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.

A comparative study of supervised and unsupervised machine learning algorithms applied to human microbiome.

Background: The human microbiome, consisting of diverse bacte-rial, fungal, protozoan and viral species, exerts a profound influence on various physiological processes and disease susceptibility. However, the complexity of microbiome data has presented significant challenges in the analysis and interpretation of these intricate datasets, leading to the development of specialized software that employs machine learning algorithms for these aims. Methods: In this paper, we analyze raw data taken from 16S rRNA gene sequencing from three studies, including stool samples from healthy control, patients with adenoma, and patients with colorectal cancer. Firstly, we use network-based methods to reduce dimensions of the dataset and consider only the most important features. In addition, we employ supervised machine learning algorithms to make prediction. Results: Results show that graph-based techniques reduces dimen-sion from 255 up to 78 features with modularity score 0.73 based on different centrality measures. On the other hand, projection methods (non-negative matrix factorization and principal component analysis) reduce dimensions to 7 features. Furthermore, we apply supervised machine learning algorithms on the most important features obtained from centrality measures and on the ones obtained from projection methods, founding that the evaluation metrics have approximately the same scores when applying the algorithms on the entire dataset, on 78 feature and on 7 features. Conclusions: This study demonstrates the efficacy of graph-based and projection methods in the interpretation for 16S rRNA gene sequencing data. Supervised machine learning on refined features from both approaches yields comparable predictive performance, emphasizing specific microbial features-bacteroides, prevotella, fusobacterium, lysinibacillus, blautia, sphingomonas, and faecalibacterium-as key in predicting patient conditions from raw data.

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.

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 causal relationship between gut microbiota and lymphoma: a two-sample Mendelian randomization study.

Background: Previous studies have indicated a potential link between the gut microbiota and lymphoma. However, the exact causal interplay between the two remains an area of ambiguity. Methods: We performed a two-sample Mendelian randomization (MR) analysis to elucidate the causal relationship between gut microbiota and five types of lymphoma. The research drew upon microbiome data from a research project of 14,306 participants and lymphoma data encompassing 324,650 cases. Single-nucleotide polymorphisms were meticulously chosen as instrumental variables according to multiple stringent criteria. Five MR methodologies, including the inverse variance weighted approach, were utilized to assess the direct causal impact between the microbial exposures and lymphoma outcomes. Moreover, sensitivity analyses were carried out to robustly scrutinize and validate the potential presence of heterogeneity and pleiotropy, thereby ensuring the reliability and accuracy. Results: We discerned 38 potential causal associations linking genetic predispositions within the gut microbiome to the development of lymphoma. A few of the more significant results are as follows: Genus Coprobacter (OR = 0.619, 95% CI 0.438-0.873, P = 0.006) demonstrated a potentially protective effect against Hodgkin's lymphoma (HL). Genus Alistipes (OR = 0.473, 95% CI 0.278-0.807, P = 0.006) was a protective factor for diffuse large B-cell lymphoma. Genus Ruminococcaceae (OR = 0.541, 95% CI 0.341-0.857, P = 0.009) exhibited suggestive protective effects against follicular lymphoma. Genus LachnospiraceaeUCG001 (OR = 0.354, 95% CI 0.198-0.631, P = 0.0004) showed protective properties against T/NK cell lymphoma. The Q test indicated an absence of heterogeneity, and the MR-Egger test did not show significant horizontal polytropy. Furthermore, the leave-one-out analysis failed to identify any SNP that exerted a substantial influence on the overall results. Conclusion: Our study elucidates a definitive causal link between gut microbiota and lymphoma development, pinpointing specific microbial taxa with potential causative roles in lymphomagenesis, as well as identifying probiotic candidates that may impact disease progression, which provide new ideas for possible therapeutic approaches to lymphoma and clues to the pathogenesis of lymphoma.

Alpha Diversity Indices as Indicators of the Variability of Gut Microbiota in Obese Adolescents of Different Ethnicities.

We compared alpha diversity indices of the intestinal microbiota in adolescents with obesity and normal body weight, taking into account their ethnicity. Intestinal biocenosis was studied by metasequencing of amplicon libraries of V3-V4 fragments of the 16S rRNA gene. The alpha diversity of the microbiota was assessed using classical and alternative indices. Statistically significant differences in intestinal microbiota were observed between Russians with obesity and Buryats with normal body weight, as well as between Russians with obesity and Buryats with obesity when assessing the Shannon-Weaver, Chao1 indices, Faith phylogenetic diversity index, ACE, Fisher, Gini coefficient, Margalef, and Menkhinik indices. It was shown that alpha diversity indices can be used to assess significance of differences and variability of the intestinal microbiota in multifactorial diseases such as obesity in adolescents; however, the scope of application of the criteria should be considered.

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.

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.

Readsynth: short-read simulation for consideration of composition-biases in reduced metagenome sequencing approaches.

BACKGROUND: The application of reduced metagenomic sequencing approaches holds promise as a middle ground between targeted amplicon sequencing and whole metagenome sequencing approaches but has not been widely adopted as a technique. A major barrier to adoption is the lack of read simulation software built to handle characteristic features of these novel approaches. Reduced metagenomic sequencing (RMS) produces unique patterns of fragmentation per genome that are sensitive to restriction enzyme choice, and the non-uniform size selection of these fragments may introduce novel challenges to taxonomic assignment as well as relative abundance estimates. RESULTS: Through the development and application of simulation software, readsynth, we compare simulated metagenomic sequencing libraries with existing RMS data to assess the influence of multiple library preparation and sequencing steps on downstream analytical results. Based on read depth per position, readsynth achieved 0.79 Pearson's correlation and 0.94 Spearman's correlation to these benchmarks. Application of a novel estimation approach, fixed length taxonomic ratios, improved quantification accuracy of simulated human gut microbial communities when compared to estimates of mean or median coverage. CONCLUSIONS: We investigate the possible strengths and weaknesses of applying the RMS technique to profiling microbial communities via simulations with readsynth. The choice of restriction enzymes and size selection steps in library prep are non-trivial decisions that bias downstream profiling and quantification. The simulations investigated in this study illustrate the possible limits of preparing metagenomic libraries with a reduced representation sequencing approach, but also allow for the development of strategies for producing and handling the sequence data produced by this promising application.

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.

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 .

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.

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.

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.

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.

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.

The causal relationship between gut microbiota and biliary tract cancer: comprehensive bidirectional Mendelian randomization analysis.

Background: Growing evidence has shown that gut microbiome composition is associated with Biliary tract cancer (BTC), but the causality remains unknown. This study aimed to explore the causal relationship between gut microbiota and BTC, conduct an appraisal of the gut microbiome's utility in facilitating the early diagnosis of BTC. Methods: We acquired the summary data for Genome-wide Association Studies (GWAS) pertaining to BTC (418 cases and 159,201 controls) from the Biobank Japan (BBJ) database. Additionally, the GWAS summary data relevant to gut microbiota (N = 18,340) were sourced from the MiBioGen consortium. The primary methodology employed for the analysis consisted of Inverse Variance Weighting (IVW). Evaluations for sensitivity were carried out through the utilization of multiple statistical techniques, encompassing Cochrane's Q test, the MR-Egger intercept evaluation, the global test of MR-PRESSO, and a leave-one-out methodological analysis. Ultimately, a reverse Mendelian Randomization analysis was conducted to assess the potential for reciprocal causality. Results: The outcomes derived from IVW substantiated that the presence of Family Streptococcaceae (OR = 0.44, P = 0.034), Family Veillonellaceae (OR = 0.46, P = 0.018), and Genus Dorea (OR = 0.29, P = 0.041) exerted a protective influence against BTC. Conversely, Class Lentisphaeria (OR = 2.21, P = 0.017), Genus Lachnospiraceae FCS020 Group (OR = 2.30, P = 0.013), and Order Victivallales (OR = 2.21, P = 0.017) were associated with an adverse impact. To assess any reverse causal effect, we used BTC as the exposure and the gut microbiota as the outcome, and this analysis revealed associations between BTC and five different types of gut microbiota. The sensitivity analysis disclosed an absence of empirical indicators for either heterogeneity or pleiotropy. Conclusion: This investigation represents the inaugural identification of indicative data supporting either beneficial or detrimental causal relationships between gut microbiota and the risk of BTC, as determined through the utilization of MR methodologies. These outcomes could hold significance for the formulation of individualized therapeutic strategies aimed at BTC prevention and survival enhancement.