HMP16SData: Efficient Access to the Human Microbiome Project Through Bioconductor.
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ABSTRACT:
SUBMITTER: Schiffer L
PROVIDER: S-EPMC6545282 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The NIH Human Microbiome Project (HMP) has been carried out over ten years and two phases to provide resources, methods, and discoveries that link interactions between humans and their microbiomes to health-related outcomes. The recently completed second phase, the Integrative Human Microbiome Project, comprised studies of dynamic changes in the microbiome and host under three conditions: pregnancy and preterm birth; inflammatory bowel diseases; and stressors that affect individuals with prediabetes. The associated research begins to elucidate mechanisms of host-microbiome interactions under these conditions, provides unique data resources (at the HMP Data Coordination Center), and represents a paradigm for future multi-omic studies of the human microbiome.
| S-EPMC6784865 | biostudies-literature
Project description:BACKGROUND:Despite the increasing recognition that microbial communities within the human body are linked to health, we have an incomplete understanding of the environmental and molecular interactions that shape the composition of these communities. Although host genetic factors play a role in these interactions, these factors have remained relatively unexplored given the requirement for large population-based cohorts in which both genotyping and microbiome characterization have been performed. METHODS:We performed whole-genome sequencing of 298 donors from the Human Microbiome Project (HMP) healthy cohort study to accompany existing deep characterization of their microbiomes at various body sites. This analysis yielded an average sequencing depth of 32x, with which we identified 27 million (M) single nucleotide variants and 2.3 M insertions-deletions. RESULTS:Taxonomic composition and functional potential of the microbiome covaried significantly with genetic principal components in the gastrointestinal tract and oral communities, but not in the nares or vaginal microbiota. Example associations included validation of known associations between FUT2 secretor status, as well as a variant conferring hypolactasia near the LCT gene, with Bifidobacterium longum abundance in stool. The associations of microbial features with both high-level genetic attributes and single variants were specific to particular body sites, highlighting the opportunity to find unique genetic mechanisms controlling microbiome properties in the microbial communities from multiple body sites. CONCLUSIONS:This study adds deep sequencing of host genomes to the body-wide microbiome sequences already extant from the HMP healthy cohort, creating a unique, versatile, and well-controlled reference for future studies seeking to identify host genetic modulators of the microbiome.
| S-EPMC5789541 | biostudies-literature
Project description:The Human Microbiome Project used rigorous good clinical practice standards to complete comprehensive body site sampling in healthy 18- to 40-yr-old adults, creating an unparalleled reference set of microbiome specimens. To ensure that specimens represented minimally perturbed microbiomes, we first screened potential participants using exclusion criteria based on health history, including the presence of systemic diseases (e.g., hypertension, cancer, or immunodeficiency or autoimmune disorders), use of potential immunomodulators, and recent use of antibiotics or probiotics. Subsequent physical examinations excluded individuals based on body mass index (BMI), cutaneous lesions, and oral health. We screened 554 individuals to enroll 300 (149 men and 151 women, mean age 26 yr, mean BMI 24 kg/m, 20.0% racial minority, and 10.7% Hispanic). We obtained specimens from the oral cavity, nares, skin, gastrointestinal tract, and vagina (15 specimens from men and 18 from women). The study evaluated longitudinal changes in an individual's microbiome by sampling 279 participants twice (mean 212 d after the first sampling; range 30-359 d) and 100 individuals 3 times (mean 72 d after the second sampling; range 30-224 d). This sampling strategy yielded 11,174 primary specimens, from which 12,479 DNA samples were submitted to 4 centers for metagenomic sequencing. Our clinical design and well-defined reference cohort has laid a foundation for microbiome research.
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Project description:Most studies describing the human gut microbiome in healthy and diseased states have emphasized the bacterial component, but the fungal microbiome (i.e., the mycobiome) is beginning to gain recognition as a fundamental part of our microbiome. To date, human gut mycobiome studies have primarily been disease centric or in small cohorts of healthy individuals. To contribute to existing knowledge of the human mycobiome, we investigated the gut mycobiome of the Human Microbiome Project (HMP) cohort by sequencing the Internal Transcribed Spacer 2 (ITS2) region as well as the 18S rRNA gene.Three hundred seventeen HMP stool samples were analyzed by ITS2 sequencing. Fecal fungal diversity was significantly lower in comparison to bacterial diversity. Yeast dominated the samples, comprising eight of the top 15 most abundant genera. Specifically, fungal communities were characterized by a high prevalence of Saccharomyces, Malassezia, and Candida, with S. cerevisiae, M. restricta, and C. albicans operational taxonomic units (OTUs) present in 96.8, 88.3, and 80.8% of samples, respectively. There was a high degree of inter- and intra-volunteer variability in fungal communities. However, S. cerevisiae, M. restricta, and C. albicans OTUs were found in 92.2, 78.3, and 63.6% of volunteers, respectively, in all samples donated over an approximately 1-year period. Metagenomic and 18S rRNA gene sequencing data agreed with ITS2 results; however, ITS2 sequencing provided greater resolution of the relatively low abundance mycobiome constituents.Compared to bacterial communities, the human gut mycobiome is low in diversity and dominated by yeast including Saccharomyces, Malassezia, and Candida. Both inter- and intra-volunteer variability in the HMP cohort were high, revealing that unlike bacterial communities, an individual's mycobiome is no more similar to itself over time than to another person's. Nonetheless, several fungal species persisted across a majority of samples, evidence that a core gut mycobiome may exist. ITS2 sequencing data provided greater resolution of the mycobiome membership compared to metagenomic and 18S rRNA gene sequencing data, suggesting that it is a more sensitive method for studying the mycobiome of stool samples.
| S-EPMC5702186 | biostudies-literature
Project description:The characterization of baseline microbial and functional diversity in the human microbiome has enabled studies of microbiome-related disease, diversity, biogeography, and molecular function. The National Institutes of Health Human Microbiome Project has provided one of the broadest such characterizations so far. Here we introduce a second wave of data from the study, comprising 1,631 new metagenomes (2,355 total) targeting diverse body sites with multiple time points in 265 individuals. We applied updated profiling and assembly methods to provide new characterizations of microbiome personalization. Strain identification revealed subspecies clades specific to body sites; it also quantified species with phylogenetic diversity under-represented in isolate genomes. Body-wide functional profiling classified pathways into universal, human-enriched, and body site-enriched subsets. Finally, temporal analysis decomposed microbial variation into rapidly variable, moderately variable, and stable subsets. This study furthers our knowledge of baseline human microbial diversity and enables an understanding of personalized microbiome function and dynamics.
| S-EPMC5831082 | biostudies-literature
Project description:Ecological stoichiometry (ES) uses organism-specific elemental content to explain differences in species life histories, species interactions, community organization, environmental constraints and even ecosystem function. Although ES has been successfully applied to a range of different organisms, most emphasis on microbial ecological stoichiometry focuses on lake, ocean, and soil communities. With the recent advances in human microbiome research, however, large amounts of data are being generated that describe differences in community composition across body sites and individuals. We suggest that ES may provide a framework for beginning to understand the structure, organization, and function of human microbial communities, including why certain organisms exist at certain locations, and how they interact with both the other microbes in their environment and their human host. As a first step, we undertake a stoichioproteomic analysis of microbial communities from different body sites. Specifically, we compare and contrast the elemental composition of microbial protein samples using annotated sequencing data from 690 gut, vaginal, oral, nares, and skin samples currently available through the Human Microbiome Project. Our results suggest significant differences in both the median and variance of the carbon, oxygen, nitrogen, and sulfur contents of microbial protein samples from different locations. For example, whereas proteins from vaginal sites are high in carbon, proteins from skin and nasal sites are high in nitrogen and oxygen. Meanwhile, proteins from stool (the gut) are particularly high in sulfur content. We interpret these differences in terms of the local environments at different human body sites, including atmospheric exposure and food intake rates.
| S-EPMC5513900 | biostudies-literature
Project description:Marine sponges (phylum Porifera) are a diverse, phylogenetically deep-branching clade known for forming intimate partnerships with complex communities of microorganisms. To date, 16S rRNA gene sequencing studies have largely utilised different extraction and amplification methodologies to target the microbial communities of a limited number of sponge species, severely limiting comparative analyses of sponge microbial diversity and structure. Here, we provide an extensive and standardised dataset that will facilitate sponge microbiome comparisons across large spatial, temporal, and environmental scales. Samples from marine sponges (n = 3569 specimens), seawater (n = 370), marine sediments (n = 65) and other environments (n = 29) were collected from different locations across the globe. This dataset incorporates at least 268 different sponge species, including several yet unidentified taxa. The V4 region of the 16S rRNA gene was amplified and sequenced from extracted DNA using standardised procedures. Raw sequences (total of 1.1 billion sequences) were processed and clustered with (i) a standard protocol using QIIME closed-reference picking resulting in 39 543 operational taxonomic units (OTU) at 97% sequence identity, (ii) a de novo clustering using Mothur resulting in 518 246 OTUs, and (iii) a new high-resolution Deblur protocol resulting in 83 908 unique bacterial sequences. Abundance tables, representative sequences, taxonomic classifications, and metadata are provided. This dataset represents a comprehensive resource of sponge-associated microbial communities based on 16S rRNA gene sequences that can be used to address overarching hypotheses regarding host-associated prokaryotes, including host specificity, convergent evolution, environmental drivers of microbiome structure, and the sponge-associated rare biosphere.
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Project description:Much has been learned about the diversity and distribution of human-associated microbial communities, but we still know little about the biology of the microbiome, how it interacts with the host, and how the host responds to its resident microbiota. The Integrative Human Microbiome Project (iHMP, http://hmp2.org), the second phase of the NIH Human Microbiome Project, will study these interactions by analyzing microbiome and host activities in longitudinal studies of disease-specific cohorts and by creating integrated data sets of microbiome and host functional properties. These data sets will serve as experimental test beds to evaluate new models, methods, and analyses on the interactions of host and microbiome. Here we describe the three models of microbiome-associated human conditions, on the dynamics of preterm birth, inflammatory bowel disease, and type 2 diabetes, and their underlying hypotheses, as well as the multi-omic data types to be collected, integrated, and distributed through public repositories as a community resource.
| S-EPMC5109542 | biostudies-literature
Project description:High-throughput sequencing of PCR-amplified taxonomic markers (like the 16S rRNA gene) has enabled a new level of analysis of complex bacterial communities known as microbiomes. Many tools exist to quantify and compare abundance levels or OTU composition of communities in different conditions. The sequencing reads have to be denoised and assigned to the closest taxa from a reference database. Common approaches use a notion of 97% similarity and normalize the data by subsampling to equalize library sizes. In this paper, we show that statistical models allow more accurate abundance estimates. By providing a complete workflow in R, we enable the user to do sophisticated downstream statistical analyses, whether parametric or nonparametric. We provide examples of using the R packages dada2, phyloseq, DESeq2, ggplot2 and vegan to filter, visualize and test microbiome data. We also provide examples of supervised analyses using random forests and nonparametric testing using community networks and the ggnetwork package.
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Project description:Integrative analysis of multi-omics data is a powerful approach for gaining functional insights into biological and medical processes. Conducting these multifaceted analyses on human samples is often complicated by the fact that the raw sequencing output is rarely available under open access. The Personal Genome Project UK (PGP-UK) is one of few resources that recruits its participants under open consent and makes the resulting multi-omics data freely and openly available. As part of this resource, we describe the PGP-UK multi-omics reference panel consisting of ten genomic, methylomic and transcriptomic data. Specifically, we outline the data processing, quality control and validation procedures which were implemented to ensure data integrity and exclude sample mix-ups. In addition, we provide a REST API to facilitate the download of the entire PGP-UK dataset. The data are also available from two cloud-based environments, providing platforms for free integrated analysis. In conclusion, the genotype-validated PGP-UK multi-omics human reference panel described here provides a valuable new open access resource for integrated analyses in support of personal and medical genomics.
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