Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.777977
Title: Dynamical adaptation in biology on multiple scales : from cells to collectives
Author: Gosztolai, Adam
ISNI:       0000 0004 7963 7417
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2018
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Abstract:
Bacteria and higher organisms alike have evolved sophisticated mechanisms to dynamically adapt to changing environments. We study temporal and spatial aspects of adaptation on multiple scales and at different levels of biological description. Firstly, in the context of Escherichia coli nitrogen assimilation, we study the cellular mechanisms facilitating dynamical adaptation to time-varying nitrogen abundance. We develop a concise mechanistic model, based on previously characterised biochemical interactions, that predicts the states of key enzymes in vivo during changes in ammonium abundance. Experimental data and model predictions reveal the dynamic role of enzymatic interactions in the signalling and regulation of the cellular nitrogen status. We suggest a novel, history-dependent mechanism regulating the ammonium uptake with the role to anticipate and buffer nitrogen shock. Secondly, we consider the chemotaxis of E. coli to study the functional role of cellular memory in chemotactic navigation. Agent-based simulations show that cells with memory achieve higher drift speeds in rugged attractant gradients than predicted by the Keller- Segel (KS) model describing gradient sensing. This behaviour is captured by a second- order correction to the KS drift velocity containing the effect of spatial correlations. Our results are consistent with the chemotactic pathway processing spatial correlations shedding light on the spatial interpretation of filtering. Thirdly, we generalise to study how the spatial information acquired at the microscopic level influences the spatial search by a population of random walkers. We extend the KS model of local search as an optimal control problem that describes the movement of searchers with spatial perception, quantified by a time horizon. Simulations and analytical arguments show that spatial perception induces faster convergence to steady state. Our results highlight the importance of transients in search; while asymptotically local strategies are optimal, biological timescales favour strategies based on finite spatial information.
Supervisor: Barahona, Mauricio ; Buck, Martin Sponsor: Biotechnology and Biological Sciences Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.777977  DOI:
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