4.6 Article

PepMANDIS: A Peptide Selection Tool for Designing Function-Based Targeted Proteomic Assays in Complex Microbial Systems

期刊

FRONTIERS IN CHEMISTRY
卷 9, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fchem.2021.722087

关键词

targeted metaproteomics; in silico peptide selection; LC-MS; MS; microbial functioning; environmental proteomics; microbial ecology; bioinformatics tool

资金

  1. project MOdern UNifying Trends in marine biology - MOUNT - Operational Programme Competitiveness, Entrepreneurship and Innovation (NSRF 20142020) [MIS 5002470]
  2. European Union (European Regional Development Fund) [LQ1601]
  3. Central European Institute of Technology (CEITEC) 2020 from the Czech Ministry of Education, Youth and Sports [LQ1601]

向作者/读者索取更多资源

Most studies focusing on microbial functioning are limited by DNA or RNA sequencing techniques, which often provide a distorted picture of the system. Untargeted proteomics is better suited for this purpose, but efficiency is reduced in complex consortia. Targeted proteomics is more appropriate for investigating specific biological processes, offering superior sensitivity and increased throughput and selectivity.
The majority of studies focusing on microbial functioning in various environments are based on DNA or RNA sequencing techniques that have inherent limitations and usually provide a distorted picture about the functional status of the studied system. Untargeted proteomics is better suited for that purpose, but it suffers from low efficiency when applied in complex consortia. In practice, the scanning capabilities of the currently employed LC-MS/MS systems provide limited coverage of key-acting proteins, hardly allowing a semiquantitative assessment of the most abundant ones from most prevalent species. When particular biological processes of high importance are under investigation, the analysis of specific proteins using targeted proteomics is a more appropriate strategy as it offers superior sensitivity and comes with the added benefits of increased throughput, dynamic range and selectivity. However, the development of targeted assays requires a priori knowledge regarding the optimal peptides to be screened for each protein of interest. In complex, multi-species systems, a specific biochemical process may be driven by a large number of homologous proteins having considerable differences in their amino acid sequence, complicating LC-MS/MS detection. To overcome the complexity of such systems, we have developed an automated pipeline that interrogates UniProt database or user-created protein datasets (e.g. from metagenomic studies) to gather homolog proteins with a defined functional role and extract respective peptide sequences, while it computes several protein/peptide properties and relevant statistics to deduce a small list of the most representative, process-specific and LC-MS/MS-amenable peptides for the microbial enzymatic activity of interest.

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