Bioinformatics for the Human Microbiome Project - PubMed (original) (raw)

Bioinformatics for the Human Microbiome Project

Dirk Gevers et al. PLoS Comput Biol. 2012.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1

Figure 1. Bioinformatics in the HMP as a model for further studies of the human microbiome.

Important computational considerations throughout the design, implementation, and analysis of a large human microbiome study such as the HMP; for details of the HMP's specific computational protocols, see , . In the HMP, study design considerations included cohort balancing for gender and geographic location and recruitment of 300 individuals for adequate power. Subject metadata were protected and distributed through dbGaP , and up to three longitudinal samples were drawn from the microbiomes of 18 body habitats. These were tracked and sequenced at up to four distinct centers, including >5,000 16S rRNA gene datasets using 454 reads from the V1–3 and V3–5 hypervariable regions and >700 Illumina whole-genome shotgun datasets totaling over 8 Tbp of sequence. Quality control of sequences and datasets was performed at multiple points throughout data generation. Computational pipelines were developed and documented for each sequence data product as well as downstream analyses, with full results and protocols available at the HMP Data Analysis and Coordinating Center (

http://hmpdacc.org

).

Figure 2

Figure 2. Topics in the study of the human microbiome with outstanding computational biology challenges.

There remain many areas in the study of the human microbiome that will benefit from further bioinformatic efforts. At a whole-population level, the dynamics and stochasticity of microbiome acquisition at birth and its subsequent intersubject transmission must be characterized. As individual hosts, we each expose our microbiomes to unique genetic, dietary, pharmaceutical, and environmental perturbations, which in turn dictate systematic immune responses that are governed by individual sensing and regulatory biomolecular mechanisms. Within our microbiome, both host-microbe and microbe-microbe interactions dictate community ecology. These are governed by a variety of molecular mechanisms well-studied in model microbes including protein–protein interactions, metabolism, regulatory networks, and extracellular transport. In many of the most difficult assay types, such as whole-community proteomics or metabolomics, informatic challenges such as molecular identification remain to be overcome.

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References

    1. Grice EA, Segre JA (2012) Interaction of the microbiome with the innate immune response in chronic wounds. Adv Exp Med Biol 946: 55–68. - PMC - PubMed
    1. Wen L, Ley RE, Volchkov PY, Stranges PB, Avanesyan L, et al. (2008) Innate immunity and intestinal microbiota in the development of Type 1 diabetes. Nature 455: 1109–1113. - PMC - PubMed
    1. Littman DR, Pamer EG (2011) Role of the commensal microbiota in normal and pathogenic host immune responses. Cell Host & Microbe 10: 311–323. - PMC - PubMed
    1. Wooley JC, Godzik A, Friedberg I (2010) A primer on metagenomics. PLoS Comput Biol 6: e1000667 doi:10.1371/journal.pcbi.1000667. - DOI - PMC - PubMed
    1. Hamady M, Knight R (2009) Microbial community profiling for human microbiome projects: tools, techniques, and challenges. Genome Res 19: 1141–1152. - PMC - PubMed

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