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Systems Biology Approach to Model the Life Cycle of Trypanosoma cruzi

Due to recent advances in reprogramming cell phenotypes, many efforts have been dedicated to developing reverse engineering procedures for the identification of gene regulatory networks that emulate dynamical properties associated with the cell fates of a given biological system. In this work, we pr...

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Autores principales: Carrea, Alejandra, Diambra, Luis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4709001/
https://www.ncbi.nlm.nih.gov/pubmed/26752404
http://dx.doi.org/10.1371/journal.pone.0146947
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author Carrea, Alejandra
Diambra, Luis
author_facet Carrea, Alejandra
Diambra, Luis
author_sort Carrea, Alejandra
collection PubMed
description Due to recent advances in reprogramming cell phenotypes, many efforts have been dedicated to developing reverse engineering procedures for the identification of gene regulatory networks that emulate dynamical properties associated with the cell fates of a given biological system. In this work, we propose a systems biology approach for the reconstruction of the gene regulatory network underlying the dynamics of the Trypanosoma cruzi’s life cycle. By means of an optimisation procedure, we embedded the steady state maintenance, and the known phenotypic transitions between these steady states in response to environmental cues, into the dynamics of a gene network model. In the resulting network architecture we identified a small subnetwork, formed by seven interconnected nodes, that controls the parasite’s life cycle. The present approach could be useful for better understanding other single cell organisms with multiple developmental stages.
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spelling pubmed-47090012016-01-15 Systems Biology Approach to Model the Life Cycle of Trypanosoma cruzi Carrea, Alejandra Diambra, Luis PLoS One Research Article Due to recent advances in reprogramming cell phenotypes, many efforts have been dedicated to developing reverse engineering procedures for the identification of gene regulatory networks that emulate dynamical properties associated with the cell fates of a given biological system. In this work, we propose a systems biology approach for the reconstruction of the gene regulatory network underlying the dynamics of the Trypanosoma cruzi’s life cycle. By means of an optimisation procedure, we embedded the steady state maintenance, and the known phenotypic transitions between these steady states in response to environmental cues, into the dynamics of a gene network model. In the resulting network architecture we identified a small subnetwork, formed by seven interconnected nodes, that controls the parasite’s life cycle. The present approach could be useful for better understanding other single cell organisms with multiple developmental stages. Public Library of Science 2016-01-11 /pmc/articles/PMC4709001/ /pubmed/26752404 http://dx.doi.org/10.1371/journal.pone.0146947 Text en © 2016 Carrea, Diambra http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Carrea, Alejandra
Diambra, Luis
Systems Biology Approach to Model the Life Cycle of Trypanosoma cruzi
title Systems Biology Approach to Model the Life Cycle of Trypanosoma cruzi
title_full Systems Biology Approach to Model the Life Cycle of Trypanosoma cruzi
title_fullStr Systems Biology Approach to Model the Life Cycle of Trypanosoma cruzi
title_full_unstemmed Systems Biology Approach to Model the Life Cycle of Trypanosoma cruzi
title_short Systems Biology Approach to Model the Life Cycle of Trypanosoma cruzi
title_sort systems biology approach to model the life cycle of trypanosoma cruzi
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4709001/
https://www.ncbi.nlm.nih.gov/pubmed/26752404
http://dx.doi.org/10.1371/journal.pone.0146947
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