Metabolic Reconstruction of the Genome of Bacillus Anthracis

Period of Performance: 07/23/1999 - 09/22/2000

$99K

Phase 1 STTR

Recipient Firm

Integrated Genomics, Inc.
2201 West Campbell Drive,
Chicago, IL 60612
Principal Investigator
Firm POC

Research Institution

University of Chicago
6030 S. Ellis Avenue Room ED-114
Chicago, IL 60637
Institution POC

Abstract

The goal of the proposed research is to provide a biologically rational approach to detection of Bacillus anthracis and protection from its toxicity. The basis of the approach is extensive sequencing of the genomic DNA, including plasmids, of B. anthracis (two strains of 78 known) as well as the genome of B. cereus, the closest known relative. For sequencing, each strain will be grown under suitable safety conditions and total DNA extracted using a protocol established successfully at IG for a wide range of bacterial. Three highly random, sized DNA libraries will be constructed: 2-kb plasmid inserts, 4-kb plasmid inserts, and 35-kb cosmid inserts. Some hybridization reactions with arrays of plasmids will probably be required to cover the same regions of all three strains. This much can be accomplished under Phase I. Preliminary sequencing (20,000-20,000 runs, equal to 3x coverage of a 3-Mb genome) of plasmid and cosmid insert ends will verify the degree of relatedness among the three strains. This should be sufficient to hit about 95% of all ORFs, and match 50-70% of them. These ORFs will be integrated in a Web shell with a set of analytical tools as has been done for Rhodobacter capsulatus. We will also collect biochemical references related to B. anthracis and transfer them into the EMP format to add specific metabolic pathways for subsequent metabolic reconstruction. The remaining sequencing, editing, alignment, annotation and metabolic reconstruction will require Phase II funding. In Phase II, we will generate polished, unambiguous genome sequence. We will also integrate it into our WIT-pro/EMP analytical environment and subject it to the various clustering algorithms to verify functional predictions. At the end of the day, we expect to provide targets, based on the sequence, for detection and prevention of anthrax.