Metabolic Model Reconstruction and Evaluation of Plasmodium Falciparum

Background Malaria is an infectious disease caused by protozoan of the genus Plasmodium and it is transmitted through the bite of an infected female Anopheles mosquito. A detailed understanding of the parasite's metabolism is necessary to gain in-depth insight into the complex interaction between the parasite, vector, and humans. To achieve this, we combine and iteratively refine different existing genome-scale metabolic models (GSMs).

Results Two GSMs for P. falciparum have been published based on its genome information, literature, and experimental data. The two models differ in terms of number of metabolites, reactions, genes, and compartments. For instance one model has four compartments while the other has nine compartments. Here, we present a refined consensus model (RCM) generated by using a new semi-automatic tool for consensus model generation, with 2121 reactions, 1250 metabolites, 479 gene associations and nine compartments. Using in-silico single gene knockouts we identified seven genes – aminolevulinate synthase, aminolevilinate dehydratase,  porphobilinogen deaminase, uroporphyrinogen decarboxylase, coproporphyrinogen III oxidase, protoporphyrinogen oxidase, and ferrochelatase. These genes are involved in Porphyrin metabolism pathway, which is an important pathway for the parasite.

Conclusions Results of knockout analysis corroborate that the RCM generated by combining the two input models in a semi-automatic manner was predictive.