Imperial College London

Krishnan

Faculty of EngineeringDepartment of Chemical Engineering

Senior Lecturer
 
 
 
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Contact

 

+44 (0)20 7594 6633j.krishnan

 
 
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Location

 

C503Roderic Hill BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

55 results found

Gorgoni B, Zhao Y-B, Krishnan J, Stansfield Iet al., 2019, Destabilisation of eukaryote mRNAs by 5’ proximal stop codons can occur independently of the nonsense-mediated mRNA decay pathway, Cells, Vol: 8, ISSN: 2073-4409

In eukaryotes, the binding of poly(A) binding protein (PAB) to the poly(A) tail is central to maintaining mRNA stability. PABP interacts with the translation termination apparatus, and with eIF4G to maintain 3′–5′ mRNA interactions as part of an mRNA closed loop. It is however unclear how ribosome recycling on a closed loop mRNA is influenced by the proximity of the stop codon to the poly(A) tail, and how post-termination ribosome recycling affects mRNA stability. We show that in a yeast disabled for nonsense mediated mRNA decay (NMD), a PGK1 mRNA with an early stop codon at codon 22 of the reading frame is still highly unstable, and that this instability cannot be significantly countered even when 50% stop codon readthrough is triggered. In an NMD-deficient mutant yeast, stable reporter alleles with more 3′ proximal stop codons could not be rendered unstable through Rli1-depletion, inferring defective Rli1 ribosome recycling is insufficient in itself to trigger mRNA instability. Mathematical modelling of a translation system including the effect of ribosome recycling and poly(A) tail shortening supports the hypothesis that impaired ribosome recycling from 5′ proximal stop codons may compromise initiation processes and thus destabilize the mRNA. A model is proposed wherein ribosomes undergo a maturation process during early elongation steps, and acquire competency to re-initiate on the same mRNA as translation elongation progresses beyond the very 5′ proximal regions of the mRNA.

Journal article

Menon G, Krishnan J, 2019, Design Principles for Compartmentalization and Spatial Organization of Synthetic Genetic Circuits, ACS SYNTHETIC BIOLOGY, Vol: 8, Pages: 1601-1619, ISSN: 2161-5063

Journal article

Krishnan J, Floros I, 2019, Adaptive information processing of network modules to dynamic and spatial stimuli, BMC Systems Biology, Vol: 13, ISSN: 1752-0509

BackgroundAdaptation and homeostasis are basic features of information processing in cells and seen in a broad range of contexts. Much of the current understanding of adaptation in network modules/motifs is based on their response to simple stimuli. Recently, there have also been studies of adaptation in dynamic stimuli. However a broader synthesis of how different circuits of adaptation function, and which circuits enable a broader adaptive behaviour in classes of more complex and spatial stimuli is largely missing.ResultsWe study the response of a variety of adaptive circuits to time-varying stimuli such as ramps, periodic stimuli and static and dynamic spatial stimuli. We find that a variety of responses can be seen in ramp stimuli, making this a basis for discriminating between even similar circuits. We also find that a number of circuits adapt exactly to ramp stimuli, and dissect these circuits to pinpoint what characteristics (architecture, feedback, biochemical aspects, information processing ingredients) allow for this. These circuits include incoherent feedforward motifs, inflow-outflow motifs and transcritical circuits. We find that changes in location in such circuits where a signal acts can result in non-adaptive behaviour in ramps, even though the location was associated with exact adaptation in step stimuli. We also demonstrate that certain augmentations of basic inflow-outflow motifs can alter the behaviour of the circuit from exact adaptation to non-adaptive behaviour. When subject to periodic stimuli, some circuits (inflow-outflow motifs and transcritical circuits) are able to maintain an average output independent of the characteristics of the input. We build on this to examine the response of adaptive circuits to static and dynamic spatial stimuli. We demonstrate how certain circuits can exhibit a graded response in spatial static stimuli with an exact maintenance of the spatial mean-value. Distinct features which emerge from the consideration of

Journal article

Krishnan J, Suwanmajo T, 2018, Exploring the intrinsic kinetics of multisite phosphorylation as part of signalling pathways, Journal of the Royal Society Interface, ISSN: 1742-5662

Journal article

Suwanmajo T, Krishnan J, 2018, Exploring the intrinsic kinetics of multisite phosphorylation as part of signalling pathways, Interface, ISSN: 1742-5662

Multisite phosphorylation is a basic way of chemically encoding substrate function and a recurringfeature of cell signalling pathways. A number of studies have explored information processingcharacteristics of multisite phosphorylation, through studies of the intrinsic kinetics. Many of thesestudies focus on the module in isolation. In this paper we build a bridge to connect the behaviour ofmultisite modification in isolation to that as part of pathways. We study the effect of activation of theenzymes (which are basic ways in which the module may be regulated), as well the effects of themodified substrates being involved in further modifications or exiting reaction compartments. Wefind that these effects can induce multiple kinds of transitions, including to behaviour not seenintrinsically in the multisite modification module. We then build on these insights to investigate howthese multisite modification systems can be tuned by enzyme activation to realize a range ofinformation processing outcomes for the design of synthetic phosphorylation circuits. Connecting thecomplexity of multisite modification kinetics, with the pathways in which they are embedded, servesas a basis for teasing out many aspects of their interaction, providing insights of relevance in systemsbiology, synthetic biology/chemistry and chemical information processing.

Journal article

Menon G, Okeke C, Krishnan J, 2017, Modelling compartmentalization towards elucidation and engineering of spatial organization in biochemical pathways, Scientific Reports, Vol: 7, ISSN: 2045-2322

Compartmentalization is a fundamental ingredient, central to the functioning of biological systems at multiple levels. At the cellular level, compartmentalization is a key aspect of the functioning of biochemical pathways and an important element used in evolution. It is also being exploited in multiple contexts in synthetic biology. Accurate understanding of the role of compartments and designing compartmentalized systems needs reliable modelling/systems frameworks. We examine a series of building blocks of signalling and metabolic pathways with compartmental organization. We systematically analyze when compartmental ODE models can be used in these contexts, by comparing these models with detailed reaction-transport models, and establishing a correspondence between the two. We build on this to examine additional complexities associated with these pathways, and also examine sample problems in the engineering of these pathways. Our results indicate under which conditions compartmental models can and cannot be used, why this is the case, and what augmentations are needed to make them reliable and predictive. We also uncover other hidden consequences of employing compartmental models in these contexts. Or results contribute a number of insights relevant to the modelling, elucidation, and engineering of biochemical pathways with compartmentalization, at the core of systems and synthetic biology.

Journal article

Menon G, Krishnan J, 2016, Bridging the gap between modules in isolation and as part of networks: a systems framework for elucidating interaction and regulation of signalling modules, Journal of Chemical Physics, Vol: 145, ISSN: 1089-7690

While signalling and biochemical modules have been the focus of numerous studies, they are typically studied in isolation, with no examination of the effects of the ambient network. In this paper we formulate and develop a systems framework, rooted in dynamical systems, to understand such effects, by studying the interaction of signalling modules. The modules we consider are (i) basic covalent modification, (ii) monostable switches, (iii) bistable switches, (iv) adaptive modules, and (v) oscillatory modules. We systematically examine the interaction of these modules by analyzing (a) sequential interaction without shared components, (b) sequential interaction with shared components, and (c) oblique interactions. Our studies reveal that the behaviour of a module in isolation may be substantially different from that in a network, and explicitly demonstrate how the behaviour of a given module, the characteristics of the ambient network, and the possibility of shared components can result in new effects. Our global approach illuminates different aspects of the structure and functioning of modules, revealing the importance of dynamical characteristics as well as biochemical features; this provides a methodological platform for investigating the complexity of natural modules shaped by evolution, elucidating the effects of ambient networks on a module in multiple cellular contexts, and highlighting the capabilities and constraints for engineering robust synthetic modules. Overall, such a systems framework provides a platform for bridging the gap between non-linear information processing modules, in isolation and as parts of networks, and a basis for understanding new aspects of natural and engineered cellular networks.

Journal article

Seaton D, Krishnan J, 2016, Model-based analysis of cell cycle responses to dynamically varying environments, PLOS Computational Biology, Vol: 12, ISSN: 1553-734X

Cell cycle progression is carefully coordinated with a cell’s intra- and extracellular environment. While some pathways have been identified that communicate information from the environment to the cell cycle, a systematic understanding of how this information is dynamically processed is lacking. We address this by performing dynamic sensitivity analysis of three mathematical models of the cell cycle in Saccharomyces cerevisiae. We demonstrate that these models make broadly consistent qualitative predictions about cell cycle progression under dynamically changing conditions. For example, it is shown that the models predict anticorrelated changes in cell size and cell cycle duration under different environments independently of the growth rate. This prediction is validated by comparison to available literature data. Other consistent patterns emerge, such as widespread nonmonotonic changes in cell size down generations in response to parameter changes. We extend our analysis by investigating glucose signalling to the cell cycle, showing that known regulation of Cln3 translation and Cln1,2 transcription by glucose is sufficient to explain the experimentally observed changes in cell cycle dynamics at different glucose concentrations. Together, these results provide a framework for understanding the complex responses the cell cycle is capable of producing in response to dynamic environments.

Journal article

Liu C, Krishnan J, Xu X-Y, 2015, Intrinsic and induced drug resistance mechanisms at the cellular and tissue scales, Integrative Biology, ISSN: 1757-9694

Journal article

Zhao Y-B, Krishnan J, 2015, Probabilistic Boolean Modeling and Analysis framework for mRNA translation, IEEE/ACM Transactions on Computational Biology and Bioinformatics, ISSN: 1557-9964

Journal article

Krishnan J, Alam-Nazki A, 2015, Spatial Control of biochemical modification cascades and pathways, Biophysical Journal

Journal article

Krishnan J, Suwanmajo T, 2015, Mixed Mechanisms in multi-site phosphorylation, Journal of the Royal Society Interface, ISSN: 1742-5689

Journal article

Liu C, Krishnan J, Xu XY, 2015, Intrinsic and induced drug resistance mechanisms: in silico investigations at the cellular and tissue scales, INTEGRATIVE BIOLOGY, Vol: 7, Pages: 1044-1060, ISSN: 1757-9694

Journal article

Krishnan J, Mois K, Suwanmajo T, 2014, The behaviour of basic autocatalytic modules in isolation and embedded in networks, Journal of Chemical Physics, ISSN: 1089-7690

Journal article

Zhao Y-B, Krishnan J, 2014, mRNA translation and protein synthesis: A comparison of modelling methodologies and a new PBN based approach, BMC Systems Biology

Journal article

Liu C, Krishnan J, Xu X-Y, 2013, Towards an integrated systems-based modelling framework for drug transport and its effect on tumour cells, Journal of Biological Engineering

Journal article

Suwanmajo T, Krishnan J, 2013, Biphasic Responses in multisite phosphorylation systems, Journal of the Royal Society Interface

Journal article

Krishnan J, Alam-Nazki A, 2013, Elucidating design principles underlying attractive and repulsive gradient sensing in eukaryotic chemotaxis

Conference paper

Liu C, Krishnan J, Xu X-Y, 2013, Investigating the effects of ABC-transporter mediated acquired drug resistance mechanisms at the cell and tissue scale, Integrative Biology

Journal article

Alam-Nazki A, Krishnan J, 2013, Covalent modification cycles through the spatial prism, Biophysical Journal, Vol: 105, Pages: 1720-1731

Journal article

Seaton D, Krishnan J, 2012, Effects of multiple enzyme-substrate interaction in basic units of cellular signal processing, Physical Biology

Journal article

Alam-Nazki A, Krishnan J, 2012, An investigation of spatial signal transduction in cellular networks, BMC Systems Biology

Journal article

Liu C, Krishnan J, Xu X-Y, 2012, An investigation of effects of drugs on solid tunmours within a systems-based mathematical modelling framework, Innovative simulation methods in healthcare

Conference paper

Krishnan J, Liu C, 2012, An investigation of signal transduction and irreversible decision making in monostable and bistable circuits, Systems and Synthetic Biology: A Systematic View, Editors: kulkarni, Stan, Raman

Book chapter

Betney R, de Silva E, Mertens C, Knox Y, Krishnan J, Stansfield Iet al., 2012, Regulation of release factor expression through a translational negative feedback loop: a systems analysis, RNA

Journal article

Seaton D, Krishnan J, 2012, Multispecific Interactions in Enzymatic Signalling Cascades, Information Processing in Cells and Tissues, Publisher: Springer, Pages: 67-73

Conference paper

Krishnan J, 2011, Chemical Engineering at the Cellular Scale: Cellular Signal Processing, INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, Vol: 50, Pages: 13236-13243, ISSN: 0888-5885

Journal article

Liu C, Krishnan J, Xu XY, 2011, A systems-based mathematical modelling framework for investigating the effect of drugs on solid tumours, THEORETICAL BIOLOGY AND MEDICAL MODELLING, Vol: 8, ISSN: 1742-4682

Journal article

Liu C, Krishnan J, Stebbing J, Xu XYet al., 2011, Use of mathematical models to understand anticancer drug delivery and its effect on solid tumors, PHARMACOGENOMICS, Vol: 12, Pages: 1337-1348, ISSN: 1462-2416

Journal article

Seaton DD, Krishnan J, 2011, The coupling of pathways and processes through shared components, BMC SYSTEMS BIOLOGY, Vol: 5, ISSN: 1752-0509

Journal article

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