Using Computer Models to Identify Common Therapeutic Targets in Host Adapted Bacterial Threat Agents

摘要

This proposal seeks to develop computer algorithms for the evaluation of metabolic pathways in bacterial biothreat agents that can be exploited as therapeutic targets. We have completed genome-scale metabolic models for Francisella Schu4 (type A strain, Francisella LVS) (type B), Burkholderia mallei, and Burkholderia pseudomallei. Some models were validated by metabolic assays, growth experiments in defined media, and transcriptomic data. Algorithms were developed and implemented for genome scale in silico simulation to identify single and synthetic lethals (double, triple, and quadruple). Identification of geneproducts that cause lethality leads to potential suitable therapeutic targets. The suitability of this approach starting from genomic data of an unknown Francisella strain was successfully tested. with a 24h turn-around time for each strain. This demonstrates the feasibility of this methodology and underlines its importance for evaluation of potentially modified or emerging bacterial pathogens.