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A Phosphoproteomics Data Resource for Systems-level Modeling of Kinase Signaling Networks

Building mechanistic models of kinase-driven signaling pathways requires quantitative measurements of protein phosphorylation across physiologically relevant conditions, but this is rarely done because of the insensitivity of traditional technologies. By using a multiplexed deep phosphoproteome prof...

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Autores principales: Feng, Song, Sanford, James A., Weber, Thomas, Hutchinson-Bunch, Chelsea M., Dakup, Panshak P., Paurus, Vanessa L., Attah, Kwame, Sauro, Herbert M., Qian, Wei-Jun, Wiley, H. Steven
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10418157/
https://www.ncbi.nlm.nih.gov/pubmed/37577496
http://dx.doi.org/10.1101/2023.08.03.551714
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author Feng, Song
Sanford, James A.
Weber, Thomas
Hutchinson-Bunch, Chelsea M.
Dakup, Panshak P.
Paurus, Vanessa L.
Attah, Kwame
Sauro, Herbert M.
Qian, Wei-Jun
Wiley, H. Steven
author_facet Feng, Song
Sanford, James A.
Weber, Thomas
Hutchinson-Bunch, Chelsea M.
Dakup, Panshak P.
Paurus, Vanessa L.
Attah, Kwame
Sauro, Herbert M.
Qian, Wei-Jun
Wiley, H. Steven
author_sort Feng, Song
collection PubMed
description Building mechanistic models of kinase-driven signaling pathways requires quantitative measurements of protein phosphorylation across physiologically relevant conditions, but this is rarely done because of the insensitivity of traditional technologies. By using a multiplexed deep phosphoproteome profiling workflow, we were able to generate a deep phosphoproteomics dataset of the EGFR-MAPK pathway in non-transformed MCF10A cells across physiological ligand concentrations with a time resolution of <12 min and in the presence and absence of multiple kinase inhibitors. An improved phosphosite mapping technique allowed us to reliably identify >46,000 phosphorylation sites on >6600 proteins, of which >4500 sites from 2110 proteins displayed a >2-fold increase in phosphorylation in response to EGF. This data was then placed into a cellular context by linking it to 15 previously published protein databases. We found that our results were consistent with much, but not all previously reported data regarding the activation and negative feedback phosphorylation of core EGFR-ERK pathway proteins. We also found that EGFR signaling is biphasic with substrates downstream of RAS/MAPK activation showing a maximum response at <3ng/ml EGF while direct substrates, such as HGS and STAT5B, showing no saturation. We found that RAS activation is mediated by at least 3 parallel pathways, two of which depend on PTPN11. There appears to be an approximately 4-minute delay in pathway activation at the step between RAS and RAF, but subsequent pathway phosphorylation was extremely rapid. Approximately 80 proteins showed a >2-fold increase in phosphorylation across all experiments and these proteins had a significantly higher median number of phosphorylation sites (~18) relative to total cellular phosphoproteins (~4). Over 60% of EGF-stimulated phosphoproteins were downstream of MAPK and included mediators of cellular processes such as gene transcription, transport, signal transduction and cytoskeletal arrangement. Their phosphorylation was either linear with respect to MAPK activation or biphasic, corresponding to the biphasic signaling seen at the level of the EGFR. This deep, integrated phosphoproteomics data resource should be useful in building mechanistic models of EGFR and MAPK signaling and for understanding how downstream responses are regulated.
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spelling pubmed-104181572023-08-12 A Phosphoproteomics Data Resource for Systems-level Modeling of Kinase Signaling Networks Feng, Song Sanford, James A. Weber, Thomas Hutchinson-Bunch, Chelsea M. Dakup, Panshak P. Paurus, Vanessa L. Attah, Kwame Sauro, Herbert M. Qian, Wei-Jun Wiley, H. Steven bioRxiv Article Building mechanistic models of kinase-driven signaling pathways requires quantitative measurements of protein phosphorylation across physiologically relevant conditions, but this is rarely done because of the insensitivity of traditional technologies. By using a multiplexed deep phosphoproteome profiling workflow, we were able to generate a deep phosphoproteomics dataset of the EGFR-MAPK pathway in non-transformed MCF10A cells across physiological ligand concentrations with a time resolution of <12 min and in the presence and absence of multiple kinase inhibitors. An improved phosphosite mapping technique allowed us to reliably identify >46,000 phosphorylation sites on >6600 proteins, of which >4500 sites from 2110 proteins displayed a >2-fold increase in phosphorylation in response to EGF. This data was then placed into a cellular context by linking it to 15 previously published protein databases. We found that our results were consistent with much, but not all previously reported data regarding the activation and negative feedback phosphorylation of core EGFR-ERK pathway proteins. We also found that EGFR signaling is biphasic with substrates downstream of RAS/MAPK activation showing a maximum response at <3ng/ml EGF while direct substrates, such as HGS and STAT5B, showing no saturation. We found that RAS activation is mediated by at least 3 parallel pathways, two of which depend on PTPN11. There appears to be an approximately 4-minute delay in pathway activation at the step between RAS and RAF, but subsequent pathway phosphorylation was extremely rapid. Approximately 80 proteins showed a >2-fold increase in phosphorylation across all experiments and these proteins had a significantly higher median number of phosphorylation sites (~18) relative to total cellular phosphoproteins (~4). Over 60% of EGF-stimulated phosphoproteins were downstream of MAPK and included mediators of cellular processes such as gene transcription, transport, signal transduction and cytoskeletal arrangement. Their phosphorylation was either linear with respect to MAPK activation or biphasic, corresponding to the biphasic signaling seen at the level of the EGFR. This deep, integrated phosphoproteomics data resource should be useful in building mechanistic models of EGFR and MAPK signaling and for understanding how downstream responses are regulated. Cold Spring Harbor Laboratory 2023-08-03 /pmc/articles/PMC10418157/ /pubmed/37577496 http://dx.doi.org/10.1101/2023.08.03.551714 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Feng, Song
Sanford, James A.
Weber, Thomas
Hutchinson-Bunch, Chelsea M.
Dakup, Panshak P.
Paurus, Vanessa L.
Attah, Kwame
Sauro, Herbert M.
Qian, Wei-Jun
Wiley, H. Steven
A Phosphoproteomics Data Resource for Systems-level Modeling of Kinase Signaling Networks
title A Phosphoproteomics Data Resource for Systems-level Modeling of Kinase Signaling Networks
title_full A Phosphoproteomics Data Resource for Systems-level Modeling of Kinase Signaling Networks
title_fullStr A Phosphoproteomics Data Resource for Systems-level Modeling of Kinase Signaling Networks
title_full_unstemmed A Phosphoproteomics Data Resource for Systems-level Modeling of Kinase Signaling Networks
title_short A Phosphoproteomics Data Resource for Systems-level Modeling of Kinase Signaling Networks
title_sort phosphoproteomics data resource for systems-level modeling of kinase signaling networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10418157/
https://www.ncbi.nlm.nih.gov/pubmed/37577496
http://dx.doi.org/10.1101/2023.08.03.551714
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