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Details of Grant 

EPSRC Reference: EP/W032813/1
Title: Engineering robust, stable, and safe synthetic genetic circuits for smart therapeutics
Principal Investigator: BAKSHI, Dr S
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Engineering
Organisation: University of Cambridge
Scheme: New Investigator Award
Starts: 01 October 2022 Ends: 31 March 2025 Value (£): 321,304
EPSRC Research Topic Classifications:
Synthetic biology
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:
Panel DatePanel NameOutcome
08 Jun 2022 Engineering Prioritisation Panel Meeting 8 and 9 June 2022 Announced
Summary on Grant Application Form
Synthetic biology is an emerging field of research where we use engineering principles for combining different biological parts to construct engineered biological systems. One of the most active areas of research in synthetic biology is engineering therapeutic bacteria that contain genetic circuits for detection and prevention of diseases. Many bacteria in nature possess the capabilities to sense minute changes in the environment and to produce biomolecules with therapeutic potential. If we can effectively combine the 'sensor' (to detect disease symptoms) and 'effector' (to produce molecules of interest) parts from different bacteria we can engineer strains that can act as 'smart' therapeutics. Such a therapeutic strain could stay in our body and autonomously detect and treat infections from pathogenic bacteria or prevent genetic or metabolic disorders such as cancer or diabetes. The potential for engineered bacteria with synthetic genetic circuits to act as the ultimate point-of-care diagnostic and therapeutic for our body is profound and exciting.

The past decade of research in synthetic biology has been very successful in expanding the repertoire of genetic parts for 'sensor' and 'effector' modules of such synthetic genetic circuits. However, when combined into the circuit, the performance has been suboptimal and difficult to predict. Furthermore, the functional lifetime of such circuits has been very short, as impairing mutants appear and take over the population or the circuit itself gets lost over time. The poor performance and short functional lifetime of synthetic genetic circuits have made it difficult to realise the enormous potential of engineered bacteria in 'bacterial therapy'.

We are proposing to build a directed evolution pipeline to engineer synthetic genetic circuits that are suitable for therapeutic applications. This pipeline involves a novel method for creating variation in circuit sequence, a transformative testbed for comparing the circuit function and its impact on the health of the carrying cell (the main determinant of functional lifetime) for each variant, and a new technology to isolate the selected variants with improvements in both. This system is developed based on key achievements in our research on analysing growth, physiology, and gene-expression of bacteria, including the recently developed microfluidic technology that enables us to monitor >100k individual bacterial cells in parallel over many hours, time-resolved imaging techniques to record the growth and fluorescence in each cell with a high framerate, and machine-learning algorithms that enable us to accurately analyse this high-throughput data. This pipeline will optimise circuits to improve their function and functional lifetime such that they can act in robust manner over a long period of time.

Since we need the therapeutic bacteria containing such circuits to be applied to our body, we need to make sure that the circuits do not get lost and are not transferred to other bacterial cells in our body. Therefore, to engineer safe therapeutic bacteria, we will integrate the synthetic circuit to the chromosome of the bacteria, where they can't be easily lost or transferred. Currently, there is no pipeline for optimising circuits integrated to the chromosome and no platform for simultaneously quantifying function and functional lifetime of a synthetic circuit. The directed evolution pipeline developed in this work will be the first of its kind to enable in situ optimisation of synthetic circuits to simultaneously improve the function and functional lifetime. We plan to use this directed evolution pipeline to engineer and optimise a 'smart' therapeutic bacterium that carries a sensor module for detecting inflammation caused by pathogens and activates oscillatory production of an antimicrobial peptide to eliminate the infecting pathogen.
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