Monitoring cellular behavior and eventually properly adapting cellular processes is key to handle the enormous complexity of today’s metabolic engineering questions. Hence, transcriptional biosensors bear the potential to augment and accelerate current metabolic engineering strategies, catalyzing vital advances in industrial biotechnology. The development of such transcriptional biosensors typically starts with exploring nature’s richness. Hence, in a first part, the transcriptional biosensor architecture and the various modi operandi are briefly discussed, as well as experimental and computational methods and relevant ontologies to search for natural transcription factors and their corresponding binding sites. In the second part of this review, various engineering approaches are reviewed to tune the main characteristics of these (natural) transcriptional biosensors, i.e., the response curve and ligand specificity, in view of specific industrial biotechnology applications, which is illustrated using success stories of transcriptional biosensor engineering.

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Akin to other engineering disciplines, extensive standardization will undoubtedly speed-up and reduce the cost of bioprocess development. In this respect, further implementation of synthetic biology standards will be crucial for the field in order to redeem its promise, i.e. to enable predictable forward engineering.

Glycosylation of small molecules can significantly alter their properties such as solubility, stability, and/or bioactivity, making glycosides attractive and highly demanded compounds. Consequently, many biotechnological glycosylation approaches have been developed, with enzymatic synthesis and whole-cell biocatalysis as the most prominent techniques. However, most processes still suffer from low yields, production rates and inefficient UDP-sugar formation. To this end, a novel metabolic engineering strategy is presented for the in vivo glucosylation of small molecules in Escherichia coli W. This strategy focuses on the introduction of an alternative sucrose metabolism using sucrose phosphorylase for the direct and efficient generation of glucose 1-phosphate as precursor for UDP-glucose formation and fructose, which serves as a carbon source for growth. By targeted gene deletions, a split metabolism is created whereby glucose 1-phosphate is rerouted from the glycolysis to product formation (i.e., glucosylation). Further, the production pathway was enhanced by increasing and preserving the intracellular UDP-glucose pool. Expression of a versatile glucosyltransferase from Vitis vinifera (VvGT2) enabled the strain to efficiently produce 14 glucose esters of various hydroxycinnamates and hydroxybenzoates with conversion yields up to 100%. To our knowledge, this fast growing (and simultaneously producing) E. coli mutant is the first versatile host described for the glucosylation of phenolic acids in a fermentative way using only sucrose as a cheap and sustainable carbon source.

To monitor the intra- and extracellular environment of micro-organisms and to adapt their metabolic processes accordingly, scientists are reprogramming nature's myriad of transcriptional regulatory systems into transcriptional biosensors, which are able to detect small molecules and, in response, express specific output signals of choice. However, the naturally occurring response curve, the key characteristic of biosensor circuits, is typically not in line with the requirements for real-life biosensor applications. In this contribution, a natural LysR-type naringenin-responsive biosensor circuit is developed and characterized with Escherichia coli as host organism. Subsequently, this biosensor is dissected into a clearly defined detector and effector module without loss of functionality, and the influence of the expression levels of both modules on the biosensor response characteristics is investigated. Two collections of ten unique synthetic biosensors each are generated. Each collection demonstrates a unique diversity of response curve characteristics spanning a 128-fold change in dynamic and 2.5-fold change in operational ranges and 3-fold change in levels of Noise, fit for a wide range of applications, such as adaptive laboratory evolution, dynamic pathway control and high-throughput screening methods. The established biosensor engineering concepts, and the developed biosensor collections themselves, are of use for the future development and customization of biosensors in general, for the multitude of biosensor applications and as a compelling alternative for the commonly used LacI-, TetR- and AraC-based inducible circuits.