Anupriya Tripathi

Best practices for analysing microbiomes

Complex microbial communities shape the dynamics of various environments, ranging from the mammalian gastrointestinal tract to the soil. Advances in DNA sequencing technologies and data analysis have provided drastic improvements in microbiome analyses, for example, in taxonomic resolution, false discovery rate control and other properties, over earlier methods. In this Review, we discuss the best practices for performing a microbiome study, including experimental design, choice of molecular analysis technology, methods for data analysis and the integration of multiple omics data sets. We focus on recent findings that suggest that operational taxonomic unit-based analyses should be replaced with new methods that are based on exact sequence variants, methods for integrating metagenomic and metabolomic data, and issues surrounding compositional data analysis, where advances have been particularly rapid. We note that although some of these approaches are new, it is important to keep sight of the classic issues that arise during experimental design and relate to research reproducibility. We describe how keeping these issues in mind allows researchers to obtain more insight from their microbiome data sets.Complex microbial communities shape the dynamics of various environments. In this Review, Knight and colleagues discuss the best practices for performing a microbiome study, including experimental design, choice of molecular analysis technology, methods for data analysis and the integration of multiple omics data sets.

Coupling Targeted and Untargeted Mass Spectrometry for Metabolome-Microbiome-Wide Association Studies of Human Fecal Samples

Increasing appreciation of the gut microbiomes role in health motivates understanding the molecular composition of human feces. To analyze such complex samples, we developed a platform coupling targeted and untargeted metabolomics. The approach is facilitated through split flow from one UPLC, joint timing triggered by contact closure relays, and a script to retrieve the data. It is designed to detect specific metabolites of interest with high sensitivity, allows for correction of targeted information, enables better quantitation thus providing an advanced analytical tool for exploratory studies. Procrustes analysis revealed that untargeted approach provides a better correlation to microbiome data, associating specific metabolites with microbes that produce or process them. With the subset of over one hundred human fecal samples from the American Gut project, the implementation of the described coupled workflow revealed that targeted analysis using combination of single transition per compound with retention time misidentifies 30% of the targeted data and could lead to incorrect interpretations. At the same time, the targeted analysis extends detection limits and dynamic range, depending on the compounds, by orders of magnitude. A software application has been developed as a part of the workflow to allows for quantitative assessments based on calibration curves. Using this approach, we detect expected microbially modified molecules such as secondary bile acids and unexpected microbial molecules including Pseudomonas-associated quinolones and rhamnolipids in feces, setting the stage for metabolome-microbiome-wide association studies (MMWAS).

Gut Microbiota Offers Universal Biomarkers across Ethnicity in Inflammatory Bowel Disease Diagnosis and Infliximab Response Prediction

In the present report, we show that the human fecal microbiota contains promising and universal biomarkers for the noninvasive evaluation of inflammatory bowel disease severity and IFX treatment efficacy, emphasizing the potential ability to mine the gut microbiota as a modality to stratify IBD patients and apply personalized therapy for optimal outcomes. ABSTRACT Gut microbiota dysbiosis contributes to the onset and perpetuation of inflammatory bowel disease (IBD). Given that gut microbiotas vary across geography and ethnicity, it remains obscure whether any universal microbial signatures for IBD diagnosis and prognosis evaluation exist irrespective of populations. Here we profiled the fecal microbiota of a series of Chinese IBD patients and combined them with two Western IBD cohorts, PRISM and RISK, for meta-analyses. We found that the gut microbial alteration patterns in IBD are similar among Chinese and Westerners. Our prediction model based on gut microbiome for IBD diagnosis is robust across the cohorts, which showed 87.5% and 79.1% prediction accuracy in Crohn’s disease (CD) and ulcerative colitis (UC) patients, respectively. A relative increase in the levels of Actinobacteria and Proteobacteria (Enterobacteriaceae) and a relative decrease in the levels of Firmicutes (Clostridiales) were strongly correlated with IBD severity (P < 0.05). Additionally, restoration of gut microbiota diversity and a significant increase in Clostridiales relative abundance were found in patients responding to infliximab (IFX [Remicade]) treatment compared to those in relapse. Moreover, certain microbes, mainly Clostridiales, predicted the treatment effectiveness with 86.5% accuracy alone and 93.8% accuracy in combination with calprotectin levels and Crohn’s disease activity index (CDAI). Taking the results together, we conclude that gut microbiota can offer a set of universal biomarkers for diagnosis, disease activity evaluation, and infliximab treatment response prediction in IBD. IMPORTANCE In the present report, we show that the human fecal microbiota contains promising and universal biomarkers for the noninvasive evaluation of inflammatory bowel disease severity and IFX treatment efficacy, emphasizing the potential ability to mine the gut microbiota as a modality to stratify IBD patients and apply personalized therapy for optimal outcomes.

The gut–liver axis and the intersection with the microbiome

In the past decade, an exciting realization has been that diverse liver diseases — ranging from nonalcoholic steatohepatitis, alcoholic steatohepatitis and cirrhosis to hepatocellular carcinoma — fall along a spectrum. Work on the biology of the gut–liver axis has assisted in understanding the basic biology of both alcoholic fatty liver disease and nonalcoholic fatty liver disease (NAFLD). Of immense importance is the advancement in understanding the role of the microbiome, driven by high-throughput DNA sequencing and improved computational techniques that enable the complexity of the microbiome to be interrogated, together with improved experimental designs. Here, we review gut–liver communications in liver disease, exploring the molecular, genetic and microbiome relationships and discussing prospects for exploiting the microbiome to determine liver disease stage and to predict the effects of pharmaceutical, dietary and other interventions at a population and individual level. Although much work remains to be done in understanding the relationship between the microbiome and liver disease, rapid progress towards clinical applications is being made, especially in study designs that complement human intervention studies with mechanistic work in mice that have been humanized in multiple respects, including the genetic, immunological and microbiome characteristics of individual patients. These ‘avatar mice’ could be especially useful for guiding new microbiome-based or microbiome-informed therapies.Attention has turned to the gut microbiota in liver disease, including alcoholic and nonalcoholic fatty liver disease and hepatocellular carcinoma. This Review describes gut–liver communications, including evidence from animal and human studies, compares conditions within the liver disease spectrum and highlights key points for designing microbiome-based studies for liver disease research.Key pointsThe liver and intestine communicate extensively through the biliary tract, portal vein and systemic mediators.Liver products primarily influence the gut microbiota composition and gut barrier integrity, whereas intestinal factors regulate bile acid synthesis, glucose and lipid metabolism in the liver.Diverse liver diseases (including nonalcoholic fatty liver disease and alcoholic liver disease) are not unrelated but converge along a common path of progression; pro-inflammatory changes in the liver and intestine mediate development of fibrosis, cirrhosis and, ultimately, hepatocellular carcinoma.Alcoholic and nonalcoholic fatty liver diseases share key characteristics, such as intestinal dysbiosis, gut permeability and shifts in levels of bile acids, ethanol and choline metabolites.Precise contributions of the microbiome to liver diseases could differ based on aetiology; improvements in experimental design and development of animal models are rapidly elucidating causal mechanisms.Advances in understanding the gut–liver axis could encourage research into microbiome-based, diagnostic, prognostic and therapeutic modalities to improve management of liver diseases.

Intermittent Hypoxia and Hypercapnia, a Hallmark of Obstructive Sleep Apnea, Alters the Gut Microbiome and Metabolome

Intestinal dysbiosis mediates various cardiovascular diseases comorbid with OSA. To understand the role of dysbiosis in cardiovascular and metabolic disease caused by OSA, we systematically study the effect of intermittent hypoxic/hypercapnic stress (IHH, mimicking OSA) on gut microbes in an animal model. We take advantage of a longitudinal study design and paired omics to investigate the microbial and molecular dynamics in the gut to ascertain the contribution of microbes on intestinal metabolism in IHH. We observe microbe-dependent changes in the gut metabolome that will guide future research on unrecognized mechanistic links between gut microbes and comorbidities of OSA. Additionally, we highlight novel and noninvasive biomarkers for OSA-linked cardiovascular and metabolic disorders. ABSTRACT Obstructive sleep apnea (OSA) is a common disorder characterized by episodic obstruction to breathing due to upper airway collapse during sleep. Because of the episodic airway obstruction, intermittently low O2 (hypoxia) and high CO2 (hypercapnia) ensue. OSA has been associated with adverse cardiovascular and metabolic outcomes, although data regarding potential causal pathways are still evolving. As changes in inspired O2 and CO2 can affect the ecology of the gut microbiota and the microbiota has been shown to contribute to various cardiometabolic disorders, we hypothesized that OSA alters the gut ecosystem, which, in turn, exacerbates the downstream physiological consequences. Here, we model human OSA and its cardiovascular consequence using Ldlr−/− mice fed a high-fat diet and exposed to intermittent hypoxia and hypercapnia (IHH). The gut microbiome and metabolome were characterized longitudinally (using 16S rRNA amplicon sequencing and untargeted liquid chromatography-tandem mass spectrometry [LC-MS/MS]) and seen to covary during IHH. Joint analysis of microbiome and metabolome data revealed marked compositional changes in both microbial (>10%, most remarkably in Clostridia) and molecular (>22%) species in the gut. Moreover, molecules that altered in abundance included microbe-dependent bile acids, enterolignans, and fatty acids, highlighting the impact of IHH on host-commensal organism cometabolism in the gut. Thus, we present the first evidence that IHH perturbs the gut microbiome functionally, setting the stage for understanding its involvement in cardiometabolic disorders. IMPORTANCE Intestinal dysbiosis mediates various cardiovascular diseases comorbid with OSA. To understand the role of dysbiosis in cardiovascular and metabolic disease caused by OSA, we systematically study the effect of intermittent hypoxic/hypercapnic stress (IHH, mimicking OSA) on gut microbes in an animal model. We take advantage of a longitudinal study design and paired omics to investigate the microbial and molecular dynamics in the gut to ascertain the contribution of microbes on intestinal metabolism in IHH. We observe microbe-dependent changes in the gut metabolome that will guide future research on unrecognized mechanistic links between gut microbes and comorbidities of OSA. Additionally, we highlight novel and noninvasive biomarkers for OSA-linked cardiovascular and metabolic disorders.

Experimental Chagas disease-induced perturbations of the fecal microbiome and metabolome

Trypanosoma cruzi parasites are the causative agents of Chagas disease. These parasites infect cardiac and gastrointestinal tissues, leading to local inflammation and tissue damage. Digestive Chagas disease is associated with perturbations in food absorption, intestinal traffic and defecation. However, the impact of T. cruzi infection on the gut microbiota and metabolome have yet to be characterized. In this study, we applied mass spectrometry-based metabolomics and 16S rRNA sequencing to profile infection-associated alterations in fecal bacterial composition and fecal metabolome through the acute-stage and into the chronic stage of infection, in a murine model of Chagas disease. We observed joint microbial and chemical perturbations associated with T. cruzi infection. These included alterations in conjugated linoleic acid (CLA) derivatives and in specific members of families Ruminococcaceae and Lachnospiraceae, as well as alterations in secondary bile acids and members of order Clostridiales. These results highlight the importance of multi-‘omics’ and poly-microbial studies in understanding parasitic diseases in general, and Chagas disease in particular.

Untargeted Mass Spectrometry-Based Metabolomics Tracks Molecular Changes in Raw and Processed Foods and Beverages

A major aspect of our daily lives is the need to acquire, store and prepare our food. Storage and preparation can have drastic effects on the compositional chemistry of our foods, but we have a limited understanding of the temporal nature of processes such as storage, spoilage, fermentation and brewing on the chemistry of the foods we eat. Here, we performed a temporal analysis of the chemical changes in foods during common household preparations using untargeted mass spectrometry and novel data analysis approaches. Common treatments of foods such as home fermentation of yogurt, brewing of tea, spoilage of meats and ripening of tomatoes altered the chemical makeup through time, through both chemical and biological processes. For example, brewing tea altered its composition by increasing the diversity of molecules, but this change was halted after 4 min of brewing. The results indicate that this is largely due to differential extraction of the material from the tea and not modification of the molecules during the brewing process. This is in contrast to the preparation of yogurt from milk, spoilage of meat and the ripening of tomatoes where biological transformations directly altered the foods molecular composition. Comprehensive assessment of chemical changes using multivariate statistics showed the varied impacts of the different food treatments, while analysis of individual chemical changes show specific alterations of chemical families in the different food types. The methods developed here represent novel approaches to studying the changes in food chemistry that can reveal global alterations in chemical profiles and specific transformations at the chemical level. Highlights We created a reference data set for tomato, milk to yogurt, tea, coffee, turkey and beef. We show that normal preparation and handling affects the molecular make-up. Tea preparation is largely driven by differential extraction. Formation of yogurt involves chemical transformations. The majority of meat molecules are not altered in 5 days at room temperature.

Publisher Correction: The gut–liver axis and the intersection with the microbiome

In the original version of Table 1 published online, upward arrows to indicate increased translocation of PAMPs were missing from the row entitled ‘Translocation’ for both the column on alcoholic liver disease and nonalcoholic fatty liver disease. This error has now been updated in the PDF and HTML version of the article.

Are microbiome studies ready for hypothesis-driven research?

Hypothesis-driven research has led to many scientific advances, but hypotheses cannot be tested in isolation: rather, they require a framework of aggregated scientific knowledge to allow questions to be posed meaningfully. This framework is largely still lacking in microbiome studies, and the only way to create it is by discovery-driven, tool-driven, and standards-driven research projects. Here we illustrate these issues using several such non-hypothesis-driven projects from our own laboratories, including spatial mapping, the American Gut Project, the Earth Microbiome Project (which is an umbrella project integrating many smaller hypothesis-driven projects), and the knowledgebase-driven tools GNPS and Qiita. We argue that an investment of community resources in infrastructure tasks, and in the controls and standards that underpin them, will greatly enhance the investment in hypothesis-driven research programs.

Microbiome 101: Studying, Analyzing, and Interpreting Gut Microbiome Data for Clinicians

&NA; Advances in technical capabilities for reading complex human microbiomes are leading to an explosion of microbiome research, leading in turn to intense interest among clinicians in applying these techniques to their patients. In this review, we discuss the content of the human microbiome, including intersubject and intrasubject variability, considerations of study design including important confounding factors, and different methods in the laboratory and on the computer to read the microbiome and its resulting gene products and metabolites. We highlight several common pitfalls for clinicians, including the expectation that an individual’s microbiome will be stable, that diet can induce rapid changes that are large compared with the differences among subjects, that everyone has essentially the same core stool microbiome, and that different laboratory and computational methods will yield essentially the same results. We also highlight the current limitations and future promise of these techniques, with the expectation that an understanding of these considerations will help accelerate the path toward routine clinical application of these techniques developed in research settings.