Mise Kazumori, Iwasaki Wataru
Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan.
Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8568, Japan.
iScience. 2020 Sep 29;23(10):101624. doi: 10.1016/j.isci.2020.101624. eCollection 2020 Oct 23.
The recent prevalence of high-throughput sequencing has been producing numerous prokaryotic community structure datasets. Although the trait-based approach is useful to interpret those datasets from ecological perspectives, available trait information is biased toward culturable prokaryotes, especially those of clinical and public health relevance, and thus may not represent the breadth of microbiota found across many of Earth's environments. To facilitate habitat-based analysis free of such bias, here we report a ready-to-use prokaryotic habitat database, ProkAtlas. ProkAtlas comprehensively links 16S rRNA gene sequences to prokaryotic habitats, using public shotgun metagenome datasets. We also developed a computational pipeline for habitat-based analysis of given prokaryotic community structures. After confirmation of the method effectiveness using 16S rRNA gene sequence datasets from individual genomes and the Earth Microbiome Project, we showed its validness and effectiveness in drawing ecological insights by applying it to six empirical prokaryotic community datasets from soil, aquatic, and human gut samples.
最近高通量测序的普及产生了大量原核生物群落结构数据集。尽管基于特征的方法有助于从生态学角度解释这些数据集,但现有的特征信息偏向于可培养的原核生物,尤其是那些与临床和公共卫生相关的原核生物,因此可能无法代表在地球许多环境中发现的微生物群的广度。为了便于进行无此类偏差的基于栖息地的分析,我们在此报告一个现成的原核生物栖息地数据库ProkAtlas。ProkAtlas利用公开的鸟枪法宏基因组数据集,将16S rRNA基因序列与原核生物栖息地进行全面关联。我们还开发了一个计算流程,用于对给定的原核生物群落结构进行基于栖息地的分析。在使用来自个体基因组和地球微生物组计划的16S rRNA基因序列数据集确认了该方法的有效性后,我们通过将其应用于来自土壤、水生和人类肠道样本的六个经验性原核生物群落数据集,展示了其在得出生态学见解方面的有效性和实用性。