Considerations for constructing a protein sequence database for metaproteomics.

Considerations for constructing a protein sequence database for metaproteomics.
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DOI:
10.1016/j.csbj.2022.01.018
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发表时间:
2022
影响因子:
6
通讯作者:
Kleiner M
Kleiner M
中科院分区:
生物学2区
文献类型:
--
作者:
Blakeley-Ruiz JA;Kleiner M

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基于质谱的宏蛋白质组学已经成为一种重要的技术,用于询问微生物群落中特定生物体的功能,以及总群落功能。通过质谱法鉴定蛋白质需要将片段肽离子的质谱与样品中蛋白质对应的蛋白质序列数据库相匹配。该序列数据库确定可以从测量中识别哪些蛋白质序列,以及可以从宏蛋白质组学测量中推断出的分类和功能信息。因此,蛋白质序列数据库的构建直接影响到宏蛋白质组学研究的结果。在数据库构建过程中,需要考虑序列信息来源和数据库管理等几个因素,以最大限度地准确识别可追溯到起源物种的蛋白质。在这篇综述中,我们概述了现有的数据库构建策略以及试图测试和验证这些策略的相关研究。基于对文献的回顾和我们的经验,我们提供了选择和实现数据库构建策略的决策树和最佳实践。
Mass spectrometry-based metaproteomics has emerged as a prominent technique for interrogating the functions of specific organisms in microbial communities, in addition to total community function. Identifying proteins by mass spectrometry requires matching mass spectra of fragmented peptide ions to a database of protein sequences corresponding to the proteins in the sample. This sequence database determines which protein sequences can be identified from the measurement, and as such the taxonomic and functional information that can be inferred from a metaproteomics measurement. Thus, the construction of the protein sequence database directly impacts the outcome of any metaproteomics study. Several factors, such as source of sequence information and database curation, need to be considered during database construction to maximize accurate protein identifications traceable to the species of origin. In this review, we provide an overview of existing strategies for database construction and the relevant studies that have sought to test and validate these strategies. Based on this review of the literature and our experience we provide a decision tree and best practices for choosing and implementing database construction strategies.
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