Distinct biogeographical patterns in snail gastrointestinal tract bacterial communities compared with sediment and water.

The factors that influence the distribution of bacterial community composition are not well understood. The role of geographical patterns, which suggest limited dispersal, is still a topic of debate. Bacteria associated with hosts face unique dispersal challenges as they often rely on their hosts, which provide specific environments for their symbionts. In this study, we examined the effect of biogeographic distances on the bacterial diversity and composition of bacterial communities in the gastrointestinal tract of Ampullaceana balthica. We compared the effects on the host-associated bacterial community to those on bacterial communities in water and sediment. This comparison was made using 16S ribosomal RNA gene sequencing. We found that the bacterial communities we sampled in Estonia, Denmark, and Northern Germany varied between water, sediment, and the gastrointestinal tract. They also varied between countries within each substrate. This indicates that the type of substrate is a dominant factor in determining bacterial community composition. We separately analyzed the turnover rates of water, sediment, and gastrointestinal bacterial communities over increasing geographic distances. We observed that the turnover rate was lower for gastrointestinal bacterial communities compared to water bacterial communities. This implies that the composition of gastrointestinal bacteria remains relatively stable over distances, while water bacterial communities exhibit greater variability. However, the gastrointestinal tract had the lowest percentage of country-specific amplicon sequence variants, suggesting bacterial colonization from local bacterial communities. Since the overlap between the water and gastrointestinal tract was highest, it appears that the gastrointestinal bacterial community is colonized by the water bacterial community. Our study confirmed that biogeographical patterns in host-associated communities differ from those in water and sediment bacterial communities. These host-associated communities consist of numerous facultative symbionts derived from the water bacterial community.

Characterization of the intestinal microbiota in MSM with HIV infection.

BACKGROUND: HIV-infected persons demonstrate notable disturbances in their intestinal microbiota; however, the impact of intestinal microbiota on HIV susceptibility in men who have sex with men (MSM), as well as the effects of HIV and antiretroviral therapy (ART) on their gut microbiota, remains under active study. Thus, our research focuses on clarifying the distinctions in intestinal microbiota composition among uninfected MSM and non-MSM healthy controls, investigating the alterations in early-stage intestinal microbial communities following HIV infection, and assessing how ART affects the intestinal microbiota. METHODS: This study enrolled four participant groups: uninfected MSM, Recent HIV-1 infection (RHI) MSM, MSM on ART, and non-MSM healthy controls, with 30 individuals in each group. We utilized 16S ribosomal DNA (16S rDNA) amplicon sequencing to analyze fecal microbiota and employed Luminex multiplex assays to measure plasma markers for microbial translocation (LBP, sCD14) and the inflammatory marker CRP. FINDINGS: Comparing uninfected MSM to non-MSM healthy controls, no substantial variances were observed in α and ß diversity. Uninfected MSM had higher average relative abundances of Bacteroidetes, Prevotella, and Alloprevotella, while Bacteroides, Firmicutes, and Faecalibacterium had lower average relative abundances. MSM on ART had lower intestinal microbiota diversity than RHI MSM and uninfected MSM. In MSM on ART, Megasphaera and Fusobacterium increased, while Faecalibacterium and Roseburia decreased at genus level. Additionally, treatment with a non-nucleoside reverse transcriptase inhibitor (NNRTI) led to significant alterations in intestinal microbiota diversity and composition compared to RHI MSM. The random forest model showed that HIV infection biomarkers effectively distinguished between newly diagnosed HIV-infected MSM and HIV-negative MSM, with an ROC AUC of 76.24% (95% CI: 61.17-91.31%). CONCLUSIONS: MSM showed early intestinal microbiota imbalances after new HIV infection. MSM on ART experienced worsened dysbiosis, indicating a combined effect of HIV and ART. NNRTI-based treatment notably changed intestinal microbiota, suggesting a potential direct impact of NNRTI drugs on intestinal microbiota.

Longitudinal multicompartment characterization of host-microbiota interactions in patients with acute respiratory failure.

Critical illness can significantly alter the composition and function of the human microbiome, but few studies have examined these changes over time. Here, we conduct a comprehensive analysis of the oral, lung, and gut microbiota in 479 mechanically ventilated patients (223 females, 256 males) with acute respiratory failure. We use advanced DNA sequencing technologies, including Illumina amplicon sequencing (utilizing 16S and ITS rRNA genes for bacteria and fungi, respectively, in all sample types) and Nanopore metagenomics for lung microbiota. Our results reveal a progressive dysbiosis in all three body compartments, characterized by a reduction in microbial diversity, a decrease in beneficial anaerobes, and an increase in pathogens. We find that clinical factors, such as chronic obstructive pulmonary disease, immunosuppression, and antibiotic exposure, are associated with specific patterns of dysbiosis. Interestingly, unsupervised clustering of lung microbiota diversity and composition by 16S independently predicted survival and performed better than traditional clinical and host-response predictors. These observations are validated in two separate cohorts of COVID-19 patients, highlighting the potential of lung microbiota as valuable prognostic biomarkers in critical care. Understanding these microbiome changes during critical illness points to new opportunities for microbiota-targeted precision medicine interventions.

Association between the gut microbiota and diabetic nephropathy: a two-sample Mendelian randomization study.

Numerous studies have revealed a correlation between the risk of developing diabetic nephropathy (DN) and the gut microbiota (GM) composition. However, it remains uncertain whether the GM composition causes DN. We aimed to explore any potential causal links between the GM composition and the risk of developing DN. A meta-analysis conducted by the MiBioGen consortium of the largest genome-wide association study (GWAS) provided aggregated data on the GM. DN data were obtained from the IEU database. The inverse-variance weighting (IVW) method was employed as the primary analytical approach. The IVW analysis indicated that genus Dialister (OR = 0.51, 95% CI: 0.34-0.77, p = 0.00118) was protective against DN. In addition, class Gammaproteobacteria (OR = 0.47, 95% CI: 0.27-0.83, p = 0.0096), class Lentisphaeria (OR =0.76, 95% CI: 0.68-0.99, p = 0.04), order Victivallales (OR = 0.76, 95% CI: 0.58-0.99, p = 0.04), and phylum Proteobacteria (OR = 0.53, 95% CI: 0.33-0.85, p = 0.00872) were negatively associated with the risk of developing DN. Genus LachnospiraceaeUCG008 (OR =1.45, 95% CI: 1.08-1.95, p = 0.01), order Bacteroidales (OR = 1.59, 95% CI: 1.02-2.49, p = 0.04), and genus Terrisporobacter (OR = 1.98, 95% CI: 1.14-3.45, p = 0.015) were positively associated with the risk of developing DN. In this study, we established a causal relationship between the genus Dialister and the risk of developing DN. Further trials are required to confirm the protective effects of probiotics on DN and to elucidate the precise protective mechanisms involving genus Dialister and DN.

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.

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.

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.

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.

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.

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.

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.

Contrasting gut bacteriomes unveiled between wild Antheraea assamensis Helfer (Lepidoptera: Saturniidae) and domesticated Bombyx mori L. (Lepidoptera: Bombycidae) silkworms.

BACKGROUND: Insect gut microbiomes play a fundamental role in various aspects of insect physiology, including digestion, nutrient metabolism, detoxification, immunity, growth and development. The wild Muga silkworm, Antheraea assamensis Helfer holds significant economic importance, as it produces golden silk. METHODS AND RESULTS: In the current investigation, we deciphered its intricate gut bacteriome through high-throughput 16S rRNA amplicon sequencing. Further, to understand bacterial community dynamics among silkworms raised under outdoor environmental conditions, we compared its gut bacteriomes with those of the domesticated mulberry silkworm, Bombyx mori L. Most abundant bacterial phyla identified in the gut of A. assamensis were Proteobacteria (78.1%), Bacteroidetes (8.0%) and Firmicutes (6.6%), whereas the most-abundant phyla in B. mori were Firmicutes (49-86%) and Actinobacteria (10-36%). Further, Gammaproteobacteria (57.1%), Alphaproteobacteria (10.47%) and Betaproteobacteria (8.28%) were the dominant bacterial classes found in the gut of A. assamensis. The predominant bacterial families in A. assamensis gut were Enterobacteriaceae (27.7%), Comamonadaceae (9.13%), Pseudomonadaceae (9.08%) Flavobacteriaceae (7.59%) Moraxellaceae (7.38%) Alteromonadaceae (6.8%) and Enterococcaceae (4.46%). In B. mori, the most-abundant bacterial families were Peptostreptococcaceae, Enterococcaceae, Lactobacillaceae and Bifidobacteriaceae, though all showed great variability among the samples. The core gut bacteriome of A. assamensis consisted of Pseudomonas, Acinetobacter, Variovorax, Myroides, Alteromonas, Enterobacter, Enterococcus, Sphingomonas, Brevundimonas, Oleispira, Comamonas, Oleibacter Vagococcus, Aminobacter, Marinobacter, Cupriavidus, Aeromonas, and Bacillus. Comparative gut bacteriome analysis revealed a more complex gut bacterial diversity in wild A. assamensis silkworms than in domesticated B. mori silkworms, which contained a relatively simple gut bacteriome as estimated by OTU richness. Predictive functional profiling of the gut bacteriome suggested that gut bacteria in A. assamensis were associated with a wide range of physiological, nutritional, and metabolic functions, including biodegradation of xenobiotics, lipid, amino acid, carbohydrate metabolism, and biosynthesis of secondary metabolites and amino acids. CONCLUSIONS: These results showed great differences in the composition and diversity of gut bacteria between the two silkworm species. Both insect species harbored core bacterial taxa commonly found in insects, but the relative abundance and composition of these taxa varied markedly.

Identification of the mutual gliding locus as a factor for gut colonization in non-native bee hosts using the ARTP mutagenesis.

BACKGROUND: The gut microbiota and their hosts profoundly affect each other's physiology and evolution. Identifying host-selected traits is crucial to understanding the processes that govern the evolving interactions between animals and symbiotic microbes. Current experimental approaches mainly focus on the model bacteria, like hypermutating Escherichia coli or the evolutionary changes of wild stains by host transmissions. A method called atmospheric and room temperature plasma (ARTP) may overcome the bottleneck of low spontaneous mutation rates while maintaining mild conditions for the gut bacteria. RESULTS: We established an experimental symbiotic system with gnotobiotic bee models to unravel the molecular mechanisms promoting host colonization. By in vivo serial passage, we tracked the genetic changes of ARTP-treated Snodgrassella strains from Bombus terrestris in the non-native honeybee host. We observed that passaged isolates showing genetic changes in the mutual gliding locus have a competitive advantage in the non-native host. Specifically, alleles in the orphan mglB, the GTPase activating protein, promoted colonization potentially by altering the type IV pili-dependent motility of the cells. Finally, competition assays confirmed that the mutations out-competed the ancestral strain in the non-native honeybee gut but not in the native host. CONCLUSIONS: Using the ARTP mutagenesis to generate a mutation library of gut symbionts, we explored the potential genetic mechanisms for improved gut colonization in non-native hosts. Our findings demonstrate the implication of the cell mutual-gliding motility in host association and provide an experimental system for future study on host-microbe interactions. Video Abstract.

Causal relationship between gut microbiota and intracranial hemorrhage: A two-sample Mendelian randomization study.

Patients with intracranial hemorrhage (ICH) usually have an imbalance in the gut microbiota (GM); however, whether this is a causal correlation remains unclear. This study used summary data from an open genome-wide association study to conduct double-sample Mendelian randomization (MR) to test the causal correlation between GM and ICH. First, we used a cutoff value of P < 10E-5 to select single nucleotide polymorphisms critical for each GM. Inverse variance weighted, weighted median, and MR-PRESSO methods were used to evaluate the strength of this causal association. Finally, functional maps and annotations from genome-wide association studies were used to determine the biological functions of the genes. MR analysis revealed that Rikenellaceae RC9 gut group was significantly positively correlated with ICH risk. For every unit increase in Rikenellaceae RC9 gut group, the relative risk of ICH increased by 34.4%(P = 4.62E-04). Rhodospirillales, Terrisporobacter, Veillonellaceae, Coprococcus 3, unknown genus, Alphaproteobacteria, and Allisonella groups were negatively correlated with the risk of ICH, while Anaerofilum, Eubacteriumbrachy group, Clostridia, Howardella, and Romboutsia were negatively correlated with the risk of ICH. Nonetheless, the specific role of single nucleotide polymorphisms gene enrichment requires further investigation. This study suggests the causal effect on ICH. The discovery of >10 GMs associated with ICH could be used to prevent and treat ICH.

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.

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.