Xochitl C. Morgan

Dysfunction of the intestinal microbiome in inflammatory bowel disease and treatment

BackgroundThe inflammatory bowel diseases (IBD) Crohns disease and ulcerative colitis result from alterations in intestinal microbes and the immune system. However, the precise dysfunctions of microbial metabolism in the gastrointestinal microbiome during IBD remain unclear. We analyzed the microbiota of intestinal biopsies and stool samples from 231 IBD and healthy subjects by 16S gene pyrosequencing and followed up a subset using shotgun metagenomics. Gene and pathway composition were assessed, based on 16S data from phylogenetically-related reference genomes, and associated using sparse multivariate linear modeling with medications, environmental factors, and IBD status.ResultsFirmicutes and Enterobacteriaceae abundances were associated with disease status as expected, but also with treatment and subject characteristics. Microbial function, though, was more consistently perturbed than composition, with 12% of analyzed pathways changed compared with 2% of genera. We identified major shifts in oxidative stress pathways, as well as decreased carbohydrate metabolism and amino acid biosynthesis in favor of nutrient transport and uptake. The microbiome of ileal Crohns disease was notable for increases in virulence and secretion pathways.ConclusionsThis inferred functional metagenomic information provides the first insights into community-wide microbial processes and pathways that underpin IBD pathogenesis.

PhyloPhlAn is a new method for improved phylogenetic and taxonomic placement of microbes

New microbial genomes are constantly being sequenced, and it is crucial to accurately determine their taxonomic identities and evolutionary relationships. Here we report PhyloPhlAn, a new method to assign microbial phylogeny and putative taxonomy using >400 proteins optimized from among 3,737 genomes. This method measures the sequence diversity of all clades, classifies genomes from deep-branching candidate divisions through closely-related subspecies, and improves consistency between phylogenetic and taxonomic groupings. PhyloPhlAn improved taxonomic accuracy for existing and newly-sequenced genomes, detecting 157 erroneous labels, correcting 46, and placing or refining 130 new genomes. We provide examples of accurate classifications from subspecies (Sulfolobus spp.) to phyla, and of preliminary rooting of deep-branching candidate divisions, including consistent statistical support for Caldiserica (formerly candidate division OP5). PhyloPhlAn will thus be useful for both phylogenetic assessment and taxonomic quality control of newly-sequenced genomes. The final phylogenies, conserved protein sequences, and open-source implementation are available online.

Relating the metatranscriptome and metagenome of the human gut.

Significance Recent years have seen incredible growth in both the scale and specificity of projects analyzing the microbial organisms living in and on the human body (the human microbiome). Such studies typically require subjects to report to clinics for sample collection, a complicated practice that is impractical for large studies. To address these issues, we developed a protocol that allows subjects to collect microbiome samples at home and ship them to laboratories for multiple different types of molecular analysis. Measurements of microbial species, gene, and gene transcript composition within self-collected samples were consistent across sampling methods. In addition, our subsequent analysis of these samples revealed interesting similarities and differences between the measured functional potential and functional activity of the human microbiome. Although the composition of the human microbiome is now well-studied, the microbiota’s >8 million genes and their regulation remain largely uncharacterized. This knowledge gap is in part because of the difficulty of acquiring large numbers of samples amenable to functional studies of the microbiota. We conducted what is, to our knowledge, one of the first human microbiome studies in a well-phenotyped prospective cohort incorporating taxonomic, metagenomic, and metatranscriptomic profiling at multiple body sites using self-collected samples. Stool and saliva were provided by eight healthy subjects, with the former preserved by three different methods (freezing, ethanol, and RNAlater) to validate self-collection. Within-subject microbial species, gene, and transcript abundances were highly concordant across sampling methods, with only a small fraction of transcripts (<5%) displaying between-method variation. Next, we investigated relationships between the oral and gut microbial communities, identifying a subset of abundant oral microbes that routinely survive transit to the gut, but with minimal transcriptional activity there. Finally, systematic comparison of the gut metagenome and metatranscriptome revealed that a substantial fraction (41%) of microbial transcripts were not differentially regulated relative to their genomic abundances. Of the remainder, consistently underexpressed pathways included sporulation and amino acid biosynthesis, whereas up-regulated pathways included ribosome biogenesis and methanogenesis. Across subjects, metatranscriptional profiles were significantly more individualized than DNA-level functional profiles, but less variable than microbial composition, indicative of subject-specific whole-community regulation. The results thus detail relationships between community genomic potential and gene expression in the gut, and establish the feasibility of metatranscriptomic investigations in subject-collected and shipped samples.

Chapter 12: Human microbiome analysis.

Humans are essentially sterile during gestation, but during and after birth, every body surface, including the skin, mouth, and gut, becomes host to an enormous variety of microbes, bacterial, archaeal, fungal, and viral. Under normal circumstances, these microbes help us to digest our food and to maintain our immune systems, but dysfunction of the human microbiota has been linked to conditions ranging from inflammatory bowel disease to antibiotic-resistant infections. Modern high-throughput sequencing and bioinformatic tools provide a powerful means of understanding the contribution of the human microbiome to health and its potential as a target for therapeutic interventions. This chapter will first discuss the historical origins of microbiome studies and methods for determining the ecological diversity of a microbial community. Next, it will introduce shotgun sequencing technologies such as metagenomics and metatranscriptomics, the computational challenges and methods associated with these data, and how they enable microbiome analysis. Finally, it will conclude with examples of the functional genomics of the human microbiome and its influences upon health and disease.

Gut microbiome composition and function in experimental colitis during active disease and treatment-induced remission

Dysregulated immune responses to gut microbes are central to inflammatory bowel disease (IBD), and gut microbial activity can fuel chronic inflammation. Examining how IBD-directed therapies influence gut microbiomes may identify microbial community features integral to mitigating disease and maintaining health. However, IBD patients often receive multiple treatments during disease flares, confounding such analyses. Preclinical models of IBD with well-defined disease courses and opportunities for controlled treatment exposures provide a valuable solution. Here, we surveyed the gut microbiome of the T-bet−/− Rag2−/− mouse model of colitis during active disease and treatment-induced remission. Microbial features modified among these conditions included altered potential for carbohydrate and energy metabolism and bacterial pathogenesis, specifically cell motility and signal transduction pathways. We also observed an increased capacity for xenobiotics metabolism, including benzoate degradation, a pathway linking host adrenergic stress with enhanced bacterial virulence, and found decreased levels of fecal dopamine in active colitis. When transferred to gnotobiotic mice, gut microbiomes from mice with active disease versus treatment-induced remission elicited varying degrees of colitis. Thus, our study provides insight into specific microbial clades and pathways associated with health, active disease and treatment interventions in a mouse model of colitis.

Biodiversity and functional genomics in the human microbiome

Over the course of our lives, humans are colonized by a tremendous diversity of commensal microbes, which comprise the human microbiome. The collective genetic potential (metagenome) of the human microbiome is orders of magnitude more than the human genome, and it profoundly affects human health and disease in ways we are only beginning to understand. Advances in computing and high-throughput sequencing have enabled population-level surveys such as MetaHIT and the recently released Human Microbiome Project, detailed investigations of the microbiome in human disease, and mechanistic studies employing gnotobiotic model organisms. The resulting knowledge of human microbiome composition, function, and range of variation across multiple body sites has begun to assemble a rich picture of commensal host-microbe and microbe-microbe interactions as well as their roles in human health and disease and their potential as diagnostic and therapeutic tools.

Meta'omic Analytic Techniques for Studying the Intestinal Microbiome

Nucleotide sequencing has become increasingly common and affordable, and is now a vital tool for studies of the human microbiome. Comprehensive microbial community surveys such as MetaHit and the Human Microbiome Project have described the composition and molecular functional profile of the healthy (normal) intestinal microbiome. This knowledge will increase our ability to analyze host and microbial DNA (genome) and RNA (transcriptome) sequences. Bioinformatic and statistical tools then can be used to identify dysbioses that might cause disease, and potential treatments. Analyses that identify perturbations in specific molecules can leverage thousands of culture-based isolate genomes to contextualize culture-independent sequences, or may integrate sequence data with whole-community functional assays such as metaproteomic or metabolomic analyses. We review the state of available systems-level models for studies of the intestinal microbiome, along with analytic techniques and tools that can be used to determine its functional capabilities in healthy and unhealthy individuals.

Biogeography of the Intestinal Mucosal and Lumenal Microbiome in the Rhesus Macaque

The gut microbiome is widely studied by fecal sampling, but the extent to which stool reflects the commensal composition at intestinal sites is poorly understood. We investigated this relationship in rhesus macaques by 16S sequencing feces and paired lumenal and mucosal samples from ten sites distal to the jejunum. Stool composition correlated highly with the colonic lumen and mucosa and moderately with the distal small intestine. The mucosal microbiota varied most based on location and was enriched in oxygen-tolerant taxa (e.g., Helicobacter and Treponema), while the lumenal microbiota showed inter-individual variation and obligate anaerobe enrichment (e.g., Firmicutes). This mucosal and lumenal community variability corresponded to functional differences, such as nutrient availability. Additionally, Helicobacter, Faecalibacterium, and Lactobacillus levels in stool were highly predictive of their abundance at most other gut sites. These results quantify the composition and biogeographic relationships between gut microbial communities in macaques and support fecal sampling for translational studies.

Associations between host gene expression, the mucosal microbiome, and clinical outcome in the pelvic pouch of patients with inflammatory bowel disease

BackgroundPouchitis is common after ileal pouch-anal anastomosis (IPAA) surgery for ulcerative colitis (UC). Similar to inflammatory bowel disease (IBD), both host genetics and the microbiota are implicated in its pathogenesis. We use the IPAA model of IBD to associate mucosal host gene expression with mucosal microbiomes and clinical outcomes. We analyze host transcriptomic data and 16S rRNA gene sequencing data from paired biopsies from IPAA patients with UC and familial adenomatous polyposis. To achieve power for a genome-wide microbiome-transcriptome association study, we use principal component analysis for transcript and clade reduction, and identify significant co-variation between clades and transcripts.ResultsHost transcripts co-vary primarily with biopsy location and inflammation, while microbes co-vary primarily with antibiotic use. Transcript-microbe associations are surprisingly modest, but the most strongly microbially-associated host transcript pattern is enriched for complement cascade genes and for the interleukin-12 pathway. Activation of these host processes is inversely correlated with Sutterella, Akkermansia, Bifidobacteria, and Roseburia abundance, and positively correlated with Escherichia abundance.ConclusionsThis study quantifies the effects of inflammation, antibiotic use, and biopsy location upon the microbiome and host transcriptome during pouchitis. Understanding these effects is essential for basic biological insights as well as for well-designed and adequately-powered studies. Additionally, our study provides a method for profiling host-microbe interactions with appropriate statistical power using high-throughput sequencing, and suggests that cross-sectional changes in gut epithelial transcription are not a major component of the host-microbiome regulatory interface during pouchitis.

Sub-clinical detection of gut microbial biomarkers of obesity and type 2 diabetes

BackgroundObesity and type 2 diabetes (T2D) are linked both with host genetics and with environmental factors, including dysbioses of the gut microbiota. However, it is unclear whether these microbial changes precede disease onset. Twin cohorts present a unique genetically-controlled opportunity to study the relationships between lifestyle factors and the microbiome. In particular, we hypothesized that family-independent changes in microbial composition and metabolic function during the sub-clinical state of T2D could be either causal or early biomarkers of progression.MethodsWe collected fecal samples and clinical metadata from 20 monozygotic Korean twins at up to two time points, resulting in 36 stool shotgun metagenomes. While the participants were neither obese nor diabetic, they spanned the entire range of healthy to near-clinical values and thus enabled the study of microbial associations during sub-clinical disease while accounting for genetic background.ResultsWe found changes both in composition and in function of the sub-clinical gut microbiome, including a decrease in Akkermansia muciniphila suggesting a role prior to the onset of disease, and functional changes reflecting a response to oxidative stress comparable to that previously observed in chronic T2D and inflammatory bowel diseases. Finally, our unique study design allowed us to examine the strain similarity between twins, and we found that twins demonstrate strain-level differences in composition despite species-level similarities.ConclusionsThese changes in the microbiome might be used for the early diagnosis of an inflamed gut and T2D prior to clinical onset of the disease and will help to advance toward microbial interventions.