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The Large Scale Structure of Human Metabolism Reveals Resilience via Extensive Signaling Crosstalk

Metabolism is loosely defined as the set of physical and chemical interactions associated with the processes responsible for sustaining life. Two evident features arise whenever one looks at metabolism: first, metabolism is conformed as a very complex and intertwined construct of the many associated...

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Autores principales: Gómez-Romero, Laura, López-Reyes, Karina, Hernández-Lemus, Enrique
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7772240/
https://www.ncbi.nlm.nih.gov/pubmed/33391012
http://dx.doi.org/10.3389/fphys.2020.588012
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author Gómez-Romero, Laura
López-Reyes, Karina
Hernández-Lemus, Enrique
author_facet Gómez-Romero, Laura
López-Reyes, Karina
Hernández-Lemus, Enrique
author_sort Gómez-Romero, Laura
collection PubMed
description Metabolism is loosely defined as the set of physical and chemical interactions associated with the processes responsible for sustaining life. Two evident features arise whenever one looks at metabolism: first, metabolism is conformed as a very complex and intertwined construct of the many associated biomolecular processes. Second, metabolism is characterized by a high degree of stability reflected by the organisms resilience to either environmental changes or pathogenic conditions. Here we will investigate the relationship between these two features. By having access to the full set of human metabolic interactions as reported in the highly curated KEGG database, we built an integrated human metabolic network comprising metabolic, transcriptional regulation, and protein-protein interaction networks. We hypothesized that a metabolic process may exhibit resilience if it can recover from perturbations at the pathway level; in other words, metabolic resilience could be due to pathway crosstalk which may implicate that a metabolic process could proceed even when a perturbation has occurred. By analyzing the topological structure of the integrated network, as well as the hierarchical structure of its main modules or subnetworks, we observed that behind biological resilience lies an intricate communication structure at the topological and functional level with pathway crosstalk as the main component. The present findings, alongside the advent of large biomolecular databases, such as KEGG may allow the study of the consequences of this redundancy and resilience for the study of healthy and pathological phenotypes with many potential applications in biomedical science.
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spelling pubmed-77722402020-12-31 The Large Scale Structure of Human Metabolism Reveals Resilience via Extensive Signaling Crosstalk Gómez-Romero, Laura López-Reyes, Karina Hernández-Lemus, Enrique Front Physiol Physiology Metabolism is loosely defined as the set of physical and chemical interactions associated with the processes responsible for sustaining life. Two evident features arise whenever one looks at metabolism: first, metabolism is conformed as a very complex and intertwined construct of the many associated biomolecular processes. Second, metabolism is characterized by a high degree of stability reflected by the organisms resilience to either environmental changes or pathogenic conditions. Here we will investigate the relationship between these two features. By having access to the full set of human metabolic interactions as reported in the highly curated KEGG database, we built an integrated human metabolic network comprising metabolic, transcriptional regulation, and protein-protein interaction networks. We hypothesized that a metabolic process may exhibit resilience if it can recover from perturbations at the pathway level; in other words, metabolic resilience could be due to pathway crosstalk which may implicate that a metabolic process could proceed even when a perturbation has occurred. By analyzing the topological structure of the integrated network, as well as the hierarchical structure of its main modules or subnetworks, we observed that behind biological resilience lies an intricate communication structure at the topological and functional level with pathway crosstalk as the main component. The present findings, alongside the advent of large biomolecular databases, such as KEGG may allow the study of the consequences of this redundancy and resilience for the study of healthy and pathological phenotypes with many potential applications in biomedical science. Frontiers Media S.A. 2020-12-16 /pmc/articles/PMC7772240/ /pubmed/33391012 http://dx.doi.org/10.3389/fphys.2020.588012 Text en Copyright © 2020 Gómez-Romero, López-Reyes and Hernández-Lemus. http://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 Physiology
Gómez-Romero, Laura
López-Reyes, Karina
Hernández-Lemus, Enrique
The Large Scale Structure of Human Metabolism Reveals Resilience via Extensive Signaling Crosstalk
title The Large Scale Structure of Human Metabolism Reveals Resilience via Extensive Signaling Crosstalk
title_full The Large Scale Structure of Human Metabolism Reveals Resilience via Extensive Signaling Crosstalk
title_fullStr The Large Scale Structure of Human Metabolism Reveals Resilience via Extensive Signaling Crosstalk
title_full_unstemmed The Large Scale Structure of Human Metabolism Reveals Resilience via Extensive Signaling Crosstalk
title_short The Large Scale Structure of Human Metabolism Reveals Resilience via Extensive Signaling Crosstalk
title_sort large scale structure of human metabolism reveals resilience via extensive signaling crosstalk
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7772240/
https://www.ncbi.nlm.nih.gov/pubmed/33391012
http://dx.doi.org/10.3389/fphys.2020.588012
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