Cluster 1- Developing biosensors for real-time monitoring of conventional and emerging pollutants
Cranfield University – Prof Zhugen Yang, Prof Frederic Coulon, PDRA1
Partner: Newcastle University Prof Thomas Curtis, Prof Natalio Krasnogor
Challenges:
Overcoming various issues associated with biosensing, including reducing cross-interference, enabling multiplexed detection, accelerating in situ amplification for quicker detection, and utilising computational models to uncover new sensing mechanisms and design probes for emerging contaminants (e.g., antibiotic resistance genes micro and nano plastics, Per- and polyfluoroalkyl substances (PFAS).
Potential solutions:
Designing, building, and validating a class of new biosensors based on a CRISPR/Cas system for ultrasensitive detection of chemical and biological contaminants. For instance, CRISPR-associated enzymes like Cas13 can reduce false-positive outcomes when combined with isothermal amplification assays. These methods enable detection as low as 10 copies per reaction and enhance selectivity for RNA assays. The use of an RNA-guided ribonuclease (Cas13) with CRISPR RNA (crRNA)–target pairing and signal amplification via Cas13 collateral cleavage activity will provide both specificity and sensitivity.
Engineering the assay into the microfluidic devices (e.g., paper microfluidics analytical devices) to enable in-field testing and use computational models to support the developed sensing platform for multiple source data collection. The goal is to provide an innovate SynBio-enabled sensing platform for continuously, rapid and on-site detection of environmental contaminants.
Drawing from large data sets collected at early stages aided by machine learning and artificial intelligence, to discover new sensing mechanisms and design probes for emerging contaminants.