Our goal is to try to understand the roles of functionally-uncharacterized genes in M. tuberculosis. We will focus on genes that are important for the growth and survival of the bacterium under conditions likely to be relevant to infection, and use multiple approaches to define phenotypes and key interactions to reveal function. We will select targets using existing genome wide screening information. Each target will be investigated using parallel independent approaches to increase the chances of success. Our overall goal is to define function using the GO (gene ontology) definitions of molecular function, cellular process and/or biological process. We will attempt to determine as many of these as possible for each target. This will be accomplished through the following objectives: Objective 1. Identify phenotypes for underexpressing strains (with Core E) Objective 2. Identify interacting genes and proteins (with Cores, C, D and E) Objective 3. Identify substrates/products of potential enzymes (with Cores B and E) Objective 4. Confirm putative interacting genes and pathways (with Cores B-E).

Public Health Relevance

Tuberculosis is an important global health problem, killing millions each year. Our rudimentary under-standing of the basic physiology underlying M. tuberculosis infection hampers our efforts to develop new drugs and vaccines. By functionally-characterizing the genes used by M. tuberculosis to cause disease, we will develop a deeper understanding of the pathogenic process and define more effective therapies.

Agency
National Institute of Health (NIH)
Type
Research Program--Cooperative Agreements (U19)
Project #
5U19AI107774-02
Application #
8738886
Study Section
Special Emphasis Panel (ZAI1)
Project Start
Project End
Budget Start
Budget End
Support Year
2
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Harvard University
Department
Type
DUNS #
City
Boston
State
MA
Country
United States
Zip Code
02115
Kery, Mary Beth; Feldman, Monica; Livny, Jonathan et al. (2014) TargetRNA2: identifying targets of small regulatory RNAs in bacteria. Nucleic Acids Res 42:W124-9
DeJesus, Michael A; Ioerger, Thomas R (2013) A Hidden Markov Model for identifying essential and growth-defect regions in bacterial genomes from transposon insertion sequencing data. BMC Bioinformatics 14:303