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Comparison of clinical efficacy and gut microbiota characteristics in children with ASD treated with fecal microbiota transplantation and ketogenic diet.

OBJECTIVE: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social communication and interaction, along with restricted, repetitive patterns of behavior. It is often accompanied by gastrointestinal dysfunction and gut microbiota dysbiosis. Fecal Microbiota Transplantation (FMT) and the Ketogenic Diet (KD) are interventions targeting the gut microbiota for ASD. METHODS: 30 participants were diagnosed with ASD according to DSM-5 and ADOS-2. ASD core symptoms were evaluated with CARS and ABC. Gut microbiota composition was analyzed by shotgun metagenomic sequencing. RESULTS: Both groups demonstrated significant improvements in core symptoms. In the FMT group, the mean CARS score significantly decreased from 34.87 to 33.53 (p&#x2009;<&#x2009;0.01); in the KD group, it declined from 35.13 to 33 (p&#x2009;<&#x2009;0.01). The mean ABC score reduced from 79.93 to 69.33 (p&#x2009;=&#x2009;0.064) in the FMT group and from 63.07 to 42.73 (p&#x2009;<&#x2009;0.01) in the KD group. Following the intervention, no statistically significant changes were observed in &#x3b1;-diversity or &#x3b2;-diversity within either group. LEfSe analysis revealed distinct post-intervention microbial signatures: FMT significantly enriched butyrate-producing taxa (Wujia chipingensis, Eubacterium sp. MSJ-33, and Butyrivibrio crossotus), while KD elevated Blautia massiliensis and decreased propionate metabolism -associated taxa (Veillonella sp. S12025-13 and Veillonella nakazawae). KEGG enrichment analysis revealed that KD enriched propionate metabolism (Fold enrichment&#x2009;=&#x2009;3.747, q&#x2009;=&#x2009;0.010) and aromatic compound degradation (Fold enrichment&#x2009;=&#x2009;3.591, q&#x2009;=&#x2009;0.010). CONCLUSIONS: Both interventions significantly improved clinical symptoms among children with ASD, potentially through distinct patterns of gut microbiota modulation. CLINICAL TRIALS NUMBER: NCT06348433 (03/21/2024).

Child

Immunological, Inflammatory, and Microbiota Determinants of Carpal Tunnel Syndrome: Evidence from Mendelian Randomization.

INTRODUCTION: Carpal Tunnel Syndrome (CTS) is a common peripheral neuropathy, and immune dysregulation and microbial dysbiosis are believed to play a role in its development. However, the cause-and-effect relationships have yet to be clarified. METHODS: Using publicly available Genome-Wide Association Study (GWAS), there are 731 immune cell phenotypes, 91 inflammatory proteins, 150 skin microbiota taxon, and 473 gut microbiota taxon based on two-sample Mendelian Randomization (MR) analysis to test whether there is a causal relationship between them and CTS. The results from the study were shown to have some degree of stability as demonstrated by various sensitivity analyses, which included running heterogeneity tests, performing MR -PRESSO, and running MR-Egger regressions. On the other hand, reverse MR was performed to verify the direction of the association. In addition, a two-step MR mediation analysis was conducted to explore whether there was a mediation effect of gut microbiota and skin microbiota, respectively, of immune and inflammatory traits on CTS. RESULTS: 22 Immune cell traits, 4 Inflammatory proteins, 18 gut microbiota taxa, and 3 skin microbiota taxa are causally associated with CTS. Reverse MR suggested feedback effects of CTS on select immune traits and gut microbiota. Mediation analysis revealed 4 gut microbiota taxa that substantially mediated immune/inflammatory effects upon CTS, with mediation rates as high as 44%; however, skin microbiota did not demonstrate any mediation. DISCUSSION: The immune dysregulation, inflammation, and the gut microbiota that cause CTS are all revealed through this research. Mendelian randomization analysis suggests that traits and inflammatory proteins of immune cells directly increase the risk of CTS, and certain types of gut microbes partially mediate these effects. Therefore, the results show a central role of the immune-gut axis in CTS pathogenesis, and suggest a systemic, rather than a local, immune-microbial interaction in disease development. CONCLUSION: We provided the first causal evidence that immune cells, inflammatory proteins, and CTS risk are causally associated with some specific taxa of gut microbiota. This contributes to a better understanding of the immune-microbiome interactions in the process of occurrence and development of CTS, and also provides theoretical support for precision prevention and treatment.

Humans

Immune-mediated indirect interaction between gut microbiota and bacterial pathogens.

BACKGROUND: In many animals, survival during infection depends on the ability to coordinate interactions between the host immune system and gut microbiota. These tripartite interactions, in turn, potentially shape pathogen virulence evolution. A key regulator of the immune system and, hence, bipartite interactions in insects is the immune deficiency (Imd) pathway, which modulates gut microbiota and pathogens by synthesizing antimicrobial peptides (AMPs) through the NF-&#x3ba;B transcription factor Relish. However, whether Imd-dependent AMPs mediate indirect interactions between gut microbiota and pathogens in a tripartite context remains unclear. Using RNAi-mediated knockdown of Tenebrio molitor Relish (TmRelish), we hypothesized that Imd-dependent AMPs influence indirect interaction between Providencia burhodogranariea_B (P. b_B) infection and the gut microbiota. RESULTS: TmRelish knockdown altered bipartite interactions by disrupting gut microbiota load and composition, increasing pathogen load, and ultimately leading to higher host mortality during infection. However, we did not find support for our tripartite hypothesis that Imd-dependent AMPs mediate indirect interactions between the gut microbiota and P. b_B infection, suggesting the involvement of alternative regulatory pathways or Imd-independent mechanisms. Nevertheless, our investigations of tripartite interactions showed a positive effect of P. b_B infection on gut microbiota load, which in turn stimulated the expression of a subset of AMPs. However, this upregulation of AMPs did not result in reduced P. b_B load. Notably, the gut microbiota did not affect pathogen load but promoted host survival during P. b_B infection, indicating a role in increasing host tolerance rather than resistance. CONCLUSIONS: These findings suggest that while Imd-dependent AMPs may not mediate tripartite interactions in our system, microbiota-host interactions, such as microbiota-mediated immune priming and changes in microbiota load, can shape infection outcomes. These effects on infection outcomes almost certainly exert important selective pressures on the evolution of bacterial virulence.

Animals

Integrated analysis of gut microbiota, serum metabolomics, and proteomics reveals novel associations with clinical symptoms in patients with cerebral infarction.

BACKGROUND: Cerebral infarction (CI) is a major cause of adult disability and mortality worldwide. Mounting evidence supports the critical role of the gut-brain axis in cerebrovascular disease progression. This study aimed to characterize the alterations in gut microbiota, serum metabolome, and serum proteome in patients with CI, and to identify multi-omics signatures associated with clinical symptoms. METHODS: A total of 20 CI patients and 20 healthy controls (HC) were enrolled. Fecal microbiota was profiled using 16&#xa0;S rRNA gene high-throughput sequencing. Serum metabolomics and proteomics were analyzed using ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and data-independent acquisition (DIA) proteomics, respectively. Spearman correlation and multi-omics integration were applied to explore the associations among microbiota, metabolites, proteins, and clinical indicators. RESULTS: CI patients displayed significant gut microbiota dysbiosis, with a markedly lower gut microbiota health index (GMHI) and higher microbiota disorder index (MDI) compared with HC (P&#x2009;<&#x2009;0.001). The genera g_norank_o_RF39 and Oxalobacter were significantly enriched in CI patients, whereas Clostridium_sensu_stricto_1 and Agathobacter were enriched in HC. Metabolomic analysis identified 445 differential metabolites, mainly involved in glycerophospholipid metabolism, phenylalanine metabolism, and caffeine metabolism. Proteomic analysis revealed 140 differentially expressed proteins linked to inflammatory responses, calcium signaling, and NF-&#x3ba;B signaling. Multi-omics integration showed that signature gut microbiota was strongly correlated (P&#x2009;<&#x2009;0.005) with key serum metabolites and proteins implicated in CI pathogenesis. CONCLUSIONS: This integrated multi-omics study revealed distinct gut microbiota, serum metabolomic, and proteomic alterations in CI patients. The microbiota-metabolite-protein regulatory axes provide novel insights into the gut-brain axis in CI and may serve as potential diagnostic biomarkers or therapeutic targets.

Humans

Brucellar spondylitis is associated with disturbance in gut microbiota and histamine metabolism associated inflammation.

BACKGROUND: The pathogenesis of brucellar spondylitis (BLS) has traditionally been considered to be primarily limited to local osteoarticular lesions. With the proposal of the "gut-spine axis" concept, the role of intestinal microecological dysbiosis in inflammatory spinal diseases has attracted in an increase of attention. The overactivated inflammatory cytokine network not only mediates bone destruction and intervertebral disc damage, but also forms a bidirectional interaction with gut microbiota dysbiosis through the "gut-spine axis," collectively driving disease progression. However, the inflammatory mechanism by which gut microbiota participates in the pathological process of BLS remains largely unclear. METHODS: This study recruited 20 BLS patients and 20 healthy donors. Multi-omics analysis including metagenomics, untargeted metabolomics, and targeted short-chain fatty acids (SCFAs) analysis, were used to compare the structural differences in gut microbiota between the two groups and screen for signature differential bacterial species. Plasma levels of histamine and histidine decarboxylase were measured by ELISA to clarify the role of differential histidine metabolic pathway in the disease. Additionally, plasma levels of lipopolysaccharide (LPS) and inflammatory cytokines (IL-1&#x3b2;, IL-6, IL-10, IL-17A, TNF-&#x3b1;) were detected by ELISA. The correlation between gut microbiota and inflammatory indicators was further analyzed. RESULTS: Compared to the healthy control group, the &#x3b1;-diversity of the gut microbiota in BLS patients was significantly reduced, with the microbial community structure exhibiting increased homogeneity. Beta diversity analysis revealed significant differences, suggesting that disease progression is associated with an overall imbalance in the gut microbiota and the deterioration of its specific structural composition. At the phylum level, the abundances of Actinomycetota, unclassified_d_Viruses, and Fusobacteriota were significantly increased in the gut microbiota of BLS patients compared to the control group, while the abundances of Bacillota and Pseudomonadota were significantly decreased. Further analysis revealed that, compared to the control group, the generic abundance of Enterococcus was significantly increased, while the proportions of Blautia, Faecalibacterium, Ruminococcus, Agathobacter, Roseburia, Clostridium, Eubacterium, Alistipes and Anaerobutyricum were significantly decreased. At the species level, the abundances of Enterococcus sp and Enterococcus-faecium were increased, whereas Blautia sp, Ruminococcus sp, Faecalibacterium sp, Faecalibacterium prausnitzii, Agathobacter rectalis, Eubacterium sp, Agathobacter sp, and Roseburia sp were decreased. Furthermore, untargeted metabolomics revealed that metabolites were enriched in the histidine metabolic pathway, and the levels of SCFAs including butyrate, isobutyrate, valerate, and 4-methylvalerate in the intestinal contents were reduced in BLS. Functional KEGG profiling revealed that key KOs involved in butyrate synthesis (e.g., K00074, K00172, K01640) and transport were globally downregulated in the patient group, whereas histidine decarboxylase KOs (K01693, K11755, K19787) that convert histidine to pro-inflammatory histamine were significantly enriched. The loss of butyrate-producing symbionts led to SCFAs deficiency and mucosal barrier disruption, creating ecological niches for facultatively anaerobic Enterococcus, which further exacerbated local inflammation via proteolytic fermentation and histamine production. Compared with the control group, BLS patients showed decreased plasma levels of IL-10, while levels of IL-1&#x3b2;, IL-6, IL-17A, and TNF-&#x3b1; were increased, and LPS levels were elevated. In addition, significantly elevated plasma pro-inflammatory LPS levels in patients with BLS suggest disruption of intestinal integrity and permeability. Correlation analysis indicated a close relationship between gut microbiota and inflammation. CONCLUSION: BLS is associated with gut microbiota dysbiosis and alterations in microbial metabolites, which may be linked to inflammatory responses and histamine metabolism. The differential microbial taxa identified in this study could be developed into a stool-based non-invasive diagnostic panel to facilitate early differentiation of BLS from other spinal disorders. Furthermore, restoring gut microbial balance through probiotic supplementation or dietary modulation may represent a promising adjunctive strategy to enhance the efficacy of standard antibiotic therapy and reduce disease recurrence.

Humans

Plasma metabolites mediate the causal relationship between gut microbiota and erectile dysfunction: insights from Mendelian randomization study.

BACKGROUND: While the relationship between gut microbiota and erectile dysfunction (ED) has been reported, the specific pathways involved remain unclear. AIM: This study aims to investigate the causal relationship between gut microbiota and ED, and to identify the potential role of plasma metabolites as mediators. METHODS: Utilizing aggregated genome-wide association study (GWAS) data, a comprehensive two-sample Mendelian randomization (MR) analysis was performed involving 196 gut microbiota taxa, 1400 plasma metabolites and ED. Causal relationships between gut microbiota, plasma metabolites and ED were explored. In addition, mediation analysis was applied to identify the pathway from gut microbiota to ED mediated by plasma metabolites. OUTCOMES: This study reveals that plasma metabolites act as mediators regulating the influence of gut microbiota on ED. RESULTS: MR analysis identified causal relationships between six gut microbial taxa and ED, with Butyrivibrio increasing the risk of ED, while Alistipes, Prevotella 9, Dialister, Marvinbryantia, and LachnospiraceaeUCG010 exhibited protective effects. Additionally, 45 plasma metabolites demonstrated causal associations with ED. Finally, mediation analysis revealed four mediation relationships. Sensitivity analysis indicated no heterogeneity or pleiotropy in this study. CLINICAL IMPLICATIONS: Modulating gut microbiota or targeting specific metabolites may offer new therapeutic approaches for ED, highlighting the potential for microbiome-based interventions. STRENGTHS AND LIMITATIONS: The MR approach and large-scale GWAS data provide robust causal evidence, but the findings are limited by their focus on European populations and lack of experimental validation. Further studies are needed to confirm these mechanisms in diverse cohorts and functional models. CONCLUSION: This study establishes a causal link between gut microbiota, plasma metabolites, and ED, identifying specific microbial taxa and metabolites as key contributors to ED risk. The mediating role of plasma metabolites highlights potential therapeutic strategies, such as probiotics or dietary interventions targeting harmful metabolites.

Mendelian randomization

Donor Microbiota Features Associated With Liver Transplant Recipient Infectious Complications: A Pilot Study Using Deep Intestinal Sampling During Liver Procurement.

BACKGROUND: The gut microbiota of living organ donors has been linked to transplant outcomes. However, little is known about the characteristics of the deceased donor gut microbiota or its potential impact on recipient outcomes. METHODS: We analyzed the deep intestinal microbiota from 24 deceased donors. Samples included luminal stool from the right and left colon as well as bile. Microbial composition was characterized using 16S V4 rRNA sequencing. &#x3b1;- and &#x3b2;-diversity analyses were performed to compare microbial communities between donor enteric sites and against stool samples from 28 healthy community controls, 14 critically ill intensive care comparators, and 12 matched liver transplant recipients. Machine learning models and logistic regression analysis were applied to explore whether features of the donor microbiota could predict recipient post-transplant complications. FINDINGS: The deceased donor microbiota showed an absence of the expected compositional variability between sampling sites, with no significant differences in either &#x3b1;- or &#x3b2;-diversity observed between bile, right and left colonic samples (all p > 0.05). Donor samples exhibited distinct microbial profiles compared with stool from both healthy and ICU comparators, including increased abundance of potential pathogens within the Enterobacteriaceae family (all p < 0.001). Features of the donor microbiota, particularly enrichment of Enterobacteriaceae, were associated with an increased risk of early post-transplant infection in recipients (&#x2264;&#xa0;30 days; p&#xa0;=&#xa0;0.011). INTERPRETATION: The deceased donor gut microbiota may represent a distinct microbial community with potential clinical relevance. Microbial profiling of donor enteric microbiota may help identify recipients at heightened risk of early post-transplant infectious complications.

Enterobacteriaceae

Identification of shared bacterial strains in the vaginal microbiota of related and unrelated reproductive-age mothers and daughters using genome-resolved metagenomics.

It has been suggested that the human microbiome might be vertically transmitted from mother to offspring and that early colonizers may play a critical role in development of the immune system. Studies have shown limited support for the vertical transmission of the intestinal microbiota but the derivation of the vaginal microbiota remains largely unknown. Although the vaginal microbiota of children and reproductive age women differ in composition, the vaginal microbiota could be vertically transmitted. To determine whether there was any support for this hypothesis, we examined the vaginal microbiota of daughter-mother pairs from the Baltimore metropolitan area (ages 14-27, 32-51; n = 39). We assessed whether the daughter's microbiota was similar in composition to their mother's using metataxonomics. Permutation tests revealed that while some pairs did have similar vaginal microbiota, the degree of similarity did not exceed that expected by chance. Genome-resolved metagenomics was used to identify shared bacterial strains in a subset of the families (n = 22). We found a small number of bacterial strains that were shared between mother-daughter pairs but identified more shared strains between individuals from different families, indicating that vaginal bacteria may display biogeographic patterns. Earlier-in-life studies are needed to demonstrate vertical transmission of the vaginal microbiota.

Child

The Mediating Role of Immune Cells in the Genetically Predicted Relationship between Gut Microbiota and Puerperal Sepsis: A Mendelian Randomization Study.

INTRODUCTION: The causal relationship between gut microbiota and puerperal sepsis (PS) remains unclear, and there is a lack of in-depth research regarding the potential mediating role of immune cells in this context. OBJECTIVE: This study aims to investigate the causal relationship between gut microbiota and PS using Mendelian randomization (MR) analysis and to assess the mediating effects of immune cells on the risk of PS onset through mediation analysis. MATERIALS AND METHODS: We selected data from large-scale genome-wide association studies (GWAS) involving 473 gut microbiota species, 731 immune cell phenotypes, and PS datasets. Univariate MR (UVMR) analysis was employed to explore the causal relationship between gut microbiota and PS, with the primary statistical method being inverse variance weighting (IVW). Multiple statistical models were applied for sensitivity analysis to minimize the confounding effects of horizontal pleiotropy and heterogeneity. Subsequently, a two-step mediation MR analysis was conducted to evaluate whether immune cells mediate the relationship between gut microbiota and PS. RESULTS AND DISCUSSION: Analysis using various statistical models indicated that 11 gut microbiota species (e.g., Azorhizobium, Bacillus velezensis, CAG-245 sp000435175, Lentimicrobiaceae, and Providencia) exhibited a causal relationship with PS. Further reverse causal analysis between PS and gut microbiota ruled out the possibility of reverse causality. The two-step mediation MR analysis demonstrated that the percentage of IgD-CD27- B cells (10.26%) and CD62L- monocytes (17.29%) partially mediated the effect of CAG-245 sp000435175 on PS risk. CONCLUSION: This study provides evidence of a causal relationship between the abundance of certain gut microbiota species and PS, while also revealing a potential mediating role of immune cells. These findings offer valuable theoretical insights into personalized treatment strategies and the development of novel diagnostic biomarkers for PS.

Humans

Two-sample Mendelian randomization study of gut microbiota and inflammatory proteins: Predictive, preventive, and personalized treatment for migraine.

The human gut microbiota is increasingly recognized as a significant factor in the pathogenesis of migraine, potentially via inflammatory pathways. Identifying specific human gut microbiota components associated with migraines, along with the investigation of particular inflammatory proteins, is essential for advancing primary prediction, targeted prevention, and personalized treatment strategies for migraines. We conducted a two-sample Mendelian randomization study using publicly available summary statistics from genome-wide association studies. Data for 473 human gut microbiota taxa were obtained from the Finnish national health survey conducted by the National Institute for Health and Welfare study (FINRISK, n = 5959 European participants). Genome-wide association study data (https://www.ebi.ac.uk/gwas/) for 91 circulating inflammatory proteins were obtained from 14,824 participants across 11 cohorts using the Olink Target 96 Inflammation panel. Migraine outcome data were obtained from the FinnGen R12 release, with cases defined using ICD-10 code G43. All genome-wide association study analyses were adjusted for sex, age, genotyping batch, and 10 genetic principal components to control population stratification (genomic inflation factors: 1.00&#x2013;1.05). Inverse variance-weighted Mendelian randomization was the primary analysis method, with Mendelian randomization-Egger, weighted median, and mode-based methods as sensitivity analyses. Two-step Mendelian randomization mediation analysis quantified the proportion of the effects of human gut microbiota on migraine that are mediated through inflammatory proteins. Thirty-seven bacterial genera were found to be associated with migraine using the inverse variance-weighted method. Of these, 18 genera exhibited a negative association, while 19 genera demonstrated a positive association with migraine risk. Additionally, eight inflammatory proteins were found to increase the risk of migraine. Among human gut microbiota, four were observed to reduce inflammatory protein levels, whereas another four were associated with increased inflammatory protein levels. Additionally, five gut microbiota were identified to influence migraine through inflammatory proteins in both Mendelian randomization analyses. Specifically, Actinobacteria, Brachyspiraceae, CAG-269 sp001915995, and Paraglaciecola were found to affect migraine outcomes via inflammatory proteins, with mediation proportions of 12%, 19%, 15.5%, and 6.7%, respectively. Lawsonibacter sp002161175 was identified to influence migraine risk through Oncostatin-M and SLAM, with mediation proportions of 15.6% and 11.3%, respectively. Our study elucidated the role of specific human gut microbiota alterations in the pathogenesis of migraine and highlighted the mediating effects of inflammatory proteins. Targeting these particular human gut microbiota alterations offers a promising strategy for predictive, preventive, and personalized medicine in migraine management, resulting in substantial clinical advancements.

causality

Integrative analysis of rumen microbiota activity and host metabolism following methanogenesis inhibition in dairy cattle.

Enteric methane emission from dairy cattle is an environmental challenge. The most efficient mitigation strategies nowadays include the use of methanogenesis inhibitors that specifically target the rumen methanogens. Specific inhibitors, such as 3-nitrooxypropanol (3-NOP), reduce methane emissions without negative effects on the products of fermentation that serve as energy metabolites for the host. However, the concomitant effects of methanogenesis inhibition on rumen microbiota and host metabolism are poorly characterized. Thus, the objective of this study was to explore the association between rumen microbiota and host metabolism when methanogenesis is inhibited. Thirteen dairy cows were used as controls, and 12 were supplemented with 3-NOP for 6 weeks. Rumen microbiota composition and activity were characterized using metagenomics and metatranscriptomics. The host metabolism was assessed in a previous publication by a metabolomic analysis of the plasma. Microbiota data were used as explanatory variables of the metabolome data in a multiblock sparse partial least squares analysis. Overall, the association between rumen microbiota and host metabolism was moderate. Notwithstanding this, a few downregulated transcripts related to glycolysis, hydrogen transfer, and protein synthesis, together with a decrease in the proportion of taxa of the Oscillospirales order, showed a correlation with host one-carbon metabolites (|r| > 0.6). These associations raised novel hypotheses that remain to be elucidated, especially with regard to the effects of dihydrogen on the accumulation of microbial glycolysis and methanogenesis metabolite intermediates.IMPORTANCEDairy cattle produce a substantial amount of methane, a potent greenhouse gas. Several strategies have been designed to reduce methane production by targeting the rumen microbiota. One such strategy specifically inhibits methanogens with a molecule called 3-nitrooxypropanol. This study uses an integrative data analysis approach, combining rumen microbiota and host metabolome information, to explore the consequences of inhibiting methanogenesis on the holobiont. This provides additional holistic insight into the effect of methane mitigation strategies on dairy cattle.

Animals

Gut microbiota-derived metabolites target C5AR1/KDM2A/HCAR3 axis in inflammatory bowel disease: a multi-machine learning algorithms and molecular docking study.

BACKGROUND: Inflammatory bowel disease (IBD) is a chronic recurrent disorder. Gut microbiota-derived metabolites regulate intestinal homeostasis, but their molecular mechanisms in IBD remain unclear. Current studies lack systematic "microbiota-metabolite-target" network mining with multi-method validation. This study integrates network pharmacology, three machine learning algorithms, and molecular docking to construct this regulatory network in IBD. METHODS: Transcriptome data were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using limma (p < 0.05, |log2FC| > 0.5). Weighted gene co-expression network analysis (WGCNA) with an optimal soft threshold of &#x3b2; = 7 was performed to identify key module genes. Candidate genes were obtained by intersecting DEGs, gut microbiota-associated genes from the gutMGene database, and WGCNA module genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to explore the functional roles of candidate genes. Core genes were identified using three machine learning algorithms (LASSO, Boruta, and SVM-RFE), followed by protein-protein interaction (PPI) network analysis. Molecular docking was performed to assess the binding affinities between hub proteins and gut microbiota-derived metabolites. RESULTS: A total of 885 DEGs were identified between the IBD and control groups, including 463 upregulated and 422 downregulated genes. WGCNA identified 280 key module genes from the purple and yellow modules. The intersection of DEGs, gut microbiota-associated genes, and WGCNA module genes yielded 19 core candidate genes. PPI network analysis combined with three machine learning algorithms jointly identified C5AR1, KDM2A, and HCAR3 as core hub genes. ROC curve analysis demonstrated that all three hub genes achieved AUC values greater than 0.7 in both the training and validation sets, indicating excellent diagnostic performance for IBD. Enrichment analysis revealed significant associations with the TNF, NF-&#x3ba;B, and IL-17 signaling pathways. Molecular docking confirmed stable binding of C5AR1 with 1,3-Diphenylpropan-2-Ol (-7.87 &#xb1; 0.83 kcal&#xb7;mol-&#xb9;) and HCAR3 with 3-Indolepropionic Acid (-6.35 &#xb1; 0.70 kcal&#xb7;mol-&#xb9;), both below -5.0 kcal&#xb7;mol-&#xb9;. CONCLUSION: This study first constructs a "gut microbiota-metabolite-hub gene" axis in IBD, providing a computational framework for microbiota-targeted precision therapy, and identifying C5AR1/KDM2A/HCAR3 as computationally predicted diagnostic biomarkers and 1,3-Diphenylpropan-2-Ol/3-Indolepropionic Acid as candidate intervention molecules that warrant further experimental validation.

Molecular Docking Simulation

Investigation of associations between the neonatal gut microbiota and severe viral lower respiratory tract infections in the first 2 years of life: a birth cohort study with metagenomics.

BACKGROUND: Early-life gut microbiota affects immune system development, including the lung immune response (gut-lung axis). We aimed to investigate whether gut microbiota composition in neonates in the first week of life is associated with hospital admissions for viral lower respiratory tract infections (vLRTIs). METHODS: The Baby Biome Study (BBS) is a prospective birth cohort, which enrolled mother-baby pairs between Jan 1, 2016, and Dec 31, 2017, at three UK hospitals. In the present study, we only included BBS babies with a sequenced first-week stool sample and successful data linkage. Stool was collected in the first week of life for shotgun-metagenomic sequencing. We examined the following microbiota features: alpha diversity (Chao1, Shannon, and Simpson indices) and community structures (cluster-partitioning against medoids method). The participants were followed up through linkage to the Hospital Episode Statistics-Admitted Patient Care (HES-APC) database to determine vLRTI hospital admission incidence in the first 2 years of life. We used Poisson mixed-effects models for univariable and multivariable analyses to evaluate the association between microbiota features and vLRTI hospital admission incidence, adjusting for confounders identified through direct acyclic graphs. FINDINGS: 3305 (95%) of the 3476 BBS-enrolled babies for whom consent to data linkage was obtained were included in the present study. 1111 (34%) babies had a first-week sequenced stool sample, of whom 1082 (97%; 564 born vaginally and 518 born by caesarean section) were successfully linked to HES-APC, and had median follow-up of 2&#xb7;0 years (IQR 1&#xb7;4-2&#xb7;9). Most babies were born at term (996 [92%] &#x2265;37 weeks gestational age and 1070 [99%] >35 weeks gestational age) and healthy (1050 [97%] had no comorbidities), and 520 (48%) were female and 562 (52%) were male. Higher first-week gut microbiota alpha diversity was associated with reduced rates of vLRTI hospital admission (Chao1 Index adjusted hazard ratio [HR] 0&#xb7;92 [95% CI 0&#xb7;85-0&#xb7;99]; Shannon Index adjusted HR 0&#xb7;57 [0&#xb7;33-0&#xb7;98]; and Simpson Index adjusted HR 0&#xb7;36 [0&#xb7;11-1&#xb7;20]). Three microbiota clusters were identified. Cluster 1 had a mixed composition and cluster 2 was dominated by Bifidobacterium breve, with both clusters observed in babies born vaginally and by caesarean section. Cluster 3 was found only in vaginally born babies and was dominated by Bifidobacterium longum. Having cluster 1 (mixed) or cluster 2 (B breve dominated) was independently associated with increased rates of vLRTI hospital admission compared with cluster 3 (B longum dominated; cluster 1 [mixed] 3&#xb7;05 [1&#xb7;25-7&#xb7;41] and cluster 2 [B breve dominated] 2&#xb7;80 [1&#xb7;06-7&#xb7;44]). INTERPRETATION: We report observational evidence that first-week gut microbiota differences are associated with clinically severe vLRTI in young children. This study identified bacterial species that could be of interest for vLRTI prevention. This finding has important implications for the design of future research and intervention strategies. FUNDING: The Wellcome Trust and Wellcome Sanger Institute core funding.

Humans

Effects of dietary interventions on gut microbiota and related cardiometabolic changes in pediatric obesity: a systematic review and meta-analysis.

BACKGROUND: Gut microbiota imbalances may contribute to obesity, yet whether dietary interventions can modulate the microbiota and improve metabolic health in pediatrics has not been thoroughly reviewed. This systematic review and meta-analysis explores the impact of dietary interventions on the gut microbiota of children and adolescents with overweight or obesity, and its association with cardiometabolic improvements. METHODS: A systematic search of clinical trials in Pubmed, Cochrane and EMBASE was conducted following PRISMA guidelines (PROSPERO n&#xb0;CRD42024505494). Risk of bias was assessed with RoB2 and ROBINS, for randomized and non-randomized intervention studies. RESULTS: Overall, 60 articles were assessed for full-text eligibility, 8 were included, and 4 provided alpha-diversity data for meta-analysis. A total of 200 participants were included (6-16 years). Six studies implemented calorie-restricted diets, one a low free-sugar diet, and one CHILD-1 diet. The meta-analysis revealed a significant increase in Chao1 (48.76 [95%CI 1.81; 95.70]; I2&#x2009;=&#x2009;86.8%, p&#x2009;<&#x2009;0.001) following a balanced calorie-restricted dietary intervention. Although&#xa0;there was heterogeneity in taxa-level changes, several butyrate-producing genera (Clostridium XVIa, Coprococcus, Roseburia, Faecalibacterium, Blautia, Butyricimonas) increased following dietary intervention. CONCLUSIONS: Balanced dietary interventions with calorie-restriction adequate for pediatric age could increase gut microbiota richness and butyrate-producing bacteria abundance. Future trials should clarify diet-driven gut microbiota changes in childhood obesity and related metabolic changes. IMPACT: Balanced calorie restriction diet may increase gut microbiota richness in childhood obesity Butyrate-producer expansion needs long-term dietary intervention Gaps in linking microbiota-metabolism interplay in pediatric obesity.

Journal Article

Capsaicin ameliorates glycemic levels via gut microbiota-derived 5-aminolevulinic acid in mice.

BACKGROUND: Capsaicin, a natural alkaloid in chili peppers, regulates glycemic levels; however, its mechanisms and therapeutic potential remain unclear. This study aimed to elucidate the role of gut microbiota and their metabolites in mediating capsaicin's glycemic regulatory effects. We conducted experiments in specific pathogen-free (SPF) and germ-free (GF) mice, transient receptor potential vanilloid 1 (TRPV1) receptor ablation studies, and fecal microbiota transplantation (FMT) to demonstrate the involvement of gut microbiota in capsaicin-mediated glycemic control. Metagenomics and metabolomics analyses were employed to identify key microbial strains and metabolic pathways. Keystone strains and metabolites were supplemented in GF mice without capsaicin intervention to validate their effects on glycemic regulation. In vitro co-culture experiments were performed to investigate the mutualistic relationships among keystone strains under capsaicin treatment. RESULTS: Gut microbiota constitute an important component of capsaicin-mediated glycemic regulation, acting in concert with but not solely dependent on TRPV1 signaling. Gut microbiota altered by capsaicin promote the production of 5-aminolevulinic acid (5-ALA), which contributes to heme synthesis and enhances glycemic control. Supplementation with Akkermansia muciniphila, Ligilactobacillus murinus, or 5-ALA in GF mice recapitulates the glycemic benefits of capsaicin. Furthermore, capsaicin enriches Akkermansia muciniphila, which in turn supports the growth of Ligilactobacillus murinus. CONCLUSION: Capsaicin-induced changes in the gut microbiota promote 5-ALA synthesis, leading to improved glycemic control. These findings suggest that dietary or probiotic interventions targeting gut microbiota, particularly Akkermansia muciniphila and 5-ALA, may offer promising strategies for managing glycemic disorders, including type 2 diabetes (T2D). Video Abstract.

Animals

Targeting the Microbiota-Gut-Brain Axis: Emerging Nanomedicine Approaches for Neurodegenerative Diseases.

The microbiota-gut-brain axis (MGBA) is a bidirectional relationship between the gut microbiota (GM) and the brain, where the GM affects the gastrointestinal tract (GIT) and the central nervous system (CNS), and vice versa. Microbiotas are important for several vital body processes, including metabolism, immunity, and homeostasis. The MGBA has three main pathways: the vagal nerve mechanism, the immune-related mechanism, and the neuroendocrine mechanism. GM imbalance, known as dysbiosis, affects the GIT, the brain, and the CNS. Furthermore, dysbiosis is linked to several neurological disorders such as Alzheimer's (AD), Parkinson's (PD), depression, autism spectrum disorder (ASD), and multiple sclerosis (MS). Studying MGBA gives researchers new therapeutic ideas using microbiota. Using special diets rich in fiber and probiotics, in addition to fecal microbiota transplantation (FMT), is being studied as a new therapy for MGBA. From the point of view that these therapeutic interventions maintain microbiota imbalance, which in turn will affect the brain and can relieve the neurological disorders caused by dysbiosis and MGBA.

Humans

New evidence for the protective effect of gut microbiota regulation of ferroptosis-related proteins against osteoporosis.

Osteoporosis (OP), characterized by bone degradation and increased fracture susceptibility, constitutes a significant global health burden. Recent findings implicate gut microbiota and ferroptosis in the regulation of bone metabolism; however, causal evidence for the gut microbiota's influence on OP specifically via ferroptosis regulation remains to be established. This study employed two-sample Mendelian randomization (MR) using genome-wide association study (GWAS) summary statistics to investigate these causal relationships and delineate mediating pathways.We assessed causal links between gut microbiota, ferroptosis-related proteins, and OP risk. Associations for gut microbiota abundance and ferroptosis-related proteins were derived from GWAS data and Icelandic blood-derived protein quantitative trait loci, respectively. Outcome data for OP were obtained from the FinnGen Release R12. The primary analysis utilized the inverse variance weighted (IVW)&#xa0;method, supplemented by sensitivity analyses to evaluate heterogeneity and horizontal pleiotropy. &#xa0;MR analysis identified 33 gut microbial taxa causally associated with OP risk: 13 protective and 20 detrimental. Similarly, 34 ferroptosis-related proteins were categorized as protective (18) or detrimental (16) for OP. Mediation analysis revealed that the protective effect of Terrisporobacter othiniensis on OP is partially mediated by the ferroptosis regulator MDM4 (indirect effect &#x3b2; = -0.020, 95% CI: -0.068 to 0.029), accounting for 6.8% of the total effect. Sensitivity analyses showed no significant evidence of heterogeneity or horizontal pleiotropy.&#xa0;This study provides the first genetically validated evidence supporting a causal relationship between specific gut microbiota, ferroptosis-associated proteins, and OP susceptibility. Specifically, Terrisporobacter othiniensis demonstrates a novel protective mechanism, modulating OP risk partly through the ferroptosis regulator MDM4. These findings broaden understanding of the "gut-bone axis" and highlight the gut microbiota-ferroptosis pathway, particularly the MDM4/p53 axis, as a promising target for novel OP prevention and therapeutic strategies.

Ferroptosis

Causal Effects of Gut Microbiota on Morning Chronotype, Insomnia and Sleep Duration: A Two-Sample Mendelian Randomization Study.

BACKGROUND: The gut microbiota has been shown to be closely associated with brain function; however, whether it exerts a causal influence on sleep traits remains to be further explored. Mendelian randomization (MR) is an emerging epidemiological approach that uses whole-genome sequencing data to infer causal relationships. In this study, we conducted a two-sample MR analysis to investigate the causal effects of gut microbiota on three domains of sleep traits: morning chronotype, insomnia, and sleep duration. METHODS: Single nucleotide polymorphisms strongly associated with 196 gut microbiota taxa were selected as instrumental variables. Morning chronotype, insomnia, and sleep duration were used as outcomes. MR and sensitivity analyses were performed to assess the causal relationships between gut microbiota and sleep traits. RESULTS: Three taxa (Bifidobacteriales, Bifidobacteriaceae, and Bifidobacterium) were negatively associated with morning chronotype, while Tyzzerella 3 showed a positive causal effect on morning chronotype. Oscillibacter was negatively associated with insomnia, whereas four taxa (Negativicutes, Selenomonadales, the Clostridium innocuum group, and Lachnoclostridium) were identified as risk-increasing factors for insomnia. Lentisphaerae and Victivallaceae were positively associated with sleep duration. Actinobacteria and Alistipes had negative effects on long sleep duration, whereas Ruminiclostridium 6 was positively associated with long sleep duration. Four taxa (Victivallales, Anaerofilum, Lentisphaerae, and Lentisphaeria) were negatively associated with short sleep duration. CONCLUSIONS: Our findings suggest that specific gut microbiota taxa may be positively or negatively associated with sleep traits. These results offer new insights into the potential role of gut microbiota in sleep regulation and provide a basis for future studies aimed at understanding whether modulating microbial composition could influence sleep health.

Mendelian randomization