Probabilistic Reconstruction and Comparative Systems Biology of Microbial Metabolism

German Plata
Vitkup Lab

Irving Cancer Research Center
1130 St. Nicholas Avenue
Room 816
New York, NY 10032

With the number of sequenced microbial species soon to be in the tens of thousands, we are in a unique position to investigate microbial function, ecology, and evolution on a large scale. The path from genotype to phenotypic predictions can be understood as a three step process: 1) genome annotation, 2) molecular network reconstruction, and 3) simulation of network behavior. Here I explore these three aspects of systems biology focusing on microbial metabolic networks. I start by describing GLOBUS, a novel probabilistic method for the genome-wide annotation of metabolic genes. GLOBUS annotations integrate multiple types of heterogeneous data including network context correlations and species phenotypic properties. Second, I describe the curation of the genome-scale metabolic network for the malaria parasite, Plasmodium falciparum. The reconstruction allowed the identification of many potential essential genes and the validation of one of them as a possible drug target for malaria treatment; the model is also a platform to contextualize multiple types of molecular data. Finally, I present a comparative analysis of phenotypic properties across hundreds of bacterial species that spans 4 billion years of evolution. The implications of the analysis for understanding microbial biodiversity and evolution are discussed.  

Event Series Name
Thesis Defense