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multiFLEX-LF: a computational approach to quantify the modification stoichiometries in label-free proteomics data sets

  • In liquid-chromatography-tandem-mass-spectrometry-based proteomics, information about the presence and stoichiometry ofprotein modifications is not readily available. To overcome this problem,we developed multiFLEX-LF, a computational tool that builds uponFLEXIQuant, which detects modified peptide precursors and quantifiestheir modification extent by monitoring the differences between observedand expected intensities of the unmodified precursors. multiFLEX-LFrelies on robust linear regression to calculate the modification extent of agiven precursor relative to a within-study reference. multiFLEX-LF cananalyze entire label-free discovery proteomics data sets in a precursor-centric manner without preselecting a protein of interest. To analyzemodification dynamics and coregulated modifications, we hierarchicallyclustered the precursors of all proteins based on their computed relativemodification scores. We applied multiFLEX-LF to a data-independent-acquisition-based data set acquired using the anaphase-promoting complex/cyclosome (APC/C)In liquid-chromatography-tandem-mass-spectrometry-based proteomics, information about the presence and stoichiometry ofprotein modifications is not readily available. To overcome this problem,we developed multiFLEX-LF, a computational tool that builds uponFLEXIQuant, which detects modified peptide precursors and quantifiestheir modification extent by monitoring the differences between observedand expected intensities of the unmodified precursors. multiFLEX-LFrelies on robust linear regression to calculate the modification extent of agiven precursor relative to a within-study reference. multiFLEX-LF cananalyze entire label-free discovery proteomics data sets in a precursor-centric manner without preselecting a protein of interest. To analyzemodification dynamics and coregulated modifications, we hierarchicallyclustered the precursors of all proteins based on their computed relativemodification scores. We applied multiFLEX-LF to a data-independent-acquisition-based data set acquired using the anaphase-promoting complex/cyclosome (APC/C) isolated at various time pointsduring mitosis. The clustering of the precursors allows for identifying varying modification dynamics and ordering the modificationevents. Overall, multiFLEX-LF enables the fast identification of potentially differentially modified peptide precursors and thequantification of their differential modification extent in large data sets using a personal computer. Additionally, multiFLEX-LF candrive the large-scale investigation of the modification dynamics of peptide precursors in time-series and case-control studies.multiFLEX-LF is available athttps://gitlab.com/SteenOmicsLab/multiflex-lf.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Pauline HiortORCiD, Christoph N. SchlaffnerORCiD, Judith A. Steen, Bernhard Y. RenardORCiDGND, Hanno SteenORCiD
DOI:https://doi.org/10.1021/acs.jproteome.1c00669
ISSN:1535-3893
ISSN:1535-3907
Pubmed ID:https://pubmed.ncbi.nlm.nih.gov/35086334
Titel des übergeordneten Werks (Englisch):Journal of proteome research
Verlag:American Chemical Society
Verlagsort:Washington
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Datum der Erstveröffentlichung:27.01.2022
Erscheinungsjahr:2022
Datum der Freischaltung:11.04.2024
Freies Schlagwort / Tag:LC-MS; MS; PTM; bioinformatics tool; label-free quantification; modification stoichiometry; post-translational modification; quantification
Band:21
Ausgabe:4
Seitenanzahl:11
Erste Seite:899
Letzte Seite:909
Fördernde Institution:U.S. National Institutes of Health [S10OD0107060, R01CA196703,; R01AI099204, U01AI124284, R01GM112007]; Deutsche Forschungsgemeinschaft; [RE3474/2-2]; HPI Research School of Data Science and Engineering
Organisationseinheiten:Digital Engineering Fakultät / Hasso-Plattner-Institut für Digital Engineering GmbH
DDC-Klassifikation:5 Naturwissenschaften und Mathematik / 54 Chemie / 540 Chemie und zugeordnete Wissenschaften
5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Peer Review:Referiert
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