Tuberculosis is a global health emergency. The continued emergence and transmission of multidrug resistance strains of M. tuberculosis threatens to return mortality rates to those of the preantibiotic era, and thereby necessitates rapid, thorough national and international surveillance of strain distribution dynamics in the population. Current strain surveillance is severely hampered by genotyping techniques that do not attain the level of strain discrimination' required, or do not lend themselves to reliable, rapid assays to detect TB transmission and disease development. A single genotyping method will be created using automated detection and sizing of fluorescent dye-labeled amplicons via capillary electrophoresis analysis of newly identified variable SSRs in combination with long sequence tandem repeats. The diversity of allelic variation for each repetitive element will be determined by screening across an extensive set of strains collected from around the world and previously analyzed by contemporary genotyping methods. The diversity of the repetitive elements will be compared with that of previous IS6110 RFLP, spoligotype, and single nucleotide polymorphism genotypic analyses as well as epidemioiogic data to define genotyping algorithms consistent with the natural history of tuberculosis disease and transmission within local, continental, and global human populations. Novel, diverse repetitive elements will be incorporated in nascent international web-based M. tuberculosis genotyping systems.
The specific aims addressed by our proposal are to: 1) identify SSRs in mycobacterial genome sequences, 2) use a diversity sample set to determine which SSRs are variable, while comparing the discriminatory power of SSR genotyping to current Mycobacterium tuberculosis genotyping methods and, 3) identify variable SSRs temporally compatible with TB transmission and observe their natural variation in vivo.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
1R01AI058053-01A2
Application #
6919529
Study Section
Genomics, Computational Biology and Technology Study Section (GCAT)
Program Officer
Mason, Robin M
Project Start
2005-04-01
Project End
2008-03-31
Budget Start
2005-04-01
Budget End
2006-03-31
Support Year
1
Fiscal Year
2005
Total Cost
$321,180
Indirect Cost
Name
University of Texas Health Science Center San Antonio
Department
Microbiology/Immun/Virology
Type
Other Domestic Higher Education
DUNS #
800772162
City
San Antonio
State
TX
Country
United States
Zip Code
78229