Krishnan

The unifying theme of the research in my group is the understanding and manipulation of information processing in cells and tissues/cell populations. This is approached through a combination of (i) mathematical modelling (ii) theoretical work (iii) systems approaches, including tool development (iv) collaboration with a range of experimentalists. Characteristic of this research area is a  broad diversity of problems at different levels and scales, substantial possibilities for application, and the confluence of the natural sciences, mathematics and engineering, including systems engineering. Some of the approaches developed and employed can be used in related non-biological contexts. This is discussed in greater detail below.

The regulation of most aspects of cellular life and functioning is accomplished by complex and sophisticated biochemical and gene regulatory networks (the intracellular level) along with cellular communication and interaction (the tissue or cell population level). The functioning of such networks both at intracellular and the intercellular level  is being probed in a broad diversity of settings and with a range of tools. Understanding information processing through  these  networks is of central importance both from basic and applied perspectives. This is because it allows us to understand how cells regulate different processes and respond to the environment and affords ways of controlling or manipulating them through synthetic and other means.

        There are a broad range of challenges involved in this endeavour. The complexity of information processing in cells and tissues/cell populations stems from multiple sources. In addition to the large number of molecular components, abundant nonlinearity in different forms, widespread feedback, the effects of stochasticity and spatial aspects and the different forms of cellular interaction all play important roles.Furthermore,the organization of networks, shaped by evolution, is often challenging to uncover.

A parallel motivation arises from the burgeoning area of synthetic biology, including the design and creation of molecular circuits and systems in a range of settings spanning cell-free systems, artificial cells, natural cells and cell collectives. Here again, given the nature of interaction of the molecular components, the design imperative, and  different kinds of potential circuit designs, the roles of different ingredients (nonlinearity, feedback, spatial organization, stochasticity) needs to be assessed and exploited in a system design setting.

      Elucidating and engineering information processing in these systems therefore presents substantial challenges and interesting opportunities for systems science and engineering. This involves the confluence of biology, physics, chemistry, mathematics and engineering. Engineering approaches are used in both elucidating system behaviour and functioning, as well as in manipulating it.

    The research in my group employs an interdisciplinary engineering approach in this context, with two broad strands. The first strand involves mathematical and computational modelling in a selection of concrete problems of basic and applied interest. We collaborate with cell biologists, biomedical scientists and engineers as well as synthetic biologists in this regard. Mathematical modelling involves temporal, spatial and stochastic descriptions as appropriate and some of the modelling is explicitly multi-level. We develop both simplified and detailed mechanistic models which are analyzed through computational and analytical means.

A complementary strand of research involves developing theoretical and systems frameworks and tools to elucidate different aspects of signal transduction, gene regulation and information processing. The  goals here include the elucidation of different aspects of signal transduction, gene regulation and information processing and the creation of platforms and tools which may be relevant in multiple contexts/systems. These approaches are relevant to both systems and synthetic biology, as they help build a bridge to tackle the complexity of natural systems on one hand, and serve as a foundational platform for engineering them on the other. Tools from dynamical systems, control engineering, systems engineering and networks are employed here.

 The research of each strand informs the other, and employing both approaches allows for a synergistic interplay between the two.

Recent and ongoing research focusses on a range of problems across different levels and scales ranging from the molecular level to the population level. In each case, we develop and employ dedicated systems approaches to reveal different key facets of system behaviour (i) Modelling and analysis of information processing in substrate modification systems, in particular multisite modification systems (ii) mRNA translation: feedback regulation, the effects of premature stop codons, and the interplay between recycle and mRNA stability, tools for modelling and analysis of mRNA translation. (iii) Information processing in signalling networks. combining on one hand the analysis of key building blocks of networks, their behaviour and interaction, and on the other hand, the modelling and analysis of signalling in specific basic cellular, physiological and biomedical contexts (eg. cancer signalling, cell cycle, immune system function) (iv) Spatial organization and regulation of biomolecular systems and networks, involving a multipronged approach ranging from analysis of basic biochemical building blocks, analysis of basic networks and network building blocks, modelling and analysis in different cellular contexts, and frameworks for design of synthetic circuits (v) Multi-level modelling and analysis of cells and cell populations

Finally, we are also interested in non-biological analouges and extensions of different aspects of the above research, as well as dynamics, self-organization, information processing and systems analysis   in engineered and related physicochemical systems.

Funding: BBSRC,EPSRC, Leverhulme Trust

Former Group members:

Postdocs

Aiman Alam-Nazki: currently Research Associate, Quantitative Systems Pharmacology,  Certara

Yun-Bo Zhao : (selected  in the 1000 talents programme, Govt. of China) currently Professor, Department of Automation, University of Science and Technology of China (USTC)

Eric de Silva : currently at University College London

PhD

Cong Liu: currently Senior Research Scientist, Certara.

Daniel Seaton: currently Scientific Director, Computational Biology, Glaxo Smith Kline.

Aiman-Alam Nazki: (Dudley-Newitt best thesis prize, Dept. of Chemical Engg., Imperial College London): EPSRC Prize Fellowship (Currently at Certara)

Oleg Lenive: currently Machine Learning Engineer, Manifold Explorations Limited

Thapanar Suwanmajo: Assistant Professor, Chiang Mai University, Thailand (deceased)

Govind Menon: (Weinberg thesis prize, Dept. of Chemical Engg, Imperial College London): currently postdoctoral scientist, John Innes Centre, Norwich

Junjun Cai: Senior Investment Associate, Neumann Advisors