Our lab seeks to understand how variability in the host environment affects the pathogenesis of disease for the pathogen Plasmodium falciparum, the etiological agent of malaria.

We are studying how variation in the metabolic microenvironment impacts the viability, morphology and function of red blood cells (RBC).

We are studying the “bystander effect”, that is, the phenomenon by which uninfected RBCs are lost during a malaria infection at a high rate, despite not being infected by a parasite. The exact cause(s) of the bystander effect are not well understood, but we hypothesize that changes in the metabolic environment of the blood plasma may play a role. We are using ex vivo cell culture systems to study how RBCs are differentially impacted by oxidative stress when variations in the microenvironment are introduced.

We are investigating the role of oxygen on Plasmodium falciparum multiplication rate.

Our work seeks to understand how fluctuations in the levels of oxygen concentration in the microenvironment, which varies across tissue sites in the body, affect the multiplication rate of Plasmodium. While it is well-known that Plasmodium grows best in the laboratory under low oxygen conditions, little is known about the biology of the parasite under higher oxygen conditions. We are characterizing the cellular and molecular mechanism(s) underlying the variability in multiplication rate under different oxygen conditions and using mathematical modeling to predict how this physiological variation may impact a host in vivo.

We are characterizing gut pathogenesis and the gut microbiome during malaria infection.

Systems biology offers the opportunity to decipher complex processes and computationally identify biological factors that are associated with malaria pathogenesis. The goal of this research is to determine how blood metabolites and gut microbes are linked to malaria disease severity. We are performing analyses on samples from longitudinal infection studies of nonhuman primates infected with the malaria parasite Plasmodium. High-throughput `omic technologies such as metabolomics and metagenomics, computational approaches such as data integration and network analyses, and detailed immunofluorescence studies on tissue are being used for the multi-omic profiling of host and commensal microbial factors in the context of malaria pathogenesis.