Commensal Oral Microbiota, Disease Severity and Mortality in Fibrotic Lung Disease.

RATIONALE: Oral microbiota associate with diseases of the mouth and serve as a source of lung microbiota. However, the role of oral microbiota in lung disease is unknown. OBJECTIVES: To determine associations between oral microbiota and disease severity and death in idiopathic pulmonary fibrosis. METHODS: We analyzed 16S rRNA gene and shotgun metagenomic sequencing data of buccal swabs from 511 patients with idiopathic pulmonary fibrosis in the multicenter CleanUP-IPF trial. Buccal swabs were collected from usual care, and antimicrobial cohorts. Microbiome data was correlated with measures of disease severity using principal component analysis and linear regression models. Associations between the buccal microbiome and mortality were determined using Cox additive models, Kaplan Meier analysis and Cox proportional hazards models. MEASUREMENTS AND MAIN RESULTS: Greater buccal microbial diversity associated with lower forced vital capacity (FVC) at baseline [mean diff -3.60: 95% CI -5.92 to -1.29 percent predicted FVC per 1 unit increment]. The buccal proportion of Streptococcus correlated positively with FVC [mean diff 0.80: 95% CI 0.16-1.43 percent predicted per 10% increase] (n=490). Greater microbial diversity was associated with an increased risk of death [HR 1.73: 95% CI 1.03-2.90] while a greater proportion of Streptococcus was associated with a reduced risk of death [HR 0.85: 95% CI 0.73 to 0.99]. The Streptococcus genus was mainly comprised of Streptococcus mitis species. CONCLUSIONS: Increasing buccal microbial diversity predicts disease severity and death in IPF. The oral commensal Streptococcus mitis spp associates with preserved lung function and improved survival.

Characterization of SARS-CoV-2 Distribution and Microbial Succession in a Clinical Microbiology Testing Facility during the SARS-CoV-2 Pandemic.

The exchange of microbes between humans and the built environment is a dynamic process that has significant impact on health. Most studies exploring the microbiome of the built environment have been predicated on improving our understanding of pathogen emergence, persistence, and transmission. Previous studies have demonstrated that SARS-CoV-2 presence significantly correlates with the proportional abundance of specific bacteria on surfaces in the built environment. However, in these studies, SARS-CoV-2 originated from infected patients. Here, we perform a similar assessment for a clinical microbiology lab while staff were handling SARS-CoV-2 infected samples. The goal of this study was to understand the distribution and dynamics of microbial population on various surfaces within different sections of a clinical microbiology lab during a short period of 2020 Coronavirus disease (COVID-19) pandemic. We sampled floors, benches, and sinks in 3 sections (bacteriology, molecular microbiology, and COVID) of an active clinical microbiology lab over a 3-month period. Although floor samples harbored SARS-CoV-2, it was rarely identified on other surfaces, and bacterial diversity was significantly greater on floors than sinks and benches. The floors were primarily colonized by bacteria common to natural environments (e.g., soils), and benchtops harbored a greater proportion of human-associated microbes, including Staphylococcus and Streptococcus. Finally, we show that the microbial composition of these surfaces did not change over time and remained stable. Despite finding viruses on the floors, no lab-acquired infections were reported during the study period, which suggests that lab safety protocols and sanitation practices were sufficient to prevent pathogen exposures. IMPORTANCE For decades, diagnostic clinical laboratories have been an integral part of the health care systems that perform diagnostic tests on patient's specimens in bulk on a regular basis. Understanding their microbiota should assist in designing and implementing disinfection, and cleaning regime in more effective way. To our knowledge, there is a lack of information on the composition and dynamics of microbiota in the clinical laboratory environments, and, through this study, we have tried to fill that gap. This study has wider implications as understanding the makeup of microbes on various surfaces within clinical laboratories could help identify any pathogenic bacterial taxa that could have colonized these surfaces, and might act as a potential source of laboratory-acquired infections. Mapping the microbial community within these built environments may also be critical in assessing the reliability of laboratory safety and sanitation practices to lower any potential risk of exposures to health care workers.

Longitudinal urinary microbiome characteristics in women with urgency urinary incontinence undergoing sacral neuromodulation.

INTRODUCTION AND HYPOTHESIS: The objective was to evaluate the stability of the urinary microbiome communities in women undergoing sacral neuromodulation (SNM) for urgency urinary incontinence (UUI). We hypothesized that clinical response to SNM therapy would be associated with changes in the urinary microbiome. METHODS: Women completed the Overactive Bladder Questionnaire Short-Form, the International Consultation on Incontinence Questionnaire Short Form, and the Female Sexual Function Index at baseline and 3 months post-SNM implantation. Transurethral urinary specimens were obtained for microbiome analysis at baseline and 3 months postoperatively. The V4 region of the 16S rRNA gene (515F-806R) was amplified with region-specific primers, and Amplicon Sequence Variants (ASVs) were identified with a closed-reference approach of taxonomic classification. Alpha-diversity was calculated using the phylogenetic (i.e., Faith's phylogenetic diversity) and nonphylogenetic metrics (i.e., Shannon diversity, and Pielou's evenness) using the QIIME2 plugin. Longitudinal paired volatility analysis was performed using the DEICODE and Gemelli plugin to account for host specificity across both time and space. RESULTS: Nineteen women who underwent SNM and provided both baseline and 3-month urine samples were included in this analysis. Women reported improvement in objective (number of UUI episodes) and subjective (symptom severity and health-related quality of life) measures. Ninety percent of the bacteria were classified as Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria. No significant differences were observed in each subject's beta-diversity at 3 months compared with their baseline microbiome. CONCLUSIONS: Our descriptive pilot study of a cohort of women who had achieved objective and subjective improvements in UUI following SNM therapy demonstrates that the urinary microbiome remains relatively stable, despite variability amongst the cohort.

Characterization of the GU microbiome in women with self-perceived bladder health over the life course.

BACKGROUND: A variety of factors influence bladder health, including environmental factors, life experiences, biologic foundations, and coexistent medical conditions. A biologically diverse microbial community exists in the urine that is likely influenced by the microbial inhabitants of the vagina. The relationship between the genitourinary (GU) microbiome and self-perceived bladder health is unknown. OBJECTIVE: To longitudinally define the GU microbiome in women with self-percieved bladder health sampled across multiple time points over a year. STUDY DESIGN: Women with no reported lower urinary tract dysfunction or symptoms (LUTS) were recruited from six clinical sites and assessed every 6 weeks for 1 year. Voided urine and vaginal samples were longitudinally collected. Self-perceived bladder health was assessed with select items from the LURN comprehensive assessment of self-reported urinary symptoms (CASUS) tool. We defined four life phases as follows: young (18-34 years, nulliparous), midlife (35-45 years, menstruating), transitional (46-60 years, perimenopausal), mature (>60 years, not using vaginal and/or systemic hormone replacement therapy). DNA was extracted from samples, and the V4 region of the 16S rRNA gene was amplified with region-specific primers. The 16S rRNA sequencing on an Illumina NovaSeq. Microbial beta-diversity was calculated using DEICODE to identify microbial taxa that cluster in the samples. Longitudinal volatility analysis was performed using the gemelli plugin. Log-abundance ratios of microbial features were explored and visualized in Qurro. RESULTS: Fifty-four (N = 16 young, N = 16 midlife, N = 15 transitional, N = 7 mature) women were enrolled and provided baseline data. Most women in each life phase (93%-98%) continued to report self-perceived bladder health throughout the 1-year follow-up as assessed by CASUS items. Temporal-based microbial diversity of urinary and vaginal microbiome remained relatively stable over 1 year in all subjects. The GU microbiomes of mature women were distinct and microbially diverse from that of young, midlife, and transitional women, with genera of Gardnerella, Cupriavidus, and Dialister contributory to the microbial features of the mature microbiome. The mature GU microbiome was statistically different (p < 0.0001) from the midlife, transitional, and young microbiome for the log ratio of Gardnerella and Cupriavidus (in the numerator) and Lactobacillus (in the denominator) for voided samples and Gardnerella and Dialister (in the numerator) and Lactobacillus (in the denominator) for vaginal samples. Differences in the GU microbiome were also demonstrated via longitudinal beta-diversity between women developing urinary frequency as reported by CASUS responses or objectively on bladder diary compared to women without urinary frequency. CONCLUSION: In women with a self-perceived healthy bladder, the GU microbiome remained stable in all age groups over a 1 year period. Differences were seen with respect to life phase, where mature women were distinct from all other groups, and with respect to self-reported LUTS.

Standardized multi-omics of Earth's microbiomes reveals microbial and metabolite diversity.

Despite advances in sequencing, lack of standardization makes comparisons across studies challenging and hampers insights into the structure and function of microbial communities across multiple habitats on a planetary scale. Here we present a multi-omics analysis of a diverse set of 880 microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry). We used standardized protocols and analytical methods to characterize microbial communities, focusing on relationships and co-occurrences of microbially related metabolites and microbial taxa across environments, thus allowing us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of an evolving community resource. We demonstrate the utility of this database by testing the hypothesis that every microbe and metabolite is everywhere but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment, whereas the relative abundances of microbially related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner. We additionally show the power of certain chemistry, in particular terpenoids, in distinguishing Earth's environments (for example, terrestrial plant surfaces and soils, freshwater and marine animal stool), as well as that of certain microbes including Conexibacter woesei (terrestrial soils), Haloquadratum walsbyi (marine deposits) and Pantoea dispersa (terrestrial plant detritus). This Resource provides insight into the taxa and metabolites within microbial communities from diverse habitats across Earth, informing both microbial and chemical ecology, and provides a foundation and methods for multi-omics microbiome studies of hosts and the environment.

Effects of 'Healthy' Fecal Microbiota Transplantation against the Deterioration of Depression in Fawn-Hooded Rats.

Depression is a recurrent, heterogeneous mood disorder occurring in more than 260 million people worldwide. Gut microbiome dysbiosis is associated with the development of depressive-like behaviors by modulating neuro-biochemical metabolism through the microbiome-gut-brain (MGB) axis. Fecal microbiota transplantation (FMT) has been proposed as a potential therapeutic solution for depression, but the therapeutic efficiency and mechanism are unknown. Here, we performed an FMT from Sprague-Dawley (SD) rats ('healthy' controls) to Fawn-hooded (FH) rats (depression model). Pre-FMT, the FH rats exhibited significantly elevated depressive-like behaviors and distinct neurotransmitter and cytokine levels compared with SD rats. Post-FMT, FH recipients receiving FH fecal microbiota (FH-FH rats) showed aggravated depressive-like behaviors, while the ones receiving SD microbiota (FH-SD rats) had significantly alleviated depressive symptoms, a significant increase in hippocampal neurotransmitters, and a significant decrease of some hippocampal cytokines than FH-FH rats. SD-FMT resulted in the FH-SD rats' gut microbiome resembling the SD donors, and a significant shift in the serum metabolome but not the hippocampal metabolome. Co-occurrence analysis suggests that SD-FMT prevented recipients' depression development via the significant decrease of gut microbial species such as Dialister sp., which led to the recipients' metabolic modulation in serum and hippocampus through the enteric nervous system, the intestinal barrier, and the blood-brain barrier. Our results provided new data pointing to multiple mechanisms of interaction for the impact of gut microbiome modulation on depression therapy. IMPORTANCE Depression is a chronic, recurrent mental disease, which could make the patients commit suicide in severe cases. Considering that gut microbiome dysbiosis could cause depressive symptoms in animals through the MGB axis, the modification of gut microbiota is expected to be a potential therapy for depression, but the daily administration of probiotics is invalid or transient. In this study, we demonstrated that the gut microbiome transferred from a healthy rat model to a depressive rat model could regulate the recipient's neurobiology and behavior via the systematic alternation of the depressive gut microbiota followed by the serum and hippocampal metabolism. These results underline the significance of understanding the impact of gut microbiota on mental disorders and suggest that 'healthy' microbiota transplantation with the function to solve the host's cerebral inflammation may serve as a novel therapeutic strategy for depression.

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.

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 ecologist's 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.

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's 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. TRIAL REGISTRATION NUMBER: NCT02059538.

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.

SARS-CoV-2 detection status associates with bacterial community composition in patients and the hospital environment.

BACKGROUND: SARS-CoV-2 is an RNA virus responsible for the coronavirus disease 2019 (COVID-19) pandemic. Viruses exist in complex microbial environments, and recent studies have revealed both synergistic and antagonistic effects of specific bacterial taxa on viral prevalence and infectivity. We set out to test whether specific bacterial communities predict SARS-CoV-2 occurrence in a hospital setting. METHODS: We collected 972 samples from hospitalized patients with COVID-19, their health care providers, and hospital surfaces before, during, and after admission. We screened for SARS-CoV-2 using RT-qPCR, characterized microbial communities using 16S rRNA gene amplicon sequencing, and used these bacterial profiles to classify SARS-CoV-2 RNA detection with a random forest model. RESULTS: Sixteen percent of surfaces from COVID-19 patient rooms had detectable SARS-CoV-2 RNA, although infectivity was not assessed. The highest prevalence was in floor samples next to patient beds (39%) and directly outside their rooms (29%). Although bed rail samples more closely resembled the patient microbiome compared to floor samples, SARS-CoV-2 RNA was detected less often in bed rail samples (11%). SARS-CoV-2 positive samples had higher bacterial phylogenetic diversity in both human and surface samples and higher biomass in floor samples. 16S microbial community profiles enabled high classifier accuracy for SARS-CoV-2 status in not only nares, but also forehead, stool, and floor samples. Across these distinct microbial profiles, a single amplicon sequence variant from the genus Rothia strongly predicted SARS-CoV-2 presence across sample types, with greater prevalence in positive surface and human samples, even when compared to samples from patients in other intensive care units prior to the COVID-19 pandemic. CONCLUSIONS: These results contextualize the vast diversity of microbial niches where SARS-CoV-2 RNA is detected and identify specific bacterial taxa that associate with the viral RNA prevalence both in the host and hospital environment. Video Abstract.

Microbial context predicts SARS-CoV-2 prevalence in patients and the hospital built environment.

Synergistic effects of bacteria on viral stability and transmission are widely documented but remain unclear in the context of SARS-CoV-2. We collected 972 samples from hospitalized ICU patients with coronavirus disease 2019 (COVID-19), their health care providers, and hospital surfaces before, during, and after admission. We screened for SARS-CoV-2 using RT-qPCR, characterized microbial communities using 16S rRNA gene amplicon sequencing, and contextualized the massive microbial diversity in this dataset in a meta-analysis of over 20,000 samples. Sixteen percent of surfaces from COVID-19 patient rooms were positive, with the highest prevalence in floor samples next to patient beds (39%) and directly outside their rooms (29%). Although bed rail samples increasingly resembled the patient microbiome throughout their stay, SARS-CoV-2 was less frequently detected there (11%). Despite surface contamination in almost all patient rooms, no health care workers providing COVID-19 patient care contracted the disease. SARS-CoV-2 positive samples had higher bacterial phylogenetic diversity across human and surface samples, and higher biomass in floor samples. 16S microbial community profiles allowed for high classifier accuracy for SARS-CoV-2 status in not only nares, but also forehead, stool and floor samples. Across these distinct microbial profiles, a single amplicon sequence variant from the genus Rothia was highly predictive of SARS-CoV-2 across sample types, and had higher prevalence in positive surface and human samples, even when comparing to samples from patients in another intensive care unit prior to the COVID-19 pandemic. These results suggest that bacterial communities contribute to viral prevalence both in the host and hospital environment.

The Future of Microbiome-Based Therapeutics in Clinical Applications.

The microbiome, a collection of microorganisms, their genomes, and the surrounding environmental conditions, is akin to a human organ, and knowledge is emerging on its role in human health and diseases. The influence of the microbiome in drug response has only been investigated in detail for the last 10 years. The human microbiome is a complex and highly dynamic system, which varies dramatically between individuals, yet there exists a common core microbiome that is heritable and can be transmitted to progeny. Here, we review the role of the human microbiome, which is now widely accepted as a major factor that drives the interpersonal variation in therapeutic response. We describe examples in which the microbiome modifies drug action. Despite its complexity, the microbiome can be readily altered, with the potential to increase the benefits and reduce the toxicity and side effects associated with pharmaceutical drugs. The potential of new microbiome-based strategies, such as fecal microbiota transplant, probiotics, and phage therapy, as promising medical therapeutics are outlined. We also suggest a combination reductionist and system-level approaches that could be applied to further investigate the role of microbiota in drug metabolism modulation of drug response. Finally, we emphasize the importance of combining microbiome and pharmacology studies as a novel means to treat disease and reduce side effects.

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.

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.

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

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.

Gut microbiota dysbiosis is associated with malnutrition and reduced plasma amino acid levels: Lessons from genome-scale metabolic modeling.

Malnutrition is a severe non-communicable disease, which is prevalent in children from low-income countries. Recently, a number of metagenomics studies have illustrated associations between the altered gut microbiota and child malnutrition. However, these studies did not examine metabolic functions and interactions between individual species in the gut microbiota during health and malnutrition. Here, we applied genome-scale metabolic modeling to model the gut microbial species, which were selected from healthy and malnourished children from three countries. Our analysis showed reduced metabolite production capabilities in children from two low-income countries compared with a high-income country. Additionally, the models were also used to predict the community-level metabolic potentials of gut microbes and the patterns of pairwise interactions among species. Hereby we found that due to bacterial interactions there may be reduced production of certain amino acids in malnourished children compared with healthy children from the same communities. To gain insight into alterations in the metabolism of malnourished (stunted) children, we also performed targeted plasma metabolic profiling in the first 2 years of life of 25 healthy and 25 stunted children. Plasma metabolic profiling further revealed that stunted children had reduced plasma levels of essential amino acids compared to healthy controls. Our analyses provide a framework for future efforts towards further characterization of gut microbial metabolic capabilities and their contribution to malnutrition.

In vitro co-cultures of human gut bacterial species as predicted from co-occurrence network analysis.

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 in vitro evaluation of the predicted microbe-microbe co-occurrences, where we chose species pairs Bifidobacterium adolescentis and Bacteroides thetaiotaomicron, as well as Faecalibacterium prausnitzii and Roseburia inulinivorans 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 in vitro combinations of microbial species under anaerobic conditions, the results of this work will aid in the understanding and design of synthetic community formulations.