Systematic in vitro evolution in <i>Plasmodium falciparum</i> reveals key determinants of drug resistance

Surveillance of drug resistance and the discovery of novel targets-key objectives in the fight against malaria-rely on identifying resistance-conferring mutations in <i>Plasmodium</i> parasites. Current approaches, while successful, require laborious experimentation or large sample sizes. To elucidate shared determinants of antimalarial resistance that can empower in silico inference, we examined the genomes of 724 <i>Plasmodium falciparum</i> clones, each selected in vitro for resistance to one of 118 compounds. We identified 1448 variants in 128 recurrently mutated genes, including drivers of antimalarial multidrug resistance. In contrast to naturally occurring variants, those selected in vitro are more likely to be missense or frameshift, involve bulky substitutions, and occur in conserved, ordered protein domains. Collectively, our dataset reveals mutation features that predict drug resistance in eukaryotic pathogens.

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Publication Details

Journal
Science
Published
2024-11-28
DOI
https://doi.org/10.1126/science.adk9893
Citations
18
Primary Topic
Malaria Research and Control
Type
article
Field-Weighted Citation Impact
9.77

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article

Systematic in vitro evolution in Plasmodium falciparum reveals key determinants of drug resistance

Frances Rocamora, Sabine Ottilie, Francisco‐Javier Gamo, John Okombo et al.
18 citations
Science
Malaria Research and Control
9.77
article

Systematic in vitro evolution in Plasmodium falciparum reveals key determinants of drug resistance

Frances Rocamora, Sabine Ottilie, Francisco‐Javier Gamo, John Okombo, Dyann F. Wirth, Heekuk Park, Marı́a G. Gómez-Lorenzo, Juan Carlos Jado, Daniel E. Goldberg, Jair L. Siqueira-Neto, A. You, Jennifer L. Small-Saunders, Madeline R. Luth, Stuart L. Schreiber, James Economy, Case W. McNamara, Tomas Yeo, Vandana Thathy, Gregory LaMonte, Sachel Mok, Tomoyo Sakata‐Kato, Sara Palomo Dı́az, Tina S. Skinner‐Adams, Karla P. Godinez‐Macias, Manu Vanaerschot, Rebecca Edgar, David A. Fidock, Guoqin Xia, Eva S. Istvan, Sunil Kumar Narwal, Bruno N. Melillo, Philip J. Rosenthal, Patrick K. Tumwebaze, Elizabeth A. Winzeler, Amanda K. Lukens, Gloria Serra, Robert L. Summers, Heledd Davies, Satish K. Dhingra, Daisy Chen, Anne‐Catrin Uhlemann, Xiu Cheng, Lee M, Stella Peña, Tolla Ndiaye, Daouda Ndiaye, Nobutaka Kato, Sindhu Daggupati
article en
18 citations

Abstract

Surveillance of drug resistance and the discovery of novel targets-key objectives in the fight against malaria-rely on identifying resistance-conferring mutations in <i>Plasmodium</i> parasites. Current approaches, while successful, require laborious experimentation or large sample sizes. To elucidate shared determinants of antimalarial resistance that can empower in silico inference, we examined the genomes of 724 <i>Plasmodium falciparum</i> clones, each selected in vitro for resistance to one of 118 compounds. We identified 1448 variants in 128 recurrently mutated genes, including drivers of antimalarial multidrug resistance. In contrast to naturally occurring variants, those selected in vitro are more likely to be missense or frameshift, involve bulky substitutions, and occur in conserved, ordered protein domains. Collectively, our dataset reveals mutation features that predict drug resistance in eukaryotic pathogens.

ScienceVol. 386(6725)
Broad Institute (US), Griffith University (AU), Scripps Research Institute (US), Harvard University (US), University of Dundee (GB), University of California, San Francisco (US), Universidad de la República de Uruguay (UY), Washington University in St. Louis (US), Columbia University Irving Medical Center (US), Wellcome Sanger Institute (GB), University of California San Diego (US), Institute of Health Research, Epidemiological Surveillance and Training (SN), Infectious Diseases Research Collaboration (UG), Wellcome Centre for Anti-Infectives Research (GB), California Institute for Biomedical Research (US), Centro Uruguayo de Imagenología Molecular (UY), Nagasaki University (JP)
Bill and Melinda Gates Foundation, National Institutes of Health, University of California, San Diego
Good health and well-being
Openalex Percentile: Top 1%
Malaria Research and Control
9.77
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