<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Luth MR</submitter><funding>NIAID NIH HHS</funding><funding>Gates Foundation</funding><funding>NIH HHS</funding><funding>NIGMS NIH HHS</funding><pagination>eadk9893</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11809290</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>386(6725)</volume><pubmed_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 &lt;i>Plasmodium&lt;/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 &lt;i>Plasmodium falciparum&lt;/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 conser</pubmed_abstract><journal>Science (New York, N.Y.)</journal><pubmed_title>Systematic in vitro evolution in &amp;lt;i&amp;gt;Plasmodium falciparum&amp;lt;/i&amp;gt; reveals key determinants of drug resistance.</pubmed_title><pmcid>PMC11809290</pmcid><funding_grant_id>R01 AI185559</funding_grant_id><funding_grant_id>R01 AI152533</funding_grant_id><funding_grant_id>R01 AI154777</funding_grant_id><funding_grant_id>R01 AI182318</funding_grant_id><funding_grant_id>R01 AI103058</funding_grant_id><funding_grant_id>T32 GM008666</funding_grant_id><funding_grant_id>R01 AI172066</funding_grant_id><funding_grant_id>T32 GM139790</funding_grant_id><funding_grant_id>R37 AI050234</funding_grant_id><funding_grant_id>INV-008249</funding_grant_id><funding_grant_id>S10 OD026929</funding_grant_id><funding_grant_id>R01 AI124678</funding_grant_id><funding_grant_id>R01 AI109023</funding_grant_id><funding_grant_id>R01 AI169892</funding_grant_id><pubmed_authors>De Siqueira-Neto JL</pubmed_authors><pubmed_authors>Summers RL</pubmed_authors><pubmed_authors>Ottilie S</pubmed_authors><pubmed_authors>Fidock DA</pubmed_authors><pubmed_authors>Thathy V</pubmed_authors><pubmed_authors>Uhlemann AC</pubmed_authors><pubmed_authors>Sakata-Kato T</pubmed_authors><pubmed_authors>Cheng X</pubmed_authors><pubmed_authors>LaMonte GM</pubmed_authors><pubmed_authors>Lukens AK</pubmed_authors><pubmed_authors>McNamara CW</pubmed_authors><pubmed_authors>Istvan ES</pubmed_authors><pubmed_authors>Kato N</pubmed_authors><pubmed_authors>Godinez-Macias KP</pubmed_authors><pubmed_authors>Ndiaye D</pubmed_authors><pubmed_authors>Winzeler EA</pubmed_authors><pubmed_authors>Palomo Diaz S</pubmed_authors><pubmed_authors>Luth MR</pubmed_authors><pubmed_authors>Gamo FJ</pubmed_authors><pubmed_authors>Lee MCS</pubmed_authors><pubmed_authors>Okombo J</pubmed_authors><pubmed_authors>Narwal SK</pubmed_authors><pubmed_authors>Xia G</pubmed_authors><pubmed_authors>Wirth DF</pubmed_authors><pubmed_authors>Melillo B</pubmed_authors><pubmed_authors>Park H</pubmed_authors><pubmed_authors>Yeo T</pubmed_authors><pubmed_authors>Goldberg DE</pubmed_authors><pubmed_authors>Vanaerschot M</pubmed_authors><pubmed_authors>Dhingra SK</pubmed_authors><pubmed_authors>Rocamora F</pubmed_authors><pubmed_authors>Gomez-Lorenzo MG</pubmed_authors><pubmed_authors>Ndiaye T</pubmed_authors><pubmed_authors>Daggupati S</pubmed_authors><pubmed_authors>Serra G</pubmed_authors><pubmed_authors>Skinner-Adams TS</pubmed_authors><pubmed_authors>Mok S</pubmed_authors><pubmed_authors>Chen D</pubmed_authors><pubmed_authors>Jado JC</pubmed_authors><pubmed_authors>Schreiber SL</pubmed_authors><pubmed_authors>Economy JM</pubmed_authors><pubmed_authors>Davies H</pubmed_authors><pubmed_authors>Small-Saunders JL</pubmed_authors><pubmed_authors>You A</pubmed_authors><pubmed_authors>Pena S</pubmed_authors><pubmed_authors>Edgar RCS</pubmed_authors><pubmed_authors>Tumwebaze PK</pubmed_authors><pubmed_authors>Rosenthal PJ</pubmed_authors></additional><is_claimable>false</is_claimable><name>Systematic in vitro evolution in &amp;lt;i&amp;gt;Plasmodium falciparum&amp;lt;/i&amp;gt; reveals key determinants of drug resistance.</name><description>Surveillance of drug resistance and the discovery of novel targets-key objectives in the fight against malaria-rely on identifying resistance-conferring mutations in &lt;i>Plasmodium&lt;/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 &lt;i>Plasmodium falciparum&lt;/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 conser</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Nov</publication><modification>2026-06-01T13:13:17.313Z</modification><creation>2025-04-04T13:11:47.866Z</creation></dates><accession>S-EPMC11809290</accession><cross_references><pubmed>39607932</pubmed><doi>10.1126/science.adk9893</doi></cross_references></HashMap>