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MAPPINGS, a tool for network analysis of large phospho-signalling datasets: application to host erythrocyte response to Plasmodium infection

Large datasets of phosphorylation interactions are constantly being generated, but deciphering the complex network structure hidden in these datasets remains challenging. Many phosphorylation interactions occurring in human cells have been identified and constitute the basis for the known phosphoryl...

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Detalles Bibliográficos
Autores principales: Adderley, Jack, O'Donoghue, Finn, Doerig, Christian, Davis, Stephen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9325900/
https://www.ncbi.nlm.nih.gov/pubmed/35909628
http://dx.doi.org/10.1016/j.crmicr.2022.100149
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author Adderley, Jack
O'Donoghue, Finn
Doerig, Christian
Davis, Stephen
author_facet Adderley, Jack
O'Donoghue, Finn
Doerig, Christian
Davis, Stephen
author_sort Adderley, Jack
collection PubMed
description Large datasets of phosphorylation interactions are constantly being generated, but deciphering the complex network structure hidden in these datasets remains challenging. Many phosphorylation interactions occurring in human cells have been identified and constitute the basis for the known phosphorylation interaction network. We overlayed onto this network phosphorylation datasets obtained from an antibody microarray approach aimed at determining changes in phospho-signalling of host erythrocytes, during infection with the malaria parasite Plasmodium falciparum. We designed a pathway analysis tool denoted MAPPINGS that uses random walks to identify chains of phosphorylation events occurring much more or much less frequently than expected. MAPPINGS highlights pathways of phosphorylation that work synergistically, providing a rapid interpretation of the most critical pathways in each dataset. MAPPINGS confirmed several signalling interactions previously shown to be modulated by infection, and revealed additional interactions which could form the basis of numerous future studies. The MAPPINGS analysis strategy described here is widely applicable to comparative phosphorylation datasets in any context, such as response of cells to infection, treatment, or comparison between differentiation stages of any cellular population.
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spelling pubmed-93259002022-07-28 MAPPINGS, a tool for network analysis of large phospho-signalling datasets: application to host erythrocyte response to Plasmodium infection Adderley, Jack O'Donoghue, Finn Doerig, Christian Davis, Stephen Curr Res Microb Sci Articles from the special issue: Modern approaches to dissect host-pathogen interactions, edited by Marcio de Castro Silva Filho and Celia Garcia Large datasets of phosphorylation interactions are constantly being generated, but deciphering the complex network structure hidden in these datasets remains challenging. Many phosphorylation interactions occurring in human cells have been identified and constitute the basis for the known phosphorylation interaction network. We overlayed onto this network phosphorylation datasets obtained from an antibody microarray approach aimed at determining changes in phospho-signalling of host erythrocytes, during infection with the malaria parasite Plasmodium falciparum. We designed a pathway analysis tool denoted MAPPINGS that uses random walks to identify chains of phosphorylation events occurring much more or much less frequently than expected. MAPPINGS highlights pathways of phosphorylation that work synergistically, providing a rapid interpretation of the most critical pathways in each dataset. MAPPINGS confirmed several signalling interactions previously shown to be modulated by infection, and revealed additional interactions which could form the basis of numerous future studies. The MAPPINGS analysis strategy described here is widely applicable to comparative phosphorylation datasets in any context, such as response of cells to infection, treatment, or comparison between differentiation stages of any cellular population. Elsevier 2022-06-28 /pmc/articles/PMC9325900/ /pubmed/35909628 http://dx.doi.org/10.1016/j.crmicr.2022.100149 Text en © 2022 The Authors. Published by Elsevier B.V. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Articles from the special issue: Modern approaches to dissect host-pathogen interactions, edited by Marcio de Castro Silva Filho and Celia Garcia
Adderley, Jack
O'Donoghue, Finn
Doerig, Christian
Davis, Stephen
MAPPINGS, a tool for network analysis of large phospho-signalling datasets: application to host erythrocyte response to Plasmodium infection
title MAPPINGS, a tool for network analysis of large phospho-signalling datasets: application to host erythrocyte response to Plasmodium infection
title_full MAPPINGS, a tool for network analysis of large phospho-signalling datasets: application to host erythrocyte response to Plasmodium infection
title_fullStr MAPPINGS, a tool for network analysis of large phospho-signalling datasets: application to host erythrocyte response to Plasmodium infection
title_full_unstemmed MAPPINGS, a tool for network analysis of large phospho-signalling datasets: application to host erythrocyte response to Plasmodium infection
title_short MAPPINGS, a tool for network analysis of large phospho-signalling datasets: application to host erythrocyte response to Plasmodium infection
title_sort mappings, a tool for network analysis of large phospho-signalling datasets: application to host erythrocyte response to plasmodium infection
topic Articles from the special issue: Modern approaches to dissect host-pathogen interactions, edited by Marcio de Castro Silva Filho and Celia Garcia
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9325900/
https://www.ncbi.nlm.nih.gov/pubmed/35909628
http://dx.doi.org/10.1016/j.crmicr.2022.100149
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