ABSTRACT
A mechanistic understanding of host-microbe interactions in the gut microbiome is hindered by poorly annotated bacterial genomes. While functional genomics can generate large gene-to-phenotype datasets to accelerate functional discovery, their applications to study gut anaerobes have been limited. For instance, most gain-of-function screens of gut-derived genes have been performed in Escherichia coli and assayed in a small number of conditions. To address these challenges, we develop Barcoded Overexpression BActerial shotgun library sequencing (Boba-seq). We demonstrate the power of this approach by assaying genes from diverse gut Bacteroidales overexpressed in Bacteroides thetaiotaomicron. From hundreds of experiments, we identify new functions and phenotypes for 29 genes important for carbohydrate metabolism or tolerance to antibiotics or bile salts. Highlights include the discovery of a D-glucosamine kinase, a raffinose transporter, and several routes that increase tolerance to ceftriaxone and bile salts through lipid biosynthesis. This approach can be readily applied to develop screens in other strains and additional phenotypic assays.
Subject(s)
Bile Acids and Salts , Carbon , Gastrointestinal Microbiome , Carbon/metabolism , Gastrointestinal Microbiome/genetics , Bile Acids and Salts/metabolism , Anti-Bacterial Agents/pharmacology , Stress, Physiological/genetics , Bacterial Proteins/genetics , Bacterial Proteins/metabolism , Bacteroides thetaiotaomicron/genetics , Bacteroides thetaiotaomicron/metabolism , Gene Expression Regulation, Bacterial , Bacteroidetes/genetics , Bacteroidetes/metabolism , Carbohydrate Metabolism/genetics , Humans , Genes, Bacterial/genetics , Escherichia coli/genetics , Escherichia coli/metabolism , Genome, BacterialABSTRACT
Recent observational studies suggest that gut microorganisms are involved in the onset and development of coronavirus disease 2019 (COVID-19), but the potential causal relationship behind them remains unclear. Exposure data were derived from the MiBioGen consortium, encompassing 211 gut microbiota (n = 18,340). The outcome data were sourced from the COVID-19 host genetics initiative (round 7), including COVID-19 severity (n = 1,086,211), hospitalization (n = 2,095,324), and susceptibility (n = 2,597,856). First, a two-sample Mendelian randomization (TSMR) was performed to investigate the causal effect between gut microbiota and COVID-19 outcomes. Second, a two-step MR was used to explore the potential mediators and underlying mechanisms. Third, several sensitivity analyses were performed to verify the robustness of the results. Five gut microbes were found to have a potential causality with COVID-19 severity, namely Betaproteobacteria (beta = 0.096, p = 0.034), Christensenellaceae (beta = -0.092, p = 0.023), Adlercreutzia (beta = 0.072, p = 0.048), Coprococcus 1 (beta = 0.089, p = 0.032), Eisenbergiella (beta = 0.064, p = 0.024). Seven gut microbes were found to have a potential causality with COVID-19 hospitalization, namely Victivallaceae (beta = 0.037, p = 0.028), Actinomyces (beta = 0.047, p = 0.046), Coprococcus 2 (beta = -0.061, p = 0.031), Dorea (beta = 0.067, p = 0.016), Peptococcus (beta = -0.035, p = 0.049), Rikenellaceae RC9 gut group (beta = 0.034, p = 0.018), and Proteobacteria (beta = -0.069, p = 0.035). Two gut microbes were found to have a potential causality with COVID-19 susceptibility, namely Holdemanella (beta = -0.024, p = 0.023) and Lachnospiraceae FCS020 group (beta = 0.026, p = 0.027). Multi-omics mediation analyses indicate that numerous plasma proteins, metabolites, and immune factors are critical mediators linking gut microbiota with COVID-19 outcomes. Sensitivity analysis suggested no significant heterogeneity or pleiotropy. These findings revealed the causal correlation and potential mechanism between gut microbiota and COVID-19 outcomes, which may improve our understanding of the gut-lung axis in the etiology and pathology of COVID-19 in the future.
Subject(s)
COVID-19 , Gastrointestinal Microbiome , SARS-CoV-2 , COVID-19/microbiology , COVID-19/virology , Humans , Gastrointestinal Microbiome/genetics , SARS-CoV-2/genetics , Mendelian Randomization Analysis , Hospitalization , Severity of Illness IndexABSTRACT
Plastics pose a considerable challenge to aquatic ecosystems because of their increasing global usage and non-biodegradable properties. Coastal plastic debris can persist in ecosystems; however, its effects on resident organisms remain unclear. A metagenomic analysis of the isopoda Ligia, collected from clean (Nae-do, ND) and plastic-contaminated sites (Maemul-do, MD) in South Korea, was conducted to clarify the effects of microplastic contamination on the gut microbiota. Ligia gut microbiota's total operational taxonomic units were higher in ND than in MD. Alpha diversity did not differ significantly between the two Ligia gut microbial communities collected from ND and MD, although richness (Observed species) was lower in MD than in ND. Proteobacteria (67.47%, ND; 57.30%, MD) and Bacteroidetes (13.63%, ND; 20.76%, MD) were the most abundant phyla found at both sites. Significant different genera in Ligia from EPS-polluted sites were observed. Functional gene analysis revealed that 19 plastic degradation-related genes, including those encoding hydrogenase, esterase, and carboxylesterase, were present in the gut microbes of Ligia from MD, indicating the potential role of the Ligia gut microbiota in plastic degradation. This study provides the first comparative field evidence of the gut microbiota dynamics of plastic detritus consumers in marine ecosystems.
Subject(s)
Gastrointestinal Microbiome , Isopoda , Gastrointestinal Microbiome/drug effects , Gastrointestinal Microbiome/genetics , Republic of Korea , Animals , Isopoda/microbiology , Water Pollutants, Chemical/toxicity , Water Pollutants, Chemical/adverse effects , Metagenomics/methodsABSTRACT
Over recent years, the prevalence of diabetes has been on the rise, paralleling improvements in living standards. Diabetic nephropathy (DN), a prevalent complication of diabetes, has also exhibited a growing incidence. While some clinical studies and reviews have hinted at a link between diabetic nephropathy and gut microbiota (GM), the nature of this connection, specifically its causative nature, remains uncertain. Investigating the causal relationship between diabetic nephropathy and gut microbiota holds the promise of aiding in disease screening and identifying novel biomarkers. In this study, we employed a two-sample Mendelian randomization analysis. Our dataset encompassed 4,111 DN patients from the GWAS database, juxtaposed with 308,539 members forming a control group. The aim was to pinpoint specific categories within the vast spectrum of the 211 known gut microbiota types that may have a direct causal relationship with diabetic nephropathy. Rigorous measures, including extensive heterogeneity and sensitivity analyses, were implemented to mitigate the influence of confounding variables on our experimental outcomes. Ultimately, our comprehensive analysis revealed 15 distinct categories of gut microbiota that exhibit a causal association with diabetic nephropathy. In summary, the phyla Bacteroidota and Verrucomicrobiae, the families Peptostreptococcaceae and Veillonellaceae, the genus Akkermansia, and the species Catenibacterium, Lachnoclostridium, Parasutterella, along with the orders Bacteroidales and Verrucomicrobiales, and the class Bacteroidetes were identified as correlates of increased risk for DN. Conversely, the family Victivallaceae, the species Eubacterium coprostanoligenes, and the Clostridium sensu stricto 1 group were found to be associated with a protective effect against the development of DN.These findings not only provide valuable insights but also open up novel avenues for clinical research, offering fresh directions for potential treatments.
Subject(s)
Diabetic Nephropathies , Gastrointestinal Microbiome , Whole Genome Sequencing , Humans , Diabetic Nephropathies/microbiology , Gastrointestinal Microbiome/genetics , Mendelian Randomization Analysis , Genome-Wide Association StudyABSTRACT
Background: Tracking the spread of antibiotic resistant bacteria is critical to reduce global morbidity and mortality associated with human and animal infections. There is a need to understand the role that wild animals in maintenance and transfer of antibiotic resistance genes (ARGs). Methods: This study used metagenomics to identify and compare the abundance of bacterial species and ARGs detected in the gut microbiomes from sympatric humans and wild mouse lemurs in a forest-dominated, roadless region of Madagascar near Ranomafana National Park. We examined the contribution of human geographic location toward differences in ARG abundance and compared the genomic similarity of ARGs between host source microbiomes. Results: Alpha and beta diversity of species and ARGs between host sources were distinct but maintained a similar number of detectable ARG alleles. Humans were differentially more abundant for four distinct tetracycline resistance-associated genes compared to lemurs. There was no significant difference in human ARG diversity from different locations. Human and lemur microbiomes shared 14 distinct ARGs with highly conserved in nucleotide identity. Synteny of ARG-associated assemblies revealed a distinct multidrug-resistant gene cassette carrying dfrA1 and aadA1 present in human and lemur microbiomes without evidence of geographic overlap, suggesting that these resistance genes could be widespread in this ecosystem. Further investigation into intermediary processes that maintain drug-resistant bacteria in wildlife settings is needed.
Subject(s)
Gastrointestinal Microbiome , Metagenome , Animals , Madagascar , Humans , Metagenome/genetics , Gastrointestinal Microbiome/genetics , Sympatry , Rural Population , Metagenomics , Bacteria/genetics , Bacteria/drug effects , Drug Resistance, Bacterial/genetics , Genes, Bacterial , Cheirogaleidae/genetics , Cheirogaleidae/microbiologyABSTRACT
Bifidobacterium pseudocatenulatum is a prevalent gut microbe in humans of all ages and plays a crucial role in host health. However, its adaptive evolutionary characteristics remain poorly understood. This study analyzed the genome of 247 B. pseudocatenulatum isolates from Chinese, Vietnamese, Japanese and other region populations using population genomics and functional genomics. Our findings revealed high genetic heterogeneity and regional clustering within B. pseudocatenulatum isolates. Significant differences were observed in genome characteristics, phylogeny, and functional genes. Specifically, Chinese and Vietnamese isolates exhibited a higher abundance of genes involved in the metabolism of plant-derived carbohydrates (GH13, GH43, and GH5 enzyme families), aligning with the predominantly vegetable-, wheat- and fruit-based diets of these populations. Additionally, we found widespread transmission of antibiotic resistance genes (tetO and tetW) through mobile genetic elements, such as genomic islands (GIs), resulting in substantial intra-regional differences. Our findings highlight distinct adaptive evolution in B. pseudocatenulatum driven by gene specialization, possibly in response to regional variations in diet and lifestyle. This study sheds light on bifidobacteria colonization mechanisms in the host gut. IMPORTANCE: Gut microbiota, as a key link in the gut-brain axis, helps to maintain the health of the organism, among which, Bifidobacterium pseudocatenulatum (B. pseudocatenulatum) is an important constituent member of the gut microbiota, which plays an important role in maintaining the balance of gut microbiota. The probiotic properties of B. pseudocatenulatum have been widely elaborated, and in order to excavate its evolutionary features at the genomic level, here we focused on the genetic background and evolutionary mechanism of the B. pseudocatenulatum genomes isolated from the intestinal tracts of different populations. Ultimately, based on the phylogenetic tree, we found that B. pseudocatenulatum has high genetic diversity and regional clustering phenomenon, in which plant-derived carbohydrate metabolism genes (GH13, GH43, GH5) showed significant regional differences, and this genetic differentiation drove the adaptive evolution, which likely shaped by diet and lifestyle.
Subject(s)
Bifidobacterium pseudocatenulatum , Gastrointestinal Microbiome , Genome, Bacterial , Phylogeny , Gastrointestinal Microbiome/genetics , Humans , Bifidobacterium pseudocatenulatum/genetics , Bifidobacterium pseudocatenulatum/metabolism , Genetic Variation , Genomics , DietABSTRACT
Plasmids are small DNA molecules that enable bacteria to share beneficial traits, influencing microbial communities. However, their role within the human gut microbiome remains largely unknown. In this study, we investigate the gut microbiomes of 34 mother-child cohorts, employing a plasmid analysis workflow to understand the impact of plasmids on the gut microbiome. We create a plasmid phylogenetic tree, devise a method for assigning plasmid hosts, and examine potential plasmid transfer networks. Our research discovers a wide variety of previously unidentified plasmid sequences, indicating that current databases do not fully represent the gut plasmidome. Interestingly, infants display greater plasmid diversity compared to mothers and other healthy adults. We find that Bacteroidota, a major bacterial phylum, serves as the primary host for gut plasmids and plays a dominant role in gut plasmid transfer events. Additionally, plasmids broaden the genetic capabilities of bacteria, with their influence on bacterial function becoming more apparent as children's gut microbiomes develop. This study sheds light on the role of plasmids in the infant gut microbiome, making a significant contribution to our understanding of plasmid biology.
Subject(s)
Gastrointestinal Microbiome , Phylogeny , Plasmids , Plasmids/genetics , Humans , Gastrointestinal Microbiome/genetics , Infant , Female , Adult , Bacteria/genetics , Bacteria/classification , Male , Feces/microbiology , Bacteroidetes/genetics , Infant, NewbornABSTRACT
Genetic variations are instrumental for unraveling phage evolution and deciphering their functional implications. Here, we explore the underlying fine-scale genetic variations in the gut phageome, especially structural variations (SVs). By using virome-enriched long-read metagenomic sequencing across 91 individuals, we identified a total of 14,438 nonredundant phage SVs and revealed their prevalence within the human gut phageome. These SVs are mainly enriched in genes involved in recombination, DNA methylation, and antibiotic resistance. Notably, a substantial fraction of phage SV sequences share close homology with bacterial fragments, with most SVs enriched for horizontal gene transfer (HGT) mechanism. Further investigations showed that these SV sequences were genetic exchanged between specific phage-bacteria pairs, particularly between phages and their respective bacterial hosts. Temperate phages exhibit a higher frequency of genetic exchange with bacterial chromosomes and then virulent phages. Collectively, our findings provide insights into the genetic landscape of the human gut phageome.
Subject(s)
Bacteria , Bacteriophages , Gastrointestinal Microbiome , Gene Transfer, Horizontal , Bacteriophages/genetics , Humans , Gastrointestinal Microbiome/genetics , Bacteria/virology , Bacteria/genetics , Metagenomics/methods , Genetic Variation , Virome/genetics , Genome, Viral , High-Throughput Nucleotide SequencingABSTRACT
Antibiotics may alter the gut microbiome, and this is one of the mechanisms by which antimicrobial resistance may be promoted. Suboptimal antimicrobial stewardship in Asia has been linked to antimicrobial resistance. We aim to examine the relationship between oral antibiotic use and composition and antimicrobial resistance in the gut microbiome in 1093 Bangladeshi infants. We leverage a trial of 8-month-old infants in rural Bangladesh: 61% of children were cumulatively exposed to antibiotics (most commonly cephalosporins and macrolides) over the 12-month study period, including 47% in the first 3 months of the study, usually for fever or respiratory infection. 16S rRNA amplicon sequencing in 11-month-old infants reveals that alpha diversity of the intestinal microbiome is reduced in children who received antibiotics within the previous 7 days; these samples also exhibit enrichment for Enterococcus and Escherichia/Shigella genera. No effect is seen in children who received antibiotics earlier. Using shotgun metagenomics, overall abundance of antimicrobial resistance genes declines over time. Enrichment for an Enterococcus-related antimicrobial resistance gene is observed in children receiving antibiotics within the previous 7 days, but not earlier. Presence of antimicrobial resistance genes is correlated to microbiome composition. In Bangladeshi children, community use of antibiotics transiently reprofiles the gut microbiome.
Subject(s)
Anti-Bacterial Agents , Gastrointestinal Microbiome , RNA, Ribosomal, 16S , Humans , Gastrointestinal Microbiome/drug effects , Gastrointestinal Microbiome/genetics , Bangladesh/epidemiology , Infant , Anti-Bacterial Agents/administration & dosage , Anti-Bacterial Agents/pharmacology , RNA, Ribosomal, 16S/genetics , Male , Female , Administration, Oral , Drug Resistance, Bacterial/genetics , Feces/microbiology , Metagenomics/methods , Bacteria/genetics , Bacteria/drug effects , Bacteria/classification , Bacteria/isolation & purification , Cephalosporins/administration & dosage , Cephalosporins/pharmacology , Cephalosporins/therapeutic use , Enterococcus/drug effects , Enterococcus/genetics , Enterococcus/isolation & purification , Antimicrobial StewardshipABSTRACT
The human gut microbiome composition has been linked to Parkinson's disease (PD). However, knowledge of the gut microbiota on the genome level is still limited. Here we performed deep metagenomic sequencing and binning to build metagenome-assembled genomes (MAGs) from 136 human fecal microbiomes (68 PD samples and 68 control samples). We constructed 952 non-redundant high-quality MAGs and compared them between PD and control groups. Among these MAGs, there were 22 different genomes of Collinsella and Prevotella, indicating high variability of those genera in the human gut environment. Microdiversity analysis indicated that Ruminococcus bromii was statistically significantly (p < 0.002) more diverse on the strain level in the control samples compared to the PD samples. In addition, by clustering all genes and performing presence-absence analysis between groups, we identified several control-specific (p < 0.05) related genes, such as speF and Fe-S oxidoreductase. We also report detailed annotation of MAGs, including Clusters of Orthologous Genes (COG), Cas operon type, antiviral gene, prophage, and secondary metabolites biosynthetic gene clusters, which can be useful for providing a reference for future studies.
Subject(s)
Feces , Gastrointestinal Microbiome , Metagenome , Parkinson Disease , Parkinson Disease/genetics , Parkinson Disease/microbiology , Humans , Feces/microbiology , Gastrointestinal Microbiome/genetics , Metagenomics/methods , Genome, Bacterial , Male , Aged , Female , Genome, Microbial , Middle Aged , High-Throughput Nucleotide SequencingABSTRACT
There is a significant focus on the role of the host microbiome in different outcomes of human parasitic diseases, including cystic echinococcosis (CE). This study was conducted to identify the intestinal microbiome of patients with CE at different stages of hydatid cyst compared to healthy individuals. Stool samples from CE patients as well as healthy individuals were collected. The samples were divided into three groups representing various stages of hepatic hydatid cyst: active (CE1 and CE2), transitional (CE3), and inactive (CE4 and CE5). One family member from each group was selected to serve as a control. The gut microbiome of patients with different stages of hydatid cysts was investigated using metagenomic next-generation amplicon sequencing of the V3-V4 region of the 16S rRNA gene. In this study, we identified 4862 Operational Taxonomic Units from three stages of hydatid cysts in CE patients and healthy individuals with a combined frequency of 2,955,291. The most abundant genera observed in all the subjects were Blautia, Agathobacter, Faecalibacterium, Bacteroides, Bifidobacterium, and Prevotella. The highest microbial frequency was related to inactive forms of CE, and the lowest frequency was observed in the group with active forms. However, the lowest OTU diversity was found in patients with inactive cysts compared with those with active and transitional cyst stages. The genus Agatobacter had the highest OTU frequency. Pseudomonas, Gemella, and Ligilactobacillus showed significant differences among the patients with different stages of hydatid cysts. Additionally, Anaerostipes and Candidatus showed significantly different reads in CE patients compared to healthy individuals. Our findings indicate that several bacterial genera can play a role in the fate of hydatid cysts in patients at different stages of the disease.
Subject(s)
Echinococcosis, Hepatic , Gastrointestinal Microbiome , RNA, Ribosomal, 16S , Humans , Gastrointestinal Microbiome/genetics , Echinococcosis, Hepatic/microbiology , Echinococcosis, Hepatic/parasitology , Male , Female , RNA, Ribosomal, 16S/genetics , Adult , Middle Aged , Feces/microbiology , Feces/parasitology , Bacteria/classification , Bacteria/genetics , Bacteria/isolation & purification , Biodiversity , High-Throughput Nucleotide SequencingABSTRACT
Objective: This study aims to investigate the associations between specific bacterial taxa of the gut microbiome and the development of aortic aneurysm diseases, utilizing Mendelian Randomization (MR) to explore these associations and overcome the confounding factors commonly present in observational studies. Methods: Employing the largest available gut microbiome and aortic aneurysm Genome-Wide Association Study databases, including MiBioGen, Dutch Microbiome Project, FinnGen, UK Biobank, and Michigan Genomics Initiative, this study performs two-sample bidirectional MR analyses. Instrumental variables, linked to microbiome taxa at significant levels, were selected for identifying relationships with abdominal aortic aneurysms (AAA), thoracic aortic aneurysms (TAA), and aortic dissection (AD). Methods like inverse variance weighted, MR-PRESSO, MR-Egger, weighted median, simple mode, and mode-based estimate were used for MR analysis. Heterogeneity was assessed with the Cochran Q test. MR-Egger regression and MR-PRESSO addressed potential unbalanced horizontal pleiotropy. Results: The analysis did not find any evidence of statistically significant associations between the gut microbiome and aortic aneurysm diseases after adjusting for the false discovery rate (FDR). Specifically, while initial results suggested correlations between 19 taxa and AAA, 25 taxa and TAA, and 13 taxa with AD, these suggested associations did not hold statistical significance post-FDR correction. Therefore, the role of individual gut microbial taxa as independent factors in the development and progression of aortic aneurysm diseases remains inconclusive. This finding underscores the necessity for larger sample sizes and more comprehensive studies to further investigate these potential links. Conclusion: The study emphasizes the complex relationship between the gut microbiome and aortic aneurysm diseases. Although no statistically significant associations were found after FDR correction, the findings provide valuable insights and highlight the importance of considering gut microbiota in aortic aneurysm diseases research. Understanding these interactions may eventually contribute to identifying new therapeutic and preventive strategies for aortic aneurysm diseases.
Subject(s)
Gastrointestinal Microbiome , Genome-Wide Association Study , Mendelian Randomization Analysis , Humans , Gastrointestinal Microbiome/genetics , Aortic Aneurysm, Abdominal/microbiology , Aortic Aneurysm, Abdominal/genetics , Aortic Aneurysm/microbiology , Aortic Aneurysm/genetics , Bacteria/classification , Bacteria/genetics , Bacteria/isolation & purification , Aortic Aneurysm, Thoracic/microbiology , Aortic Aneurysm, Thoracic/genetics , Aortic Dissection/microbiologyABSTRACT
Urban parks play a significant role in urban ecosystems and are strongly associated with human health. Nevertheless, the biological contamination of urban parks - opportunistic pathogens and antibiotic resistance genes (ARGs) - has been poorly reported. Here, metagenomic and 16 S rRNA sequencing methods were used to study the distribution and assembly of opportunistic pathogens and ARGs in soil and water from nine parks in Lanzhou city, and further compared them with local human gut microbiomes to investigate the potential transmission risk. Our results revealed that the most important type of drug resistance in urban parks was multidrug resistance, with various resistance mechanisms. Approximately half of ARGs were shared between human gut and park environment, and it was noteworthy that cross-species transmission might exist among some high-risk ARGs, such as mepA and mdtE, with a significant enrichment in human gut. Metagenomic binning uncovered several bacterial genomes carrying adjacent ARGs, MGEs, and virulence genes, indicating a possibility that these genes may jointly transfer among different environments, particularly from park environment to human. Our results provided a reference point for the management of environmental pollutants in urban parks.
Subject(s)
Metagenomics , Humans , Parks, Recreational , Gastrointestinal Microbiome/drug effects , Gastrointestinal Microbiome/genetics , RNA, Ribosomal, 16S/genetics , China , Bacteria/genetics , Bacteria/drug effects , Bacteria/classification , Soil Microbiology , Cities , Drug Resistance, Bacterial/genetics , Water Microbiology , Genes, BacterialABSTRACT
BACKGROUND: Alongside microbiota development, the evolution of the resistome is crucial in understanding the early-life acquisition and persistence of Antibiotic Resistance Genes (ARGs). Therefore, the aim of this study is to provide a comprehensive view of the evolution and dynamics of the neonatal resistome from 7 days to 4 months of age using a high-throughput qPCR platform. METHODS: In the initial phase, a massive screening of 384 ARGs using a high-throughput qPCR in pooled healthy mother-infant pairs feces from the MAMI cohort was carried out to identify the most abundant and prevalent ARGs in infants and in mothers. This pre-analysis allowed for later targeted profiling in a large number of infants in a longitudinal manner during the first 4 months of life. 16S rRNA V3-V4 amplicon sequencing was performed to asses microbial composition longitudinally. Potential factors influencing the microbiota and ARGs in this period were also considered, such as mode of birth and breastfeeding type. RESULTS: Following the massive screening, the top 45 abundant ARGs and mobile genetic elements were identified and studied in 72 infants during their first months of life (7 days, 1, 2, and 4 months). These genes were associated with resistance to aminoglycosides, beta-lactams and tetracyclines, among others, as well as integrons, and other mobile genetic elements. Changes in both ARG composition and quantity were observed during the first 4 months of life: most ARGs abundance increased over time, but mobile genetic elements decreased significantly. Further exploration of modulating factors highlighted the effect on ARG composition of specific microbial genus, and the impact of mode of birth at 7 days and 4 months. The influence of infant formula feeding was observed at 4-month-old infants, who exhibited a distinctive resistome composition. CONCLUSIONS: This study illustrates the ARG evolution and dynamics in the infant gut by use of a targeted, high-throughput, quantitative PCR-based method. An increase in antibiotic resistance over the first months of life were observed with a fundamental role of delivery mode in shaping resistance profiles. Further, we highlighted the influence of feeding methods on the resistome development. These findings offer pivotal insights into dynamics of and factors influencing early-life resistome, with potential avenues for intervention strategies.
Subject(s)
Anti-Bacterial Agents , Feces , Gastrointestinal Microbiome , RNA, Ribosomal, 16S , Humans , Gastrointestinal Microbiome/drug effects , Gastrointestinal Microbiome/genetics , Infant , Infant, Newborn , Feces/microbiology , Female , Anti-Bacterial Agents/pharmacology , RNA, Ribosomal, 16S/genetics , Male , Breast Feeding , Bacteria/genetics , Bacteria/drug effects , Bacteria/classification , Genes, Bacterial/genetics , Drug Resistance, Bacterial/genetics , Evolution, Molecular , Drug Resistance, Microbial/genetics , Longitudinal StudiesABSTRACT
BACKGROUND: Several studies have explored the potential link between gut microbiota and breast cancer; nevertheless, the causal relationship between gut microbiota and breast cancer remains unclear. METHODS: We utilized summary statistics from genome-wide association studies (GWAS) of the gut microbiome from the MiBioGen project with summary data from GWAS on breast cancer from the FinnGen consortium and the IEU database, with the IEU data sourced from the Biobank Japan. Preliminary statistical analyses were conducted using inverse variance weighting (IVW), supplemented by various sensitivity analysis methods, including MR-Egger regression, weighted median, weighted mode, simple median, and simple mode, to ensure the robustness of our findings. Heterogeneity and pleiotropy were assessed to avoid misleading conclusions caused by unconsidered confounders or non-specific effects of genetic variants, ensuring that the results reflect a genuine causal relationship. RESULTS: In European populations, four types of gut microbiota were associated with breast cancer. The genus Erysipelatoclostridium was positively associated with the risk of breast cancer, with an odds ratio (OR) of 1.21 (95% confidence interval [CI] 1.083-1.358), false discovery rate (FDR) = 0.0039. The class Coriobacteriia, order Coriobacteriales, and family Coriobacteriaceae, which belong to the same phylogenetic system, showed a consistent inversely association with breast cancer risk, with an OR of 0.757 (95% CI 0.616-0.930), FDR = 0.0281. In East Asian populations, three types of gut microbiota were related to breast cancer. The Eubacterium ruminantium group was positively associated with breast cancer risk, with an OR of 1.259 (95% CI 1.056-1.499), FDR = 0.0497. The families Porphyromonadaceae and Ruminococcaceae were inversely associated with breast cancer risk, with ORs of 0.304 (95% CI 0.155-0.596), FDR = 0.0005, and 0.674 (95% CI 0.508-0.895), FDR = 0.03173, respectively. However, these two taxa had limited instrumental variables, restricting the statistical power and potentially affecting the interpretation of the results. CONCLUSION: This MR analysis demonstrated a probable causal link between specific gut microbiota and breast cancer. This study, through Mendelian randomization analysis comparing European and East Asian populations, reveals that gut microbiota may influence breast cancer risk differently across populations, providing potential directions for developing targeted prevention and treatment methods.
Subject(s)
Breast Neoplasms , Gastrointestinal Microbiome , Genome-Wide Association Study , Mendelian Randomization Analysis , Female , Humans , Breast Neoplasms/genetics , Breast Neoplasms/microbiology , Breast Neoplasms/epidemiology , East Asian People/genetics , Gastrointestinal Microbiome/genetics , Polymorphism, Single Nucleotide , Risk Factors , White People/geneticsABSTRACT
Antibiotic resistance genes (ARGs) are prevalent in the infant gut microbiota and make up the intestinal resistome, representing a community ARG reservoir. This study focuses on the dynamics and persistence of ARGs in the early gut microbiota, and the effect of early exposures therein. We leveraged 2,328 stool metagenomes from 475 children in the HELMi cohort and the available parental samples to study the diversity, dynamics, and intra-familial sharing of the resistome during the first two years of life. We found higher within-family similarity of the gut resistome composition and ARG load in infant-mother pairs, and between spouses, but not in father-infant pairs. Early gut microbiota composition and development correlated with the ARG load; Bacteroides correlated positively and Bifidobacterium negatively with the load, reflecting the typical resistance levels in these taxa. Caesarean delivered infants harbored lower ARG loads, partly reflecting the scarcity of Bacteroides compared to vaginally delivered. Exposure to intrapartum or post-natal antibiotics showed only modest associations with the ARG load and composition, mainly before 12 months. Our results indicate that the resistome is strongly driven by the normal development of the microbiota in early life, and suggest importance of longer evolution of ARGs over effects of recent antibiotic exposure.
Subject(s)
Anti-Bacterial Agents , Bacteria , Feces , Gastrointestinal Microbiome , Humans , Gastrointestinal Microbiome/drug effects , Gastrointestinal Microbiome/genetics , Infant , Female , Feces/microbiology , Male , Cohort Studies , Anti-Bacterial Agents/pharmacology , Bacteria/genetics , Bacteria/classification , Bacteria/drug effects , Bacteria/isolation & purification , Infant, Newborn , Bacteroides/genetics , Bacteroides/drug effects , Bacteroides/growth & development , Child, Preschool , Metagenome , Drug Resistance, Bacterial/geneticsABSTRACT
Gut bacteria might play an important role in male reproductive disorders, such as male infertility and sperm abnormalities; however, their causal role is unclear. Herein, Mendelian randomization (MR)-Egger, weighted median, inverse variance weighting, Simple mode, and Weighted mode were used to test the causal relationship between gut microbes and male reproductive diseases. The MR results were validated using various metrics. The MR results were also consolidated using reverse causality speculation, conducted using two-way MR analysis and Steiger filtering. Biological function was analysed using enrichment analyses. The results suggested that eight intestinal microflorae were causally associated with male infertility. The Eubacterium oxidoreducens group was associated with an increased risk of male infertility, while the family Bacteroidaceae was negatively associated with male reproductive diseases. Eight intestinal microflorae were causally associated with abnormal spermatozoa. The family Streptococcaceae was associated with a high risk of abnormal spermatozoa, whereas the family Porphyromonadaceae was associated with a low risk of abnormal spermatozoa. No pleiotropy was observed, this study identified a high correlation between the gut flora and the likelihood of male reproductive diseases. Future research will attempt to advance microbial-focused treatments for such diseases.
Subject(s)
Gastrointestinal Microbiome , Infertility, Male , Mendelian Randomization Analysis , Male , Humans , Gastrointestinal Microbiome/genetics , Infertility, Male/microbiology , Infertility, Male/genetics , Spermatozoa/microbiologyABSTRACT
Evidence from previous studies have demonstrated that gut microbiota are closely associated with occurrence of interstitial cystitis/bladder pain syndrome (IC/BPS), yet the causal link between the two is not well known. In this study, we performed a two-sample Mendelian randomization (MR) analysis to determine the possible causal association between gut microbiota with IC/BPS. Gut microbiota summary level data were derived from the genome-wide association study (GWAS) conducted by MiBioGen and the IC/BPS GWAS summary level data were obtained from the GWAS Catalog. Next, we performed an MR study to investigate the causal link between gut microbiota and IC/BPS. The primary method for causal analysis was the inverse variance weighted (IVW), and the MR results were validated through multiple sensitivity analyses. A positive association was found between IC/BPS and eight gut microbial taxa, including genus Bacteroides, genus Haemophilus, genus Veillonella, genus Coprococcus1, genus Butyricimonas, family Bacteroidaceae, family Christensenellaceae, and order Lactobacillales. Sensitivity analysis revealed lack of significant pleiotropy or heterogeneity in the obtained results. This MR analysis reveals that a causal association exists between some gut microbiota with IC/BPS. This finding may is expected to guide future research and development of IC/BPS preventions and treatments based on the bladder-gut axis. However, given the clinical complexity and diagnostic challenges of IC/BPS, along with the limitations of using large-scale GWAS summary data for analysis, our MR results require further validation through additional research.
Subject(s)
Cystitis, Interstitial , Gastrointestinal Microbiome , Genome-Wide Association Study , Mendelian Randomization Analysis , Cystitis, Interstitial/microbiology , Cystitis, Interstitial/genetics , Humans , Gastrointestinal Microbiome/genetics , Polymorphism, Single NucleotideABSTRACT
The critical role of the human gut microbiota in kidney stone formation remains largely unknown, due to the low taxonomic resolution of previous sequencing technologies. Therefore, this study aimed to explore the gut microbiota using high-throughput sequencing to provide valuable insights and identify potential bacterial species and metabolite roles involved in kidney stone formation. The overall gut bacterial community and its potential functions in healthy participants and patients were examined using PacBio sequencing targeting the full-length 16S rRNA gene, coupled with stone and statistical analyses. Most kidney stones comprised calcium oxalate and calcium phosphate (75%), pure calcium oxalate (20%), and calcium phosphate and magnesium phosphate (5%), with higher content of Ca (130,510.5 ± 108,362.7 ppm) followed by P (18,746.4 ± 23,341.2 ppm). The microbial community structure was found to be weaker in patients' kidney stone samples, followed by patients' stool samples, than in healthy participants' stool samples. The most abundant bacterial species in kidney stone samples was uncultured Morganella, whereas that in patient and healthy participant stool samples was Bacteroides vulgatus. Similarly, Akkermansia muciniphila was significantly enriched in patient stool samples at the species level, whereas Bacteroides plebeius was significantly enriched in kidney stone samples than that in healthy participant stool samples. Three microbial metabolic pathways, TCA cycle, fatty acid oxidation, and urea cycle, were significantly enriched in kidney stone patients compared to healthy participants. Inferring bacteria at the species level revealed key players in kidney stone formation, enhancing the clinical relevance of gut microbiota.