) or AD169 expressing HA-tagged UL138 (138HA). Enrichment relative to WT infection control from the same experiment is shown. All bar graphs represent the mean ± SEM from three biological replicates. *: <span class="html-italic">p</span> ≤ 0.05, **: <span class="html-italic">p</span> &lt; 0.01, ***: <span class="html-italic">p</span> &lt; 0.001 by one-way ANOVA with Tukey’s post hoc test for multiple comparisons.</p>
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<p><b>Model for VPA-responsive IFN-I and viral IE gene expression mediated by cGAS-STING-TBK1.</b> Activation of the cGAS-STING-TBK1 pathway in HCMV-infected cells drives the transcription of cellular IFNB1 and viral IE1/2. In the presence of UL138, the pathway is inhibited, reducing the accumulation of IFNB1 and IE1/2. Model adapted from [<a href="#B38-viruses-16-00877" class="html-bibr">38</a>].</p>
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21 pages, 5518 KiB  
Article
Effects of Akt Activator SC79 on Human M0 Macrophage Phagocytosis and Cytokine Production
by Robert J. Lee, Nithin D. Adappa and James N. Palmer
Cells 2024, 13(11), 902; https://doi.org/10.3390/cells13110902 - 24 May 2024
Viewed by 355
Abstract
Akt is an important kinase in metabolism. Akt also phosphorylates and activates endothelial and neuronal nitric oxide (NO) synthases (eNOS and nNOS, respectively) expressed in M0 (unpolarized) macrophages. We showed that e/nNOS NO production downstream of bitter taste receptors enhances macrophage phagocytosis. In [...] Read more.
Akt is an important kinase in metabolism. Akt also phosphorylates and activates endothelial and neuronal nitric oxide (NO) synthases (eNOS and nNOS, respectively) expressed in M0 (unpolarized) macrophages. We showed that e/nNOS NO production downstream of bitter taste receptors enhances macrophage phagocytosis. In airway epithelial cells, we also showed that the activation of Akt by a small molecule (SC79) enhances NO production and increases levels of nuclear Nrf2, which reduces IL-8 transcription during concomitant stimulation with Toll-like receptor (TLR) 5 agonist flagellin. We hypothesized that SC79’s production of NO in macrophages might likewise enhance phagocytosis and reduce the transcription of some pro-inflammatory cytokines. Using live cell imaging of fluorescent biosensors and indicator dyes, we found that SC79 induces Akt activation, NO production, and downstream cGMP production in primary human M0 macrophages. This was accompanied by a reduction in IL-6, IL-8, and IL-12 production during concomitant stimulation with bacterial lipopolysaccharide, an agonist of pattern recognition receptors including TLR4. Pharmacological inhibitors suggested that this effect was dependent on Akt and Nrf2. Together, these data suggest that several macrophage immune pathways are regulated by SC79 via Akt. A small-molecule Akt activator may be useful in some infection settings, warranting future in vivo studies. Full article
(This article belongs to the Special Issue Macrophage Activation and Regulation)
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Graphical abstract

Graphical abstract
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<p>Akt isoform expression in M0 macrophages. (<b>A</b>) Expression (transcripts per million, TPM) of Akt isoforms in immune cells in the DIC database; (<b>B</b>) Normalized gene counts of Akt isoforms from GEO dataset GSE122597. (<b>C</b>) Expression of Akt isoforms relative to housekeeping gene UBC determined via performing qPCR on the monocytes and derived M0 macrophages used here; data points show results from 3 independent donors. (<b>D</b>) Imaging cytometry analysis of staining of macrophage markers (CD14, CD68, and CD16) with eNOS and iNOS in M0 macrophages. All markers were significantly above the control (mouse IgG) except iNOS, which was upregulated in M1 macrophages; * <span class="html-italic">p</span> &lt; 0.05 vs. IgG isotype control via one-way ANOVA with Dunnett’s post-test. (<b>E</b>) Fluo-4 Ca<sup>2+</sup> trace (average of n = 3 experiments) showing response to 50 µM histamine inhibited by H1 antagonist cetirizine. The time of addition of histamine ± cetirizine is denoted by the arrow. (<b>F</b>) Immunofluorescence of Akt and eNOS in M0 macrophages. The nuclear DAPI stain is shown in yellow. The scale bar is 5 µm. (<b>G</b>) Isotype control (rabbit and goat serum) staining. All images are representative of images from cells from 3 independent donors collected and imaged on different days. The scale bar is 5 µm.</p>
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<p>Visualization of SC79 Akt activation in M0 macrophages using fluorescent biosensors. (<b>A</b>) Schematic of the AktAR biosensor. Cerulean (cyan fluorescent protein (CFP) variant) and circularly permutated (cp) Venus (YFP variant) surround a forkhead-associated domain (FHA1)-phosphorylated amino acid binding domain and FOXO1 Akt substrate sequence. Akt phosphorylation causes a change in conformation, and a closer proximity of CFP and YFP increases FRET (an increase in the YFP/CFP emission ratio). (<b>B</b>) Representative traces from single experiments of AktAR2 YFP/CFP ratio changes in response to 1–10 µM SC79 ± MK2206 or LY294002. Time of addition of the indicated drugs is denoted by the arrow. (<b>C</b>) Bar graph of the same responses as in B from 4 independent experiments from different donors per condition. (<b>D</b>) Diagram of the TORCAR biosensor. Phosphorylation of the 4EBP1 motif brings CFP and YFP further apart and decreases FRET (an increased CFP/YFP emission ratio). (<b>E</b>) Representative traces from single experiments of TORCAR (or mutated T/A control TORCAR) FRET ratio changes in response to 1–10 µM SC79 ± rapamycin. Time of addition of the indicated drugs is denoted by the arrow. (<b>F</b>) Bar graph of the same responses as in (<b>E</b>) from 4 independent experiments from different donors per condition. Significance was determined via one-way ANOVA with Dunnett’s post-test, comparing values to the vehicle control; * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>SC79 activates NO production via Akt. (<b>A</b>) Bar graph of endpoint DAF-FM fluorescence from 5 independent experiments using macrophages from different donors. Responses were tested with 0.1–10 µg/mL SC79 ± Akt inhibitors MK2206 (10 µg/mL) or GSK690693 (10 µM), PKC inhibitor Gö6983 (10 µM), PKA inhibitor H89 (10 µM), NOS inhibitor L-NAME (10 µM), or inactive D-NAME (10 µM). Significance was determined via one-way ANOVA with Dunnett’s post-test, comparing values to those for HBSS alone; * <span class="html-italic">p</span> &lt; 0.05. (<b>B</b>) DAF-FM fluorescence data with 1 and 10 µg/mL SC79 ± 10 µM CFTR<sub>inh</sub>172 pretreatment. No significant differences were determined via one-way ANOVA. (<b>C</b>) Representative real-time traces of DAF-FM fluorescence, ± L-NAME or D-NAME. Time of addition of the indicated drugs is denoted by the arrow. (<b>D</b>) Data from 5 independent experiments done similarly as in (<b>C</b>). Significance was determined via one-way ANOVA with Dunnett’s post-test, comparing values to those for SC79 alone; * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>SC79 activates cGMP production downstream of NO. (<b>A</b>) Representative traces of cGMP biosensor fluorescence changes with stimulation by 10 µg/mL SC79 vs. the vehicle (0.1% DMSO) only. An upward deflection corresponds to an increase in cGMP levels. Time of addition of the indicated drugs is denoted by the arrow. (<b>B</b>) Bar graph of results from independent experiments done similarly as in (<b>A</b>). Significance was determined via one-way ANOVA with Dunnett’s post-test, comparing values to those for HBSS plus the vehicle (0.1% DMSO) alone; * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>SC79 enhances FITC <span class="html-italic">E. coli</span> phagocytosis, likely via Akt and NO signaling. (<b>A</b>) Images showing phagocytosis of FITC-labeled <span class="html-italic">E. coli</span> (magenta, DAPI nuclear stain in green) in primary human monocyte-derived macrophages, as described [<a href="#B17-cells-13-00902" class="html-bibr">17</a>,<a href="#B19-cells-13-00902" class="html-bibr">19</a>]. (<b>B</b>) FITC fluorescence (indicating macrophage phagocytosis) increased with SC79 treatment, which was blocked by Akt inhibitor MK2206 or GSK690693 and NOS inhibitor L-NAME. Significance was determined via one-way ANOVA with Dunnett’s post-test, comparing all values to those of the control; * <span class="html-italic">p</span> &lt; 0.05. Data are from 5 independent experiments using cells from 5 donors.</p>
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<p>SC79 enhances pHrodo <span class="html-italic">S. aureus</span> phagocytosis, likely via Akt and NO signaling. (<b>A</b>) The phagocytosis of pHrodo <span class="html-italic">S. aureus</span> also increased with 10 µg/mL SC79 and was blocked by MK2206. Note that pHrodo only fluoresces in acidic environments like the phagosome, confirming that internalization reflects phagocytosis. Data were obtained from 5 independent experiments using cells from 5 donors. Significance was determined via one-way ANOVA with Bonferroni’s post-test; ** <span class="html-italic">p</span> &lt; 0.01. (<b>B</b>) The same type of experiments as in A, but testing SC79 ± L-NAME or D-NAME; significance determined via one-way ANOVA with Dunnett’s post-test, comparing all values to those of the control (HBSS + 0.1% DMSO); ** <span class="html-italic">p</span> &lt; 0.01. (<b>C</b>) The same type of experiments as in A and B, but testing SC79 ± guanylyl cyclase inhibitor ODQ or NS2028 or adenylyl cyclase inhibitor KH 7 (all at 10 µM); significance determined via one-way ANOVA with Dunnett’s post-test, comparing all values to those of the control (HBSS + 0.1% DMSO); ** <span class="html-italic">p</span> &lt; 0.01. (<b>D</b>) Micrographs of pHrodo <span class="html-italic">S. aureus</span> phagocytosed in macrophages. Top and bottom rows show images from two different donors. (<b>E</b>) Quantification of 4 independent experiments, as shown in (<b>D</b>), confirming the dose-dependent increase in phagocytosis with SC79; significance was determined via one-way ANOVA with Dunnett’s post-test, comparing all values to those of the control; ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>SC79 enhancement of phagocytosis is not altered by CFTR<sub>inh</sub>172. (<b>A</b>) The same type of FITC <span class="html-italic">E. coli</span> phagocytosis experiments as in <a href="#cells-13-00902-f005" class="html-fig">Figure 5</a>, testing the SC79 ± CFTR<sub>inh</sub>172 pretreatment. (<b>B</b>) The same type of phagocytosis experiments of pHrodo <span class="html-italic">S. aureus</span> as in <a href="#cells-13-00902-f006" class="html-fig">Figure 6</a>, but testing SC79 ± CFTR<sub>inh</sub>172 pretreatment. Significance was determined via one-way ANOVA with Bonferroni’s post-test with paired comparisons; * <span class="html-italic">p</span> &lt; 0.05 vs. 0 µg/mL SC79 (HBSS + 0.1% DMSO vehicle control); n.s. means there was no statistical significance between bracketed groups. Data from 5–6 independent experiments per condition with macrophages from different donors.</p>
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<p>SC79 enhances LPS or bacterial-induced superoxide production. (<b>A</b>) Bar graph of macrophage MitoSox Red fluorescence measured on plate reader (396 nm excitation, 610 nm emission) after 60 min stimulation with LPS or <span class="html-italic">E. coli</span> ± SC79. (<b>B</b>) Bar graph of macrophage dihydroethidium fluorescence (518 nm excitation, 605 nm emission) from experiments similar to those in (<b>A</b>). Data from 4–5 independent experiments per condition with macrophages from different donors; significance determined via one-way ANOVA with Bonferroni’s post-test with paired comparisons (±SC79); * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Reduction in macrophage cytokines with SC79. (<b>A</b>) LDH release into cell culture media. Staurosporine and triton X-100 were controls used to induce apoptotic death (often followed by secondary necrosis in vitro [<a href="#B107-cells-13-00902" class="html-bibr">107</a>]) and nonspecific lysis, respectively. No LDH was observed with SC79 (one-way ANOVA; Dunnett’s post-test; n = 4 experiments per condition from separate donors); * <span class="html-italic">p</span> &gt; 0.05. (<b>B</b>) Macrophage IL-12 (M1 marker) or IL-10 (M2 marker) release determined by performing ELISA after 72 h on M1 cocktail (20 ng/mL IFNγ + 100 ng/mL LPS)- or M2-polarizing IL-4 (20 ng/mL). Significance was determined via one-way ANOVA with Bonferroni’s post-test, comparing values with those of M0 (no stimulation); * <span class="html-italic">p</span> &gt; 0.05; n = 8 experiments per condition from separate donors. (<b>C</b>) Dose response of brusatol or ML385 with IL-6 release. Significance was determined via one-way ANOVA with Bonferroni’s post-test, comparing values with those of the control (no stimulation); * <span class="html-italic">p</span> &gt; 0.05; n = 4 experiments from separate donors. (<b>D</b>–<b>F</b>) Bar graphs of IL-6 (<b>D</b>), IL-8 (<b>E</b>), or IL-12 (<b>F</b>) release with SC79 (10 µg/mL) ± LPS (100 ng/mL) ± 10 nM brusatol or ML385, as indicated. Significance was determined via one-way ANOVA, with Bonferroni’s post-test; * <span class="html-italic">p</span> &lt; 0.05 vs. control (media + vehicle) and <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 between bracketed columns. n = 4–5 experiments from separate donors. (<b>G</b>) The same type of experiments as in D-F but using <span class="html-italic">P. aeruginosa</span>-conditioned media ± SC79 ± ML385. Significance was determined via one-way ANOVA with Bonferroni’s post-test; * <span class="html-italic">p</span> &lt; 0.05 between bracketed columns. (<b>H</b>) IL-6 (green) or IL-8 (magenta) transcript with LPS ± SC79 ± ML385. Significance was tested via one-way ANOVA with Bonferroni’s post-test; * <span class="html-italic">p</span> &lt; 0.05 vs. control and <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 between bracketed columns; n = 4 experiments from separate donors. (<b>I</b>) Nrf2 target transcript levels with SC79 ± brusatol or ML385. Significance was tested via one-way ANOVA with Dunnett’s post-test; * <span class="html-italic">p</span> &lt; 0.05 vs. control; n = 4 experiments from separate donors. (<b>J</b>) TNF transcript levels with LPS ± SC79. Significance was tested via one-way ANOVA with Dunnett’s post-test; * <span class="html-italic">p</span> &lt; 0.05 vs. control; n = 4 experiments from separate donors.</p>
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19 pages, 2218 KiB  
Review
Plant Immunity: At the Crossroads of Pathogen Perception and Defense Response
by Sajad Ali, Anshika Tyagi and Zahoor Ahmad Mir
Plants 2024, 13(11), 1434; https://doi.org/10.3390/plants13111434 - 22 May 2024
Viewed by 572
Abstract
Plants are challenged by different microbial pathogens that affect their growth and productivity. However, to defend pathogen attack, plants use diverse immune responses, such as pattern-triggered immunity (PTI), effector-triggered immunity (ETI), RNA silencing and autophagy, which are intricate and regulated by diverse signaling [...] Read more.
Plants are challenged by different microbial pathogens that affect their growth and productivity. However, to defend pathogen attack, plants use diverse immune responses, such as pattern-triggered immunity (PTI), effector-triggered immunity (ETI), RNA silencing and autophagy, which are intricate and regulated by diverse signaling cascades. Pattern-recognition receptors (PRRs) and nucleotide-binding leucine-rich repeat (NLR) receptors are the hallmarks of plant innate immunity because they can detect pathogen or related immunogenic signals and trigger series of immune signaling cascades at different cellular compartments. In plants, most commonly, PRRs are receptor-like kinases (RLKs) and receptor-like proteins (RLPs) that function as a first layer of inducible defense. In this review, we provide an update on how plants sense pathogens, microbe-associated molecular patterns (PAMPs or MAMPs), and effectors as a danger signals and activate different immune responses like PTI and ETI. Further, we discuss the role RNA silencing, autophagy, and systemic acquired resistance as a versatile host defense response against pathogens. We also discuss early biochemical signaling events such as calcium (Ca2+), reactive oxygen species (ROS), and hormones that trigger the activation of different plant immune responses. This review also highlights the impact of climate-driven environmental factors on host–pathogen interactions. Full article
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<p>A schematic illustration showing the effect of climate change on environmental factors (A), pathogens (B), and the host defense system (C). Climate change increases temperature, rainfall, humidity, drought, carbon dioxide, and methane, which affects the plant health and immune system. These factors also change pathogen distribution, virulence, and resistance.</p>
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<p>Schematic illustration showing the activation of two-tier plant immunity, namely PTI and ETI, in plants after pathogen, MAMPs/DAMPs, or effectors perception by PPRs and NLRs. Plants undergo biochemical reprogramming such as calcium burst, ROS production, and hormonal activation, which regulates diverse antimicrobial responses like hypersensitive response or programmed cell death or systemic acquired resistance.</p>
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<p>A schematic representation showing SA- and JA-dependent plant immunity against bacterial, viral, and fungal pathogens. This illustration also shows the roles of different players that modulate SA/JA-dependent immune responses.</p>
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19 pages, 2800 KiB  
Article
Nucleotide-Binding Oligomerization Domain 1 (NOD1) Agonists Prevent SARS-CoV-2 Infection in Human Lung Epithelial Cells through Harnessing the Innate Immune Response
by Edurne Garcia-Vidal, Ignasi Calba, Eva Riveira-Muñoz, Elisabet García, Bonaventura Clotet, Pere Serra-Mitjà, Cecilia Cabrera, Ester Ballana and Roger Badia
Int. J. Mol. Sci. 2024, 25(10), 5318; https://doi.org/10.3390/ijms25105318 - 13 May 2024
Viewed by 581
Abstract
The lung is prone to infections from respiratory viruses such as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). A challenge in combating these infections is the difficulty in targeting antiviral activity directly at the lung mucosal tract. Boosting the capability of the respiratory [...] Read more.
The lung is prone to infections from respiratory viruses such as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). A challenge in combating these infections is the difficulty in targeting antiviral activity directly at the lung mucosal tract. Boosting the capability of the respiratory mucosa to trigger a potent immune response at the onset of infection could serve as a potential strategy for managing respiratory infections. This study focused on screening immunomodulators to enhance innate immune response in lung epithelial and immune cell models. Through testing various subfamilies and pathways of pattern recognition receptors (PRRs), the nucleotide-binding and oligomerization domain (NOD)-like receptor (NLR) family was found to selectively activate innate immunity in lung epithelial cells. Activation of NOD1 and dual NOD1/2 by the agonists TriDAP and M-TriDAP, respectively, increased the number of IL-8+ cells by engaging the NF-κB and interferon response pathways. Lung epithelial cells showed a stronger response to NOD1 and dual NOD1/2 agonists compared to control. Interestingly, a less-pronounced response to NOD1 agonists was noted in PBMCs, indicating a tissue-specific effect of NOD1 in lung epithelial cells without inducing widespread systemic activation. The specificity of the NOD agonist pathway was confirmed through gene silencing of NOD1 (siRNA) and selective NOD1 and dual NOD1/2 inhibitors in lung epithelial cells. Ultimately, activation induced by NOD1 and dual NOD1/2 agonists created an antiviral environment that hindered SARS-CoV-2 replication in vitro in lung epithelial cells. Full article
(This article belongs to the Special Issue Viral and Host Targets to Fight RNA Viruses)
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<p>NLR agonists induce innate immune activation in in vitro lung epithelial and myeloid models. (<b>A</b>) Workflow to screen for potential immunomodulators of the innate immune system in A549 lung epithelial and THP-1 myeloid cell lines. (<b>B</b>) Library classification of tested compounds according to their reported target. (<b>C</b>) Heatmap illustrates the immune activation induced by immunomodulators targeting PRR subfamilies in lung epithelial A549 and myeloid THP-1 cells, as determined by the intracellular staining of IL-8 by flow cytometry. (<b>D</b>) Representative dot-plots showing IL-8+ intracellular staining of lung epithelial A549 (<b>left panel</b>) and myeloid THP-1 (<b>right panel</b>) cells upon treatment with NLR agonists, as determined by flow cytometry compared to untreated (UN) cells.</p>
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<p>Cytokine response is preferentially triggered by NOD1 and dual NOD1/2 agonists in lung epithelial cells. (<b>A</b>) Cytokine response to NLR agonists triggered by NOD1-, NOD1/2- and NOD2-specific agonists in lung epithelial A549-Dual cells. Immune response was determined by the percentage of intracellular IL-8+ (<b>left</b>) and TNFα+ (<b>right</b>) cell quantification by flow cytometry after 24 h of treatment, using LPS (1 µg/mL, yellow bar) non-treated condition (UN, black bar) as controls. (<b>B</b>) Induction of the proinflammatory response upon treatment with increasing concentrations of NOD1, NOD1/2 and NOD2 ligands in lung epithelial A549-Dual cells after 24 h of treatment. The intracellular stainings of IL-8 and TNFα were determined by flow cytometry as subrogate representative markers of the proinflammatory response, using LPS and UN as controls. Mean ± SD of three independent experiments is shown. * <span class="html-italic">p</span> &lt; 0.05; *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>NOD1 and NOD1/2 agonists induce innate immune activation in vitro in lung epithelial through the NF-κB and ISRE pathways. (<b>A</b>) Induction of the NF-κB activity triggered by NLR agonists upon recognition by the NOD1, NOD1/2 and NOD2 receptors in lung epithelial A549-Dual cells after 24 h of treatment. LPS (yellow bar) and Poly(I:C) (grey bar) were used as controls for NF-κB activation. (<b>B</b>) Assessment of NLR agonist activity on type I IFN response signaling by the quantification of interferon-stimulated response element (ISRE)-dependent gene expression in lung epithelial A549-Dual cells after 24 h of treatment. Values were relativized to the untreated (ND, black bar) condition. (<b>C</b>) Relative mRNA expression of IL-8, CXCL10 and ISG15 in A549-Dual treated cells with 50 µM of selected NOD agonists for 8 h measured by qPCR (normalized to GAPDH expression). Mean ± SD of three independent experiments is shown. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Activity of NOD1 and dual NOD1/2 agonists is specific in lung epithelial cells. (<b>A</b>) Gene expression of NOD1 receptor in A549-Dual cells transiently silenced with siRNA targeting NOD1 (siNOD1). Mock and non-specific siRNA (siNT) were used as controls. (<b>B</b>) Cell viability of A549-Dual cells treated with siNOD1 and siNT, using mock condition as control. Cell viability was determined by LIVE/DEAD staining and measured by flow cytometry. (<b>C</b>) Activity of NOD1 agonists (TriDAP and C12-iE-DAP), dual NOD1/2 (M-TriDAP) and NOD2 (MDP) in A549 cells treated with siNOD1. Intracellular staining of proinflammatory IL-8+ cells was determined by flow cytometry using the mock and siNT conditions, respectively. (<b>D</b>) Induction of the NF-κB and ISRE (<b>E</b>) activation pathways in A549-Dual cells treated with NOD1, dual NOD1/2 or NOD2 agonists with 50 µM of selective NOD1 inhibitor ML130, 50 µM of NOD1/2 inhibitor NOD-IN-1 or untreated (UNT), respectively. Red dotted line indicates the basal NF-κB (<b>left</b>) or ISRE activity (<b>right</b>) in A549-Dual cells. Mean ± SD of three independent experiments is shown. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>NLR agonist-induced cytokine response is preferentially triggered by NOD2 in PBMCs. (<b>A</b>) Assessment of the cytokine response to NLR agonists triggered by specific NOD1, dual NOD1/2 and NOD2 agonists in PBMCs. The percentages of intracellular IL-1β+, TNFα+ and IL-6+ cells were measured as representative markers of the proinflammatory response. Values were relativized to the non-treated condition (ND, black bar). LPS (1 µg/mL, yellow bar) and PMA (50 ng/mL) + ionomycin (1 µM) were used as positive controls. (<b>B</b>) Dose-response induction of proinflammatory cytokines IL-1β+, TNFα+ and IL-6+ in PBMCs treated with increasing concentrations of TriDAP (NOD1), M-TriDAP (dual NOD1/2) and MDP (NOD2) agonists. Mean ± SD of three independent experiments is shown. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>NOD1 and dual NOD1/2 agonists impair SARS-CoV-2 replication in lung epithelial cells. Pretreatment of lung epithelial A549-Dual cells for 3 h with increasing concentrations of NOD1 and dual NOD1/2 agonists preferentially inhibits SARS-CoV-2 replication. (<b>A</b>) Representative dot-plots of infected cells treated with NOD agonists as measured by flow cytometry. (<b>B</b>) Quantification of viral replication measured as the percentage of SARS-CoV-2-GFP+ cells determined by flow cytometry after 48 h of infection. Values were relativized to the untreated condition (INF, black bar). TLR3 agonist Poly(I:C) (light gray bars) was used as control for the induction of the innate immune response. Mean ± SD of three independent experiments is shown. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; EC<sub>50</sub>: half maximal effective concentration.</p>
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13 pages, 729 KiB  
Review
Hepatocyte Intrinsic Innate Antiviral Immunity against Hepatitis Delta Virus Infection: The Voices of Bona Fide Human Hepatocytes
by Yein Woo, Muyuan Ma, Masashi Okawa and Takeshi Saito
Viruses 2024, 16(5), 740; https://doi.org/10.3390/v16050740 - 8 May 2024
Viewed by 1292
Abstract
The pathogenesis of viral infection is attributed to two folds: intrinsic cell death pathway activation due to the viral cytopathic effect, and immune-mediated extrinsic cellular injuries. The immune system, encompassing both innate and adaptive immunity, therefore acts as a double-edged sword in viral [...] Read more.
The pathogenesis of viral infection is attributed to two folds: intrinsic cell death pathway activation due to the viral cytopathic effect, and immune-mediated extrinsic cellular injuries. The immune system, encompassing both innate and adaptive immunity, therefore acts as a double-edged sword in viral infection. Insufficient potency permits pathogens to establish lifelong persistent infection and its consequences, while excessive activation leads to organ damage beyond its mission to control viral pathogens. The innate immune response serves as the front line of defense against viral infection, which is triggered through the recognition of viral products, referred to as pathogen-associated molecular patterns (PAMPs), by host cell pattern recognition receptors (PRRs). The PRRs–PAMPs interaction results in the induction of interferon-stimulated genes (ISGs) in infected cells, as well as the secretion of interferons (IFNs), to establish a tissue-wide antiviral state in an autocrine and paracrine manner. Cumulative evidence suggests significant variability in the expression patterns of PRRs, the induction potency of ISGs and IFNs, and the IFN response across different cell types and species. Hence, in our understanding of viral hepatitis pathogenesis, insights gained through hepatoma cell lines or murine-based experimental systems are uncertain in precisely recapitulating the innate antiviral response of genuine human hepatocytes. Accordingly, this review article aims to extract and summarize evidence made possible with bona fide human hepatocytes-based study tools, along with their clinical relevance and implications, as well as to identify the remaining gaps in knowledge for future investigations. Full article
(This article belongs to the Special Issue Life Cycle of Hepatitis D Virus (HDV) and HDV-Like Agents)
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<p>Overview of the hepatic IFN system in the regulation of HDV infection in human hepatocytes: current understanding and gaps in knowledge. HDV enters hepatocytes through the interaction between its HBsAg and the host cell surface protein NTCP. Replication occurs in the nucleus, generating various viral RNA species. Currently, MDA5, one of the RLHs, and to a lesser extent, RIG-I, are considered key PRRs that sense HDV PAMPs (vRNA species). The interaction between RLHs and vRNA species triggers the activation of the MAVS-IRF3/7 pathway and induces ISGs and IFNs (1). ADAR1, an ISG, facilitates the HDV life cycle by introducing a point mutation enabling L-HDAg production, functioning as a proviral host factor. OAS, another ISG, activates the RNaseL pathway via the production of ppp2′-5′A, which in turn produces RIG-I and MDA5 ligands through cleaving vRNA and host RNA species. Therefore, both RIG-I and MDA5 are expected to play a role in the induction of ISGs and IFNs in HDV infection. IFNs, predominantly type III IFNs, secreted from the infected hepatocytes act on both infected and infection-naïve hepatocytes to induce ISGs via activation of Jak-STAT signaling cascades (2); thereby serving as the second wave of the antiviral response in the infected cells as well as establishing a tissue-wide antiviral state in the liver. Despite these sophisticated innate antiviral responses, the hepatocyte intrinsic IFN system is incapable of halting HDV infection due to HDV’s high resistance to the antiviral properties of ISGs and the establishment of cellular IFN refractoriness resulting from constitutive exposure to IFNs.</p>
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21 pages, 1496 KiB  
Review
The Dynamic Relationship between Dengue Virus and the Human Cutaneous Innate Immune Response
by Michelle M. Martí, Priscila M. S. Castanha and Simon M. Barratt-Boyes
Viruses 2024, 16(5), 727; https://doi.org/10.3390/v16050727 - 4 May 2024
Viewed by 956
Abstract
Dengue virus (DENV) is a continuing global threat that puts half of the world’s population at risk for infection. This mosquito-transmitted virus is endemic in over 100 countries. When a mosquito takes a bloodmeal, virus is deposited into the epidermal and dermal layers [...] Read more.
Dengue virus (DENV) is a continuing global threat that puts half of the world’s population at risk for infection. This mosquito-transmitted virus is endemic in over 100 countries. When a mosquito takes a bloodmeal, virus is deposited into the epidermal and dermal layers of human skin, infecting a variety of permissive cells, including keratinocytes, Langerhans cells, macrophages, dermal dendritic cells, fibroblasts, and mast cells. In response to infection, the skin deploys an array of defense mechanisms to inhibit viral replication and prevent dissemination. Antimicrobial peptides, pattern recognition receptors, and cytokines induce a signaling cascade to increase transcription and translation of pro-inflammatory and antiviral genes. Paradoxically, this inflammatory environment recruits skin-resident mononuclear cells that become infected and migrate out of the skin, spreading virus throughout the host. The details of the viral–host interactions in the cutaneous microenvironment remain unclear, partly due to the limited body of research focusing on DENV in human skin. This review will summarize the functional role of human skin, the cutaneous innate immune response to DENV, the contribution of the arthropod vector, and the models used to study DENV interactions in the cutaneous environment. Full article
(This article belongs to the Special Issue Innate and Adaptive Immunity to Cutaneous Virus Infection)
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<p>Schematic of pattern recognition receptors (PRRs) involved in intracellular viral sensing and downstream signaling. TLR-3/7/8/9, RIG-I, and MDA5 are ds- or ssRNA-sensing proteins, whereas cGAS is a dsDNA-sensing protein. These PRRs culminate in the recruitment and phosphorylation of interferon regulatory factors (IRFs). Activated IRFs translocate to the nucleus and bind IFN-stimulated response elements (ISRE) that induce transcription of type I interferons (IFNs) and select IFN-stimulated genes (ISGs). Released type I IFN binds to IFN-αβ receptors (IFNAR) and induces the JAK-STAT signaling pathway. JAK-Tyk2 kinases dimerize, and the activated form phosphorylates signal transducers and activators of transcription 1 and 2 (STAT). IRF9 is recruited to this complex and nuclearly translocates, inducing the expression of ISGs. These pathways create a positive feedback loop that amplifies the transcription of IFNs and ISGs in the skin, fostering an antiviral environment to combat viral infections. Red circles represent phosphorylation.</p>
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<p>Schematic of an ex vivo human skin explant model. (1). Dengue virus (DENV) is inoculated into tissue with a bifurcated needle. (2). DENV infects keratinocytes and nearby Langerhans cells. (3). Infected and bystander keratinocytes produce cytokines and chemokines to activate the immune response and recruit immune cells from surrounding tissue to the site of infection. (4). The virus spreads to the dermis and infects fibroblasts, mast cells, dermal dendritic cells, and macrophages. (5). Infected and bystander dermal cells produce cytokines and chemokines to recruit cells and prevent the spread of infection. (6). Infected Langerhans cells and dermal dendritic cells migrate out of the tissue into the media, mimicking the migration to lymphoid tissue that occurs in humans. * Red = infected cells, blue = uninfected cells. Cells not drawn to scale; lymphocytes and natural killer cells not pictured.</p>
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17 pages, 21285 KiB  
Article
DC-SIGN of Largemouth Bass (Micropterus salmoides) Mediates Immune Functions against Aeromonas hydrophila through Collaboration with the TLR Signaling Pathway
by Mengmeng Huang, Jingwen Liu, Zhenzhen Yuan, Youxing Xu, Yang Guo, Shun Yang and Hui Fei
Int. J. Mol. Sci. 2024, 25(9), 5013; https://doi.org/10.3390/ijms25095013 - 3 May 2024
Viewed by 649
Abstract
C-type lectins in organisms play an important role in the process of innate immunity. In this study, a C-type lectin belonging to the DC-SIGN class of Micropterus salmoides was identified. MsDC-SIGN is classified as a type II transmembrane protein. The extracellular segment of [...] Read more.
C-type lectins in organisms play an important role in the process of innate immunity. In this study, a C-type lectin belonging to the DC-SIGN class of Micropterus salmoides was identified. MsDC-SIGN is classified as a type II transmembrane protein. The extracellular segment of MsDC-SIGN possesses a coiled-coil region and a carbohydrate recognition domain (CRD). The key amino acid motifs of the extracellular CRD of MsDC-SIGN in Ca2+-binding site 2 were EPN (Glu-Pro-Asn) and WYD (Trp-Tyr-Asp). MsDC-SIGN-CRD can bind to four pathogen-associated molecular patterns (PAMPs), including lipopolysaccharide (LPS), glucan, peptidoglycan (PGN), and mannan. Moreover, it can also bind to Gram-positive, Gram-negative bacteria, and fungi. Its CRD can agglutinate microbes and displays D-mannose and D-galactose binding specificity. MsDC-SIGN was distributed in seven tissues of the largemouth bass, among which the highest expression was observed in the liver, followed by the spleen and intestine. Additionally, MsDC-SIGN was present on the membrane of M. salmoides leukocytes, thereby augmenting the phagocytic activity against bacteria. In a subsequent investigation, the expression patterns of the MsDC-SIGN gene and key genes associated with the TLR signaling pathway (TLR4, NF-κB, and IL10) exhibited an up-regulated expression response to the stimulation of Aeromonas hydrophila. Furthermore, through RNA interference of MsDC-SIGN, the expression level of the DC-SIGN signaling pathway-related gene (RAF1) and key genes associated with the TLR signaling pathway (TLR4, NF-κB, and IL10) was decreased. Therefore, MsDC-SIGN plays a pivotal role in the immune defense against A. hydrophila by modulating the TLR signaling pathway. Full article
(This article belongs to the Section Molecular Immunology)
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<p>Molecular characteristics of MsDC-SIGN. (<b>A</b>) Nucleotide and deduced amino acid sequences of MsDC-SIGN. Nucleotides and amino acids are numbered. CRD domains are underlined and conserved cysteines are shown in bold italics. The motifs governing carbohydrate-binding specificity are shadowed. (<b>B</b>) The predicted structure domains of MsDC-SIGN by SMART. The blue region is the transmembrane region, the green region is coiled-coil, and the pink region is CRD. (<b>C</b>) ClustalW multiple sequence alignment of MsDC-SIGN with other C-type lectins, including FcLectin (AAX63905.1, <span class="html-italic">Penaeus chinensis</span>), SsCTL4 (AXQ05184.1, <span class="html-italic">S. schlegelii</span>), Ec-CTLP (AGM15882.1, <span class="html-italic">Epinephelus coioides</span>), SpCTL-6 (AIC80997.1, <span class="html-italic">Scylla paramamosain</span>), P-selectin (NP_002996, <span class="html-italic">H. sapiens</span>), PtCTL-3 (ATE51203.1, <span class="html-italic">Portunus trituberculatus</span>), LvLec (ABU62825.1, <span class="html-italic">Penaeus vannamei</span>), and MsDC-SIGN (XP_038580390.1, <span class="html-italic">Micropterus salmoides</span>). Amino acid residues that are conserved in at least 50% of sequences are shaded dark gray, and similar amino acids are shaded light gray. Conserved cysteine residues involved in the formation of CRD internal disulfide bridges are marked with ▲, and the two extra cysteine residues in the long-form are marked with △. The motifs determining the carbohydrate-binding specificity are boxed.</p>
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<p>Analysis of rCRD by SDS-PAGE (<b>A</b>) and Western blot (<b>B</b>). (<b>A</b>) Lane M: protein molecular standard; Lane 1: negative control of rCRD (without induction); Lane 2: cell lysate of rCRD with induction; Lane 3: purified rCRD. (<b>B</b>) Lane M: prestained protein molecular standard; Lane 1: Western blot based on the purified rCRD of MsDC-SIGN with mouse serum antibody IgG.</p>
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<p>ELISA investigation of the interaction between rCRD and PAMPs. Plates were coated with four PAMPs and then incubated with rCRD and rTrx at different concentrations. After incubation with the rabbit anti-6×His-tag (HRP) polyclonal antibody (1:4000, Abcam), interactions between rCRD and PAMPs were detected following the instructions of the EL-TMB Chromogenic Reagent kit (Sangon) at 450 nm. (<b>A</b>) The binding curve of rCRD to glucan; (<b>B</b>) the binding curve of rCRD to LPS; (<b>C</b>) the binding curve of rCRD to PGN; (<b>D</b>) the binding curve of rCRD to mannan.</p>
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<p>The microbe-binding spectrum of rCRD assessed by ELISA. Plates coated with microbes were incubated with rCRD and rTrx. After incubation with the rabbit anti-6×His-tag (HRP) polyclonal antibody (1:4000, Abcam), interactions between microbes and recombinant proteins were detected following the instructions of the EL-TMB Chromogenic Reagent kit (Sangon) at 450 nm. ** indicates an extremely significant difference (<span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Microorganism agglutination activity of rCRD of MsDC-SIGN. Microorganisms (<span class="html-italic">A</span>. <span class="html-italic">hydrophila</span>, <span class="html-italic">V. fluvialis</span>, and <span class="html-italic">S</span>. <span class="html-italic">aureus</span>) were first washed with TBS buffer and then resuspended to a concentration of 1 × 10<sup>8</sup> cells mL<sup>−1</sup>. They were then separately mixed with rCRD at a concentration of 10 μM, with rTrx used as a negative control. CaCl<sub>2</sub> or EDTA-2Na was added to reach a final concentration of 5 mM, and the samples were incubated at 30 °C for 30 min. After incubation, the samples were fixed with 4% paraformaldehyde, clinical slices were prepared, stained with Giemsa stain, and observed under a light microscope to detect agglutination.</p>
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<p>The carbohydrate-binding specificity of rCRD was determined by agglutination inhibition assay. rCRD was preincubated with D-mannose, N-acetylglucosamine (NAG), D-fucose, D-lactose, D-galactose, and mixtures of the aforementioned carbohydrates. Subsequently, rCRD, along with the carbohydrates, was incubated with <span class="html-italic">S. aureus</span>. The agglutination inhibition activity was observed.</p>
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<p>Confocal analysis of MsDC-SIGN distribution on leukocytes. Leukocytes were stained with polyclonal antibody against rCRD followed by Alexa Fluor 488-labeled anti-mouse immunoglobulin (IgG) antibody staining. Dil and DAPI were used to stain cell membrane and cell nucleus, respectively. (<b>A</b>) Leukocytes incubated with polyclonal antibody against rCRD; (<b>B</b>) leukocytes incubated with mouse negative control antibody.</p>
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<p>Flow cytometric analysis of phagocytosis of largemouth bass leukocytes to <span class="html-italic">A</span>. <span class="html-italic">hydrophila</span>. (<b>A</b>) Leukocytes in the peripheral blood were gated (P1, P2, and P3) on an FSC/SSC dot plot. (<b>B</b>–<b>D</b>) The fluorescence histogram showing the percentage of phagocytic leukocytes gated in P1, P2, and P3. (<b>E</b>) Leukocytes in the peripheral blood incubated with the antibody against rCRD were gated (P1, P2, and P3) on an FSC/SSC dot plot. (<b>F</b>–<b>H</b>) The fluorescence histogram showing the percentage of phagocytic leukocytes blocked with the antibody against rCRD gated in P1, P2, and P3. (<b>I</b>) Statistical analysis of the phagocytosis rate of leukocytes without or with the antibody against rCRD blocking. The asterisk on the bars represents statistical significance of phagocytic rates between two groups (** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>The tissue distribution pattern of MsDC-SIGN, TLR4, NF-κB, and IL10. (<b>A</b>) The tissue distribution pattern of MsDC-SIGN; (<b>B</b>) the tissue distribution pattern of TLR4; (<b>C</b>) the tissue distribution pattern of NF-κB; (<b>D</b>) the tissue distribution pattern of IL10. The β-actin gene was used as the internal control. The results are presented as the mean ± S.E. (n = 5).</p>
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<p>The expression levels of MsDC-SIGN and TLR4 signaling pathway genes post stimulation of <span class="html-italic">M. salmoides</span> by <span class="html-italic">A. hydrophila</span>. (<b>A</b>) The expression pattern of MsDC-SIGN, TLR4, NF-κB, and IL10 in the intestine post stimulation. (<b>B</b>) The expression pattern of MsDC-SIGN, TLR4, NF-κB, and IL10 in the liver post stimulation. * Indicates that there is a significant difference between the two groups of data in the experimental group and the control group (<span class="html-italic">p</span> &lt; 0.05); ** indicates that the difference between the two groups of data in the experimental group and the control group is extremely significant (<span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Expression levels of key genes in the DC-SIGN signaling pathway and the TLR signaling pathway after MsDC-SIGN silencing and <span class="html-italic">A. hydrophila</span> stimulation. (<b>A</b>) Expression level of the MsDC-SIGN gene. (<b>B</b>) Expression level of the RAF1 gene. (<b>C</b>) Expression level of the TLR4 gene. (<b>D</b>) Expression level of the NF-κB gene. (<b>E</b>) Expression level of the IL10 gene. * Indicates that there is a significant difference between the two groups of data in the experimental group and the control group (<span class="html-italic">p</span> &lt; 0.05); ** indicates that the difference between the two groups of data in the experimental group and the control group is extremely significant (<span class="html-italic">p</span> &lt; 0.01).</p>
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11 pages, 836 KiB  
Communication
Availability of Receptors for Advanced Glycation End-Products (RAGE) Influences Differential Transcriptome Expression in Lungs from Mice Exposed to Chronic Secondhand Smoke (SHS)
by Katrina L. Curtis, Ashley Chang, Ryan Van Slooten, Christian Cooper, Madison N. Kirkham, Thomas Armond, Zack deBernardi, Brett E. Pickett, Juan A. Arroyo and Paul R. Reynolds
Int. J. Mol. Sci. 2024, 25(9), 4940; https://doi.org/10.3390/ijms25094940 - 30 Apr 2024
Viewed by 754
Abstract
The receptor for advanced glycation end-products (RAGE) has a central function in orchestrating inflammatory responses in multiple disease states including chronic obstructive pulmonary disease (COPD). RAGE is a transmembrane pattern recognition receptor with particular interest in lung disease due to its naturally abundant [...] Read more.
The receptor for advanced glycation end-products (RAGE) has a central function in orchestrating inflammatory responses in multiple disease states including chronic obstructive pulmonary disease (COPD). RAGE is a transmembrane pattern recognition receptor with particular interest in lung disease due to its naturally abundant pulmonary expression. Our previous research demonstrated an inflammatory role for RAGE following acute exposure to secondhand smoke (SHS). However, chronic inflammatory mechanisms associated with RAGE remain ambiguous. In this study, we assessed transcriptional outcomes in mice exposed to chronic SHS in the context of RAGE expression. RAGE knockout (RKO) and wild-type (WT) mice were delivered nose-only SHS via an exposure system for six months and compared to control mice exposed to room air (RA). We specifically compared WT + RA, WT + SHS, RKO + RA, and RKO + SHS. Analysis of gene expression data from WT + RA vs. WT + SHS showed FEZ1, Slpi, and Msln as significant at the three-month time point; while RKO + SHS vs. WT + SHS identified cytochrome p450 1a1 and Slc26a4 as significant at multiple time points; and the RKO + SHS vs. WT + RA revealed Tmem151A as significant at the three-month time point as well as Gprc5a and Dynlt1b as significant at the three- and six-month time points. Notable gene clusters were functionally analyzed and discovered to be specific to cytoskeletal elements, inflammatory signaling, lipogenesis, and ciliogenesis. We found gene ontologies (GO) demonstrated significant biological pathways differentially impacted by the presence of RAGE. We also observed evidence that the PI3K-Akt and NF-κB signaling pathways were significantly enriched in DEGs across multiple comparisons. These data collectively identify several opportunities to further dissect RAGE signaling in the context of SHS exposure and foreshadow possible therapeutic modalities. Full article
(This article belongs to the Special Issue Advanced Glycation End Products (AGEs) and Their Receptor RAGE)
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<p>Principal Component Analysis Between All Samples. Visualization shows the quadruplicate samples tend to group primarily by WT or RKO, and secondarily by time point and exposure type. Relationships among the color-coded samples are shown in two dimensions.</p>
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<p>Correlation Analysis Between All Samples. Color-coded pairwise correlation values between all samples are shown. Samples having darker shading are more closely correlated. The diagonal, representing a self-to-self comparison, shows perfect correlation.</p>
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<p>Most Significant Signaling Pathways and Differentially Expressed Genes in the Comparison of RKO + SHS vs. WT + SHS After Three Months: (<b>A</b>) Dot plot of significant signaling pathways between RAGE-knockout animals and wild-type animals after three months of exposure to secondhand smoke. Dot size and color represent number of genes in the pathway and the adjusted <span class="html-italic">p</span>-value, respectively. (<b>B</b>) Table showing the five most significant differentially expressed genes in a comparison between RAGE-knockout animals and wild-type animals after three months of exposure to secondhand smoke. (<b>C</b>) Table showing the top five most significant KEGG intracellular signaling pathways in a comparison between RAGE-knockout animals and wild-type animals after three months of exposure to secondhand smoke.</p>
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29 pages, 3947 KiB  
Review
Exploring Immune Redox Modulation in Bacterial Infections: Insights into Thioredoxin-Mediated Interactions and Implications for Understanding Host–Pathogen Dynamics
by Omer M. A. Dagah, Billton Bryson Silaa, Minghui Zhu, Qiu Pan, Linlin Qi, Xinyu Liu, Yuqi Liu, Wenjing Peng, Zakir Ullah, Appolonia F. Yudas, Amir Muhammad, Xianquan Zhang and Jun Lu
Antioxidants 2024, 13(5), 545; https://doi.org/10.3390/antiox13050545 - 29 Apr 2024
Viewed by 1137
Abstract
Bacterial infections trigger a multifaceted interplay between inflammatory mediators and redox regulation. Recently, accumulating evidence has shown that redox signaling plays a significant role in immune initiation and subsequent immune cell functions. This review addresses the crucial role of the thioredoxin (Trx) system [...] Read more.
Bacterial infections trigger a multifaceted interplay between inflammatory mediators and redox regulation. Recently, accumulating evidence has shown that redox signaling plays a significant role in immune initiation and subsequent immune cell functions. This review addresses the crucial role of the thioredoxin (Trx) system in the initiation of immune reactions and regulation of inflammatory responses during bacterial infections. Downstream signaling pathways in various immune cells involve thiol-dependent redox regulation, highlighting the pivotal roles of thiol redox systems in defense mechanisms. Conversely, the survival and virulence of pathogenic bacteria are enhanced by their ability to counteract oxidative stress and immune attacks. This is achieved through the reduction of oxidized proteins and the modulation of redox-sensitive signaling pathways, which are functions of the Trx system, thereby fortifying bacterial resistance. Moreover, some selenium/sulfur-containing compounds could potentially be developed into targeted therapeutic interventions for pathogenic bacteria. Taken together, the Trx system is a key player in redox regulation during bacterial infection, and contributes to host–pathogen interactions, offering valuable insights for future research and therapeutic development. Full article
(This article belongs to the Section Antioxidant Enzyme Systems)
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<p>Overview of TLR and NOD receptor-mediated immune response. Step 1: Pathogen Detection: TLRs identify extracellular/endosomal PAMPs and DAMPs, such as lipopolysaccharides and heat shock proteins. NOD-1 and NOD-2 detect intracellular peptidoglycan fragments. Step 2: Signal Transduction: TLRs activate signaling leading to kinase activation (IRAKs, TRAF-6). NOD receptors directly activate RIPK-2 kinase. Step 3: Activation of Signaling Complexes, ROS Production, and Response Amplification: 3.1. Activation of Signaling Complexes: both receptor types stimulate the TAK-1/TAB complex, which then activates the IKK complex essential for NF-κB pathway initiation. 3.2. Activation of NOX: Triggered by NOD-2 signaling or TLRs, NOX generates reactive oxygen species (ROS). This directly activates the IKK complex. 3.3. Role of TRAF-6 and NOD-2: TRAF-6 and NOD-2 can enhance the production of mitochondrial ROS (mROS), which further activates the IKK complex. 3.4. Dissociation of Trx from TXNIP: the increase in ROS causes Trx to dissociate from TXNIP. 3.5. Activation of the IKK Complex: each of these steps synergistically contributes to the activation of the IKK complex, central to regulating inflammatory responses and immune function. Step 4: NF-κB-Mediated Transcription and MAPK Activation: 4.1. NF-κB-Mediated Transcription: IKK complex phosphorylates IκB, allowing NF-κB to enter the nucleus and upregulate inflammatory genes, including cytokines and chemokines. 4.2. MAPK Activation: ROS and mROS contribute to the activation of the MAPK pathway. Step 5: Inflammatory Response and Immune Activation: NF-κB facilitates the assembly of the NLRP-3 inflammasome, which promotes the production of cytokines and chemokines. Concurrently, the activation of the MAPK pathway leads to the release of cytokines and interferons (IFN), thereby driving the recruitment of immune cells such as macrophages and neutrophils. This cascade enhances inflammation and pathogen neutralization through phagocytosis and the subsequent production of ROS/RNS. (PAMPs: pathogen-associated molecular patterns; PRRs: pattern recognition receptors; TLRs: toll-like receptors; NLRs: nucleotide-binding oligomerization domain-like receptors; DAMPs: damage-associated molecular patterns; IRAK: IL-1 receptor-associated kinase; TRAF-6: TNF receptor-associated factor 6; TAK-1: TGF-beta-activated kinase 1; TAB: TAK1-binding protein; IKK: IκB kinase; IκB: inhibitor kappa B; NF-κB: nuclear factor kappa-light-chain-enhancer of activated B cells; mROS: mitochondrial reactive oxygen species; NOD-1/2: nucleotide-binding oligomerization domain 1/2; RIPK-2: receptor-interacting protein kinase 2; NLRP-3: NLR family pyrin domain containing 3; IL-1β: interleukin-1 beta; NOX: NADPH oxidase; ROS: reactive oxygen species; MAPK: mitogen-activated protein kinase; Trx: thioredoxin; TXNIP: thioredoxin-interacting protein; TNF-α: tumor necrosis factor-alpha; ILs: interleukins; IFNs: interferons).</p>
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<p>Phagocytosis in neutrophils. Step 1: Mobilization of Azurophilic Granules: Neutrophils mobilize azurophilic granules, specialized lysosomes containing antimicrobial proteins such as MPO, elastase, and cathepsin. The azurophilic granules fuse with the phagosome, releasing their contents to interact with the engulfed pathogen. Step 2: Activation of NOX: the NOX-2 complex on the phagosomal membrane becomes activated, catalyzing the transfer of electrons from NADPH to molecular oxygen, generating ROS in the form of O<sub>2</sub><sup>−</sup>. Step 3: Conversion of Superoxide to Hydrogen Peroxide: SOD within the phagosome catalyzes the conversion of superoxide anion into H<sub>2</sub>O<sub>2</sub>. Step 4: Myeloperoxidase-Catalyzed Reactions: MPO released from azurophilic granules uses hydrogen peroxide as a substrate to form HOCl, a potent antimicrobial agent. Step 5: Synergistic Enzymatic Action: enzymes like elastase and cathepsin, alongside HOCl, degrade bacterial proteins, nucleic acids, and cell walls, effectively destroying the pathogen. (MPO: myeloperoxidase; NOX-2: NADPH oxidase 2; ROS: reactive oxygen species; O<sub>2</sub><sup>−</sup>: superoxide anion; SOD: superoxide dismutase: H<sub>2</sub>O<sub>2</sub>: hydrogen peroxide; HOCl: hypochlorous acid).</p>
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<p>NETosis in neutrophils. (Suicidal NETosis). Step 1: Activation of PKC-α: Various agents such as PMA directly stimulate PKC-α. Additionally, increased intracellular Ca<sup>2</sup>⁺ due to antibodies and the calcium ionophore A23187 elevate intracellular calcium levels, subsequently activating PKC-α. FGFR activation triggers PLC-γ, producing DAG to enhance PKC-α activity. Step 2: Cascade of Biochemical Reactions: PKC-α initiates the RAF kinase/threonine protein kinase/mitogen-activated protein kinase/extracellular signal-regulated kinase (RAF/MEK/ERK) signaling pathway, which then stimulates NOX, leading to ROS production. Step 3: ROS-Mediated Dissociation and Granule Release: Elevated ROS levels cause the oxidative dissociation of Trx from TXNIP, releasing Trx. Furthermore, ROS facilitates the release of azurophilic granules containing MPO, elastase, and cathepsin, which are crucial for the nuclear processes involved in suicidal NETosis. Step 4: Activation of PAD4: Increased intracellular calcium, due to the calcium ionophore A23187 and antibodies, can directly activate PAD4. Furthermore, freed Trx offers an alternative activation route for PAD4, distinctively without utilizing its oxidoreductive function. Step 5: Inflammatory Signaling Loop: CXCR activation by IL-8 initiates the PI3K/PKB pathway, promoting downstream signaling that activates NF-κB. NF-κB activation, stimulated by the PI3K/PKB pathway and TXNIP after dissociation from TRX, enhances iNOS production. This is essential for NO generation, which exacerbates inflammation and reinforces the suicidal NETosis feedback loop. Step 6: Histone Citrullination and NET Formation: PAD4 converts arginine to citrulline in histones, leading to histone citrullination and promoting NET formation, essential for both types of NETosis. (Vital NETosis). Step 1: Bacterial Induction and Calcium Elevation Pathway: Bacteria like <span class="html-italic">E. coli</span> and <span class="html-italic">S. aureus</span>, or bacterial-specific molecular patterns recognized by PRRs, induce vital NETosis. Activation of receptors such as TLR-2, TLR-4, and CR raises intracellular Ca<sup>2</sup>⁺ levels, facilitating PAD4 activation. Step 2: Activation of PAD4 and Histone Modification: similar to suicidal NETosis, elevated Ca<sup>2</sup>⁺ levels activate PAD4, which then mediates histone citrullination. Step 3: Histone Decondensation and NET Release: histone citrullination causes decondensation, and in vital NETosis, NETs are released from vesicles without causing membrane rupture or neutrophil death. (NETosis: neutrophil extracellular trap formation; PKC-α: protein kinase C alpha; PMA: phorbol myristate acetate; FGFR: fibroblast growth factor receptor; PLC-γ: phospholipase C-gamma; DAG: diacylglycerol; RAF/MEK/ERK—RAF kinase/mitogen-activated protein kinase/extracellular signal-regulated kinase signaling pathway; NOX: NADPH oxidase; ROS: reactive oxygen species; Trx: thioredoxin; TXNIP: thioredoxin interacting protein; MPO: myeloperoxidase; PAD-4: peptidylarginine deiminase 4; CXCR: C-X-C motif chemokine receptor; IL-8: interleukin 8; PI3K/PKB: phosphoinositide 3-kinases/protein kinase B signaling pathway; NF-κB: nuclear factor kappa-light-chain-enhancer of activated B cells; iNOS: inducible nitric oxide synthase; NO: nitric oxide; PRRs: pattern recognition receptors; TLR-2, TLR-4: toll-like receptor 2, toll-like receptor 4; CR: complement receptor).</p>
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<p>M1 macrophage pH regulation. Step 1: Bacterial Engulfment and NOX-2 Activation: macrophages engulf bacteria, activating NOX-2, which produces ROS. Step 2: TXNIP Dissociates from Trx: ROS triggers the dissociation of TXNIP from Trx, freeing TXNIP. Step 3: Activation of NF-κB and NLRP-3: Free TXNIP activates the transcription factor NF-κB and the NLRP-3 inflammasome, crucial for inflammatory responses. Concurrently, free Trx inhibits ROS. Step 4: Caspase-1 Activation: NLRP-3 activates caspase-1, which processes inflammatory cytokines and regulates ROS levels, maintaining an acidic phagosomal environment (pH 4). Step 5: Enhanced Bacterial Degradation: the acidic pH activates enzymes that degrade bacteria, promoting effective immune responses [<a href="#B17-antioxidants-13-00545" class="html-bibr">17</a>,<a href="#B24-antioxidants-13-00545" class="html-bibr">24</a>,<a href="#B29-antioxidants-13-00545" class="html-bibr">29</a>,<a href="#B57-antioxidants-13-00545" class="html-bibr">57</a>]. (NOX-2: NADPH oxidase 2; ROS: reactive oxygen species; TXNIP: thioredoxin-interacting protein; Trx: thioredoxin; NF-κB: nuclear factor kappa-light-chain-enhancer of activated B cells; NLRP-3: NLR family pyrin domain containing 3; IL-1β: interleukin 1 beta).</p>
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<p>M2 macrophage polarization. Step 1: Activation of STAT-6/PPAR-γ by IL-4: IL-4 stimulates PPARγ activation through STAT-6, which inhibits PKC-α and diminishes NOX-mediated ROS generation via the RAF/MEK/ERK pathway. Furthermore, the activation of STAT-6 and IRF-4 produces H<sub>2</sub>O<sub>2</sub>, which is essential for starting the transcription of M2-specific genes. IL-4 increases Arg-1 activity, shifting metabolism from nitric oxide (via iNOS) to ornithine, supporting tissue repair, via STAT-6/PPAR-γ [<a href="#B63-antioxidants-13-00545" class="html-bibr">63</a>,<a href="#B64-antioxidants-13-00545" class="html-bibr">64</a>]. Step 2: Nrf-2 Activation and Oxidative Stress Defense Enhancement: Nrf-2 regulates expression of SOD-1 and Trx systems by binding to antioxidant response elements (AREs), enhancing defense against oxidative stress and promoting M2 gene transcription [<a href="#B63-antioxidants-13-00545" class="html-bibr">63</a>,<a href="#B64-antioxidants-13-00545" class="html-bibr">64</a>]. SOD-1 assists in the activation of STAT-6 and IRF-4 by producing H<sub>2</sub>O<sub>2</sub>, which is essential for starting the transcription of M2-specific genes. Additionally, the overexpression of SOD-1 leads to a decrease in iNOS gene expression and a reduction in NO synthesis, while simultaneously promoting arginase I expression and increasing urea production These alterations affect collagen synthesis and play a role in the development of fibrosis [<a href="#B65-antioxidants-13-00545" class="html-bibr">65</a>,<a href="#B66-antioxidants-13-00545" class="html-bibr">66</a>]. The Trx system actively inhibits ROS production, whereas the Prx system specifically inhibits NO production. This targeted inhibition is crucial for reducing oxidative stress and supporting cellular repair mechanisms, thereby promoting M2 macrophage polarization [<a href="#B67-antioxidants-13-00545" class="html-bibr">67</a>,<a href="#B68-antioxidants-13-00545" class="html-bibr">68</a>]. Step 3: NOX-2 Downregulation and Lysosomal Enhancement: IL-4 directly downregulates NOX-2 and enhances expression of cathepsins S and L, improving phagosome protein degradation efficiency [<a href="#B62-antioxidants-13-00545" class="html-bibr">62</a>]. Step 4: Activation of PI3K/PKBPathway by PGE-2: PGE-2 activates the PI3K/PKB pathway, further suppressing NOX-2 activation and aiding M2 polarization [<a href="#B69-antioxidants-13-00545" class="html-bibr">69</a>]. (M2: M2 type macrophage; STAT-6: signal transducer and activator of transcription 6; PPAR-γ: peroxisome proliferator-activated receptor gamma; IL-4: interleukin 4; PKC-α: protein kinase C alpha; NOX: NADPH oxidase; ROS: reactive oxygen species: RAF: RAF kinase; MEK: mitogen-activated protein kinase; ERK: extracellular signal-regulated kinase; IRF-4: interferon regulatory factor 4; H<sub>2</sub>O<sub>2</sub>: hydrogen peroxide; Arg-1: arginase 1; iNOS: inducible nitric oxide synthase; Nrf-2: nuclear factor erythroid 2-related factor 2; SOD-1: superoxide dismutase 1; Trx: thioredoxin; AREs: antioxidant response elements; Prx: peroxiredoxin; NOX-2: NADPH oxidase 2; PI3K: phosphoinositide 3-kinase; PKB: protein kinase B; PGE-2: prostaglandin E2).</p>
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<p>Trx1 role in proliferation and differentiation of T cells. Step 1: NK Cells’ Role: NK cells influence the maturation of dendritic cells by releasing TNF-α and IFN-γ. Not only does IFN-γ mature DCs, but it also significantly drives the differentiation of Th1 cells. Step 2: DCs’ Role: Mature dendritic cells capture antigens and present them to naive T cells. This antigen presentation is crucial for the initial activation of the naive T cells, setting the stage for the adaptive immune response. The protein Trx1, secreted by dendritic cells, regulates the expression of CD4 and CD30 receptors on T cells. Trx1 not only adjusts receptor expression but also facilitates the conversion of cystine to cysteine, crucial for T-cell proliferation. Trx-1 deactivates IL-4, suppressing the Th2 immune response and favoring Th1. Step 3: Influence of Cytokines on Differentiation: Naive T cells differentiate into various helper T-cell subsets under the influence of local cytokines. IL-4 drives the differentiation into Th2 cells, while IFN-γ promotes the development of Th1 cells. Step 4: MDSCs’ Role: MDSCs limit cystine availability by competing for this molecule, which is essential for its conversion by antigen-presenting cells. This competition impairs T-cell function and promotes immune suppression by interacting with Trx1. Step 5: Feedback Loop between Th1 Cells and Macrophages Involving Trx-1 and IFN-γ: Trx1 enhances IFN-γ production in Th1 cells, which in turn promotes higher levels of Trx1. This feedback loop also involves IFN-γ-activated Trx1 in macrophages, which boosts IL-12 secretion by modulating the thiol redox state. (Trx1: thioredoxin 1; NK cells: natural killer cells; TNF-α: tumor necrosis factor alpha; IFN-γ: interferon gamma; DCs: dendritic cells; T cells: T lymphocytes; CD4: cluster of differentiation 4; CD30: cluster of differentiation 30; IL-4: interleukin 4; Th1: T helper type 1 cells; Th2: T helper type 2 cells; MDSCs: myeloid-derived suppressor cells; IL-12: interleukin 12).</p>
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<p>Role of Trx and Grx in oxidative stress response in bacteria. (<b>A</b>) The Trx system begins with the reduction of oxidized cysteine residues in proteins, facilitated by the CXXC motif in Trx. This involves an initial attack by the N-terminal cysteine of Trx to form a mixed disulfide with the substrate, followed by the action of the second cysteine to release a reduced substrate and oxidized Trx. The oxidized Trx is then regenerated by thioredoxin reductase, using NADPH as a reducing agent. (<b>B</b>) The process starts when dithiol Grx, using its N-terminal cysteine, attacks a disulfide bond in a substrate protein, creating a mixed disulfide complex. Then, the C-terminal cysteine of Grx also attacks, releasing a reduced substrate and turning Grx into its oxidized form. This oxidized Grx is then returned to its reduced state by two GSH molecules, forming GSSG in the process. Finally, GR converts the GSSG back into GSH. (<b>C</b>) Trx provides the electrons to peroxiredoxin and Msr in the defence against oxidative stress. Prx scavenges free radicals directly, and Msrs reduces free oxidized methionine or oxidized methionine residues in proteins. Trx is essential for regenerating active Msrs, highlighting its indispensable role across different systems. (Trx: thioredoxin; TrxR: thioredoxin reductase; Grx: glutaredoxin; GR: glutathione reductase; GSH: glutathione; GSSG: glutathione disulfide; Prx: peroxiredoxin; Met: methionine; MsrA: methionine sulfoxide reductase A; MsrB: methionine sulfoxide reductase B; Oxd.: oxidized; Red.: reduced).</p>
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<p>Mechanisms of immune suppression during bacterial infection. (<b>A</b>) Infection with <span class="html-italic">B. abortus</span> causes the expression of iNOS and production of NO, which suppress the expression of TXNIP within infected macrophages. Since TXNIP is crucial for activating NF-κB, its suppression leads to decreased activity of this critical transcription factor. With NF-κB activity diminished, the production of NO and ROS, both vital for immune defense, is also reduced. (<b>B</b>) <span class="html-italic">Edwardsiella piscicida</span> secretes Trxlp, a protein that mimics the structure of human hTrx1 but is devoid of redox activity. Trxlp binds directly to the IKK complex, which is essential for the activation of the NF-κB signaling pathway. This pathway is pivotal for initiating immune responses such as inflammation and apoptosis. The direct engagement of Trxlp with IKK obstructs the nuclear translocation of NF-κB. Without NF-κB in the nucleus, the transcription of immune response genes is hindered, which in turn reduces inflammation and apoptosis. Trxlp also interacts with Prx enzymes that normally reduce H<sub>2</sub>O<sub>2</sub>. This interaction instead leads to a localized accumulation of H<sub>2</sub>O<sub>2</sub>. The increase in H<sub>2</sub>O<sub>2</sub>, facilitated by Trxlp’s interaction with Prx, suppresses apoptosis signal-regulating kinase 1 (ASK1). ASK1 is involved in activating MAP kinases, key players in stress response pathways including those governing inflammation and cell death. Suppressing ASK1 leads to reduction in the activation of MAP kinases and the production of pro-inflammatory cytokines. This results in a weakened immune response, creating a more favorable environment for bacterial survival. (TXNIP: thioredoxin-interacting protein; NF-κB: nuclear factor kappa-light-chain-enhancer of activated B cells; NO: nitric oxide; ROS: reactive oxygen species; Trxlp: thioredoxin-like protein; hTrx1: human thioredoxin 1; IKK: IκB kinase inhibitor of kappa B; Prx: peroxiredoxin; H<sub>2</sub>O<sub>2</sub>: hydrogen peroxide; ASK1: apoptosis signal-regulating kinase 1; MAPKs: mitogen-activated protein kinases).</p>
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Article
Extracellular Nicotinamide Phosphoribosyltransferase Is a Therapeutic Target in Experimental Necrotizing Enterocolitis
by Melissa D. Halpern, Akash Gupta, Nahla Zaghloul, Senthilkumar Thulasingam, Christine M. Calton, Sara M. Camp, Joe G. N. Garcia and Mohamed Ahmed
Biomedicines 2024, 12(5), 970; https://doi.org/10.3390/biomedicines12050970 - 28 Apr 2024
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Abstract
Necrotizing enterocolitis (NEC) is the most common gastrointestinal emergency of prematurity. Postulated mechanisms leading to inflammatory necrosis of the ileum and colon include activation of the pathogen recognition receptor Toll-like receptor 4 (TLR4) and decreased levels of transforming growth factor beta (TGFβ). Extracellular [...] Read more.
Necrotizing enterocolitis (NEC) is the most common gastrointestinal emergency of prematurity. Postulated mechanisms leading to inflammatory necrosis of the ileum and colon include activation of the pathogen recognition receptor Toll-like receptor 4 (TLR4) and decreased levels of transforming growth factor beta (TGFβ). Extracellular nicotinamide phosphoribosyltransferase (eNAMPT), a novel damage-associated molecular pattern (DAMP), is a TLR4 ligand and plays a role in a number of inflammatory disease processes. To test the hypothesis that eNAMPT is involved in NEC, an eNAMPT-neutralizing monoclonal antibody, ALT-100, was used in a well-established animal model of NEC. Preterm Sprague–Dawley pups delivered prematurely from timed-pregnant dams were exposed to hypoxia/hypothermia and randomized to control—foster mother dam-fed rats, injected IP with saline (vehicle) 48 h after delivery; control + mAB—foster dam-fed rats, injected IP with 10 µg of ALT-100 at 48 h post-delivery; NEC—orally gavaged, formula-fed rats injected with saline; and NEC + mAb—formula-fed rats, injected IP with 10 µg of ALT-100 at 48 h. The distal ileum was processed 96 h after C-section delivery for histological, biochemical, molecular, and RNA sequencing studies. Saline-treated NEC pups exhibited markedly increased fecal blood and histologic ileal damage compared to controls (q < 0.0001), and findings significantly reduced in ALT-100 mAb-treated NEC pups (q < 0.01). Real-time PCR in ileal tissues revealed increased NAMPT in NEC pups compared to pups that received the ALT-100 mAb (p < 0.01). Elevated serum levels of tumor necrosis factor alpha (TNFα), interleukin 6 (IL-6), interleukin-8 (IL-8), and NAMPT were observed in NEC pups compared to NEC + mAb pups (p < 0.01). Finally, RNA-Seq confirmed dysregulated TGFβ and TLR4 signaling pathways in NEC pups that were attenuated by ALT-100 mAb treatment. These data strongly support the involvement of eNAMPT in NEC pathobiology and eNAMPT neutralization as a strategy to address the unmet need for NEC therapeutics. Full article
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<p>In each of the two separate studies, pups from 3–5 timed-pregnant Sprague–Dawley rats were delivered via C-section one day prior to scheduled birth. Pups were randomized and divided into four groups: control + vehicle, <span class="html-italic">n</span> = 10: fed by a foster dam and injected with saline (vehicle) 48 h post-delivery; control + ALT-100, <span class="html-italic">n</span> = 10: fed by a foster dam and injected with ALT-100 diluted in the vehicle 48 h post-delivery; NEC + vehicle, <span class="html-italic">n</span> = 29: exclusively hand-fed via oral gavage with formula and injected with the vehicle 48 h post-delivery; and NEC + ALT-100, <span class="html-italic">n</span> = 28: exclusively hand-fed via oral gavage with formula and injected with ALT-100 diluted in the vehicle 48 h post-delivery. Pups from all four groups were exposed to hypoxia (N<sub>2</sub> gas for 60 s), followed by hypothermia (4 °C for 10 min) twice daily. Pups from all groups were sacrificed at 96 h post-delivery.</p>
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<p>Elevated NAMPT expression in blood and ileal tissues from NEC pups. (<b>A</b>) Serum eNAMPT levels were evaluated in Ctrl + mAb (<span class="html-italic">n</span> = 5), NEC (<span class="html-italic">n</span> = 5), and NEC + mAb (<span class="html-italic">n</span> = 5) groups. There was a significant increase in serum eNAMPT levels among rat pups with NEC, which was attenuated in the NEC + eNAMPT ALT-100 mAb group. mAb RT-PCR (<b>B</b>) and Western blot (control 1-4 lanes; NEC 5-7 lanes; NEC + mAb 8-10 lanes) and densitometry (<b>C</b>) analyses of NAMP from ileal tissue homogenates showed a significant increase in protein NAMPT levels in the NEC group (<span class="html-italic">n</span> = 3) compared to the Ctrl + mAb group (<span class="html-italic">n</span> = 3) and a significant reduction in NAMPT expression in the NEC + ALT-100 mAb group (<span class="html-italic">n</span> = 3). Significant differences were determined by one-way ANOVA, followed by the Newman–Kuels post hoc test: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>eNAMPT-neutralizing mAb reduces NEC pathology. (<b>A</b>) Pathology scores represent ileal damage, as graded on a scale of 0 (healthy) to 4 (necrosis), with half point values used for a more refined assessment of disease. A score of 2 or greater is considered NEC. Data compiled from two independent studies. Ctrl, <span class="html-italic">n</span> = 10; Ctrl + mAb, <span class="html-italic">n</span> = 10; NEC, <span class="html-italic">n</span> = 29; and NEC + mAb, <span class="html-italic">n</span> = 28. Lines represent the mean pathology score for each group. (<b>B</b>) Fecal occult blood was measured by the guaiac test in Ctrl, <span class="html-italic">n</span> = 5; Ctrl + mAb, <span class="html-italic">n</span> = 5; NEC, <span class="html-italic">n</span> = 15; and NEC + mAb, <span class="html-italic">n</span> = 15. Scores represent the level of blood in the feces, as graded on a scale of 0 to 4, and lines represent the mean occult blood score for each group. Significant differences were determined by the Kruskal–Wallis test, followed by the Benjamini–Kreiger–Yekutieli false discovery rate method for multiple comparisons (** <span class="html-italic">q</span> &lt; 0.01, **** <span class="html-italic">q</span> &lt; 0.0001). Representative histology images show ileal damage in Ctrl (<b>C</b>), histological damage score 0.0), Ctrl + mAb (<b>D</b>), histological damage score 0.5), NEC (<b>E</b>), histological damage score 2.5), and NEC + mAb (<b>F</b>), histological damage score 1.5). Yellow arrowheads indicate RBC accumulation in the lamina propria. Scale bars represent 50 μm.</p>
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<p>Serum proinflammatory mediators in NEC are reduced by ALT-100, the eNAMPT-neutralizing mAb. Serum samples were obtained from pups’ blood at sacrifice from Ctrl + mAb, <span class="html-italic">n</span> = 8; NEC, <span class="html-italic">n</span> = 12; and NEC + mAb, <span class="html-italic">n</span> = 9. TNFα (<b>A</b>), IL-6 (<b>B</b>), and IL-8 (<b>C</b>) levels were determined by ELISA. Significant differences were determined by one-way ANOVA, followed by the Newman–Kuels post hoc test (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Heat map of TLR signaling genes (<b>A</b>) and TRL signaling pathway genes statistically significantly altered by the eNAMPT-neutralizing mAb (<b>B</b>–<b>H</b>). All groups, <span class="html-italic">n</span> = 3. Principal component analysis was performed using the Partek algorithm.</p>
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<p>Heat map of TGF<span class="html-italic">β</span> signaling genes (<b>A</b>) and TGF<span class="html-italic">β</span> signaling pathway genes (<b>B</b>–<b>G</b>). All groups, <span class="html-italic">n</span> = 3. Principal component analysis was performed using the Partek algorithm. In (<b>H</b>), reduced ileal TGF<span class="html-italic">β</span> in the NEC groups is normalized by treatment with the anti-eNAMPT mAb (Ctrl + mAb, <span class="html-italic">n</span> = 8; NEC, <span class="html-italic">n</span> = 11; and NEC + mAb, <span class="html-italic">n</span> = 12). Significant differences were determined by one-way ANOVA, followed by the Newman–Kuels post hoc test (* <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01).</p>
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