Maltose Utilization as a Novel Selection Strategy for Continuous Evolution of Microbes with Enhanced Metabolite Production

Programming Nutrient Detection with Modular Regulators for Dynamic Control of Microbial Biosynthesis

Dynamic control of biosynthetic pathways improves the bioproduction efficiency. One common approach is to use genetic sensors that control pathway expression in response to a nutrient molecule in the target feedstock. However, programming the cellular response requires the engineering of numerous genetic parts, which poses a significant barrier to explore the use of different nutrients as cellular signals. Here we created a dynamic control platform based on a set of modular transcriptional regulators; these regulators control the same promoter for driving gene expression, but each of them responds to a unique signal. We demonstrated that by replacing only the regulator, a different nutrient molecule can then be used for induction of the same genetic circuit. To show host versatility, we implemented this platform in both Escherichia coli and Pseudomonas putida. This platform was then used to program the induction of ethanol production by three nutrients, fructose, cellobiose, and galactose, of which each molecule can be present in a different set of crops. These results suggest that our platform facilitates the use of different agricultural products for the dynamic control of biosynthesis.

Engineering microbial metabolic homeostasis for chemicals production

Microbial-based bio-refining promotes the development of a biotechnology revolution to encounter and tackle the enormous challenges in petroleum-based chemical production by biomanufacturing, biocomputing, and biosensing. Nevertheless, microbial metabolic homeostasis is often incompatible with the efficient synthesis of bioproducts mainly due to: inefficient metabolic flow, robust central metabolism, sophisticated metabolic network, and inevitable environmental perturbation. Therefore, this review systematically summarizes how to optimize microbial metabolic homeostasis by strengthening metabolic flux for improving biotransformation turnover, redirecting metabolic direction for rewiring bypass pathway, and reprogramming metabolic network for boosting substrate utilization. Future directions are also proposed for providing constructive guidance on the development of industrial biotechnology.

Directed evolution of highly sensitive and stringent choline-induced gene expression controllers

Gene expression controllers are useful tools for microbial production of recombinant proteins and valued bio-based chemicals. Despite its usefulness, they have rarely been applied to the practical industrial bioprocess, due to the lack of systems that meets the three requirements: low cost, safety, and tight control, to the inducer molecules. Previously, we have developed the high-spec gene induction system controlled by safe and cheap inducer choline. However, the system requires relatively high concentration (~100 mM) of choline to fully induce the gene under control. In this work, we attempted to drastically improve the sensitivity of this induction system to further reduce the induction costs. To this end, we devised a simple circuit which couples gene induction system with positive-feedback loop (P-loop) of choline importer protein BetT. After the tuning of translation level of BetT (strength of the P-loop) and deletion of endogenous betI (noise sources), highly active yet stringent control of gene expression was achieved using about 100 times less amount of inducer molecules. The choline induction system developed in this study has the lowest basal expression, the lowest choline needed to be activated, and the highest amplitude of induction as the highest available promoter such as those known as PT5 system. With this system, one can tightly control the expression level of genes of interest with negligible cost for inducer molecule, which has been the bottleneck for the application to the large-scale industrial processes.

Relieving metabolic burden to improve robustness and bioproduction by industrial microorganisms

Metabolic burden is defined by the influence of genetic manipulation and environmental perturbations on the distribution of cellular resources. The rewiring of microbial metabolism for bio-based chemical production often leads to a metabolic burden, followed by adverse physiological effects, such as impaired cell growth and low product yields. Alleviating the burden imposed by undesirable metabolic changes has become an increasingly attractive approach for constructing robust microbial cell factories. In this review, we provide a brief overview of metabolic burden engineering, focusing specifically on recent developments and strategies for diminishing the burden while improving robustness and yield. A variety of examples are presented to showcase the promise of metabolic burden engineering in facilitating the design and construction of robust microbial cell factories. Finally, challenges and limitations encountered in metabolic burden engineering are discussed.

Biosensor-Assisted Engineering for Diverse Microbial Cellular Physiologies

Recent advancements in biosensor technology have revolutionized the field of microbial engineering, enabling efficient and precise optimization of strains for the production of valuable chemicals. This review comprehensively explores the innovative integration of biosensors to enhance microbial cell factories, with a particular emphasis on the crucial role of high-throughput biosensor-assisted screening. Biosensor-assisted approaches have enabled the identification of novel transporters, the elucidation of underlying transport mechanisms, and the fine-tuning of metabolic pathways for enhanced production. Furthermore, this review illustrates the utilization of biosensors for manipulating cellular behaviors, including interactions with environmental factors, and the reduction of nongenetic cell-to-cell variations. This review highlights the indispensable role of biosensors in advancing the field of microbial engineering through the modulation and exploitation of diverse cellular physiological processes.

Base editor-mediated large-scale screening of functional mutations in bacteria for industrial phenotypes

Base editing, the targeted introduction of point mutations into cellular DNA, holds promise for improving genome-scale functional genome screening to single-nucleotide resolution. Current efforts in prokaryotes, however, remain confined to loss-of-function screens using the premature stop codons-mediated gene inactivation library, which falls far short of fully releasing the potential of base editors. Here, we developed a base editor-mediated functional single nucleotide variant screening pipeline in Escherichia coli. We constructed a library with 31,123 sgRNAs targeting 462 stress response-related genes in E. coli, and screened for adaptive mutations under isobutanol and furfural selective conditions. Guided by the screening results, we successfully identified several known and novel functional mutations. Our pipeline might be expanded to the optimization of other phenotypes or the strain engineering in other microorganisms.

Advances in Synthetic-Biology-Based Whole-Cell Biosensors: Principles, Genetic Modules, and Applications in Food Safety

A whole-cell biosensor based on synthetic biology provides a promising new method for the on-site detection of food contaminants. The basic components of whole-cell biosensors include the sensing elements, such as transcription factors and riboswitches, and reporting elements, such as fluorescence, gas, etc. The sensing and reporting elements are coupled through gene expression regulation to form a simple gene circuit for the detection of target substances. Additionally, a more complex gene circuit can involve other functional elements or modules such as signal amplification, multiple detection, and delay reporting. With the help of synthetic biology, whole-cell biosensors are becoming more versatile and integrated, that is, integrating pre-detection sample processing, detection processes, and post-detection signal calculation and storage processes into cells. Due to the relative stability of the intracellular environment, whole-cell biosensors are highly resistant to interference without the need of complex sample preprocessing. Due to the reproduction of chassis cells, whole-cell biosensors replicate all elements automatically without the need for purification processing. Therefore, whole-cell biosensors are easy to operate and simple to produce. Based on the above advantages, whole-cell biosensors are more suitable for on-site detection than other rapid detection methods. Whole-cell biosensors have been applied in various forms such as test strips and kits, with the latest reported forms being wearable devices such as masks, hand rings, and clothing. This paper examines the composition, construction methods, and types of the fundamental components of synthetic biological whole-cell biosensors. We also introduce the prospect and development trend of whole-cell biosensors in commercial applications.

An operator-based expression toolkit for Bacillus subtilis enables fine-tuning of gene expression and biosynthetic pathway regulation

A gene regulatory system is an important tool for the engineering of biosynthetic pathways of organisms. Here, we report the development of an inducible-ON/OFF regulatory system using a malO operator as a key element. We identified and modulated sequence, position, numbers, and spacing distance of malO operators, generating a series of activating or repressive promoters with tunable strength. The stringency and robustness are both guaranteed in this system, a maximal induction factor of 790-fold was achieved, and nine proteins from different organisms were expressed with high yields. This system can be utilized as a gene switch, promoter enhancer, or metabolic valve in synthetic biology applications. This operator-based engineering strategy can be employed for developing similar regulatory systems in different microorganisms.

Genetic elements are key components of metabolic engineering and synthetic biological applications, allowing the development of organisms as biosensors and for manufacturing valuable chemicals and protein products. In contrast to the gram-negative model bacterium Escherichia coli, the gram-positive model bacterium Bacillus subtilis lacks such elements with precise and flexible characteristics, which is a great barrier to employing B. subtilis for laboratory studies and industrial applications. Here, we report the development of a malO-based genetic toolbox that is derived from the operator box in the malA promoter, enabling gene regulation via compatible “ON” and “OFF” switches. This engineered toolbox combines promoter-based mutagenesis and host-specific metabolic engineering of transactivation components upon maltose induction to achieve stringent, robust, and homogeneous gene regulation in B. subtilis. We further demonstrate the synthetic biological applications of the toolbox by utilizing these genetic elements as a gene switch, a promoter enhancer, and an ON-OFF dual-control device in biosynthetic pathway optimization. Collectively, this regulatory system provides a comprehensive genetic toolbox for controlling the expression of genes in biosynthetic pathways and regulatory networks to optimize the production of valuable chemicals and proteins in B. subtilis.

Effective use of biosensors for high-throughput library screening for metabolite production

The development of fast and affordable microbial production from recombinant pathways is a challenging endeavor, with targeted improvements difficult to predict due to the complex nature of living systems. To address the limitations in biosynthetic pathways, much work has been done to generate large libraries of various genetic parts (promoters, RBSs, enzymes, etc.) to discover library members that bring about significantly improved levels of metabolite production. To evaluate these large libraries, high throughput approaches are necessary, such as those that rely on biosensors. There are various modes of operation to apply biosensors to library screens that are available at different scales of throughput. The effectiveness of each biosensor-based method is dependent on the pathway or strain to which it is applied, and all approaches have strengths and weaknesses to be carefully considered for any high throughput library screen. In this review, we discuss the various approaches used in biosensor screening for improved metabolite production, focusing on transcription factor-based biosensors.

Biosensor-based growth-coupling and spatial separation as an evolution strategy to improve small molecule production of Corynebacterium glutamicum

Evolutionary engineering is a powerful method to improve the performance of microbial cell factories, but can typically not be applied to enhance the production of chemicals due to the lack of an appropriate selection regime. We report here on a new strategy based on transcription factor-based biosensors, which directly couple production to growth. The growth of Corynebacterium glutamicum was coupled to the intracellular concentration of branched-chain amino acids, by integrating a synthetic circuit based on the Lrp biosensor upstream of two growth-regulating genes, pfkA and hisD. Modelling and experimental data highlight spatial separation as key strategy to limit the selection of 'cheater' strains that escaped the evolutionary pressure. This approach facilitated the isolation of strains featuring specific causal mutations enhancing amino acid production. We envision that this strategy can be applied with the plethora of known biosensors in various microbes, unlocking evolution as a feasible strategy to improve production of chemicals.

Modular tuning engineering and versatile applications of genetically encoded biosensors

Genetically encoded biosensors have a diverse range of detectable signals and potential applications in many fields, including metabolism control and high-throughput screening. Their ability to be used in situ with minimal interference to the bioprocess of interest could revolutionize synthetic biology and microbial cell factories. The performance and functions of these biosensors have been extensively studied and have been rapidly improved. We review here current biosensor tuning strategies and attempt to unravel how to obtain ideal biosensor functions through experimental adjustments. Strategies for expanding the biosensor input signals that increases the number of detectable compounds have also been summarized. Finally, different output signals and their practical requirements for biotechnology and biomedical applications and environmental safety concerns have been analyzed. This in-depth review of the responses and regulation mechanisms of genetically encoded biosensors will assist to improve their design and optimization in various application scenarios.

Synthetic biosensor accelerates evolution by rewiring carbon metabolism toward a specific metabolite

Proper carbon flux distribution between cell growth and production of a target compound is important for biochemical production because improper flux reallocation inhibits cell growth, thus adversely affecting production yield. Here, using a synthetic biosensor to couple production of a specific metabolite with cell growth, we spontaneously evolve cells under the selective condition toward the acquisition of genotypes that optimally reallocate cellular resources. Using 3-hydroxypropionic acid (3-HP) production from glycerol in Escherichia coli as a model system, we determine that mutations in the conserved regions of proteins involved in global transcriptional regulation alter the expression of several genes associated with central carbon metabolism. These changes rewire central carbon flux toward the 3-HP production pathway, increasing 3-HP yield and reducing acetate accumulation by alleviating overflow metabolism. Our study provides a perspective on adaptive laboratory evolution (ALE) using synthetic biosensors, thereby supporting future efforts in metabolic pathway optimization.

Biosensor-Assisted Adaptive Laboratory Evolution for Violacein Production

Violacein is a naturally occurring purple pigment, widely used in cosmetics and has potent antibacterial and antiviral properties. Violacein can be produced from tryptophan, consequently sufficient tryptophan biosynthesis is the key to violacein production. However, the complicated biosynthetic pathways and regulatory mechanisms often make the tryptophan overproduction challenging in Escherichia coli. In this study, we used the adaptive laboratory evolution (ALE) strategy to improve violacein production using galactose as a carbon source. During the ALE, a tryptophan-responsive biosensor was employed to provide selection pressure to enrich tryptophan-producing cells. From the biosensor-assisted ALE, we obtained an evolved population of cells capable of effectively catabolizing galactose to tryptophan and subsequently used the population to obtain the best violacein producer. In addition, whole-genome sequencing of the evolved strain identified point mutations beneficial to the overproduction. Overall, we demonstrated that the biosensor-assisted ALE strategy could be used to rapidly and selectively evolve the producers to yield high violacein production.

The Tryptophan-Induced tnaC Ribosome Stalling Sequence Exposes High Amino Acid Cross-Talk That Can Be Mitigated by Removal of NusB for Higher Orthogonality

A growing number of engineered synthetic circuits have employed biological parts coupling transcription and translation in bacterial systems to control downstream gene expression. One such example, the leader sequence of the tryptophanase (tna) operon, is a transcription-translation system commonly employed as an l-tryptophan inducible circuit controlled by ribosome stalling. While induction of the tna operon has been well-characterized in response to l-tryptophan, cross-talk of this modular component with other metabolites in the cell, such as other naturally occurring amino acids, has been less explored. In this study, we investigated the impact of natural metabolites and E. coli host factors on induction of the tna leader sequence. To do so, we constructed and biochemically validated an experimental assay using the tna operon leader sequence to assess differential regulation of transcription elongation and translation in response to l-tryptophan. Operon induction was then assessed following addition of each of the 20 naturally occurring amino acids to discover that several additional amino acids (e.g., l-alanine, l-cysteine, l-glycine, l-methionine, and l-threonine) also induce expression of the tna leader sequence. Following characterization of dose-dependent induction by l-cysteine relative to l-tryptophan, the effect on induction by single gene knockouts of protein factors associated with transcription and/or translation were interrogated. Our results implicate the endogenous cellular protein, NusB, as an important factor associated with induction of the operon by the alternative amino acids. As such, removal of the nusB gene from strains intended for tryptophan-sensing utilizing the tna leader region reduces amino acid cross-talk, resulting in enhanced orthogonal control of this commonly used synthetic system.

Transcription-Factor-based Biosensor Engineering for Applications in Synthetic Biology

Transcription-factor-based biosensors (TFBs) are often used for metabolite detection, adaptive evolution, and metabolic flux control. However, designing TFBs with superior performance for applications in synthetic biology remains challenging. Specifically, natural TFBs often do not meet real-time detection requirements owing to their slow response times and inappropriate dynamic ranges, detection ranges, sensitivity, and selectivity. Furthermore, designing and optimizing complex dynamic regulation networks is time-consuming and labor-intensive. This Review highlights TFB-based applications and recent engineering strategies ranging from traditional trial-and-error approaches to novel computer-model-based rational design approaches. The limitations of the applications and these engineering strategies are additionally reviewed.

Advanced strategies and tools to facilitate and streamline microbial adaptive laboratory evolution

Adaptive laboratory evolution (ALE) has served as a historic microbial engineering method that mimics natural selection to obtain desired microbes. The past decade has witnessed improvements in all aspects of ALE workflow, in terms of growth coupling, genotypic diversification, phenotypic selection, and genotype-phenotype mapping. The developing growth-coupling strategies facilitate ALE to a wider range of appealing traits. In vivo mutagenesis methods and multiplexed automated culture platforms open new gates to streamline its execution. Meanwhile, the application of multi-omics analyses and multiplexed genetic engineering promote efficient knowledge mining. This article provides a comprehensive and updated review of these advances, highlights newest significant applications, and discusses future improvements, aiming to provide a practical guide for implementation of novel, effective, and efficient ALE experiments.

Dynamic control in metabolic engineering: Theories, tools, and applications

Metabolic engineering has allowed the production of a diverse number of valuable chemicals using microbial organisms. Many biological challenges for improving bio-production exist which limit performance and slow the commercialization of metabolically engineered systems. Dynamic metabolic engineering is a rapidly developing field that seeks to address these challenges through the design of genetically encoded metabolic control systems which allow cells to autonomously adjust their flux in response to their external and internal metabolic state. This review first discusses theoretical works which provide mechanistic insights and design choices for dynamic control systems including two-stage, continuous, and population behavior control strategies. Next, we summarize molecular mechanisms for various sensors and actuators which enable dynamic metabolic control in microbial systems. Finally, important applications of dynamic control to the production of several metabolite products are highlighted, including fatty acids, aromatics, and terpene compounds. Altogether, this review provides a comprehensive overview of the progress, advances, and prospects in the design of dynamic control systems for improved titer, rate, and yield metrics in metabolic engineering.

Enhancing n-Butanol Tolerance of Escherichia coli by Overexpressing of Stress-Responsive Molecular Chaperones

Microbial tolerance to organic solvents is critical for efficient production of biofuels. In this study, n-butanol tolerance of Escherichia coli JM109 was improved by overexpressing of genes encoding stress-responsive small RNA-regulator, RNA chaperone, and molecular chaperone. Gene rpoS, coding for sigma S subunit of RNA polymerase, was the most efficient in improving n-butanol tolerance of E. coli. The highest OD₆₀₀ and the specific growth rate of JM109/pQE80L-rpoS reached 1.692 and 0.144 h^-1 respectively at 1.0% (v/v) n-butanol. Double and triple expression of molecular chaperones rpoS, secB, and groS were conducted and optimized. Recombinant strains JM109/pQE80L-secB-rpoS and JM109/pQE80L-groS-secB-rpoS exhibited the highest n-butanol tolerance, with specific growth rates of 0.164 and 0.165 h^-1, respectively. Membrane integrity, potentials, and cell morphology analyses demonstrated the high viability of JM109/pQE80L-groS-secB-rpoS. This study provides guidance on employing various molecular chaperones for enhancing the tolerance of E. coli against n-butanol.

Unlocking nature's biosynthetic potential by directed genome evolution

Microorganisms have been increasingly explored as microbial cell factories for production of fuels, chemicals, drugs, and materials. Among the various metabolic engineering strategies, directed genome evolution has emerged as one of the most powerful tools to unlock the full biosynthetic potential of microorganisms. Here we summarize the directed genome evolution strategies that have been developed in recent years, including adaptive laboratory evolution and various targeted genome-scale engineering strategies, and discuss their applications in basic and applied biological research.

Developing E. coli-E. coli co-cultures to overcome barriers of heterologous tryptamine biosynthesis

Tryptamine is an alkaloid compound with demonstrated bioactivities and is also a precursor molecule to many important hormones and neurotransmitters. The high efficiency biosynthesis of tryptamine from inexpensive and renewable carbon substrates is of great research and application significance. In the present study, a tryptamine biosynthesis pathway was established in a metabolically engineered E. coli-E. coli co-culture. The upstream and downstream strains of the co-culture were dedicated to tryptophan provision and conversion to tryptamine, respectively. The constructed co-culture was cultivated using either glucose or glycerol as carbon source for de novo production of tryptamine. The manipulation of the co-culture strains' inoculation ratio was adapted to balance the biosynthetic strengths of the pathway modules for bioproduction optimization. Moreover, a biosensor-assisted cell selection strategy was adapted to improve the pathway intermediate tryptophan provision by the upstream strain, which further enhanced the tryptamine biosynthesis. The resulting biosensor-assisted modular co-culture produced 194 ​mg/L tryptamine with a yield of 0.02 ​g/g glucose using shake flask cultivation. The findings of this work demonstrate that the biosensor-assisted modular co-culture engineering offers a new perspective for conducting microbial biosynthesis.

Transcription Factor Engineering for High-Throughput Strain Evolution and Organic Acid Bioproduction: A Review

Metabolic regulation of gene expression for the microbial production of fine chemicals, such as organic acids, is an important research topic in post-genomic metabolic engineering. In particular, the ability of transcription factors (TFs) to respond precisely in time and space to various small molecules, signals and stimuli from the internal and external environment is essential for metabolic pathway engineering and strain development. As a key component, TFs are used to construct many biosensors in vivo using synthetic biology methods, which can be used to monitor the concentration of intracellular metabolites in organic acid production that would otherwise remain “invisible” within the intracellular environment. TF-based biosensors also provide a high-throughput screening method for rapid strain evolution. Furthermore, TFs are important global regulators that control the expression levels of key enzymes in organic acid biosynthesis pathways, therefore determining the outcome of metabolic networks. Here we review recent advances in TF identification, engineering, and applications for metabolic engineering, with an emphasis on metabolite monitoring and high-throughput strain evolution for the organic acid bioproduction.

Biosensor-based enzyme engineering approach applied to psicose biosynthesis

Bioproduction of chemical compounds is of great interest for modern industries, as it reduces their production costs and ecological impact. With the use of synthetic biology, metabolic engineering and enzyme engineering tools, the yield of production can be improved to reach mass production and cost-effectiveness expectations. In this study, we explore the bioproduction of D-psicose, also known as D-allulose, a rare non-toxic sugar and a sweetener present in nature in low amounts. D-psicose has interesting properties and seemingly the ability to fight against obesity and type 2 diabetes. We developed a biosensor-based enzyme screening approach as a tool for enzyme selection that we benchmarked with the Clostridium cellulolyticum D-psicose 3-epimerase for the production of D-psicose from D-fructose. For this purpose, we constructed and characterized seven psicose responsive biosensors based on previously uncharacterized transcription factors and either their predicted promoters or an engineered promoter. In order to standardize our system, we created the Universal Biosensor Chassis, a construct with a highly modular architecture that allows rapid engineering of any transcription factor-based biosensor. Among the seven biosensors, we chose the one displaying the most linear behavior and the highest increase in fluorescence fold change. Next, we generated a library of D-psicose 3-epimerase mutants by error-prone PCR and screened it using the biosensor to select gain of function enzyme mutants, thus demonstrating the framework's efficiency.

In vivo continuous evolution of metabolic pathways for chemical production

Microorganisms have long been used as chemical plant to convert simple substrates into complex molecules. Various metabolic pathways have been optimised over the past few decades, but the progresses were limited due to our finite knowledge on metabolism. Evolution is a knowledge-free genetic randomisation approach, employed to improve the chemical production in microbial cell factories. However, evolution of large, complex pathway was a great challenge. The invention of continuous culturing systems and in vivo genetic diversification technologies have changed the way how laboratory evolution is conducted, render optimisation of large, complex pathway possible. In vivo genetic diversification, phenotypic selection, and continuous cultivation are the key elements in in vivo continuous evolution, where any human intervention in the process is prohibited. This approach is crucial in highly efficient evolution strategy of metabolic pathway evolution.

Establishment of BmoR-based biosensor to screen isobutanol overproducer

Background

Isobutanol, a C4 branched-chain higher alcohol, is regarded as an attractive next-generation transport fuel. Metabolic engineering for efficient isobutanol production has been achieved in many studies. BmoR, an alcohol-regulated transcription factor, mediates a σ⁵⁴-dependent promoter P_bmo of alkane monooxygenase in n-alkane metabolism of Thauera butanivorans and displays high sensitivity to C4–C6 linear alcohols and C3–C5 branched-chain alcohols. In this study, to achieve the high-level production of isobutanol, we established a screening system which relied on the combination of BmoR-based biosensor and isobutanol biosynthetic pathway and then employed it to screen isobutanol overproduction strains from an ARTP mutagenesis library.

Results

Firstly, we constructed and verified a GFP-based BmoR-P_bmo device responding to the isobutanol produced by the host. Then, this screening system was employed to select three mutants which exhibited higher GFP/OD₆₀₀ values than that of wild type. Significantly, GFP/OD₆₀₀ of mutant 10 was 190.7 ± 4.8, a 1.4-fold higher value than that of wild type. Correspondingly, the isobutanol titer of that strain was 1597.6 ± 129.6 mg/L, 2.0-fold higher than the wild type. With the overexpression of upstream pathway genes, the isobutanol production from mutant 10 reached 14.0 ± 1.0 g/L after medium optimization in shake flask. The isobutanol titer reached 56.5 ± 1.8 g/L in a fed-batch production experiment.

Conclusions

This work screened out isobutanol overproduction strains from a mutagenesis library by using a screening system which depended on the combination of BmoR-based biosensor and isobutanol biosynthetic pathway. Optimizing fermentation condition and reinforcing upstream pathway could realize the increase of isobutanol production from the overproducer. Lastly, fed-batch fermentation of the mutant enhanced the isobutanol production to 56.5 ± 1.8 g/L.

In vivo biosensors: mechanisms, development, and applications

In vivo biosensors can recognize and respond to specific cellular stimuli. In recent years, biosensors have been increasingly used in metabolic engineering and synthetic biology, because they can be implemented in synthetic circuits to control the expression of reporter genes in response to specific cellular stimuli, such as a certain metabolite or a change in pH. There are many types of natural sensing devices, which can be generally divided into two main categories: protein-based and nucleic acid-based. Both can be obtained either by directly mining from natural genetic components or by engineering the existing genetic components for novel specificity or improved characteristics. A wide range of new technologies have enabled rapid engineering and discovery of new biosensors, which are paving the way for a new era of biotechnological progress. Here, we review recent advances in the design, optimization, and applications of in vivo biosensors in the field of metabolic engineering and synthetic biology.

Pooled CRISPR interference screening enables genome-scale functional genomics study in bacteria with superior performance

To fully exploit the microbial genome resources, a high-throughput experimental platform is needed to associate genes with phenotypes at the genome level. We present here a novel method that enables investigation of the cellular consequences of repressing individual transcripts based on the CRISPR interference (CRISPRi) pooled screening in bacteria. We identify rules for guide RNA library design to handle the unique structure of prokaryotic genomes by tiling screening and construct an E. coli genome-scale guide RNA library (~60,000 members) accordingly. We show that CRISPRi outperforms transposon sequencing, the benchmark method in the microbial functional genomics field, when similar library sizes are used or gene length is short. This tool is also effective for mapping phenotypes to non-coding RNAs (ncRNAs), as elucidated by a comprehensive tRNA-fitness map constructed here. Our results establish CRISPRi pooled screening as a powerful tool for mapping complex prokaryotic genetic networks in a precise and high-throughput manner.