A systems biology framework for modeling metabolic enzyme inhibition of Mycobacterium tuberculosis.
BACKGROUND
Because metabolism is fundamental in sustaining microbial life, drugs that target pathogen-specific metabolic enzymes and pathways can be very effective. In particular, the metabolic challenges faced by intracellular pathogens, such as Mycobacterium tuberculosis, residing in the infected host provide novel opportunities for therapeutic intervention.


RESULTS
We developed a mathematical framework to simulate the effects on the growth of a pathogen when enzymes in its metabolic pathways are inhibited. Combining detailed models of enzyme kinetics, a complete metabolic network description as modeled by flux balance analysis, and a dynamic cell population growth model, we quantitatively modeled and predicted the dose-response of the 3-nitropropionate inhibitor on the growth of M. tuberculosis in a medium whose carbon source was restricted to fatty acids, and that of the 5'-O-(N-salicylsulfamoyl) adenosine inhibitor in a medium with low-iron concentration.


CONCLUSIONS
The predicted results quantitatively reproduced the experimentally measured dose-response curves, ranging over three orders of magnitude in inhibitor concentration. Thus, by allowing for detailed specifications of the underlying enzymatic kinetics, metabolic reactions/constraints, and growth media, our model captured the essential chemical and biological factors that determine the effects of drug inhibition on in vitro growth of M. tuberculosis cells.
Fang
Xin
X
Biotechnology HPC Software Applications Institute, Telemedicine and Advanced Technology Research Center, U,S, Army Medical Research and Materiel Command, Ft, Detrick, MD 21702, USA. xfang@bioanalysis.org
Wallqvist
Anders
A
Reifman
Jaques
J
D001426:Bacterial Proteins / Q000378:metabolism*; D049109:Cell Proliferation / Q000187:drug effects; D002470:Cell Survival / Q000187:drug effects; D003198:Computer Simulation; D008954:Models, Biological; D009169:Mycobacterium tuberculosis / Q000187:drug effects / Q000378:metabolism*; D009574:Nitro Compounds / Q000008:administration & dosage*; D011422:Propionates / Q000008:administration & dosage*; D015398:Signal Transduction / Q000187:drug effects / Q000502:physiology*; D013385:Succinate Dehydrogenase / Q000037:antagonists & inhibitors*; D049490:Systems Biology / Q000379:methods*
D001426:Bacterial Proteins; D009574:Nitro Compounds; D011422:Propionates; D013385:Succinate Dehydrogenase; C015392:3-nitropropionic acid