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ComPIL 2.0: An Updated Comprehensive Metaproteomics Database.

Sung Kyu Robin Park, Titus Jung, Peter S Thuy-Boun

    Journal of Proteome Research
    |December 12, 2018
    PubMed
    Summary
    This summary is machine-generated.

    We developed ComPIL 2.0, an enhanced metaproteomic analysis tool, to rapidly query vast sequence databases. This updated method significantly increases identified peptides and proteins in complex microbiome samples.

    Keywords:
    ComPILProLuCIDmetaproteomicsmicrobiomeproteomics search engine

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    Area of Science:

    • Proteomics
    • Bioinformatics
    • Microbiome Research

    Background:

    • The volume of high-throughput sequencing data has grown exponentially.
    • Existing metaproteomic analysis tools face challenges in querying increasingly large sequence databases.
    • Accurate and rapid querying is crucial for analyzing complex metasamples with unknown compositions.

    Purpose of the Study:

    • To design and present an updated metaproteomic analysis method (ComPIL 2.0) for efficient querying of large sequence databases.
    • To accommodate the growing amount of publicly available sequence data.
    • To improve the analysis of complex samples from human, animal, and environmental microbiomes.

    Main Methods:

    • Rebuilding the ComPIL libraries with updated, publicly disseminated sequence data.
    • Modifying the ProLuCID-ComPIL search engine for optimized querying of experimental spectra.
    • Creating a ComPIL 2.0 database comprising 113 million protein records and approximately 4.8 billion unique tryptic peptide sequences.

    Main Results:

    • ComPIL 2.0 is 2.3 times larger than the original version.
    • Searching a human gut microbiome proteomic sample with ComPIL 2.0 revealed a substantial increase in identified unique peptides and proteins compared to the first ComPIL version.
    • Demonstrated high confidence and accuracy in protein identification.

    Conclusions:

    • ComPIL 2.0 offers a significant advancement for metaproteomic analysis.
    • The enhanced database and search engine facilitate more comprehensive and accurate identification of proteins in complex biological systems.
    • The method's accuracy and confidence may promote its wider adoption for large-scale proteomic annotation.