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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2020
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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. |
format | Online Article Text |
id | pubmed-7419141 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
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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