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Search Results (2,163)

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Keywords = gut dysbiosis

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21 pages, 3375 KiB  
Article
Obesity as Inducer of Cognitive Function Decline via Dysbiosis of Gut Microbiota in Rats
by Hoda B. Mabrok, Asmaa A. Ramadan, Ibrahim M. Hamed and Doha A. Mohamed
Brain Sci. 2024, 14(8), 807; https://doi.org/10.3390/brainsci14080807 (registering DOI) - 12 Aug 2024
Abstract
Diet-induced obesity is a global phenomenon that affects the population worldwide with manifestations at both the phenotypic and genotypic levels. Cognitive function decline is a major global health challenge. The relation between obesity and cognitive function is a debatable issue. The main goal [...] Read more.
Diet-induced obesity is a global phenomenon that affects the population worldwide with manifestations at both the phenotypic and genotypic levels. Cognitive function decline is a major global health challenge. The relation between obesity and cognitive function is a debatable issue. The main goal of the current research was to study the implications of obesity on cognitive function and gut microbiota diversity and its impact on plasma and brain metabolic parameters in rats. Obesity was induced in rats by feeding on a high-fat (HF) or a high-fat/high-sucrose (HFHS) diet. The results reveal that both the HF (0.683) and HFHS (0.688) diets were effective as obesity inducers, which was confirmed by a significant increase in the body mass index (BMI). Both diet groups showed dyslipidemia and elevation of oxidative stress, insulin resistance (IR), and inflammatory markers with alterations in liver and kidney functions. Obesity led to a reduction in cognitive function through a reduction in short-term memory by 23.8% and 30.7% in the rats fed HF and HFHS diets, respectively, and learning capacity and visuo-spatial memory reduced by 8.9 and 9.7 s in the rats fed an HF or HFHS diet, respectively. Bacteroidetes, Firmicutes, Proteobacteria, Fusobacteria, and Spirochaetes phyla were detected. The Firmicutes/Bacteroidetes ratio (F/B) significantly decreased in the HF group, while it increased in the HFHS group compared to the normal control. The two species, Bacteroides acidifaciens and Bacteroides ovatus, which are associated with IR, were drastically compromised by the high-fat/high-sucrose diet. Some species that have been linked to reduced inflammation showed a sharp decrease in the HFHS group, while Prevotella copri, which is linked to carbohydrate metabolism, was highly enriched. In conclusion: Obesity led to cognitive impairment through changes in short-term and visuo-spatial memory. A metagenomic analysis revealed alterations in the abundance of some microbial taxa associated with obesity, inflammation, and insulin resistance in the HF and HFHS groups. Full article
(This article belongs to the Section Nutritional Neuroscience)
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Graphical abstract

Graphical abstract
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<p>Flow chart of the animal experiment.</p>
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<p>Growth curves of different rat groups during the study. NC: Normal control, HF: High-fat, HFHS: High-fat/high-sucrose. Similar letters mean non-significant difference within groups at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Acetyl cholinesterase in brain tissue of normal rat and obese rat groups. Similar letters mean non-significant difference within groups at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Y-maze and Morris water maze tests of normal rat and obese rat groups. (<b>A</b>,<b>C</b>) Similar letters mean non-significant difference within groups at <span class="html-italic">p</span> &lt; 0.05. (<b>B</b>) * <span class="html-italic">p</span> &gt; 0.05 and *** <span class="html-italic">p</span> &gt; 0.001.</p>
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<p>Counts of Bacteroidetes and Firmicutes phyla in rat feces quantified by qPCR and expressed as log10 copies/g wet feces and Firmicutes/Bacteroidetes ratio. (<b>a</b>) Bacteroidetes and Firmicutes count; (<b>b</b>) Firmicutes/Bacteroidetes ratio. For each phylum, bars with different letters are significantly different at <span class="html-italic">p</span> ≤ 0.05.</p>
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<p>Relative abundance of microbiota at the phylum level in the guts of rats among the test groups using metagenomic analysis. NC: Normal control, HF: High-fat, HFHS: High-fat/high-sucrose.</p>
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<p>Relative abundance of microbiota at the family level in the guts of rats among the test groups using metagenomic analysis. NC: Normal control, HF: High-fat, HFHS: High-fat/high-sucrose.</p>
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<p>Relative abundance of microbiota at the genus level in the guts of rats among the test groups using metagenomic analysis. NC: Normal control, HF: High-fat, HFHS: High-fat/high-sucrose.</p>
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<p>Heat map of the top 25 species differentially enriched across the test groups. NC: Normal control, HF: High-fat, HFHS: High-fat/high-sucrose.</p>
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16 pages, 1686 KiB  
Article
Effects of Synbiotic Administration on Gut Microbiome and Fecal Bile Acids in Dogs with Chronic Hepatobiliary Disease: A Randomized Case–Control Study
by Verena Habermaass, Corrado Biolatti, Francesco Bartoli, Eleonora Gori, Natascia Bruni, Daniela Olivero and Veronica Marchetti
Vet. Sci. 2024, 11(8), 364; https://doi.org/10.3390/vetsci11080364 (registering DOI) - 10 Aug 2024
Viewed by 265
Abstract
Alteration in the gut microbiome in human patients with chronic liver disease is a well-known pathophysiological mechanism. Therefore, it represents both a diagnostic and therapeutical target. Intestinal dysbiosis has also been identified in dogs with chronic liver disease, but clinical trials evaluating the [...] Read more.
Alteration in the gut microbiome in human patients with chronic liver disease is a well-known pathophysiological mechanism. Therefore, it represents both a diagnostic and therapeutical target. Intestinal dysbiosis has also been identified in dogs with chronic liver disease, but clinical trials evaluating the effectiveness of synbiotic administration are lacking. Thirty-two dogs with chronic hepatobiliary disease were equally randomized into two groups: one treated with a synbiotic complex for 4–6 weeks (TG) and one untreated control group (CG). All dogs underwent clinical evaluation, complete anamnesis, bloodwork, abdominal ultrasound, fecal bile acids, and gut microbiome evaluation at T0–T1 (after 4–6 weeks). Treated dogs showed a significant reduction in ALT activity (p = 0.007) and clinical resolution of gastrointestinal signs (p = 0.026) compared to control dogs. The synbiotic treatment resulted in a lower increase in Enterobacteriaceae and Lachnospiraceae compared to the control group but did not affect the overall richness and number of bacterial species. No significant changes in fecal bile acids profile were detected with synbiotic administration. Further studies are needed to better evaluate the effectiveness of synbiotic administration in these patients and the metabolic pathways involved in determining the clinical and biochemical improvement. Full article
(This article belongs to the Special Issue Small Animal Gastrointestinal Diseases: Challenges and Advances)
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Figure 1
<p>Trend of serum ALT (U/L) in TG (treatment group) and CG (control group) between T0 and T1 timepoints. Reference range 20–70 U/L. Black lines refers to a reduced ALT concentration between T0-T1, red lines refers to its increase.</p>
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<p>Boxplot of the alpha diversity and species number (OTU) of the CG (control group) and TG (treatment group).</p>
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<p>Most represented bacterial families (&gt;1000 OTU) in the fecal microbiome of TG (treatment group) at T0 (<b>left</b>) and T1 (<b>right</b>).</p>
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<p>Most represented bacterial families (&gt;1000 OTU) in the fecal microbiome of CG (control group) at T0 (<b>left</b>) and T1 (<b>right</b>).</p>
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36 pages, 2344 KiB  
Review
Microbiota-Derived Extracellular Vesicle as Emerging Actors in Host Interactions
by Paola Margutti, Antonella D’Ambrosio and Silvia Zamboni
Int. J. Mol. Sci. 2024, 25(16), 8722; https://doi.org/10.3390/ijms25168722 (registering DOI) - 9 Aug 2024
Viewed by 251
Abstract
The human microbiota is an intricate micro-ecosystem comprising a diverse range of dynamic microbial populations mainly consisting of bacteria, whose interactions with hosts strongly affect several physiological and pathological processes. The gut microbiota is being increasingly recognized as a critical player in maintaining [...] Read more.
The human microbiota is an intricate micro-ecosystem comprising a diverse range of dynamic microbial populations mainly consisting of bacteria, whose interactions with hosts strongly affect several physiological and pathological processes. The gut microbiota is being increasingly recognized as a critical player in maintaining homeostasis, contributing to the main functions of the intestine and distal organs such as the brain. However, gut dysbiosis, characterized by composition and function alterations of microbiota with intestinal barrier dysfunction has been linked to the development and progression of several pathologies, including intestinal inflammatory diseases, systemic autoimmune diseases, such as rheumatic arthritis, and neurodegenerative diseases, such as Alzheimer’s disease. Moreover, oral microbiota research has gained significant interest in recent years due to its potential impact on overall health. Emerging evidence on the role of microbiota–host interactions in health and disease has triggered a marked interest on the functional role of bacterial extracellular vesicles (BEVs) as mediators of inter-kingdom communication. Accumulating evidence reveals that BEVs mediate host interactions by transporting and delivering into host cells effector molecules that modulate host signaling pathways and cell processes, influencing health and disease. This review discusses the critical role of BEVs from the gut, lung, skin and oral cavity in the epithelium, immune system, and CNS interactions. Full article
(This article belongs to the Section Molecular Immunology)
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Figure 1

Figure 1
<p>Schematic representation of microbiota’s presence in the human body. In red is indicated the gut microbiota that represents more than 99% of the total microbial community within the body (created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>).</p>
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<p>Schematic representation of communication network in the body. The communication network in the body is a complex and interconnected system that allows for different organs and systems to work together. There are different axes in the human body that represent bidirectional or multi-directional communications among different body compartments consisting not only of anatomical connections but also of molecules derived from the immune and endocrine systems, metabolites transported through the bloodstream, and bacterial products including BEVs originating from microbiota residing in the different organs. The gut is the key place of interaction with other organs. The brain–gut axis (green) is a complex connection system between the CNS and gastrointestinal tract based on the vagus nerve, enteric nervous system, neuroendocrine system, and circulatory system, thereby affecting the gut microbiota homeostasis and brain function, including behavior. The Gut–Lung–Brain (pink) axis is an intricate network, linking the gut, lung, and brain, that consists of various components, such as vagus nerve, hypothalamus–pituitary–adrenal (HPA) axis, immune system, metabolites, and bacterial microbiota. For instance, the vagus nerve, communicating with the gastrointestinal tract and respiratory apparatus, influences the motility, immunity, permeability of gut mucosa and bronchial smooth muscle contraction, and oxygen consumption. The oral–brain–gut axis (orange) is a complex interconnection among the oral cavity, brain, and gut, and it is mostly observed by studying the role of oral microbiota in periodontitis and neurodegenerative diseases. Microbiota resident in the gut–lung epithelial mucosa are among the targets of these molecules, and, in turn, they respond by producing different mediators (such as fatty acids, gut peptides, BEVs) that impact directly and indirectly the brain functions. The brain–gut–other organ axis (blue) is mainly based on the vagus nerve’s innervation of other organs. In particular, the vagus nerve supplies parasympathetic fibers to all organs, except the adrenal glands, transmitting and receiving information feedback. (Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>).</p>
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<p>Structure of the Gram-negative and Gram-positive cell envelope and biogenesis mechanisms of BEVs. (<b>A</b>) The architecture of Gram-negative cell envelope consists of two membranes: outer membrane (OM) and inner membrane (IM). The OM consists of an exterior leaflet of lipopolysaccharides (LPS) and an internal leaflet of phospholipids while IM is composed of a classic phospholipid bilayer. Between IM and OM, there is the periplasmic space, a thin layer of peptidoglycans (PG) in which Braun’s lipoproteins (Lpp) are immersed and covalently link PG to the two layers providing structural integrity to OM. The porin outer-membrane proteins (Omp) and Tol–Pal (peptidoglycan-associated lipoprotein) complex are embedded in OM and interact with OM via PG. The structure of the Gram-positive cell envelope consists of a thick layer of PG in which are present molecules of lipoteichoic acids (LTA) covalently linked to lipids of the underlying cytoplasmic membrane and wall lipoteichoic acids (WTA), conferring a negative charge to Gram-positive bacteria. The plasmatic membrane (PM) is a classic lipid bilayer in which are immerse membrane channels and functional transmembrane proteins (in orange and green colors). The periplasmic space is located between PG and PM. (<b>B</b>) BEV biogenesis occurs through three mechanisms: blebbing, explosive cell lysis, and nanotube formation. Gram-negative bacteria produce mainly OMVs through blebbing and EOMVs through explosive cell lysis in which OM dissociates from the PG, forming OM vesicles; OIMVs are produced by explosive cell lysis and contain both inner and outer membranes. Gram-positive bacteria produce cytoplasmic membranes (CMVs) lacking an OM through an explosive cell lysis mechanism or a non-explosive lysis (bubbling) consisting of the cell integrity loss and cell death. The formation of BEVs from nanotube, filamentous structures occurs in both Gram-positive bacteria, through a process of extrusion of the plasma membrane, and Gram-negative bacteria, from the extrusion of the OM. (Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>).</p>
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<p>Schematic interaction between BEVs and cellular barriers in health and disease (created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>).</p>
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18 pages, 4917 KiB  
Article
The Beneficial Effects of Lacticaseibacillus paracasei subsp. paracasei DSM 27449 in a Letrozole-Induced Polycystic Ovary Syndrome Rat Model
by Yan Zhang Lee, Shih-Hsuan Cheng, Yu-Fen Lin, Chien-Chen Wu and Ying-Chieh Tsai
Int. J. Mol. Sci. 2024, 25(16), 8706; https://doi.org/10.3390/ijms25168706 - 9 Aug 2024
Viewed by 237
Abstract
Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder affecting women of reproductive age globally. Emerging evidence suggests that the dysregulation of microRNAs (miRNAs) and gut dysbiosis are linked to the development of PCOS. In this study, the effects of Lacticaseibacillus paracasei subsp. [...] Read more.
Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder affecting women of reproductive age globally. Emerging evidence suggests that the dysregulation of microRNAs (miRNAs) and gut dysbiosis are linked to the development of PCOS. In this study, the effects of Lacticaseibacillus paracasei subsp. paracasei DSM 27449 (DSM 27449) were investigated in a rat model of PCOS induced by letrozole. The administration of DSM 27449 resulted in improved ovarian function, reduced cystic follicles, and lower serum testosterone levels. Alterations in miRNA expressions and increased levels of the pro-apoptotic protein Bax in ovarian tissues were observed in PCOS-like rats. Notably, the administration of DSM 27449 restored the expression of miRNAs, including miR-30a-5p, miR-93-5p, and miR-223-3p, leading to enhanced ovarian function through the downregulation of Bax expressions in ovarian tissues. Additionally, 16S rRNA sequencing showed changes in the gut microbiome composition after letrozole induction. The strong correlation between specific bacterial genera and PCOS-related parameters suggested that the modulation of the gut microbiome by DSM 27449 was associated with the improvement of PCOS symptoms. These findings demonstrate the beneficial effects of DSM 27449 in ameliorating PCOS symptoms in letrozole-induced PCOS-like rats, suggesting that DSM 27449 may serve as a beneficial dietary supplement with the therapeutic potential for alleviating PCOS. Full article
(This article belongs to the Special Issue Molecular Research in Prebiotics, Probiotics and Postbiotics)
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Figure 1

Figure 1
<p>Effects of letrozole treatment on the weight of rats. (<b>A</b>) A detailed animal treatment scheme. Female Sprague-Dawley rats were randomly divided into four groups. The control group received 1% carboxymethyl cellulose (CMC), whereas the letrozole, Diane-35, and DSM 27449 groups received 1 mg/kg body weight of letrozole during polycystic ovary syndrome (PCOS) induction. Letrozole-induced PCOS-like rats received phosphate-buffered saline (PBS), Diane-35, or DSM 27449 by oral gavage. Estrous cycle determination was performed during the experiment, and an oral glucose tolerance test (OGTT) was performed at the end of the experiment. (<b>B</b>) Growth curves of rats from day 1–42. (<b>C</b>) Average weight gain at the end of the study between the groups. N = 8 per group; * <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, and **** <span class="html-italic">p</span> &lt; 0.0001 compared with the control group; <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 compared with the letrozole group.</p>
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<p>Effects of <span class="html-italic">L. paracasei</span> subsp. <span class="html-italic">paracasei</span> DSM 27449 on ovarian function in letrozole-induced polycystic ovary syndrome-like rats. (<b>A</b>) Representative estrous cycles in rats (P, proestrus; E, estrus; M/D, metestrus/diestrus). (<b>B</b>) Percentage of time spent in different phases of the estrous cycle for the last five days of the experiment. (<b>C</b>) Hematoxylin and eosin staining of representative ovaries. The number of (<b>D</b>) cystic follicles and (<b>E</b>) corpora lutea of the experimental groups. N = 8 per group; * <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, and **** <span class="html-italic">p</span> &lt; 0.0001 compared with the control group; <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 compared with the letrozole group. Scale bar = 100 μm in (<b>C</b>).</p>
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<p><span class="html-italic">L. paracasei</span> subsp. <span class="html-italic">paracasei</span> DSM 27449 attenuated an increase in serum testosterone levels and androgen-receptor (AR) expression in letrozole-induced polycystic ovary syndrome-like rats. (<b>A</b>) Serum testosterone levels. N = 6–8 per group. (<b>B</b>) AR immunohistochemical staining of representative ovarian sections. (<b>C</b>) Quantitative analysis of AR-positive areas in the ovarian sections. N = 8 per group; * <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, and **** <span class="html-italic">p</span> &lt; 0.0001 compared with the control group; <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01, and <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 compared with the letrozole group. Scale bar = 100 μm in (<b>B</b>).</p>
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<p><span class="html-italic">L. paracasei</span> subsp. <span class="html-italic">paracasei</span> DSM 27449 downregulated the expression of the pro-apoptotic protein Bax in the ovarian tissues of letrozole-induced polycystic ovary syndrome (PCOS)-like rats. (<b>A</b>) Heat map of the Spearman’s rank correlation test visualizing the correlation between PCOS-related parameters and microRNA expressions. N = 6–8 per group, * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01. (<b>B</b>) Immunohistochemical staining of Bax (top), Bcl-2 (middle), and Beclin-1 (bottom) on representative ovarian sections. Quantitative analysis of the expression of (<b>C</b>) Bax, (<b>D</b>) Bcl-2, and (<b>E</b>) Beclin-1 in the ovarian sections. N = 8 per group; ** <span class="html-italic">p</span> &lt; 0.01 compared with the control group; <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 compared with the letrozole group. Scale bar = 100 μm in (<b>B</b>).</p>
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<p>Effects of <span class="html-italic">L. paracasei</span> subsp. <span class="html-italic">paracasei</span> DSM 27449 on the gut microbiome in letrozole-induced polycystic ovary syndrome-like rats. Alpha diversity is represented by (<b>A</b>) the Chao1 index, (<b>B</b>) the Shannon index, and (<b>C</b>) the Simpson index. N = 8 per group; <sup><span>$</span><span>$</span></sup> <span class="html-italic">p</span> &lt; 0.01 compared with the Diane-35 group. (<b>D</b>) Beta diversity is represented by a non-metric multi-dimensional scaling (NMDS) plot and the analysis of similarities (ANOSIMs). (<b>E</b>) Composition of the gut microbiome at the phylum level. (<b>F</b>–<b>K</b>) Relative abundance of differential bacteria at the genus level between the control and letrozole groups and between the control and DSM 27449 groups. N = 8 per group; the Bonferroni method was applied to correct for Type I errors, with statistical significance considered at * <span class="html-italic">p</span> &lt; 0.05/2.</p>
Full article ">Figure 5 Cont.
<p>Effects of <span class="html-italic">L. paracasei</span> subsp. <span class="html-italic">paracasei</span> DSM 27449 on the gut microbiome in letrozole-induced polycystic ovary syndrome-like rats. Alpha diversity is represented by (<b>A</b>) the Chao1 index, (<b>B</b>) the Shannon index, and (<b>C</b>) the Simpson index. N = 8 per group; <sup><span>$</span><span>$</span></sup> <span class="html-italic">p</span> &lt; 0.01 compared with the Diane-35 group. (<b>D</b>) Beta diversity is represented by a non-metric multi-dimensional scaling (NMDS) plot and the analysis of similarities (ANOSIMs). (<b>E</b>) Composition of the gut microbiome at the phylum level. (<b>F</b>–<b>K</b>) Relative abundance of differential bacteria at the genus level between the control and letrozole groups and between the control and DSM 27449 groups. N = 8 per group; the Bonferroni method was applied to correct for Type I errors, with statistical significance considered at * <span class="html-italic">p</span> &lt; 0.05/2.</p>
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<p>Heat maps of the Spearman’s rank correlation coefficient. (<b>A</b>) Heat map representing the correlation between differential genera and polycystic ovary syndrome-related parameters. (<b>B</b>) Heat map representing the correlation between differential genera and microRNA expressions. N = 6–8 per group; * <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, and **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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16 pages, 315 KiB  
Review
Dietary Effects on the Gut Phageome
by Andrea Howard, Amanda Carroll-Portillo, Joe Alcock and Henry C. Lin
Int. J. Mol. Sci. 2024, 25(16), 8690; https://doi.org/10.3390/ijms25168690 - 9 Aug 2024
Viewed by 233
Abstract
As knowledge of the gut microbiome has expanded our understanding of the symbiotic and dysbiotic relationships between the human host and its microbial constituents, the influence of gastrointestinal (GI) microbes both locally and beyond the intestine has become evident. Shifts in bacterial populations [...] Read more.
As knowledge of the gut microbiome has expanded our understanding of the symbiotic and dysbiotic relationships between the human host and its microbial constituents, the influence of gastrointestinal (GI) microbes both locally and beyond the intestine has become evident. Shifts in bacterial populations have now been associated with several conditions including Crohn’s disease (CD), Ulcerative Colitis (UC), irritable bowel syndrome (IBS), Alzheimer’s disease, Parkinson’s Disease, liver diseases, obesity, metabolic syndrome, anxiety, depression, and cancers. As the bacteria in our gut thrive on the food we eat, diet plays a critical role in the functional aspects of our gut microbiome, influencing not only health but also the development of disease. While the bacterial microbiome in the context of disease is well studied, the associated gut phageome—bacteriophages living amongst and within our bacterial microbiome—is less well understood. With growing evidence that fluctuations in the phageome also correlate with dysbiosis, how diet influences this population needs to be better understood. This review surveys the current understanding of the effects of diet on the gut phageome. Full article
(This article belongs to the Special Issue Gut Microbiota in Human Diseases and Health)
15 pages, 1927 KiB  
Article
Probiotic Lactobacilli Ameliorate Antibiotic-Induced Cognitive and Behavioral Impairments in Mice
by Dina Yarullina, Vera Novoselova, Anastasia Alexandrova, Alisa Arslanova, Olga Yakovleva, Ilnar Shaidullov, Yury Nikolaev, Galina El-Registan, Vladimir Kudrin and Guzel Sitdikova
Microbiol. Res. 2024, 15(3), 1471-1485; https://doi.org/10.3390/microbiolres15030099 - 8 Aug 2024
Viewed by 229
Abstract
Increasing evidence suggests that the gut microbiota, through the “microbiota–gut–brain axis”, can regulate anxiety, mood, and cognitive abilities such as memory and learning processes. Consistently with this, treatments altering the gut microbiota, such as antibiotics and probiotics, may influence brain function and impact [...] Read more.
Increasing evidence suggests that the gut microbiota, through the “microbiota–gut–brain axis”, can regulate anxiety, mood, and cognitive abilities such as memory and learning processes. Consistently with this, treatments altering the gut microbiota, such as antibiotics and probiotics, may influence brain function and impact behavior. The mechanisms that underlie the interplay between the intestinal microbiota and the brain have been intensively studied. We aimed to investigate the effects of two probiotic lactobacilli strains, Lacticaseibacillus rhamnosus 12L and Lactiplantibacillus plantarum 8PA3, on behavioral disorders in mice induced by a two-week parenteral treatment with broad-spectrum antibiotics. On completion of the treatment, the mice were subjected to behavioral tests, including the open field test (OFT), novel object recognition test (ORT), and T-maze test. Antibiotic-treated mice demonstrated anxiety-related behavior, decreased cognition, and retarded exploratory activity that were ameliorated by the administration of probiotics. As was determined by high-performance liquid chromatography (HPLC), both tested strains produced serotonin and its metabolite 5-hydroxyindoleacetic acid (5-HIAA), as well as dopamine, which was further metabolized into norepinephrine by L. plantarum 8PA3 and epinephrine by L. rhamnosus 12L. Moreover, these lactobacilli were found to harbor catecholamines and 3,4-dihydroxyphenylacetic acid (DOPAC) in their biomass when grown on MRS broth. Additionally, L. plantarum 8PA3 and L. rhamnosus 12L were able to impact oxidative stress via H2O2 production and antioxidant activity, as determined in this study by the ferrous oxidation–xylenol orange (FOX) assay and the 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging assay, respectively. The results obtained in this study support the role of probiotics as a promising therapeutic for neurological disorders. However, more investigations are required to confirm the clinical significance of this finding. Full article
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Figure 1

Figure 1
<p>Effects of treatment with antibiotics (AB) and antibiotics together with probiotics (AB + LB) on mortality (<b>A</b>) and weight (<b>B</b>) of mice. (<b>A</b>) The white part is the percentage of surviving animals and the green part is the percentage of dead animals after two weeks of treatment. (<b>B</b>) The initial weight of the mice before treatment was assumed to be 100%. Data are expressed as the mean ± SEM; n = 5; * <span class="html-italic">p</span> &lt; 0.05 compared to the control untreated group, # <span class="html-italic">p</span> &lt; 0.05 compared to the initial values.</p>
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<p>Effects of treatment with antibiotics (AB) and antibiotics together with probiotics (AB + LB) on anxiety levels of mice. (<b>A</b>) The integral anxiety score of the mice during the two-week treatment. In (<b>B</b>–<b>D</b>), the parameters of the anxiety levels of the mice are given for the open field test upon the completion of the treatment. (<b>B</b>) The frequency of grooming activity in the mice. (<b>C</b>) The time spent by the mice in the center square of the arena. (<b>D</b>) The number of fecal boli produced by the mice. Data are expressed as the mean ± SEM; n = 5. * <span class="html-italic">p</span> &lt; 0.05 compared to the control untreated group, # <span class="html-italic">p</span> &lt; 0.05 compared to the initial values.</p>
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<p>Effects of treatment with antibiotics (AB) and antibiotics together with probiotics (AB + LB) on locomotory activity of mice, measured in open field test upon completion of treatment. (<b>A</b>) The number of crossed squares, i.e., horizontal activity. (<b>B</b>) The number of rearings, i.e., vertical activity. (<b>C</b>) The total locomotor activity of the mice, calculated as the sum of the horizontal activity (square crossings) and vertical activity (number of rearings). Data are expressed as the mean ± SEM; n = 5; * <span class="html-italic">p</span> &lt; 0.05 compared to the control untreated group, # <span class="html-italic">p</span> &lt; 0.05 compared to the initial values.</p>
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<p>Effects of treatment with antibiotics (AB) and antibiotics together with probiotics (AB + LB) on cognitive function of mice, measured upon completion of treatment. (<b>A</b>) Head dips. (<b>B</b>) Novel object recognition (NOR) score. (<b>C</b>) Percentage of alternation in the T-maze. Data are expressed as the mean ± SEM; n = 5; * <span class="html-italic">p</span> &lt; 0.05 compared to the initial values, # <span class="html-italic">p</span> &lt; 0.05 compared to the control untreated group.</p>
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<p>Production and processing of neurotransmitters by <span class="html-italic">L. plantarum</span> 8PA3 (<b>A</b>) and <span class="html-italic">L. rhamnosus</span> 12L (<b>B</b>). Numbers indicate the amount produced during growth in MRS broth (pmol/mL). Negative values indicate an inability to synthesize the neurotransmitter and absorption from the nutrient medium. Frames indicate the secretion of the neurotransmitter into the saline.</p>
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14 pages, 868 KiB  
Article
Intestinal Dysbiosis, Tight Junction Proteins, and Inflammation in Rheumatoid Arthritis Patients: A Cross-Sectional Study
by Arkaitz Mucientes, José Manuel Lisbona-Montañez, Natalia Mena-Vázquez, Patricia Ruiz-Limón, Sara Manrique-Arija, Aimara García-Studer, Fernando Ortiz-Márquez and Antonio Fernández-Nebro
Int. J. Mol. Sci. 2024, 25(16), 8649; https://doi.org/10.3390/ijms25168649 - 8 Aug 2024
Viewed by 256
Abstract
Recent studies point to intestinal permeability as an important factor in the establishment and development of rheumatoid arthritis (RA). Tight junctions (TJs) play a major role in intestinal homeostasis. The alteration of this homeostasis is related to RA. Furthermore, RA patients present dysbiosis [...] Read more.
Recent studies point to intestinal permeability as an important factor in the establishment and development of rheumatoid arthritis (RA). Tight junctions (TJs) play a major role in intestinal homeostasis. The alteration of this homeostasis is related to RA. Furthermore, RA patients present dysbiosis and a lower microbiota diversity compared to healthy individuals. A cross-sectional study including RA patients and sex- and age-matched healthy controls was performed. The quantification of TJ proteins was carried out by ELISA. Gut microbiota was evaluated by NGS platform Ion Torrent S. The inflammatory variables included were DAS28, CRP, inflammatory cytokines (IL-6, IL-1, TNF-α) and oxidised LDL. Claudin-1 levels showed significant differences between groups. Results evidenced a correlation between claudin-1 values and age (r: −0.293; p < 0.05), IL6 (r: −0.290; p < 0.05) and CRP (r: −0.327; p < 0.05), and between zonulin values and both age (r: 0.267; p < 0.05) and TNFα (r: 0.266; p < 0.05). Moreover, claudin-1 and CRP levels are related in RA patients (β: −0.619; p: 0.045), and in patients with high inflammatory activity, the abundance of the genus Veillonella is positively associated with claudin-1 levels (β: 39.000; p: 0.004). Full article
(This article belongs to the Special Issue Molecular Research in Rheumatoid Arthritis)
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<p>Schematic representation of the gastrointestinal barrier, highlighting the tight junction (TJ) proteins analysed. Zonulin (red) modulates intestinal permeability by regulating TJ disassembly. Occludin (green) and claudin-1 (yellow) are structural proteins of the TJ that co-ordinately maintain the integrity and selective permeability of the barrier. When zonulin binds the EGFR (dark blue) and PAR2 (dark green) receptors, it activates a cascade of reactions that ultimately result in the displacement of occludin and claudin-1, leading to loosening of the TJs (2). When zonulin signalling stops, the TJs return to their closed basal state (1).</p>
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<p>Concentration of the distinct tight junction proteins analysed in faeces. Red: rheumatoid arthritis (RA) patients; blue: healthy controls. Data are shown as mean ± standard deviation for claudin-1 and median (p25–p75) for occludin and zonulin. Significance level: * <span class="html-italic">p</span> ≤ 0.05.</p>
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15 pages, 1175 KiB  
Review
Gut Microbiota, Deranged Immunity, and Hepatocellular Carcinoma
by Emidio Scarpellini, Giuseppe Guido Maria Scarlata, Valeria Santori, Marialaura Scarcella, Nazarii Kobyliak and Ludovico Abenavoli
Biomedicines 2024, 12(8), 1797; https://doi.org/10.3390/biomedicines12081797 - 7 Aug 2024
Viewed by 268
Abstract
Background: Liver cancer, particularly hepatocellular carcinoma (HCC), is a significant gastrointestinal disease with a mortality rate as high as nearly 80% within five years. The disease’s pathophysiology involves deranged immune responses and bile acid metabolism, with the gut microbiota (GM) playing a crucial [...] Read more.
Background: Liver cancer, particularly hepatocellular carcinoma (HCC), is a significant gastrointestinal disease with a mortality rate as high as nearly 80% within five years. The disease’s pathophysiology involves deranged immune responses and bile acid metabolism, with the gut microbiota (GM) playing a crucial role. Recent research highlights the potential of GM in influencing HCC treatment outcomes, especially regarding immune checkpoint inhibitors (ICIs). However, few patients currently benefit from ICIs due to a lack of effective response biomarkers. Aims and methods: This review aimed to explore the literature on HCC treatment issues, focusing on immune response, bile acid metabolism, and GM dysbiosis. This review included studies from PubMed, Medline, and major gastroenterology and hepatology meetings, using keywords like gut microbiota, immune system, liver cancer, and checkpoint inhibitors. Results: GM dysbiosis significantly impacts immune response and bile acid metabolism, making it a promising biomarker for ICI response. Modulating GM can enhance ICI treatment efficacy, although more research is needed to confirm its direct therapeutic benefits for HCC. Conclusions: GM dysbiosis is integral to liver cancer pathogenesis and treatment response. Its modulation offers promising therapeutic avenues for improving HCC prognosis and response to immunotherapy. Full article
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<p>Mechanisms underlying the interactions between the gut microbiota, deranged immunity, and liver cancer. Gut microbiota dysbiosis drives immune system immunosurveillance impairment in the liver through its metabolites and the interaction with bile acid metabolism. Vagus nerve signaling modulates immune response within the liver and is affected by gut microbiota composition. LPS: lipopolysaccharide; SCFAs: short-chain fatty acids; MAMPs: microbe-associated molecular patterns; PAMPs: pathogen-associated molecular patterns; BAs: bile acids; DCs: dendritic cells; MHs: mesenchymal hepatic cells.</p>
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<p>Key conclusive points for take-home messages.</p>
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18 pages, 1468 KiB  
Review
The Microbiome in Inflammatory Bowel Disease
by Aranzazu Jauregui-Amezaga and Annemieke Smet
J. Clin. Med. 2024, 13(16), 4622; https://doi.org/10.3390/jcm13164622 - 7 Aug 2024
Viewed by 425
Abstract
The management of patients with inflammatory bowel disease (IBD) aims to control inflammation through the use of immunosuppressive treatments that target various points in the inflammatory cascade. However, the efficacy of these therapies in the long term is limited, and they often are [...] Read more.
The management of patients with inflammatory bowel disease (IBD) aims to control inflammation through the use of immunosuppressive treatments that target various points in the inflammatory cascade. However, the efficacy of these therapies in the long term is limited, and they often are associated with severe side effects. Although the pathophysiology of the disease is not completely understood, IBD is regarded as a multifactorial disease that occurs due to an inappropriate immune response in genetically susceptible individuals. The gut microbiome is considered one of the main actors in the development of IBD. Gut dysbiosis, characterised by significant changes in the composition and functionality of the gut microbiota, often leads to a reduction in bacterial diversity and anti-inflammatory anaerobic bacteria. At the same time, bacteria with pro-inflammatory potential increase. Although changes in microbiome composition upon biological agent usage have been observed, their role as biomarkers is still unclear. While most studies on IBD focus on the intestinal bacterial population, recent studies have highlighted the importance of other microbial populations, such as viruses and fungi, in gut dysbiosis. In order to modulate the aberrant immune response in patients with IBD, researchers have developed therapies that target different players in the gut microbiome. These innovative approaches hold promise for the future of IBD treatment, although safety concerns are the main limitations, as their effects on humans remain unknown. Full article
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<p>Schematic representation of the human intestinal microbiome. The microbiota is a broad concept that includes microorganisms (the microbiota), the genes and gene products of the microbiota, and the microenvironment. Most nutrients are digested and absorbed in the small intestine. However, dietary fibre remains intact until it reaches the colon. In the colon, a fermentation process is performed by enzymes produced by gut bacteria, resulting in short-chain fatty acid (SCFA) production, including acetate, propionate, and butyrate. These metabolites participate in various cellular and immunological processes. They stimulate the production of mucins, reduce the intestinal permeability, and promote anti-inflammatory pathways. Among the SCFAs, butyrate is the main energy source for the intestinal epithelial cells and has modulator functions that lead to a decreased concentration of oxygen in the intestinal lumen. As a result, the number of obligate anaerobic bacteria, including those of the phylum Firmicutes, which produce butyrate, increases. Bile acids (BAs) are the end products of cholesterol catabolism and are released into the small intestine through the ampulla of Vater. They form micelles with lipid molecules and facilitate their absorption in the small bowel through the enterohepatic circulation. However, there is a small proportion of BAs that remain in the gut and is metabolised by the gut bacteria [<a href="#B11-jcm-13-04622" class="html-bibr">11</a>]. Tryptophan is an essential amino acid that should be ingested with the diet. Gut bacteria convert it into tryptamine and other products. These products can function as endogenous ligands for the aryl hydrocarbon receptor (AhR), an essential signalling pathway in the maintenance of gut homeostasis [<a href="#B12-jcm-13-04622" class="html-bibr">12</a>].</p>
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<p>Overview of the intestinal mucosal barrier. The human gut is a vast surface of contact with the environment that is colonised by trillions of gut microbes. The intestinal barrier comprises a thick layer of mucus, a single layer of epithelial cells, and the inner lamina propria hosting innate and adaptive immune cells. The intestinal epithelium, along with the mucus layer that covers it, acts as a physical barrier.</p>
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<p>Multi-omics for the study of the human gut microbiome in inflammatory bowel disease. Metagenomics involves identifying the bacterial composition and diversity using techniques such as 16S rRNA gene amplicon or shotgun sequencing. This method provides information on the presence or absence of specific genes in the microbiome. Metatranscriptomics focuses on assessing the functionality of the microbiome by analysing gene expression over time using RNA sequencing techniques. Proteomics studies the entire set of proteins that a genome can express in a cell, known as the proteome. Combining metagenomic and metaproteomic data, it is possible to characterise signalling proteins and pathways. Metabolomics explores the metabolome, which consists of metabolites derived from both the host and microorganisms.</p>
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17 pages, 11847 KiB  
Article
Hepatic Steatosis Can Be Partly Generated by the Gut Microbiota–Mitochondria Axis via 2-Oleoyl Glycerol and Reversed by a Combination of Soy Protein, Chia Oil, Curcumin and Nopal
by Mónica Sánchez-Tapia, Sandra Tobón-Cornejo, Lilia G. Noriega, Natalia Vázquez-Manjarrez, Diana Coutiño-Hernández, Omar Granados-Portillo, Berenice M. Román-Calleja, Astrid Ruíz-Margáin, Ricardo U. Macías-Rodríguez, Armando R. Tovar and Nimbe Torres
Nutrients 2024, 16(16), 2594; https://doi.org/10.3390/nu16162594 - 6 Aug 2024
Viewed by 718
Abstract
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a serious health problem, and recent evidence indicates that gut microbiota plays a key role in its development. It is known that 2-oleoyl glycerol (2-OG) produced by the gut microbiota is associated with hepatic fibrosis, but [...] Read more.
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a serious health problem, and recent evidence indicates that gut microbiota plays a key role in its development. It is known that 2-oleoyl glycerol (2-OG) produced by the gut microbiota is associated with hepatic fibrosis, but it is not known whether this metabolite is involved in the development of hepatic steatosis. The aim of this study was to evaluate how a high-fat–sucrose diet (HFS) increases 2-OG production through gut microbiota dysbiosis and to identify whether this metabolite modifies hepatic lipogenesis and mitochondrial activity for the development of hepatic steatosis as well as whether a combination of functional foods can reverse this process. Wistar rats were fed the HFS diet for 7 months. At the end of the study, body composition, biochemical parameters, gut microbiota, protein abundance, lipogenic and antioxidant enzymes, hepatic 2-OG measurement, and mitochondrial function of the rats were evaluated. Also, the effect of the consumption of functional food with an HFS diet was assessed. In humans with MASLD, we analyzed gut microbiota and serum 2-OG. Consumption of the HFS diet in Wistar rats caused oxidative stress, hepatic steatosis, and gut microbiota dysbiosis, decreasing α-diversity and increased Blautia producta abundance, which increased 2-OG. This metabolite increased de novo lipogenesis through ChREBP and SREBP-1. 2-OG significantly increased mitochondrial dysfunction. The addition of functional foods to the diet modified the gut microbiota, reducing Blautia producta and 2-OG levels, leading to a decrease in body weight gain, body fat mass, serum glucose, insulin, cholesterol, triglycerides, fatty liver formation, and increased mitochondrial function. To use 2-OG as a biomarker, this metabolite was measured in healthy subjects or with MASLD, and it was observed that subjects with hepatic steatosis II and III had significantly higher 2-OG than healthy subjects, suggesting that the abundance of this circulating metabolite could be a predictor marker of hepatic steatosis. Full article
(This article belongs to the Special Issue Diet, Oxidative Stress and Liver Metabolism)
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<p>Consumption of a high-fat diet +5% sucrose in the drinking water (HFS) produces hepatic steatosis. (<b>A</b>) Experimental model of hepatic steatosis, (<b>B</b>) Body weight gain, (<b>C</b>) Body composition, serum (<b>D</b>) Glucose, (<b>E</b>) Insulin, (<b>F</b>) Total cholesterol, (<b>G</b>) Triglycerides, and (<b>H</b>) Histological analysis of liver from rats fed HFS or Control diet (C) for 7 months. Mean ± SEM is shown in each graph, n = 6–7 in each group. Significant differences are presented by asterisk, *** <span class="html-italic">p</span> &lt; 0.0002, **** <span class="html-italic">p</span> &lt; 0.00001.</p>
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<p>Consumption of a high-fat +5% sucrose diet in the drinking water (HFS) promotes dysbiosis of the gut microbiota and a chronic inflammatory state. (<b>A</b>) Alpha diversity, (<b>B</b>) Principal Component Analysis, (<b>C</b>) Linear Discriminant Analysis, Prediction of metagenome functionality (PICRUST) of (<b>D</b>) lipid metabolism and (<b>E</b>) inflammation. (<b>F</b>) serum LPS, (<b>G</b>) Western blot, and (<b>H</b>) Densitometric analysis of colonic inflammatory proteins extracted from rats fed HFS or C diet for 7 months. Mean ± SEM is shown in each graph, n = 6–7 in each group. Significant differences are presented by asterisk, ** <span class="html-italic">p</span> &lt; 0.0021, *** <span class="html-italic">p</span> &lt; 0.0002, **** <span class="html-italic">p</span> &lt; 0.00001.</p>
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<p>Effect of 2-oleoyl glycerol (2-OG) on rat hepatocytes. (<b>A</b>) Western blot and (<b>B</b>) Densitometric analysis of hepatic lipogenic proteins, (<b>C</b>) Oxygen consumption rate, (<b>D</b>) Mitochondrial function parameters, (<b>E</b>) Extracellular acidification rate, and (<b>F</b>) Cellular glycolysis analysis in hepatocytes cultured with vehicle or 2-OG. Mean ± SEM is shown in each graph. Significant differences are presented by asterisk, * <span class="html-italic">p</span> &lt; 0.0332, ** <span class="html-italic">p</span> &lt; 0.0021.</p>
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<p>2-oleoyl glycerol (2-OG) stimulates lipogenesis in rats fed high fat +5% sucrose in the drinking water (HFS). (<b>A</b>) hepatic 2-OG concentration, (<b>B</b>) Western blot analysis, (<b>C</b>) Densitometric analysis of transcription factors and target enzymes of lipogenesis, (<b>D</b>) Macroscopic view of liver, (<b>E</b>) Hepatic triglycerides and cholesterol concentrations, (<b>F</b>) Hepatic lipid profile and (<b>G</b>) Analysis of correlations of lipogenic proteins, 2-OG concentration and <span class="html-italic">Blautia producta</span>, in rats fed a control diet or HFS diet. Mean ± SEM is shown in each graph. Significant differences are presented by asterisk. * <span class="html-italic">p</span> &lt; 0.0332, ** <span class="html-italic">p</span> &lt; 0.0021, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Effect of a combination of functional foods on hepatic steatosis. (<b>A</b>) Experimental model, (<b>B</b>) Body weight gain, (<b>C</b>) Body composition, serum fasting, (<b>D</b>) Glucose, (<b>E</b>) Insulin, (<b>F</b>) Total cholesterol and (<b>G</b>) triglycerides, and (<b>H</b>) histological analysis of liver from rats fed HFS diet with or without functional foods for 3 months. Mean ± SEM is shown in each graph. Significant differences are presented by asterisk, ** <span class="html-italic">p</span> &lt; 0.0021, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Functional foods modify gut microbiota, attenuating hepatic steatosis. (<b>A</b>) Alpha diversity, (<b>B</b>) Linear Discriminant Analysis, (<b>C</b>) Western Blot and (<b>D</b>) Densitometric analysis of hepatic pro-inflammatory cytokines, (<b>E</b>) Serum LPS concentration, (<b>F</b>) Hepatic concentration of 2-oleoyl glycerol (2-OG), (<b>G</b>) Western blot and (<b>H</b>) Densitometric analysis of hepatic lipogenic proteins. (<b>I</b>) Macroscopic view of the liver, (<b>J</b>) hepatic triglycerides and cholesterol, and (<b>K</b>) Hepatic lipid profile of rats fed HFS with or without functional foods for 3 months. Mean ± SEM is shown in each graph. Significant differences are presented by asterisk, * <span class="html-italic">p</span> &lt; 0.0332, ** <span class="html-italic">p</span> &lt; 0.0021, *** <span class="html-italic">p</span> &lt; 0.0002, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Consumption of Functional foods in the diet improves mitochondrial function. (<b>A</b>) Hepatic CPT-1 protein abundance, (<b>B</b>) Oxygen consumption rate and (<b>C</b>) Mitochondrial function parameters in hepatocytes incubated with different concentrations of the functional food extract, (<b>D</b>) Reactive oxygen species, (<b>E</b>) Western blot and (<b>F</b>) Densitometric analysis of the transcription factor Nrf 2 and antioxidant enzymes SOD2, catalase, GPx4 in liver of rats fed HFS diet with or without functional foods for 3 months. Mean ± SEM is shown in each graph. Significant differences are presented by asterisks * <span class="html-italic">p</span> &lt; 0.0332, ** <span class="html-italic">p</span> &lt; 0.0021, **** <span class="html-italic">p</span> &lt; 0.0001, or letters (a &gt; b &gt; c).</p>
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<p>Subjects with MASLD increase <span class="html-italic">Blautia producta</span> and serum concentrations of 2-OG. (<b>A</b>) Alpha diversity, (<b>B</b>) Principal component analysis, (<b>C</b>) Most abundant genus in subject with MASLD, (<b>D</b>) Species Linear discriminant analysis between healthy and MASLD subjects, (<b>E</b>) Serum 2-OG concentration, and (<b>F</b>) correlation analysis between anthropometric variables, elastography parameters, 2-OG, and <span class="html-italic">Blautia producta</span> in subjects with MASLD. Mean ± SEM is shown in each graph. Significant differences are presented by asterisk, *** <span class="html-italic">p</span> &lt; 0.0002, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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13 pages, 1821 KiB  
Review
Epigenetics, Microbiome and Personalized Medicine: Focus on Kidney Disease
by Giuseppe Gigliotti, Rashmi Joshi, Anam Khalid, David Widmer, Mariarosaria Boccellino and Davide Viggiano
Int. J. Mol. Sci. 2024, 25(16), 8592; https://doi.org/10.3390/ijms25168592 - 6 Aug 2024
Viewed by 335
Abstract
Personalized medicine, which involves modifying treatment strategies/drug dosages based on massive laboratory/imaging data, faces large statistical and study design problems. The authors believe that the use of continuous multidimensional data, such as those regarding gut microbiota, or binary multidimensional systems properly transformed into [...] Read more.
Personalized medicine, which involves modifying treatment strategies/drug dosages based on massive laboratory/imaging data, faces large statistical and study design problems. The authors believe that the use of continuous multidimensional data, such as those regarding gut microbiota, or binary multidimensional systems properly transformed into a continuous variable, such as the epigenetic clock, offer an advantageous scenario for the design of trials of personalized medicine. We will discuss examples focusing on kidney diseases, specifically on IgA nephropathy. While gut dysbiosis can provide a treatment strategy to restore the standard gut microbiota using probiotics, transforming epigenetic omics data into epigenetic clocks offers a promising tool for personalized acute and chronic kidney disease care. Epigenetic clocks involve a complex transformation of DNA methylome data into estimated biological age. These clocks can identify people at high risk of developing kidney problems even before symptoms appear. Some of the effects of both the epigenetic clock and microbiota on kidney diseases seem to be mediated by endothelial dysfunction. These “big data” (epigenetic clocks and microbiota) can help tailor treatment plans by pinpointing patients likely to experience rapid declines or those who might not need overly aggressive therapies. Full article
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<p>Gut microbiota and kidney disease in personalized medicine. Changes in gut microbiota are thought to induce an overactivation of the gut immune system. This may result in a local inflammatory disease (inflammatory bowel disease, such as Crohn’s disease or ulcerative colitis), or damage to other organs such as in Systemic Lupus Erythematosus (SLE) or IgA Nephropathy (IgAN). The regulation of gut dysbiosis using a personalized medicine approach may reduce the chance of these conditions being triggered. Arrows indicate stimulation, crossed arrow (X) means inhibition.</p>
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<p><b>Left</b>: Relationship between number of glomeruli and maximum lifespan. The blue dot represents Homo sapiens. <b>Right</b>: Graphical representation of the MDRD formula reported in the text, with theoretical relationship between age and eGFR (the constant value of the formula has been fixed considering a male Caucasian subject and a constant creatinine of 0.96). The number of glomeruli in different mammals has been derived from [<a href="#B51-ijms-25-08592" class="html-bibr">51</a>,<a href="#B52-ijms-25-08592" class="html-bibr">52</a>]. The lifespans of different mammals have been derived from [<a href="#B53-ijms-25-08592" class="html-bibr">53</a>] and from the AnAge database (<a href="http://genomics.senescence.info/species/" target="_blank">http://genomics.senescence.info/species/</a> accessed on 10 June 2007) and the database from [<a href="#B54-ijms-25-08592" class="html-bibr">54</a>] (<a href="https://www.demogr.mpg.de/longevityrecords/0203.htm" target="_blank">https://www.demogr.mpg.de/longevityrecords/0203.htm</a> accessed on 10 June 2023).</p>
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<p>Epigenetic clock and kidney disease in personalized medicine. <b>Upper panel</b>: The epigenetic landscape of DNA is correlated with the human ageing process, and therefore with the individual variability in kidney diseases such as IgAN. It is possible that the ageing of endothelial cells mediates this relationship. <b>Lower panel</b>: Overall hypothesis regarding the microbiota and epigenetic clock control of kidney disease variability. Gut dysbiosis may represent a relevant trigger for kidney diseases such as IgAN. The epigenetic clock represents a modulator of endothelial and fibroblast responses to the immune trigger. A personalized medicine approach based on microbiome and epigenome data might result in a personalized treatment strategy.</p>
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19 pages, 1608 KiB  
Review
Marine Bioactive Compounds with Functional Role in Immunity and Food Allergy
by Ana G. Abril, Mónica Carrera and Manuel Pazos
Nutrients 2024, 16(16), 2592; https://doi.org/10.3390/nu16162592 - 6 Aug 2024
Viewed by 711
Abstract
Food allergy, referred to as the atypical physiological overreaction of the immune system after exposure to specific food components, is considered one of the major concerns in food safety. The prevalence of this emerging worldwide problem has been increasing during the last decades, [...] Read more.
Food allergy, referred to as the atypical physiological overreaction of the immune system after exposure to specific food components, is considered one of the major concerns in food safety. The prevalence of this emerging worldwide problem has been increasing during the last decades, especially in industrialized countries, being estimated to affect 6–8% of young children and about 2–4% of adults. Marine organisms are an important source of bioactive substances with the potential to functionally improve the immune system, reduce food allergy sensitization and development, and even have an anti-allergic action in food allergy. The present investigation aims to be a comprehensive report of marine bioactive compounds with verified actions to improve food allergy and identified mechanisms of actions rather than be an exhaustive compilation of all investigations searching beneficial effects of marine compounds in FA. Particularly, this research highlights the capacity of bioactive components extracted from marine microbial, animal, algae, and microalgae sources, such as n-3 long-chain polyunsaturated fatty acids (LC-PUFA), polysaccharide, oligosaccharide, chondroitin, vitamin D, peptides, pigments, and polyphenols, to regulate the immune system, epigenetic regulation, inflammation, and gut dysbiosis that are essential factors in the sensitization and effector phases of food allergy. In conclusion, the marine ecosystem is an excellent source to provide foods with the capacity to improve the hypersensitivity induced against specific food allergens and also bioactive compounds with a potential pharmacological aptitude to be applied as anti-allergenic in food allergy. Full article
(This article belongs to the Special Issue Relationship between Food Allergy and Human Health)
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<p>Th2 cell-mediated inflammatory response to oral antigen in the gut (adapted from Abril et al. [<a href="#B10-nutrients-16-02592" class="html-bibr">10</a>]).</p>
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<p>Biosynthesis of bioactive lipid mediators derived from the marine <span class="html-italic">n</span>-3 eicosapentaenoic acid (EPA, 20:5 <span class="html-italic">n</span>-3) and docosahexaenoic acid (DHA, 22:6 <span class="html-italic">n</span>-3) and the competition with the production of pro-inflammatory lipid mediators derived from the <span class="html-italic">n</span>-6 arachidonic acid (ARA; 20:4 <span class="html-italic">n</span>-6) (adapted from Abril et al. [<a href="#B10-nutrients-16-02592" class="html-bibr">10</a>]).</p>
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<p>The role of vitamin D in food allergy. Reproduced from Giannetti et al., 2020 [<a href="#B122-nutrients-16-02592" class="html-bibr">122</a>], with permission from publisher Frontiers, 2024 (Creative Commons CC-BY licence (CC-BY 4.0).</p>
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14 pages, 541 KiB  
Review
The Potential Role of Butyrate in the Pathogenesis and Treatment of Autoimmune Rheumatic Diseases
by Carmela Coccia, Francesco Bonomi, Anna Lo Cricchio, Edda Russo, Silvia Peretti, Giulia Bandini, Gemma Lepri, Francesca Bartoli, Alberto Moggi-Pignone, Serena Guiducci, Francesco Del Galdo, Daniel E. Furst, Marco Matucci Cerinic and Silvia Bellando-Randone
Biomedicines 2024, 12(8), 1760; https://doi.org/10.3390/biomedicines12081760 - 5 Aug 2024
Viewed by 444
Abstract
The gut microbiota is a complex ecosystem of microorganisms residing in the human gastrointestinal tract, playing a crucial role in various biological processes and overall health maintenance. Dysbiosis, an imbalance in the composition and function of the gut microbiota, is linked to systemic [...] Read more.
The gut microbiota is a complex ecosystem of microorganisms residing in the human gastrointestinal tract, playing a crucial role in various biological processes and overall health maintenance. Dysbiosis, an imbalance in the composition and function of the gut microbiota, is linked to systemic autoimmune diseases (SAD). Short-chain fatty acids (SCFAs), especially butyrate, produced by the gut microbiota through the fermentation of dietary fibers, play a significant role in immunomodulation and maintaining intestinal homeostasis. Butyrate is essential for colonocyte energy, anti-inflammatory responses, and maintaining intestinal barrier integrity. Studies show reduced butyrate-producing bacteria in SAD patients, suggesting that increasing butyrate levels could have therapeutic benefits. Butyrate’s anti-inflammatory effects and its potential therapeutic role have been studied in rheumatoid arthritis, Sjogren’s syndrome, systemic lupus erythematosus, systemic sclerosis, and Behçet’s disease. Despite promising in vitro and animal model results, human studies are limited, and the optimal strategies for modulating dysbiosis in SADs remain elusive. This review explores the current evidence on the immunoregulatory role of butyrate and its potential therapeutic effects in SAD. Full article
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<p>Mechanism of action of butyrate and its role in modulating the immune system. HDAC: histone deacetylase, SMA: smooth muscle actin.</p>
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27 pages, 3236 KiB  
Review
Nature of the Association between Rheumatoid Arthritis and Cervical Cancer and Its Potential Therapeutic Implications
by Kirill Gusakov, Alexander Kalinkovich, Shai Ashkenazi and Gregory Livshits
Nutrients 2024, 16(15), 2569; https://doi.org/10.3390/nu16152569 - 5 Aug 2024
Viewed by 995
Abstract
It is now established that patients with rheumatoid arthritis (RA) have an increased risk of developing cervical cancer (CC) or its precursor, cervical intraepithelial neoplasia (CIN). However, the underlying mechanisms of this association have not been elucidated. RA is characterized by unresolved chronic [...] Read more.
It is now established that patients with rheumatoid arthritis (RA) have an increased risk of developing cervical cancer (CC) or its precursor, cervical intraepithelial neoplasia (CIN). However, the underlying mechanisms of this association have not been elucidated. RA is characterized by unresolved chronic inflammation. It is suggested that human papillomavirus (HPV) infection in RA patients exacerbates inflammation, increasing the risk of CC. The tumor microenvironment in RA patients with CC is also marked by chronic inflammation, which aggravates the manifestations of both conditions. Gut and vaginal dysbiosis are also considered potential mechanisms that contribute to the chronic inflammation and aggravation of RA and CC manifestations. Numerous clinical and pre-clinical studies have demonstrated the beneficial effects of various nutritional approaches to attenuate chronic inflammation, including polyunsaturated fatty acids and their derivatives, specialized pro-resolving mediators (SPMs), probiotics, prebiotics, and certain diets. We believe that successful resolution of chronic inflammation and correction of dysbiosis, in combination with current anti-RA and anti-CC therapies, is a promising therapeutic approach for RA and CC. This approach could also reduce the risk of CC development in HPV-infected RA patients. Full article
(This article belongs to the Section Nutritional Immunology)
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<p>Schematic presentation of mechanisms underlying the involvement of gut and vaginal dysbiosis in the creation of chronic inflammation in RA patients with HPV-induced CC. Gut and vaginal dysbiosis in RA patients is characterized by the prevalence of specific bacteria species that cause several detrimental effects, such as the destruction of tight junction proteins and intestinal barrier integrity. This results in lipopolysaccharide leakage into the gut lumen, leading to the activation of gut-resident immune cells, including dendritic cells (DCs), macrophages, neutrophils, intraepithelial lymphoid cells (ILCs), Th17 cells, B cells, invariant natural killer T cells (iNKTs), mucosal-associated invariant T cells (MAITs), T-follicular helper cells (Tfhs), and T-regulatory cells (Tregs). The activated immune cells secrete a variety of pro-inflammatory molecules, which can activate epithelial and immune cells in autocrine, paracrine, and endocrine (systematic) manners, culminating in the creation of chronic inflammation. HPV infection is accompanied by both gut and vaginal dysbiosis, typically associated with the prevalence of bacterial species, as displayed in the diagram. Development of CC in HPV-infected RA patients exacerbates gut and vaginal dysbiosis. Dysbiosis, in turn, maintains and worsens chronic inflammation, which, as suggested in the review, is responsible for the aggravation of RA and CC manifestations. Further explanations are given in the text. <span class="html-italic">Abbreviations</span>: CIN, cervical intraepithelial neoplasia; <span class="html-italic">C. rodentium</span>, <span class="html-italic">Citrobacter rodentium</span>; <span class="html-italic">C. aerofaciens</span>, <span class="html-italic">Collinsella aerofaciens</span>; HPV, human papillomavirus; <span class="html-italic">P. gingivalis</span>, <span class="html-italic">Porphyromonas gingivalis</span>; SFB, segmented filamentous bacteria; TME, tumor microenvironment.</p>
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<p>A schematic presentation of the chronic inflammatory profile in RA patients with CC. The cells depicted in the diagram are found in both the inflamed joints and the TME of HPV-infected RA patients with CC. They express and secrete a variety of factors, which are mostly pro-inflammatory or immunosuppressive, creating a vicious loop of chronic inflammation. Moreover, infection of RA patients with HPV can further aggravate chronic inflammation and manifestations. It can also contribute to the enhanced progression of CIN to CC. Further explanations are given in the text. <span class="html-italic">Abbreviations</span>: Arg-1, arginase 1; BREG, B regulatory cells; CCL20, chemokine ligand 20; COX, cyclooxygenase; CSF, colony-stimulating factor; CTLA, cytotoxic T lymphocyte-associated protein; DC, dendritic cell; Foxp3, forkhead box P3; GM-CSF, granulocyte-macrophage growth factor; HPV, human papillomavirus; IDO, indoleamine 2,3-dioxygenase; IFN, interferon; IL, interleukin; iNOS, inducible nitric oxide synthase; LIF, leukemia inhibitory factor; MDSC, myeloid-derived suppressor cells; MMP, metalloproteinase; Mph, macrophage; Nets, netosis; Neu, neutrophil; NK, natural killer cell; NO, nitrogen oxide; PD-L1, programmed death-ligand-1; PGE2, prostaglandin E2; RANKL, receptor activator of NF-kB ligand; RANTES, regulated upon activation, normal T cell expressed and presumably secreted; ROS, reactive oxygen species; TGF, transforming growth factor; Th, T helper cell; TLR, toll-like receptor; TME, tumor microenvironment; TREG, T regulatory cell; VEGF, vascular endothelial growth factor.</p>
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<p>Simplified presentation of SPM biosynthesis, SPM receptors, and the process of inflammation resolution. (<b>A</b>) During the resolution phase of acute inflammation, SPMs (e.g., resolvins RvE1, 2, 3; RvD1-6) and maresins (MaR1,2) are biosynthesized from essential ω-3 PUFAs, including EPA and DHA. The main enzymes involved in the production of resolvins and maresins are CYP450 and LOX. There are several intermediates, such as 17/18-HpDHAs in the synthesis of resolvins and 14-HDHA in the synthesis of maresins by 12/15-LOXs. (<b>B</b>) SPMs trigger their pro-resolving signals via designated GPCRs expressed on various cells, mainly immune cells. (<b>C</b>) Physiologically, acute inflammation terminates by SPM-mediated resolution, which involves restriction of neutrophil tissue infiltration, counter-regulation of pro-inflammatory chemokines and cytokines, reduction of ROS and NLRP3 inflammasome generation, induction of apoptosis in active neutrophils and their subsequent efferocytosis by macrophages, accumulation of anti-inflammatory M2 macrophages, and other related processes. Ultimately, the resolution process leads to tissue healing and restoration of tissue homeostasis. Down arrow means “decrease”, up arrow means “increase”. Further explanations are given in the text. <span class="html-italic">Abbreviations</span>: GPCR, G protein-coupled receptor; EPA, eicosapentaenoic acid; HEPE, hydroxyeicosapentaenoic acid; HpDHA, hydroperoxydocosahexaenoic acid; HpEPE, hydroperoxyeicosapentaenoic acid; MAPK, mitogen-activated protein kinase; JAK-STAT, Janus kinase (JAK)-signal transducer and activator of transcription (STAT); LOX, lipoxygenase; Lymph, lymphocyte; Mph, macrophage; Neu, neutrophil; NK, natural killer cell; NF-κB, nuclear factor kappa-light-chain-enhancer of activated B cells; PUFA, polyunsaturated fatty acids; ROS, reactive oxygen species; SPMs, specialized pro-resolving molecules.</p>
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<p>Proposed therapeutic strategy to attenuate the manifestations of RA and CC and reduce CC risk in patients with RA by reversing chronic inflammation and correcting dysbiosis. We assume that failure to resolve chronic inflammation, as well as gut and vaginal dysbiosis, are key factors in the pathogenesis of RA and CC, aggravated manifestations, and increased risk of CC development in RA patients. These processes appear to mutually interact, creating a vicious cycle that maintains and worsens both RA and CC. Accordingly, the use of stable SPM receptor mimetics and agonists, such as BML-111, the anti-ChemR23 agonist antibody (resolvin E1 receptor), and dysbiosis correction have promising therapeutic potential for these conditions. Those treatments are intended to complement traditional treatments for RA and CC. Further explanations are given in the text. <span class="html-italic">Abbreviations</span>: HPV, human papillomavirus; SPMs, specialized pro-resolving molecules; RA, rheumatoid arthritis.</p>
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27 pages, 1675 KiB  
Review
Brain-Gut and Microbiota-Gut-Brain Communication in Type-2 Diabetes Linked Alzheimer’s Disease
by Yomna S. Momen, Jayshree Mishra and Narendra Kumar
Nutrients 2024, 16(15), 2558; https://doi.org/10.3390/nu16152558 - 3 Aug 2024
Viewed by 1260
Abstract
The gastrointestinal (GI) tract, home to the largest microbial population in the human body, plays a crucial role in overall health through various mechanisms. Recent advancements in research have revealed the potential implications of gut-brain and vice-versa communication mediated by gut-microbiota and their [...] Read more.
The gastrointestinal (GI) tract, home to the largest microbial population in the human body, plays a crucial role in overall health through various mechanisms. Recent advancements in research have revealed the potential implications of gut-brain and vice-versa communication mediated by gut-microbiota and their microbial products in various diseases including type-2 diabetes and Alzheimer’s disease (AD). AD is the most common type of dementia where most of cases are sporadic with no clearly identified cause. However, multiple factors are implicated in the progression of sporadic AD which can be classified as non-modifiable (e.g., genetic) and modifiable (e.g. Type-2 diabetes, diet etc.). Present review focusses on key players particularly the modifiable factors such as Type-2 diabetes (T2D) and diet and their implications in microbiota-gut-brain (MGB) and brain-gut (BG) communication and cognitive functions of healthy brain and their dysfunction in Alzheimer’s Disease. Special emphasis has been given on elucidation of the mechanistic aspects of the impact of diet on gut-microbiota and the implications of some of the gut-microbial products in T2D and AD pathology. For example, mechanistically, HFD induces gut dysbiosis with driven metabolites that in turn cause loss of integrity of intestinal barrier with concomitant colonic and systemic chronic low-grade inflammation, associated with obesity and T2D. HFD-induced obesity and T2D parallel neuroinflammation, deposition of Amyloid β (Aβ), and ultimately cognitive impairment. The review also provides a new perspective of the impact of diet on brain-gut and microbiota-gut-brain communication in terms of transcription factors as a commonly spoken language that may facilitates the interaction between gut and brain of obese diabetic patients who are at a higher risk of developing cognitive impairment and AD. Other commonality such as tyrosine kinase expression and functions maintaining intestinal integrity on one hand and the phagocytic clarence by migratory microglial functions in brain are also discussed. Lastly, the characterization of the key players future research that might shed lights on novel potential pharmacological target to impede AD progression are also discussed. Full article
(This article belongs to the Special Issue The Role of Probiotics on Gut Health)
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<p>High fat diet-induced Gut Dysbiosis and Leaky Gut are involved in AD Pathogenesis. Consumption of high fat diet causes gut dysbiosis in terms of predominance of pathogenic bacteria and the harmful metabolites which bind to receptors on the surface of intestinal epithelial cells and other cells, inducing deleterious cellular responses and ultimately loss of intestinal barrier integrity. As a result of leaky gut, the pathogenic bacteria and metabolites travel through the systemic circulation to the brain where they induce the microglia cells polarization, and eventually neuroinflammation. TLR: Toll like receptors, LPS: Lipopolysaccharide, TJPs: tight junction proteins, SCFAs: short chain fatty acids, IL-6: Interleukin-6, TNFα: Tumor necrosis factor-α.</p>
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<p>Perspective on HFD-dysregulated Transcription Factors Contribution in AD Progression. High fat diet induces gut dysbiosis. Upon binding to cell surface receptors, the gut dysbiosis-driven metabolites dysregulate downstream transcription factors. Those transcription factors regulate the expression of genes implicated in colonic inflammation, insulin resistance, type 2 diabetes, and eventually systemic low-grade inflammation that indirectly leads to Alzheimer’s disease progression. On the other hand, genes related to microglial cells metabolic reprogramming and cytoskeleton remodeling, as well as Amyloidβ production are dysregulated resulting in neuroinflammation ending with Alzheimer’s disease.</p>
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