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Community detection in empirical kinase networks identifies new potential members of signalling pathways

Phosphoproteomics allows one to measure the activity of kinases that drive the fluxes of signal transduction pathways involved in biological processes such as immune function, senescence and cell growth. However, deriving knowledge of signalling network circuitry from these data is challenging due t...

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Autores principales: Basanta, Celia De Los Angeles Colomina, Bazzi, Marya, Hijazi, Maruan, Bessant, Conrad, Cutillas, Pedro R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10325051/
https://www.ncbi.nlm.nih.gov/pubmed/37352361
http://dx.doi.org/10.1371/journal.pcbi.1010459
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author Basanta, Celia De Los Angeles Colomina
Bazzi, Marya
Hijazi, Maruan
Bessant, Conrad
Cutillas, Pedro R.
author_facet Basanta, Celia De Los Angeles Colomina
Bazzi, Marya
Hijazi, Maruan
Bessant, Conrad
Cutillas, Pedro R.
author_sort Basanta, Celia De Los Angeles Colomina
collection PubMed
description Phosphoproteomics allows one to measure the activity of kinases that drive the fluxes of signal transduction pathways involved in biological processes such as immune function, senescence and cell growth. However, deriving knowledge of signalling network circuitry from these data is challenging due to a scarcity of phosphorylation sites that define kinase-kinase relationships. To address this issue, we previously identified around 6,000 phosphorylation sites as markers of kinase-kinase relationships (that may be conceptualised as network edges), from which empirical cell-model-specific weighted kinase networks may be reconstructed. Here, we assess whether the application of community detection algorithms to such networks can identify new components linked to canonical signalling pathways. Phosphoproteomics data from acute myeloid leukaemia (AML) cells treated separately with PI3K, AKT, MEK and ERK inhibitors were used to reconstruct individual kinase networks. We used modularity maximisation to detect communities in each network, and selected the community containing the main target of the inhibitor used to treat cells. These analyses returned communities that contained known canonical signalling components. Interestingly, in addition to canonical PI3K/AKT/mTOR members, the community assignments returned TTK (also known as MPS1) as a likely component of PI3K/AKT/mTOR signalling. We drew similar insights from an external phosphoproteomics dataset from breast cancer cells treated with rapamycin and oestrogen. We confirmed this observation with wet-lab laboratory experiments showing that TTK phosphorylation was decreased in AML cells treated with AKT and MTOR inhibitors. This study illustrates the application of community detection algorithms to the analysis of empirical kinase networks to uncover new members linked to canonical signalling pathways.
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spelling pubmed-103250512023-07-07 Community detection in empirical kinase networks identifies new potential members of signalling pathways Basanta, Celia De Los Angeles Colomina Bazzi, Marya Hijazi, Maruan Bessant, Conrad Cutillas, Pedro R. PLoS Comput Biol Research Article Phosphoproteomics allows one to measure the activity of kinases that drive the fluxes of signal transduction pathways involved in biological processes such as immune function, senescence and cell growth. However, deriving knowledge of signalling network circuitry from these data is challenging due to a scarcity of phosphorylation sites that define kinase-kinase relationships. To address this issue, we previously identified around 6,000 phosphorylation sites as markers of kinase-kinase relationships (that may be conceptualised as network edges), from which empirical cell-model-specific weighted kinase networks may be reconstructed. Here, we assess whether the application of community detection algorithms to such networks can identify new components linked to canonical signalling pathways. Phosphoproteomics data from acute myeloid leukaemia (AML) cells treated separately with PI3K, AKT, MEK and ERK inhibitors were used to reconstruct individual kinase networks. We used modularity maximisation to detect communities in each network, and selected the community containing the main target of the inhibitor used to treat cells. These analyses returned communities that contained known canonical signalling components. Interestingly, in addition to canonical PI3K/AKT/mTOR members, the community assignments returned TTK (also known as MPS1) as a likely component of PI3K/AKT/mTOR signalling. We drew similar insights from an external phosphoproteomics dataset from breast cancer cells treated with rapamycin and oestrogen. We confirmed this observation with wet-lab laboratory experiments showing that TTK phosphorylation was decreased in AML cells treated with AKT and MTOR inhibitors. This study illustrates the application of community detection algorithms to the analysis of empirical kinase networks to uncover new members linked to canonical signalling pathways. Public Library of Science 2023-06-23 /pmc/articles/PMC10325051/ /pubmed/37352361 http://dx.doi.org/10.1371/journal.pcbi.1010459 Text en © 2023 Basanta et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Basanta, Celia De Los Angeles Colomina
Bazzi, Marya
Hijazi, Maruan
Bessant, Conrad
Cutillas, Pedro R.
Community detection in empirical kinase networks identifies new potential members of signalling pathways
title Community detection in empirical kinase networks identifies new potential members of signalling pathways
title_full Community detection in empirical kinase networks identifies new potential members of signalling pathways
title_fullStr Community detection in empirical kinase networks identifies new potential members of signalling pathways
title_full_unstemmed Community detection in empirical kinase networks identifies new potential members of signalling pathways
title_short Community detection in empirical kinase networks identifies new potential members of signalling pathways
title_sort community detection in empirical kinase networks identifies new potential members of signalling pathways
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10325051/
https://www.ncbi.nlm.nih.gov/pubmed/37352361
http://dx.doi.org/10.1371/journal.pcbi.1010459
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