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Transcriptional biosensors have various applications in metabolic engineering, including dynamic pathway control and high-throughput screening of combinatorial strain libraries. Previously, various biosensors have been created from naturally occurring transcription factors (TFs), largely relying on native sequences without the possibility to modularly optimize their response curve. The lack of design and engineering techniques thus greatly hinders the development of custom biosensors. In view of the intended application this is detrimental. In contrast, a bottom-up approach to design tailor-made biosensors was pursued here. Novel biosensors were created that respond to N-acetylneuraminic acid (Neu5Ac), an important sugar moiety with various biological functions, by employing native and engineered promoters that interact with the TF NanR. This bottom-up approach, whereby various tuned modules, e.g., the ribosome binding site (RBS) controlling NanR translation can be combined, enabled the reliable engineering of various response curve characteristics. The latter was validated by testing these biosensors in combination with various Neu5Ac-producing pathways, which allowed to produce up to 1.4 ± 0.4 g/L extracellular Neu5Ac. In this way, the repertoire of biosensors was expanded with seven novel functional Neu5Ac-responsive biosensors. ispartof: BIOTECHNOLOGY AND BIOENGINEERING vol:115 issue:7 pages:1855-1865 ispartof: location:United States status: published

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.

Transcriptional biosensors enable key applications in both metabolic engineering and synthetic biology. Due to nature's immense variety of metabolites, these applications require biosensors with a ligand specificity profile customized to the researcher's needs. In this work, chimeric biosensors were created by introducing parts of a donor regulatory circuit from Sinorhizobium meliloti, delivering the desired luteolin-specific response, into a nonspecific biosensor chassis from Herbaspirillum seropedicae. Two strategies were evaluated for the development of chimeric LysR-type biosensors with customized ligand specificity profiles toward three closely related flavonoids, naringenin, apigenin, and luteolin. In the first strategy, chimeric promoter regions were constructed at the biosensor effector module, while in the second strategy, chimeric transcription factors were created at the biosensor detector module. Via both strategies, the biosensor repertoire was expanded with luteolin-specific chimeric biosensors demonstrating a variety of response curves and ligand specificity profiles. Starting from the nonspecific biosensor chassis, a shift from 27.5% to 95.3% luteolin specificity was achieved with the created chimeric biosensors. Both strategies provide a compelling, faster, and more accessible route for the customization of biosensor ligand specificity, compared to de novo design and construction of each biosensor circuit for every desired ligand specificity.

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.

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.

Leaping DNA read-and-write technologies, and extensive automation and miniaturization are radically transforming the field of biological experimentation by providing the tools that enable the cost-effective high-throughput required to address the enormous complexity of biological systems. However, standardization of the synthetic biology workflow has not kept abreast with dwindling technical and resource constraints, leading, for example, to the collection of multi-level and multi-omics large data sets that end up disconnected or remain under- or even unexploited.In this contribution, we critically evaluate the various efforts, and the (limited) success thereof, in order to introduce standards for defining, designing, assembling, characterizing, and sharing synthetic biology parts. The causes for this success or the lack thereof, as well as possible solutions to overcome these, are discussed.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.

Despite the potential in utilizing microbial fermentation for chemical production, the field of industrial biotechnology still lacks a standard, universally applicable principle for strain optimization. A key challenge has been in finding and applying effective ways to address metabolic flux imbalances. Strategies based on rational design require significant a priori knowledge and often fail to take a holistic view of cellular metabolism. Combinatorial approaches enable more global searches but require a high-throughput screen. Here, we present the recent advances and promises of a novel approach to metabolic pathway and strain optimization called multivariate modular metabolic engineering (MMME). In this technique, key enzymes are organized into distinct modules and simultaneously varied based on expression to balance flux through a pathway. Because of its simplicity and broad applicability, MMME has the potential to systematize and revolutionize the field of metabolic engineering and industrial biotechnology.