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Immuno-metabolic signaling in leishmaniasis: insights gained from mathematical modeling
MOTIVATION: Leishmaniasis is a global concern especially in underdeveloped and developing subtropical and tropical regions. The extent of infectivity in host is majorly dependent on functional polarization of macrophages. Classically activated M1 macrophage can eliminate parasite through production...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10548086/ https://www.ncbi.nlm.nih.gov/pubmed/37799190 http://dx.doi.org/10.1093/bioadv/vbad125 |
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author | Khandibharad, Shweta Singh, Shailza |
author_facet | Khandibharad, Shweta Singh, Shailza |
author_sort | Khandibharad, Shweta |
collection | PubMed |
description | MOTIVATION: Leishmaniasis is a global concern especially in underdeveloped and developing subtropical and tropical regions. The extent of infectivity in host is majorly dependent on functional polarization of macrophages. Classically activated M1 macrophage can eliminate parasite through production of iNOS and alternatively activated M2 macrophages can promote parasite growth through by providing shelter and nutrients to parasite. The biological processes involved in immune signaling and metabolism of host and parasite might be responsible for deciding fate of parasite. RESULTS: Using systems biology approach, we constructed two mathematical models and inter-regulatory immune-metabolic networks of M1 and M2 state, through which we identified crucial components that are associated with these phenotypes. We also demonstrated how parasite may modulate M1 phenotype for its growth and proliferation and transition to M2 state. Through our previous findings as well as from recent findings we could identify SHP-1 as a key component in regulating the immune-metabolic characterization of M2 macrophage. By targeting SHP-1 at cellular level, it might be possible to modulate immuno-metabolic mechanism and thereby control parasite survival. AVAILABILITY AND IMPLEMENTATION: Mathematical modeling is implemented as a workflow and the models are deposited in BioModel database. FactoMineR is available at: https://github.com/cran/FactoMineR/tree/master. |
format | Online Article Text |
id | pubmed-10548086 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-105480862023-10-05 Immuno-metabolic signaling in leishmaniasis: insights gained from mathematical modeling Khandibharad, Shweta Singh, Shailza Bioinform Adv Original Article MOTIVATION: Leishmaniasis is a global concern especially in underdeveloped and developing subtropical and tropical regions. The extent of infectivity in host is majorly dependent on functional polarization of macrophages. Classically activated M1 macrophage can eliminate parasite through production of iNOS and alternatively activated M2 macrophages can promote parasite growth through by providing shelter and nutrients to parasite. The biological processes involved in immune signaling and metabolism of host and parasite might be responsible for deciding fate of parasite. RESULTS: Using systems biology approach, we constructed two mathematical models and inter-regulatory immune-metabolic networks of M1 and M2 state, through which we identified crucial components that are associated with these phenotypes. We also demonstrated how parasite may modulate M1 phenotype for its growth and proliferation and transition to M2 state. Through our previous findings as well as from recent findings we could identify SHP-1 as a key component in regulating the immune-metabolic characterization of M2 macrophage. By targeting SHP-1 at cellular level, it might be possible to modulate immuno-metabolic mechanism and thereby control parasite survival. AVAILABILITY AND IMPLEMENTATION: Mathematical modeling is implemented as a workflow and the models are deposited in BioModel database. FactoMineR is available at: https://github.com/cran/FactoMineR/tree/master. Oxford University Press 2023-09-14 /pmc/articles/PMC10548086/ /pubmed/37799190 http://dx.doi.org/10.1093/bioadv/vbad125 Text en © The Author(s) 2023. Published by Oxford University Press. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Khandibharad, Shweta Singh, Shailza Immuno-metabolic signaling in leishmaniasis: insights gained from mathematical modeling |
title | Immuno-metabolic signaling in leishmaniasis: insights gained from mathematical modeling |
title_full | Immuno-metabolic signaling in leishmaniasis: insights gained from mathematical modeling |
title_fullStr | Immuno-metabolic signaling in leishmaniasis: insights gained from mathematical modeling |
title_full_unstemmed | Immuno-metabolic signaling in leishmaniasis: insights gained from mathematical modeling |
title_short | Immuno-metabolic signaling in leishmaniasis: insights gained from mathematical modeling |
title_sort | immuno-metabolic signaling in leishmaniasis: insights gained from mathematical modeling |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10548086/ https://www.ncbi.nlm.nih.gov/pubmed/37799190 http://dx.doi.org/10.1093/bioadv/vbad125 |
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