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Search Results (210)

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13 pages, 2585 KiB  
Article
Effects of Aneurysmal Subarachnoid Hemorrhage in Patients Without In-Hospital Infection on FABP-I, LBP, and sCD-14
by Brigitta Orban, Diana Simon, Szabina Erdo-Bonyar, Timea Berki, Tihamer Molnar, Laszlo Zavori, Attila Schwarcz, Zoltan Peterfi and Peter Csecsei
Int. J. Mol. Sci. 2025, 26(2), 485; https://doi.org/10.3390/ijms26020485 - 8 Jan 2025
Viewed by 468
Abstract
Aneurysmal subarachnoid hemorrhage (aSAH) is a serious condition complicated by delayed cerebral ischemia (DCI), where inflammation plays a key role. Although altered gut permeability is noted in other conditions, its significance in aSAH remains unclear. Fatty acid-binding protein (FABP-I), lipopolysaccharide-binding protein (LBP), and [...] Read more.
Aneurysmal subarachnoid hemorrhage (aSAH) is a serious condition complicated by delayed cerebral ischemia (DCI), where inflammation plays a key role. Although altered gut permeability is noted in other conditions, its significance in aSAH remains unclear. Fatty acid-binding protein (FABP-I), lipopolysaccharide-binding protein (LBP), and soluble CD-14 (sCD-14) are established markers of barrier dysfunction. This study investigates gut permeability marker changes in early and late aSAH phases. The study included 177 aSAH patients and 100 controls. Serum samples were collected on days 1 (D1) and 9 (D9) after ictus. FABP-I, LBP, and sCD-14 levels were measured via ELISA, and clinical data were recorded. Outcomes were assessed using the 90-day modified Rankin scale (mRS 0–3 = favorable outcome). Serum FABP-I was significantly lower in aSAH patients (p < 0.05), while LBP and sCD-14 were higher (p < 0.001) compared to controls. FABP-I did not differ between outcome groups, but LBP and sCD-14 were significantly elevated in unfavorable outcomes (p < 0.001). These markers differed in patients without in-hospital infection, with higher levels noted in DCI patients during the later phase (p < 0.05). In aSAH patients without infection, differences in LBP and sCD-14 levels between outcome groups suggest potential endotoxin release from microbial systems, contributing to neuroinflammation and influencing outcomes. Full article
(This article belongs to the Special Issue Interplay Between the Human Microbiome and Diseases)
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<p>Serum level of FABP-I, LBP and sCD-14 in aSAH patients versus controls (<b>A</b>–<b>C</b>) and in different outcome groups (<b>D</b>–<b>F</b>). FABP-I, fatty acid-binding protein-intestinal, LBP, lipopolysaccharide-binding protein, D1, sampling time 24 h after ictus, D9, sampling time 9 days after ictus, fav, favorable (modified Rankin score 0–3) outcome, unfavor, unfavorable (modified Rankin score 4–6) outcome, ns, non-significant, * denotes <span class="html-italic">p</span> &lt; 0.05, *** denotes <span class="html-italic">p</span> &lt; 0.001, **** denotes <span class="html-italic">p</span> &lt; 0.0001, number of control subjects: 100, number of patients with favorable outcome: 94, number of patients with unfavorable outcome: 83.</p>
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<p>Serum level of FABP-I (<b>A</b>), LBP (<b>B</b>) and sCD-14 (<b>C</b>) in patients with and without delayed cerebral ischemia. DCI delayed cerebral ischemia, <span class="html-italic">+</span>, patients with DCI, −, patients without DCI, FABP-I, fatty acid-binding protein-intestinal, LBP, lipopolysaccharide-binding protein, ns, non-significant, * denotes <span class="html-italic">p</span> &lt; 0.05, ** denotes <span class="html-italic">p</span> &lt; 0.01, number of patients with DCI: 47, number of patients without DCI: 130.</p>
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<p>Serum levels of LBP and sCD-14 in aSAH patients without in-hospital infection according to 3-month outcome. The serum LBP level in the aSAH group without infection (<b>A</b>), the serum sCD-14 level in the aSAH group without infection (<b>B</b>). D1, sampling time 24 h after ictus, D9, sampling time 9 days after ictus, favor, favorable (modified Rankin score 0–3) outcome, unfavor, unfavorable (modified Rankin score 4–6) outcome, * denotes <span class="html-italic">p</span> &lt; 0.05, ** denotes <span class="html-italic">p</span> &lt; 0.01, *** denotes <span class="html-italic">p</span> &lt; 0.001, number of patients in each group, favorable outcome: <span class="html-italic">n</span> = 61, unfavorable outcome: <span class="html-italic">n</span> = 55.</p>
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<p>Heat map showing correlation matrix of FABP-I, LBP and sCD-14. In heatmap, red indicates positive, while blue indicates negative correlation. The darker the color, the stronger the correlation. The Spearman rank correlation test was used. A <span class="html-italic">p</span>-value &lt; 0.05 was accepted as significant. <span class="html-italic">p</span> &gt; 0.10 are presented in white squares. FABP-I, fatty acid-binding protein-intestinal, LBP, lipopolysaccharide-binding protein, D1, sampling time 24 h after ictus, D9, sampling time 9 days after ictus.</p>
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23 pages, 1946 KiB  
Review
Gut Microbiota, Bacterial Translocation, and Stroke: Current Knowledge and Future Directions
by Cristina Granados-Martinez, Nuria Alfageme-Lopez, Manuel Navarro-Oviedo, Carmen Nieto-Vaquero, Maria Isabel Cuartero, Blanca Diaz-Benito, Maria Angeles Moro, Ignacio Lizasoain, Macarena Hernandez-Jimenez and Jesus Miguel Pradillo
Biomedicines 2024, 12(12), 2781; https://doi.org/10.3390/biomedicines12122781 - 6 Dec 2024
Cited by 1 | Viewed by 926
Abstract
Stroke is one of the most devastating pathologies in terms of mortality, cause of dementia, major adult disability, and socioeconomic burden worldwide. Despite its severity, treatment options remain limited, with no pharmacological therapies available for hemorrhagic stroke (HS) and only fibrinolytic therapy or [...] Read more.
Stroke is one of the most devastating pathologies in terms of mortality, cause of dementia, major adult disability, and socioeconomic burden worldwide. Despite its severity, treatment options remain limited, with no pharmacological therapies available for hemorrhagic stroke (HS) and only fibrinolytic therapy or mechanical thrombectomy for ischemic stroke (IS). In the pathophysiology of stroke, after the acute phase, many patients develop systemic immunosuppression, which, combined with neurological dysfunction and hospital management, leads to the onset of stroke-associated infections (SAIs). These infections worsen prognosis and increase mortality. Recent evidence, particularly from experimental studies, has highlighted alterations in the microbiota–gut–brain axis (MGBA) following stroke, which ultimately disrupts the gut flora and increases intestinal permeability. These changes can result in bacterial translocation (BT) from the gut to sterile organs, further contributing to the development of SAIs. Given the novelty and significance of these processes, especially the role of BT in the development of SAIs, this review summarizes the latest advances in understanding these phenomena and discusses potential therapeutic strategies to mitigate them, ultimately reducing post-stroke complications and improving treatment outcomes. Full article
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<p>Schematic representation of the MGBA under two distinct conditions. Left: The primary pathways involved in the MGBA in a healthy state, illustrating the connections between the brain and gut through neuroendocrine pathways (ANS and ENS, including the vagus nerve, and the HPA axis), as well as the immune system. Right: Alterations in MGBA pathways following stroke. The increase in catecholamines and cortisol induces systemic immunosuppression. Stroke-induced overactivation of the HPA axis and the ANS/ENS systems leads to increased gastrointestinal permeability, dysbiosis, inflammation, and alterations in intestinal motility. Together, these factors contribute to the exacerbation of both peripheral and brain inflammatory processes, as well as an increased susceptibility to SAIs by promoting BT from the gut to sterile organs, thereby raising the risk of secondary infections.</p>
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<p>Potential therapeutic strategies to reduce GI dysbiosis, leaky gut, and BT after stroke.</p>
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26 pages, 2977 KiB  
Article
Therapeutic Efficacy of the Inositol D-Pinitol as a Multi-Faceted Disease Modifier in the 5×FAD Humanized Mouse Model of Alzheimer’s Amyloidosis
by Dina Medina-Vera, Antonio J. López-Gambero, Julia Verheul-Campos, Juan A. Navarro, Laura Morelli, Pablo Galeano, Juan Suárez, Carlos Sanjuan, Beatriz Pacheco-Sánchez, Patricia Rivera, Francisco J. Pavon-Morón, Cristina Rosell-Valle and Fernando Rodríguez de Fonseca
Nutrients 2024, 16(23), 4186; https://doi.org/10.3390/nu16234186 - 4 Dec 2024
Viewed by 1226
Abstract
Background/Objectives: Alzheimer’s disease (AD), a leading cause of dementia, lacks effective long-term treatments. Current therapies offer temporary relief or fail to halt its progression and are often inaccessible due to cost. AD involves multiple pathological processes, including amyloid beta (Aβ) deposition, insulin resistance, [...] Read more.
Background/Objectives: Alzheimer’s disease (AD), a leading cause of dementia, lacks effective long-term treatments. Current therapies offer temporary relief or fail to halt its progression and are often inaccessible due to cost. AD involves multiple pathological processes, including amyloid beta (Aβ) deposition, insulin resistance, tau protein hyperphosphorylation, and systemic inflammation accelerated by gut microbiota dysbiosis originating from a leaky gut. Given this context, exploring alternative therapeutic interventions capable of addressing the multifaceted components of AD etiology is essential. Methods: This study suggests D-Pinitol (DPIN) as a potential treatment modifier for AD. DPIN, derived from carob pods, demonstrates insulin-sensitizing, tau hyperphosphorylation inhibition, and antioxidant properties. To test this hypothesis, we studied whether chronic oral administration of DPIN (200 mg/kg/day) could reverse the AD-like disease progression in the 5×FAD mice. Results: Results showed that treatment of 5×FAD mice with DPIN improved cognition, reduced hippocampal Aβ and hyperphosphorylated tau levels, increased insulin-degrading enzyme (IDE) expression, enhanced pro-cognitive hormone circulation (such as ghrelin and leptin), and normalized the PI3K/Akt insulin pathway. This enhancement may be mediated through the modulation of cyclin-dependent kinase 5 (CDK5). DPIN also protected the gut barrier and microbiota, reducing the pro-inflammatory impact of the leaky gut observed in 5×FAD mice. DPIN reduced bacterial lipopolysaccharide (LPS) and LPS-associated inflammation, as well as restored intestinal proteins such as Claudin-3. This effect was associated with a modulation of gut microbiota towards a more balanced bacterial composition. Conclusions: These findings underscore DPIN’s promise in mitigating cognitive decline in the early AD stages, positioning it as a potential disease modifier. Full article
(This article belongs to the Section Lipids)
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Graphical abstract

Graphical abstract
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<p>Anhedonic and anxiety-like behavior after 18 weeks of D-Pinitol treatment in 5×FAD mice. (<b>A</b>) Experimental procedure where mice were supplemented with D-Pinitol (DPIN, 200 mg/kg/day) ad libitum in their drinking water for 18 weeks. All animals were about 14 weeks of age (3.5 months old) at the beginning of the experiment. Experimental groups: non-transgenic (Non-Tg-DPIN; n = 16; 7 males; 9 females) and transgenic 5×FAD (5×FAD-DPIN; n = 17; 10 males; 7 females) mice. Control groups of both genotypes: non-transgenic (Non-Tg-CTR; n = 16; 7 males; 9 females), and 5×FAD transgenic mice (5×FAD-CTR; n = 14; 7 males; 7 females) received water as a vehicle solution. Animal control weight (CW) was recorded at 3.5–5.5–6.5–7.5 months of age). Behavioral tests were performed at baseline point (3.5 months old) and after 16 weeks with DPIN treatment (8 month old): sucrose preference test (SPT) and elevated plus maze (EPM). The Morris water maze (MWM) behavioral test began at 7.5 months of age and was finalized at 8 months of age. The animals were sacrificed at 32 weeks of age (8 months) and tissue samples were rapidly removed. (<b>B</b>) Body weight in grams (g). Two-way ANOVA test: (*) <span class="html-italic">p</span>&lt; 0.05 genotype effect; (#) <span class="html-italic">p</span>&lt; 0.05 age effect. (<b>C</b>) Sucrose preference test (%) at the baseline point and after 18 weeks of DPIN treatment. Dashed lines represent the criterion for anhedonia ≤ 65%. Two-way ANOVA and Tukey’s test: (##) <span class="html-italic">p</span> &lt; 0.01 between 5×FAD (5×FAD-CTR and 5×FAD-DPIN) compared to Non-Tg mice (Non-Tg-CTR and Non-Tg-DPIN) at the baseline point. (<b>D</b>) Time spent in seconds (s) in the open arms at the baseline point and after 18 weeks of DPIN treatment in the EPM. Two-way ANOVA and Tukey’s test: (##) <span class="html-italic">p</span> &lt; 0.01 between 5×FAD (5×FAD-CTR and 5×FAD-DPIN) compared to Non-Tg mice (Non-Tg-CTR and Non-Tg-DPIN) at the baseline point and after 18 weeks of DPIN. (<b>E</b>) Total distance moved in centimeters (cm) at the baseline point and after 18 weeks of DPIN treatment in the EPM test. Results are shown as the mean ± SEM. Two-way ANOVA and Tukey’s test from (<b>C</b>–<b>E</b>): (*) <span class="html-italic">p</span> &lt; 0.05 and (**) <span class="html-italic">p</span> &lt; 0.01 in the 5×FAD mice after 18 weeks of DPIN treatment.</p>
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<p>Assessment of cognitive function by Morris water maze after 18 weeks of D-Pinitol treatment. Data is presented as the mean ± SEM. Two-way ANOVA + Tukey’s test for multiple comparisons were performed. (<b>A</b>) Path length in centimeters (cm) (* <span class="html-italic">p</span> &lt; 0.05) during the habituation training. (<b>B</b>) During the visual training (2 days, visible platform; 4 trials/day), all experimental groups diminished the escape latency (s) on the second day (# <span class="html-italic">p</span> &lt; 0.05 day 2 vs. day 1). (<b>C</b>) Non-Tg-DPIN and 5×FAD-DPIN showed a reduced cumulative distance (cm) to reach the platform on the second training day (* <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01). (<b>D</b>) On acquisition training, each subject received six trials per acquisition day (4 days, hidden platform; 6 trials/day). The escape latency (s) was decreased on the last and the fourth training day (* <span class="html-italic">p</span> &lt; 0.05), (<b>E</b>) being more significant in the Non-Tg-DPIN experimental group (* <span class="html-italic">p</span> &lt; 0.05). (<b>F</b>) The cumulative distance (cm) to reach the hidden platform was also evaluated and showed a similar profile to the escape latency outcomes on acquisition training. (<b>G</b>) On memory retention test 1 (without platform; 1 trial/day), all animals demonstrated similar measures of time (s) spent searching the target quadrant (Q1) (# <span class="html-italic">p</span> &lt; 0.05 Q1 vs. the other quadrants). (<b>H</b>) After 48 h, each subject received six trials for one day on the reversal spatial learning day (1 day, hidden platform; 6 trials/day). 5×FAD-DPIN reached the new hidden platform position significantly faster (s) than 5×FAD-CTR (* <span class="html-italic">p</span> &lt; 0.05) and (<b>I</b>) with less distance traveled (cm) (* <span class="html-italic">p</span> &lt; 0.05). (<b>J</b>) On memory retention test 2, 5×FAD-CTR exhibited impaired long-term spatial memory as measured by less time spent (s) in the new position of the platform (Q3) and persisted for a longer period on the Q1 position that they learned on the acquisition training compared to Non-Tg-CTR (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01). (<b>K</b>,<b>L</b>) shows a graphical representation of the path traveled by each group during the first and second memory retention tests.</p>
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<p>Regulation of hormones related to insulin and metabolic health after 18 weeks of D-Pinitol treatment. Plasma levels (pg/mL) of (<b>A</b>) insulin, (<b>B</b>) glucagon, (<b>C</b>) insulin/glucagon ratio, (<b>D</b>) plasminogen activator inhibitor-1 (PAI-1), (<b>E</b>) leptin, and (<b>F</b>) ghrelin. Histograms represent mean ± SEM (n = 10). Two-way ANOVA and Tukey’s test for multiple comparisons were performed: (*) <span class="html-italic">p</span> &lt; 0.05, (**) <span class="html-italic">p</span> &lt; 0.01, and (***) <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Activation of the hippocampal PI3K/Akt pathway after 18 weeks of D-Pinitol treatment. Western blot analysis of the phosphorylation status of the p85 regulatory domain of (<b>A</b>) the phosphatidylinositol 3 kinase (p85-PI3K) phosphorylation at tyrosine 607, (<b>B</b>) and the quantity of total p85-PI3K, (<b>C</b>) protein Kinase B (Akt) phosphorylation on serine 473, (<b>D</b>) and the amount of total Akt, (<b>E</b>) glycogen synthase kinase 3β (GSK-3β) phosphorylation at serine 9, (<b>F</b>) and the amount of total GSK-3β, (<b>G</b>) cyclin-dependent kinase 5 (CDK5) subunits p25 (<b>H</b>) and p35, (<b>I</b>) and the total quantity of CDK5 on Non-Tg and 5×FAD with (DPIN) and without (controls = CTR) D-Pinitol treatment. (<b>J</b>) The blots represent all bands. Molecular weights (MWs) are expressed in kilodaltons (kDa). The corresponding expression of γ-Adaptin is shown as a loading control per lane. All samples were obtained simultaneously and processed in parallel. Histograms represent mean ± SEM (n = 4). Two-way ANOVA and Tukey’s test for multiple comparisons were performed: (*) <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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<p>Amyloid beta clearance and tau dephosphorylation in the hippocampus of 5×FAD mice after 18 weeks of D-Pinitol treatment. Western blot analysis of (<b>A</b>) tau [AT8] phosphorylation on serine 202 and threonine 205, (<b>B</b>) tau [AT100] phosphorylation on threonine 212 and serine 214, (<b>C</b>) the total amount of tau, and (<b>D</b>) insulin-degrading enzyme (IDE) on Non-Tg and 5×FAD with (DPIN) and without (controls = CTR) D-Pinitol treatment. (<b>E</b>) The blots represent all bands. Molecular weights (MW) are expressed in kilodaltons (kDa). The corresponding expression of γ-Adaptin is shown as a loading control per lane. All samples were obtained simultaneously and processed in parallel. Histograms (<b>A</b>–<b>D</b>) represent mean ± SEM (n = 4). (<b>F</b>,<b>H</b>) Images correspond to representative immunostaining of Aβ 1-40 (Aβ 1-40) and Aβ 1-42 (Aβ 1-42) densitometry in the hippocampus of Non-Tg and 5×FAD controls (CTR) and after 18 weeks of continuous drinking treatment with D-Pinitol (DPIN). Scale bar: 100 µm. Histograms in (<b>G</b>,<b>I</b>) represent the mean ± SEM of the number of Aβ from all samples per group (n = 8). Two-way ANOVA and Tukey’s test for multiple comparisons were performed: (*) <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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<p>Effects of D-Pinitol treatment on proinflammatory cytokine levels in plasma and small intestine. mRNA expression (in relative units) in the small intestine of (<b>A</b>) Claudin 3, (<b>B</b>) occludin, and (<b>C</b>) Toll-like receptor 4 (TLR4). Graphs (<b>D</b>–<b>G</b>) correspond to plasma levels (pg/mL) of (<b>D</b>) LPS plasma level (pg/mL) and the pro-inflammatory cytokines (<b>E</b>) Interleukin 5 (IL-5), (<b>F</b>) Interleukin 6 (IL-6), (<b>G</b>) Keratinocyte chemoattractant (KC)/human growth-regulated oncogene (GRO), and (<b>H</b>) Tumor necrosis factor alpha (TNF-α). Histograms represent mean ± SEM (n = 7) in the groups Non-Tg and 5×FAD with (DPIN) and without (controls = CTR) D-Pinitol treatment. Two-way ANOVA and Tukey’s test for multiple comparisons were performed: (*) <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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<p>Differences in fecal microbiota by genotype and D-Pinitol treatment in Alzheimer’s transgenic and Non-Tg mice. (<b>A</b>) Taxonomic compositions obtained from the analysis of DNA sequences from fecal microbiota samples using QIIME2 (<a href="https://qiime2.org/" target="_blank">https://qiime2.org/</a>, accessed on 1 January 2024) were compared at the family level in terms of relative frequency (%). The sequences were grouped into operational taxonomic units (OTUs) using a 97% similarity threshold. Significant differences for ‘Genotype × Treatment’ variables have been detected mostly in seven families: (<b>B</b>) Prevotellaceae, (<b>C</b>) Eggerthellaceae, (<b>D</b>) Streptococcaceae, (<b>E</b>) Marinifilaceae, (<b>F</b>) Lachnospiraceae, (<b>G</b>) Acholeplasmataceae, and (<b>H</b>) Enterococcaceae. Histograms represent relative abundance (%) in the groups Non-Tg and 5×FAD with (DPIN) and without (controls = CTR) D-Pinitol treatment. Statistical inference was performed using the Kruskal–Wallis test and Mann–Whitney U for each OTU, allowing for comparisons and identification of significant differences between groups: (*) <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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14 pages, 935 KiB  
Brief Report
The Interplay Between Depression, Probiotics, Diet, Immunometabolic Health, the Gut, and the Liver—A Secondary Analysis of the Pro-Demet Randomized Clinical Trial
by Oliwia Gawlik-Kotelnicka, Jakub Rogalski, Karolina H. Czarnecka-Chrebelska, Jacek Burzyński, Paulina Jakubowska, Anna Skowrońska and Dominik Strzelecki
Nutrients 2024, 16(23), 4024; https://doi.org/10.3390/nu16234024 - 24 Nov 2024
Viewed by 1301
Abstract
(1) Background: Depression, metabolic alternations, and liver diseases are highly comorbid. Studies have shown that probiotics might be helpful in the treatment of the above-mentioned states. The aim of this secondary analysis was to search for possible predictors of probiotics’ efficacy on liver-related [...] Read more.
(1) Background: Depression, metabolic alternations, and liver diseases are highly comorbid. Studies have shown that probiotics might be helpful in the treatment of the above-mentioned states. The aim of this secondary analysis was to search for possible predictors of probiotics’ efficacy on liver-related outcome measures. (2) Methods: Data from 92 subjects from a randomized clinical trial on the effect of probiotics on depression were analyzed. The shift in liver steatosis and fibrosis indices was assessed in the context of baseline immunometabolic, psychometric, dietary, and intestinal permeability factors. Correlation analysis and linear regression models were used. (3) Results: A total of 30% of the variance of the improvement in the score of the aspartate transferase to platelet ratio index was explained by probiotic use, higher pre-intervention triglycerides, cholesterol, C-reactive protein levels, increased cereal intake, and a lower consumption of sweets. Then, the model of the change in alanine transferase indicated that probiotics were efficient when used by subjects with higher basal levels of intestinal permeability markers. (4) Conclusions: Probiotics being used along with a healthy diet may provide additional benefits, such as decreased cardiovascular risk, for patients with measures consistent with the immunometabolic form of depression. Probiotic augmentation may be useful for liver protection among subjects with a suspected “leaky gut” syndrome. ClinicalTrials.gov: NCT04756544. Full article
(This article belongs to the Special Issue Metabolic Features and Nutritional Interventions in Chronic Diseases)
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<p>Forest plots of the multiple linear regression models with interactions, including the type of intervention (probiotic vs. placebo). (<b>A</b>) For the changes in alanine aminotransferase (ALT); (<b>B</b>) for the changes in aspartate aminotransferase (AST)-to-platelets ratio index (APRI). * means interaction. Abbreviations: bSCFAS = blood short-chain fatty acids; CRP = C-reactive protein; D-DASS = Depression subscale of Depression, Anxiety, and Stress Scale; I-FABP = intestinal fatty-acid binding protein; TG = triglycerides.</p>
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41 pages, 2830 KiB  
Review
Unraveling the Role of the Human Gut Microbiome in Health and Diseases
by Mohamad Khalil, Agostino Di Ciaula, Laura Mahdi, Nour Jaber, Domenica Maria Di Palo, Annarita Graziani, Gyorgy Baffy and Piero Portincasa
Microorganisms 2024, 12(11), 2333; https://doi.org/10.3390/microorganisms12112333 - 15 Nov 2024
Cited by 1 | Viewed by 4153
Abstract
The human gut is a complex ecosystem that supports billions of living species, including bacteria, viruses, archaea, phages, fungi, and unicellular eukaryotes. Bacteria give genes and enzymes for microbial and host-produced compounds, establishing a symbiotic link between the external environment and the host [...] Read more.
The human gut is a complex ecosystem that supports billions of living species, including bacteria, viruses, archaea, phages, fungi, and unicellular eukaryotes. Bacteria give genes and enzymes for microbial and host-produced compounds, establishing a symbiotic link between the external environment and the host at both the gut and systemic levels. The gut microbiome, which is primarily made up of commensal bacteria, is critical for maintaining the healthy host’s immune system, aiding digestion, synthesizing essential nutrients, and protecting against pathogenic bacteria, as well as influencing endocrine, neural, humoral, and immunological functions and metabolic pathways. Qualitative, quantitative, and/or topographic shifts can alter the gut microbiome, resulting in dysbiosis and microbial dysfunction, which can contribute to a variety of noncommunicable illnesses, including hypertension, cardiovascular disease, obesity, diabetes, inflammatory bowel disease, cancer, and irritable bowel syndrome. While most evidence to date is observational and does not establish direct causation, ongoing clinical trials and advanced genomic techniques are steadily enhancing our understanding of these intricate interactions. This review will explore key aspects of the relationship between gut microbiota, eubiosis, and dysbiosis in human health and disease, highlighting emerging strategies for microbiome engineering as potential therapeutic approaches for various conditions. Full article
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<p>Density, type, and distribution of microbiome in the human gastrointestinal tract. The prevalent phyla of the human gut are depicted, along with the most represented genera which populate different gut segments. A vast majority of commensal bacteria are found in the colon. A lower bacterial population is found in the stomach and small intestine. Activation of specific gut–organ/apparatus axes in health is indicated. Legend: CFU, colony forming unit, ↑: increased.</p>
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<p>Metabolites are produced during the colonic fermentation of carbohydrates and proteins. Legend: CO<sub>2</sub>, carbon dioxide; CH<sub>4</sub>, methane; H<sub>2</sub>, hydrogen; NO, nitric oxide; SCFAs, short-chain fatty acids. Created with <a href="http://Biorender.com" target="_blank">Biorender.com</a>.</p>
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<p>Effects of microbiome metabolites on the immune system and different targets. Food and nutrients encounter the microbiome highly represented in the colon. The microbiota metabolites serve as the nutrients for some bacteria and can shape the composition of the gut microbiome in health (eubiosis) and disease (dysbiosis). Bacterial cross-feeding (C-F) is when one bacterium is taken up by or exchanges its bacterial products with another microbe (e.g., lactate). Bacterial metabolites can act in different ways, i.e., by direct local effect (DLE) on either enterocytes and/or immune cells in the lamina propria. Such local effects can activate further systemic pathways. Microbiome metabolites can be absorbed and transported to remote organs to exert direct systemic effects (DSEs) or elicit indirect systemic effects (ISEs). Metabolites can also induce the host to release antibacterial molecules into the gut lumen. Enterohepatic circulation (EHC) is another example of the biotransformation of secreted primary bile acids to secondary bile acids by the resident colonic microbiome. Created with <a href="http://Biorender.com" target="_blank">Biorender.com</a>.</p>
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<p>Principal modulatory effects of gut microbiome on host metabolism. The pleiotropic effect of microbiome-derived metabolites is evident on gluco-lipid and protein metabolisms, satiety, adipocyte functions (both white and brown adipose tissues involved in energy storage and non-shivering thermogenesis, respectively), muscle and heart function, and insulin sensitivity, among others. Short-chain fatty acids (SCFAs) such as acetate can inhibit lipolysis and increase adipogenesis. This effect is associated with the improved capacity of lipid storage of adipose tissues. SCFAs also influence pancreatic β-cell function and insulin secretion via the receptor GPR43, as well as lipid, carbohydrate, and protein metabolism of skeletal muscle through G protein-coupled receptors GPR41 and GPR43 and hydroxycarboxylic acid receptors (HDACs). The effect of SCFAs is seen also in the heart as an energy source and decreases heart rate, cardiac contractility, and blood pressure. Similarly, in the liver, SCFAs are an energy source; propionate is used for the synthesis of glucose and acetate can be used as substrates to synthesize cholesterol and long-chain fatty acids. Energy expenditure increases and hepatic steatosis decreases with SCFAs since hepatic lipogenesis is switched to hepatic beta-oxidation, a mechanism that contributes to protect against high-fat diet-induced obesity and metabolic dysfunction-associated steatotic liver disease (MASLD) [<a href="#B77-microorganisms-12-02333" class="html-bibr">77</a>,<a href="#B241-microorganisms-12-02333" class="html-bibr">241</a>]. Bile acids (BAs) in the terminal ileum target the membrane-associated G protein-coupled bile acid receptor 1 (GPBAR-1) with effects on the release of gut hormones such as glucagon-like peptide-1 (GLP-1) and peptide YY (PYY), involved in the regulation of appetite and gut motility. The interaction of BAs with the nuclear farnesoid X receptor (FXR) increases liver glycogen synthesis and insulin sensitivity, pancreas insulin secretion, and increased energy metabolism in the liver, brown adipose tissue, and muscles. Also in the liver, BAs contribute to regulating triglyceride metabolism, very low-density lipoprotein, and lipogenesis [<a href="#B57-microorganisms-12-02333" class="html-bibr">57</a>,<a href="#B83-microorganisms-12-02333" class="html-bibr">83</a>,<a href="#B143-microorganisms-12-02333" class="html-bibr">143</a>]. BCAAs contribute to protein synthesis, glucose and lipid metabolism, insulin resistance, hepatocyte proliferation, and thermogenesis of BAT. Other microbiome-derived metabolites are TMAO, tryptophan, and indole derivatives which, at different levels, are involved in energy and nutrient metabolism. If dysbiosis occurs, translocation of harmful metabolites such as lipopolysaccharides (LPSs) can occur across the leaky gut with further negative systemic effects. Legend: BAs, bile acids; BCAAs, branched-chain amino acids; GLP-1, glucagon-like peptide-1; LPSs, lipopolysaccharides; PYY, peptide YY; SCFAs, short-chain fatty acids; TMA, trimethyl amine; TMAO, trimethylamine-N-oxide [<a href="#B71-microorganisms-12-02333" class="html-bibr">71</a>]. Created with <a href="http://Biorender.com" target="_blank">Biorender.com</a>.</p>
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<p>Crosstalk between microbiome and gut barrier. In the gut lumen, the complex morpho-functional multilayer gut barrier consists of several levels labeled on the right part of the figure. In health, microbes populate the central mucin layer, i.e., glycoproteins secreted by the epithelial Goblet cells. In eubiosis, microbes never come in close contact with the enterocytes. The functional–chemical layer is a combination of gut peristalsis and secretions of gastric acid, pancreatic juice, liver bile, antimicrobial proteins produced by the Paneth cells, and bacteria-specific immunoglobulin A (IgA) secreted by mature IgA-secreting plasma cells. The mucosa layer consists of epithelial specialized cells (here we show the enterocytes, the Goblet cell, and the Paneth cell). Intestinal epithelial cells present the pattern-recognition receptors (PRRs) able to sense the pathogen-associated molecular patterns (PAMPs) of microorganisms in the lumen. The lamina propria hosts the muscularis mucosa consisting of smooth muscle cells and the immunological layer, a complex and highly responsive set of macrophages, mast cells, and T- and B-lymphocytes which can be activated by dendritic cells presenting microbial derivatives and leading to the maturation of IgA-secreting plasma cells, which will secrete bacterial-specific IgA permeating the enterocyte by transcytosis. The gut vascular layer includes the endothelial cells. This level prevents the translocation of bacteria and/or microbial components across the extracellular and the intestinal epithelial barrier. A further layer is the liver barrier where resident macrophages (Kupffer cells) keep the liver free of bacteria. The set of structures that control the intercellular permeability between enterocytes includes the tight junctions, i.e., junctional adhesion molecules (JAMs, Claudin, occludin), the adherents junction, and the desmosome from the brush border to the basolateral membrane [<a href="#B245-microorganisms-12-02333" class="html-bibr">245</a>]. SCFAs, bile acids, and indole derivatives can enhance the physical barrier via increasing tight junction proteins. SCFAs can cross the barrier and interact with several targets such as histone deacetylases (HDACs) and G protein-coupled receptors (GPRs). Indole derivatives can interact with the aryl hydrocarbon receptors (AhRs) and can also protect the tight junction machinery. Bile acids can cross the enterocytes and produce effects on the nuclear farnesoid X receptor and the membrane-associated G protein-coupled bile acid receptor 1 (GPBAR-1). All such effects contribute to maintaining the immunological response in tune with the gut luminal events and can lead to the release of anti-inflammatory cytokines such as IL-10 and IL-22. In the presence of disease, (events are depicted on the right side of the slide as dysbiosis) there is closer contact between the microbiota and the enterocytes, followed by disruption of the junction system and translocation of lipopolysaccharides and/or bacteria. Thus, translocation triggers the activation of immune cells and leads to the production of pro-inflammatory cytokines which initiate the vicious cycle acting on local epithelial cells to worsen the physical barrier. Extraintestinal organs can be affected by the leaky gut condition, especially in the chronic state. Adapted from [<a href="#B49-microorganisms-12-02333" class="html-bibr">49</a>]. Created with <a href="http://Biorender.com" target="_blank">Biorender.com</a>.</p>
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<p>Potential clinical consequences of gut dysbiosis. With dysbiosis, the classical axes originating from the gut microbiota (green boxes) can be disrupted at various levels (red/orange boxes) and will contribute to the onset/perpetuation of disease. Local (gut) consequences are also shown. Abbreviations: CRC, colorectal cancer; CVD, cardiovascular disease; HCC, hepatocellular carcinoma; IBD, inflammatory bowel disease; IBS, irritable bowel disease; MASH, metabolic dysfunction-associated steatohepatitis; MASLD, metabolic dysfunction-associated steatotic liver disease. Created with <a href="https://smart.servier.com/" target="_blank">https://smart.servier.com/</a>.</p>
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21 pages, 1815 KiB  
Review
Physical Exercise and the Gut Microbiome: A Bidirectional Relationship Influencing Health and Performance
by Sanish Varghese, Shrinidhi Rao, Aadam Khattak, Fahad Zamir and Ali Chaari
Nutrients 2024, 16(21), 3663; https://doi.org/10.3390/nu16213663 - 28 Oct 2024
Cited by 1 | Viewed by 4963
Abstract
Background/Objectives: The human gut microbiome is a complex ecosystem of microorganisms that can influence our health and exercise habits. On the other hand, physical exercise can also impact our microbiome, affecting our health. Our narrative review examines the bidirectional relationship between physical activity [...] Read more.
Background/Objectives: The human gut microbiome is a complex ecosystem of microorganisms that can influence our health and exercise habits. On the other hand, physical exercise can also impact our microbiome, affecting our health. Our narrative review examines the bidirectional relationship between physical activity and the gut microbiome, as well as the potential for targeted probiotic regimens to enhance sports performance. Methods: We conducted a comprehensive literature review to select articles published up till January 2024 on the topics of physical exercise, sports, probiotics, and gut microbiota from major scientific databases, incorporating over 100 studies. Results: We found that the impact of physical activity on the gut microbiome varies with the type and intensity of exercise. Moderate exercise promotes a healthy immune system, while high-intensity exercise for a long duration can cause a leaky gut and consequent systemic inflammation, which may disrupt the microbial balance. Combining aerobic and resistance training significantly affects bacterial diversity, linked to a lower prevalence of chronic metabolic disorders. Furthermore, exercise enhances gut microbiome diversity, increases SCFA production, improves nutrient utilization, and modulates neural and hormonal pathways, improving gut barrier integrity. Our findings also showed probiotic supplementation is associated with decreased inflammation, enhanced sports performance, and fewer gastrointestinal disturbances, suggesting that the relationship between the gut microbiome and physical activity is mutually influential. Conclusions: The bidirectional relationship between physical activity and the gut microbiome is exemplified by how exercise can promote beneficial bacteria while a healthy gut microbiome can potentially enhance exercise ability through various mechanisms. These findings underscore the importance of adding potential tailored exercise regimens and probiotic supplementation that consider individual microbiome profiles into exercise programs. Full article
(This article belongs to the Section Prebiotics and Probiotics)
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<p>Effects of physical-activity-induced changes in the gastrointestinal microbiome.</p>
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<p>Effects of probiotics on athletic health and performance.</p>
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<p>Mechanisms underlying the mutual relationship between physical activity and the gut microbiome.</p>
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23 pages, 4405 KiB  
Article
Beneficial Effects of Ginger Root Extract on Pain Behaviors, Inflammation, and Mitochondrial Function in the Colon and Different Brain Regions of Male and Female Neuropathic Rats: A Gut–Brain Axis Study
by Julianna Maria Santos, Hemalata Deshmukh, Moamen M. Elmassry, Vadim Yakhnitsa, Guangchen Ji, Takaki Kiritoshi, Peyton Presto, Nico Antenucci, Xiaobo Liu, Volker Neugebauer and Chwan-Li Shen
Nutrients 2024, 16(20), 3563; https://doi.org/10.3390/nu16203563 - 21 Oct 2024
Cited by 1 | Viewed by 1770
Abstract
Background: Neuroinflammation and mitochondrial dysfunction have been implicated in the progression of neuropathic pain (NP) but can be mitigated by supplementation with gingerol-enriched ginger (GEG). However, the exact benefits of GEG for each sex in treating neuroinflammation and mitochondrial homeostasis in different brain [...] Read more.
Background: Neuroinflammation and mitochondrial dysfunction have been implicated in the progression of neuropathic pain (NP) but can be mitigated by supplementation with gingerol-enriched ginger (GEG). However, the exact benefits of GEG for each sex in treating neuroinflammation and mitochondrial homeostasis in different brain regions and the colon remain to be determined. Objective: Evaluate the effects of GEG on emotional/affective pain and spontaneous pain behaviors, neuroinflammation, as well as mitochondria homeostasis in the amygdala, frontal cortex, hippocampus, and colon of male and female rats in the spinal nerve ligation (SNL) NP model. Methods: One hundred rats (fifty males and fifty females) were randomly assigned to five groups: sham + vehicle, SNL + vehicle, and SNL with three different GEG doses (200, 400, and 600 mg/kg BW) for 5 weeks. A rat grimace scale and vocalizations were used to assess spontaneous and emotional/affective pain behaviors, respectively. mRNA gene and protein expression levels for tight junction protein, neuroinflammation, mitochondria homeostasis, and oxidative stress were measured in the amygdala, frontal cortex, hippocampus, and colon using qRT-PCR and Western blot (colon). Results: GEG supplementation mitigated spontaneous pain in both male and female rats with NP while decreasing emotional/affective responses only in male NP rats. GEG supplementation increased intestinal integrity (claudin 3) and suppressed neuroinflammation [glial activation (GFAP, CD11b, IBA1) and inflammation (TNFα, NFκB, IL1β)] in the selected brain regions and colon of male and female NP rats. GEG supplementation improved mitochondrial homeostasis [increased biogenesis (TFAM, PGC1α), increased fission (FIS, DRP1), decreased fusion (MFN2, MFN1) and mitophagy (PINK1), and increased Complex III] in the selected brain regions and colon in both sexes. Some GEG dose–response effects in gene expression were observed in NP rats of both sexes. Conclusions: GEG supplementation decreased emotional/affective pain behaviors of males and females via improving gut integrity, suppressing neuroinflammation, and improving mitochondrial homeostasis in the amygdala, frontal cortex, hippocampus, and colon in both male and female SNL rats in an NP model, implicating the gut–brain axis in NP. Sex differences observed in the vocalizations assay may suggest different mechanisms of evoked NP responses in females. Full article
(This article belongs to the Section Nutrition and Public Health)
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<p>Effects of GEG on spontaneous pain (RGS score) in the male rats (<b>A</b>) and female rats (<b>B</b>). Data are expressed as mean ± SEM and were analyzed by one-way ANOVA followed by Bonferroni multiple comparisons test, <span class="html-italic">n</span> = 9 per group. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 for SNL-V vs. Sham-V group. <sup>+</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>++</sup> <span class="html-italic">p</span> &lt; 0.01, <sup>+++</sup> <span class="html-italic">p</span> &lt; 0.001 SNL-GEG groups vs. SNL-V group.</p>
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<p>Effects of GEG on emotional pain responses (duration of vocalizations) in the male rats (<b>A</b>) and female rats (<b>B</b>). Data are expressed as mean ± SEM and were analyzed by one-way ANOVA followed by Bonferroni multiple comparisons test. <span class="html-italic">n</span> = 5–7 per group. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 for SNL-V vs. Sham-V group. <sup>+</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>++</sup> <span class="html-italic">p</span> &lt; 0.01, <sup>+++</sup> <span class="html-italic">p</span> &lt; 0.001 for other groups vs. SNL-V group.</p>
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<p>Effects of GEG on plasma LBP in the male rats (<b>A</b>) and female rats (<b>B</b>) assessed by ELISA. Data are expressed as mean ± SEM and were analyzed by one-way ANOVA followed by Bonferroni multiple comparisons test. <span class="html-italic">n</span> = 4–6 per group. * <span class="html-italic">p</span> &lt; 0.05 compared with Sham-V group. <sup>+</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>++</sup> <span class="html-italic">p</span> &lt; 0.01 compared with SNL-V group.</p>
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<p>Effects of GEG on claudin 3 gene expression levels in amygdala, frontal cortex, hippocampus, and colon of male rats (<b>A</b>) and female rats (<b>B</b>) and protein expression levels in colon of male and female rats (<b>C</b>). For gene expression, data are expressed as mean ± SEM and were analyzed by one-way ANOVA followed by Tukey’s test, <span class="html-italic">n</span> = 7–9 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, **** <span class="html-italic">p</span> &lt; 0.0001 for SNL-V vs. Sham-V group, and other groups vs. SNL-V group. For protein expression, data are expressed as mean ± SEM and were analyzed by one-way ANOVA followed by Tukey’s multiple comparisons test, <span class="html-italic">n</span> = 7–9 per group. * <span class="html-italic">p</span> &lt; 0.05 compared with Sham-V group. <sup>+</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>++</sup> <span class="html-italic">p</span> &lt; 0.01 compared with SNL-V group.</p>
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<p>Effects of GEG on the neuroinflammation-associated gene expression levels in amygdala, frontal cortex, hippocampus, and colon of male rats (<b>A</b>) and protein expression levels in colon of male rats (<b>B</b>). For gene expression, data are expressed as mean ± SEM and were analyzed by one-way ANOVA followed by Tukey’s test, <span class="html-italic">n</span> = 7–9 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, **** <span class="html-italic">p</span> &lt; 0.0001 for SNL-V vs. Sham-V group, and other groups vs. SNL-V group. For protein expression, data are expressed as mean ± SEM and were analyzed by one-way ANOVA followed by Tukey’s multiple comparisons test, <span class="html-italic">n</span> = 7–9 per group. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 compared with Sham-V group. <sup>+</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>++</sup> <span class="html-italic">p</span> &lt; 0.01, <sup>+++</sup> <span class="html-italic">p</span> &lt; 0.001 compared with SNL-V group.</p>
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<p>Effects of GEG on the neuroinflammation-associated gene expression levels in amygdala, frontal cortex, hippocampus, and colon of female rats (<b>A</b>) and protein expression levels in colon of female rats (<b>B</b>). For gene expression, data are expressed as mean ± SEM and were analyzed by one-way ANOVA followed by Tukey’s test, <span class="html-italic">n</span> = 7–9 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, **** <span class="html-italic">p</span> &lt; 0.0001 for SNL-V vs. Sham-V group, and other groups vs. SNL-V group. For protein expression, data are expressed as mean ± SEM and were analyzed by one-way ANOVA followed by Tukey’s multiple comparisons test, <span class="html-italic">n</span> = 7–9 per group. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 compared with Sham-V group. <sup>+</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>++</sup> <span class="html-italic">p</span> &lt; 0.01 compared with SNL-V group.</p>
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<p>Effects of GEG on mitochondrial function-associated gene expression levels in amygdala, frontal cortex, hippocampus, and colon of male rats (<b>A</b>) and protein expression levels in colon of male rats (<b>B</b>). For gene expression, data are expressed as mean ± SEM and were analyzed by one-way ANOVA followed by Tukey’s test, <span class="html-italic">n</span> = 7–9 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, **** <span class="html-italic">p</span> &lt; 0.0001 for SNL-V vs. Sham-V group, and other groups vs. SNL-V group. For protein expression, data are expressed as mean ± SEM and were analyzed by one-way ANOVA followed by Tukey’s test, <span class="html-italic">n</span> = 7–9 per group. ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001 compared with Sham-V group. <sup>+</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>++</sup> <span class="html-italic">p</span> &lt; 0.01, <sup>+++</sup> <span class="html-italic">p</span> &lt; 0.001 compared with SNL-V group.</p>
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<p>Effects of GEG on the mitochondrial function-associated gene expression levels in amygdala, frontal cortex, hippocampus, and colon of female rats (<b>A</b>) and protein expression levels in colon of female rats (<b>B</b>). For gene expression, data are expressed as mean ± SEM and were analyzed by one-way ANOVA followed by Tukey’s test, <span class="html-italic">n</span> = 7–9 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, **** <span class="html-italic">p</span> &lt; 0.0001 for SNL-V vs. Sham-V group, and other groups vs. SNL-V group. For protein expression, data are expressed as mean ± SEM and were analyzed by one-way ANOVA followed by Tukey’s multiple comparisons test, <span class="html-italic">n</span> = 7–9 per group. * <span class="html-italic">p</span> &lt; 0.05 compared with Sham-V group. <sup>+</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>++</sup> <span class="html-italic">p</span> &lt; 0.01, <sup>+++</sup> <span class="html-italic">p</span> &lt; 0.001 compared with SNL-V group.</p>
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13 pages, 902 KiB  
Article
Oral Spore-Based Probiotic Supplementation Alters Post-Prandial Expression of mRNA Associated with Gastrointestinal Health
by Brian K. McFarlin, Sarah E. Deemer and Elizabeth A. Bridgeman
Biomedicines 2024, 12(10), 2386; https://doi.org/10.3390/biomedicines12102386 - 18 Oct 2024
Viewed by 1034
Abstract
Background/Objectives: Unregulated post-prandial dietary endotoxemia may accumulate over time and underlie the development of chronic disease (e.g., leaky gut, inflammatory bowel disease, etc.), for which oral probiotic supplementation may be a prophylactic. The purpose of this study was to determine if 45 [...] Read more.
Background/Objectives: Unregulated post-prandial dietary endotoxemia may accumulate over time and underlie the development of chronic disease (e.g., leaky gut, inflammatory bowel disease, etc.), for which oral probiotic supplementation may be a prophylactic. The purpose of this study was to determine if 45 d of oral spore-based probiotic supplementation altered gastrointestinal-associated mRNA expression following a high-fat meal. Methods: A subset of apparently healthy individuals from a larger study who had dietary endotoxemia at baseline completed 45 d of supplementation with either a placebo (rice flour; n = 10) or spore-based probiotic (Megasporebiotic™; Novonesis, Kongens Lyngby, Denmark; Bacillus indicus (HU36™), Bacillus subtilis (HU58™), Bacillus coagulans (SC208™), and Bacillus licheniformis (SL-307), and Bacillus clausii (SC109™); n = 10). Venous blood was collected in Paxgene RNA tubes prior to (PRE), 3 h, and 5 h after consumption of a high-fat meal (85% of the daily fat RDA and 65% of the daily calorie needs). Total RNA was analyzed for 579 mRNAs of interest (Nanostring nCounter Sprint; Seattle, WA, USA). After normalization to housekeeping controls and calculation of differential expression relative to PRE and controlled for FDR, 15 mRNAs were determined to be significantly changed at either 3 h and/or 5 h post-prandial in the probiotic group but not in the placebo group. Results: Significant mRNA expressions were associated with gastrointestinal tract barrier function (four mRNAs: BATF3, CCR6, CXCR6, and PDCD2), gastrointestinal immunity (four mRNAs: CLEC5A, IL7, CARD9, and FCER1G), or future IBD risk (seven mRNAs: PD-L1, CSF1R, FAS, BID, FADD, GATA3, and KIR3DL). Conclusions: Collectively, the present findings may support the notion that post-prandial immune response to eating is enhanced following 45 d of probiotic supplementation. Full article
(This article belongs to the Special Issue Epigenetic Regulation and Its Impact for Medicine)
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<p>mRNA quality control. Quality control data are presented for determination of mRNA expression using a Nanostring nCounter multiplex system. Panel (<b>A</b>) presents the Log10 counts for the 6 positive controls spiked into each sample. The expression of the controls was within manufacturer’s parameters. Panel (<b>B</b>) presents the variance in expression for 40 housekeeping mRNAs spiked into each sample. 32 housekeeper mRNAs were used for normalization (green circles)-based QC analysis completed using the geNorm algorithm.</p>
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<p>Gastrointestinal tract barrier function. Volcano plots present differential expression of probiotic mRNA expression pattern at 3H (<b>A</b>) and 5H (<b>B</b>). Additional bar plots (<b>C</b>) represent mRNA expression response for mRNA that reached significance for probiotic. Total RNA and subsequent mRNA expression analysis was completed using PAXgene whole blood was used as the RNA source. We found four mRNA whose expression reached significance (adjusted <span class="html-italic">p</span> &lt; 0.05) and were associated with GI barrier function: BATF3, CCR6, CXCR6, and PDCD2. The values in the volcano plot and bar graphs are presented as Log2 fold changes, and the significance is shown as the –Log10 <span class="html-italic">p</span>-value. * Indicates significant difference (adjusted <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Gastrointestinal tract immunity. Volcano plots present differential expression of probiotic mRNA expression pattern at 3H (<b>A</b>) and 5H (<b>B</b>). Additional bar plots (<b>C</b>) represent mRNA expression response for mRNA that reached significance for probiotic. Total RNA and subsequent mRNA expression analysis was completed using PAXgene whole blood was used as the RNA source. We found four mRNA whose expression reached significance (adjusted <span class="html-italic">p</span> &lt; 0.05) and were associated with GI immunity: CLEC5A, IL7, CARD9, and FCER1G. The values in the volcano plot and bar graphs are presented as Log2 fold changes, and the significance is shown as the –Log10 <span class="html-italic">p</span>-value. * Indicates significant difference (adjusted <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Future risk of IBD. Volcano plots present differential expression of probiotic mRNA expression pattern at 3H (<b>A</b>) and 5H (<b>B</b>). Additional bar plots (<b>C</b>) represent mRNA expression response for mRNA that reached significance for probiotic. Total RNA and subsequent mRNA expression analysis was completed using PAXgene whole blood was used as the RNA source. We found seven mRNA whose expression reached significance (adjusted <span class="html-italic">p</span> &lt; 0.05) and were associated with Future risk of IBD: PD-L1, CSF1R, FAS, BID, FADD, GATA3, and KIR3DL1. The values in the volcano plot and bar graphs are presented as Log2 fold changes, and the significance is shown as the –Log10 <span class="html-italic">p</span>-value. * Indicates significant difference (adjusted <span class="html-italic">p</span> &lt; 0.05).</p>
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15 pages, 1284 KiB  
Review
Exploring the Interconnection between Metabolic Dysfunction and Gut Microbiome Dysbiosis in Osteoarthritis: A Narrative Review
by Hui Li, Jihan Wang, Linjie Hao and Guilin Huang
Biomedicines 2024, 12(10), 2182; https://doi.org/10.3390/biomedicines12102182 - 25 Sep 2024
Viewed by 1436
Abstract
Osteoarthritis (OA) is a prevalent joint disorder and the most common form of arthritis, affecting approximately 500 million people worldwide, or about 7% of the global population. Its pathogenesis involves a complex interplay between metabolic dysfunction and gut microbiome (GM) alterations. This review [...] Read more.
Osteoarthritis (OA) is a prevalent joint disorder and the most common form of arthritis, affecting approximately 500 million people worldwide, or about 7% of the global population. Its pathogenesis involves a complex interplay between metabolic dysfunction and gut microbiome (GM) alterations. This review explores the relationship between metabolic disorders—such as obesity, diabetes, and dyslipidemia—and OA, highlighting their shared risk factors, including aging, sedentary lifestyle, and dietary habits. We further explore the role of GM dysbiosis in OA, elucidating how systemic inflammation, oxidative stress, and immune dysregulation driven by metabolic dysfunction and altered microbial metabolites contribute to OA progression. Additionally, the concept of “leaky gut syndrome” is discussed, illustrating how compromised gut barrier function exacerbates systemic and local joint inflammation. Therapeutic strategies targeting metabolic dysfunction and GM composition, including lifestyle interventions, pharmacological and non-pharmacological factors, and microbiota-targeted therapies, are reviewed for their potential to mitigate OA progression. Future research directions emphasize the importance of identifying novel biomarkers for OA risk and treatment response, adopting personalized treatment approaches, and integrating multiomics data to enhance our understanding of the metabolic–GM–OA connection and advance precision medicine in OA management. Full article
(This article belongs to the Special Issue Molecular Research on Osteoarthritis and Osteoporosis)
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<p>Interconnections between metabolic dysfunction and osteoarthritis (OA).</p>
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<p>Illustration of the mechanisms underlying the influence of gut dysbiosis on OA pathophysiology.</p>
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13 pages, 1149 KiB  
Review
An Update on Blastocystis: Possible Mechanisms of Blastocystis-Mediated Colorectal Cancer
by Stefania Tocci, Soumita Das and Ibrahim M. Sayed
Microorganisms 2024, 12(9), 1924; https://doi.org/10.3390/microorganisms12091924 - 22 Sep 2024
Cited by 1 | Viewed by 2805
Abstract
Blastocystis is an anaerobic parasite that colonizes the intestinal tract of humans and animals. When it was first discovered, Blastocystis was considered to be a normal flora with beneficial effects on human health, such as maintaining gut hemostasis and improving intestinal barrier integrity. [...] Read more.
Blastocystis is an anaerobic parasite that colonizes the intestinal tract of humans and animals. When it was first discovered, Blastocystis was considered to be a normal flora with beneficial effects on human health, such as maintaining gut hemostasis and improving intestinal barrier integrity. Later, with increasing research on Blastocystis, reports showed that Blastocystis sp. is associated with gastrointestinal disorders, colorectal cancer (CRC), and neurological disorders. The association between Blastocystis sp. and CRC has been confirmed in several countries. Blastocystis sp. can mediate CRC via similar mechanisms to CRC-associated bacteria, including infection-mediated inflammation, increased oxidative stress, induced gut dysbiosis, and damage to intestinal integrity, leading to a leaky gut. IL-8 is the main inflammatory cytokine released from epithelial cells and can promote CRC development. The causal association of Blastocystis sp. with other diseases needs further investigation. In this review, we have provided an update on Blastocystis sp. and summarized the debate about the beneficial and harmful effects of this parasite. We have also highlighted the possible mechanisms of Blastocystis-mediated CRC. Full article
(This article belongs to the Special Issue Parasitic Diseases in Humans and Animals)
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<p>Possible mechanisms through which <span class="html-italic">Blastocystis</span> can promote CRC. (1) Invasion of and survival in the host by targeting the immune responses through the degradation of IgA and suppression of antimicrobial products, iNOS. (2) <span class="html-italic">Blastocystis</span> infection induces an infection-mediated inflammation by stimulating the release of inflammatory cytokines, mainly IL-8, TNF-α, IL-6, and IL-1β, and oxidative stress that promotes gut leakiness and stimulates the oncogenesis pathways. (3) <span class="html-italic">Blastocystis</span> disrupts the intestinal barrier inducing a leaky gut by targeting ZO-1 protein. (4) <span class="html-italic">Blastocystis</span> infection causes gut microbial dysbiosis.</p>
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<p>Summary of beneficial and harmful effects of <span class="html-italic">Blastocystis</span>. <span class="html-italic">Blastocystis</span> can part of the normal flora and maintain the gut hemostasis by increasing the beneficial bacteria in gut. Also, it can increase intestinal TJs and gut barrier integrity. On the other hand, several diseases were reported in association with <span class="html-italic">Blastocystis</span> (foe) such as CRC, cancer outside the gut, gastrointestinal disorders (IBD and IBS), and neurological disorders.</p>
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20 pages, 3200 KiB  
Article
Infant Milk Formula Enriched in Dairy Cream Brings Its Digestibility Closer to Human Milk and Supports Intestinal Health in Pre-Clinical Studies
by Alina Kondrashina, Gianfranco Mamone, Linda Giblin and Jonathan A. Lane
Nutrients 2024, 16(18), 3065; https://doi.org/10.3390/nu16183065 - 11 Sep 2024
Viewed by 1894
Abstract
Human breast milk (HBM) is the “gold standard” for infant nutrition. When breast milk is insufficient or unavailable, infant milk formula (IMF) can provide a safe and nutritious alternative. However, IMFs differ considerably from HBM in composition and health function. We compared the [...] Read more.
Human breast milk (HBM) is the “gold standard” for infant nutrition. When breast milk is insufficient or unavailable, infant milk formula (IMF) can provide a safe and nutritious alternative. However, IMFs differ considerably from HBM in composition and health function. We compared the digestibility and potential health functions of IMF containing low cream (LC-) or high cream (HC-) with pooled HBM. After simulated infant digestion of these samples, the bioavailability of key nutrients and immunomodulatory activities were determined via cell-based in vitro assays. A Caenorhabditis elegans leaky gut model was established to investigate cream effects on gut health. Distinct differences were observed in peptide diversity and sequences released from HC-IMF compared with LC-IMF during simulated digestion (p < 0.05). Higher levels of free fatty acids were absorbed through 21-day differentiated Caco-2/HT-29MTX monolayers from HC-IMF, compared with LC-IMF and HBM (p < 0.05). Furthermore, the immune-modulating properties of HC-IMF appeared to be more similar to HBM than LC-IMF, as observed by comparable secretion of cytokines IL-10 and IL-1β from THP-1 macrophages (p > 0.05). HC-IMF also supported intestinal recovery in C. elegans following distortion versus LC-IMF (p < 0.05). These observations suggest that cream as a lipid source in IMF may provide added nutritional and functional benefits more aligned with HBM. Full article
(This article belongs to the Section Lipids)
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<p>Schematic representation of the <span class="html-italic">C. elegans</span> model of intestinal damage: preventive (<b>A</b>) and recovery (<b>B</b>) experimental setup for intestinal damage in the <span class="html-italic">C. elegans</span> model. Concentrations used were as follows: IMF (10 μL/mL); MTX (0.5 μg/mL); Nile red (0.05 μg/mL). Sixty worms were used per treatment, and experiments were performed in duplicates. <span class="html-italic">C. elegans</span>, <span class="html-italic">Caenorhabditis elegans</span>; MTX, methotrexate.</p>
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<p>Peptide release and absorption from HBM, HC-IMF, and LC-IMF in infant gastrointestinal digestion. Molecular weight distribution of proteins and peptides by SE-HPLC prior to the digestion (G0), after the gastric phase (G60), and after the intestinal phase (I60) (<b>A</b>). Number of released individual peptides in stages of simulated infant digestion and absorption by LC–MS/MS in LC-IMF, HC-IMF, and HBM. Different letters indicate significant differences in number of individual unique peptides, <span class="html-italic">p</span> &lt; 0.05 (<b>B</b>). Relative abundance of released individual peptides from different parental proteins in stages of simulated infant digestion and absorption by LC–MS/MS in LC-IMF and HC-IMF (<b>C</b>). N = 3. HC-IMF, high-cream IMF; LC-IMF, low-cream IMF.</p>
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<p>Free AAs and free FAs release and absorption from HBM, LC-IMF, and HC-IMF. Profile of free AAs release (<b>A</b>,<b>B</b>) and free FAs release (<b>C</b>,<b>D</b>) in simulated gastrointestinal digesta and after the simulated absorption with 21-day-old Caco-2/HT-29MTX monolayers over 4 h incubation with I60 samples at 500 μg protein/cm<sup>2</sup> in HBSS buffer. N = 3. Different letters within a time point indicate significant differences in total AAs or FAs concentrations, <span class="html-italic">p</span> &lt; 0.05. Raw data on free AA release are provided in <a href="#app1-nutrients-16-03065" class="html-app">Supplementary Table S2</a>.</p>
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<p>Mineral release and absorption in HBM, LC-IMF, and HC-IMF. The concentration of Ca (<b>A</b>) and Mg (<b>B</b>) in IMF and HBM prior to the digestion (G0), after the gastric phase (G60), after the intestinal phase (I60), and after absorption across 21-day-old Caco-2/HT29-MTX monolayers at 500 μg protein/cm<sup>2</sup>. Values are represented as mean with SD as error bars, N = 3. Different letters at each time point indicate significant differences (<span class="html-italic">p</span> &lt; 0.05). HC-IMF, high-cream IMF; LC-IMF, low-cream IMF; SD, standard deviation.</p>
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<p>Functional effects. Tight junction (TJ) protein expression in 21-day differentiated monolayers after 4 h incubation with IMF I60 samples (at 500 μg protein/cm<sup>2</sup> in HBSS) (<b>A</b>), and quantification of the bands by densitometry (<b>B</b>), N = 3. Intestinal barrier monolayer integrity by TEER in 21-day differentiated monolayers after 4-h incubation with IMF samples (<b>C</b>). Monolayers in the HBSS buffer had an average TEER of 664 ± 72 Ω×cm<sup>2</sup> and were assigned a value of 100%, N = 18. Release of satiety hormone GLP-1 (active) over 4 h incubation with 0.5 × 10<sup>6</sup> cells/well in 12-well plates STC-1 cells treated with 500 μg protein/cm<sup>2</sup> of IMF I60 digesta in Krebs buffer (<b>D</b>), N = 9. Different letters for each treatment indicate significant differences (<span class="html-italic">p</span> &lt; 0.05). HC-IMF, high-cream IMF; LC-IMF, low-cream IMF.</p>
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<p>Immunomodulatory properties. THP-1 cells (5 × 10<sup>5</sup> cells/well in 12 well plates) were differentiated for 3 days and then treated with digested IMF samples (at 500 μg protein/cm<sup>2</sup> in HBSS) or HBM in the same dilution for 4 h. Concentrations of secreted IFN-ɣ (<b>A</b>), IL-10 (<b>B</b>), IL1-β (<b>C</b>), IL-6 (<b>D</b>), IL-8 (<b>E</b>), and TNF-α (<b>F</b>) are represented as mean with SD as error bar, N = 6. Different letters at each time point indicate significant differences (<span class="html-italic">p</span> &lt; 0.05). HC-IMF, high-cream IMF; LC-IMF, low-cream IMF; SD, standard deviation.</p>
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<p>Intestinal damage. Effect of LC-IMF and HC-IMF on the recovery (<b>A</b>) and prevention (<b>B</b>) of intestinal barrier damage by MTX (positive control) in a <span class="html-italic">C. elegans</span> model. Prevention and recovery effects were determined by the intensity of Nile red staining of the body after leakage from the intestinal cavity, which was expressed as a percentage of fluorescence for each treatment group compared to the MTX-treated group (positive control). Concentrations used were as follows: IMF (10 μL/mL); MTX (0.5 μg/mL); Nile red (0.05 μg/mL). Sixty worms were used per treatment, and experiments were completed in duplicate. Values are represented as mean with SD as error bar, N = 3. Values without common letters differ significantly from each other (<span class="html-italic">p</span> &lt; 0.05). <span class="html-italic">C. elegans</span>, <span class="html-italic">Caenorhabditis elegans</span>; HC-IMF, high-cream IMF; LC-IMF, low-cream IMF; MTX, methotrexate; NGM, normal growth medium; SD, standard deviation.</p>
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21 pages, 1511 KiB  
Review
Psychobiotic Properties of Lactiplantibacillus plantarum in Neurodegenerative Diseases
by Mariagiovanna Di Chiano, Fabio Sallustio, Daniela Fiocco, Maria Teresa Rocchetti, Giuseppe Spano, Paola Pontrelli, Antonio Moschetta, Loreto Gesualdo, Raffaella Maria Gadaleta and Anna Gallone
Int. J. Mol. Sci. 2024, 25(17), 9489; https://doi.org/10.3390/ijms25179489 - 31 Aug 2024
Viewed by 2673
Abstract
Neurodegenerative disorders are the main cause of cognitive and physical disabilities, affect millions of people worldwide, and their incidence is on the rise. Emerging evidence pinpoints a disturbance of the communication of the gut–brain axis, and in particular to gut microbial dysbiosis, as [...] Read more.
Neurodegenerative disorders are the main cause of cognitive and physical disabilities, affect millions of people worldwide, and their incidence is on the rise. Emerging evidence pinpoints a disturbance of the communication of the gut–brain axis, and in particular to gut microbial dysbiosis, as one of the contributors to the pathogenesis of these diseases. In fact, dysbiosis has been associated with neuro-inflammatory processes, hyperactivation of the neuronal immune system, impaired cognitive functions, aging, depression, sleeping disorders, and anxiety. With the rapid advance in metagenomics, metabolomics, and big data analysis, together with a multidisciplinary approach, a new horizon has just emerged in the fields of translational neurodegenerative disease. In fact, recent studies focusing on taxonomic profiling and leaky gut in the pathogenesis of neurodegenerative disorders are not only shedding light on an overlooked field but are also creating opportunities for biomarker discovery and development of new therapeutic and adjuvant strategies to treat these disorders. Lactiplantibacillus plantarum (LBP) strains are emerging as promising psychobiotics for the treatment of these diseases. In fact, LBP strains are able to promote eubiosis, increase the enrichment of bacteria producing beneficial metabolites such as short-chain fatty acids, boost the production of neurotransmitters, and support the homeostasis of the gut–brain axis. In this review, we summarize the current knowledge on the role of the gut microbiota in the pathogenesis of neurodegenerative disorders with a particular focus on the benefits of LBP strains in Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, autism, anxiety, and depression. Full article
(This article belongs to the Special Issue Molecular Insights into Neurotrophins and Neuropsychiatric Disorders)
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<p>Caption. Microbiota-gut-brain-axis. Both eubiosis and an intact gut barrier promote a physiological communication within the gut-brain axis. On the contrary, a dysbiosic GM is associated with a disrupted intestinal barrier and triggers the release of inflammatory mediators that, one reaching the brain, cause neuronal changes leading to the pathogenesis of neurodegenerative disorders.</p>
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<p>Caption. Dysbiosis affecting the gut-brain interaction. A Dysbalance of species abundance in the GM influences the gut-brain axis and plays a crucialrole in the pathogenesis of neurodegenerative disorders. Abbreviation: ALS amyotrophic lateral sclerosis, MS multiple sclerosis, AD Alzheimer disease, ASD autism spectrum disorder, PD Parkinson disease.</p>
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11 pages, 920 KiB  
Systematic Review
Effect of Saccharomyces boulardii on Liver Diseases: A Systematic Review
by Roman Maslennikov, Nona Benuni, Anna Levshina, Farida Adzhieva, Tatyana Demina, Alina Kucher, Ekaterina Pervushova, Evgeniya Yuryeva, Elena Poluektova, Oxana Zolnikova, Evgenii Kozlov, Alexey Sigidaev and Vladimir Ivashkin
Microorganisms 2024, 12(8), 1678; https://doi.org/10.3390/microorganisms12081678 - 15 Aug 2024
Viewed by 2039
Abstract
We aimed to systematize the results of published studies on the use of Saccharomyces boulardii (SB) for the treatment of various liver disorders (CRD42022378050). Searches were conducted using PubMed and Scopus on 1 August 2022. The PubMed search was updated on 15 June [...] Read more.
We aimed to systematize the results of published studies on the use of Saccharomyces boulardii (SB) for the treatment of various liver disorders (CRD42022378050). Searches were conducted using PubMed and Scopus on 1 August 2022. The PubMed search was updated on 15 June 2024. The review included sixteen studies: ten experimental animal studies (EASs) and six randomized controlled trials (RCTs). The CNCM I-745 strain was used in 68.8% of the included studies. SB reduced the severity of many manifestations of cirrhosis, and lowered the Child–Pugh scores in RCT. SB reduced the serum concentrations of TNF-α, IL-1β, IL-6, and IL-4 in animals with metabolic dysfunction-associated steatotic liver disease (MASLD); lowered the serum TNF-α and IL-6 levels in experimental cirrhosis in rats; and reduced the CRP levels in decompensated cirrhosis. The EAS of MASLD revealed that SB reduced liver steatosis and inflammation and lowered the liver expression of genes of TNF-α, IL-1β, interferon-γ, and IL-10. In studies on experimental cirrhosis and MASLD, SB reduced the liver expression of genes of TGF-β, α-SMA, and collagen as well as liver fibrosis. SB reduced the abundance of Escherichia (Proteobacteria), increased the abundance of Bacteroidetes in the gut microbiota, prevented an increase in intestinal barrier permeability, and reduced bacterial translocation and endotoxemia. Full article
(This article belongs to the Special Issue Probiotics, Prebiotics, and Gut Microbes)
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<p>PRISMA flow diagram.</p>
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<p>Proposed mechanism of restoration of the gut–liver axis by <span class="html-italic">Saccharomyces boulardii</span>.</p>
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12 pages, 2274 KiB  
Article
IFN-β Overexpressing Adipose-Derived Mesenchymal Stem Cells Mitigate Alcohol-Induced Liver Damage and Gut Permeability
by Soonjae Hwang, Young Woo Eom, Seong Hee Kang, Soon Koo Baik and Moon Young Kim
Int. J. Mol. Sci. 2024, 25(15), 8509; https://doi.org/10.3390/ijms25158509 - 4 Aug 2024
Cited by 1 | Viewed by 1359
Abstract
Alcoholic liver disease (ALD) is a form of hepatic inflammation. ALD is mediated by gut leakiness. This study evaluates the anti-inflammatory effects of ASCs overexpressing interferon-beta (ASC-IFN-β) on binge alcohol-induced liver injury and intestinal permeability. In vitro, ASCs were transfected with a non-viral [...] Read more.
Alcoholic liver disease (ALD) is a form of hepatic inflammation. ALD is mediated by gut leakiness. This study evaluates the anti-inflammatory effects of ASCs overexpressing interferon-beta (ASC-IFN-β) on binge alcohol-induced liver injury and intestinal permeability. In vitro, ASCs were transfected with a non-viral vector carrying the human IFN-β gene, which promoted hepatocyte growth factor (HGF) secretion in the cells. To assess the potential effects of ASC-IFN-β, C57BL/6 mice were treated with three oral doses of binge alcohol and were administered intraperitoneal injections of ASC-IFN-β. Mice treated with binge alcohol and administered ASC-IFN-β showed reduced liver injury and inflammation compared to those administered a control ASC. Analysis of intestinal tissue from ethanol-treated mice administered ASC-IFN-β also indicated decreased inflammation. Additionally, fecal albumin, blood endotoxin, and bacterial colony levels were reduced, indicating less gut leakiness in the binge alcohol-exposed mice. Treatment with HGF, but not IFN-β or TRAIL, mitigated the ethanol-induced down-regulation of cell death and permeability in Caco-2 cells. These results demonstrate that ASCs transfected with a non-viral vector to induce IFN-β overexpression have protective effects against binge alcohol-mediated liver injury and gut leakiness via HGF. Full article
(This article belongs to the Special Issue Molecular Research in Human Stem Cells)
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<p>ASCs expressing IFN-β secrete HGF. Adipose tissue-derived mesenchymal stem cells (ASCs) were treated with human IFN-β (100 to 1000 units/mL) for 24 h. (<b>A</b>) ELISA of HGF in ASCs treated with human IFN-β for 24 h. (<b>B</b>) Real-time PCR analysis of HGF expression in ASCs treated with human IFN-β for 24 h. (<b>C</b>) ELISA of HGF in supernatants of ASCs transfected with a non-viral vector to carry plasmids containing the IFN-β gene for 24 h. (<b>D</b>) Real-time PCR analysis of HGF expression in ASCs transfected with a non-viral vector to carry plasmids containing the IFN-β gene for 24 h. Scatter plot. Horizontal bar; median. Significance between the treated groups was determined using the Mann–Whitney U test. * <span class="html-italic">p</span> &lt; 0.05; ns—no statistical significance.</p>
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<p>Treatment of ASCs expressing IFN-β decreases binge alcohol-induced liver damage and inflammation. C57BL/6 female mice were treated with binge ethanol. (<b>A</b>) Experimental design. C57BL/6 female mice were treated with binge alcohol three times (6 g/kg/dose). Binge alcohol-exposed C57BL/6 mice were injected intraperitoneally with ASC-IFN-β (2.0 × 10<sup>6</sup> cells/200 μL of PBS) once. The mice were sacrificed 1 h after the last binge alcohol treatment. (<b>B</b>) Body weight was measured after the third injection of ethanol. (<b>C</b>) H&amp;E staining of liver tissue. (<b>D</b>) Liver weight (mg)/body weight (g). (<b>E</b>) Serum AST levels. (<b>F</b>) Serum ALT levels (<span class="html-italic">n</span> = 5–17 mice per group). (<b>G</b>) TNF-α expression in the liver. (<b>H</b>) iNOS expression in the liver. (<b>I</b>) IL-1β expression in the liver. S, sham; E, binge ethanol; ASC-Mock, ASC transfected with vectors alone; ASC-IFN-β, ASC transfected with vector carrying plasmid containing the IFN-β gene. Significance between the treated groups was determined using the Mann–Whitney U test. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; ns—no statistical significance.</p>
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<p>Treatment of ASCs expressing <span class="html-italic">IFN-β</span> decreases inflammation and barrier permeability in the small intestine. (<b>A</b>) H&amp;E staining of the small intestine (ileum). (<b>B</b>) Inflammation scores. (<b>C</b>) Villus lengths. (<b>D</b>) Crypt lengths (<span class="html-italic">n</span> = 5–13 mice per group). (<b>E</b>) TNF-α expression in ileum. (<b>F</b>) IL-1β expression in ileum. (<b>G</b>) iNOS expression in ileum. (<b>H</b>) Fecal albumin levels in stool (<span class="html-italic">n</span> = 5–12 mice per group). (<b>I</b>) Endotoxin levels in serum (<span class="html-italic">n</span> = 5–12 mice per group). (<b>J</b>) Median number of colonies. S, sham; E, binge ethanol; ASC-Mock, ASCs transfected with vectors alone; ASC-IFN-β, ASCs transfected with vector carrying plasmid containing the IFN-β gene. Significance between the treated groups was determined using the Mann–Whitney U test. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; ns—no statistical significance.</p>
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<p>Evaluation of caspase 3 activity and permeability in ethanol-exposed intestinal epithelial cells. Caco-2 cells were treated with IFN-β, TRAIL, and HGF for 24 h, individually. Caspase 3 activity was measured via a caspase 3 commercial kit. The barrier function of Caco-2 cells was measured for transepithelial electrical resistance (TEER) and translocated FITC-4k dextran. (<b>A</b>) Caspase 3 activity (<span class="html-italic">n</span> = 4/group) of ethanol-exposed Caco-2 treated with IFN-β (250 to 1000 unit/mL). (<b>B</b>) Caspase 3 activity (<span class="html-italic">n</span> = 4/group) of ethanol-exposed Caco-2 treated with TRAIL (10 to 40 ng/mL). (<b>C</b>) Caspase 3 activity (<span class="html-italic">n</span> = 4/group) of ethanol-exposed Caco-2 treated with HGF (10 to 40 ng/mL). (<b>D</b>) TEER of Caco-2 treated with IFN-β, TRAIL, and HGF for 24 h, individually. (<b>E</b>) Relative intensities of FITC-4k dextran in Transwell seeded with Caco-2 monolayers treated with IFN-β (1000 unit/mL), TRAIL (40 ng/mL), or HGF (40 ng/mL) for 24 h, individually. S, sham; ET, ethanol. Significance between the treated groups was determined using the Mann–Whitney U test. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; ns—no statistical significance.</p>
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19 pages, 3770 KiB  
Article
Nutraceutical Additives Modulate Microbiota and Gut Health in Post-Weaned Piglets
by Jaime A. Ángel-Isaza, Víctor Herrera Franco, Albeiro López-Herrera and Jaime E. Parra-Suescun
Vet. Sci. 2024, 11(8), 332; https://doi.org/10.3390/vetsci11080332 - 25 Jul 2024
Viewed by 1560
Abstract
Due to the challenge of weaning pigs and the need to reduce the use of antimicrobials in animal feed, there is a growing need to look for nutraceutical alternatives to reduce the adverse effects of the post-weaning period. We evaluate the effect of [...] Read more.
Due to the challenge of weaning pigs and the need to reduce the use of antimicrobials in animal feed, there is a growing need to look for nutraceutical alternatives to reduce the adverse effects of the post-weaning period. We evaluate the effect of different feed nutraceutical additives on the microbial communities, gut health biomarkers, and productivity of pigs during the post-weaning period. The study involved 240 piglets weaned on the 21st day of age and randomized to six different diets: D1-BD commercial standard feed, D2-AGP: D1 + 150 ppm zinc bacitracin, D3-MD: D1 + 550 ppm maltodextrin, D4-FOS: D1 + 300 ppm fructo-oligosaccharides, D5-EO: D1 + 70 ppm Lippia origanoides essential oil, and D6-SH: D1 + 750 ppm sodium humate. On day 30 post-weaning, zootechnical parameters were evaluated, and jejunal samples were taken to obtain morphometric variables, expression of barrier and enzymatic proteins, and analysis of microbial communities. Animals fed D4-FOS and D5-EO had the lowest feed conversion ratio and higher expression of barrier and enzymatic proteins compared to D1-BD, D2-AGP, and D3-MD. The use of the additives modified the gut microbial communities of the piglets. In conclusion, fructo-oligosaccharides and Lippia origanoides essential oil were the best alternatives to zinc bacitracin as antibiotic growth promoters. Full article
(This article belongs to the Special Issue Nutraceuticals to Mitigate the Secret Killers in Animals)
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<p>Intestinal morphometric appearances of the jejunum in piglets at 30 days post-weaning. Cross-sections of the jejunum stained with hematoxylin–eosin. Scale bars indicate 1000 μm. (<b>A</b>) D1-BD: balanced feed without additives or antibiotics, (<b>B</b>) D2-AGP: BD + 150 ppm zinc bacitracin, (<b>C</b>) D3-MD: BD + 550 ppm maltodextrin, (<b>D</b>) D4-FOS: BD + 300 ppm fructo-oligosaccharides, (<b>E</b>) D5-EO: BD + 70 ppm <span class="html-italic">Lippia origanoides</span> essential oil, (<b>F</b>) D6-SH: BD + 750 ppm sodium humate.</p>
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<p>Relative mRNA expression of barrier proteins in the jejunum of piglets supplemented with different types of nutraceutical additives during the 30-day post-weaning period. Differences between diets as determined by Tukey’s test (α ≤ 0.05) are indicated by different letters A, B, C, and D within the same protein. <span class="html-italic">n</span> = 5 experimental units per diet. ZO: zonula occludens, CL: claudin, OC: occludin. D1-BD: balanced feed without additives or antibiotics, D2-AGP: BD + 150 ppm zinc bacitracin, D3-MD: BD + 550 ppm maltodextrin, D4-FOS: BD + 300 ppm fructo-oligosaccharides, D5-EO: BD + 70 ppm <span class="html-italic">Lippia origanoides</span> essential oil, D6-SH: BD + 750 ppm sodium humate.</p>
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<p>Relative mRNA expression of enzymatic proteins in the jejunum of piglets supplemented with different types of nutraceutical additives during the 30-day post-weaning period. Differences between diets as determined by Tukey’s test (α ≤ 0.05) are indicated by different letters, A, B, C, D, and E, within the same protein. <span class="html-italic">n</span> = 5 experimental units per diet. APA: Aminopeptidase A, APN: Aminopeptidase N, MGA: maltase–glucoamylase, SI: sucrase–isomaltase. D1-BD: balanced feed without additives or antibiotics, D2-AGP: BD + 150 ppm zinc bacitracin, D3-MD: BD + 550 ppm maltodextrin, D4-FOS: BD + 300 ppm fructo-oligosaccharides, D5-EO: BD + 70 ppm <span class="html-italic">Lippia origanoides</span> essential oil, D6-SH: BD + 750 ppm sodium humate.</p>
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<p>Alpha (A) and Beta (B) diversity of ileal microbial communities of pigs 30 days post-weaning. Part (<b>A</b>) shows box and whisker plots of the alpha diversity indices: Chao1, Shannon, and Simpson. Differences between diets as determined by Tukey’s test (α ≤ 0.05) are indicated by different letters: A, B, and C. Part (<b>B</b>) presents the Principal Coordinate Analysis (PcoA) based on Bray–Curtis distances showing the distribution of microbial composition of each group and distribution ellipses indicating 95% confidence intervals for each group of piglets fed different diets at 30 days post-weaning. D1-BD: balanced feed without additives, D2-AGP: BD + 150 ppm zinc bacitracin, D3-MD: BD + 550 ppm maltodextrin, D4-FOS: BD + 300 ppm fructo-oligosaccharides, D5-EO: BD + 70 ppm <span class="html-italic">Lippia origanoides</span> essential oil, D6-SH: BD + 750 ppm sodium humate.</p>
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<p>Venn diagram showing the unique and shared taxa in the microbial communities of piglets receiving different feed additives at 30 days post-weaning. The Venn diagram illustrates the distribution and overlap of microbial taxa across the dietary treatments employed in this study. Each colored ellipse represents a distinct diet. The peripheral regions of each ellipse indicate taxa exclusively associated with that particular diet. The intersections between ellipses quantify shared taxa between two or more diets, demonstrating the degree of microbial overlap among treatments. The central region, where all ellipses converge, represents the core microbiome—comprising taxa consistently present across all diets. D2-AGP (red ellipse): BD + 150 ppm zinc bacitracin, D3-MD (yellow ellipse): BD + 550 ppm maltodextrin, D4-FOS (blue ellipse): BD + 300 ppm fructo-oligosaccharides, D5-EO (green ellipse): BD + 70 ppm <span class="html-italic">Lippia origanoides</span> essential oil, D6-SH (gray ellipse): BD + 750 ppm sodium humate.</p>
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<p>Relative abundance of phyla (<b>A</b>) and relative abundance of the top 15 most abundant genera (<b>B</b>) in the ileal microbial communities of piglets at 30 days post-weaning. D1-BD: Balanced feed without additives or antibiotics, D2-AGP: BD + 150 ppm zinc bacitracin, D3-MD: BD + 550 ppm maltodextrin, D4-FOS: BD + 300 ppm fructo-oligosaccharides, D5-EO: BD + 70 ppm <span class="html-italic">Lippia origanoides</span> essential oil, D6-SH: BD + 750 ppm sodium humate.</p>
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<p>Heat map of Spearman’s correlations between relevant taxa with productive variables and expression of barrier and enzymatic proteins (<b>A</b>). LEfse analysis for identifying characteristic taxa in ileal microbial communities (<b>B</b>) of piglets 30 days post-weaning with different nutraceutical additives in their diets. The histogram shows the LDA scores of taxa whose abundance differed significantly between diets in the Kruskal–Wallis rank sum test (<span class="html-italic">p</span> &lt; 0.01) and which had an LDA score &gt; 4.0 between diets. DWG: daily weight gain, F:G ratio: feed conversion ratio, VH: villus height, CD: crypt depth, V:C: villus height-to-crypt depth ratio, IAA: intestinal absorptive area, APA: Aminopeptidase A, APN: Aminopeptidase N, MGA: maltase–glucoamylase, SI: sucrase–isomaltase, ZO: zonula occludens, CL: claudin, OC: occludin. D1-BD: balanced feed without additives or antibiotics, D2-AGP: BD + 150 ppm zinc bacitracin, D3-MD: BD + 550 ppm maltodextrin, D4-FOS: BD + 300 ppm fructo-oligosaccharides, D6-SH: BD + 750 ppm sodium humate.</p>
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