Design, Evolution, and Characterization of a Xylose Biosensor in Escherichia coli Using the XylR/xylO System with an Expanded Operating Range

Engineering the next-generation synthetic cell factory driven by protein engineering

Synthetic cell factory offers substantial advantages in economically efficient production of biofuels, chemicals, and pharmaceutical compounds. However, to create a high-performance synthetic cell factory, precise regulation of cellular material and energy flux is essential. In this context, protein components including enzymes, transcription factor-based biosensors and transporters play pivotal roles. Protein engineering aims to create novel protein variants with desired properties by modifying or designing protein sequences. This review focuses on summarizing the latest advancements of protein engineering in optimizing various aspects of synthetic cell factory, including: enhancing enzyme activity to eliminate production bottlenecks, altering enzyme selectivity to steer metabolic pathways towards desired products, modifying enzyme promiscuity to explore innovative routes, and improving the efficiency of transporters. Furthermore, the utilization of protein engineering to modify protein-based biosensors accelerates evolutionary process and optimizes the regulation of metabolic pathways. The remaining challenges and future opportunities in this field are also discussed.

State-of-the-art in engineering small molecule biosensors and their applications in metabolic engineering

Genetically encoded biosensors are crucial for enhancing our understanding of how molecules regulate biological systems. Small molecule biosensors, in particular, help us understand the interaction between chemicals and biological processes. They also accelerate metabolic engineering by increasing screening throughput and eliminating the need for sample preparation through traditional chemical analysis. Additionally, they offer significantly higher spatial and temporal resolution in cellular analyte measurements. In this review, we discuss recent progress in in vivo biosensors and control systems-biosensor-based controllers-for metabolic engineering. We also specifically explore protein-based biosensors that utilize less commonly exploited signaling mechanisms, such as protein stability and induced degradation, compared to more prevalent transcription factor and allosteric regulation mechanism. We propose that these lesser-used mechanisms will be significant for engineering eukaryotic systems and slower-growing prokaryotic systems where protein turnover may facilitate more rapid and reliable measurement and regulation of the current cellular state. Lastly, we emphasize the utilization of cutting-edge and state-of-the-art techniques in the development of protein-based biosensors, achieved through rational design, directed evolution, and collaborative approaches.

Growth-coupled high throughput selection for directed enzyme evolution

Directed enzyme evolution has revolutionized the rapid development of enzymes with desired properties. However, the lack of a high-throughput method to identify the most suitable variants from a large pool of genetic diversity poses a major bottleneck. To overcome this challenge, growth-coupled in vivo high-throughput selection approaches (GCHTS) have emerged as a novel selection system for enzyme evolution. GCHTS links the survival of the host cell with the properties of the target protein, resulting in a screening system that is easily measurable and has a high throughput-scale limited only by transformation efficiency. This allows for the rapid identification of desired variants from a pool of >109 variants in each experiment. In recent years, GCHTS approaches have been extensively utilized in the directed evolution of multiple enzymes, demonstrating success in catalyzing non-native substrates, enhancing catalytic activity, and acquiring novel functions. This review introduces three main strategies employed to achieve GCHTS: the elimination of toxic compounds via desired variants, enabling host cells to thrive in hazardous conditions; the complementation of an auxotroph with desired variants, where essential genes for cell growth have been eliminated; and the control of the transcription or expression of a reporter gene related to host cell growth, regulated by the desired variants. Additionally, we highlighted the recent developments in the in vivo continuous evolution of enzyme technology, including phage-assisted continuous evolution (PACE) and orthogonal DNA Replication (OrthoRep). Furthermore, this review discusses the challenges and future prospects in the field of growth-coupled selection for protein engineering.

Prebiotics-Controlled Disposable Engineered Bacteria for Intestinal Diseases

As a new method of diagnosis and treatment for intestinal diseases, intelligent engineered bacteria based on synthetic biology have been developed vigorously in recent years. However, how to deal with the engineered bacteria in vivo after completing the tasks is an urgent problem to be resolved. In this study, we constructed a thiosulfate (a biomarker of inflammatory bowel disease)-responsive engineered bacteria to generate two signals, sfGFP (monitoring) and gain-of-function (translation activation) mutation (ACG to ATG), in the initiation codon of lysisE (recording) via the CRISPR/Cas9-mediated base editing system. Once these two signals were detected, xylose could be added to induce lysis E expression, resulting in the destruction of the edited bacteria and the release of AvCystain simultaneously. Overall, our innovative engineered bacteria can record instant and historical information of the disease, and especially, the edited bacteria can be artificially attenuated and release drug in situ when needed, ultimately serving as a disposable and recyclable candidate for more types of diseases.

Enzyme directed evolution using genetically encodable biosensors

Directed evolution has been remarkably successful in identifying enzyme variants with new or improved properties, such as altered substrate scope or novel reactivity. Genetically encodable biosensors (GEBs), which convert the concentration of a small molecule ligand into an easily detectable output signal, have seen increasing application to enzyme directed evolution in the last decade. GEBs enable the use of high-throughput methods to assess enzyme activity of very large libraries, which can accelerate the search for variants with desirable activity. Here, we review different classes of GEBs and their properties in the context of enzyme evolution, how GEBs have been integrated into directed evolution workflows, and recent examples of enzyme evolution efforts utilizing GEBs. Finally, we discuss the advantages, challenges, and opportunities for using GEBs in the directed evolution of enzymes.

Advances in engineering and optimization of transcription factor-based biosensors for plug-and-play small molecule detection

Transcription factor (TF)-based biosensors have been applied in biotechnology for a variety of functions, including protein engineering, dynamic control, environmental detection, and point-of-care diagnostics. Such biosensors are promising analytical tools due to their wide range of detectable ligands and modular nature. However, designing biosensors tailored for applications of interest with the desired performance parameters, including ligand specificity, remains challenging. Biosensors often require significant engineering and tuning to meet desired specificity, sensitivity, dynamic range, and operating range parameters. Another limitation is the orthogonality of biosensors across hosts, given the role of the cellular context. Here, we describe recent advances and examples in the engineering and optimization of TF-based biosensors for plug-and-play small molecule detection. We highlight novel developments in TF discovery and biosensor design, TF specificity engineering, and biosensor tuning, with emphasis on emerging computational methods.

Metabolic Engineering and Regulation of Diol Biosynthesis from Renewable Biomass in Escherichia coli

As bulk chemicals, diols have wide applications in many fields, such as clothing, biofuels, food, surfactant and cosmetics. The traditional chemical synthesis of diols consumes numerous non-renewable energy resources and leads to environmental pollution. Green biosynthesis has emerged as an alternative method to produce diols. Escherichia coli as an ideal microbial factory has been engineered to biosynthesize diols from carbon sources. Here, we comprehensively summarized the biosynthetic pathways of diols from renewable biomass in E. coli and discussed the metabolic-engineering strategies that could enhance the production of diols, including the optimization of biosynthetic pathways, improvement of cofactor supplementation, and reprogramming of the metabolic network. We then investigated the dynamic regulation by multiple control modules to balance the growth and production, so as to direct carbon sources for diol production. Finally, we proposed the challenges in the diol-biosynthesis process and suggested some potential methods to improve the diol-producing ability of the host.

Engineering of Synthetic Transcriptional Switches in Yeast

Transcriptional switches can be utilized for many purposes in synthetic biology, including the assembly of complex genetic circuits to achieve sophisticated cellular systems and the construction of biosensors for real-time monitoring of intracellular metabolite concentrations. Although to date such switches have mainly been developed in prokaryotes, those for eukaryotes are increasingly being reported as both rational and random engineering technologies mature. In this review, we describe yeast transcriptional switches with different modes of action and how to alter their properties. We also discuss directed evolution technologies for the rapid and robust construction of yeast transcriptional switches.

Reconstructing the transcription regulatory network to optimize resource allocation for robust biosynthesis

An ideal microbial cell factory (MCF) should deliver maximal resources to production, which conflicts with the microbe's native growth-oriented resource allocation strategy and can therefore lead to early termination of the high-yield period. Reallocating resources from growth to production has become a critical factor in constructing robust MCFs. Instead of strengthening specific biosynthetic pathways, emerging endeavors are focused on rearranging the gene regulatory network to fundamentally reprogram the resource allocation pattern. Combining this idea with transcriptional regulation within the hierarchical regulatory network, this review discusses recent engineering strategies targeting the transcription machinery, module networks, regulatory edges, and bottom network layer. This global view will help to construct a production-oriented phenotype that fully harnesses the potential of MCFs.

Measurement of lactose concentration in milk by using engineered bacteria producing lycopene

Lycopene is an orange-red carotenoid, which confers a visual phenotype to assess genetic transformation of microorganisms. In this study, the lycopene synthesis pathway was constructed in engineered Escherichia coli BL21 (DE3) by transforming plasmid pET-15b-crtBEI, wherein crtB, crtE, and crtI could be expressed under the control of T7 promoter and LacO operator gene, and lycopene could be accumulated in the engineered bacteria upon induction of lactose. A good linear relationship was observed between the lycopene content in engineered bacterial culture and lactose concentration in the range of 4-52 g/L; using this relation, the lactose concentration in milk could be determined. This method could be used to overcome several limitations of the high-performance liquid chromatography (HPLC) method for lactose detection, such as cumbersome sample preparation and expensive detection equipment. Moreover, this method required only a clean bench, shaker, and spectrophotometer for lactose analysis. Additionally, no significant difference was observed between this method and HPLC in terms of lactose measurement in milk, indicating that this method is reasonable and simple.

D-Xylose Sensing in Saccharomyces cerevisiae: Insights from D-Glucose Signaling and Native D-Xylose Utilizers

Extension of the substrate range is among one of the metabolic engineering goals for microorganisms used in biotechnological processes because it enables the use of a wide range of raw materials as substrates. One of the most prominent examples is the engineering of baker's yeast Saccharomyces cerevisiae for the utilization of d-xylose, a five-carbon sugar found in high abundance in lignocellulosic biomass and a key substrate to achieve good process economy in chemical production from renewable and non-edible plant feedstocks. Despite many excellent engineering strategies that have allowed recombinant S. cerevisiae to ferment d-xylose to ethanol at high yields, the consumption rate of d-xylose is still significantly lower than that of its preferred sugar d-glucose. In mixed d-glucose/d-xylose cultivations, d-xylose is only utilized after d-glucose depletion, which leads to prolonged process times and added costs. Due to this limitation, the response on d-xylose in the native sugar signaling pathways has emerged as a promising next-level engineering target. Here we review the current status of the knowledge of the response of S. cerevisiae signaling pathways to d-xylose. To do this, we first summarize the response of the native sensing and signaling pathways in S. cerevisiae to d-glucose (the preferred sugar of the yeast). Using the d-glucose case as a point of reference, we then proceed to discuss the known signaling response to d-xylose in S. cerevisiae and current attempts of improving the response by signaling engineering using native targets and synthetic (non-native) regulatory circuits.