Novel Plasmodium falciparum metabolic network reconstruction identifies shifts associated with clinical antimalarial resistance

Abstract

Background: Malaria remains a major public health burden and resistance has emerged to every antimalarial on the market, including the frontline drug, artemisinin. Our limited understanding of Plasmodium biology hinders the elucidation of resistance mechanisms. In this regard, systems biology approaches can facilitate the integration of existing experimental knowledge and further understanding of these mechanisms.

Results: Here, we developed a novel genome-scale metabolic network reconstruction, iPfal17, of the asexual blood-stage P. falciparum parasite to expand our understanding of metabolic changes that support resistance. We identified 11 metabolic tasks to evaluate iPfal17 performance. Flux balance analysis and simulation of gene knockouts and enzyme inhibition predict candidate drug targets unique to resistant parasites. Moreover, integration of clinical parasite transcriptomes into the iPfal17 reconstruction reveals patterns associated with antimalarial resistance. These results predict that artemisinin sensitive and resistant parasites differentially utilize scavenging and biosynthetic pathways for multiple essential metabolites, including folate and polyamines. Our findings are consistent with experimental literature, while generating novel hypotheses about artemisinin resistance and parasite biology. We detect evidence that resistant parasites maintain greater metabolic flexibility, perhaps representing an incomplete transition to the metabolic state most appropriate for nutrient-rich blood.

Conclusion: Using this systems biology approach, we identify metabolic shifts that arise with or in support of the resistant phenotype. This perspective allows us to more productively analyze and interpret clinical expression data for the identification of candidate drug targets for the treatment of resistant parasites.

Keywords: Artemisinin resistance; Flux balance analysis; Malaria; Metabolism; Network reconstruction; Plasmodium falciparum.

Fig. 1

Ring-stage parasites are genotypically and phenotypically distinct, yet expression profiles fail to separate resistance phenotypes. a & b Genotypic clustering: Genotypic (any mutation in PfKelch13) and phenotypic markers (parasite clearance half-life) were used to define artemisinin resistance in ring-stage parasites from GSE59097; using both markers, resistant and sensitive parasites from Cambodia (a) and Vietnam (b) separated into distinct populations. Genotype was identified in [49] with samples classified as containing the reference allele (blue), a mutant allele (red, any in the PfKelch13 propeller domain), a mixed population (black, at least two reads from each the reference and mutant alleles), or missing (grey, no sequencing data or fewer than 5 reads). c Phenotypic clustering: Resistant (red) and sensitive (blue) parasites from the two countries fail to cluster with consideration of genome-wide gene expression data (data not shown) or expression of metabolic genes alone

Fig. 2

iPfal17 model curation is broad and comprehensive. Number of reactions in the P. falciparum reconstruction grouped by metabolic subsystems. Subsets of those reactions with gene annotations, literature citations, and modifications in the curation effort for this reconstruction are noted

Fig. 3

Computational pipeline. We curated an existing blood-stage P. falciparum reconstruction to generate our iPfal17 network reconstruction. We integrated transcriptomics data into this model using the MADE algorithm to generate four condition-specific models. We used these models to predict reaction essentiality; we highlight consensus results across resistant or sensitive models. MADE, Metabolic Adjustment for Differential Expression

Fig. 4

Artemisinin resistant and sensitive parasites have unique metabolite transport capabilities. a Transport differences: Resistant parasites exhibit greater metabolic flexibility, allowing either import or biosynthesis of putrescine, p-aminobenzoate, adenosyl-methionine into the parasite’s cytoplasm (grey). Sensitive parasites rely on import only Import or synthesis of ATP, ADP, and phosphate into the apicoplast (green organelle) is essential for sensitive parasites. Resistant parasites require transport of oxygen, fumarate, oxaloacetate, NADP, NADPH, tetrahydrofolate (thf), NH₄, and glycine into the mitochondria, in yellow. b p-aminobenzoate in glycolysis: Resistant parasites generate p-aminobenzoate via alternative components of the glycolysis pathway. Arrows colored for flux via FVA and stars for essentiality. FVA, flux variability analysis

Fig. 5

Artemisinin resistance displays unique metabolic weaknesses. a Trycarboxylic acid cycle: Resistant parasites rely on generation of oxaloacetate from the conversion of fumarate to malate, using fumarate hydratase and malate dehydrogenase, in the mitochondria. Sensitive parasites can also import malate into the mitochondria and use an alternative enzyme (malate:quinone oxidoreductase) to convert malate to oxaloacetate. b Folate metabolism: Inhibition of the SHMT enzyme (left) and the glycine cleavage system (right) is lethal in resistant parasites. Sensitive parasites can use either of these enzyme complexes interchangeably to produce mthf and thf. c Cofactor synthesis: The import of thiamine and the conversion of thiamine to thiamine diphosphate via thiamine thiphosphokinase is essential in resistant parasites. Sensitive parasites can also synthesize thiamine diphosphate de novo. Arrows colored for flux via FVA and stars for essentiality. Gray background indicates cytosolic localization, yellow indicates mitochondrial localization. FVA, flux variability analysis. SHMT, serine hydroxylmethltransferase, mthf, methyltetrahydrofolate, thf, tetrahydrofolate