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Clostridium difficile infections (CDI) are caused by colonization and growth of toxigenic strains of C. difficile in individuals whose intestinal microbiota has been perturbed, in most cases following antimicrobial therapy. Determination of the protective commensal gut community members could inform the development of treatments for CDI. Here, we utilized the lethal enterocolitis model in Syrian golden hamsters to analyze the microbiota disruption and recovery along a 20-day period following a single dose of clindamycin on day 0, inducing in vivo susceptibility to C. difficile infection. To determine susceptibility in vitro, spores of strain VPI 10463 were cultured with and without soluble hamster fecal filtrates and growth was quantified by quantitative PCR and toxin immunoassay. Fecal microbial population changes over time were tracked by 16S ribosomal RNA gene analysis via V4 sequencing and the PhyloChip assay. C. difficile culture growth and toxin production were inhibited by the presence of fecal extracts from untreated hamsters but not extracts collected 5 days post-administration of clindamycin. In vitro inhibition was re-established by day 15, which correlated with resistance of animals to lethal challenge. A substantial fecal microbiota shift in hamsters treated with antibiotics was observed, marked by significant changes across multiple phyla including Bacteroidetes and Proteobacteria. An incomplete return towards the baseline microbiome occurred by day 15 correlating with the inhibition of C. difficile growth in vitro and in vivo. These data suggest that soluble factors produced by the gut microbiota may be responsible for the suppression of C. difficile growth and toxin production.

The human microbiome substantially affects many aspects of human physiology, including metabolism, drug interactions and numerous diseases. This realization, coupled with ever-improving nucleotide sequencing technology, has precipitated the collection of diverse data sets that profile the microbiome. In the past 2 years, studies have begun to include sufficient numbers of subjects to provide the power to associate these microbiome features with clinical states using advanced algorithms, increasing the use of microbiome studies both individually and collectively. Here we discuss tools and strategies for microbiome studies, from primer selection to bioinformatics analysis.

Here we present a standard developed by the Genomic Standards Consortium (GSC) for reporting marker gene sequences--the minimum information about a marker gene sequence (MIMARKS). We also introduce a system for describing the environment from which a biological sample originates. The 'environmental packages' apply to any genome sequence of known origin and can be used in combination with MIMARKS and other GSC checklists. Finally, to establish a unified standard for describing sequence data and to provide a single point of entry for the scientific community to access and learn about GSC checklists, we present the minimum information about any (x) sequence (MIxS). Adoption of MIxS will enhance our ability to analyze natural genetic diversity documented by massive DNA sequencing efforts from myriad ecosystems in our ever-changing biosphere.

Objectives Differences in gut bacteria have been described in several autoimmune disorders. In this exploratory pilot study, we compared gut bacteria in patients with multiple sclerosis and healthy controls and evaluated the influence of glatiramer acetate and vitamin D treatment on the microbiota. Methods Subjects were otherwise healthy white women with or without relapsing-remitting multiple sclerosis who were vitamin D insufficient. Patients with multiple sclerosis were untreated or were receiving glatiramer acetate. Subjects collected stool at baseline and after 90 days of vitamin D3 (5000 IU/d) supplementation. The abundance of operational taxonomic units was evaluated by hybridization of 16S rRNA to a DNA microarray. Results While there was overlap of gut bacterial communities, the abundance of some operational taxonomic units, including Faecalibacterium, was lower in patients with multiple sclerosis. Glatiramer acetate–treated patients with multiple sclerosis showed differences in community composition compared with untreated subjects, including Bacteroidaceae, Faecalibacterium, Ruminococcus, Lactobacillaceae, Clostridium, and other Clostridiales. Compared with the other groups, untreated patients with multiple sclerosis had an increase in the Akkermansia, Faecalibacterium, and Coprococcus genera after vitamin D supplementation. Conclusions While overall bacterial communities were similar, specific operational taxonomic units differed between healthy controls and patients with multiple sclerosis. Glatiramer acetate and vitamin D supplementation were associated with differences or changes in the microbiota. This study was exploratory, and larger studies are needed to confirm these preliminary results.

Contamination is a critical issue in high-throughput metagenomic studies, yet progress toward a comprehensive solution has been limited. We present SourceTracker, a Bayesian approach to estimate the proportion of contaminants in a given community that come from possible source environments. We applied SourceTracker to microbial surveys from neonatal intensive care units (NICUs), offices and molecular biology laboratories, and provide a database of known contaminants for future testing.

Herbivory is an important modulator of plant biodiversity and productivity in grasslands, but our understanding of herbivore-induced changes on below-ground processes and communities is limited. Using a long-term (17 years) experimental site, we evaluated impacts of rabbit and invertebrate grazers on some soil functions involved in carbon cycling, microbial diversity, structure and functional composition. Both rabbit and invertebrate grazing impacted soil functions and microbial community structure. All functional community measures (functions, biogeochemical cycling genes, network association between different taxa) were more strongly affected by invertebrate grazers than rabbits. Furthermore, our results suggest that exclusion of invertebrate grazers decreases both microbial biomass and abundance of genes associated with key biogeochemical cycles, and could thus have long-term consequences for ecosystem functions. The mechanism behind these impacts are likely to be driven by both direct effects of grazing altering the pattern of nutrient inputs and by indirect effects through changes in plant species composition. However, we could not entirely discount that the pesticide used to exclude invertebrates may have affected some microbial community measures. Nevertheless, our work illustrates that human activity that affects grazing intensity may affect ecosystem functioning and sustainability, as regulated by multi-trophic interactions between above- and below-ground communities.

Background: We present the Biological Observation Matrix (BIOM, pronounced " biome" ) format: a JSON-based file format for representing arbitrary observation by sample contingency tables with associated sample and observation metadata. As the number of categories of comparative omics data types (collectively, the " ome-ome" ) grows rapidly, a general format to represent and archive this data will facilitate the interoperability of existing bioinformatics tools and future meta-analyses.Findings: The BIOM file format is supported by an independent open-source software project (the biom-format project), which initially contains Python objects that support the use and manipulation of BIOM data in Python programs, and is intended to be an open development effort where developers can submit implementations of these objects in other programming languages.Conclusions: The BIOM file format and the biom-format project are steps toward reducing the " bioinformatics bottleneck" that is currently being experienced in diverse areas of biological sciences, and will help us move toward the next phase of comparative omics where basic science is translated into clinical and environmental applications. The BIOM file format is currently recognized as an Earth Microbiome Project Standard, and as a Candidate Standard by the Genomic Standards Consortium. © 2012 2012 McDonald et al.; licensee BioMed Central Ltd.

Gut microbial communities represent one source of human genetic and metabolic diversity. To examine how gut microbiomes differ between human populations when viewed from the perspective of component microbial lineages, encoded metabolic functions, stage of postnatal development, and environmental exposures, we characterized bacterial species present in fecal samples obtained from 531 individuals representing healthy Amerindians from the Amazonas of Venezuela, residents of rural Malawian communities, and inhabitants of USA metropolitan areas, as well as the gene content of 110 of their microbiomes. This cohort encompassed infants, children, teenagers and adults, parents and offspring, and included mono- and dizygotic twins. Shared features of the functional maturation of the gut microbiome were identified during the first three years of life in all three populations, including age-associated changes in the representation of genes involved in vitamin biosynthesis and metabolism. Pronounced differences in bacterial species assemblages and functional gene repertoires were noted between individuals residing in the USA compared to the other two countries. These distinctive features are evident in early infancy as well as adulthood. In addition, the similarity of fecal microbiomes among family members extends across cultures. These findings underscore the need to consider the microbiome when evaluating human development, nutritional needs, physiological variations, and the impact of Westernization.

Commensal microbiota play a critical role in maintaining oral tolerance. The effect of food allergy on the gut microbial ecology remains unknown.We sought to establish the composition of the gut microbiota in experimental food allergy and its role in disease pathogenesis.Food allergy-prone mice with a gain-of-function mutation in the IL-4 receptor α chain (Il4raF709) and wild-type (WT) control animals were subjected to oral sensitization with chicken egg ovalbumin (OVA). Enforced tolerance was achieved by using allergen-specific regulatory T (Treg) cells. Community structure analysis of gut microbiota was performed by using a high-density 16S rDNA oligonucleotide microarrays (PhyloChip) and massively parallel pyrosequencing of 16S rDNA amplicons.OVA-sensitized Il4raF709 mice exhibited a specific microbiota signature characterized by coordinate changes in the abundance of taxa of several bacterial families, including the Lachnospiraceae, Lactobacillaceae, Rikenellaceae, and Porphyromonadaceae. This signature was not shared by similarly sensitized WT mice, which did not exhibit an OVA-induced allergic response. Treatment of OVA-sensitized Il4raF709 mice with OVA-specific Treg cells led to a distinct tolerance-associated signature coincident with the suppression of the allergic response. The microbiota of allergen-sensitized Il4raF709 mice differentially promoted OVA-specific IgE responses and anaphylaxis when reconstituted in WT germ-free mice.Mice with food allergy exhibit a specific gut microbiota signature capable of transmitting disease susceptibility and subject to reprogramming by enforced tolerance. Disease-associated microbiota may thus play a pathogenic role in food allergy.

QIIME (canonically pronounced “chime”) is a software application that performs microbial community analysis. It is an acronym for Quantitative Insights In to Microbial Ecology, and has been used to analyze and interpret nucleic acid sequence data from fungal, viral, bacterial, and archaeal communities. The following protocols describe how to install QIIME on a single computer and use it to analyze microbial 16S sequence data from nine distinct microbial communities.

High-throughput sequencing technologies provide new opportunities to address longstanding questions about habitat adaptation in microbial organisms. How have microbes managed to adapt to such a wide range of environments, and what genomic features allow for such adaptation? We review recent large-scale studies of habitat adaptation, with emphasis on those that utilize phylogenetic techniques. On the basis of current trends, we summarize methodological challenges faced by investigators, and the tools, techniques, and analytical approaches available to overcome them. Phylogenetic approaches and detailed information about each environmental sample will be critical as the ability to collect genome sequences continues to expand.

Coevolution of mammals and their gut microbiota has profoundly affected their radiation into myriad habitats. We used shotgun sequencing of microbial community DNA and targeted sequencing of bacterial 16S ribosomal RNA genes to gain an understanding of how microbial communities adapt to extremes of diet. We sampled fecal DNA from 33 mammalian species and 18 humans who kept detailed diet records, and we found that the adaptation of the microbiota to diet is similar across different mammalian lineages. Functional repertoires of microbiome genes, such as those encoding carbohydrate-active enzymes and proteases, can be predicted from bacterial species assemblages. These results illustrate the value of characterizing vertebrate gut microbiomes to understand host evolutionary histories at a supraorganismal level.

We present the Genomic Standards Consortium’s (GSC) “Minimum Information about an ENvironmental Sequence” (MIENS) standard for describing marker genes. Adoption of MIENS will enhance our ability to analyze natural genetic diversity across the Tree of Life as it is currently being documented by massive DNA sequencing efforts from myriad ecosystems in our ever-changing biosphere.

The development of high-throughput sequencing methods allows for the characterization of microbial communities in a wide range of environments on an unprecedented scale. However, insight into microbial community composition is limited by our ability to detect patterns in this flood of sequences. Here we compare the performance of 51 analysis techniques using real and simulated bacterial 16S rRNA pyrosequencing datasets containing either clustered samples or samples arrayed across environmental gradients. We find that many diversity patterns are evident with severely undersampled communities, and that methods vary widely in their ability to detect gradients and clusters. Chi-squared distances and Pearson correlation distances perform especially well for detecting gradients, while Gower and Canberra distances perform especially well for detecting clusters. These results also provide a basis for understanding tradeoffs between number of samples and depth of coverage, tradeoffs which are important to consider when designing studies to characterize microbial communities.

We present the Genomic Standards Consortium's (GSC) 'Minimum Information about an ENvironmental Sequence' (MIENS) standard for describing marker genes. Adoption of MIENS will enhance our ability to analyze natural genetic diversity across the Tree of Life as it is currently being documented by massive DNA sequencing efforts from myriad ecosystems in our ever-changing biosphere.

Growing interest in the gut microbiome has revealed links between gut microbiome composition and many diseases including not only infections but also obesity, diabetes and inflammatory bowel disease. The microbiome composition can undergo changes as a result of interactions between gut microbiome and exogenous agents. However, the impact of commonly used pharmaceuticals on the gut microbiome has not been well characterized. In this study, we characterized the impact of 24 common pharmaceuticals on gut microbiome compositional shift in mice and in a human fecal culture system. Mice were dosed with each optimized pharmaceutical compound daily for five consecutive days. Fecal samples were collected on day -1, 0, 4 and 5 of the administration. For the human fecal culture system, human stool samples were collected and immediately stored at -80 degree C. After resuspension of the sample in reduced medium, fecal cultures were incubated with individual compounds for 24 hours in an anaerobic chamber. DNA was extracted, then the V4 region of 16S rRNA gene was amplified by PCR and sequenced using the Illumina MiSeq. A negative binomial Wald test was used to detect microbial taxa difference. Principal component analysis exhibits greatest shift in mice microbiome by antimicrobial drugs such as Azithromycin, Amoxicillin and Metronidazole as well as Type 2 diabetes drugs such as Acarbose and Metformin between day 0 and day 5. Permutational multivariate analysis of variance using Euclidean distance exhibited greatest significant microbiome shift by Acarbose, Amoxicillin and Metformin (p 0.1). These results suggest different impact of administration of antimicrobial agents (e.g. protein synthesis inhibitor) and modulation of glucose availability to the intestinal microbiome. Similar microbiome shifts were also observed in the anaerobic human fecal culture system. Understanding the impact of pharmaceuticals to the gut microbiome could ultimately be useful in improving predictions of the therapeutic intervention outcomes on variety of individuals.

Individual bacteria and shifts in the composition of the microbiome have been associated with human diseases including cancer. To investigate changes in the microbiome associated with oral cancers, we profiled cancers and anatomically matched contralateral normal tissue from the same patient by sequencing 16S rDNA hypervariable region amplicons. In cancer samples from both a discovery and a subsequent confirmation cohort, abundance of Firmicutes (especially Streptococcus) and Actinobacteria (especially Rothia) was significantly decreased relative to contralateral clinically normal samples from the same patient. Significant decreases in abundance of these phyla were observed for pre-cancers, but not when comparing samples from contralateral sites (tongue and floor of mouth) from healthy individuals. Patients with cancer or dysplasia, however, could be distinguished from healthy normal individuals by increased abundance of Prevotella. Weighted UniFrac principal coordinates analysis based on 12 taxa separated most cancers from other samples with greatest separation of node positive cases. Citation Format: Donna G. Albertson, Justin Kuczynski, Aditi Bhattacharya, Bing Huey, Patricia M. Corby, Erica L. S. Queiroz, Kira Nightingale, Alexander R. Kerr, Mark D. DeLacure, Ratna Veeramachaneni, Adam Olshen, Brian L. Schmidt. Changes in abundance of oral microbiota associated with oral cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4885. doi:10.1158/1538-7445.AM2014-4885

Individual bacteria and shifts in the composition of the microbiome have been associated with human diseases including cancer. To investigate changes in the microbiome associated with oral cancers, we profiled cancers and anatomically matched contralateral normal tissue from the same patient by sequencing 16S rDNA hypervariable region amplicons. In cancer samples from both a discovery and a subsequent confirmation cohort, abundance of Firmicutes (especially Streptococcus) and Actinobacteria (especially Rothia) was significantly decreased relative to contralateral normal samples from the same patient. Significant decreases in abundance of these phyla were observed for pre-cancers, but not when comparing samples from contralateral sites (tongue and floor of mouth) from healthy individuals. Weighted UniFrac principal coordinates analysis based on 12 taxa separated most cancers from other samples with greatest separation of node positive cases. These studies begin to develop a framework for exploiting the oral microbiome for monitoring oral cancer development, progression and recurrence.

Objective: To compare the composition of gut bacteria in MS patients and healthy controls. Background Alterations in gut bacteria are associated with some autoimmune disorders but have not been assessed in MS. Design/Methods: Subjects were white women with or without relapsing-remitting MS who were vitamin D insufficient but who were otherwise relatively healthy. MS patients were untreated or were receiving glatiramer acetate. Subjects were asked to collect the first morning stool at baseline and after 90 days of daily vitamin D3 supplementation and to ship the samples overnight on ice packs to the laboratory, where they were frozen at -80 degrees. DNA was batch extracted from the stool, and the bacterial profiles were analyzed using a PhyloChip Assay (Second Genome, Inc). Abundance of operational taxonomic units (OTUs) was compared between groups (Adonis tests for significance testing; prediction analysis for microarrays to describe specific taxa). Results: Fifteen subjects participated in the study; among MS patients (n=7), one submitted the initial sample late, while two gave specimens only after supplementation. There was a trend for MS patients and controls to have differences in their microbial communities (Adonis p=0.15), punctuated by differences in Firmicutes, Bacteriodetes, and Proteobacteria OTUs. The bacterial profiles of MS patients treated with glatiramer acetate (n=5) differed from untreated MS patients (Adonis p=0.007). This was largely associated with differences in Firmicutes OTUs. Overall, among both groups, vitamin D therapy led to increased abundance of several Enterobacteriaceae OTUs although among MS patients, notable changes in abundance occurred in Firmicutes, Actinobacteria, and Proteobacteria. Conclusions: MS patients treated with glatiramer acetate may have differences in overall gut bacteria and in the abundance of some taxa compared to untreated patients. Although there was no statistically significant difference in the overall gut microbiome of MS patients and controls, there were some differences in taxa abundances between these populations. Supported by: NIH (EMM: K23NS067055). Disclosure: Dr. Mowry has nothing to disclose. Dr. Waubant has received personal compensation for activities with Teva Neuroscience, Actelion, Sanofi-Aventis Pharmaceuticals, Roche Diagnostics Corporation and Biogen Idec as a speaker and/or consultant. Dr. Waubant has received research support from Biogen Idec and Sanofi-Aventis Pharmaceuticals. Dr. Chehoud has received personal compensation for activities with Second Genome as a consultant. Dr. DeSantis has received personal compensation for activities with Second Genome.Dr. DeSantis holds stock and/or stock options in Second Genome.Dr. DeSantis has received (royalty or license fee or contractual rights) payments from Lawrence Berkeley Laboratories. Dr. Kuczynski has received personal compensation for activities with Second Genome as an employee. Dr. Kuczynski has received research support from Second Genome. Dr. Warrington has received personal compensation for activities with Second Genome, Inc. and Cernostics as an employee and/or participant on an advisory board.

Future sequencing of the human microbiota will require greater breadth rather than depth., Culture-independent studies of human microbiota by direct genomic sequencing reveal quite distinct differences among communities, indicating that improved sequencing capacity can be most wisely utilized to study more samples, rather than more sequences per sample.

High-throughput DNA sequencing is revolutionizing how we study microbial communities. In the past decade, DNA sequencing has undergone an impressive increase in efficiency. For example, with traditional Sanger sequencing, obtaining the sequence of an 800-bp DNA segment costs about $5, whereas the comparable cost when using a newer high-throughput machine would be only about $0.000025—a 200,000-fold difference that allows far more creative projects with far more samples.

Background Murine norovirus (MNV) is the most common gastrointestinal pathogen of research mice and can alter research outcomes in biomedical mouse models of inflammatory bowel disease (IBD). Despite indications that an altered microbiota is a risk factor for IBD, the response of the murine intestinal microbiota to MNV infection has not been examined. Microbiota disruption caused by MNV infection could introduce the confounding effects observed in research experiments. Therefore, this study investigated the effects of MNV infection on the intestinal microbiota of wild-type mice. Results The composition of the intestinal microbiota was assessed over time in both outbred Swiss Webster and inbred C57BL/6 mice following MNV infection. Mice were infected with both persistent and non-persistent MNV strains and tissue-associated or fecal-associated microbiota was analyzed by 16S rRNA-encoding gene pyrosequencing. Analysis of intestinal bacterial communities in infected mice at the phylum and family level showed no major differences to uninfected controls, both in tissue-associated samples and feces, and also over time following infection, demonstrating that the intestinal microbiota of wild-type mice is highly resistant to disruption following MNV infection. Conclusions This is the first study to describe the intestinal microbiota following MNV infection and demonstrates that acute or persistent MNV infection is not associated with major disruptions of microbial communities in Swiss Webster and C57BL/6 mice.