Review Article | Open Access
Volume 2024 |Article ID 0037 | https://doi.org/10.34133/bdr.0037

Accelerating Genetic Sensor Development, Scale-up, and Deployment Using Synthetic Biology

Shivang Hina-Nilesh Joshi,1 Christopher Jenkins,2 David Ulaeto,2 Thomas E. Gorochowski 1,3

1School of Biological Sciences, University of Bristol, Bristol BS8 1TQ, UK
2CBR Division, Defence Scienceand Technology Laboratory, Porton Down, Wiltshire SP4 0JQ, UK
3BrisEngBio, School of Chemistry,University of Bristol, Bristol BS8 1TS, UK

Received 
30 Jan 2024
Accepted 
23 Apr 2024
Published
25 Jun 2024

Abstract

Living cells are exquisitely tuned to sense and respond to changes in their environment. Repurposing these systems to create engineered biosensors has seen growing interest in the field of synthetic biology and provides a foundation for many innovative applications spanning environmental monitoring to improved biobased production. In this review, we present a detailed overview of currently available biosensors and the methods that have supported their development, scale-up, and deployment. We focus on genetic sensors in living cells whose outputs affect gene expression. We find that emerging high-throughput experimental assays and evolutionary approaches combined with advanced bioinformatics and machine learning are establishing pipelines to produce genetic sensors for virtually any small molecule, protein, or nucleic acid. However, more complex sensing tasks based on classifying compositions of many stimuli and the reliable deployment of these systems into real-world settings remain challenges. We suggest that recent advances in our ability to precisely modify nonmodel organisms and the integration of proven control engineering principles (e.g., feedback) into the broader design of genetic sensing systems will be necessary to overcome these hurdles and realize the immense potential of the field.

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