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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-01-01
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| Series: | Current Research in Microbial Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666517422000463 |
| _version_ | 1811178515947585536 |
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| author | Jack Adderley Finn O'Donoghue Christian Doerig Stephen Davis |
| author_facet | Jack Adderley Finn O'Donoghue Christian Doerig Stephen Davis |
| author_sort | Jack Adderley |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-11T06:20:44Z |
| format | Article |
| id | doaj.art-7660cc1e14564112ae30254ae61bbbdd |
| institution | Directory Open Access Journal |
| issn | 2666-5174 |
| language | English |
| last_indexed | 2024-04-11T06:20:44Z |
| publishDate | 2022-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Current Research in Microbial Sciences |
| spelling | doaj.art-7660cc1e14564112ae30254ae61bbbdd2022-12-22T04:40:36ZengElsevierCurrent Research in Microbial Sciences2666-51742022-01-013100149MAPPINGS, a tool for network analysis of large phospho-signalling datasets: application to host erythrocyte response to Plasmodium infectionJack Adderley0Finn O'Donoghue1Christian Doerig2Stephen Davis3School of Health and Biomedical Sciences, RMIT University, Bundoora VIC 3083, Australia; Corresponding authors.School of Science, RMIT University, Melbourne, VIC 3053, AustraliaSchool of Health and Biomedical Sciences, RMIT University, Bundoora VIC 3083, Australia; Corresponding authors.School of Science, RMIT University, Melbourne, VIC 3053, AustraliaLarge 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.http://www.sciencedirect.com/science/article/pii/S2666517422000463SignallingHost-pathogen interactionsComputational network analysisMalaria |
| spellingShingle | Jack Adderley Finn O'Donoghue Christian Doerig Stephen Davis MAPPINGS, a tool for network analysis of large phospho-signalling datasets: application to host erythrocyte response to Plasmodium infection Current Research in Microbial Sciences Signalling Host-pathogen interactions Computational network analysis Malaria |
| 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 | Signalling Host-pathogen interactions Computational network analysis Malaria |
| url | http://www.sciencedirect.com/science/article/pii/S2666517422000463 |
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