Microbial culturomics: paradigm shift in the human gut microbiome study

基因组 微生物群 生物 人类微生物组计划 焦测序 人体微生物群 系统类型 核糖体RNA 肠道菌群 16S核糖体RNA 基因组 遗传学 微生物学 细菌 基因 免疫学
作者
Jean‐Christophe Lagier,Fabrice Armougom,Matthieu Million,Perrine Hugon,Isabelle Pagnier,Christian P. Robert,Fadi Bittar,Ghislain Fournous,Grégory Gimenez,Marie Maraninchi,J F Trape,Eugene V. Koonin,Bernard La Scola,Didier Raoult
出处
期刊:Clinical Microbiology and Infection [Elsevier BV]
卷期号:18 (12): 1185-1193 被引量:1110
标识
DOI:10.1111/1469-0691.12023
摘要

Comprehensive determination of the microbial composition of the gut microbiota and the relationships with health and disease are major challenges in the 21st century. Metagenomic analysis of the human gut microbiota detects mostly uncultured bacteria. We studied stools from two lean Africans and one obese European, using 212 different culture conditions (microbial culturomics), and tested the colonies by using mass spectrometry and 16S rRNA amplification and sequencing. In parallel, we analysed the same three samples by pyrosequencing 16S rRNA amplicons targeting the V6 region. The 32 500 colonies obtained by culturomics have yielded 340 species of bacteria from seven phyla and 117 genera, including two species from rare phyla (Deinococcus-Thermus and Synergistetes, five fungi, and a giant virus (Senegalvirus). The microbiome identified by culturomics included 174 species never described previously in the human gut, including 31 new species and genera for which the genomes were sequenced, generating c. 10 000 new unknown genes (ORFans), which will help in future molecular studies. Among these, the new species Microvirga massiliensis has the largest bacterial genome so far obtained from a human, and Senegalvirus is the largest virus reported in the human gut. Concurrent metagenomic analysis of the same samples produced 698 phylotypes, including 282 known species, 51 of which overlapped with the microbiome identified by culturomics. Thus, culturomics complements metagenomics by overcoming the depth bias inherent in metagenomic approaches.
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