Jacques Izard, The Forsyth Institute
Background/Question/Methods
To understand what triggers changes in microbial community composition and how these changes affect our health, the first step is to find out who is there (by detecting genes using metagenomics) and what is that they do (by detecting gene activity using transcriptomics). Both metagenomic and transcriptomic approaches rely on gene sequences. While technology to produce the sequence data is rapidly advancing a few major hurdles subsist. For example: 1) the lack of genomic data specific to the microbiota observed and the lack of associated annotation to interpret metagenomic data, 2) the lack of clear taxonomy to understand the microbiome in function of published data, and 3) the lack of strains to work with that could be used as models in the laboratory. One of the most studied and best characterized microbial community in humans is the dental plaque. With bacterial members in over 600 taxa, 170 genera and 13 phyla, the diversity is undeniable. This diversity, however, was not represented in culture collection deposits nor in GenBank.
Results/Conclusions
Mining private bacterial culture collections of isolates from the oral cavity, we were able to identify strains for phylotypes (sequence groups) previously thought to be detected only by culture-independent methods. Over 100 different strains have been included in the Human Microbiome Project (HMP) sequencing effort (http://hmpdacc.org) by our group and the genomes and annotation are publicly available. The strains have been deposited at the Biodefense and Emerging Infections Research Resources Repository (http://beiresources.org) for public access of model strains. The phylogenetic relatedness of the strains has been clarified by creating the Human Oral Taxon (HOT) classification. Each HOT is a phylotype defined as a cluster of 16S rRNA gene sequences that have greater than 98.5% similarity to one another. Investigators can also identify their 16S rDNA sequence(s) using a Blast search at the Human Oral Microbiome Database (http://homd.org). This curated database allows in depth analysis of the biodiversity of the oral microbiome.
An estimated 300 genomes from oral isolates will be sequenced and annotated. One can start at looking for what microbial diversity means at a body site. Can commensalism and pathogenicity be predicted? Are there predictors of population shifts that are disease associated?