4.7 Article

A community-supported metaproteomic pipeline for improving peptide identifications in hydrothermal vent microbiota

期刊

BRIEFINGS IN BIOINFORMATICS
卷 22, 期 5, 页码 -

出版社

OXFORD UNIV PRESS
DOI: 10.1093/bib/bbab052

关键词

metaproteomics; metagenome data; hydrothermal vent; microbiota; analysis pipeline

资金

  1. National Natural Science Foundation of China [31871329, 41530967, 91951117, 41676177]
  2. Oceanic Interdisciplinary Program of Shanghai Jiao Tong University [SL2020MS022]

向作者/读者索取更多资源

Investigations on metaproteomics of deep-sea hydrothermal vent microbiota can be challenging, but with the right analysis strategy and database, protein identification rates and information richness can significantly increase, providing us with a deeper understanding of microbial lifestyles and metabolic capabilities in extreme environments.
Microorganisms in deep-sea hydrothermal vents provide valuable insights into life under extreme conditions. Mass spectrometry-based proteomics has been widely used to identify protein expression and function. However, the metaproteomic studies in deep-sea microbiota have been constrained largely by the low identification rates of protein or peptide. To improve the efficiency of metaproteomics for hydrothermal vent microbiota, we firstly constructed a microbial gene database (HVentDB) based on 117 public metagenomic samples from hydrothermal vents and proposed a metaproteomic analysis strategy, which takes the advantages of not only the sample-matched metagenome, but also the metagenomic information released publicly in the community of hydrothermal vents. A two-stage false discovery rate method was followed up to control the risk of false positive. By applying our community-supported strategy to a hydrothermal vent sediment sample, about twice as many peptides were identified when compared with the ways against the sample-matched metagenome or the public reference database. In addition, more enriched and explainable taxonomic and functional profiles were detected by the HVentDB-based approach exclusively, as well as many important proteins involved in methane, amino acid, sugar, glycan metabolism and DNA repair, etc. The new metaproteomic analysis strategy will enhance our understanding of microbiota, including their lifestyles and metabolic capabilities in extreme environments. The database HVentDB is freely accessible from http://lilab.life.sjtu.edu.cn:8080/HventDB/main.html.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据