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

Abstract

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.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2011
Accession Number
ADA552311

Entities

People

  • Simon Daefler

Organizations

  • Icahn School of Medicine at Mount Sinai

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Amino Acids
  • Anabolism
  • Anti-Bacterial Agents
  • Bacteria
  • Carbohydrates
  • Carrier Proteins
  • Computational Biology
  • Computers
  • Gammaproteobacteria
  • Lethality
  • Metabolic Pathways
  • Metabolism
  • Neutral Amino Acids
  • Pathogenic Bacteria
  • Simulations
  • Systems Biology

Fields of Study

  • Biology

Readers

  • Computational Modeling and Simulation
  • Microbial Pathology
  • Molecular Genetics