将元基因组学和元蛋白组学结合起来,描述肠道微生物群的生态位和代谢本质。

IF 5.1 Q1 ECOLOGY ISME communications Pub Date : 2024-05-01 eCollection Date: 2024-01-01 DOI:10.1093/ismeco/ycae063
Tong Wang, Leyuan Li, Daniel Figeys, Yang-Yu Liu
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引用次数: 0

摘要

微生物的基因组编码了其潜在的功能,这些功能可以通过表达的蛋白质来实现。蛋白质的选择性表达如何取决于其对微生物生长的新陈代谢的重要性或其作为生态壁龛索取资源的能力,这一点仍然难以捉摸。为了揭示蛋白质的代谢或生态作用,我们开发了一个计算管道,它将元基因组学和元蛋白组学数据配对,同时量化每个蛋白质的基因水平和蛋白质水平的功能冗余。我们首先利用消费者资源模型的模拟数据说明了这一计算流程背后的理念。然后,我们利用人类和小鼠肠道微生物组样本的真实数据对其进行了验证。特别是,我们分析了 ABC 型转运体和核糖体蛋白,证实我们的管道所预测的代谢和生态作用与先前的知识非常吻合。最后,我们对人类肠道微生物组样本进行了体外培养,并研究了生态位中涉及的各种糖类的过度供给如何影响群落结构和蛋白质丰度。这些结果证明了我们的管道在确定蛋白质的代谢和生态作用方面的性能,以及它在帮助我们设计营养干预措施以调节人类微生物组方面的潜力。
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Pairing metagenomics and metaproteomics to characterize ecological niches and metabolic essentiality of gut microbiomes.

The genome of a microorganism encodes its potential functions that can be implemented through expressed proteins. It remains elusive how a protein's selective expression depends on its metabolic essentiality to microbial growth or its ability to claim resources as ecological niches. To reveal a protein's metabolic or ecological role, we developed a computational pipeline, which pairs metagenomics and metaproteomics data to quantify each protein's gene-level and protein-level functional redundancy simultaneously. We first illustrated the idea behind the pipeline using simulated data of a consumer-resource model. We then validated it using real data from human and mouse gut microbiome samples. In particular, we analyzed ABC-type transporters and ribosomal proteins, confirming that the metabolic and ecological roles predicted by our pipeline agree well with prior knowledge. Finally, we performed in vitro cultures of a human gut microbiome sample and investigated how oversupplying various sugars involved in ecological niches influences the community structure and protein abundance. The presented results demonstrate the performance of our pipeline in identifying proteins' metabolic and ecological roles, as well as its potential to help us design nutrient interventions to modulate the human microbiome.

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