2024-12-09 カリフォルニア大学サンディエゴ校(UCSD)
<関連情報>
- https://today.ucsd.edu/story/a-new-approach-to-predicting-malaria-drug-resistance
- https://www.science.org/doi/10.1126/science.adk9893
マラリア原虫の系統的試験管内進化から薬剤耐性の主要な決定因子が明らかになった Systematic in vitro evolution in Plasmodium falciparum reveals key determinants of drug resistance
Madeline R. Luth, Karla P. Godinez-Macias, Daisy Chen, John Okombo, […], and Elizabeth A. Winzeler
Science Published:29 Nov 2024
DOI:https://doi.org/10.1126/science.adk9893
Editor’s summary
The genomes of the malaria parasite are highly variable, making predictions for evolving drug resistance challenging. Moreover, technical and logistic complexity means that field surveillance for drug resistance is difficult. Luth et al. closely examined the genomes of Plasmodium falciparum clones known to be resistant to a range of antimalarial compounds and identified higher-probability variants in a set of 128 genes. In addition to known targets, new resistance genes and alleles were identified, as well as the characteristics of the genome and encoded proteins that are associated with multidrug resistance. The variants were more likely to be missense or frameshift mutations involving bulky amino acid changes and to occur in conserved protein domains. The prevalence of such molecular markers might offer early warning signals for drug development studies and for adapting regional malaria control policies. —Caroline Ash
Structured Abstract
INTRODUCTION
Malaria parasites frequently evolve resistance to antimalarials in the laboratory and in the field. Because large-scale phenotyping of parasites for drug resistance is impractical, evaluation of the prevalence of molecular markers for drug resistance provides an early warning to inform region-specific malaria treatments. Thus, a major goal of sequencing clinical isolates is to identify the emergence of drug resistance markers and to scan for alleles and regions of the genome under selection. A key challenge in these efforts is distinguishing functional variants that drive the observed phenotype from passenger mutations, which do not confer phenotype changes.
RATIONALE
In vitro evolution and whole-genome analysis, an early discovery method for identifying resistance mechanisms and drug targets, has yielded a rich dataset of mutations found in Plasmodium falciparum parasites resistant to diverse antimalarial compounds. These samples reflect short-term selection, permitting the use of statistical methods to pinpoint mutations underlying resistance phenotypes. Insights into genetic determinants of antimalarial resistance from this dataset may enable in silico methods for identifying resistance-conferring mutations, which are needed to improve genomic surveillance of clinical drug resistance and accelerate target-based drug discovery of novel antimalarials.
RESULTS
Through comprehensive analysis of the whole-genome sequences of 724 P. falciparum clones evolved to resist one of 118 small-molecule growth inhibitors, we identify previously unknown resistance alleles and genes, highlight drivers of multidrug resistance, and show that in vitro evolved variants are more likely to (i) be missense or frameshift, (ii) involve bulky amino acid changes, and (iii) occur in conserved, ordered protein domains. Our data illustrate an evolutionary landscape in which each compound typically selects for driver mutations in only one or a few genes related to the compound’s mechanism of action, but multiple different mutations in a gene, ranging from substitutions near protein binding pockets to copy number amplification, can confer resistance. Copy number variants, in particular, frequently drove resistance by amplifying targets, such as tRNA synthetases, or drug efflux transporters such as PfABCI3 and PfMDR1. Through network analysis, we also found that AP2 transcription factors were often mutated alongside known resistance drivers across selections with different compounds, suggesting roles in culture adaptation or multidrug resistance. By comparing compound susceptibility of parasites with in vitro evolved versus naturally occurring missense variants in the multidrug resistance genes pfmdr1 and pfcarl, as well as a known target, PfATP4, we validated the roles of these in vitro evolved variants in resistance to the compound(s) with which they were selected and observed that protein structural localization is a key differentiator between driver and passenger mutations.
CONCLUSION
Our dataset provides a starting collection for algorithms that can identify genomic changes in clinical isolates that are likely associated with drug resistance in different species. It also presents insights for distinguishing functional from nonfunctional variants in forward genetic approaches.
Resistance-conferring missense mutations occur in conserved, well-ordered protein domains.
P. falciparum multidrug resistance protein 1 (PfMDR1) homology model bound to vincristine (colored orange), highlighting missense variants found in parasite samples worldwide (“field,” colored green), variants associated with resistance phenotypes from in vitro compound selection experiments (“evolved,” colored pink), and variants present in both datasets (colored blue).
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 Plasmodium 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 Plasmodium falciparum 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.
