Transcription factor-based biosensors are used to identify producer strains, a critical bottleneck in cell factory engineering. Here, we address two challenges with this methodology: transplantation of heterologous transcriptional regulators into new hosts to generate functional biosensors and biosensing of the extracellular product concentration that accurately reflects the effective cell factory production capacity. We describe the effects of different translation initiation rates on the dynamic range of a p-coumaric acid biosensor based on the Bacillus subtilis transcriptional repressor PadR by varying its ribosomal binding site. Furthermore, we demonstrate the functionality of this p-coumaric acid biosensor in Escherichia coli and Corynebacterium glutamicum. Finally, we encapsulate yeast p-coumaric acid-producing cells with E. coli-biosensing cells in picoliter droplets and, in a microfluidic device, rapidly sort droplets containing yeast cells producing high amounts of extracellular p-coumaric acid using the fluorescent E. coli biosensor signal. As additional biosensors become available, such approaches will find broad applications for screening of an extracellular product.

We present the optimization of E. coli biosensor bacteria and demonstrate their use to detect and sort co-encapsulated S. cerevisiae yeast cells by their p-Coumaric acid (pCA) production in picoliter microfluidic droplets at high throughput. This strategy allows us to enrich pCA producing cell factories by the cell permeable product pCA using a biosensor in a separate cell.

Background: Photosynthetic cyanobacteria are attractive for a range of biotechnological applications including biofuel production. However, due to slow growth, screening of mutant libraries using microtiter plates is not feasible. Results: We present a method for high-throughput, single-cell analysis and sorting of genetically engineered l-lactate-producing strains of Synechocystis sp. PCC6803. A microfluidic device is used to encapsulate single cells in picoliter droplets, assay the droplets for L-lactate production, and sort strains with high productivity. We demonstrate the separation of low- and high-producing reference strains, as well as enrichment of a more productive L-lactate-synthesizing population after UV-induced mutagenesis. The droplet platform also revealed population heterogeneity in photosynthetic growth and lactate production, as well as the presence of metabolically stalled cells. Conclusions: The workflow will facilitate metabolic engineering and directed evolution studies and will be useful in studies of cyanobacteria biochemistry and physiology.