期刊
JOURNAL OF PROTEOME RESEARCH
卷 18, 期 2, 页码 616-622出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.8b00722
关键词
ComPIL; ProLuCID; proteomics search engine; microbiome; metaproteomics
资金
- Scripps Research Institute
- Boehringer Ingelheim
- US Environmental Protection Agency STAR Predoctoral Fellowship [FP917296-01-0]
- National Institutes of Health [1R56 AG057459, 5R33 CA212973, 5R01 HL131697, 5P41 GM103533, 5R01 MH067880, 5R01 AI113867]
We designed a metaproteomic analysis method (ComPIL) to accommodate the ever-increasing number of sequences against which experimental shotgun proteomics spectra could be accurately and rapidly queried. Our objective was to create these large databases for the analysis of complex metasamples with unknown composition, including those derived from human, animal, and environmental microbiomes. The amount of high-throughput sequencing data has substantially increased since our original database was assembled in 2014. Here, we present a rebuild of the ComPIL libraries comprised of updated publicly disseminated sequence data as well as a modified version of the search engine ProLuCID-ComPIL optimized for querying experimental spectra. ComPIL 2.0 consists of 113 million protein records and roughly 4.8 billion unique tryptic peptide sequences and is 2.3 times the size of our original version. We searched a data set collected on a healthy human gut microbiome proteomic sample and compared the results to demonstrate that ComPIL 2.0 showed a substantial increase in the number of unique identified peptides and proteins compared to the first ComPIL version. The high confidence of protein identification and accuracy demonstrated by the use of ComPIL 2.0 may encourage the method's application for large-scale proteomic annotation of complex protein systems.
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