Genetically encoded biosensors for the circular plastics bioeconomy.

Current plastic production and consumption routes are unsustainable due to impact upon climate change and pollution, and therefore reform across the entire value chain is required. Biotechnology offers solutions for production from renewable feedstocks, and to aid end of life recycling/upcycling of plastics. Biology sequence/design space is complex requiring high-throughput analytical methods to facilitate the iterative optimisation, design-build, test-learn (DBTL), cycle of Synthetic Biology.

Complex waste stream valorization through combined enzymatic hydrolysis and catabolic assimilation by Pseudomonas putida.

Biogenic waste-derived feedstocks for production of fuels, chemicals, and materials offer great potential supporting the transition to net-zero and greater circularity. However, such feedstocks are heterogeneous and subject to geographical and seasonal variability. Here, we show that, through careful strain selection and metabolic engineering, Pseudomonas putida can be employed to permit efficient co-utilization of highly heterogeneous substrate compositions derived from hydrolyzed mixed municipal-like waste fractions (food, plastic, organic, paper, cardboard, and textiles) for growth and synthesis of exemplar bioproducts.

Tuning the performance of a TphR-based terephthalate biosensor with a design of experiments approach.

Transcription factor-based biosensors are genetic tools that aim to predictability link the presence of a specific input stimuli to a tailored gene expression output. The performance characteristics of a biosensor fundamentally determines its potential applications. However, current methods to engineer and optimise tailored biosensor responses are highly nonintuitive, and struggle to investigate multidimensional sequence/design space efficiently.