A kinetic platform for in silico modeling of the metabolic dynamics in Escherichia coli

Abstract

Background

A prerequisite for a successful design and discovery of an antibacterial drug is the identification of essential targets as well as potent inhibitors that adversely affect the survival of bacteria. In order to understand how intracellular perturbations occur due to inhibition of essential metabolic pathways, we have built, through the use of ordinary differential equations, a mathematical model of 8 major Escherichia coli pathways.

Results

Individual in vitro enzyme kinetic parameters published in the literature were used to build the network of pathways in such a way that the flux distribution matched that reported from whole cells. Gene regulation at the transcription level as well as feedback regulation of enzyme activity was incorporated as reported in the literature. The unknown kinetic parameters were estimated by trial and error through simulations by observing network stability. Metabolites, whose biosynthetic pathways were not represented in this platform, were provided at a fixed concentration. Unutilized products were maintained at a fixed concentration by removing excess quantities from the platform. This approach enabled us to achieve steady state levels of all the metabolites in the cell. The output of various simulations correlated well with those previously published.

Conclusion

Such a virtual platform can be exploited for target identification through assessment of their vulnerability, desirable mode of target enzyme inhibition, and metabolite profiling to ascribe mechanism of action following a specific target inhibition. Vulnerability of targets in the biosynthetic pathway of coenzyme A was evaluated using this platform. In addition, we also report the utility of this platform in understanding the impact of a physiologically relevant carbon source, glucose versus acetate, on metabolite profiles of bacterial pathogens.

Keywords:

• antibacterial drug
• mathematical model
• kinetic platform
• metabolic dynamics
• Escherichia coli

Acknowledgment

We are indebted to Anand Kumar and Umender Sharma for critically reviewing the manuscript. The authors would like to thank Asha Balakrishnan for carrying out the amino acid analysis and Tanmay Banerjee for the microarray data input into the platform.

Authors’ contribution

Aditya Barve, Ansu Kumar and Shireen Vali designed, constructed and validated the E. coli computational platform at the Cellworks site. Various simulations carried out by Aditya Barve and Ansu Kumar at Cellworks were reconfirmed by Anvita Gupta and Suresh Solapure at AstraZeneca India. The design and formulation for simulation were carried out by Suresh Solapure, Vasanthi Ramachandran, Kothandaraman Seshadri and Santanu Datta. The experimental validations were carried out by Suresh Solapure and Vasanthi Ramachandran. After contributions from all the contributors, the manuscript was written by Aditya Barve, Suresh Solapure, Vasanthi Ramachandran, Kothandaraman Seshadri and Santanu Datta. All the authors read and approved the final manuscript.

Disclosure

The authors disclose no conflicts of interest for this work.