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Gene target discovery with network analysis in Toxoplasma gondii
Infectious diseases are of great relevance for global health, but needed drugs and vaccines have not been developed yet or are not effective in many cases. In fact, traditional scientific approaches with intense focus on individual genes or proteins have not been successful in providing new treatmen...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6345969/ https://www.ncbi.nlm.nih.gov/pubmed/30679502 http://dx.doi.org/10.1038/s41598-018-36671-y |
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author | Alonso, Andres M. Corvi, Maria M. Diambra, Luis |
author_facet | Alonso, Andres M. Corvi, Maria M. Diambra, Luis |
author_sort | Alonso, Andres M. |
collection | PubMed |
description | Infectious diseases are of great relevance for global health, but needed drugs and vaccines have not been developed yet or are not effective in many cases. In fact, traditional scientific approaches with intense focus on individual genes or proteins have not been successful in providing new treatments. Hence, innovations in technology and computational methods provide new tools to further understand complex biological systems such as pathogen biology. In this paper, we apply a gene regulatory network approach to analyze transcriptomic data of the parasite Toxoplasma gondii. By means of an optimization procedure, the phenotypic transitions between the stages associated with the life cycle of T. gondii were embedded into the dynamics of a gene regulatory network. Thus, through this methodology we were able to reconstruct a gene regulatory network able to emulate the life cycle of the pathogen. The community network analysis has revealed that nodes of the network can be organized in seven communities which allow us to assign putative functions to 338 previously uncharacterized genes, 25 of which are predicted as new pathogenic factors. Furthermore, we identified a small gene circuit that drives a series of phenotypic transitions that characterize the life cycle of this pathogen. These new findings can contribute to the understanding of parasite pathogenesis. |
format | Online Article Text |
id | pubmed-6345969 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-63459692019-01-29 Gene target discovery with network analysis in Toxoplasma gondii Alonso, Andres M. Corvi, Maria M. Diambra, Luis Sci Rep Article Infectious diseases are of great relevance for global health, but needed drugs and vaccines have not been developed yet or are not effective in many cases. In fact, traditional scientific approaches with intense focus on individual genes or proteins have not been successful in providing new treatments. Hence, innovations in technology and computational methods provide new tools to further understand complex biological systems such as pathogen biology. In this paper, we apply a gene regulatory network approach to analyze transcriptomic data of the parasite Toxoplasma gondii. By means of an optimization procedure, the phenotypic transitions between the stages associated with the life cycle of T. gondii were embedded into the dynamics of a gene regulatory network. Thus, through this methodology we were able to reconstruct a gene regulatory network able to emulate the life cycle of the pathogen. The community network analysis has revealed that nodes of the network can be organized in seven communities which allow us to assign putative functions to 338 previously uncharacterized genes, 25 of which are predicted as new pathogenic factors. Furthermore, we identified a small gene circuit that drives a series of phenotypic transitions that characterize the life cycle of this pathogen. These new findings can contribute to the understanding of parasite pathogenesis. Nature Publishing Group UK 2019-01-24 /pmc/articles/PMC6345969/ /pubmed/30679502 http://dx.doi.org/10.1038/s41598-018-36671-y Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Alonso, Andres M. Corvi, Maria M. Diambra, Luis Gene target discovery with network analysis in Toxoplasma gondii |
title | Gene target discovery with network analysis in Toxoplasma gondii |
title_full | Gene target discovery with network analysis in Toxoplasma gondii |
title_fullStr | Gene target discovery with network analysis in Toxoplasma gondii |
title_full_unstemmed | Gene target discovery with network analysis in Toxoplasma gondii |
title_short | Gene target discovery with network analysis in Toxoplasma gondii |
title_sort | gene target discovery with network analysis in toxoplasma gondii |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6345969/ https://www.ncbi.nlm.nih.gov/pubmed/30679502 http://dx.doi.org/10.1038/s41598-018-36671-y |
work_keys_str_mv | AT alonsoandresm genetargetdiscoverywithnetworkanalysisintoxoplasmagondii AT corvimariam genetargetdiscoverywithnetworkanalysisintoxoplasmagondii AT diambraluis genetargetdiscoverywithnetworkanalysisintoxoplasmagondii |