Changes in lipid composition of phosphonate treated Plasmodium falciparum

Malaria, caused by Plasmodium falciparum, remains a significant health burden. The barrier to developing anti-malarial drugs is the ability of the parasite to rapidly generate resistance. We previously demonstrated that Salinipostin A (SalA), a natural product, potently kills parasites by inhibiting multiple lipid-metabolizing serine hydrolases, a mechanism with a low propensity for resistance. Given the difficulty of employing natural products as therapeutic agents, we synthesized a small library of lipidic mixed alkyl/aryl phosphonates as bioisosteres of SalA. Two constitutional isomers exhibited divergent anti-parasitic potencies which enabled the identification of therapeutically relevant targets. We also confirm that this compound kills parasites through a mechanism that is distinct from both SalA and the pan-lipase inhibitor, Orlistat. In addition, like SalA, our compound induces only weak resistance, attributable to mutations in a single protein involved in multidrug resistance. These data suggest that mixed alkyl/aryl phosphonates are promising, synthetically tractable antimalarials with a low propensity to induce resistance.

Methods
Preparation of Lipidomic Samples

For lipid analysis, synchronized W2 ring stage of 50 mL cultures of 10% parasitemia in 4 % hematocrit were treated with 920nM (5x IC50) of compound 22 or DMSO vehicle for 16 h. Red blood cells were saponin lysed and the parasite pellet was collected. Parasite pellets were subsequently collected and resuspended in 1 ml of 1xPBS buffer and transferred into glass vials pre-loaded with 2:1 chloroform/methanol to a final ratio of 2:1:1 chloroform/methanol/1xPBS. Samples were vigorously shaken and spun down at 1000g and the organic layer was collected. Three vials of lipids extracted from each treatment were dried down under a stream of argon.

Lipid analysis using high-performance liquid chromatography-mass spectroscopy

Lipidomics was performed on an Agilent 6545 Q-TOF LC/MS as previously described and data was analyzed using the online XCMS platform (Onguka et al., 2021). Metabolites shown to be significantly changed between the two treatment groups were then searched by their mass and classified using the online LipidMaps tool (Conroy et al., 2023).