A Meta-proteogenomic Approach to Peptide Identification Incorporating Assembly Uncertainty and Genomic Variation
A Meta-proteogenomic Approach to Peptide Identification Incorporating Assembly Uncertainty and Genomic Variation
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DOI：
10.1074/mcp.tir118.001233
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发表时间：
2019-08-09
影响因子：
7
通讯作者：
Ye, Yuzhen
中科院分区：
文献类型：
--
作者：
Li, Sujun;Tang, Haixu;Ye, Yuzhen
匹配的宏基因组和/或元转录组数据，目前经常使用不足，可以是有用的参考元蛋白质组串联质谱（MS/MS）数据分析。在这里，我们开发了一个软件管道，用于从元蛋白质组MS/MS数据中识别肽和蛋白质，使用从匹配的元基因组（和元转录组）数据中衍生的蛋白质作为搜索数据库，基于两种新方法Graph 2 Pro（已发布）和Var 2 Pep（新）。Graph 2 Pro保留并使用宏基因组组装的不确定性用于基于参考的MS/MS数据分析。Var 2 Pep考虑了在宏基因组/元转录组测序读段中发现的未保留在组装体（重叠群）中的变异。新的软件流水线提供了两种工具的一站式应用程序，它支持使用常用的组装器（包括MegaHit和MetaSPAdes）进行宏基因组组装。当在两个多组微生物组数据集上进行测试时，与传统的基于重叠群或读取的方法相比，我们的管道将元蛋白质组MS/MS光谱的识别率显著提高了约两倍（仅Var 2 Pep识别了5.6%至24.1%的独特肽，具体取决于数据集）。我们还表明，鉴定的变体肽对于微生物组的功能分析是重要的。所有结果表明，重要的是要考虑到组装的不确定性和基因组变异，以促进元蛋白质组学MS/MS数据的解释。
Matching metagenomic and/or metatranscriptomic data, currently often under-used, can be useful reference for metaproteomic tandem mass spectra (MS/MS) data analysis. Here we developed a software pipeline for identification of peptides and proteins from metaproteomic MS/MS data using proteins derived from matching metagenomic (and metatranscriptomic) data as the search database, based on two novel approaches Graph2Pro (published) and Var2Pep (new). Graph2Pro retains and uses uncertainties of metagenome assembly for reference- based MS/MS data analysis. Var2Pep considers the variations found in metagenomic/metatranscriptomic sequencing reads that are not retained in the assemblies (contigs). The new software pipeline provides one stop application of both tools, and it supports the use of metagenome assembly from commonly used assemblers including MegaHit and metaSPAdes. When tested on two collections of multi-omic microbiome data sets, our pipeline significantly improved the identification rate of the metaproteomic MS/MS spectra by about two folds, comparing to conventional contig-or read-based approaches (the Var2Pep alone identified 5.6% to 24.1% more unique peptides, depending on the data set). We also showed that identified variant peptides are important for functional profiling of microbiomes. All results suggested that it is important to take into consideration of the assembly uncertainties and genomic variants to facilitate metaproteomic MS/MS data interpretation.