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培养物扩增宏基因组测序可深入分析囊性纤维化肺病微生物组。

Culture-enriched metagenomic sequencing enables in-depth profiling of the cystic fibrosis lung microbiota.

机构信息

School of Life Sciences, University of Nottingham, Nottingham, UK.

Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, Alberta, Canada.

出版信息

Nat Microbiol. 2020 Feb;5(2):379-390. doi: 10.1038/s41564-019-0643-y. Epub 2020 Jan 20.

DOI:10.1038/s41564-019-0643-y
PMID:31959969
Abstract

Amplicon sequencing (for example, of the 16S rRNA gene) identifies the presence and relative abundance of microbial community members. However, metagenomic sequencing is needed to identify the genetic content and functional potential of a community. Metagenomics is challenging in samples dominated by host DNA, such as those from the skin, tissue and respiratory tract. Here, we combine advances in amplicon and metagenomic sequencing with culture-enriched molecular profiling to study the human microbiota. Using the cystic fibrosis lung as an example, we cultured an average of 82.13% of the operational taxonomic units representing 99.3% of the relative abundance identified in direct sequencing of sputum samples; importantly, culture enrichment identified 63.3% more operational taxonomic units than direct sequencing. We developed the PLate Coverage Algorithm (PLCA) to determine a representative subset of culture plates on which to conduct culture-enriched metagenomics, resulting in the recovery of greater taxonomic diversity-including of low-abundance taxa-with better metagenome-assembled genomes, longer contigs and better functional annotations when compared to culture-independent methods. The PLCA is also applied as a proof of principle to a previously published gut microbiota dataset. Culture-enriched molecular profiling can be used to better understand the role of the human microbiota in health and disease.

摘要

扩增子测序(例如 16S rRNA 基因)可识别微生物群落成员的存在和相对丰度。然而,需要进行宏基因组测序以鉴定群落的遗传内容和功能潜力。在以宿主 DNA 为主的样本中,例如皮肤、组织和呼吸道样本,宏基因组学具有挑战性。在这里,我们将扩增子和宏基因组测序的进展与培养富集的分子分析相结合,以研究人类微生物组。以囊性纤维化肺为例,我们培养了痰液样本直接测序中代表 99.3%相对丰度的操作分类单位的平均 82.13%;重要的是,培养富集比直接测序多鉴定出 63.3%的操作分类单位。我们开发了 PLate Coverage Algorithm (PLCA) 来确定一组有代表性的培养板,以进行培养富集宏基因组学,与非培养方法相比,这导致了更高的分类多样性(包括低丰度分类群)的恢复,具有更好的宏基因组组装基因组、更长的连续体和更好的功能注释。PLCA 也被用作一个原理证明应用于先前发表的肠道微生物组数据集。培养富集的分子分析可以帮助更好地了解人类微生物组在健康和疾病中的作用。

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