Oligotyping analysis of the human oral microbiome

口腔微生物群 人类微生物组计划 微生物群 生物 进化生物学 人体微生物群 分类单元 生物多样性 基因组 生态学 计算生物学 遗传学 基因
作者
A. Murat Eren,Gary G. Borisy,Susan M. Huse,Jessica L. Mark Welch
出处
期刊:Proceedings of the National Academy of Sciences of the United States of America [National Academy of Sciences]
卷期号:111 (28) 被引量:309
标识
DOI:10.1073/pnas.1409644111
摘要

The Human Microbiome Project provided a census of bacterial populations in healthy individuals, but an understanding of the biomedical significance of this census has been hindered by limited taxonomic resolution. A high-resolution method termed oligotyping overcomes this limitation by evaluating individual nucleotide positions using Shannon entropy to identify the most information-rich nucleotide positions, which then define oligotypes. We have applied this method to comprehensively analyze the oral microbiome. Using Human Microbiome Project 16S rRNA gene sequence data for the nine sites in the oral cavity, we identified 493 oligotypes from the V1-V3 data and 360 oligotypes from the V3-V5 data. We associated these oligotypes with species-level taxon names by comparison with the Human Oral Microbiome Database. We discovered closely related oligotypes, differing sometimes by as little as a single nucleotide, that showed dramatically different distributions among oral sites and among individuals. We also detected potentially pathogenic taxa in high abundance in individual samples. Numerous oligotypes were preferentially located in plaque, others in keratinized gingiva or buccal mucosa, and some oligotypes were characteristic of habitat groupings such as throat, tonsils, tongue dorsum, hard palate, and saliva. The differing habitat distributions of closely related oligotypes suggest a level of ecological and functional biodiversity not previously recognized. We conclude that the Shannon entropy approach of oligotyping has the capacity to analyze entire microbiomes, discriminate between closely related but distinct taxa and, in combination with habitat analysis, provide deep insight into the microbial communities in health and disease.
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