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Theory and Modelling of Biological Systems

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Computational and evolutionary cell biology

Though cells are the basic units of all living things, we know remarkably little about their activity and evolution. At the same time, new experiments are generating a torrent of data about the structure and interactions of the bio-molecules from which cells are made up. We seek to bridge the gap: going from molecules to cellular phenotypes. What makes this enterprise exciting is that a complex system can have properties different from  those of its constituent parts. We study the molecular basis of the emergent properties of two cellular systems: the network of factors that turn gene transcription on and off; and the complex trafficking of materials between the multitude of intracellular compartments.

Our work involves a close interplay between simple mathematical models and quantitative experiments: we use techniques borrowed from control theory and electrical engineering to design and experimentally test synthetic transcriptional networks built from well-understood molecular components in bacterial cells; and we use biophysical models to explore how organelles and traffic arise from basic molecular interactions in eukaryotic cells. Ultimately, cells are products of basic evolutionary forces: mutation and recombination which act on molecules; selection and drift which act on phenotypes and populations. Studying the emergence of phenotype from molecular interactions will be essential if we are to understand the deep evolutionary origins of modern cells.

 

  • Rai N, Anand R, Ramkumar K, Sreenivasan V, Dabholkar S, Venkatesh KV, Thattai M (2012) Prediction by promoter logic in bacterial quorum sensing. PLoS Comput. Biol. 8: e1002361.
  • Anand R, Rai N, Thattai M (2011) Promoter reliability in modular transcriptional networks. Methods Enzymol. 497: 31.
  • Ramadas R, Thattai M (2010) Flipping DNA to generate and regulate microbial consortia. Genetics 184: 285.
  • Callahan B, Thattai M, Shraiman BI (2009) Emergent gene order in a model of modular polyketide synthases. Proc. Natl. Acad. Sci. USA 106: 19410.

 

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