Active Genetics & Molecular Biology Infection & Immunity

Understanding the delicate balance of drug resistance and evolutionary fitness in malaria

In plain English

AI plain-English summary

Malaria parasites are evolving to survive the drugs designed to kill them, and this project will map the genetic changes that allow resistance to spread. Artemisinin-based combination therapies are the last line of defence against malaria, but resistance to these drugs has already emerged in Asia and parts of East Africa. If it spreads across Africa, the death toll—already hundreds of thousands of children under five each year—could rise sharply. The puzzle is that the same resistance mutation in the *k13* gene produces different outcomes depending on the parasite’s broader genetic background: Asian strains tolerate the mutation well, while African strains often grow poorly with it. This suggests that other, unknown genes are helping resistance take hold. The project will identify those supporting genes by combining classical genetics with modern genomic sequencing. If successful, it will reveal which genetic environments are “hospitable” to resistance mutations. Surveillance programmes currently monitor only for *k13* mutations; adding these background genes would allow health authorities to predict where resistance is likely to emerge and focus control resources accordingly. This is fundamental evolutionary biology applied to a pressing public health problem. The work does not promise a new drug, but it could make existing surveillance far more precise—potentially buying time to contain resistance before it becomes catastrophic.

View original technical description
Malaria is caused by the mosquito-borne parasite Plasmodium falciparum and causes hundreds of thousands of deaths globally, almost all in children under five. Despite improvements in public health measures, cases have increased in the past decade, partly due to increasing drug resistance. Current first-line treatments are artemisinin-based combination therapies (ACTs), combining artemisinin-based compounds (ART) with a second longer-lasting drug. ART resistance has emerged in Asia and parts of Eastern Africa; spread of resistance across the rest of Africa would lead to a public health catastrophe. ART resistance is driven by alterations in the k13 gene, yet different parasite strains show variable levels of resistance when expressing the same k13 allele. This suggests that other regions of the parasite genome (i.e. the genetic background) also play a critical role in generating ART resistance as a functional outcome. Moreover, in many African strains, parasites with mutant k13 replicate less well, which is called having a "fitness cost". The same fitness cost is not seen in Asian strains that have shown artemisinin resistance for 10-15 years longer. This suggests that for ART resistance to become widespread, fitness costs must be overcome, and that the genetic background of the parasite must play a role. Parasite genetic differences could act by enabling further resistance or compensating for the fitness cost of mutant k13. This “supportive” genetic background appears to be present in Asian strains, but less so in African strains. Resistance to piperaquine (PPQ), a partner drug in ACT, has also been described in South-East Asia, driven by mutations in pfcrt (Plasmodium falciparum chloroquine resistance transporter), a gene also associated with chloroquine resistance. As with ART, studies from the Lee (University of Dundee) and Fidock labs (Columbia University) have shown that PPQ-resistance-associated pfcrt mutations are more likely to cause resistance in Asian strains compared to African strains. This suggests that, like ART resistance, genetic background plays an important role in PPQ resistance. My fellowship aims to leverage traditional genetic approaches from the Fidock lab with state-of-the-art genomic methods from the Lee lab to quantitatively determine how parasite genetic background influences both the fitness cost of drug-resistance mutations and susceptibility to multiple anti-malarial drugs. An improved understanding of the relationship between drug resistance and fitness will provide fundamental insights into the evolutionary biology of malaria parasites, and is vital to design accurate surveillance systems for malaria drug resistance. Currently, surveillance programmes monitor for k13 mutations, but knowing which other genes contribute to fitness in the context of drug selective pressure would mean that these can also be monitored. Because ART resistance in Africa is currently confined to small areas, understanding which areas provide a “hospitable” genetic environment for ART resistance mutations will enable better geographic focusing of resources for malaria control. The major aims of this project are to: Aim 1: Identify P. falciparum genes co-inherited with mutations in k13 or pfcrt that either complement drug resistance or compensate for fitness costs incurred by those mutations. Aim 2: Determine the function of specific genes that are co-inherited with ART-resistant k13 mutations, to identify variants that are necessary or sufficient for increased parasite fitness or resistance. Aim 3: Explore the effect of PPQ-resistance-associated pfcrt mutations on African and Asian strains of P. falciparum, and clarify the role of non-pfcrt genes in PPQ resistance and/or compensatory fitness.

View the original record at the funder ↗

Researchers

Owain Donnelly (Principal Investigator)

Related Research

Grants with similar aims, by meaning.

Next-generation sequencing of barcoded Plasmodium falciparum mutants to dissect parasite fitness costs associated with drug resistance
Plasmodium Falciparum anti-malaria drug resistance in The Gambia: Identification of potential genetic markers by retrospective whole genome approaches
Preventing the transmission of artemisinin resistant falciparum malaria
Evaluating multiple loci modulating susceptibility of African malaria parasites to artemisinin
Novel tools and approaches for safer and more effective treatment of Plasmodium vivax malaria

Original classification

Fellowship

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.