www.fgks.org   »   [go: up one dir, main page]

You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Sign in to use this feature.

Years

Between: -

Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Search Results (1,069)

Search Parameters:
Journal = Microorganisms
Section = Food Microbiology

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
16 pages, 504 KiB  
Article
Exploring the Effects of Freeze-Dried Sourdoughs with Lactiplantibacillus pentosus 129 and Limosilactobacillus fermentum 139 on the Quality of Long-Fermentation Bread
by Joanderson Gama Santos, Evandro Leite de Souza, Marcus Vinícius de Souza Couto, Tatiana Zanella Rodrigues, Ana Regina Simplício de Medeiros, Angela Maria Tribuzy de Magalhães Cordeiro, Marcos dos Santos Lima, Maria Elieidy Gomes de Oliveira, Maiara da Costa Lima, Noádia Priscilla Rodrigues de Araújo, Ingrid Conceição Dantas Gonçalves and Estefânia Fernandes Garcia
Microorganisms 2024, 12(6), 1199; https://doi.org/10.3390/microorganisms12061199 - 14 Jun 2024
Viewed by 294
Abstract
Sourdough production is a complex fermentation process. Natural sourdough fermentation without standardization causes great variability in microbial communities and derived products. Starter cultures have emerged as alternatives to natural fermentation processes, which could improve bakery quality and produce bioactive compounds. This study aimed [...] Read more.
Sourdough production is a complex fermentation process. Natural sourdough fermentation without standardization causes great variability in microbial communities and derived products. Starter cultures have emerged as alternatives to natural fermentation processes, which could improve bakery quality and produce bioactive compounds. This study aimed to evaluate the impacts of freeze-drying on the production and viability of sourdoughs with Lactiplantibacillus pentosus 129 (Lp) and Limosilactobacillus fermentum 139 (Lf), as well as their effects on the quality of long-fermentation bread. These strains were selected based on their better performance considering acidification and exopolysaccharide production capacity. Sourdough with Lp and Lf were propagated until the 10th day, when physicochemical and microbiological parameters were determined. The produced sourdoughs were freeze-dried, and bread samples were produced. The freeze-drying process resulted in high survival rates and few impacts on the metabolic activity of Lp and Lf until 60 days of storage. Incorporating Lp and Lf improved the microbiological and physicochemical properties of sourdough and long-fermentation breads. Tested freeze-dried sourdoughs led to reduced bread aging (higher specific volume and decreased starch retrogradation) and increased digestibility. The results show the potential of the freeze-dried sourdoughs produced with Lp and Lf as innovative strategies for standardizing production protocols for the bakery industry, especially for producing long-term fermentation bread. Full article
(This article belongs to the Section Food Microbiology)
Show Figures

Figure 1

Figure 1
<p>Sizes of microbial cell subpopulations with different physiological status in fresh sourdough before and after the freeze-drying. Sc: sourdough control; SLp: sourdough inoculated with <span class="html-italic">L. pentosus</span> 129; SLf: sourdough inoculated with <span class="html-italic">L. fermentum</span> 139; FSc: freeze-dried sourdough control; FSLp: freeze-dried sourdough inoculated with <span class="html-italic">L. pentosus</span> 129; FSLf: freeze-dried inoculated with <span class="html-italic">L. fermentum</span> 139.</p>
Full article ">
16 pages, 592 KiB  
Article
Leuconostoc gelidum Is the Major Species Responsible for the Spoilage of Cooked Sausage Packaged in a Modified Atmosphere, and Hop Extract Is the Best Inhibitor Tested
by Giuseppe Comi, Andrea Colautti, Cristian Edoardo Maria Bernardi, Simone Stella, Elisabetta Orecchia, Francesca Coppola and Lucilla Iacumin
Microorganisms 2024, 12(6), 1175; https://doi.org/10.3390/microorganisms12061175 - 10 Jun 2024
Viewed by 395
Abstract
Cooked sausages packaged in a modified atmosphere (MAP: 20% CO2, 70% N2, <0.2% O2) with evident yellow stains were analyzed. The aims of this work were to study the microbial cause of the spoilage and to evaluate different [...] Read more.
Cooked sausages packaged in a modified atmosphere (MAP: 20% CO2, 70% N2, <0.2% O2) with evident yellow stains were analyzed. The aims of this work were to study the microbial cause of the spoilage and to evaluate different antimicrobial compounds to prevent it. Leuconostoc gelidum was identified as the primary cause of the yellow coating in spoiled cooked sausage, as confirmed by its intentional inoculation on slices of unspoiled sausage. Leuconostoc gelidum was the main bacteria responsible for the yellow coating in spoiled cooked sausage, as confirmed by its intentional inoculation on slices of unspoiled sausage. The yellow color was also evident during growth in the model system containing cooked sausage extract, but the colonies on MRS agar appeared white, demonstrating that the food substrate stimulated the production of the yellow pigment. The spoilage was also characterized by different volatile compounds, including ketones, ethanol, acetic acid, and ethyl acetate, found in the spoiled cooked sausage packages. These compounds explained the activity of Leuc. gelidum because they are typical of heterofermentative LAB, cultivated either on food substrates or in artificial broths. Leuc. gelidum also produced slight swelling in the spoiled packages. The efficacy of different antimicrobials was assessed in model systems composed of cooked sausage extract with the antimicrobials added at food product concentrations. The data showed that sodium lactate, sodium acetate, and a combination of sodium lactate and sodium diacetate could only slow the growth of the spoiler—they could not stop it from occurring. Conversely, hop extract inhibited Leuc. gelidum, showing a minimal inhibitory concentration (MIC) of approximately 0.008 mg CAE/mL in synthetic broth and 4 mg CAE/kg in cooked sausage slices. Adding hop extract at the MIC did not allow Leuc. gelidum growth and did not change the sensorial characteristics of the cooked sausages. To our knowledge, this is the first report of the antimicrobial activities of hop extracts against Leuc. gelidum either in vitro or in vivo. Full article
(This article belongs to the Section Food Microbiology)
Show Figures

Figure 1

Figure 1
<p>Growth of <span class="html-italic">Leuconostoc gelidum</span> on cooked sausage: (<b>a</b>) growth; (<b>b</b>) no growth.</p>
Full article ">
17 pages, 3878 KiB  
Article
Functional Analysis of Stress Resistance of Bacillus cereus SCL10 Strain Based on Whole-Genome Sequencing
by Yanzhen Mao, Ye Yang, Fu Lin, Hanyu Chu, Lijie Zhou, Jiaojiao Han, Jun Zhou and Xiurong Su
Microorganisms 2024, 12(6), 1168; https://doi.org/10.3390/microorganisms12061168 - 8 Jun 2024
Viewed by 388
Abstract
A Gram-positive, rod-shaped, aerobic, motile, and spore-forming bacterium, designated SCL10, was isolated from Acaudina molpadioides exposure to Co-60 radiation. In this study, whole-genome sequencing was performed to identify the strain as Bacillus cereus and functional characterization, with a focus on stress resistance. The [...] Read more.
A Gram-positive, rod-shaped, aerobic, motile, and spore-forming bacterium, designated SCL10, was isolated from Acaudina molpadioides exposure to Co-60 radiation. In this study, whole-genome sequencing was performed to identify the strain as Bacillus cereus and functional characterization, with a focus on stress resistance. The genome of the B. cereus SCL10 strain was sequenced and assembled, revealing a size of 4,979,182 bp and 5167 coding genes. The genes involved in biological functions were annotated by using the GO, COG, KEGG, NR, and Swiss-Prot databases. The results showed that genes related to alkyl hydroperoxide reductase (ahpC, ahpF), DNA-binding proteins from starved cells (dps), spore and biofilm formation (spoVG, spo0A, gerP), cold shock-like protein (cspC, cspE), ATP-dependent chaperone (clpB), and photolyase, small, acid-soluble spore protein (SASP) and DNA repair protein (recA, radD) could explain the stress resistance. These findings suggest that antioxidant activity, sporulation, biofilm formation, and DNA protection may be considered as the main resistance mechanisms under exposure to radiation in the B. cereus SCL10 strain. Full article
(This article belongs to the Special Issue Food Microorganisms and Genomics)
Show Figures

Figure 1

Figure 1
<p>The species identification of genes annotated. The top 10 species with the highest matches were selected in the Non-Redundant Protein Sequence (NR) Database. The height of the bar represents the number of genes.</p>
Full article ">Figure 2
<p>The general function annotation of the <span class="html-italic">B. cereus</span> SCL10 strain involving eight databases. The number of genes annotated varies across different databases, which can be compared with a total number of 5167 coding sequence genes. The eight databases are labeled in different colors and the numbers are gene counts. COG: Cluster of Orthologous Groups of Proteins, GO: Gene Ontology, Pfam: Protein Family, Swiss-Prot: Non-redundant High-quality Proteins, KEGG: Kyoto Encyclopedia of Genes and Genomes, CAZy: Carbohydrate-active Enzymes, TCDB: Transporter Classification Database, antiSMASH: Secondary Metabolism Gene Clusters.</p>
Full article ">Figure 3
<p>The different function classification of the <span class="html-italic">B. cereus</span> SCL10 strain. (<b>A</b>) KEGG annotation. The <span class="html-italic">X</span>-axis is the number of genes, and the <span class="html-italic">Y</span>-axis is the KEGG pathway. Different colors of the columns represent different categories, and the corresponding category names are on the right side. (<b>B</b>) COG annotation. Different letters and colors represent different classifications, and the numbers beside the petals represent the number of genes. (<b>C</b>) GO annotation. The three colors of the outer circle represent the three categories, which are used to distinguish biological processes, cell components, and molecular functions. The bars indicate the number of genes with different functions at all levels of the catalog.</p>
Full article ">Figure 4
<p>The classification and gene number of protein families of the <span class="html-italic">B. cereus</span> SCL10 strain. The top 20 protein families with the highest numbers and correlations with resistance were selected in the protein families (Pfam) database.</p>
Full article ">Figure 5
<p>The TCDB annotation of the <span class="html-italic">B. cereus</span> SCL10 strain. The TC system is classified into 5 levels, each level corresponds to a letter or number in the TC number, and each letter or number represents a specific type of transport protein. Level 2 is a more specific subcategory below Level 1, and Level 3 is a transporter protein family classification. The horizontal coordinate indicates the number of Level 2.</p>
Full article ">Figure 6
<p>Gene distribution in gene islands of <span class="html-italic">B. cereus</span> SCL10 strain. On the left is the gene island ID, and on the right is the number and size of genes contained in the gene island. Horizontal coordinates are length scales. GIs shown in figure are less than 15 kb.</p>
Full article ">Figure 7
<p>Pathogenic factors and antibiotic resistance analysis of <span class="html-italic">B. cereus</span> SCL10 strain. (<b>A</b>) Distribution of virulence factors. (<b>B</b>) Distribution of pathogen–host interaction genes. (<b>C</b>) Distribution of main top 20 antibiotic resistance genes.</p>
Full article ">Figure 8
<p>Comparative genomic and evolutionary analysis of <span class="html-italic">B. cereus</span> SCL10 strain and other 19 strains. (<b>A</b>) Phylogenetic analysis based on single-copy genes of 20 strains. (<b>B</b>) Synteny analysis of <span class="html-italic">B. cereus</span> SCL10 strain and <span class="html-italic">B. cereus</span> MH19 strain. Red represents forward alignment, blue represents reverse alignment, and gaps represent possible rearrangements between two genomes. (<b>C</b>) Venn diagram of gene family analysis showing shared and unique genes of 20 strains.</p>
Full article ">
18 pages, 1558 KiB  
Article
Virulence Potential and Antimicrobial Resistance of Listeria monocytogenes Isolates Obtained from Beef and Beef-Based Products Deciphered Using Whole-Genome Sequencing
by Ayanda Manqele, Abiodun Adesiyun, Thendo Mafuna, Rian Pierneef, Rebone Moerane and Nomakorinte Gcebe
Microorganisms 2024, 12(6), 1166; https://doi.org/10.3390/microorganisms12061166 - 8 Jun 2024
Viewed by 280
Abstract
Listeria monocytogenes is a ubiquitous bacterial pathogen that threatens the food chain and human health. In this study, whole-genome sequencing (WGS) was used for the genomic characterization of L. monocytogenes (n = 24) from beef and beef-based products. Multilocus Sequence Type (MLST) analysis [...] Read more.
Listeria monocytogenes is a ubiquitous bacterial pathogen that threatens the food chain and human health. In this study, whole-genome sequencing (WGS) was used for the genomic characterization of L. monocytogenes (n = 24) from beef and beef-based products. Multilocus Sequence Type (MLST) analysis revealed that ST204 of CC204 was the most common sequence type (ST). Other sequence types detected included ST1 and ST876 of CC1, ST5 of CC5, ST9 of CC9, ST88 of CC88, ST2 and ST1430 of CC2, and ST321 of CC321. Genes encoding for virulence factors included complete LIPI-1 (pfrA-hly-plcA-plcB-mpl-actA) from 54% (13/24) of the isolates of ST204, ST321, ST1430, and ST9 and internalin genes inlABC that were present in all the STs. All the L. monocytogenes STs carried four intrinsic/natural resistance genes, fosX, lin, norB, and mprF, conferring resistance to fosfomycin, lincosamide, quinolones, and cationic peptides, respectively. Plasmids pLGUG1 and J1776 were the most detected (54% each), followed by pLI100 (13%) and pLM5578 (7%). The prophage profile, vB_LmoS_188, was overrepresented amongst the isolates, followed by LP_101, LmoS_293_028989, LP_030_2_021539, A006, and LP_HM00113468. Listeria genomic island 2 (LGI-2) was found to be present in all the isolates, while Listeria genomic island 3 (LGI-3) was present in a subset of isolates (25%). The type VII secretion system was found in 42% of the isolates, and sortase A was present in all L. monocytogenes genomes. Mobile genetic elements and genomic islands did not harbor any virulence, resistance, or environmental adaptation genes that may benefit L. monocytogenes. All the STs did not carry genes that confer resistance to first-line antibiotics used for the treatment of listeriosis. The characterization of L. monocytogenes in our study highlighted the environmental resistance and virulence potential of L. monocytogenes and the risk posed to the public, as this bacterium is frequently found in food and food processing environments. Full article
(This article belongs to the Section Food Microbiology)
15 pages, 1297 KiB  
Article
Acid Adaptation Enhances Tolerance of Escherichia coli O157:H7 to High Voltage Atmospheric Cold Plasma in Raw Pineapple Juice
by Allison Little, Aubrey Mendonca, James Dickson, Paulo Fortes-Da-Silva, Terri Boylston, Braden Lewis, Shannon Coleman and Emalie Thomas-Popo
Microorganisms 2024, 12(6), 1131; https://doi.org/10.3390/microorganisms12061131 - 1 Jun 2024
Viewed by 357
Abstract
Pathogens that adapt to environmental stress can develop an increased tolerance to some physical or chemical antimicrobial treatments. The main objective of this study was to determine if acid adaptation increased the tolerance of Escherichia coli O157:H7 to high voltage atmospheric cold plasma [...] Read more.
Pathogens that adapt to environmental stress can develop an increased tolerance to some physical or chemical antimicrobial treatments. The main objective of this study was to determine if acid adaptation increased the tolerance of Escherichia coli O157:H7 to high voltage atmospheric cold plasma (HVACP) in raw pineapple juice. Samples (10 mL) of juice were inoculated with non-acid-adapted (NAA) or acid-adapted (AA) E. coli to obtain a viable count of ~7.00 log10 CFU/mL. The samples were exposed to HVACP (70 kV) for 1–7 min, with inoculated non-HVACP-treated juice serving as a control. Juice samples were analyzed for survivors at 0.1 h and after 24 h of refrigeration (4 °C). Samples analyzed after 24 h exhibited significant decreases in viable NAA cells with sub-lethal injury detected in both NAA and AA survivors (p < 0.05). No NAA survivor in juice exposed to HVACP for 5 or 7 min was detected after 24 h. However, the number of AA survivors was 3.33 and 3.09 log10 CFU/mL in juice treated for 5 and 7 min, respectively (p < 0.05). These results indicate that acid adaptation increases the tolerance of E. coli to HVACP in pineapple juice. The potentially higher tolerance of AA E. coli O157:H7 to HVACP should be considered in developing safe juice processing parameters for this novel non-thermal technology. Full article
Show Figures

Figure 1

Figure 1
<p>Schematic of the components of the dielectric barrier, high voltage atmospheric cold plasma (HVACP) system used to treat pineapple juice.</p>
Full article ">Figure 2
<p>Effect of holding time (0.1 h and 24 h) following HVACP (70 kV) treatment on the viability of non-acid-adapted (<b>A</b>) and acid-adapted (<b>B</b>) <span class="html-italic">Escherichia coli</span> O157:H7 survivors in pineapple juice. The survivors were recovered on sorbitol MacConkey (SMAC) agar. For each treatment time, different letters (A or B) above the bars indicate a significant difference in the number of survivors at 0.1 h and 24 h post-treatment (<span class="html-italic">p</span> &lt; 0.05). Asterisk (<b><span style="color:#0070C0">*</span></b>) indicates that the pathogen was not detected.</p>
Full article ">Figure 3
<p>Effect of holding time (0.1 h and 24 h) following HVACP (70 kV) treatment on the viability of non-acid-adapted (<b>A</b>) and acid-adapted (<b>B</b>) <span class="html-italic">Escherichia coli</span> O157:H7 survivors in pineapple juice. Survivors were recovered on a thin agar layer (TAL) medium. For each treatment time, different letters (A or B) above the bars indicate a significant difference in the number of survivors at 0.1 h and 24 h post-treatment (<span class="html-italic">p</span> &lt; 0.05). Asterisk (<b><span style="color:#7030A0">*</span></b>) indicates that the pathogen was not detected.</p>
Full article ">Figure 4
<p>Effect of physiological state (NAA and AA) on the survival of <span class="html-italic">Escherichia coli</span> O157:H7 in raw pineapple juice held at 4 °C for 24 h after HVACP (70 kV) treatment. Survivors were recovered on sorbitol MacConkey (SMAC) agar (<b>A</b>) and TAL medium (<b>B</b>). For each treatment time, different first letters (A or B) above the bars indicate a significant difference in the viable counts of NAA and AA cells (<span class="html-italic">p</span> &lt; 0.05). Asterisk (<b><span style="color:#0070C0">*</span></b>) indicates that the pathogen was not detected.</p>
Full article ">
12 pages, 278 KiB  
Article
Impact of Refrigerated Storage on Microbial Growth, Color Stability, and pH of Turkey Thigh Muscles
by Agnieszka Orkusz, Giorgia Rampanti, Monika Michalczuk, Martyna Orkusz and Roberta Foligni
Microorganisms 2024, 12(6), 1114; https://doi.org/10.3390/microorganisms12061114 - 30 May 2024
Viewed by 315
Abstract
The quality of poultry meat offered to the consumer depends mainly on the level of hygiene during all stages of its production, storage time, and temperature. This study investigated the effect of refrigerated storage on the microbiological contamination, color, and pH of turkey [...] Read more.
The quality of poultry meat offered to the consumer depends mainly on the level of hygiene during all stages of its production, storage time, and temperature. This study investigated the effect of refrigerated storage on the microbiological contamination, color, and pH of turkey thigh muscles stored at 1 °C over six days. Microbial growth, including total mesophilic aerobes, presumptive lactic acid bacteria, and Enterobacteriaceae, significantly increased, impacting the meat’s sensory attributes and safety. On the 6th day of meat storage, the content of total mesophilic aerobes, presumptive lactic acid bacteria, and Enterobacteriaceae was 1.82 × 107 CFU/g, 1.00 × 104 CFU/g, and 1.87 × 105 CFU/g, respectively. The stability of color was assessed by quantifying the total heme pigments, comparing myoglobin, oxymyoglobin, and metmyoglobin concentrations, analyzing color parameters L*, a*, b*, and the sensory assessment of surface color, showing a decline in total heme pigments, three myoglobin forms, redness (a*) and lightness (L*). In contrast, yellowness (b*) increased. These changes were correlated with the growth of spoilage microorganisms that influenced the meat’s pigmentation and pH, with a notable rise in pH associated with microbial metabolization. Based on the conducted research, it was found that the maximum storage time of turkey thigh muscles at a temperature of 1 °C is 4 days. On the 4th day of storage, the total mesophilic aerobe content was 3.5 × 105 CFU/g. This study underscores the critical need for maintaining controlled refrigeration conditions to mitigate spoilage, ensuring food safety, and preserving turkey meat’s sensory and nutritional qualities. There is a need for further research to improve turkey meat storage techniques under specific temperature conditions by studying the impact of using varying packaging materials (with different barrier properties) or the application of natural preservatives. Additionally, future studies could focus on evaluating the effectiveness of cold chain management practices to ensure the quality and safety of turkey products during storage. By addressing these research gaps, practitioners and researchers can contribute to developing more efficient and sustainable turkey meat supply chains, which may help mitigate food wastage by safeguarding the quality and safety of the meat. Full article
(This article belongs to the Section Food Microbiology)
14 pages, 1683 KiB  
Article
Temporal and Spatial Dynamics of Vibrio harveyi: An Environmental Parameter Correlation Investigation in a 4-Metre-Deep Dicentrarchus labrax Aquaculture Tank
by Alix Da Fonseca Ferreira, Roxane Roquigny, Thierry Grard and Cédric Le Bris
Microorganisms 2024, 12(6), 1104; https://doi.org/10.3390/microorganisms12061104 - 29 May 2024
Viewed by 296
Abstract
Nowadays, European seabass (Dicentrarchus labrax) aquaculture is undergoing a significant expansion. Nevertheless, the aquaculture industry is plagued by vibriosis. The spatial and temporal dynamics of Vibrio harveyi were studied on a European seabass farm in northern France during seven months of [...] Read more.
Nowadays, European seabass (Dicentrarchus labrax) aquaculture is undergoing a significant expansion. Nevertheless, the aquaculture industry is plagued by vibriosis. The spatial and temporal dynamics of Vibrio harveyi were studied on a European seabass farm in northern France during seven months of 2022. Concrete specimens were suspended and water was pumped from different depths (0.3 m, 2.15 m and 4 m deep), providing insights into the biofilm and planktonic V. harveyi dynamics. The abundances of V. harveyi, in the biofilm and free-living forms, were positively correlated. The water parameters revealed seasonal fluctuations in temperature, pH, and salinity, with no significant differences observed across the water column. Quantification of V. harveyi revealed no significant differences between depths, but seasonality, with peak abundances observed in August, correlated with temperature increases. Principal component analysis identified temperature as a primary driver, but also additional parameters, such as salinity and pH. Vibriosis occurred during the sampling period, providing valuable insights into the conditions before, during, and after the outbreaks. This study underscores the importance of understanding V. harveyi behaviour in aquaculture, particularly in the context of global warming, for effective disease management and sustainable practices. Full article
(This article belongs to the Special Issue Seafood-Borne Pathogens)
Show Figures

Figure 1

Figure 1
<p>Biofilm concentrations of <span class="html-italic">V. harveyi</span> in log genome copy equivalents (GE)·cm<sup>−2</sup> and <span class="html-italic">V. harveyi</span> concentrations in log GE·mL<sup>−1</sup> according to the tank depth and time. The coloured lines correspond to the averages of the 5 replicates (raw concentration data are provided in <a href="#app1-microorganisms-12-01104" class="html-app">Table S2</a>). Antibiotic treatments with oxytetracycline are indicated in dark green, and their period of effect is estimated in light green. The dashed line marks the qPCR detection threshold for <span class="html-italic">V. harveyi</span> quantification, delineating the limit above which presence is reliably detected.</p>
Full article ">Figure 2
<p>Circle of correlation of the PCA for parameters, including <span class="html-italic">V. harveyi</span> in water ([<span class="html-italic">Vh</span> water]), <span class="html-italic">V. harveyi</span> in biofilms ([<span class="html-italic">Vh</span> concrete]), dissolved oxygen, temperature, salinity, turbidity, pH, and fish mortality (Mortality). The contribution of each variable indicates its importance in explaining the overall variance in the dataset.</p>
Full article ">Figure 3
<p>Correlation matrix of tank environmental parameters, including <span class="html-italic">V. harveyi</span> concentrations in water ([<span class="html-italic">Vh</span> Water]), <span class="html-italic">V. harveyi</span> in biofilms ([<span class="html-italic">Vh</span> Concrete]), dissolved oxygen, temperature, salinity, turbidity, pH, and fish mortality (Mortality). The size of the circles corresponds to the strength of the correlation, with larger circles indicating stronger correlations and small ones indicating weak correlations. Only statistically significant correlations (<span class="html-italic">p</span> &lt; 0.05) between the parameters are shown.</p>
Full article ">
23 pages, 9218 KiB  
Article
Screening the Protective Agents Able to Improve the Survival of Lactic Acid Bacteria Strains Subjected to Spray Drying Using Several Key Enzymes Responsible for Carbohydrate Utilization
by Jing Liu, Shanshan Xie, Mengfan Xu, Xiaoying Jiang, Qian Wang, Hongfei Zhao and Bolin Zhang
Microorganisms 2024, 12(6), 1094; https://doi.org/10.3390/microorganisms12061094 - 28 May 2024
Viewed by 355
Abstract
The aim of this study was to identify the most effective protectants for enhancing the viability of specific lactic acid bacteria (LAB) strains (Lactobacillus delbrueckii subsp. bulgaricus CICC 6097, Lactiplantibacillus plantarum CICC 21839, Lactobacillus acidophilus NCFM) by assessing their enzymatic activity when exposed to spray [...] Read more.
The aim of this study was to identify the most effective protectants for enhancing the viability of specific lactic acid bacteria (LAB) strains (Lactobacillus delbrueckii subsp. bulgaricus CICC 6097, Lactiplantibacillus plantarum CICC 21839, Lactobacillus acidophilus NCFM) by assessing their enzymatic activity when exposed to spray drying (inlet/outlet temperature: 135 °C/90 °C). Firstly, it was found that the live cell counts of the selected LAB cells from the 10% (w/v) recovered skim milk (RSM) group remained above 107 CFU/g after spray drying. Among all the three groups (1% w/v RSM group, 10% w/v RSM group, and control group), the two enzymes pyruvate kinase (PK) and lactate dehydrogenase (LDH) were more sensitive to spray drying than hexokinase (HK) and β-galactosidase (β-GAL). Next, transcriptome data of Lb. acidophilus NCFM showed that 10% (w/v) RSM improved the down-regulated expressions of genes encoding PK (pyk) and LDH (ldh) after spray drying compared to 1% (w/v) RSM. Finally, four composite protectants were created, each consisting of 10% (w/v) RSM plus a different additive—sodium glutamate (CP-A group), sucrose (CP-B group), trehalose (CP-C group), or a combination of sodium glutamate, sucrose, and trehalose (CP-D group)—to encapsulate Lb. acidophilus NCFM. It was observed that the viable counts of strain NCFM (8.56 log CFU/g) and enzymatic activity of PK and LDH in the CP-D group were best preserved compared to the other three groups. Therefore, our study suggested that measuring the LDH and PK activity could be used as a promising tool to screen the effective spray-dried protective agent for LAB cells. Full article
(This article belongs to the Special Issue Microbial Fermentation, Food and Food Sustainability)
Show Figures

Figure 1

Figure 1
<p>The viable counts (log CFU/g) of spray drying powders containing <span class="html-italic">Lb. acidophilus</span> NCFM, <span class="html-italic">Lb</span>. <span class="html-italic">bulgaricus</span> CICC 6097, and <span class="html-italic">Lpb</span>. <span class="html-italic">plantarum</span> CICC 21839 from 1% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group or 10% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group. Different letters from a to d on the top of each column indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 2
<p>Images (<b>a</b>–<b>c</b>) show pH changes in milk fermented by <span class="html-italic">Lb. acidophilus</span> NCFM, <span class="html-italic">Lb</span>. <span class="html-italic">bulgaricus</span> CICC 6097, and <span class="html-italic">Lpb</span>. <span class="html-italic">plantarum</span> CICC 21839 after spray drying, respectively.</p>
Full article ">Figure 3
<p>Microscopic characteristics of powders and membrane integrity of cells after spray drying. Image A shows the morphology and particle size distributions of spray-dried powders containing the selected 3 LAB strains. Images (<b>i</b>,<b>iii</b>,<b>v</b>) are the morphological changes in 1% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group powders with <span class="html-italic">Lb. acidophilus</span> NCFM, <span class="html-italic">Lb</span>. <span class="html-italic">bulgaricus</span> CICC 6097, and <span class="html-italic">Lpb</span>. <span class="html-italic">plantarum</span> CICC 21839, respectively (magnification = 5000×). Images (<b>ii</b>,<b>iv</b>,<b>vi</b>) are the morphological changes in 10% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group powders with <span class="html-italic">Lb. acidophilus</span> NCFM, <span class="html-italic">Lb</span>. <span class="html-italic">bulgaricus</span> CICC 6097, and <span class="html-italic">Lpb</span>. <span class="html-italic">plantarum</span> CICC 21839, respectively (magnification = 5000×). Particle size distribution images on the right of each SEM image represent the average particle size of each powder.</p>
Full article ">Figure 4
<p>Image (<b>A</b>) shows the cell membrane integrity of the selected 3 LAB strains after spray drying. Images (<b>a</b>,<b>d</b>,<b>g</b>) from control group indicate 3 LAB strains without having experienced spray drying. Images (<b>a</b>–<b>c</b>) represent <span class="html-italic">Lb. acidophilus</span> NCFM from control group, 1% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group, and 10% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group, respectively. Images (<b>d</b>–<b>f</b>) represent <span class="html-italic">Lb</span>. <span class="html-italic">bulgaricus</span> CICC 6097 from control group, 1% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group, and 10% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group, respectively. Images (<b>g</b>–<b>i</b>) represent <span class="html-italic">Lpb</span>. <span class="html-italic">plantarum</span> CICC 21839 from control group, 1% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group, and 10% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group, respectively. Image (<b>B</b>) shows relative fluorescent intensities from different strains groups’ fluorescence microscope images. The red/green color represents the percentage of the chromogenic area of red/green cells to the total co-chromogenic area of cells in the fluorescence microscope images. Image (<b>a</b>–<b>c</b>) represent <span class="html-italic">Lb. acidophilus</span> NCFM, <span class="html-italic">Lb</span>. <span class="html-italic">bulgaricus</span> CICC 6097, and <span class="html-italic">Lpb</span>. <span class="html-italic">plantarum</span> CICC 21839, respectively.</p>
Full article ">Figure 4 Cont.
<p>Image (<b>A</b>) shows the cell membrane integrity of the selected 3 LAB strains after spray drying. Images (<b>a</b>,<b>d</b>,<b>g</b>) from control group indicate 3 LAB strains without having experienced spray drying. Images (<b>a</b>–<b>c</b>) represent <span class="html-italic">Lb. acidophilus</span> NCFM from control group, 1% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group, and 10% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group, respectively. Images (<b>d</b>–<b>f</b>) represent <span class="html-italic">Lb</span>. <span class="html-italic">bulgaricus</span> CICC 6097 from control group, 1% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group, and 10% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group, respectively. Images (<b>g</b>–<b>i</b>) represent <span class="html-italic">Lpb</span>. <span class="html-italic">plantarum</span> CICC 21839 from control group, 1% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group, and 10% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group, respectively. Image (<b>B</b>) shows relative fluorescent intensities from different strains groups’ fluorescence microscope images. The red/green color represents the percentage of the chromogenic area of red/green cells to the total co-chromogenic area of cells in the fluorescence microscope images. Image (<b>a</b>–<b>c</b>) represent <span class="html-italic">Lb. acidophilus</span> NCFM, <span class="html-italic">Lb</span>. <span class="html-italic">bulgaricus</span> CICC 6097, and <span class="html-italic">Lpb</span>. <span class="html-italic">plantarum</span> CICC 21839, respectively.</p>
Full article ">Figure 5
<p>The four key enzyme activities of <span class="html-italic">Lb. acidophilus</span> NCFM, <span class="html-italic">Lb</span>. <span class="html-italic">bulgaricus</span> CICC 6097, and <span class="html-italic">Lpb</span>. <span class="html-italic">plantarum</span> CICC 21839 from 1% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group or 10% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group. The control group results indicate the 3 LAB strains without having experienced spray drying. Images (<b>a</b>–<b>d</b>) show HK activity, β-GAL activity, PK activity, and LDH activity of 3 LAB strains in 1% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group or 10% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group. Different letters from a to c on the top of each column indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 6
<p>(<b>A</b>) Volcano plot of differential genes in <span class="html-italic">Lb. acidophilus</span> NCFM. The red pots represent up-regulated differential genes, green pots represent down-regulated differential genes, and blue pots represent no differential genes. (<b>B</b>) The number of different clusters of expressed genes in the GO terms enriched by the biological process (BP), molecular function (MF), and cell component (CC) in <span class="html-italic">Lb. acidophilus</span> NCFM. The differential genes of control group vs. the differential genes of 1% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group mean the expressed genes of <span class="html-italic">Lb. acidophilus</span> NCFM from 1% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group vs. the expressed genes of <span class="html-italic">Lb. acidophilus</span> NCFM without having undertaken spray drying (<span class="html-italic">p</span> &lt; 0.05); the differential genes of 10% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group vs. the differential genes 1% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group indicate the expressed genes of <span class="html-italic">Lb. acidophilus</span> NCFM from 10% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group vs. the expressed genes of <span class="html-italic">Lb. acidophilus</span> NCFM from 1% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 6 Cont.
<p>(<b>A</b>) Volcano plot of differential genes in <span class="html-italic">Lb. acidophilus</span> NCFM. The red pots represent up-regulated differential genes, green pots represent down-regulated differential genes, and blue pots represent no differential genes. (<b>B</b>) The number of different clusters of expressed genes in the GO terms enriched by the biological process (BP), molecular function (MF), and cell component (CC) in <span class="html-italic">Lb. acidophilus</span> NCFM. The differential genes of control group vs. the differential genes of 1% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group mean the expressed genes of <span class="html-italic">Lb. acidophilus</span> NCFM from 1% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group vs. the expressed genes of <span class="html-italic">Lb. acidophilus</span> NCFM without having undertaken spray drying (<span class="html-italic">p</span> &lt; 0.05); the differential genes of 10% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group vs. the differential genes 1% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group indicate the expressed genes of <span class="html-italic">Lb. acidophilus</span> NCFM from 10% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group vs. the expressed genes of <span class="html-italic">Lb. acidophilus</span> NCFM from 1% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM group (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 7
<p>Effect of 10% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM-based composite protectants on the enzymes PK and LDH, viable counts, and fermented performance of <span class="html-italic">Lb. acidophilus</span> NCFM after spray drying. Images (<b>a</b>–<b>d</b>) show PK activity, LDH activity, viable counts, and fermented performance of strain NCFM from 10% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) RSM-based composite protectants, respectively. Different letters from “a to e” on the top of each column indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">
14 pages, 2793 KiB  
Article
Triglyceride-Catabolizing Lactiplantibacillus plantarum GBCC_F0227 Shows an Anti-Obesity Effect in a High-Fat-Diet-Induced C57BL/6 Mouse Obesity Model
by Jinwook Kim, Seong-Gak Jeon, Min-Jung Kwak, So-Jung Park, Heeji Hong, Seon-Bin Choi, Ji-Hyun Lee, So-Woo Kim, A-Ram Kim, Young-Kyu Park, Byung Kwon Kim and Bo-Gie Yang
Microorganisms 2024, 12(6), 1086; https://doi.org/10.3390/microorganisms12061086 - 27 May 2024
Viewed by 411
Abstract
Given the recognized involvement of the gut microbiome in the development of obesity, considerable efforts are being made to discover probiotics capable of preventing and managing obesity. In this study, we report the discovery of Lactiplantibacillus plantarum GBCC_F0227, isolated from fermented food, which [...] Read more.
Given the recognized involvement of the gut microbiome in the development of obesity, considerable efforts are being made to discover probiotics capable of preventing and managing obesity. In this study, we report the discovery of Lactiplantibacillus plantarum GBCC_F0227, isolated from fermented food, which exhibited superior triglyceride catabolism efficacy compared to L. plantarum WCSF1. Molecular analysis showed elevated expression levels of α/β hydrolases with lipase activity (abH04, abH08_1, abH08_2, abH11_1, and abH11_2) in L. plantarum GBCC_F0227 compared to L. plantarum WCFS1, demonstrating its enhanced lipolytic activity. In a high-fat-diet (HFD)-induced mouse obesity model, the administration of L. plantarum GBCC_F0227 mitigated weight gain, reduced blood triglycerides, and diminished fat mass. Furthermore, L. plantarum GBCC_F0227 upregulated adiponectin gene expression in adipose tissue, indicative of favorable metabolic modulation, and showed robust growth and low cytotoxicity, underscoring its industrial viability. Therefore, our findings encourage the further investigation of L. plantarum GBCC_F0227’s therapeutic applications for the prevention and treatment of obesity and associated metabolic diseases. Full article
Show Figures

Figure 1

Figure 1
<p><span class="html-italic">L. plantarum</span> GBCC_F0227 demonstrates robust efficacy in triglyceride catabolism. (<b>A</b>) Lactic acid bacteria were anaerobically cultured in MRS medium at 37 °C for 16 h, and the triglyceride concentration in the medium was measured. (<b>B</b>) After culturing the lactic acid bacteria to OD<sub>600</sub> values of 3 and 6, the triglyceride concentration in the medium was measured. Data are represented as mean ± SD (<span class="html-italic">n</span> = 3 per sample). *** <span class="html-italic">p</span> &lt; 0.001 (one-way ANOVA, Tukey test).</p>
Full article ">Figure 2
<p>Morphological and cultural characteristics of <span class="html-italic">L. plantarum</span> GBCC_F0227. (<b>A</b>) Scanning electron microscope image. (<b>B</b>) Growth curve according to culture time under anaerobic and aerobic conditions. Data are presented as mean ± SD (<span class="html-italic">n</span> = 3 per sample).</p>
Full article ">Figure 3
<p>Comparison of <span class="html-italic">L. plantarum</span> GBCC_F0227 and LGG acid resistance. The numbers of viable cells (CFU/mL) of (<b>A</b>) <span class="html-italic">L. plantarum</span> GBCC_F0227 and (<b>B</b>) LGG after anaerobic culturing for 2 and 4 h under various pH conditions. (<b>C</b>) The numbers of viable cells of <span class="html-italic">L. plantarum</span> GBCC_F0227 and LGG over time in sequential incubation with artificial gastric fluid (pH 3.0) and artificial intestinal fluid (pH 8.0) under aerobic conditions. All data are presented as mean ± SD (<span class="html-italic">n</span> = 3 per sample).</p>
Full article ">Figure 4
<p>Analysis of <span class="html-italic">L. plantarum</span> GBCC_F0227 cytotoxicity. Caco-2 cells were incubated with <span class="html-italic">L. plantarum</span> GBCC_F0227 or <span class="html-italic">Staphylococcus aureus</span> ATCC 6538 for 24 h and cytotoxicity was measured using the LDH assay. The positive control was the lysis buffer, and the negative control was sterilized water. Cytotoxicity was expressed as (<b>A</b>) OD values and (<b>B</b>) % cytotoxicity. All data are presented as mean ± SD.</p>
Full article ">Figure 5
<p>Expression patterns of genes encoding α/β hydrolases with lipase activity in <span class="html-italic">L. plantarum</span> GBCC_F0227. GBCC_F0227 and WCFS1 strains of <span class="html-italic">L. plantarum</span> were cultured to OD<sub>600</sub> values of (<b>A</b>) 3 or (<b>B</b>) 6, respectively, and the relative expressions of genes encoding α/β hydrolases with lipase activity, such as abH04, abH08_1, abH08_2, abH11_1, and abH11_2, were measured using qRT-PCR. All data are presented as mean ± SD. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 (unpaired Student’s <span class="html-italic">t</span>-test).</p>
Full article ">Figure 6
<p>Effects of <span class="html-italic">L. plantarum</span> GBCC_F0227 in an HFD-induced mouse obesity model. Mice were fed either a normal chow diet (NCD), a 60% high-fat diet (HFD), or the HFD with oral administration of <span class="html-italic">L. plantarum</span> GBCC_F0227 at a dose of 5 × 10<sup>9</sup> CFU/head daily. (<b>A</b>) Changes in body weight, (<b>B</b>) ratios of fat-to-lean body mass, and (<b>C</b>) weight of epididymal white adipose tissue (eWAT) were measured (G1 group, <span class="html-italic">n</span> = 6; G2 group, <span class="html-italic">n</span> = 8; G3 group, <span class="html-italic">n</span> = 11). (<b>D</b>) eWAT sections were stained with H&amp;E and (<b>E</b>) the lipid droplet sizes of adipocytes were calculated. In the same adipose tissues, (<b>F</b>) the relative expression of adiponectin was measured using qRT-PCR (G1 group, <span class="html-italic">n</span> = 12; G2 group, <span class="html-italic">n</span> = 11; G3 group, <span class="html-italic">n</span> = 12). (<b>G</b>) The levels of total cholesterol (TCHO) and triglyceride (TG) in serum were measured (G1 group, <span class="html-italic">n</span> = 9; G2 group, <span class="html-italic">n</span> = 11; G3 group, <span class="html-italic">n</span> = 8). All data are presented as mean ± SEM. * <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 (one-way ANOVA, Tukey’s multiple comparisons test).</p>
Full article ">
18 pages, 2690 KiB  
Article
Druggability Analysis of Protein Targets for Drug Discovery to Combat Listeria monocytogenes
by Robert Hanes, Yanhong Liu and Zuyi Huang
Microorganisms 2024, 12(6), 1073; https://doi.org/10.3390/microorganisms12061073 - 25 May 2024
Viewed by 533
Abstract
Extensive research has been conducted to identify key proteins governing stress responses, virulence, and antimicrobial resistance, as well as to elucidate their interactions within Listeria monocytogenes. While these proteins hold promise as potential targets for novel strategies to control L. monocytogenes, [...] Read more.
Extensive research has been conducted to identify key proteins governing stress responses, virulence, and antimicrobial resistance, as well as to elucidate their interactions within Listeria monocytogenes. While these proteins hold promise as potential targets for novel strategies to control L. monocytogenes, given their critical roles in regulating the pathogen’s metabolism, additional analysis is needed to further assess their druggability—the chance of being effectively bound by small-molecule inhibitors. In this work, 535 binding pockets of 46 protein targets for known drugs (mainly antimicrobials) were first analyzed to extract 13 structural features (e.g., hydrophobicity) in a ligand–protein docking platform called Molsoft ICM Pro. The extracted features were used as inputs to develop a logistic regression model to assess the druggability of protein binding pockets, with a value of one if ligands can bind to the protein pocket. The developed druggability model was then used to evaluate 23 key proteins from L. monocytogenes that have been identified in the literature. The following proteins are predicted to be high-potential druggable targets: GroEL, FliH/FliI complex, FliG, FlhB, FlgL, FlgK, InlA, MogR, and PrfA. These findings serve as an initial point for future research to identify specific compounds that can inhibit druggable target proteins and to design experimental work to confirm their effectiveness as drug targets. Full article
(This article belongs to the Special Issue An Update on Listeria monocytogenes 3.0)
Show Figures

Figure 1

Figure 1
<p>(<b>A</b>) Example protein structure (PDB 1C25) showing 2 pockets (blue mesh and red mesh) without ligands; (<b>B</b>) example protein structure (PDB 3ZG9) showing 1 pocket (blue mesh) with ligand.</p>
Full article ">Figure 2
<p>The framework of our druggability analysis approach for protein targets of <span class="html-italic">L. monocytogenes</span>.</p>
Full article ">Figure 3
<p>Comparison of results for each structural feature for pockets with and without ligands: (<b>a</b>) volume, <span class="html-italic">p</span>-value = 2.2 × 10<sup>−16</sup> (Mann–Whitney); (<b>b</b>) hydrophobicity, <span class="html-italic">p</span>-value = 0.0417 (<span class="html-italic">t</span>-test); (<b>c</b>) buriedness, <span class="html-italic">p</span>-value = 1.734 × 10<sup>−7</sup> (<span class="html-italic">t</span>-test); (<b>d</b>) aromatic, <span class="html-italic">p</span>-value = 1.309 × 10<sup>−12</sup> (Mann–Whitney); (<b>e</b>) DLID, <span class="html-italic">p</span>-value = 2.2 × 10<sup>−16</sup> (<span class="html-italic">t</span>-test); (<b>f</b>) area, <span class="html-italic">p</span>-value = 2.2 × 10<sup>−16</sup> (Mann–Whitney); (<b>g</b>) loopFraction, <span class="html-italic">p</span>-value = 0.6116 (Mann–Whitney); (<b>h</b>) dTSsc, <span class="html-italic">p</span>-value = 2.2 × 10<sup>−16</sup> (Mann–Whitney); (<b>i</b>) relTSsc, <span class="html-italic">p</span>-value = 0.5352 (Mann–Whitney); (<b>j</b>) Bfactor, <span class="html-italic">p</span>-value = 0.001695 (Mann–Whitney); (<b>k</b>) relBfactor, <span class="html-italic">p</span>-value = 1.906 × 10<sup>−5</sup> (Mann–Whitney); (<b>l</b>) radius, <span class="html-italic">p</span>-value = 2.2 × 10<sup>−16</sup> (Mann–Whitney); (<b>m</b>) nonsphericity, <span class="html-italic">p</span>-value = 8 × 10<sup>−7</sup> (Mann–Whitney).</p>
Full article ">Figure 3 Cont.
<p>Comparison of results for each structural feature for pockets with and without ligands: (<b>a</b>) volume, <span class="html-italic">p</span>-value = 2.2 × 10<sup>−16</sup> (Mann–Whitney); (<b>b</b>) hydrophobicity, <span class="html-italic">p</span>-value = 0.0417 (<span class="html-italic">t</span>-test); (<b>c</b>) buriedness, <span class="html-italic">p</span>-value = 1.734 × 10<sup>−7</sup> (<span class="html-italic">t</span>-test); (<b>d</b>) aromatic, <span class="html-italic">p</span>-value = 1.309 × 10<sup>−12</sup> (Mann–Whitney); (<b>e</b>) DLID, <span class="html-italic">p</span>-value = 2.2 × 10<sup>−16</sup> (<span class="html-italic">t</span>-test); (<b>f</b>) area, <span class="html-italic">p</span>-value = 2.2 × 10<sup>−16</sup> (Mann–Whitney); (<b>g</b>) loopFraction, <span class="html-italic">p</span>-value = 0.6116 (Mann–Whitney); (<b>h</b>) dTSsc, <span class="html-italic">p</span>-value = 2.2 × 10<sup>−16</sup> (Mann–Whitney); (<b>i</b>) relTSsc, <span class="html-italic">p</span>-value = 0.5352 (Mann–Whitney); (<b>j</b>) Bfactor, <span class="html-italic">p</span>-value = 0.001695 (Mann–Whitney); (<b>k</b>) relBfactor, <span class="html-italic">p</span>-value = 1.906 × 10<sup>−5</sup> (Mann–Whitney); (<b>l</b>) radius, <span class="html-italic">p</span>-value = 2.2 × 10<sup>−16</sup> (Mann–Whitney); (<b>m</b>) nonsphericity, <span class="html-italic">p</span>-value = 8 × 10<sup>−7</sup> (Mann–Whitney).</p>
Full article ">Figure 3 Cont.
<p>Comparison of results for each structural feature for pockets with and without ligands: (<b>a</b>) volume, <span class="html-italic">p</span>-value = 2.2 × 10<sup>−16</sup> (Mann–Whitney); (<b>b</b>) hydrophobicity, <span class="html-italic">p</span>-value = 0.0417 (<span class="html-italic">t</span>-test); (<b>c</b>) buriedness, <span class="html-italic">p</span>-value = 1.734 × 10<sup>−7</sup> (<span class="html-italic">t</span>-test); (<b>d</b>) aromatic, <span class="html-italic">p</span>-value = 1.309 × 10<sup>−12</sup> (Mann–Whitney); (<b>e</b>) DLID, <span class="html-italic">p</span>-value = 2.2 × 10<sup>−16</sup> (<span class="html-italic">t</span>-test); (<b>f</b>) area, <span class="html-italic">p</span>-value = 2.2 × 10<sup>−16</sup> (Mann–Whitney); (<b>g</b>) loopFraction, <span class="html-italic">p</span>-value = 0.6116 (Mann–Whitney); (<b>h</b>) dTSsc, <span class="html-italic">p</span>-value = 2.2 × 10<sup>−16</sup> (Mann–Whitney); (<b>i</b>) relTSsc, <span class="html-italic">p</span>-value = 0.5352 (Mann–Whitney); (<b>j</b>) Bfactor, <span class="html-italic">p</span>-value = 0.001695 (Mann–Whitney); (<b>k</b>) relBfactor, <span class="html-italic">p</span>-value = 1.906 × 10<sup>−5</sup> (Mann–Whitney); (<b>l</b>) radius, <span class="html-italic">p</span>-value = 2.2 × 10<sup>−16</sup> (Mann–Whitney); (<b>m</b>) nonsphericity, <span class="html-italic">p</span>-value = 8 × 10<sup>−7</sup> (Mann–Whitney).</p>
Full article ">Figure 4
<p>Density plot for predicted results for test data.</p>
Full article ">Figure 5
<p>Confusion matrix of predicted results for test data (horizontal line y = 0.5 indicates cutoff value).</p>
Full article ">
17 pages, 595 KiB  
Review
Translating Human and Animal Model Studies to Dogs’ and Cats’ Veterinary Care: Beta-Glucans Application for Skin Disease, Osteoarthritis, and Inflammatory Bowel Disease Management
by Andressa Rodrigues Amaral, Larissa Wünsche Risolia, Mariana Fragoso Rentas, Pedro Henrique Marchi, Júlio Cesar de Carvalho Balieiro, Thiago Henrique Annibale Vendramini and Marcio Antonio Brunetto
Microorganisms 2024, 12(6), 1071; https://doi.org/10.3390/microorganisms12061071 - 25 May 2024
Viewed by 713
Abstract
The inclusion of beta-glucans in dog and cat food is associated with numerous beneficial effects on the health of these animals. In this regard, there is an effort to elucidate the potential of this nutraceutical in chronic patients. Since there is a lack [...] Read more.
The inclusion of beta-glucans in dog and cat food is associated with numerous beneficial effects on the health of these animals. In this regard, there is an effort to elucidate the potential of this nutraceutical in chronic patients. Since there is a lack of a review on the topic, this review article aims to compile and discuss the evidence found to date. Atopic dermatitis, inflammatory bowel disease, and osteoarthritis are diseases of significant clinical relevance in dogs and cats. In general, the pathophysiology of these chronic conditions is related to immune-mediated and inflammatory mechanisms. Therefore, the immunomodulation and anti-inflammatory effects of beta-glucans are highlighted throughout this review. The available information seems to indicate that the studies on beta-glucans’ impact on allergic processes in dogs indicate a reduction in clinical signs in atopic dermatitis cases. Additionally, while beta-glucans show promise as a safe supplement, particularly for osteoarthritis, further clinical trials are imperative, especially in uncontrolled environments. Beta-glucans emerge as a potential nutraceutical offering immune benefits for inflammatory bowel disease patients, although extensive research is required to define its optimal origin, molecular weight, dosage, and specific applications across animals suffering from this disease. Full article
Show Figures

Figure 1

Figure 1
<p>Conceptual diagram of studies or case reports involving beta-glucans, routes of administration, dosages, and treatment length in dogs and cats. Superscript numbers indicate the number of studies found; C = cat; D = dog; * concentration not declared.</p>
Full article ">
15 pages, 2945 KiB  
Article
Gold Nanoparticle-Based Plasmonic Detection of Escherichia coli, Salmonella enterica, Campylobacter jejuni, and Listeria monocytogenes from Bovine Fecal Samples
by Ahmed Ghazy, Rejoice Nyarku, Rawah Faraj, Kingsley Bentum, Yilkal Woube, McCoy Williams, Evangelyn Alocilja and Woubit Abebe
Microorganisms 2024, 12(6), 1069; https://doi.org/10.3390/microorganisms12061069 - 25 May 2024
Viewed by 467
Abstract
Current diagnostic methods for detecting foodborne pathogens are time-consuming, require sophisticated equipment, and have a low specificity and sensitivity. Magnetic nanoparticles (MNPs) and plasmonic/colorimetric biosensors like gold nanoparticles (GNPs) are cost-effective, high-throughput, precise, and rapid. This study aimed to validate the use of [...] Read more.
Current diagnostic methods for detecting foodborne pathogens are time-consuming, require sophisticated equipment, and have a low specificity and sensitivity. Magnetic nanoparticles (MNPs) and plasmonic/colorimetric biosensors like gold nanoparticles (GNPs) are cost-effective, high-throughput, precise, and rapid. This study aimed to validate the use of MNPs and GNPs for the early detection of Escherichia coli O157:H7, Salmonella enterica spp., Campylobacter jejuni, and Listeria monocytogenes in bovine fecal samples. The capture efficiency (CE) of the MNPs was determined by using Salmonella Typhimurium (ATCC_13311) adjusted at an original concentration of 1.5 × 108 CFU/mL. One (1) mL of this bacterial suspension was spiked into bovine fecal suspension (1 g of fecal sample in 9 mL PBS) and serially diluted ten-fold. DNA was extracted from Salmonella Typhimurium to determine the analytical specificity and sensitivity/LOD of the GNPs. The results showed that the CE of the MNPs ranged from 99% to 100% and could capture as little as 1 CFU/mL. The LOD of the GNPs biosensor was 2.9 µg/µL. The GNPs biosensor was also tested on DNA from 38 naturally obtained bovine fecal samples. Out of the 38 fecal samples tested, 81.6% (31/38) were positive for Salmonella enterica spp., 65.8% (25/38) for C. jejuni, 55.3% (21/38) for L. monocytogenes, and 50% (19/38) for E. coli O157:H7. We have demonstrated that MNP and GNP biosensors can detect pathogens or their DNA at low concentrations. Ensuring food safety throughout the supply chain is paramount, given that these pathogens may be present in cattle feces and contaminate beef during slaughter. Full article
Show Figures

Figure 1

Figure 1
<p>A general mechanism for target-aggregating <span class="html-italic">G</span>NP plasmonic/colorimetric DNA biosensors. Image from [<a href="#B19-microorganisms-12-01069" class="html-bibr">19</a>].</p>
Full article ">Figure 2
<p>Schematic illustration of the steps used in the MNP capture of <span class="html-italic">Salmonella</span> Typhimurium from bovine fecal samples and the use of a GNPs plasmonic biosensor for the detection of <span class="html-italic">E. coli</span> O157:H7, <span class="html-italic">S. enterica</span> spp., <span class="html-italic">C. jejuni</span>, and <span class="html-italic">L. monocytogenes</span> from bovine fecal samples. The image was created with Biorender.com (Accessed on 10 May 2024).</p>
Full article ">Figure 3
<p>Capture efficiency of <span class="html-italic">Salmonella enterica</span> by glycan-coated MNPs. The numbers above the columns are the log10 of the number of cells captured by the MNPs (CFU/mL) divided by the number of cells in the initial dilution (CFU/mL), expressed as a percentage.</p>
Full article ">Figure 4
<p>Capture of <span class="html-italic">Salmonella enterica</span> on XLD agar; (Set A) with MNPs and (Set B) direct plating.</p>
Full article ">Figure 5
<p>Specificity of GNPs biosensor. Bacterial pathogens include <span class="html-italic">Salmonella enterica</span> spp. (target); <span class="html-italic">L. monocytogenes</span> and <span class="html-italic">S. aureus</span> are non-targets, and their DNA is used in mixed DNA. Insert image is corresponding plasmonic image. (<b>a</b>) UV–Vis spectrum and (<b>b</b>) graph showing absorbance at 520 nm.</p>
Full article ">Figure 6
<p>Sensitivity of GNPs biosensor. (<b>a</b>) represents plasmonic signals with varying DNA concentrations of <span class="html-italic">Salmonella</span> spp. The negative control is the non-spiked fecal sample, and the non-target control is <span class="html-italic">L. monocytogenes</span> DNA. (<b>b</b>) represents the calibration curves of the DNA concentration with their corresponding absorbance at 520 nm. The two-way ANOVA result shows a statistical significance between the absorbance for each dilution and between non-targets and targets; <span class="html-italic">p</span>-value &lt; 0.0001 with an alpha level set to 0.05.</p>
Full article ">Figure 7
<p>Bacterial colonies from bovine fecal samples captured by MNP. (<b>A1</b>,<b>B1</b>,<b>C1</b>,<b>D1</b>) indicate colonies without MNPs capture. (<b>A2</b>,<b>B2</b>,<b>C2</b>,<b>D2</b>) show bacterial colonies with MNPs capture for <span class="html-italic">Salmonella enterica</span> spp. (<b>A</b>); <span class="html-italic">E. coli</span> O157:H7 (<b>B</b>); <span class="html-italic">C. jejuni</span> (<b>C</b>); and <span class="html-italic">L. monocytogenes</span> (<b>D</b>).</p>
Full article ">Figure 8
<p>GNPs biosensor performance on bovine fecal samples in detecting <span class="html-italic">C. jejuni</span> (<b>a</b>), <span class="html-italic">Salmonella</span> spp. (<b>b</b>), <span class="html-italic">E. coli</span> O157:H7 (<b>c</b>), and <span class="html-italic">L. monocytogenes</span> (<b>d</b>).</p>
Full article ">
19 pages, 1931 KiB  
Review
Bioplastic Production from Agri-Food Waste through the Use of Haloferax mediterranei: A Comprehensive Initial Overview
by Angela Longo, Francesca Fanelli, Marianna Villano, Marco Montemurro and Carlo Giuseppe Rizzello
Microorganisms 2024, 12(6), 1038; https://doi.org/10.3390/microorganisms12061038 - 21 May 2024
Viewed by 444
Abstract
The research on bioplastics (both biobased and biodegradable) is steadily growing and discovering environmentally friendly substitutes for conventional plastic. This review highlights the significance of bioplastics, analyzing, for the first time, the state of the art concerning the use of agri-food waste as [...] Read more.
The research on bioplastics (both biobased and biodegradable) is steadily growing and discovering environmentally friendly substitutes for conventional plastic. This review highlights the significance of bioplastics, analyzing, for the first time, the state of the art concerning the use of agri-food waste as an alternative substrate for biopolymer generation using Haloferax mediterranei. H. mediterranei is a highly researched strain able to produce polyhydroxybutyrate (PHB) since it can grow and produce bioplastic in high-salinity environments without requiring sterilization. Extensive research has been conducted on the genes and pathways responsible for PHB production using H. mediterranei to find out how fermentation parameters can be regulated to enhance cell growth and increase PHB accumulation. This review focuses on the current advancements in utilizing food waste as a substitute for costly substrates to reduce feedstock expenses. Specifically, it examines the production of biomass and the recovery of PHB from agri-food waste. Furthermore, it emphasizes the characterization of PHB and the significance of hydroxyvalerate (HV) abundance in the formation of Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) copolymer. The downstream processing options are described, and the crucial factors associated with industrial scale-up are assessed, including substrates, bioreactors, process parameters, and bioplastic extraction and purification. Additionally, the economic implications of various options are discussed. Full article
(This article belongs to the Special Issue Microbial Fermentation, Food and Food Sustainability)
Show Figures

Figure 1

Figure 1
<p>Schematic representation of the most important pure culture of microorganisms used in bioplastic production with organic waste as inexpensive substrates, including the type of polymer synthesized.</p>
Full article ">Figure 2
<p>Schematic representation of key <span class="html-italic">H. mediterranei</span> genes involved in PHBV synthesis, metabolism, and regulation. <span class="html-italic">phaJ1:</span> enoyl-CoA hydratases J1; <span class="html-italic">phaR</span>: PHA granule-associated regulator; <span class="html-italic">phaP</span>: granule structural protein; <span class="html-italic">phaE</span>: subunit E of PHA synthase; <span class="html-italic">phaC</span>: subunit C of PHA synthase; <span class="html-italic">phaH</span>: phasin; <span class="html-italic">bdhA</span>: 3-hydroxybutyrate dehydrogenase <span class="html-italic">phaZ</span>: PHA polyhydroxyalkanoate depolymerase; <span class="html-italic">phaAα</span>: α subunit of β-ketothiolases PhaA; <span class="html-italic">phaAβ</span>: β subunit of β-ketothiolases PhaA; <span class="html-italic">btkBα</span>: α subunit of β-ketothiolases Btk B; <span class="html-italic">btkBβ</span>: β subunit of β-ketothiolases BtkB; <span class="html-italic">phaB1</span>: acetoacetyl-CoA reductase B1; <span class="html-italic">phaB2</span>: acetoacetyl-CoA reductase B2; see text for details.</p>
Full article ">Figure 3
<p>Graphical representation of the most important factors that drive PHBV production costs.</p>
Full article ">
13 pages, 1516 KiB  
Article
Lactobacillus rhamnosus PL1 and Lactobacillus plantarum PM1 versus Placebo as Prophylaxis for Recurrence of Urinary Tract Infections in Children
by Maria Daniel, Hanna Szymanik-Grzelak, Janusz Sierdziński and Małgorzata Pańczyk-Tomaszewska
Microorganisms 2024, 12(6), 1037; https://doi.org/10.3390/microorganisms12061037 - 21 May 2024
Viewed by 362
Abstract
Urinary tract infections (UTIs) rank among the most prevalent bacterial infections in children. Probiotics appear to reduce the risk of recurrence of UTIs. This study aimed to evaluate whether probiotics containing Lactobacillus rhamnosus PL1 and Lactobacillus plantarum PM1 therapy prevent UTIs in the [...] Read more.
Urinary tract infections (UTIs) rank among the most prevalent bacterial infections in children. Probiotics appear to reduce the risk of recurrence of UTIs. This study aimed to evaluate whether probiotics containing Lactobacillus rhamnosus PL1 and Lactobacillus plantarum PM1 therapy prevent UTIs in the pediatric population compared to a placebo. A superiority, double-blind, randomized, controlled trial was conducted. In total, 54 children aged 3–18 years with recurrent UTIs or ≥one acute pyelonephritis and ≥one risk factor of recurrence of UTIs were randomly assigned (27 patients in each arm) to a 90-day probiotic or placebo arm. The age, sex, diagnosis, renal function, risk factors, and etiology of UTIs did not vary between the groups. During the intervention, 26% of children taking the probiotic had episodes of UTI, and it was not significantly less than in the placebo group. The number of UTI episodes during the intervention and the follow-up period decreased significantly in both groups, but the difference between them was insignificant. We observed a decrease in UTIs during the study of almost 50% in the probiotic group compared to the placebo group. Probiotics can be used as natural, safe prophylaxis for children with risk factors for UTIs in whom antibiotic prevention is not indicated. Full article
(This article belongs to the Special Issue Effects of Probiotics on Health, 2nd Edition)
Show Figures

Figure 1

Figure 1
<p>The study period was divided into 3-month interventions and 6 months of follow-up.</p>
Full article ">Figure 2
<p>A flowchart of the recruiting process.</p>
Full article ">Figure 3
<p>The number of UTI episodes during the intervention and follow-up period.</p>
Full article ">Figure 4
<p>Median of UTI episodes before and during the study.</p>
Full article ">Figure 5
<p>Median of days antibiotic therapy due to UTIs before and during the study.</p>
Full article ">
13 pages, 2902 KiB  
Article
The Probiotic Strain Lactobacillus acidophilus CL1285 Reduces Fat Deposition and Oxidative Stress and Increases Lifespan in Caenorhabditis elegans
by Samir Bouasker, Sonja Nodland and Mathieu Millette
Microorganisms 2024, 12(6), 1036; https://doi.org/10.3390/microorganisms12061036 - 21 May 2024
Viewed by 496
Abstract
Caenorhabditis elegans was recently shown to be a powerful model for studying and identifying probiotics with specific functions. Lactobacillus acidophilus CL1285, Lacticaseibacillus casei LBC80R, and Lacticaseibacillus rhamnosus CLR2, which are three bacteria that were marketed by Bio-K+, were evaluated using the nematode C. elegans [...] Read more.
Caenorhabditis elegans was recently shown to be a powerful model for studying and identifying probiotics with specific functions. Lactobacillus acidophilus CL1285, Lacticaseibacillus casei LBC80R, and Lacticaseibacillus rhamnosus CLR2, which are three bacteria that were marketed by Bio-K+, were evaluated using the nematode C. elegans to study fat accumulation, lifespan, and resistance to oxidative stress. Although the general effects of probiotics in terms of protection against oxidative stress were highlighted, the CL1285 strain had an interesting and specific feature, namely its ability to prevent fat accumulation in nematodes; this effect was verified by both the Oil Red and Nile Red methods. This observed phenotype requires daf-16 and is affected by glucose levels. In addition, in a daf-16- and glucose-dependent manner, CL1285 extended the lifespan of C. elegans; this effect was unique to CL1285 and not found in the other L. acidophilus subtypes in this study. Our findings indicate that L. acidophilus CL1285 impacts fat/glucose metabolism in C. elegans and provides a basis to further study this probiotic, which could have potential health benefits in humans and/or in mammals. Full article
(This article belongs to the Special Issue Probiotic and Postbiotic Properties of Lactobacillus)
Show Figures

Figure 1

Figure 1
<p>Reduction in fat accumulation in <span class="html-italic">C. elegans</span> fed with CL1285. (<b>a</b>) Oil Red visualization of N2 worms fed various bacteria for 3 days after reaching adult stage. (<b>b</b>) Oil Red density estimation using ImageJ quantification of 10 representative Oil-Red-stained worms; 100% is fixed for N2 worms given OP50 food. *** <span class="html-italic">p</span> &lt; 0.05; one way-ANOVA with Tukey’s HSD test relative to OP50 control. (<b>c</b>) Fluorescence measurement of Nile-Red-stained worms (approximately 180 worms, in triplicate) after 3 days of being fed various sources of food. Orlistat was used as a control inhibitor of lipid accumulation; 100% is fixed for N2 worms given OP50 food. *** <span class="html-italic">p</span> &lt; 0.01; ** <span class="html-italic">p</span> &lt; 0.05; <span class="html-italic">t</span> test relative to the OP50 control.</p>
Full article ">Figure 2
<p>Oxidative stress protection of probiotic bacteria in <span class="html-italic">C. elegans</span>: H<sub>2</sub>O<sub>2</sub> survival assay on worms fed different food for 3 days after adult stage and 6 h on H<sub>2</sub>O<sub>2</sub> (1.5, 3 and 5 mM); 100% is fixed for untreated worms given OP50. *** <span class="html-italic">p</span> &lt; 0.01; ** <span class="html-italic">p</span> &lt; 0.05; one way-ANOVA with Tukey’s HSD test relative to OP50 control.</p>
Full article ">Figure 3
<p>Life extension of <span class="html-italic">C. elegans</span> fed CL1285 probiotic. (<b>a</b>) Survival curve and table of N2 worms given various bacterial expositions after the adult stage. *** indicates the results of Log-rank test analysis (<span class="html-italic">p</span> &lt; 0.01) performed with OASIS2 online software (accessed on 17 May 2022). (<b>b</b>) The table describes number of worms, their mean lifespan, the log-rank test Bonferroni-corrected <span class="html-italic">p</span>-value, and the percentage of change compared to control. Three independent experiments were performed.</p>
Full article ">Figure 4
<p>Glucose limits fat reduction in CL1285. Fluorescence measurement of Nile Red stained worms (approximately 180 worms, in triplicate) after 3 days with various sources food with or without 2% glucose addition in NGM media. Orlistat was used as a control inhibitor of lipid accumulation; 100% is fixed for N2 given OP50 food without glucose. *** <span class="html-italic">p</span> &lt; 0.05; one way-ANOVA with Tukey’s HSD test relative to each OP50 control.</p>
Full article ">Figure 5
<p>Glucose limits the benefits of CL1285 in lifespan. (<b>a</b>) Survival curve of N2 worms given various bacterial expositions after reaching the adult stage. *** <span class="html-italic">p</span> &lt; 0.001 and N.S (not significant) indicates the results of log-rank test analysis performed with OASIS2 online software. (<b>b</b>) The table describes the mean lifespan, the log-rank test Bonferroni-corrected <span class="html-italic">p</span>-value, and the percentage of change compared to control.</p>
Full article ">Figure 6
<p>Mechanistic study of CL1285 fat reduction using <span class="html-italic">C. elegans</span> mutant strains. (<b>a</b>) Oil Red visualization of representative N2 worms or mutant line fed OP50 or CL1285 for 3 days after reaching adult stage. (<b>b</b>) Fluorescence measurement of Nile Red stained worms (approximately 180 worms, in triplicate) after being fed various sources of food for 3 days. Orlistat was used as the control inhibitor of lipid accumulation; 100% is fixed for N2 given OP50 food. *** <span class="html-italic">p</span> &lt; 0.01; one way-ANOVA with Tukey’s HSD test relative to OP50 control for each mutant strain. N.S (not significant).</p>
Full article ">Figure 7
<p>Mechanistic study of life extension of CL1285 using <span class="html-italic">C. elegans</span> mutant strains. Survival curve of worms given various bacterial expositions after adult stage using the <span class="html-italic">C. elegans</span> mutant strains <span class="html-italic">daf-16</span> (<b>a</b>) and <span class="html-italic">pmk-1</span> (<b>b</b>). *** <span class="html-italic">p</span> &lt; 0.01 and N.S (not significant) indicates the results of log-rank test analysis performed with OASIS2 online software. (<b>c</b>) The table describes the mean lifespan, the log-rank test Bonferroni-corrected <span class="html-italic">p</span>-value, and the percentage of change compared to control.</p>
Full article ">Figure 8
<p>Comparative study of life extension and fat reduction in CL1285 and commercial <span class="html-italic">L. acidophilus</span> strains. (<b>a</b>) Fluorescence measurement of Nile Red stained worms (approximately 180 worms, in triplicate) after being fed with various sources of food for 3 days. Orlistat was used as a control inhibitor of lipid accumulation; 100% is fixed for N2 given OP50 food. *** <span class="html-italic">p</span> &lt; 0.01; one-way-ANOVA with Tukey’s HSD test relative to OP50 control. (<b>b</b>) Survival curve of N2 worms given various bacterial expositions after adult stage using the <span class="html-italic">C. elegans</span> N2 strain. *** <span class="html-italic">p</span> &lt; 0.01 and N.S (not significant) indicates the results of log-rank test analysis performed with OASIS2 online software. (<b>c</b>) The table describes the mean lifespan, the log-rank test Bonferroni-corrected <span class="html-italic">p</span>-value, and the percentage of change compared to control.</p>
Full article ">
Back to TopTop