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Predicting functional and regulatory divergence of a drug resistance transporter gene in the human malaria parasite

BACKGROUND: The paradigm of resistance evolution to chemotherapeutic agents is that a key coding mutation in a specific gene drives resistance to a particular drug. In the case of resistance to the anti-malarial drug chloroquine (CQ), a specific mutation in the transporter pfcrt is associated with r...

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Autores principales: Siwo, Geoffrey H, Tan, Asako, Button-Simons, Katrina A, Samarakoon, Upeka, Checkley, Lisa A, Pinapati, Richard S, Ferdig, Michael T
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4352545/
https://www.ncbi.nlm.nih.gov/pubmed/25765049
http://dx.doi.org/10.1186/s12864-015-1261-6
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author Siwo, Geoffrey H
Tan, Asako
Button-Simons, Katrina A
Samarakoon, Upeka
Checkley, Lisa A
Pinapati, Richard S
Ferdig, Michael T
author_facet Siwo, Geoffrey H
Tan, Asako
Button-Simons, Katrina A
Samarakoon, Upeka
Checkley, Lisa A
Pinapati, Richard S
Ferdig, Michael T
author_sort Siwo, Geoffrey H
collection PubMed
description BACKGROUND: The paradigm of resistance evolution to chemotherapeutic agents is that a key coding mutation in a specific gene drives resistance to a particular drug. In the case of resistance to the anti-malarial drug chloroquine (CQ), a specific mutation in the transporter pfcrt is associated with resistance. Here, we apply a series of analytical steps to gene expression data from our lab and leverage 3 independent datasets to identify pfcrt-interacting genes. Resulting networks provide insights into pfcrt’s biological functions and regulation, as well as the divergent phenotypic effects of its allelic variants in different genetic backgrounds. RESULTS: To identify pfcrt-interacting genes, we analyze pfcrt co-expression networks in 2 phenotypic states - CQ-resistant (CQR) and CQ-sensitive (CQS) recombinant progeny clones - using a computational approach that prioritizes gene interactions into functional and regulatory relationships. For both phenotypic states, pfcrt co-expressed gene sets are associated with hemoglobin metabolism, consistent with CQ’s expected mode of action. To predict the drivers of co-expression divergence, we integrate topological relationships in the co-expression networks with available high confidence protein-protein interaction data. This analysis identifies 3 transcriptional regulators from the ApiAP2 family and histone acetylation as potential mediators of these divergences. We validate the predicted divergences in DNA mismatch repair and histone acetylation by measuring the effects of small molecule inhibitors in recombinant progeny clones combined with quantitative trait locus (QTL) mapping. CONCLUSIONS: This work demonstrates the utility of differential co-expression viewed in a network framework to uncover functional and regulatory divergence in phenotypically distinct parasites. pfcrt-associated co-expression in the CQ resistant progeny highlights CQR-specific gene relationships and possible targeted intervention strategies. The approaches outlined here can be readily generalized to other parasite populations and drug resistances. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1261-6) contains supplementary material, which is available to authorized users.
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spelling pubmed-43525452015-03-09 Predicting functional and regulatory divergence of a drug resistance transporter gene in the human malaria parasite Siwo, Geoffrey H Tan, Asako Button-Simons, Katrina A Samarakoon, Upeka Checkley, Lisa A Pinapati, Richard S Ferdig, Michael T BMC Genomics Research Article BACKGROUND: The paradigm of resistance evolution to chemotherapeutic agents is that a key coding mutation in a specific gene drives resistance to a particular drug. In the case of resistance to the anti-malarial drug chloroquine (CQ), a specific mutation in the transporter pfcrt is associated with resistance. Here, we apply a series of analytical steps to gene expression data from our lab and leverage 3 independent datasets to identify pfcrt-interacting genes. Resulting networks provide insights into pfcrt’s biological functions and regulation, as well as the divergent phenotypic effects of its allelic variants in different genetic backgrounds. RESULTS: To identify pfcrt-interacting genes, we analyze pfcrt co-expression networks in 2 phenotypic states - CQ-resistant (CQR) and CQ-sensitive (CQS) recombinant progeny clones - using a computational approach that prioritizes gene interactions into functional and regulatory relationships. For both phenotypic states, pfcrt co-expressed gene sets are associated with hemoglobin metabolism, consistent with CQ’s expected mode of action. To predict the drivers of co-expression divergence, we integrate topological relationships in the co-expression networks with available high confidence protein-protein interaction data. This analysis identifies 3 transcriptional regulators from the ApiAP2 family and histone acetylation as potential mediators of these divergences. We validate the predicted divergences in DNA mismatch repair and histone acetylation by measuring the effects of small molecule inhibitors in recombinant progeny clones combined with quantitative trait locus (QTL) mapping. CONCLUSIONS: This work demonstrates the utility of differential co-expression viewed in a network framework to uncover functional and regulatory divergence in phenotypically distinct parasites. pfcrt-associated co-expression in the CQ resistant progeny highlights CQR-specific gene relationships and possible targeted intervention strategies. The approaches outlined here can be readily generalized to other parasite populations and drug resistances. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1261-6) contains supplementary material, which is available to authorized users. BioMed Central 2015-02-22 /pmc/articles/PMC4352545/ /pubmed/25765049 http://dx.doi.org/10.1186/s12864-015-1261-6 Text en © Siwo et al.; licensee BioMed Central. 2015 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 work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Siwo, Geoffrey H
Tan, Asako
Button-Simons, Katrina A
Samarakoon, Upeka
Checkley, Lisa A
Pinapati, Richard S
Ferdig, Michael T
Predicting functional and regulatory divergence of a drug resistance transporter gene in the human malaria parasite
title Predicting functional and regulatory divergence of a drug resistance transporter gene in the human malaria parasite
title_full Predicting functional and regulatory divergence of a drug resistance transporter gene in the human malaria parasite
title_fullStr Predicting functional and regulatory divergence of a drug resistance transporter gene in the human malaria parasite
title_full_unstemmed Predicting functional and regulatory divergence of a drug resistance transporter gene in the human malaria parasite
title_short Predicting functional and regulatory divergence of a drug resistance transporter gene in the human malaria parasite
title_sort predicting functional and regulatory divergence of a drug resistance transporter gene in the human malaria parasite
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4352545/
https://www.ncbi.nlm.nih.gov/pubmed/25765049
http://dx.doi.org/10.1186/s12864-015-1261-6
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