Evolving controllers and controlling evolution

Lead Research Organisation: University of Exeter
Department Name: Engineering Computer Science and Maths


Biological systems, in particular cellular interaction networks, display complex dynamics and widely-conserved structural features such as modularity and robustness. Many of the same dynamical and structural features are found in engineered systems and networks across a diverse range of industrial applications4 Crucially, however, although the end-results may in certain respects look very similar, the processes by which engineered and natural systems arrive at successful designs are very different - in engineering, modularity and robustness in a given system result from the use of formalised design processes (systems and control engineering); in biology, from the process of evolution. In this project, we propose to exploit synergies and bring about cross-fertilisation of tools and ideas between the fields of control theory and evolutionary theory to address the following specific questions: (1) What evolutionary pressures have given rise to robustness in biological systems? Have biological systems evolved primarily to be robust, or has robustness arisen as a by-product of other more important characteristics? (2) Is module-based design an optimal approach to the engineering of synthetic biological systems or are there alternatives? Are there key features of biological systems and mutational operators that evolution exploits as a design tool? (3) Is it possible to control evolution? Can we apply control engineering tools to the evolutionary process to generate synthetic biological systems with desired characteristics? (4) Are there evolutionary principles that can be used for designing better engineering systems? Can we combine evolutionary simulation with mathematical optimization to simultaneously evolve both the structure and parameter values of large networked control systems to optimally satisfy conflicting design criteria? We believe that even partial answers to these questions will lead to transformative research breakthroughs across the fields of systems biology, synthetic biology and systems and control engineering.

Planned Impact

We expect this research to lead to breakthroughs across the fields of systems biology, synthetic biology and systems and control engineering, which means the project has considerable potential for scientific, economic and societal impact. Scientific Impact Impact on Research Communities The proposed research will have significant scientific impact, benefiting synthetic biology, systems biology and engineering communities. In particular, cross-fertilisation of tools and ideas between the fields of control theory and evolutionary theory will (i) increase our ability to engineer biology, (ii) allow a better understanding of functional properties of complex biological systems, and (iii) lead to the development of novel and biologically-inspired engineering tools and approaches for designing advanced control systems. See Impact Plan for plans to increase such impact on the broader research community. Impact on Collaboration and Education By combining engineering and evolution for design of synthetic modules, the proposed research will further develop this awareness in the field of synthetic biology. More importantly, this research will directly explore the changes that result from the hybridization of biology and engineering, specifically the relationship of integration to interdisciplinarity, how these are achieved in this particular research contexts, and whether these achievements can elucidate synthetic biology broadly. This will improve collaborations among established scientists and provide a case study for the education of young scientists just entering the field (e.g. as study material or discussion topic in relevant courses). See Impact Plan for plans to increase such impact on education. Economic Impact Direct Translational Impact The proposed research is expected to feed directly into increasing the capacity of synthetic biology to develop and deliver applications and of control engineering to tackle control problems of high complexity. We will continually evaluate the possibility of bringing these scientific developments to commercial stage and seek opportunities both within the academia and industry to do so. See Impact Plan for plans to increase such translational impact. Innovation Impact In a larger context, this proposal is an extensive attempt to bridge the gap between approaches that use design in a pure engineering sense and those that use design through evolution (i.e. natural exploration of all possible designs). We envisage that this novel design approach will enable synthetic biologists to engineer biological systems with higher functionalities. Furthermore, it can lead to evolutionarily and biologically inspired tools and approaches in other engineering domains, especially those related to network theory and design (e.g. computer science). Social Impact The proposed research brings evolution and design together to allow a unique opportunity to address these topics in a tractable manner at a social, educational and scientific level. Its philosophical component will address humanities and societal issues, with a particular focus on what the hybridization of evolution and design means for broad society-wide understanding of synthetic biology (a topic of controversy and concern). By focusing on evolution and its potential as a design process, from the point of view of both the lay public and the scientist, we will take existing debates about synthetic biology to a new level and offer collaborative opportunities to think in innovative and evolutionarily informed ways about synthetic biology and engineering living systems. We will do this via two public dialogue events in Exeter, where (with assistance from the Communication Officer at Egenis) we will hold panel discussions with a mix of scientists, social scientists and science commentators followed by audience participation. See Impact Plan for further plans to maximise the social impact of these events and the project.


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Related Projects

Project Reference Relationship Related To Start End Award Value
EP/I017445/1 01/10/2011 23/05/2013 £416,929
EP/I017445/2 Transfer EP/I017445/1 01/08/2013 30/11/2014 £155,755
Description See also award EP/I017445/2. We have discovered key structural and dynamic features of biological systems that endow them with specific abilities to perform information processing. In addition, we have discovered features that endow such biological systems with robustness, i.e. ability to continue performing their function despite perturbations to their parameters.
We have also developed computational tools and approaches that can assist in future analysis of biological system dynamics. In particular, we have developed novel methods to simulate and analyze the evolution of biological systems in the computer. This approach allows us to "re-play" evolution of a biological system of interest in a computer and analyze the emergence of system properties under different evolutionary (e.g. selective pressures) and structural conditions (e.g. allowing multi-domain proteins).
Exploitation Route Synthetic Biology / Bioengineering: The discovered features will assist with ongoing efforts to engineer biological systems de novo to achieve controlled and bespoke systems that are designed.
Medicine: The discovered structural and dynamical features of biological systems will assist in better understanding of natural systems and can assist particularly in drug development and understanding of disease mechanisms.
Engineering: The discovered structural and dynamical features will inspire novel engineering solutions to achieve robustness and information processing in mad-made system. In particular, our findings on robustness inspire a new control engineering approach that can be used in a multitude of areas including Aerospace, Defense and Marine
Sectors Aerospace, Defence and Marine,Healthcare,Pharmaceuticals and Medical Biotechnology

URL http://osslab.lifesci.warwick.ac.uk/?pid=resources
Description Robustness in biology and engineering 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact This workshop brings together biologists, philosophers, engineers and mathematicians interested in systems and synthetic biology, in order to discuss the central notion of evolvability: the capacity of organisms for adaptive evolution, which secures the emergence of beneficial traits that can undergo natural selection. The workshop proposes to examine the history and multiple current usages of the notion of evolvability, and its relation to other key ideas within systems and synthetic biology, such as the idea of robustness. In particular, we will discuss the ways in which evolvability is being modelled, with specific emphasis on mathematical modelling and theoretical approaches coming from engineering, such as control theory. Speakers will concern themselves with the ways in which models capture and operationalize the idea of evolvability, and reflect on the ways in which modelling strategies adopted in systems biology over the last two decades are impacting on current conceptualisations of what it means for organisms to be able to evolve.

This workshop has led to a larger, and more formal activity organized subsequently at the Konrad Lorenz Institute.
Year(s) Of Engagement Activity 2012