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Details of Grant 

EPSRC Reference: EP/M002306/1
Title: Engineering Fellowships for Growth: Advanced synthetic biology measurement to enable programmable functional biomaterials
Principal Investigator: Ellis, Professor TM
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Agilent Technologies Ltd California Institute of Technology Refactored Materials Inc
Regents of the Univ California Berkeley SynBioBeta University of the Arts London
Department: Bioengineering
Organisation: Imperial College London
Scheme: EPSRC Fellowship
Starts: 17 November 2014 Ends: 30 July 2020 Value (£): 963,842
EPSRC Research Topic Classifications:
Control Engineering Synthetic biology
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:
Panel DatePanel NameOutcome
12 Mar 2014 Engineering Fellowships for Growth - SynBio Announced
Summary on Grant Application Form
Synthetic biology accelerates the research and development of new biotechnologies by rigorously applying engineering design principles to the way we work with biological systems. The most prominent application of synthetic biology is the rational modification and redesign of living organisms like microbes for new efficient use in sectors such as energy production, biomaterials, biomedicine, drug production and food technology. Crucial to developing and applying synthetic biology is the rigorous quantification, modelling and analysis of synthetic biology designs. By using this engineering framework researchers aim to predict how engineered biological systems will operate.

Despite many successes, it is still difficult to predict how engineered cells behave when new synthetic genetic information is added to these host cells. Key to the high failure rates in forward engineering in synthetic biology is the lack of high-quality data available on parts and devices. Without a holistic dataset reporting on performance of a biological part in its host cell, it is difficult to predict how it will behave when included in complex designs. The work proposed in this project seeks to address this by developing a novel workflow to obtain a richer-dataset on thousands of different parts and devices as they are implemented in bacterial host cells. To achieve this goal, a screening workflow will be established, that for the first time incorporates in vitro prototyping, with in vivo assaying and mass-spectrometry profiling to simultaneously capture how synthetic biology device design affects gene expression, expression load and host cell health, energy and growth. Measuring these multiple parameters in parallel will greatly enrich predictive models and ideally will lead to robust in silico predictions on performance characteristics such as growth rate and mutation likelihood. In this project, modelling will be developed specifically for this task and mass spectrometry will also be introduced as a state-of-the-art measurement tool. Both are new frontiers for synthetic biology.

While this research will have a very wide impact and accelerate the many different future applications of synthetic biology, in this project it will be specifically used to tackle a high-value biomaterials application that would be unlikely to succeed without the strong engineering foundations this work provides. For this part of the project, predictions of gene expression and growth will be used to express a library of different functional proteins in engineered microbes and microbial consortia that can then be polymerised together to generate polyprotein biomaterials with programmable catalytic and material properties. For example, by combining silk proteins with lipase enzymes in biological polymers, advanced materials such as self-cleaning fabrics can be realised. While this materials work is intended as a showcase for the foundational methods developed in this project, it will no doubt lead to many future exciting applications and new industries in a rich variety of commercial, engineering and research sectors, from fashion and manufacturing to medicine.
Key Findings
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Organisation Website: http://www.imperial.ac.uk