Shotgun proteomics aims to identify and quantify the thousands of proteins in complex mixtures such as cell and tissue lysates and biological fluids. This approach uses liquid chromatography coupled with tandem mass spectrometry and typically generates hundreds of thousands of mass spectra that require specialized computational environments for data analysis. PatternLab for proteomics is a unified computational environment for analyzing shotgun proteomic data. PatternLab V (PLV) is the most comprehensive and crucial update so far, the result of intensive interaction with the proteomics community over several years. All PLV modules have been optimized and its graphical user interface has been completely updated for improved user experience. Major improvements were made to all aspects of the software, ranging from boosting the number of protein identifications to faster extraction of ion chromatograms. PLV provides modules for preparing sequence databases, protein identification, statistical filtering and in-depth result browsing for both labeled and label-free quantitation. The PepExplorer module can even pinpoint de novo sequenced peptides not already present in the database. PLV is of broad applicability and therefore suitable for challenging experimental setups, such as time-course experiments and data handling from unsequenced organisms. PLV interfaces with widely adopted software and community initiatives, e.g., Comet, Skyline, PEAKS and PRIDE. It is freely available at http://www.patternlabforproteomics.org.
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The software used in this protocol can be found at http://patternlabforproteomics.org
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We thank W. Nagib, from Fiocruz, for creating the new PatternLab logo and entrance screen and J. Eng, from the University of Washington, for all the support and adaptations in the Comet search engine. We thank Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ), Fiocruz, and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) for financial support. R.H.V. (grant 304523/2019-4), V.C.B. (grant 300987/2019-6) and P.C.C. (grant 308930/2020-7) are CNPq research fellows. J.R.Y. acknowledges NIH P41 GM103533.
The authors declare no competing interests.
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Key references using this protocol
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Key data used in this protocol
Camillo-Andrade, A. C. et al. Sci. Rep. 10, 19392 (2020): https://doi.org/10.1038/s41598-020-76325-6
Shalit, T. et al. Proteome Res. 14, 1979–1986 (2015): https://doi.org/10.1021/pr501045t
This protocol is an update to Nat. Protoc. 11, 102–117 (2015): https://doi.org/10.1038/nprot.2015.133
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Santos, M.D.M., Lima, D.B., Fischer, J.S.G. et al. Simple, efficient and thorough shotgun proteomic analysis with PatternLab V. Nat Protoc 17, 1553–1578 (2022). https://doi.org/10.1038/s41596-022-00690-x