Genetically predicted gut microbiota mediate the association between plasma lipidomics and primary sclerosing cholangitis.

BACKGROUND: Primary sclerosing cholangitis (PSC) is a complex disease with pathogenic mechanisms that remain to be elucidated. Previous observational studies with small sample sizes have reported associations between PSC, dyslipidemia, and gut microbiota dysbiosis. However, the causality of these associations is uncertain, and there has been no systematic analysis to date. METHODS: The datasets comprise data on PSC, 179 lipid species, and 412 gut microbiota species. PSC data (n = 14,890) were sourced from the International PSC Study Group, while the dataset pertaining to plasma lipidomics originated from a study involving 7174 Finnish individuals. Data on gut microbiota species were derived from the Dutch Microbiome Project study, which conducted a genome-wide association study involving 7738 participants. Furthermore, we employed a two-step Mendelian randomization (MR) analysis to quantify the proportion of the effect of gut microbiota-mediated lipidomics on PSC. RESULTS: Following a rigorous screening process, our MR analysis revealed a causal relationship between higher levels of gene-predicted Phosphatidylcholine (O-16:1_18:1) (PC O-16:1_18:1) and an increased risk of developing PSC (inverse variance-weighted method, odds ratio (OR) 1.30, 95% confidence interval (CI) 1.03-1.63). There is insufficient evidence to suggest that gene-predicted PSC impacts the levels of PC O-16:1_18:1 (OR 1.01, 95% CI 0.98-1.05). When incorporating gut microbiota data into the analysis, we found that Eubacterium rectale-mediated genetic prediction explains 17.59% of the variance in PC O-16:1_18:1 levels. CONCLUSION: Our study revealed a causal association between PC O-16:1_18:1 levels and PSC, with a minor portion of the effect mediated by Eubacterium rectale. This study aims to further explore the pathogenesis of PSC and identify promising therapeutic targets. For patients with PSC who lack effective treatment options, the results are encouraging.

Co-localization of antibiotic resistance genes is widespread in the infant gut microbiome and associates with an immature gut microbial composition.

BACKGROUND: In environmental bacteria, the selective advantage of antibiotic resistance genes (ARGs) can be increased through co-localization with genes such as other ARGs, biocide resistance genes, metal resistance genes, and virulence genes (VGs). The gut microbiome of infants has been shown to contain numerous ARGs, however, co-localization related to ARGs is unknown during early life despite frequent exposures to biocides and metals from an early age. RESULTS: We conducted a comprehensive analysis of genetic co-localization of resistance genes in a cohort of 662 Danish children and examined the association between such co-localization and environmental factors as well as gut microbial maturation. Our study showed that co-localization of ARGs with other resistance and virulence genes is common in the early gut microbiome and is associated with gut bacteria that are indicative of low maturity. Statistical models showed that co-localization occurred mainly in the phylum Proteobacteria independent of high ARG content and contig length. We evaluated the stochasticity of co-localization occurrence using enrichment scores. The most common forms of co-localization involved tetracycline and fluoroquinolone resistance genes, and, on plasmids, co-localization predominantly occurred in the form of class 1 integrons. Antibiotic use caused a short-term increase in mobile ARGs, while non-mobile ARGs showed no significant change. Finally, we found that a high abundance of VGs was associated with low gut microbial maturity and that VGs showed even higher potential for mobility than ARGs. CONCLUSIONS: We found that the phenomenon of co-localization between ARGs and other resistance and VGs was prevalent in the gut at the beginning of life. It reveals the diversity that sustains antibiotic resistance and therefore indirectly emphasizes the need to apply caution in the use of antimicrobial agents in clinical practice, animal husbandry, and daily life to mitigate the escalation of resistance. Video Abstract.

Deciphering the Impact of Defecation Frequency on Gut Microbiome Composition and Diversity.

This study explores the impact of defecation frequency on the gut microbiome structure by analyzing fecal samples from individuals categorized by defecation frequency: infrequent (1-3 times/week, n = 4), mid-frequent (4-6 times/week, n = 7), and frequent (daily, n = 9). Utilizing 16S rRNA gene-based sequencing and LC-MS/MS metabolome profiling, significant differences in microbial diversity and community structures among the groups were observed. The infrequent group showed higher microbial diversity, with community structures significantly varying with defecation frequency, a pattern consistent across all sampling time points. The Ruminococcus genus was predominant in the infrequent group, but decreased with more frequent defecation, while the Bacteroides genus was more common in the frequent group, decreasing as defecation frequency lessened. The infrequent group demonstrated enriched biosynthesis genes for aromatic amino acids and branched-chain amino acids (BCAAs), in contrast to the frequent group, which had a higher prevalence of genes for BCAA catabolism. Metabolome analysis revealed higher levels of metabolites derived from aromatic amino acids and BCAA metabolism in the infrequent group, and lower levels of BCAA-derived metabolites in the frequent group, consistent with their predicted metagenomic functions. These findings underscore the importance of considering stool consistency/frequency in understanding the factors influencing the gut microbiome.

Uncovering specific taxonomic and functional alteration of gut microbiota in chronic kidney disease through 16S rRNA data.

Introduction: Chronic kidney disease (CKD) is worldwide healthcare burden with growing incidence and death rate. Emerging evidence demonstrated the compositional and functional differences of gut microbiota in patients with CKD. As such, gut microbial features can be developed as diagnostic biomarkers and potential therapeutic target for CKD. Methods: To eliminate the outcome bias arising from factors such as geographical distribution, sequencing platform, and data analysis techniques, we conducted a comprehensive analysis of the microbial differences between patients with CKD and healthy individuals based on multiple samples worldwide. A total of 980 samples from six references across three nations were incorporated from the PubMed, Web of Science, and GMrepo databases. The obtained 16S rRNA microbiome data were subjected to DADA2 processing, QIIME2 and PICRUSt2 analyses. Results: The gut microbiota of patients with CKD differs significantly from that of healthy controls (HC), with a substantial decrease in the microbial diversity among the CKD group. Moreover, a significantly reduced abundance of bacteria Faecalibacterium prausnitzii (F. prausnitzii) was detected in the CKD group through linear discriminant analysis effect size (LEfSe) analysis, which may be associated with the alleviating effects against CKD. Notably, we identified CKD-depleted F. prausnitzii demonstrated a significant negative correlation with three pathways based on predictive functional analysis, suggesting its potential role in regulating systemic acidbase disturbance and pro-oxidant metabolism. Discussion: Our findings demonstrated notable alterations of gut microbiota in CKD patients. Specific gut-beneficial microbiota, especially F. prausnitzii, may be developed as a preventive and therapeutic tool for CKD clinical management.

Critical COVID-19, Victivallaceae abundance, and celiac disease: A mediation Mendelian randomization study.

Celiac disease exhibits a higher prevalence among patients with coronavirus disease 2019. However, the potential influence of COVID-19 on celiac disease remains uncertain. Considering the significant association between gut microbiota alterations, COVID-19 and celiac disease, the two-step Mendelian randomization method was employed to investigate the genetic causality between COVID-19 and celiac disease, with gut microbiota as the potential mediators. We employed the genome-wide association study to select genetic instrumental variables associated with the exposure. Subsequently, these variables were utilized to evaluate the impact of COVID-19 on the risk of celiac disease and its potential influence on gut microbiota. Employing a two-step Mendelian randomization approach enabled the examination of potential causal relationships, encompassing: 1) the effects of COVID-19 infection, hospitalized COVID-19 and critical COVID-19 on the risk of celiac disease; 2) the influence of gut microbiota on celiac disease; and 3) the mediating impact of the gut microbiota between COVID-19 and the risk of celiac disease. Our findings revealed a significant association between critical COVID-19 and an elevated risk of celiac disease (inverse variance weighted [IVW]: P = 0.035). Furthermore, we observed an inverse correlation between critical COVID-19 and the abundance of Victivallaceae (IVW: P = 0.045). Notably, an increased Victivallaceae abundance exhibits a protective effect against the risk of celiac disease (IVW: P = 0.016). In conclusion, our analysis provides genetic evidence supporting the causal connection between critical COVID-19 and lower Victivallaceae abundance, thereby increasing the risk of celiac disease.

Quantitative microbiome profiling of honey bee (Apis mellifera) guts is predictive of winter colony loss in northern Virginia (USA).

For the past 15 years, the proportion of honey bee hives that fail to survive winter has averaged ~ 30% in the United States. Winter hive loss has significant negative impacts on agriculture, the economy, and ecosystems. Compared to other factors, the role of honey bee gut microbial communities in driving winter hive loss has received little attention. We investigate the relationship between winter survival and honey bee gut microbiome composition of 168 honey bees from 23 hives, nine of which failed to survive through winter 2022. We found that there was a substantial difference in the abundance and community composition of honey bee gut microbiomes based on hive condition, i.e., winter survival or failure. The overall microbial abundance, as assessed using Quantitative Microbiome Profiling (QMP), was significantly greater in hives that survived winter 2022 than in those that failed, and the average overall abundance of each of ten bacterial genera was also greater in surviving hives. There were no significant differences in alpha diversity based on hive condition, but there was a highly significant difference in beta diversity. The bacterial genera Commensalibacter and Snodgrassella were positively associated with winter hive survival. Logistic regression and random forest machine learning models on pooled ASV counts for the genus data were highly predictive of winter outcome, although model performance decreased when samples from the location with no hive failures were excluded from analysis. As a whole, our results show that the abundance and community composition of honey bee gut microbiota is associated with winter hive loss, and can potentially be used as a diagnostic tool in evaluating hive health prior to the onset of winter. Future work on the functional characterization of the honey bee gut microbiome's role in winter survival is warranted.

Investigating the causal relationship of gut microbiota with GERD and BE: a bidirectional mendelian randomization.

BACKGROUND: Gut microbiota(GM) have been proven associated with lots of gastrointestinal diseases, but its causal relationship with Gastroesophageal reflux disease(GERD) and Barrett's esophagus(BE) hasn't been explored. We aimed to uncover the causal relation between GM and GERD/BE and potential mediators by utilizing Mendelian Randomization(MR) analysis. METHODS: Summary statistics of GM(comprising 301 bacteria taxa and 205 metabolism pathways) were extracted from MiBioGen Consortium(N = 18,340) and Dutch Microbiome Project(N = 7,738), GERD and BE from a multitrait meta-analysis(NGERD=602,604, NBE=56,429). Bidirectional two-sample MR analysis and linkage disequilibrium score regression(LDSC) were used to explore the genetic correlation between GM and GERD/BE. Mediation MR analysis was performed for the risk factors of GERD/BE, including Body mass index(BMI), weight, type 2 diabetes, major depressive disorder(MDD), smoking initiation, alcohol consumption, and dietary intake(including carbohydrate, sugar, fat, protein intake), to detect the potential mediators between GM and GERD/BE. RESULTS: 11 bacterial taxa and 13 metabolism pathways were found associated with GERD, and 18 taxa and 5 pathways exhibited causal relationship with BE. Mediation MR analysis suggested weight and BMI played a crucial role in these relationships. LDSC identified 1 taxon and 4 metabolism pathways related to GERD, and 1 taxon related to BE. Specie Faecalibacterium prausnitzii had a suggestive impact on both GERD(OR = 1.087, 95%CI = 1.01-1.17) and BE(OR = 1.388, 95%CI = 1.03-1.86) and LDSC had determined their correlation. Reverse MR indicated that BE impacted 10 taxa and 4 pathways. CONCLUSIONS: This study established a causal link between gut microbiota and GERD/BE, and identified the probable mediators. It offers new insights into the role of gut microbiota in the development and progression of GERD and BE in the host.

Genetically determined gut microbiota associates with pulmonary arterial hypertension: a Mendelian randomization study.

BACKGROUND: Emerging evidences have demonstrated that gut microbiota composition is associated with pulmonary arterial hypertension (PAH). However, the underlying causality between intestinal dysbiosis and PAH remains unresolved. METHOD: An analysis using the two-sample Mendelian randomization (MR) approach was conducted to examine the potential causal relationship between gut microbiota and PAH. To assess exposure data, genetic variants associated with 196 bacterial traits were extracted from the MiBioGen consortium, which included a sample size of 18,340 individuals. As for the outcomes, summary statistics for PAH were obtained from the NHGRI-EBI GWAS Catalog, which conducted a meta-analysis of four independent studies comprising a total of 11,744 samples. Causal effects were estimated employing various methods, including inverse variance weighted (IVW), MR-Egger, weighted median, weight mode and simple mode, with sensitivity analyses also being implemented with Cochran's Q test, MR-Egger intercept test, MR-PRESSO, leave-one-out analysis, and funnel plots. RESULTS: Following false discovery rate (FDR) correction, the genetically predicted genus Eubacterium fissicatena group (odds ratio (OR) 1.471, 95% confidence interval (CI) 1.178-1.837, q = 0.076) exhibited a causal association with PAH. In addition, the genus LachnospiraceaeUCG004 (OR 1.511, 95% CI 1.048-2.177) and genus RuminococcaceaeUCG002 (OR 1.407, 95% CI 1.040-1.905) showed a suggestive increased risk of PAH, while genus Eubacterium eligens group (OR 0.563, 95% CI 0.344-0.922), genus Phascolarctobacterium (OR 0.692, 95% CI 0.487-0.982), genus Erysipelatoclostridium (OR 0.757, 95% CI 0.579-0.989) and genus T-yzzerella3 (OR 0.768, 95% CI 0.624-0.945) were found to have nominal protective effect against PAH. CONCLUSION: The findings from our MR study have revealed a potential causal relationship between gut microbiota and PAH. Specifically, we have identified four types of gut microbiota that exhibit a protective effect on PAH, as well as three types that have a detrimental impact on PAH, thereby offering valuable insights for future mechanistic and clinical investigations in the field of PAH.

Association between gut microbiota and spinal stenosis: a two-sample mendelian randomization study.

Introduction: Considerable evidence has unveiled a potential correlation between gut microbiota and spinal degenerative diseases. However, only limited studies have reported the direct association between gut microbiota and spinal stenosis. Hence, in this study, we aimed to clarify this relationship using a two-sample mendelian randomization (MR) approach. Materials and Methods: Data for two-sample MR studies was collected and summarized from genome-wide association studies (GWAS) of gut microbiota (MiBioGen, n = 13, 266) and spinal stenosis (FinnGen Biobank, 9, 169 cases and 164, 682 controls). The inverse variance-weighted meta-analysis (IVW), complemented with weighted median, MR-Egger, weighted mode, and simple mode, was used to elucidate the causality between gut microbiota and spinal stenosis. In addition, we employed mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) and the MR-Egger intercept test to assess horizontal multiplicity. Cochran's Q test to evaluate heterogeneity, and "leave-one-out" sensitivity analysis to determine the reliability of causality. Finally, an inverse MR analysis was performed to assess the reverse causality. Results: The IVW results indicated that two gut microbial taxa, the genus Eubacterium fissicatena group and the genus Oxalobacter, have a potential causal relationship with spinal stenosis. Moreover, eight potential associations between genetic liability of the gut microbiota and spinal stenosis were implied. No significant heterogeneity of instrumental variables or horizontal pleiotropy were detected. In addition, "leave-one-out" sensitivity analysis confirmed the reliability of causality. Finally, the reverse MR analysis revealed that no proof to substantiate the discernible causative relationship between spinal stenosis and gut microbiota. Conclusion: This analysis demonstrated a possible causal relationship between certain particular gut microbiota and the occurrence of spinal stenosis. Further studies focused on the mechanism of gut microbiota-mediated spinal stenosis can lay the groundwork for targeted prevention, monitoring, and treatment of spinal stenosis.

Genome plasticity shapes the ecology and evolution of Phocaeicola dorei and Phocaeicola vulgatus.

Phocaeicola dorei and Phocaeicola vulgatus are very common and abundant members of the human gut microbiome and play an important role in the infant gut microbiome. These species are closely related and often confused for one another; yet, their genome comparison, interspecific diversity, and evolutionary relationships have not been studied in detail so far. Here, we perform phylogenetic analysis and comparative genomic analyses of these two Phocaeicola species. We report that P. dorei has a larger genome yet a smaller pan-genome than P. vulgatus. We found that this is likely because P. vulgatus is more plastic than P. dorei, with a larger repertoire of genetic mobile elements and fewer anti-phage defense systems. We also found that P. dorei directly descends from a clade of P. vulgatus¸ and experienced genome expansion through genetic drift and horizontal gene transfer. Overall, P. dorei and P. vulgatus have very different functional and carbohydrate utilisation profiles, hinting at different ecological strategies, yet they present similar antimicrobial resistance profiles.

The causality of gut microbiota on onset and progression of sepsis: a bi-directional Mendelian randomization analysis.

Background: Several observational studies have proposed a potential link between gut microbiota and the onset and progression of sepsis. Nevertheless, the causality of gut microbiota and sepsis remains debatable and warrants more comprehensive exploration. Methods: We conducted a two-sample Mendelian randomization (MR) analysis to test the causality between gut microbiota and the onset and progression of sepsis. The genome-wide association study (GWAS) summary statistics for 196 bacterial traits were extracted from the MiBioGen consortium, whereas the GWAS summary statistics for sepsis and sepsis-related outcomes came from the UK Biobank. The inverse-variance weighted (IVW) approach was the primary method used to examine the causal association. To complement the IVW method, we utilized four additional MR methods. We performed a series of sensitivity analyses to examine the robustness of the causal estimates. Results: We assessed the causality of 196 bacterial traits on sepsis and sepsis-related outcomes. Genus Coprococcus2 [odds ratio (OR) 0.81, 95% confidence interval (CI) (0.69-0.94), p = 0.007] and genus Dialister (OR 0.85, 95% CI 0.74-0.97, p = 0.016) had a protective effect on sepsis, whereas genus Ruminococcaceae UCG011 (OR 1.10, 95% CI 1.01-1.20, p = 0.024) increased the risk of sepsis. When it came to sepsis requiring critical care, genus Anaerostipes (OR 0.49, 95% CI 0.31-0.76, p = 0.002), genus Coprococcus1 (OR 0.65, 95% CI 0.43-1.00, p = 0.049), and genus Lachnospiraceae UCG004 (OR 0.51, 95% CI 0.34-0.77, p = 0.001) emerged as protective factors. Concerning 28-day mortality of sepsis, genus Coprococcus1 (OR 0.67, 95% CI 0.48-0.94, p = 0.020), genus Coprococcus2 (OR 0.48, 95% CI 0.27-0.86, p = 0.013), genus Lachnospiraceae FCS020 (OR 0.70, 95% CI 0.52-0.95, p = 0.023), and genus Victivallis (OR 0.82, 95% CI 0.68-0.99, p = 0.042) presented a protective effect, whereas genus Ruminococcus torques group (OR 1.53, 95% CI 1.00-2.35, p = 0.049), genus Sellimonas (OR 1.25, 95% CI 1.04-1.50, p = 0.019), and genus Terrisporobacter (OR 1.43, 95% CI 1.02-2.02, p = 0.040) presented a harmful effect. Furthermore, genus Coprococcus1 (OR 0.42, 95% CI 0.19-0.92, p = 0.031), genus Coprococcus2 (OR 0.34, 95% CI 0.14-0.83, p = 0.018), and genus Ruminiclostridium6 (OR 0.43, 95% CI 0.22-0.83, p = 0.012) were associated with a lower 28-day mortality of sepsis requiring critical care. Conclusion: This MR analysis unveiled a causality between the 21 bacterial traits and sepsis and sepsis-related outcomes. Our findings may help the development of novel microbiota-based therapeutics to decrease the morbidity and mortality of sepsis.

Exploring the casual association between gut microbiome, circulating inflammatory cytokines and chronic pancreatitis: A Mendelian randomization analysis.

It has been established that gut dysbiosis contributed to the pathogenesis of digestive disorders. We aimed to explore the causal relationships between intestinal microbiota, circulating inflammatory cytokines and chronic pancreatitis (CP). Summary statistics of genome-wide association studies (GWAS) of intestinal microbiome was retrieved from the MiBioGen study and the GWAS data of 91 circulating inflammatory cytokines and CP were obtained from the GWAS catalog. The 2-sample bidirectional Mendelian randomization (MR) analysis was performed between gut microbiota, circulating inflammatory cytokines and CP, in which the inverse variance weighted (IVW) method was regarded as the primary analysis approach. To prove the reliability of the causal estimations, multiple sensitivity analyses were utilized. IVW results revealed that genetically predicted 2 genera, including Sellimonas and Eubacteriumventriosumgroup, and plasm C-C motif chemokine 23 (CCL23) level were positively associated with CP risk, while genus Escherichia Shigella, Eubacteriumruminantiumgroup and Prevotella9, and plasma Caspase 8, Adenosine Deaminase (ADA), and SIR2-like protein 2 (SIRT2) level, demonstrated an ameliorative effect on CP. Leave-one-out analysis confirmed the robustness of the aforementioned causal effects and no significant horizontal pleiotropy or heterogeneity of the instrumental variables was detected. However, no association was found from the identified genera to the CP-related circulating inflammatory cytokines. Besides, the reverse MR analysis demonstrated no causal relationship from CP to the identified genera and circulating inflammatory cytokines. Taken together, our comprehensive analyses offer evidence in favor of the estimated causal connections from the 5 genus-level microbial taxa and 4 circulating inflammatory cytokines to CP risk, which may help to reveal the underlying pathogenesis of CP.

Designing function-specific minimal microbiomes from large microbial communities.

Microorganisms exist in large communities of diverse species, exhibiting various functionalities. The mammalian gut microbiome, for instance, has the functionality of digesting dietary fibre and producing different short-chain fatty acids. Not all microbes present in a community contribute to a given functionality; it is possible to find a minimal microbiome, which is a subset of the large microbiome, that is capable of performing the functionality while maintaining other community properties such as growth rate and metabolite production. Such a minimal microbiome will also contain keystone species for SCFA production in that community. In this work, we present a systematic constraint-based approach to identify a minimal microbiome from a large community for a user-proposed function. We employ a top-down approach with sequential deletion followed by solving a mixed-integer linear programming problem with the objective of minimising the L1-norm of the membership vector. Notably, we consider quantitative measures of community growth rate and metabolite production rates. We demonstrate the utility of our algorithm by identifying the minimal microbiomes corresponding to three model communities of the gut, and discuss their validity based on the presence of the keystone species in the community. Our approach is generic, flexible and finds application in studying a variety of microbial communities. The algorithm is available from https://github.com/RamanLab/minMicrobiome .

Unveiling the gut bacteriome diversity and distribution in the national fish hilsa (Tenualosa ilisha) of Bangladesh.

The field of fish microbiome research has rapidly been advancing, primarily focusing on farmed or laboratory fish species rather than natural or marine fish populations. This study sought to reveal the distinctive gut bacteriome composition and diversity within the anadromous fish species Tenualosa ilisha (hilsa), which holds the status of being the national fish of Bangladesh. We conducted an analysis on 15 gut samples obtained from 15 individual hilsa fishes collected from three primary habitats (e.g., freshwater = 5, brackish water = 5 and marine water = 5) in Bangladesh. The analysis utilized metagenomics based on 16S rRNA gene sequencing targeting the V3-V4 regions. Our comprehensive identification revealed a total of 258 operational taxonomic units (OTUs). The observed OTUs were represented by six phyla, nine classes, 19 orders, 26 families and 40 genera of bacteria. Our analysis unveiled considerable taxonomic differences among the habitats (freshwater, brackish water, and marine water) of hilsa fishes, as denoted by a higher level of shared microbiota (p = 0.007, Kruskal-Wallis test). Among the identified genera in the gut of hilsa fishes, including Vagococcus, Morganella, Enterobacter, Plesiomonas, Shigella, Clostridium, Klebsiella, Serratia, Aeromonas, Macrococcus, Staphylococcus, Proteus, and Hafnia, several are recognized as fish probiotics. Importantly, some bacterial genera such as Sinobaca, Synechococcus, Gemmata, Serinicoccus, Saccharopolyspora, and Paulinella identified in the gut of hilsa identified in this study have not been reported in any aquatic or marine fish species. Significantly, we observed that 67.50% (27/40) of bacterial genera were found to be common among hilsa fishes across all three habitats. Our findings offer compelling evidence for the presence of both exclusive and communal bacteriomes within the gut of hilsa fishes, exhibiting potential probiotic properties. These observations could be crucial for guiding future microbiome investigations in this economically significant fish species.

Genetic association between gut microbiota and the risk of Guillain-Barré syndrome.

BACKGROUND: Guillain-Barré Syndrome (GBS) is an autoimmune disease that typically develops after a previous gastrointestinal (GI) infection. However, the exact association between Gut Microbiota (GM) and GBS still remains unknown due to various challenges. This study aimed to investigate the potential causal association between GM and GBS by using a two-sample Mendelian Randomization (TSMR) analysis. METHODS: Utilizing the largest available genome-wide association study (GWAS) meta-analysis from the MiBioGen consortium (n = 13,266) as a foundation, we conducted a TSMR to decipher the causal relationship between GM and GBS. Various analytical methods were employed, including the inverse variance weighted (IVW), MR-PRESSO, MR-Egger, and weighted median. The heterogeneity of instrumental variables (IVs) was assessed using Cochran's Q statistics. RESULTS: The analysis identified three microbial taxa with a significantly increased risk association for GBS, including Ruminococcus gnavus group (OR = 1.40, 95 % CI: 1.07-1.83), Ruminococcus gauvreauii group (OR = 1.51, 95 % CI: 1.02-2.25), and Ruminococcaceae UCG009 (OR = 1.42, 95 % CI: 1.02-1.97), while Eubacterium brachy group (OR = 1.44, 95 % CI: 1.10-1.87) and Romboutsia (OR = 1.67, 95 % CI: 1.12-2.47) showed a suggestively causal association. On the other hand, Ruminococcaceae UCG004 (OR = 0.61, 95 % CI: 0.41-0.91) had a protective effect on GBS, while Bacilli (OR = 0.60, 95 % CI: 0.38-0.96), Gamma proteobacteria (OR = 0.63, 95 % CI: 0.41-0.98) and Lachnospiraceae UCG001 (OR = 0.69, 95 % CI: 0.49-0.96) showed a suggestively protective association for GBS. CONCLUSION: The MR analysis suggests a potential causal relationship between specific GM taxa and the risk of GBS. However, further extensive research involving diversified populations is imperative to validate these findings.

Co-occurrence patterns of gut microbiome, antibiotic resistome and the perturbation of dietary uptake in captive giant pandas.

The microbiome is a key source of antibiotic resistance genes (ARGs), significantly influenced by diet, which highlights the interconnectedness between diet, gut microbiome, and ARGs. Currently, our understanding is limited on the co-occurrence among gut microbiome, antibiotic resistome in the captive giant panda and the perturbation of dietary uptake, especially for the composition and forms in dietary nutrition. Here, a qPCR array with 384 primer sets and 16 S rRNA gene amplicon sequencing were used to characterize the antibiotic resistome and microbiomes in panda feces, dietary bamboo, and soil around the habitat. Diet nutrients containing organic and mineral substances in soluble and insoluble forms were also quantified. Organic and mineral components in water-unextractable fractions were 7.5 to 139 and 637 to 8695 times higher than those in water-extractable portions in bamboo and feces, respectively, while the latter contributed more to the variation (67.5 %) of gut microbiota. Streptococcus, Prevotellaceae, and Bacteroides were the dominant genera in giant pandas. The ARG patterns in panda guts showed higher diversity in old individuals but higher abundance in young ones, driven directly by the bacterial community change and mobile genetic element mediation and indirectly by dietary intervention. Our results suggest that dietary nutrition mainly accounts for the shift of gut microbiota, while bacterial community and mobile genetic elements influenced the variation of gut antibiotic resistome.

Exploring causality in the association between gut microbiota and irritable bowel syndrome risk: a large Mendelian randomization study.

BACKGROUND: In the past, some observational studies have highlighted the correlation between gut microbiota and irritable bowel syndrome (IBS). However, it is still unknown if the composition of gut microbiota shows a causal effect on the risk of IBS. AIM: To conduct Mendelian randomization (MR) analysis of the samples to study the probable causal relationship between the gut microbiota, their taxonomic groups, and the risk of IBS. MATERIALS AND METHODS: In this study, the summarized data regarding 211 gut microbiota and their IBS genome-wide association studies (GWAS) were collected from public databases. The causal estimates were determined using five MR techniques, where Inverse Variance Weighted (IVW) regression was employed as the major MR technique. Herein, MR-PRESSO and MR-Egger intercept tests were conducted to prevent horizontal pleiotropy. Cochran's Q test was used to evaluate heterogeneity using the IVW and MR-Egger techniques. RESULTS: IVW results showed that gut microbes, belonging to Class Gammaproteobacteria (P = 0.04; OR = 1.45), Family XIII (P = 0.03; OR = 1.34), Family Prevotellaceae (P = 0.003; OR =1.24), and Lachnospiraceae UCG004 (P = 0.049; OR = 1.19) increased the risk of IBS, while Alcaligenaceae (P = 0.03; OR = 0.83, 95% CI: 0.69-0.98) and Coprobacter (P = 0.02; OR = 0.86, 95% CI: 0.76-0.98) decreased the risk of IBS. CONCLUSIONS: This study presented novel insights that highlighted the causal relationship between gut microbiota and IBS, and offered new treatment strategies for preventing or treating IBS.

Atherosclerosis, gut microbiome, and exercise in a meta-omics perspective: a literature review.

Background: Cardiovascular diseases are the leading cause of death worldwide, significantly impacting public health. Atherosclerotic cardiovascular diseases account for the majority of these deaths, with atherosclerosis marking the initial and most critical phase of their pathophysiological progression. There is a complex relationship between atherosclerosis, the gut microbiome's composition and function, and the potential mediating role of exercise. The adaptability of the gut microbiome and the feasibility of exercise interventions present novel opportunities for therapeutic and preventative approaches. Methodology: We conducted a comprehensive literature review using professional databases such as PubMed and Web of Science. This review focuses on the application of meta-omics techniques, particularly metagenomics and metabolomics, in studying the effects of exercise interventions on the gut microbiome and atherosclerosis. Results: Meta-omics technologies offer unparalleled capabilities to explore the intricate connections between exercise, the microbiome, the metabolome, and cardiometabolic health. This review highlights the advancements in metagenomics and metabolomics, their applications in research, and examines how exercise influences the gut microbiome. We delve into the mechanisms connecting these elements from a metabolic perspective. Metagenomics provides insight into changes in microbial strains post-exercise, while metabolomics sheds light on the shifts in metabolites. Together, these approaches offer a comprehensive understanding of how exercise impacts atherosclerosis through specific mechanisms. Conclusions: Exercise significantly influences atherosclerosis, with the gut microbiome serving as a critical intermediary. Meta-omics technology holds substantial promise for investigating the gut microbiome; however, its methodologies require further refinement. Additionally, there is a pressing need for more extensive cohort studies to enhance our comprehension of the connection among these element.

Integrative metagenomic analysis reveals distinct gut microbial signatures related to obesity.

Obesity is a metabolic disorder closely associated with profound alterations in gut microbial composition. However, the dynamics of species composition and functional changes in the gut microbiome in obesity remain to be comprehensively investigated. In this study, we conducted a meta-analysis of metagenomic sequencing data from both obese and non-obese individuals across multiple cohorts, totaling 1351 fecal metagenomes. Our results demonstrate a significant decrease in both the richness and diversity of the gut bacteriome and virome in obese patients. We identified 38 bacterial species including Eubacterium sp. CAG:274, Ruminococcus gnavus, Eubacterium eligens and Akkermansia muciniphila, and 1 archaeal species, Methanobrevibacter smithii, that were significantly altered in obesity. Additionally, we observed altered abundance of five viral families: Mesyanzhinovviridae, Chaseviridae, Salasmaviridae, Drexlerviridae, and Casjensviridae. Functional analysis of the gut microbiome indicated distinct signatures associated to obesity and identified Ruminococcus gnavus as the primary driver for function enrichment in obesity, and Methanobrevibacter smithii, Akkermansia muciniphila, Ruminococcus bicirculans, and Eubacterium siraeum as functional drivers in the healthy control group. Additionally, our results suggest that antibiotic resistance genes and bacterial virulence factors may influence the development of obesity. Finally, we demonstrated that gut vOTUs achieved a diagnostic accuracy with an optimal area under the curve of 0.766 for distinguishing obesity from healthy controls. Our findings offer comprehensive and generalizable insights into the gut bacteriome and virome features associated with obesity, with the potential to guide the development of microbiome-based diagnostics.

Gut microbiome composition reveals the distinctiveness between the Bengali people and the Indigenous ethnicities in Bangladesh.

Ethnicity has a significant role in shaping the composition of the gut microbiome, which has implications in human physiology. This study intends to investigate the gut microbiome of Bengali people as well as several indigenous ethnicities (Chakma, Marma, Khyang, and Tripura) residing in the Chittagong Hill Tracts areas of Bangladesh. Following fecal sample collection from each population, part of the bacterial 16 s rRNA gene was amplified and sequenced using Illumina NovaSeq platform. Our findings indicated that Bangladeshi gut microbiota have a distinct diversity profile when compared to other countries. We also found out that Bangladeshi indigenous communities had a higher Firmicutes to Bacteroidetes ratio than the Bengali population. The investigation revealed an unclassified bacterium that was differentially abundant in Bengali samples while the genus Alistipes was found to be prevalent in Chakma samples. Further research on these bacteria might help understand diseases associated with these populations. Also, the current small sample-sized pilot study hindered the comprehensive understanding of the gut microbial diversity of the Bangladeshi population and its potential health implications. However, our study will help establish a basic understanding of the gut microbiome of the Bangladeshi population.