Metagenomic analysis of microbe-mediated vitamin metabolism in the human gut microbiome

Abstract Background Human gut microbial communities have been known to produce vitamins, which are subsequently absorbed by the host in the large intestine. However, the relationship between species with vitamin pathway associated functional features or their gene abundance in different states of health and disease is lacking. Here, we analyzed shotgun fecal metagenomes of individuals from four different countries for genes that are involved in vitamin biosynthetic pathways and transport mechanisms and corresponding species’ abundance. Results We found that the prevalence of these genes were found to be distributed across the dominant phyla of gut species. The number of positive correlations were high between species harboring genes related to vitamin biosynthetic pathways and transporter mechanisms than that with either alone. Although, the range of total gene abundances remained constant across healthy populations at the global level, species composition and their presence for metabolic pathway related genes determine the abundance and functional genetic content of vitamin metabolism. Based on metatranscriptomics data, the equation between abundance of vitamin-biosynthetic enzymes and vitamin-dependent enzymes suggests that the production and utilization potential of these enzymes seems way more complex usage allocations than just mere direct linear associations. Conclusions Our findings provide a rationale to examine and disentangle the interrelationship between B-vitamin dosage (dietary or microbe-mediated) on gut microbial members and the host, in the gut microbiota of individuals with under- or overnutrition

Metagenomic analysis of bile salt biotransformation in the human gut microbiome

Background: In the biochemical milieu of human colon, bile acids act as signaling mediators between the host and its gut microbiota. Biotransformation of primary to secondary bile acids have been known to be involved in the immune regulation of human physiology. Several 16S amplicon-based studies with inflammatory bowel disease (IBD) subjects were found to have an association with the level of fecal bile acids. However, a detailed investigation of all the bile salt biotransformation genes in the gut microbiome of healthy and IBD subjects has not been performed. Results: Here, we report a comprehensive analysis of the bile salt biotransformation genes and their distribution at the phyla level. Based on the analysis of shotgun metagenomes, we found that the IBD subjects harbored a significantly lower abundance of these genes compared to the healthy controls. Majority of these genes originated from Firmicutes in comparison to other phyla. From metabolomics data, we found that the IBD subjects were measured with a significantly low level of secondary bile acids and high levels of primary bile acids compared to that of the healthy controls. Conclusions: Our bioinformatics-driven approach of identifying bile salt biotransformation genes predicts the bile salt biotransformation potential in the gut microbiota of IBD subjects. The functional level of dysbiosis likely contributes to the variation in the bile acid pool. This study sets the stage to envisage potential solutions to modulate the gut microbiome with the objective to restore the bile acid pool in the gut

Phylogeny-Aware Analysis of Metagenome Community Ecology Based on Matched Reference Genomes while Bypassing Taxonomy

We introduce the operational genomic unit (OGU) method, a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent of taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance, and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldom applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome data sets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project data set and more accurate prediction of human age by the gut microbiomes of Finnish individuals included in the FINRISK 2002 cohort. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate adoption of the OGU method in future metagenomics studies. IMPORTANCE Shotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene amplicon sequencing for decoding the composition and structure of microbial communities. Current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution. To solve these challenges, we introduce operational genomic units (OGUs), which are the individual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition and (ii) permitting use of phylogeny-aware tools. Our analysis of real-world data sets shows that it is advantageous over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGUs as an effective practice in metagenomic studies.Peer reviewe

Phylogeny-Aware Analysis of Metagenome Community Ecology Based on Matched Reference Genomes while Bypassing Taxonomy

We introduce the operational genomic unit (OGU) method, a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent of taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance, and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldom applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome data sets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project data set and more accurate prediction of human age by the gut microbiomes of Finnish individuals included in the FINRISK 2002 cohort. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate adoption of the OGU method in future metagenomics studies.IMPORTANCE Shotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene amplicon sequencing for decoding the composition and structure of microbial communities. Current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution. To solve these challenges, we introduce operational genomic units (OGUs), which are the individual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition and (ii) permitting use of phylogeny-aware tools. Our analysis of real-world data sets shows that it is advantageous over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGUs as an effective practice in metagenomic studies.</p

Impairment of gut microbial biotin metabolism and host biotin status in severe obesity: effect of biotin and prebiotic supplementation on improved metabolism

Objectives Gut microbiota is a key component in obesity and type 2 diabetes, yet mechanisms and metabolites central to this interaction remain unclear. We examined the human gut microbiome\u27s functional composition in healthy metabolic state and the most severe states of obesity and type 2 diabetes within the MetaCardis cohort. We focused on the role of B vitamins and B7/B8 biotin for regulation of host metabolic state, as these vitamins influence both microbial function and host metabolism and inflammation. Design We performed metagenomic analyses in 1545 subjects from the MetaCardis cohorts and different murine experiments, including germ-free and antibiotic treated animals, faecal microbiota transfer, bariatric surgery and supplementation with biotin and prebiotics in mice. Results Severe obesity is associated with an absolute deficiency in bacterial biotin producers and transporters, whose abundances correlate with host metabolic and inflammatory phenotypes. We found suboptimal circulating biotin levels in severe obesity and altered expression of biotin-associated genes in human adipose tissue. In mice, the absence or depletion of gut microbiota by antibiotics confirmed the microbial contribution to host biotin levels. Bariatric surgery, which improves metabolism and inflammation, associates with increased bacterial biotin producers and improved host systemic biotin in humans and mice. Finally, supplementing high-fat diet-fed mice with fructo-oligosaccharides and biotin improves not only the microbiome diversity, but also the potential of bacterial production of biotin and B vitamins, while limiting weight gain and glycaemic deterioration. Conclusion Strategies combining biotin and prebiotic supplementation could help prevent the deterioration of metabolic states in severe obesity

Systems and Synthetic Biology: ​“Mining human gut microbial metabolism through in vitro and in silico approaches”

The human gut microbiome is a consequence of mutual co-evolutionary interaction between the eukaryotic and prokaryotic parts of the mammalian holobiont. Based on the environmental and dietary inputs, there is a succession of microorganisms living inside the human colon. They have evolved to perform metabolic tasks that are not possible by the human host — for example, they breakdown complex polysaccharides and produce bioactive molecules such as short-chain fatty acids. They have the potential to transform human generated metabolites (e.g., primary bile acids) to signaling compounds such as secondary bile acids. They also produce several of B-vitamins, which otherwise human host derive through dietary means. Cognate receptors in various host cells could sense these bioactive metabolites and contribute to a wide variety of physiological function through signaling system in the host. An imbalance between the microbial activity and their effect on the host system could lead to the development of metabolic diseases.Provided the critical role of gut microbial metabolism, this thesis presents the evaluation of metabolic genes of gut microbiota such as bile acid, vitamin, and short-chain fatty acid metabolism using metabolic reconstructions and bioinformatics analysis in different states of health. Fecal metagenomes of subjects with inflammatory bowel diseases, type 2 diabetes and malnutrition were analyzed for such functional analyses. Furthermore, abundant gut microbial species were characterized to study their growth and metabolism in in vitro co-cultures using network analysis. The findings explained here\ua0 show the gut microbial metabolic diversity in various cohorts and conditions. It also includes a discussion on the challenges and future perspectives in a broader context of its potential application. The efforts undertaken in this work aims to inspire how the interplay between gut microbial metabolism and the host health status could contribute to the overall well-being of an individual

Conceptual strategies for characterizing interactions in microbial communities.

Understanding the sets of inter- and intraspecies interactions in microbial communities is a fundamental goal of microbial ecology. However, the study and quantification of microbial interactions pose several challenges owing to their complexity, dynamic nature, and the sheer number of unique interactions within a typical community. To overcome such challenges, microbial ecologists must rely on various approaches to distill the system of study to a functional and conceptualizable level, allowing for a practical understanding of microbial interactions in both simplified and complex systems. This review broadly addresses the role of several conceptual approaches available for the microbial ecologists arsenal, examines specific tools used to accomplish such approaches, and describes how the assumptions, expectations, and philosophies underlying these tools change across scales of complexity

Carbohydrate active enzymes are affected by diet transition from milk to solid food in infant gut microbiota

Infants experience a dramatic change in their food in the first year after birth when they shift from breast milk to solid food. This results in a large change in presence of indigestible polysaccharides, a primary energy resource of gut microbes. How the gut microbiota adapts to this dietary shift has not been well examined. Here, by using metagenomics data, we studied carbohydrate-active enzymes (CAZymes) of gut microbiota, which are essential enzymes catalyzing the breakdown of polysaccharides, during this dietary shift. We developed a new approach to categorize CAZyme families by food intake and found CAZyme families associated with milk or solid food. We also found CAZymes with most abundance in 12 months infants that are not associated with solid food or milk but may be related to modulating carbohydrates in the mucus. Additionally, the abundance of gut CAZymes were found to be affected by many other factors, including delivery modes and life style in adults. Taken together, our findings provide novel insights into the dynamic change of gut CAZymes in early human life and provide potential markers for food interference or gut microbiota restoration

Differential Fecal Microbiome Dysbiosis after Equivalent Traumatic Brain Injury in Aged Versus Young Adult Mice.

Traumatic brain injury (TBI) has a bimodal age distribution with peak incidence at age 24 and age 65 with worse outcomes developing in aged populations. Few studies have specifically addressed age at the time of injury as an independent biologic variable in TBI-associated secondary pathology. Within the framework of our published work, identifying age related effects of TBI on neuropathology, cognition, memory and motor function we analyzed fecal pellets collected from young and aged TBI animals to assess for age-induced effects in TBI induced dysbiosis. In this follow up, work we hypothesized increased dysbiosis after TBI in aged (80-week-old, N=10) versus young (14-week-old, N=10) mice. C57BL/6 males received a sham incision or TBI via open-head controlled cortical impact. Fresh stool pellets were collected 1-day pre-TBI, then 1, 7, and 28-days post-TBI for 16S rRNA gene sequencing and taxonomic analysis. Data revealed an age induced increase in disease associated microbial species which were exacerbated by injury. Consistent with our hypothesis, aged mice demonstrated a high number of disease associated changes to the gut microbiome pre- and post-injury. Our data suggest divergent microbiome phenotypes in injury between young and aged reflecting a previously unknown interaction between age, TBI, and the gut-brain axis implying the need for different treatment strategies

<i>In vitro</i> co-cultures of human gut bacterial species as predicted from co-occurrence network analysis

<div><p>Network analysis of large metagenomic datasets generated by current sequencing technologies can reveal significant co-occurrence patterns between microbial species of a biological community. These patterns can be analyzed in terms of pairwise combinations between all species comprising a community. Here, we construct a co-occurrence network for abundant microbial species encompassing the three dominant phyla found in human gut. This was followed by an <i>in vitro</i> evaluation of the predicted microbe-microbe co-occurrences, where we chose species pairs <i>Bifidobacterium adolescentis</i> and <i>Bacteroides thetaiotaomicron</i>, as well as <i>Faecalibacterium prausnitzii</i> and <i>Roseburia inulinivorans</i> as model organisms for our study. We then delineate the outcome of the co-cultures when equal distributions of resources were provided. The growth behavior of the co-culture was found to be dependent on the types of microbial species present, their specific metabolic activities, and resulting changes in the culture environment. Through this reductionist approach and using novel <i>in vitro</i> combinations of microbial species under anaerobic conditions, the results of this work will aid in the understanding and design of synthetic community formulations.</p></div