We will use state-of-the-art, quantitative mass spectrometry-based proteomics to define membership of protein complexes in wild-type and mutant Mtb strains under a variety of growth and perturbational conditions. Systematic and unbiased definifion of the membership of key protein complexes, and the changes in that membership under a variety of growth and perturbaional condtions, will provide critical insights into the biological function of genes important for growth and survival of Mtb. By integrating results of proteomics, metablomics and transcriptomic analyses, a comprehensive picture of the interactions and expression programs critical for growth and survival of the organism should emerge. We will also use state-of-the-art, quantitative global proteomics to profile auxotrophic strains of Mtb to understand the roles of genes encoding proteins and non-coding RNAs of unknown function in M. tuberculosis. We will choose condtions/time points just before changes in growth occur to minimize the possibility that changes in protein abundance are a consequence of changes in growth and survival but, instead, are directly attributable to the mutation. Both wild type and mutant bacteria strains will be analyzed by comparative quantitative proteomic analysis. We anticipate that we will find several different types of changes. We will correlate changes with observations from other experiments across the consortium.

Public Health Relevance

Protein complexes, rather than individual proteins or binary interacfing proteins, are the funcfional units in cells. The function of any protein is context dependent, deciphering the macromolecular context in which proteins are found is key to understanding cellular funcfion and dynamics. The systematic unbiased ID of peptide/proteins under a range of condifions will provide critical insight into the pathways and survival of Mtb

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
1U19AI107774-01
Application #
8597709
Study Section
Special Emphasis Panel (ZAI1-FDS-M (M1))
Project Start
2013-07-02
Project End
2018-06-30
Budget Start
2013-07-02
Budget End
2014-06-30
Support Year
1
Fiscal Year
2013
Total Cost
$256,103
Indirect Cost
$35,363
Name
Harvard University
Department
Type
DUNS #
149617367
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