Summary Inflammatory bowel diseases (IBD), including Crohn’s disease (CD), are genetically linked to host pathways that implicate an underlying role for aberrant immune responses to intestinal microbiota. However, patterns of gut microbiome dysbiosis in IBD patients are inconsistent among published studies. Using samples from multiple gastrointestinal locations collected prior to treatment in new-onset cases, we studied the microbiome in the largest pediatric CD cohort to date. An axis defined by an increased abundance in bacteria which include Enterobacteriaceae, Pasteurellacaea, Veillonellaceae, and Fusobacteriaceae, and decreased abundance in Erysipelotrichales, Bacteroidales, and Clostridiales, correlates strongly with disease status. Microbiome comparison between CD patients with and without antibiotic exposure indicates that antibiotic use amplifies the microbial dysbiosis associated with CD. Comparing the microbial signatures between the ileum, rectum, and fecal samples indicates that at this early stage of disease, assessing the rectal mucosa-associated microbiome offers unique potential for convenient and early diagnosis of CD.

BackgroundUnderstanding the factors regulating our microbiota is important but requires appropriate statistical methodology. When comparing two or more populations most existing approaches either discount the underlying compositional structure in the microbiome data or use probability models such as the multinomial and Dirichlet-multinomial distributions, which may impose a correlation structure not suitable for microbiome data.ObjectiveTo develop a methodology that accounts for compositional constraints to reduce false discoveries in detecting differentially abundant taxa at an ecosystem level, while maintaining high statistical power.MethodsWe introduced a novel statistical framework called analysis of composition of microbiomes (ANCOM). ANCOM accounts for the underlying structure in the data and can be used for comparing the composition of microbiomes in two or more populations. ANCOM makes no distributional assumptions and can be implemented in a linear model framework to adjust for covariates as well as model longitudinal data. ANCOM also scales well to compare samples involving thousands of taxa.ResultsWe compared the performance of ANCOM to the standard t-test and a recently published methodology called Zero Inflated Gaussian (ZIG) methodology (1) for drawing inferences on the mean taxa abundance in two or more populations. ANCOM controlled the false discovery rate (FDR) at the desired nominal level while also improving power, whereas the t-test and ZIG had inflated FDRs, in some instances as high as 68% for the t-test and 60% for ZIG. We illustrate the performance of ANCOM using two publicly available microbial datasets in the human gut, demonstrating its general applicability to testing hypotheses about compositional differences in microbial communities.ConclusionAccounting for compositionality using log-ratio analysis results in significantly improved inference in microbiota survey data.

Summary The bacteria that colonize humans and our built environments have the potential to influence our health. Microbial communities associated with seven families and their homes over six weeks were assessed, including three families that moved home. Microbial communities differed significantly among homes, and the home microbiome was largely sourced from humans. The microbiota in each home were identifiable by family. Network analysis identified humans as the primary bacterial vector, and a Bayesian method significantly matched individuals to their dwellings. Draft genomes of potential human pathogens were observed on a kitchen counter could be matched to the hands of occupants. Following a house move, the microbial community in the new house rapidly converged on the microbial community of the occupants’ former house, suggesting rapid colonization by the family’s microbiota.

Recent studies suggest that gut microbiomes of urban-industrialized societies are different from those of traditional peoples. Here, we examine the relationship between lifeways and gut microbiota through taxonomic and functional potential characterization of fecal samples from hunter-gatherer and traditional agriculturalist communities in Peru, and an urban-industrialized community from the US. We find that in addition to taxonomic and metabolic differences between urban and traditional lifestyles, hunter-gatherers form a distinct sub-group among traditional peoples. As observed in previous studies, we find that Treponema are characteristic of traditional gut microbiomes. Moreover, through genome reconstruction (2.2–2.5 MB, coverage depth 26-513×) and functional potential characterization, we discover these Treponema are diverse, fall outside of pathogenic clades, and are similar to Treponema succinifaciens, a known carbohydrate metabolizer in swine. Gut Treponema are found in non-human primates and all traditional peoples studied to date, suggesting they are symbionts lost in urban-industrialized societies.

Disruption of healthy microbial communities has been linked to numerous diseases, yet microbial interactions are little understood. This is due in part to the large number of bacteria, and the much larger number of interactions (easily in the millions), making experimental investigation very difficult at best and necessitating the nascent field of computational exploration through microbial correlation networks. We benchmark the performance of eight correlation techniques on simulated and real data in response to challenges specific to microbiome studies: fractional sampling of ribosomal RNA sequences, uneven sampling depths, rare microbes and a high proportion of zero counts. Also tested is the ability to distinguish signals from noise, and detect a range of ecological and time-series relationships. Finally, we provide specific recommendations for correlation technique usage. Although some methods perform better than others, there is still considerable need for improvement in current techniques.

Vertebrate corpse decomposition provides an important stage in nutrient cycling in most terrestrial habitats, yet microbially mediated processes are poorly understood. Here we combine deep microbial community characterization, community-level metabolic reconstruction, and soil biogeochemical assessment to understand the principles governing microbial community assembly during decomposition of mouse and human corpses on different soil substrates. We find a suite of bacterial and fungal groups that contribute to nitrogen cycling and a reproducible network of decomposers that emerge on predictable time scales. Our results show that this decomposer community is derived primarily from bulk soil, but key decomposers are ubiquitous in low abundance. Soil type was not a dominant factor driving community development, and the process of decomposition is sufficiently reproducible to offer new opportunities for forensic investigations.T he process of decay and decomposition in mammalian and other vertebrate taxa is a key step in biological nutrient cycling. Without the action of vertebrate and invertebrate scavengers, bacteria, archaea, fungi, and protists, chemical decomposition of animal waste would proceed extremely slowly and lead to reservoirs of biochemical waste (1). The coevolution of microbial decomposers with the availability of vertebrate corpses over the past 400 million years is expected to result in conservation of key biochemical metabolic pathways and cross-kingdom ecological interactions for efficient recycling of nutrient reserves. Although mammalian corpses likely represent a relatively small component of the detritus pool (2, 3) in most ecosystems, their role in nutrient cycling and community dynamics may be disproportionately large relative to input size, owing to the high nutrient content of corpses (3, 4) and their rapid rates of decomposition [e.g., up to three orders of magnitude faster than plant litter (2)]. These qualities make corpses a distinct and potentially critical driver of terrestrial function (5, 6).When a mammalian body is decomposing, microbial and biochemical activity results in a series of decomposition stages (5) that are associated with a reproducible microbial succession across mice (7), swine (8), and human corpses (9). Yet the microbial metabolism and successional ecology underpinning decomposition are still poorly understood. At present, we do not fully comprehend (i) whether microbial taxa that drive decomposition are ubiquitous across environment, season, and host phylogeny; (ii) whether microbes that drive decomposition derive primarily from the host or from the environment; and (iii) whether the metabolic succession of microbial decomposition is conserved across the physicochemical context of decay and host phylogeny.Several questions arise: Are microbial decomposer communities ubiquitous? What is the origin of the microbial decomposer community? How does mammalian decomposition affect the metabolic capacity of microbial communities? To answer these questions, we used mouse...

Establishing the time since death is critical in every death investigation, yet existing techniques are susceptible to a range of errors and biases. For example, forensic entomology is widely used to assess the postmortem interval (PMI), but errors can range from days to months. Microbes may provide a novel method for estimating PMI that avoids many of these limitations. Here we show that postmortem microbial community changes are dramatic, measurable, and repeatable in a mouse model system, allowing PMI to be estimated within approximately 3 days over 48 days. Our results provide a detailed understanding of bacterial and microbial eukaryotic ecology within a decomposing corpse system and suggest that microbial community data can be developed into a forensic tool for estimating PMI.DOI: http://dx.doi.org/10.7554/eLife.01104.001

The intestinal microbiota provides colonization resistance against pathogens, limiting pathogen expansion and transmission. These microbiota-mediated mechanisms were previously identified by observing loss of colonization resistance after antibiotic treatment or dietary changes, which severely disrupt microbiota communities. We identify a microbiota-mediated mechanism of colonization resistance against Salmonella enterica serovar Typhimurium (S. Typhimurium) by comparing high-complexity commensal communities with different levels of colonization resistance. Using inbred mouse strains with different infection dynamics and S. Typhimurium intestinal burdens, we demonstrate that Bacteroides species mediate colonization resistance against S. Typhimurium by producing the short-chain fatty acid propionate. Propionate directly inhibits pathogen growth in vitro by disrupting intracellular pH homeostasis, and chemically increasing intestinal propionate levels protects mice from S. Typhimurium. In addition, administering susceptible mice Bacteroides, but not a propionate-production mutant, confers resistance to S. Typhimurium. This work provides mechanistic understanding into the role of individualized microbial communities in host-to-host variability of pathogen transmission.