Engineering Fellowships For Growth: Designing Feedback Control in Biology for Robustness and Scalability

Lead Research Organisation: University of Oxford
Department Name: Engineering Science

Abstract

Synthetic Biology is the "Engineering of Biology": it aspires to use the Engineering design cycle to produce bio-circuits that behave predictably and reliably, usually with specific applications in mind. Synthetic Biology has the potential to create new industries and technologies in several sectors, from agriculture to the environment, and from energy to healthcare. Some of these applications require Synthetic Biology designs to be scalable, so that small circuits can be composed to form larger systems. Currently, however, even small bio-circuits seldom function as expected because of the high level of uncertainty in the cellular environment, the way poorly-characterized parts are assembled together and the lack of a systematic framework for integrating parts to form systems. This is a major challenge that needs to be overcome in order for the potential of Synthetic Biology to be fulfilled and for industry and society to reap the rewards.

Natural systems use several mechanisms to overcome this major challenge. The most important one involves careful use of feedback control. This is done at all levels of organization - from the genetic, metabolic, cellular to the systems level. The regulation of biochemical processes inside a cell is key for ensuring robust functionality despite the high levels of environmental uncertainty and intrinsic and extrinsic noise.

This Fellowship application will use a systems and control engineering approach, based on modelling, abstraction, standardization and the development of new bio-feedback modules to target specific uncertainties in the cell. I will create an interdisciplinary research team which will demonstrate that through careful design and implementation of feedback control components, the functionality of the rest of the designed circuitry can be made robust and allow scalability. The feedback designs will be done at multiple organizational scales and interactions (genetic, signalling and cell-cell), which will be implemented in the laboratory, demonstrating the effectiveness of the approach.

Planned Impact

Synthetic Biology is expected to have significant impact on the economy and society, as outlined in the recent UK Synthetic Biology Roadmap for the UK. Currently, Synthetic Biology constructs do not operate as intended, as they suffer from the uncertainty of the cellular environment in which they have to operate. Moreover, our ability to interconnect them to form larger systems is limited.

The aim of this research fellowship is to develop bio-feedback control modules that can be used by Synthetic Biologists to improve the robustness of their constructs, but also to improve their composability. Allowing scalability and robustness of these modules will undoubtedly have a large impact on the economy and society.

In particular, using feedback control at various scales will bring significant industrial and economic benefits. Industries in which this research has a large potential for economic impact include pharmaceuticals, energy, and agriculture. In the medium to long term, possible applications of synthetic biological systems have been proposed in biosynthesis (including biofuels), biosensors, environmental clean-up, smart materials, etc. Another major long-term potential application of Synthetic Biology will bring wider benefits to society through the development of personalised medicine, with therapies delivered through the application of functionally engineered cells.

In order to realize the full potential of Synthetic Biology to perform the variety of tasks specific to this large number of industrial applications, it is rapidly becoming critical for simple isolated systems to be able to be combined to allow the design of the increasingly sophisticated functions envisioned. For industrial relevance, the design of biological systems needs to be specified at a high, functional level, which is currently not attainable due to the unreliability of the synthetic components at our disposal in the presence of uncertainty when implemented in the cell. This research will be crucial to providing the standardized framework needed to allow the design of biological systems to be scaled to the required level.

At the societal level, it is important that researchers and users of Synthetic Biology are engaged with the wider public as research progresses. There are widely-held concerns over the ethical and safety implications of many aspects of the manipulation and creation of biological systems. This research is intended to apply the principles of Control Engineering to Synthetic Biology. Robust control theory is expressly concerned with ensuring the reliability and safety of engineered systems in the presence of uncertainty. Therefore a key impact of this research will be to help to transform the public perception of Synthetic Biology from a collection of ad hoc methods into a formal engineering discipline.
 
Description The aim of this Fellowship is to use a systems and control engineering approach, based on modelling, abstraction and standardization to develop new bio-feedback modules to target specific uncertainties in the cell. The vision is to create an interdisciplinary research team which will demonstrate that through careful design and implementation of feedback control components, the functionality of the rest of the designed circuitry can be made robust and allow scalability. The feedback designs will be done at multiple organizational scales and interactions (genetic, signalling and cell-cell), which will be implemented in the laboratory, demonstrating the effectiveness of the approach.

As part of this project we have developed feedback modules at the transcription and translation level and signalling pathways, to target uncertainties due to noise and cross-talk. We were the first group to use small RNA to design and implement feedback loops in cells, and we have introduced a new feedback mechanism to target cross-talk. At the same time we have developed Chi.Bio, an automated platform for characterisation of biological experiments, which has been taken up by a number of academic and industrial groups.
Exploitation Route The results of this fellowship can be used to design feedback controllers in Synthetic Biology and ensure that designs are robust and work as intended. Moreover, Chi.Bio is being used by tens of academic and industrial users to facilitate characterisation of their designs.
Sectors Energy,Environment,Healthcare,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology

URL http://sysos.eng.ox.ac.uk/wiki/index.php/Designing_feedback_control_in_Synthetic_Biology
 
Description The project has led to two major findings: one is the design of biofeedback controllers, which is currently being used by some industrial groups to improve the performance of their designs/yields and reduce cross-talk. The other finding has to do with Chi.Bio, an automated platform for characterisation of biological designs, which is being used by industry to characterise their designs.
First Year Of Impact 2020
Sector Energy,Environment,Healthcare,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology
Impact Types Economic

 
Description Impact Acceleration Award - Oxford
Amount £63,272 (GBP)
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 04/2020 
End 09/2021
 
Title Chi.Bio: an automated platform for characterisation of biological designs. 
Description Chi.Bio (https://chi.bio/) is an open-source robotic platform for experimental automation in biological science research and education. By combining heating, stirring, liquid handling, spectrometry, and optogenetics into a single easy-to-use platform, Chi.Bio can simplify laboratory protocols and drastically reduce equipment costs. 
Type Of Material Technology assay or reagent 
Year Produced 2019 
Provided To Others? Yes  
Impact To date, the platform has been adopted by ~80 laboratories in academia and industry. 
URL https://chi.bio/
 
Description Collaboration in Synthetic Biology with Caltech 
Organisation California Institute of Technology
Country United States 
Sector Academic/University 
PI Contribution Meetings and other exchanges of information, data and collaborations.
Collaborator Contribution Materials and knowledge.
Impact Multidisciplinary; outputs are still under development.
Start Year 2011
 
Description Collaboration in Synthetic Biology with ETHZ 
Organisation ETH Zurich
Country Switzerland 
Sector Academic/University 
PI Contribution Meetings, discussions, exchange of information and knowledge
Collaborator Contribution Meetings, discussions, exchange of information and knowledge
Impact A paper is currently under review.
Start Year 2011
 
Description Collaboration in Synthetic Biology with KAIST 
Organisation Korea Advanced Institute of Science and Technology (KAIST)
Country Korea, Republic of 
Sector Academic/University 
PI Contribution Discussions with KAIST staff.
Collaborator Contribution Discussions with my group.
Impact None to date.
Start Year 2015
 
Description Collaboration in Synthetic Biology with MIT 
Organisation Massachusetts Institute of Technology
Country United States 
Sector Academic/University 
PI Contribution Collaboration on Synthetic Biology, tools and methods.
Collaborator Contribution Collaboration on Synthetic Biology, tools and methods.
Impact A joint paper is currently under review; multidisciplinary.
Start Year 2011
 
Description Collaboration in Synthetic Biology with Microsoft Research 
Organisation Microsoft Research
Department Microsoft Research Cambridge
Country United Kingdom 
Sector Private 
PI Contribution Discussions with Microsoft Research staff.
Collaborator Contribution Discussions with our team on Synthetic Biology.
Impact Collaboration is ongoing.
Start Year 2015
 
Title Chi.Bio: an automated platform for characterisation of biological designs. 
Description Chi.Bio (https://chi.bio/) is an open-source robotic platform for experimental automation in biological science research and education. By combining heating, stirring, liquid handling, spectrometry, and optogenetics into a single easy-to-use platform, Chi.Bio can simplify laboratory protocols and drastically reduce equipment costs. 
Type Of Technology New/Improved Technique/Technology 
Year Produced 2019 
Impact To date, the platform has been adopted by ~20 laboratories in academia and industry. 
URL https://chi.bio/
 
Description School Visit 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Schools
Results and Impact Synthetic Biology outreach to Year 12 students
Year(s) Of Engagement Activity 2017
 
Description Workshop in Control Engineering and Synthetic Biology 
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 About 70 academics, industrialists, policymakers and postgraduate/undergraduate students took part in an international workshop at the interface of control engineering and synthetic biology, organised at Worcester College Oxford in September 2019. Discussions focused on the use of control engineering principles in Synthetic Biology but also how synthetic biology drives research in control engineering.
Year(s) Of Engagement Activity 2019
URL http://sysos.eng.ox.ac.uk/wiki/index.php/SynBioControl2019
 
Description Workshop organisation 
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 Workshop on control engineering and synthetic biology, "what next".
Year(s) Of Engagement Activity 2017
URL http://sysos.eng.ox.ac.uk/wiki/index.php/SynBioControl2017