Synthetic biology enabled cellular and cell-free biosensors for environmental contaminants

Abstract

Cell-based biosensors have great potential to detect various toxic and pathogenic contaminants in aqueous environments. However, frequently they cannot meet practical requirements due to insufficient sensing performance, inadequate sensing platforms and biosafety issues.

Here, I investigated a novel, comprehensive and modular methodology for optimising cell-based biosensors to address these challenges, and to enable them for their practical applications. In particular, this methodology combines multiple synthetic biology strategies, which can systematically and significantly improve sensors’ sensing performance in a predictable manner.

It first optimises a sensor’s sensitivity by regulating its intracellular receptor densities, then further improves its output by applying a multi-layer transcriptional amplifier cascade, and finally regulates its leakiness by combining promoter structure engineering and post-translational regulation. Exemplary bacterial cell-based arsenic and mercury sensors were used to demonstrate this methodology, and their detection limits and outputs were improved up to 5,000-fold and 750-fold respectively.

Facilitated by this methodology, I developed easy-to-interpret sensing platforms for cost-effective and portable field testing, where the analytes were easily quantified by simple visualisation. Physical entrapment methods, i.e., agarose gel entrapment and microfluidic biodisplay, were applied to the sensing platforms to mitigate and minimise the biosafety concerns.

To further eliminate the biosafety issues, the arsenic and mercury sensors were transferred into a crude cell extract-based cell-free system (CFS). To adapt the sensors to the CFS, aforementioned methodology combined with additional tuning methods were applied, such as tuning the sensors’ DNA concentration and their receptor to promoter ratio, introducing transcriptional amplifiers and promoter engineering. A similar paper-based sensing platform could be generated based on these optimisation methods. A mercury sensor with colorimetric output was adapted to a paper-based CFS, where the sensor’s response to 2 ppb mercury could be easily visualised by the naked eye.

Overall, the verified signal amplifying methodology along with the cellular and CFS-based sensing platforms can be widely applicable to many other cell-based sensors, paving the way for their real world applications in the environment and healthcare.