Programming Bacteria With Light—Sensors and Applications in Synthetic Biology

Key Points Early synthetic biology designs, namely the genetic toggle switch and repressilator, showed that regulatory components can be characterized and assembled to bring about complex, electronics-inspired behaviours in living systems (for example, memory storage and timekeeping). Through the characterization and assembly of genetic parts and biological building blocks, many more devices have been constructed, including switches, memory elements, oscillators, pulse generators, digital logic gates, filters and communication modules. Advances in the field are now allowing expansion beyond small gene networks to the realm of larger biological programs, which hold promise for a wide range of applications, including biosensing, therapeutics and the production of biofuels, pharmaceuticals and biomaterials. Synthetic biosensing circuits consist of sensitive elements that bind analytes and transducer modules that mobilize cellular responses. Balancing these two modules involves engineering modularity and specificity into the various circuits. Biosensor sensitive elements include environment-responsive promoters (transcriptional), RNA aptamers (translational) and protein receptors (post-translational). Biosensor transducer modules include engineered gene networks (transcriptional), non-coding regulatory RNAs (translational) and protein signal-transduction circuits (post-translational). The contributions of synthetic biology to therapeutics include: engineered networks and organisms for disease-mechanism elucidation, drug-target identification, drug-discovery platforms, therapeutic treatment, therapeutic delivery, and drug production and access. In the microbial production of biofuels and pharmaceuticals, synthetic biology has supplemented traditional genetic and metabolic engineering efforts by aiding the construction of optimized biosynthetic pathways. Optimizing metabolic flux through biosynthetic pathways is traditionally accomplished by driving the expression of pathway enzymes with strong, inducible promoters. New synthetic approaches include the rapid diversification of various pathway components, the rational and model-guided assembly of pathway components, and hybrid solutions.

The complexity of cellular gene, protein, and metabolite networks can hinder attempts to elucidate their structure and function. To address this problem, we used systematic transcriptional perturbations to construct a first-order model of regulatory interactions in a nine-gene subnetwork of the SOS pathway in Escherichia coli. The model correctly identified the major regulatory genes and the transcriptional targets of mitomycin C activity in the subnetwork. This approach, which is experimentally and computationally scalable, provides a framework for elucidating the functional properties of genetic networks and identifying molecular targets of pharmacological compounds.