Tackling Malaria Resistance with an Integrated Modeling/Experimental Approach

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 DESCRIPTION (provided by applicant): Malaria is responsible for almost a million deaths per year across the world. Plasmodium falciparum, the causative agent of the most deadly form of this disease, can readily develop resistance when treated with antimalarial drugs. Laboratory-reared resistant lines allow us to study how these parasites survive during drug challenge and help to inform more successful treatment strategies. Both clinical and laboratory investigations reveal that resistant parasites have specific changes in their genome that lead to excess amounts of the target protein (through genomic amplification) or the physical prevention of drug binding (through mutations). Because metabolism within an organism is highly interconnected with all cellular processes, pathways that interact with the mutated target must also make adjustments to support the parasite's continued ability to thrive. Some of these metabolic shifts may be minor and go unnoticed while others could confer unexpected benefits such as cross-resistance to additional drugs. This proposal describes a multifaceted approach to uncover and then impede these metabolic shifts that "enhance" parasite survival. Using an existing experimental system in which cross-resistance between two clinically-relevant antimalarials was observed, we will: 1) employ metabolomics data to construct a biologically accurate metabolic network reconstruction of the parasite before and after the generation of resistance in order identify metabolic dependencies of the resistant state and 2) computationally and empirically interrogate these critical pathways to determine if their abrogation can prevent P. falciparum resistance. Given that this work involves the disease-causing organism, which is refractory to experimental manipulation, computational models help to focus hypotheses and experimental design and mitigate risk. Additionally, since we are working with a validated experimental system and the approach takes advantage of expertise of the co-PIs involved in this proposal, we are well-positioned to rapidly build a pipeline of effective computational and experimental approaches. Once this is achieved, investigations can expand to uncover metabolic modulators of other clinically-relevant antimalarials. The ultimate goal will be to compile results from varios experimental systems and identify pathways that are required for parasite survival under stress. Targeting the general stress response would limit the development of resistance and have wide- reaching implications. A promising "resistance blocker" could be administered alongside relevant antimalarial drugs to prolong their effects and decrease worldwide malaria deaths.