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The use of intracellular, biosensor-based dynamic regulation strategies to regulate and improve the production of useful compounds have progressed significantly over previous decades. By employing such an approach, it is possible to simultaneously realize high productivity and optimum growth states. However, industrial fermentation conditions contain a mixture of high- and low-performance non-genetic variants, as well as young and aged cells at all growth phases. Such significant individual variations would hinder the precise controlling of metabolic flux at the single-cell level to achieve high productivity at the macroscopic population level. Intracellular biosensors, as the regulatory centers of metabolic networks, can real-time sense intra- and extracellular conditions and, thus, could be synthetically adapted to balance the biomass formation and overproduction of compounds by individual cells. Herein, we highlight advances in the designing and engineering approaches to intracellular biosensors. Then, the spatiotemporal properties of biosensors associated with the distribution of inducers are compared. Also discussed is the use of such biosensors to dynamically control the cellular metabolic flux. Such biosensors could achieve single-cell regulation or collective regulation goals, depending on whether or not the inducer distribution is only intracellular.

β-alanine is an important biomolecule used in nutraceuticals, pharmaceuticals, and chemical synthesis. The relatively eco-friendly bioproduction of β-alanine has recently attracted more interest than petroleum-based chemical synthesis. In this work, we developed two types of in vivo high-throughput screening platforms, wherein one was utilized to identify a novel target ribonuclease E (encoded by rne) as well as a redox-cofactor balancing module that can enhance de novo β-alanine biosynthesis from glucose, and the other was employed for screening fermentation conditions. When combining these approaches with rational upstream and downstream module engineering, an engineered E. coli producer was developed that exhibited 3.4- and 6.6-fold improvement in β-alanine yield (0.85 mol β-alanine/mole glucose) and specific β-alanine production (0.74 g/L/OD 600 ), respectively, compared to the parental strain in a minimal medium. Across all of the strains constructed, the best yielding strain exhibited 1.08 mol β-alanine/mole glucose (equivalent to 81.2% of theoretic yield). The final engineered strain produced 6.98 g/L β-alanine in a batch-mode bioreactor and 34.8 g/L through a whole-cell catalysis. This approach demonstrates the utility of biosensor-enabled high-throughput screening for the production of β-alanine., Competing Interests: Declaration of competing interest The authors declare that they have no conflict of interest., (Copyright © 2022 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.)

A key bottleneck in the microbial production of therapeutic plant metabolites is identifying enzymes that can improve yield. The facile identification of genetically encoded biosensors can overcome this limitation and become part of a general method for engineering scaled production. We have developed a combined screening and selection approach that quickly refines the affinities and specificities of generalist transcription factors; using RamR as a starting point, we evolve highly specific (>100-fold preference) and sensitive (half-maximum effective concentration (EC 50 ) < 30 μM) biosensors for the alkaloids tetrahydropapaverine, papaverine, glaucine, rotundine and noscapine. High-resolution structures reveal multiple evolutionary avenues for the malleable effector-binding site and the creation of new pockets for different chemical moieties. These sensors further enabled the evolution of a streamlined pathway for tetrahydropapaverine, a precursor to four modern pharmaceuticals, collapsing multiple methylation steps into a single evolved enzyme. Our methods for evolving biosensors enable the rapid engineering of pathways for therapeutic alkaloids., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Prokaryotic transcription factors can be repurposed as analytical and synthetic tools for precise chemical measurement and regulation. Monoterpenes encompass a broad chemical family that are commercially valuable as flavors, cosmetics, and fragrances, but have proven difficult to measure, especially in cells. Herein, we develop genetically encoded, generalist monoterpene biosensors by using directed evolution to expand the effector specificity of the camphor-responsive TetR-family regulator CamR from Pseudomonas putida . Using a novel negative selection coupled with a high-throughput positive screen (Seamless Enrichment of Ligand-Inducible Sensors, SELIS), we evolve CamR biosensors that can recognize four distinct monoterpenes: borneol, fenchol, eucalyptol, and camphene. Different evolutionary trajectories surprisingly yielded common mutations, emphasizing the utility of CamR as a platform for creating generalist biosensors. Systematic promoter optimization driving the reporter increased the system's signal-to-noise ratio to 150-fold. These sensors can serve as a starting point for the high-throughput screening and dynamic regulation of bicyclic monoterpene production strains.

Enzymes are represented across a vast space of protein sequences and structural forms and have activities that far exceed the best chemical catalysts; however, engineering them to have novel or enhanced activity is limited by technologies for sensing product formation. Here, we describe a general and scalable approach for characterizing enzyme activity that uses the metabolism of the host cell as a biosensor by which to infer product formation. Since different products consume different molecules in their synthesis, they perturb host metabolism in unique ways that can be measured by mass spectrometry. This provides a general way by which to sense product formation, to discover unexpected products and map the effects of mutagenesis., (© 2021. The Author(s).)

Genetically encoded biosensors are extensively utilized in synthetic biology and metabolic engineering. However, reported xylose biosensors are far too sensitive with a limited operating range to be useful for most sensing applications. In this study, we describe directed evolution of Escherichia coli XylR, and construction of biosensors based on XylR and the corresponding operator xylO . The operating range of biosensors containing the mutant XylR was increased by nearly 10-fold comparing with the control. Two individual amino acid mutations (either L73P or N220T) in XylR were sufficient to extend the linear response range to upward of 10 g/L xylose. The evolved biosensors described here are well suited for developing whole-cell biosensors for detecting varying xylose concentrations across an expanded range. As an alternative use of this system, we also demonstrate the utility of XylR and xylO as a xylose inducible system to enable graded gene expression through testing with β-galactosidase gene and the lycopene synthetic pathway. This evolution strategy identified a less-sensitive biosensor for real applications, thus providing new insights into strategies for expanding operating ranges of other biosensors for synthetic biology applications.

Muconic acid is a valuable platform chemical with potential applications in the production of polymers such as nylon and polyethylene terephthalate (PET). The conjugate base, muconate, has been previously biosynthesized in the bacterial host Escherichia coli. Likewise, previous significant pathway engineering lead to the first reported instance of rationally engineered production of muconic acid in the yeast Saccharomyces cerevisiae. To further increase muconic acid production in this host, a combined adaptive laboratory evolution (ALE) strategy and rational metabolic engineering is employed. To this end, a biosensor module that responds to the endogenous aromatic amino acid (AAA) as a surrogate for pathway flux is adapted. Following two rounds of ALE coupled with an anti-metabolite feeding strategy, the strains with improved AAA pathway flux is isolated. Next, it is demonstrated that this increased flux can be redirected into the composite muconic acid pathway with a threefold increase in the total titer of the composite pathway compared to our previously engineered strain. Finally, a truncation of the penta-functional ARO1 protein is complemented and overexpress an endogenous aromatic decarboxylase to establish a final strain capable of producing 0.5 g L -1 muconic acid in shake flasks and 2.1 g L -1 in a fed-batch bioreactor with a yield of 12.9 mg muconic acid/g glucose at the rate of 9.0 mg h -1 . This value represents the highest titer of muconic acid reported to date in S. cerevisiae, in addition to the highest reported titer of a shikimate pathway derivative in this host., (© 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)