This application for the Mentored Quantitative Research Career Development Award requests funding to support Dr. Elebeoba E. May, a computational scientist, to receive training in the molecular aspects of infectious diseases and to participate in a mentored research program focused on understanding the genetic basis of Mycobacterium tuberculosis latency and reactivation. This career development proposal consists of an overlapping didactic and research phase. The majority of Dr. May's didactic phase will occur during the first three years. This developmental phase is designed to provide significant training in the biology of infectious diseases with an emphasis on tuberculosis as a model organism. The coursework, seminars, and workshops will provide the biological background that will enable Dr. May to successfully implement the proposed research. Dr. May will gradually move into the research phase, compiling data the first two years and then increasing research activities from year three through year five. The research objective is to quantitatively identify, model and analyze genetic networks, metabolic networks, and immune response pathways that are involved in the Mtb latency and reactivation process.
Specific aims and steps for accomplishing the research objective include: 1) Determine host-Mtb gene expression during a murine model of Mtb infection and subsequent development of latency; 2) Develop a quantitative model of Mtb and host during infection relating gene-level expression to metabolic pathways, and metabolic pathways to cellular immune response; 3) For a given microarray expression profile, simulate and quantify host-pathogen interactions for Mtb-mouse immune response during latency and reactivation. The quantitative models developed will be used to perform virtual Mtb knockout experiments to identify genes that influence latency and reactivation. In vivo anti-sense knockout experiments will be performed to validate whether the genes identified by the quantitative model impact latency and reactivation. Successful completion of this program will provide Dr. May with the training necessary to successfully develop and conduct independent research programs in biomedicine and infectious diseases. This work will also augment current understanding of latency and reactivation in Mtb, a pathogen that causes significant morbidity worldwide.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Mentored Quantitative Research Career Development Award (K25)
Project #
1K25HL075105-01A1
Application #
6851258
Study Section
Special Emphasis Panel (ZHL1-CSR-Q (O1))
Program Officer
Colombini-Hatch, Sandra
Project Start
2005-09-21
Project End
2010-07-31
Budget Start
2005-09-21
Budget End
2006-07-31
Support Year
1
Fiscal Year
2005
Total Cost
$140,567
Indirect Cost
Name
Sandia Corp-Sandia National Laboratories
Department
Type
DUNS #
007113228
City
Albuquerque
State
NM
Country
United States
Zip Code
87123
Sershen, Cheryl L; Plimpton, Steven J; May, Elebeoba E (2016) Oxygen Modulates the Effectiveness of Granuloma Mediated Host Response to Mycobacterium tuberculosis: A Multiscale Computational Biology Approach. Front Cell Infect Microbiol 6:6
May, Elebeoba E; Sershen, Cheryl L (2016) Oxygen Availability and Metabolic Dynamics During Mycobacterium tuberculosis Latency. IEEE Trans Biomed Eng 63:2036-46
Sershen, Cheryl L; Plimpton, Steven J; May, Elebeoba E (2014) A method for modeling oxygen diffusion in an agent-based model with application to host-pathogen infection. Conf Proc IEEE Eng Med Biol Soc 2014:306-9
May, Elebeoba E; Leitão, Andrei; Tropsha, Alexander et al. (2013) A systems chemical biology study of malate synthase and isocitrate lyase inhibition in Mycobacterium tuberculosis during active and NRP growth. Comput Biol Chem 47:167-80
May, E E; Schiek, R L (2009) BioXyce: an engineering platform for the study of cellular systems. IET Syst Biol 3:77-89
May, Elebeoba; Leitao, Andrei; Faulon, Jean-Loup et al. (2008) Understanding virulence mechanisms in M. tuberculosis infection via a circuit-based simulation framework. Conf Proc IEEE Eng Med Biol Soc 2008:4953-5