Gunawan:Suresh Poovathingal

Chemical and Biological Systems Engineering Laboratory

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Suresh Kumar Poovathingal

Suresh Kumar Poovathingal

Department of Chemical and Biomolecular Engineering
National University of Singapore
4 Engineering Dr. 4 Blk E5 #02-16
Singapore 117576
Tel:+65 6516 7859

I work in the Dynamical BioSystems Lab at National University of Singapore.

Education

• 2006, MS, Technische Universitaet Hamburg-Harburg, Germany
• 1999, BEngg, B.M.S College of Engg, Bangalore University, India

Research interests

Systems Biology of Aging

The mitochondrial free radical theory of aging (mFRTA) implicates reactive oxygen species (ROS) as the causative agent for the degeneration of mitochondrial genome integrity and cellular respiratory function resulting in the tissue dysfunction. Although several premises of mFRTA are still intensely debated, the role of mitochondria and ROS in aging has been supported by the transgenic mice studies. At the moment, there is no definitive explanation about the mechanisms by which somatic mtDNA mutations expand in an organism’s life.

Our motivation to implement a stochastic modeling approach stems from the inadequacies of the current practice in elucidating the dynamics and mechanism of mtDNA instability from data, which were obtained through standard but suboptimal experimental protocols. Further complicating this problem is the fact that the cellular processes are inherently noisy. In order to capture these uncertainties, we have developed a minimal stochastic mutation model based on the Chemical Master Equation (CME). The model was used for simulating point mutation burden in several cell lines of both the wild-type and transgenic mice. All the parameters used for modeling were derived from the literature. The simulation outcomes were validated against published experimental data.

Our preliminary investigation elucidated two sources of uncertainties and the coupling of these uncertainties can introduce large enough noise that prevents a conclusive deduction of mtDNA mutation dynamics, even using the state-of-the-art experimental technique. Further, the developmental stages and cell divisions in an organism were found to have a significant contribution in initiating the mitochondrial genome instability. Such significant effect of noise motivates an integration of in silico, in vivo and in vitro experiments in future aging studies.

Publications/Presentations

1. Poovathingal SK and Gunawan R. Global parameter estimation methods for stochastic biochemical systems. BMC Bioinformatics. 2010 Aug 6;11:414. DOI:10.1186/1471-2105-11-414 |
2. Poovathingal SK, Gruber J, Halliwell B, and Gunawan R. Stochastic drift in mitochondrial DNA point mutations: a novel perspective ex silico. PLoS Comput Biol. 2009 Nov;5(11):e1000572. DOI:10.1371/journal.pcbi.1000572 |

3. Suresh P, Gruber J, Halliwell B, Gunawan R. (2009) Stochasticity in mitochondrial DNA point mutation and its relevance in Caenorhabditis elegans Aging (ICSB), Stanford, California, USA, Aug 30 - Sep 4

4. Suresh P, Gruber J, Halliwell B, Gunawan R. (2009) A global approach for estimating the kinetic parameters of stochastic biological systems, In Proceedings of the Third International Conference on Foundations of Systems Biology in Engineering (FOSBE), Denver, Colorado, USA, August 9 - 12, PP: 56 - 59

5. Suresh P, Gruber J, Halliwell B, Gunawan R. (2008) Aging Studies: A Stochastic Approach in point mutation dynamics in mouse model in AiChe annual general meeting , Philadelphia, USA, Nov 16-21

Useful links

• Our Lab webpage