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Modeling the metabolic interplay between a parasitic worm and its bacterial endosymbiont allows the identification of novel drug targets

The filarial nematode Brugia malayi represents a leading cause of disability in the developing world, causing lymphatic filariasis in nearly 40 million people. Currently available drugs are not well-suited to mass drug administration efforts, so new treatments are urgently required. One potential vu...

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Autores principales: Curran, David M, Grote, Alexandra, Nursimulu, Nirvana, Geber, Adam, Voronin, Dennis, Jones, Drew R, Ghedin, Elodie, Parkinson, John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7419141/
https://www.ncbi.nlm.nih.gov/pubmed/32779567
http://dx.doi.org/10.7554/eLife.51850
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author Curran, David M
Grote, Alexandra
Nursimulu, Nirvana
Geber, Adam
Voronin, Dennis
Jones, Drew R
Ghedin, Elodie
Parkinson, John
author_facet Curran, David M
Grote, Alexandra
Nursimulu, Nirvana
Geber, Adam
Voronin, Dennis
Jones, Drew R
Ghedin, Elodie
Parkinson, John
author_sort Curran, David M
collection PubMed
description The filarial nematode Brugia malayi represents a leading cause of disability in the developing world, causing lymphatic filariasis in nearly 40 million people. Currently available drugs are not well-suited to mass drug administration efforts, so new treatments are urgently required. One potential vulnerability is the endosymbiotic bacteria Wolbachia—present in many filariae—which is vital to the worm. Genome scale metabolic networks have been used to study prokaryotes and protists and have proven valuable in identifying therapeutic targets, but have only been applied to multicellular eukaryotic organisms more recently. Here, we present iDC625, the first compartmentalized metabolic model of a parasitic worm. We used this model to show how metabolic pathway usage allows the worm to adapt to different environments, and predict a set of 102 reactions essential to the survival of B. malayi. We validated three of those reactions with drug tests and demonstrated novel antifilarial properties for all three compounds.
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spelling pubmed-74191412020-08-12 Modeling the metabolic interplay between a parasitic worm and its bacterial endosymbiont allows the identification of novel drug targets Curran, David M Grote, Alexandra Nursimulu, Nirvana Geber, Adam Voronin, Dennis Jones, Drew R Ghedin, Elodie Parkinson, John eLife Computational and Systems Biology The filarial nematode Brugia malayi represents a leading cause of disability in the developing world, causing lymphatic filariasis in nearly 40 million people. Currently available drugs are not well-suited to mass drug administration efforts, so new treatments are urgently required. One potential vulnerability is the endosymbiotic bacteria Wolbachia—present in many filariae—which is vital to the worm. Genome scale metabolic networks have been used to study prokaryotes and protists and have proven valuable in identifying therapeutic targets, but have only been applied to multicellular eukaryotic organisms more recently. Here, we present iDC625, the first compartmentalized metabolic model of a parasitic worm. We used this model to show how metabolic pathway usage allows the worm to adapt to different environments, and predict a set of 102 reactions essential to the survival of B. malayi. We validated three of those reactions with drug tests and demonstrated novel antifilarial properties for all three compounds. eLife Sciences Publications, Ltd 2020-08-11 /pmc/articles/PMC7419141/ /pubmed/32779567 http://dx.doi.org/10.7554/eLife.51850 Text en © 2020, Curran et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Computational and Systems Biology
Curran, David M
Grote, Alexandra
Nursimulu, Nirvana
Geber, Adam
Voronin, Dennis
Jones, Drew R
Ghedin, Elodie
Parkinson, John
Modeling the metabolic interplay between a parasitic worm and its bacterial endosymbiont allows the identification of novel drug targets
title Modeling the metabolic interplay between a parasitic worm and its bacterial endosymbiont allows the identification of novel drug targets
title_full Modeling the metabolic interplay between a parasitic worm and its bacterial endosymbiont allows the identification of novel drug targets
title_fullStr Modeling the metabolic interplay between a parasitic worm and its bacterial endosymbiont allows the identification of novel drug targets
title_full_unstemmed Modeling the metabolic interplay between a parasitic worm and its bacterial endosymbiont allows the identification of novel drug targets
title_short Modeling the metabolic interplay between a parasitic worm and its bacterial endosymbiont allows the identification of novel drug targets
title_sort modeling the metabolic interplay between a parasitic worm and its bacterial endosymbiont allows the identification of novel drug targets
topic Computational and Systems Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7419141/
https://www.ncbi.nlm.nih.gov/pubmed/32779567
http://dx.doi.org/10.7554/eLife.51850
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