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A multiscale mechanistic model of human dendritic cells for in-silico investigation of immune responses and novel therapeutics discovery

Dendritic cells (DCs) are professional antigen-presenting cells (APCs) with the unique ability to mediate inflammatory responses of the immune system. Given the critical role of DCs in shaping immunity, they present an attractive avenue as a therapeutic target to program the immune system and revers...

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Autores principales: Aghamiri, Sara Sadat, Puniya, Bhanwar Lal, Amin, Rada, Helikar, Tomáš
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10040975/
https://www.ncbi.nlm.nih.gov/pubmed/36993954
http://dx.doi.org/10.3389/fimmu.2023.1112985
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author Aghamiri, Sara Sadat
Puniya, Bhanwar Lal
Amin, Rada
Helikar, Tomáš
author_facet Aghamiri, Sara Sadat
Puniya, Bhanwar Lal
Amin, Rada
Helikar, Tomáš
author_sort Aghamiri, Sara Sadat
collection PubMed
description Dendritic cells (DCs) are professional antigen-presenting cells (APCs) with the unique ability to mediate inflammatory responses of the immune system. Given the critical role of DCs in shaping immunity, they present an attractive avenue as a therapeutic target to program the immune system and reverse immune disease disorders. To ensure appropriate immune response, DCs utilize intricate and complex molecular and cellular interactions that converge into a seamless phenotype. Computational models open novel frontiers in research by integrating large-scale interaction to interrogate the influence of complex biological behavior across scales. The ability to model large biological networks will likely pave the way to understanding any complex system in more approachable ways. We developed a logical and predictive model of DC function that integrates the heterogeneity of DCs population, APC function, and cell-cell interaction, spanning molecular to population levels. Our logical model consists of 281 components that connect environmental stimuli with various layers of the cell compartments, including the plasma membrane, cytoplasm, and nucleus to represent the dynamic processes within and outside the DC, such as signaling pathways and cell-cell interactions. We also provided three sample use cases to apply the model in the context of studying cell dynamics and disease environments. First, we characterized the DC response to Sars-CoV-2 and influenza co-infection by in-silico experiments and analyzed the activity level of 107 molecules that play a role in this co-infection. The second example presents simulations to predict the crosstalk between DCs and T cells in a cancer microenvironment. Finally, for the third example, we used the Kyoto Encyclopedia of Genes and Genomes enrichment analysis against the model’s components to identify 45 diseases and 24 molecular pathways that the DC model can address. This study presents a resource to decode the complex dynamics underlying DC-derived APC communication and provides a platform for researchers to perform in-silico experiments on human DC for vaccine design, drug discovery, and immunotherapies.
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spelling pubmed-100409752023-03-28 A multiscale mechanistic model of human dendritic cells for in-silico investigation of immune responses and novel therapeutics discovery Aghamiri, Sara Sadat Puniya, Bhanwar Lal Amin, Rada Helikar, Tomáš Front Immunol Immunology Dendritic cells (DCs) are professional antigen-presenting cells (APCs) with the unique ability to mediate inflammatory responses of the immune system. Given the critical role of DCs in shaping immunity, they present an attractive avenue as a therapeutic target to program the immune system and reverse immune disease disorders. To ensure appropriate immune response, DCs utilize intricate and complex molecular and cellular interactions that converge into a seamless phenotype. Computational models open novel frontiers in research by integrating large-scale interaction to interrogate the influence of complex biological behavior across scales. The ability to model large biological networks will likely pave the way to understanding any complex system in more approachable ways. We developed a logical and predictive model of DC function that integrates the heterogeneity of DCs population, APC function, and cell-cell interaction, spanning molecular to population levels. Our logical model consists of 281 components that connect environmental stimuli with various layers of the cell compartments, including the plasma membrane, cytoplasm, and nucleus to represent the dynamic processes within and outside the DC, such as signaling pathways and cell-cell interactions. We also provided three sample use cases to apply the model in the context of studying cell dynamics and disease environments. First, we characterized the DC response to Sars-CoV-2 and influenza co-infection by in-silico experiments and analyzed the activity level of 107 molecules that play a role in this co-infection. The second example presents simulations to predict the crosstalk between DCs and T cells in a cancer microenvironment. Finally, for the third example, we used the Kyoto Encyclopedia of Genes and Genomes enrichment analysis against the model’s components to identify 45 diseases and 24 molecular pathways that the DC model can address. This study presents a resource to decode the complex dynamics underlying DC-derived APC communication and provides a platform for researchers to perform in-silico experiments on human DC for vaccine design, drug discovery, and immunotherapies. Frontiers Media S.A. 2023-03-10 /pmc/articles/PMC10040975/ /pubmed/36993954 http://dx.doi.org/10.3389/fimmu.2023.1112985 Text en Copyright © 2023 Aghamiri, Puniya, Amin and Helikar https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Aghamiri, Sara Sadat
Puniya, Bhanwar Lal
Amin, Rada
Helikar, Tomáš
A multiscale mechanistic model of human dendritic cells for in-silico investigation of immune responses and novel therapeutics discovery
title A multiscale mechanistic model of human dendritic cells for in-silico investigation of immune responses and novel therapeutics discovery
title_full A multiscale mechanistic model of human dendritic cells for in-silico investigation of immune responses and novel therapeutics discovery
title_fullStr A multiscale mechanistic model of human dendritic cells for in-silico investigation of immune responses and novel therapeutics discovery
title_full_unstemmed A multiscale mechanistic model of human dendritic cells for in-silico investigation of immune responses and novel therapeutics discovery
title_short A multiscale mechanistic model of human dendritic cells for in-silico investigation of immune responses and novel therapeutics discovery
title_sort multiscale mechanistic model of human dendritic cells for in-silico investigation of immune responses and novel therapeutics discovery
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10040975/
https://www.ncbi.nlm.nih.gov/pubmed/36993954
http://dx.doi.org/10.3389/fimmu.2023.1112985
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