bioRxivGenomicsPreprint
Mapping The Malaria Parasite Drug-Able Genome Using In Vitro Evolution And Chemogenomics
Annie N. CowelliD, Eva S. IstvaniD, Amanda K. LukensiD, Marı́a G. Gómez-LorenzoiD, Manu VanaerschotiD, Tomoyo SakataiD, Erika L. FlanneryiD, Pamela Magistrado-Coxen, Matthew AbrahamiD, Gregory LaMonteiD, Roy M. WilliamsiD, Virginia Franco, María LinaresiD, Ignacio Arriaga, Selina E. R. BoppiD, Victoria C. Corey, Nina F. GnädigiD, Olivia Coburn‐Flynn, Christin ReimeriD, Purva GuptaiD, James M. MurithiiD, Olivia FuchsiD, Erika SasakiiD, Sang Woon KimiD, Christine H. TengiD, , Elizabeth A. WinzeleriD
Abstract
Chemogenetic characterization through in vitro evolution combined with whole genome analysis is a powerful tool to discover novel antimalarial drug targets and identify drug resistance genes. Our comprehensive genome analysis of 262 Plasmodium falciparum parasites treated with 37 diverse compounds reveals how the parasite evolves to evade the action of small molecule growth inhibitors. This detailed data set revealed 159 gene amplifications and 148 nonsynonymous changes in 83 genes which developed during resistance acquisition. Using a new algorithm, we show that gene amplifications contribute to 1/3 of drug resistance acquisition events. In addition to confirming known multidrug resistance mechanisms, we discovered novel multidrug resistance genes. Furthermore, we identified promising new drug target-inhibitor pairs to advance the malaria elimination campaign, including: thymidylate synthase and a benzoquinazolinone, farnesyltransferase and a pyrimidinedione, and a dipeptidylpeptidase and an arylurea. This deep exploration of the P. falciparum resistome and drug-able genome will guide future drug discovery and structural biology efforts, while also advancing our understanding of resistance mechanisms of the deadliest malaria parasite.\n\nOne Sentence SummaryWhole genome sequencing reveals how Plasmodium falciparum evolves resistance to diverse compounds and identifies new antimalarial drug targets.
- organism: human
- assay: whole-genome sequencing
- research focus: drug response / drug discovery
- approach: statistical model
- Citations
- 1
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