使用深度学习分类器和综合蛋白质数据库探究反刍动物的真核微生物。

Probing the eukaryotic microbes of ruminants with a deep-learning classifier and comprehensive protein databases.

作者信息

Yan Ming, Andersen Thea O, Pope Phillip B, Yu Zhongtang

机构信息

Department of Animal Sciences, The Ohio State University, Columbus, Ohio 43210, USA.

Center of Microbiome Science, The Ohio State University, Columbus, Ohio 43210, USA.

出版信息

Genome Res. 2025 Feb 14;35(2):368-378. doi: 10.1101/gr.279825.124.

Abstract

Metagenomics, particularly genome-resolved metagenomics, have significantly deepened our understanding of microbes, illuminating their taxonomic and functional diversity and roles in ecology, physiology, and evolution. However, eukaryotic populations within various microbiomes, including those in the mammalian gastrointestinal (GI) tract, remain relatively underexplored in metagenomic studies owing to the lack of comprehensive reference genome databases and robust bioinformatic tools. The GI tract of ruminants, particularly the rumen, contains a high eukaryotic biomass but a relatively low diversity of ciliates and fungi, which significantly impacts feed digestion, methane emissions, and rumen microbial ecology. In the present study, we developed GutEuk, a bioinformatics tool that improves upon the currently available Tiara and EukRep in accurately identifying eukaryotic sequences from metagenomes. GutEuk is optimized for high precision across different sequence lengths. It can also distinguish fungal and protozoal sequences, further elucidating their unique ecological, physiological, and nutritional impacts. GutEuk was shown to facilitate comprehensive analyses of protozoa and fungi within more than 1000 rumen metagenomes, revealing a greater genomic diversity among protozoa than previously documented. We further curated several ruminant eukaryotic protein databases, significantly enhancing our ability to distinguish the functional roles of ruminant fungi and protozoa from those of prokaryotes. Overall, the newly developed package GutEuk and its associated databases create new opportunities for the in-depth study of GI tract eukaryotes.

摘要

宏基因组学,尤其是基因组解析宏基因组学,极大地加深了我们对微生物的理解,揭示了它们的分类学和功能多样性以及在生态、生理和进化中的作用。然而,由于缺乏全面的参考基因组数据库和强大的生物信息学工具,在宏基因组研究中,包括哺乳动物胃肠道(GI)在内的各种微生物群落中的真核生物群体仍相对未被充分探索。反刍动物的胃肠道,特别是瘤胃,含有较高的真核生物生物量,但纤毛虫和真菌的多样性相对较低,这对饲料消化、甲烷排放和瘤胃微生物生态有显著影响。在本研究中,我们开发了GutEuk,这是一种生物信息学工具,在从宏基因组中准确识别真核生物序列方面比目前可用的Tiara和EukRep有所改进。GutEuk针对不同序列长度进行了高精度优化。它还可以区分真菌和原生动物序列,进一步阐明它们独特的生态、生理和营养影响。结果表明,GutEuk有助于对1000多个瘤胃宏基因组中的原生动物和真菌进行全面分析,揭示原生动物之间比以前记录的更大的基因组多样性。我们进一步整理了几个反刍动物真核生物蛋白质数据库,显著提高了我们区分反刍动物真菌和原生动物与原核生物功能作用的能力。总体而言,新开发的软件包GutEuk及其相关数据库为深入研究胃肠道真核生物创造了新机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/028b/11874962/17288e7e1dfe/368f01.jpg

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