Genetic Biosensor Design for Natural Product Biosynthesis in Microorganisms

Advances and perspectives in genetic expression and operation for the oleaginous yeast Yarrowia lipolytica

The utilization of industrial biomanufacturing has emerged as a viable and sustainable alternative to fossil-based resources for producing functional chemicals. Moreover, advancements in synthetic biology have created new opportunities for the development of innovative cell factories. Notably, Yarrowia lipolytica, an oleaginous yeast that is generally regarded as safe, possesses several advantageous characteristics, including the ability to utilize inexpensive renewable carbon sources, well-established genetic backgrounds, and mature genetic manipulation methods. Consequently, there is increasing interest in manipulating the metabolism of this yeast to enhance its potential as a biomanufacturing platform. Here, we reviewed the latest developments in genetic expression strategies and manipulation tools related to Y. lipolytica, particularly focusing on gene expression, chromosomal operation, CRISPR-based tool, and dynamic biosensors. The purpose of this review is to serve as a valuable reference for those interested in the development of a Y. lipolytica microbial factory.

2D Materials in Advanced Electronic Biosensors for Point-of-Care Devices

Since two-dimensionalal (2D) materials have distinct chemical and physical properties, they are widely used in various sectors of modern technologies. In the domain of diagnostic biodevices, particularly for point-of-care (PoC) biomedical diagnostics, 2D-based field-effect transistor biosensors (bio-FETs) demonstrate substantial potential. Here, in this review article, the operational mechanisms and detection capabilities of biosensing devices utilizing graphene, transition metal dichalcogenides (TMDCs), black phosphorus, and other 2D materials are addressed in detail. The incorporation of these materials into FET-based biosensors offers significant advantages, including low detection limits (LOD), real-time monitoring, label-free diagnosis, and exceptional selectivity. The review also highlights the diverse applications of these biosensors, ranging from conventional to wearable devices, underscoring the versatility of 2D material-based FET devices. Additionally, the review provides a comprehensive assessment of the limitations and challenges faced by these devices, along with insights into future prospects and advancements. Notably, a detailed comparison of FET-based biosensors is tabulated along with various other biosensing platforms and their working mechanisms. Ultimately, this review aims to stimulate further research and innovation in this field while educating the scientific community about the latest advancements in 2D materials-based biosensors.

Concentration Recognition-Based Auto-Dynamic Regulation System (CRUISE) Enabling Efficient Production of Higher Alcohols

Microbial factories lacking the ability of dynamically regulating the pathway enzymes overexpression, according to in situ metabolite concentrations, are suboptimal, especially when the metabolic intermediates are competed by growth and chemical production. The production of higher alcohols (HAs), which hijacks the amino acids (AAs) from protein biosynthesis, minimizes the intracellular concentration of AAs and thus inhibits the host growth. To balance the resource allocation and maintain stable AA flux, this work utilizes AA-responsive transcriptional attenuator ivbL and HA-responsive transcriptional activator BmoR to establish a concentration recognition-based auto-dynamic regulation system (CRUISE). This system ultimately maintains the intracellular homeostasis of AA and maximizes the production of HA. It is demonstrated that ivbL-driven enzymes overexpression can dynamically regulate the AA-to-HA conversion while BmoR-driven enzymes overexpression can accelerate the AA biosynthesis during the HA production in a feedback activation mode. The AA flux in biosynthesis and conversion pathways is balanced via the intracellular AA concentration, which is vice versa stabilized by the competition between AA biosynthesis and conversion. The CRUISE, further aided by scaffold-based self-assembly, enables 40.4 g L-1 of isobutanol production in a bioreactor. Taken together, CRUISE realizes robust HA production and sheds new light on the dynamic flux control during the process of chemical production.

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.

Design of a dual-responding genetic circuit for high-throughput identification of L-threonine-overproducing Escherichia coli

L-threonine is a crucial amino acid that is extensively employed in the realms of food, animal feed and pharmaceuticals. Unfortunately, the lack of an appropriate biosensor has hindered the establishment of a robust high-throughput screening (HTS) system for the identification of the desired strains from random mutants. In this study, a dual-responding genetic circuit that capitalizes on the L-threonine inducer-like effect, the L-threonine riboswitch, and a signal amplification system was designed for the purpose of screening L-threonine overproducers. This platform effectively enhanced the performance of the enzyme and facilitated the identification of high L-threonine-producing strains from a random mutant library. Consequently, pathway optimization and directed evolution of the key enzyme enhanced L-threonine production by 4 and 7-fold, respectively. These results demonstrate the potential of biosensor design for dynamic metabolite detection and offer a promising tool for HTS and metabolic regulation for the development of L-threonine-hyperproducing strains.

Generating information-dense promoter sequences with optimal string packing

Dense arrangements of binding sites within nucleotide sequences can collectively influence downstream transcription rates or initiate biomolecular interactions. For example, natural promoter regions can harbor many overlapping transcription factor binding sites that influence the rate of transcription initiation. Despite the prevalence of overlapping binding sites in nature, rapid design of nucleotide sequences with many overlapping sites remains a challenge. Here, we show that this is an NP-hard problem, coined here as the nucleotide String Packing Problem (SPP). We then introduce a computational technique that efficiently assembles sets of DNA-protein binding sites into dense, contiguous stretches of double-stranded DNA. For the efficient design of nucleotide sequences spanning hundreds of base pairs, we reduce the SPP to an Orienteering Problem with integer distances, and then leverage modern integer linear programming solvers. Our method optimally packs libraries of 20-100 binding sites into dense nucleotide arrays of 50-300 base pairs in 0.05-10 seconds. Unlike approximation algorithms or meta-heuristics, our approach finds provably optimal solutions. We demonstrate how our method can generate large sets of diverse sequences suitable for library generation, where the frequency of binding site usage across the returned sequences can be controlled by modulating the objective function. As an example, we then show how adding additional constraints, like the inclusion of sequence elements with fixed positions, allows for the design of bacterial promoters. The nucleotide string packing approach we present can accelerate the design of sequences with complex DNA-protein interactions. When used in combination with synthesis and high-throughput screening, this design strategy could help interrogate how complex binding site arrangements impact either gene expression or biomolecular mechanisms in varied cellular contexts.

Author Summary

The way protein binding sites are arranged on DNA can control the regulation and transcription of downstream genes. Areas with a high concentration of binding sites can enable complex interplay between transcription factors, a feature that is exploited by natural promoters. However, designing synthetic promoters that contain dense arrangements of binding sites is a challenge. The task involves overlapping many binding sites, each typically about 10 nucleotides long, within a constrained sequence area, which becomes increasingly difficult as sequence length decreases, and binding site variety increases. We introduce an approach to design nucleotide sequences with optimally packed protein binding sites, which we call the nucleotide String Packing Problem (SPP). We show that the SPP can be solved efficiently using integer linear programming to identify the densest arrangements of binding sites for a specified sequence length. We show how adding additional constraints, like the inclusion of sequence elements with fixed positions, allows for the design of bacterial promoters. The presented approach enables the rapid design and study of nucleotide sequences with complex, dense binding site architectures.

Genetic Circuits for Feedback Control of Gamma-Aminobutyric Acid Biosynthesis in Probiotic Escherichia coli Nissle 1917

Engineered microorganisms such as the probiotic strain Escherichia coli Nissle 1917 (EcN) offer a strategy to sense and modulate the concentration of metabolites or therapeutics in the gastrointestinal tract. Here, we present an approach to regulate the production of the depression-associated metabolite gamma-aminobutyric acid (GABA) in EcN using genetic circuits that implement negative feedback. We engineered EcN to produce GABA by overexpressing glutamate decarboxylase and applied an intracellular GABA biosensor to identify growth conditions that improve GABA biosynthesis. We next employed characterized genetically encoded NOT gates to construct genetic circuits with layered feedback to control the rate of GABA biosynthesis and the concentration of GABA produced. Looking ahead, this approach may be utilized to design feedback control of microbial metabolite biosynthesis to achieve designable smart microbes that act as living therapeutics.

Creation of Architecturally Minimal Transcriptionally Activating Riboswitches Responsive to Theophylline Reveals an Unconventional Design Strategy

Riboswitches are noncoding RNA switches that are largely utilized in bacteria and play a significant role in synthetic biology. Nonetheless, their natural counterparts possess lengthy sequences and intricate structures, posing challenges for their modular integration into complex gene circuits. Consequently, it is imperative to develop simplified synthetic riboswitches that can be effortlessly incorporated into gene circuits. The conventional approach to generate synthetic riboswitches entails tedious library construction and extensive screening, which frequently yields suboptimal performance. To overcome this obstacle, alternative methods are urgently needed. In this study, we created a novel approach to designing a diverse set of transcription-activating riboswitches that exhibit high performance and broad compatibility. The strategy involved starting with a synthetic theophylline RNA aptamer and designing an expression platform that forms a transcriptional terminator in its inactive state but switches to an antiterminator when it is activated. Several sequences were designed, constructed, and subjected to virtual screening, resulting in the identification of two transcription-activating riboswitches. These riboswitches were then engineered to reduce the basal leakage and increase the activation level through extending the hairpin region using a screened random sequence. These architecturally minimal synthetic riboswitches were highly adapted to different constitutive promoters in a modular manner, generating a differentially responsive output to theophylline. As a proof-of-principle, the synthetic riboswitches were applied to rewire a synthetic quorum-sensing circuit (QSC). The reprogrammed QSC successfully modulated the temporal responsive profile against the activation. This strategy is expected to expand the variety of high-performance riboswitches that are responsive to different ligands, thereby further facilitating the design of complex genetic circuits.

New insights into the roles of fungi and bacteria in the development of medicinal plant

BACKGROUND

The interaction between microorganisms and medicinal plants is a popular topic. Previous studies consistently reported that microorganisms were mainly considered pathogens or contaminants. However, with the development of microbial detection technology, it has been demonstrated that fungi and bacteria affect beneficially the medicinal plant production chain.

AIM OF REVIEW

Microorganisms greatly affect medicinal plants, with microbial biosynthesis a high regarded topic in medicinal plant-microbial interactions. However, it lacks a systematic review discussing this relationship. Current microbial detection technologies also have certain advantages and disadvantages, it is essential to compare the characteristics of various technologies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

This review first illustrates the role of fungi and bacteria in various medicinal plant production procedures, discusses the development of microbial detection and identification technologies in recent years, and concludes with microbial biosynthesis of natural products. The relationship between fungi, bacteria, and medicinal plants is discussed comprehensively. We also propose a future research model and direction for further studies.

Genetically encoded ATP and NAD(P)H biosensors: potential tools in metabolic engineering

To date, many metabolic engineering tools and strategies have been developed, including tools for cofactor engineering, which is a common strategy for bioproduct synthesis. Cofactor engineering is used for the regulation of pyridine nucleotides, including NADH/NAD+ and NADPH/NADP+, and adenosine triphosphate/adenosine diphosphate (ATP/ADP), which is crucial for maintaining redox and energy balance. However, the intracellular levels of NADH/NAD+, NADPH/NADP+, and ATP/ADP cannot be monitored in real time using traditional methods. Recently, many biosensors for detecting, monitoring, and regulating the intracellular levels of NADH/NAD+, NADPH/NADP+, and ATP/ADP have been developed. Although cofactor biosensors have been mainly developed for use in mammalian cells, the potential application of cofactor biosensors in metabolic engineering in bacterial and yeast cells has received recent attention. Coupling cofactor biosensors with genetic circuits is a promising strategy in metabolic engineering for optimizing the production of biochemicals. In this review, we focus on the development of biosensors for NADH/NAD+, NADPH/NADP+, and ATP/ADP and the potential application of these biosensors in metabolic engineering. We also provide critical perspectives, identify current research challenges, and provide guidance for future research in this promising field.

Progress and prospect: Biosynthesis of plant natural products based on plant chassis

Plant-derived natural products are a specific class of active substances with numerous applications in the medical, energy, and industrial fields. Many of these substances are in high demand and have become the fundamental materials for various purposes. Recently, the use of synthetic biology to produce plant-derived natural products has become a significant trend. Plant chassis, in particular, offer unique advantages over microbial chassis in terms of cell structure, product affinity, safety, and storage. The development of the plant hairy root tissue culture system has accelerated the commercialization and industrialization of synthetic biology in the production of plant-derived natural products. This paper will present recent progress in the synthesis of various plant natural products using plant chassis, organized by the types of different structures. Additionally, we will summarize the four primary types of plant chassis used for synthesizing natural products from plant sources and review the enabling technologies that have contributed to the development of synthetic biology in recent years. Finally, we will present the role of isolated and combined use of different optimization strategies in breaking the upper limit of natural product production in plant chassis. This review aims to provide practical references for synthetic biologists and highlight the great commercial potential of plant chassis biosynthesis, such as hairy roots.

Design of synthetic bacterial biosensors

Novel whole-cell bacterial biosensor designs require an emphasis on moving toward field deployment. Many current sensors are characterized under specified laboratory conditions, which frequently do not represent actual deployment conditions. To this end, recent developments such as toolkits for probing new host chassis that are more robust to environments of interest, have paved the way for improved designs. Strategies for rational tuning of genetic components or tools such as genetic amplifiers or designs that allow post hoc tuning are essential in optimizing existing biosensors for practical application. Furthermore, recent work has seen a rise in directed evolution techniques, which can be immensely valuable in both tuning existing sensors and developing sensors for new analytes that lack characterized sensors. Combined with advancements in bioinformatics and capabilities in rewiring two-component systems, many new sensors can be established, broadening biosensor use cases. Last, recent work in CRISPR-based dynamic regulation and memory mechanisms, as well as kill-switches for biosafety and innovative output integration concepts, represents promising steps toward designing bacterial biosensors for deployment in dynamic and heterogeneous conditions.

Biosensor-guided discovery and engineering of metabolic enzymes

A variety of chemicals have been produced through metabolic engineering approaches, and enhancing biosynthesis performance can be achieved by using enzymes with high catalytic efficiency. Accordingly, a number of efforts have been made to discover enzymes in nature for various applications. In addition, enzyme engineering approaches have been attempted to suit specific industrial purposes. However, a significant challenge in enzyme discovery and engineering is the efficient screening of enzymes with the desired phenotype from extensive enzyme libraries. To overcome this bottleneck, genetically encoded biosensors have been developed to specifically detect target molecules produced by enzyme activity at the intracellular level. Especially, the biosensors facilitate high-throughput screening (HTS) of targeted enzymes, expanding enzyme discovery and engineering strategies with advances in systems and synthetic biology. This review examines biosensor-guided HTS systems and highlights studies that have utilized these tools to discover enzymes in diverse areas and engineer enzymes to enhance their properties, such as catalytic efficiency, specificity, and stability.

Combination of microbial and chemical synthesis for the sustainable production of β-elemene, a promising plant-extracted anticancer compound

Beta-elemene, a class of sesquiterpene derived from the Chinese medicinal herb Curcuma wenyujin, is widely used in clinical medicine due to its broad-spectrum antitumor activity. However, the unsustainable plant extraction prompted the search for environmentally friendly strategies for β-elemene production. In this study, we designed a Yarrowia lipolytica cell factory that can continuously produce germacrene A, which is further converted into β-elemene with 100% yield through a Cope rearrangement reaction by shifting the temperature to 250°C. First, the productivity of four plant-derived germacrene A synthases was evaluated. After that, the metabolic flux of the precursor to germacrene A was maximized by optimizing the endogenous mevalonate pathway, inhibiting the competing squalene pathway, and expressing germacrene A synthase gene in multiple copies. Finally, the most promising strain achieved the highest β-elemene titer reported to date with 5.08 g/L. This sustainable and green method has the potential for industrial β-elemene production.

Target-dependent RNA polymerase as universal platform for gene expression control in response to intracellular molecules

Controlling gene expression in response to specific molecules is an essential technique for regulating cellular functions. However, current platforms with transcription and translation regulators have a limited number of detectable molecules to induce gene expression. Here to address these issues, we present a Target-dependent RNA polymerase (TdRNAP) that can induce RNA transcription in response to the intracellular target specifically recognized by single antibody. By substituting the fused antibody, we demonstrate that TdRNAPs respond to a wide variety of molecules, including peptides, proteins, RNA, and small molecules, and produce desired transcripts in human cells. Furthermore, we show that multiple TdRNAPs can construct orthogonal and multilayer genetic circuits. Finally, we apply TdRNAP to achieve cell-specific genome editing that is autonomously triggered by detecting the target gene product. TdRNAP can expand the molecular variety for controlling gene expression and provide the genetic toolbox for bioengineering and future therapeutic applications.

Multidimensional engineering of Escherichia coli for efficient synthesis of L-tryptophan

Development of microbial cell factory for L-tryptophan (L-trp) production has received widespread attention but still requires extensive efforts due to weak metabolic flux distribution and low yield. Here, the riboswitch-based high-throughput screening (HTS) platform was established to construct a powerful L-trp-producing chassis cell. To facilitate L-trp biosynthesis, gene expression was regulated by promoter and N-terminal coding sequences (NCS) engineering. Modules of degradation, transport and by-product synthesis related to L-trp production were also fine-tuned. Next, a novel transcription factor YihL was excavated to negatively regulate L-trp biosynthesis. Self-regulated promoter-mediated dynamic regulation of branch pathways was performed and cofactor supply was improved for further L-trp biosynthesis. Finally, without extra addition, the yield of strain Trp30 reached 42.5 g/L and 0.178 g/g glucose after 48 h of cultivation in 5-L bioreactor. Overall, strategies described here worked up a promising method combining HTS and multidimensional regulation for developing cell factories for products in interest.

Identifying, Characterizing, and Engineering a Phenolic Acid-Responsive Transcriptional Factor from Bacillus amyloliquefaciens

Transcriptional factors-based biosensors are commonly used in metabolic engineering for inducible control of gene expression and related applications such as high-throughput screening and dynamic pathway regulations. Mining for novel transcriptional factors is essential for expanding the usability of these toolsets. Here, we report the identification, characterization, and engineering of a phenolic acid responsive regulator PadR from Bacillus amyloliquefaciens (BaPadR). This BaPadR-based biosensor system showed a unique ligand preference and exhibited a high output strength comparable to that of commonly used inducible expression systems. Through engineering the DNA binding region of BaPadR, we further enhanced the dynamic range of the biosensor system. The DNA sequences that are responsible for BaPadR recognition were located by promoter truncation and hybrid promoter building. To further explore the tunability of the sensor system, base substitutions were performed on the BaPadR binding region of the phenolic acid decarboxylase promoter (PpadC) and the hybrid promoter. This novel biosensor system can serve as a valuable tool in future synthetic biology applications.

Natural products of pentacyclic triterpenoids: from discovery to heterologous biosynthesis

Covering: up to 2022Pentacyclic triterpenoids are important natural bioactive substances that are widely present in plants and fungi. They have significant medicinal efficacy, play an important role in reducing blood glucose and protecting the liver, and have anti-inflammatory, anti-oxidation, anti-fatigue, anti-viral, and anti-cancer activities. Pentacyclic triterpenoids are derived from the isoprenoid biosynthetic pathway, which generates common precursors of triterpenes and steroids, followed by cyclization with oxidosqualene cyclases (OSCs) and decoration via cytochrome P450 monooxygenases (CYP450s) and glycosyltransferases (GTs). Many biosynthetic pathways of triterpenoid saponins have been elucidated by studying their metabolic regulation network through the use of multiomics and identifying their functional genes. Unfortunately, natural resources of pentacyclic triterpenoids are limited due to their low content in plant tissues and the long growth cycle of plants. Based on the understanding of their biosynthetic pathway and transcriptional regulation, plant bioreactors and microbial cell factories are emerging as alternative means for the synthesis of desired triterpenoid saponins. The rapid development of synthetic biology, metabolic engineering, and fermentation technology has broadened channels for the accumulation of pentacyclic triterpenoid saponins. In this review, we summarize the classification, distribution, structural characteristics, and bioactivity of pentacyclic triterpenoids. We further discuss the biosynthetic pathways of pentacyclic triterpenoids and involved transcriptional regulation. Moreover, the recent progress and characteristics of heterologous biosynthesis in plants and microbial cell factories are discussed comparatively. Finally, we propose potential strategies to improve the accumulation of triterpenoid saponins, thereby providing a guide for their future biomanufacturing.

In Vivo Detection of Low Molecular Weight Platform Chemicals and Environmental Contaminants by Genetically Encoded Biosensors

Genetically encoded biosensor systems operating in living cells are versatile, cheap, and transferable tools for the detection and quantification of a broad range of small molecules. This review presents state-of-the-art biosensor designs and assemblies, featuring transcription factor-, riboswitch-, and enzyme-coupled devices, highly engineered fluorescent probes, and emerging two-component systems. Importantly, (bioinformatic-assisted) strategies to resolve contextual issues, which cause biosensors to miss performance criteria in vivo, are highlighted. The optimized biosensing circuits can be used to monitor chemicals of low molecular mass (<200 g mol^-1) and physicochemical properties that challenge conventional chromatographical methods with high sensitivity. Examples herein include but are not limited to formaldehyde, formate, and pyruvate as immediate products from (synthetic) pathways for the fixation of carbon dioxide (CO₂), industrially important derivatives like small- and medium-chain fatty acids and biofuels, as well as environmental toxins such as heavy metals or reactive oxygen and nitrogen species. Lastly, this review showcases biosensors capable of assessing the biosynthesis of platform chemicals from renewable resources, the enzymatic degradation of plastic waste, or the bioadsorption of highly toxic chemicals from the environment. These applications offer new biosensor-based manufacturing, recycling, and remediation strategies to tackle current and future environmental and socioeconomic challenges including the wastage of fossil fuels, the emission of greenhouse gases like CO₂, and the pollution imposed on ecosystems and human health.

Genetic circuits for feedback control of gamma-aminobutyric acid biosynthesis in probiotic Escherichia coli Nissle 1917

Engineered microorganisms such as the probiotic strain Escherichia coli Nissle 1917 (EcN) offer a strategy to sense and modulate the concentration of metabolites or therapeutics in the gastrointestinal tract. Here, we present an approach to regulate production of the depression-associated metabolite gamma-aminobutyric acid (GABA) in EcN using genetic circuits that implement negative feedback. We engineered EcN to produce GABA by overexpressing glutamate decarboxylase (GadB) from E. coli and applied an intracellular GABA biosensor to identify growth conditions that improve GABA biosynthesis. We next employed characterized genetically-encoded NOT gates to construct genetic circuits with layered feedback to control the rate of GABA biosynthesis and the concentration of GABA produced. Looking ahead, this approach may be utilized to design feedback control of microbial metabolite biosynthesis to achieve designable smart microbes that act as living therapeutics.

Regulatory transcription factor (CooA)-driven carbon monoxide partial pressure sensing whole-cell biosensor

We designed and constructed a whole-cell biosensor capable of detecting the presence and quantity of carbon monoxide (CO) using the CO regulatory transcription factor. This biosensor utilizes CooA, a CO-sensing transcription regulator that activates the expression of carbon monoxide dehydrogenase (CODH), to detect the presence of CO and respond by triggering the expression of a GUS reporter protein (β-glucuronidase). The GUS reporter protein is expressed from a CO-induced CooA-binding promoter (P_cooF) by CooA and enables the effective colorimetric detection of CO. An Escherichia coli strain used to validate the biosensor showed growth and GUS activity under anaerobic conditions; this study used the inert gas (Ar) to create anaerobic conditions. The pBRCO biosensor could successfully detect the presence of CO in the headspace. Moreover, the GUS-specific activity of pBRCO according to the CO strength as partial pressure followed Michaelis-Menten kinetics (R² = 0.98). It was confirmed that the GUS-specific activity of pBRCO increased linearly up to 30.39 kPa (R² = 0.98), and thus, a quantitative analysis of CO concentration (i.e., partial pressure) was possible.

Tailoring the whole-cell sensing spectrum with cyborgian redox machinery

Whole-cell biosensors are an important class of analytical tools that offer the advantages of low cost, facile operation, and unique reproduction/regeneration ability. However, it has always been quite challenging to expand the sensing spectrum of the host. Here, a new approach to extend the cell sensing spectrum with biomineralized nanoparticles is developed. The nano-biohybrid design comprise biomineralized FeS nanoparticles firmly anchored onto the bacterium, Shewanella oneidensis MR-1, wherein the nanoparticles are wired to the cellular electron transfer machinery (MtrCAB/OmcA) of the bacterium, forming an artificial cyborgian redox machinery consisting of FeS-MtrCAB/OmcA-FccA. Strikingly, with this cyborgian redox machinery, the sensing spectrum of FeS hybridized S. oneidensis MR-1 cell is successfully expanded to enable whole-cell electrochemical detection of Vitamin B12, while an unhybridized native cell is incapable of sensing. This proof-of-concept nano-biohybrid design offers a new perspective on manipulating the microbial toolkit for an expanded sensing spectrum in whole-cell biosensors.

A roadmap to establish a comprehensive platform for sustainable manufacturing of natural products in yeast

Secondary natural products (NPs) are a rich source for drug discovery. However, the low abundance of NPs makes their extraction from nature inefficient, while chemical synthesis is challenging and unsustainable. Saccharomyces cerevisiae and Pichia pastoris are excellent manufacturing systems for the production of NPs. This Perspective discusses a comprehensive platform for sustainable production of NPs in the two yeasts through system-associated optimization at four levels: genetics, temporal controllers, productivity screening, and scalability. Additionally, it is pointed out critical metabolic building blocks in NP bioengineering can be identified through connecting multilevel data of the optimized system using deep learning.

CRISPR-dCas12a-mediated genetic circuit cascades for multiplexed pathway optimization

The production efficiency of microbial cell factories is sometimes limited by the lack of effective methods to regulate multiple targets in a coordinated manner. Here taking the biosynthesis of glucosamine-6-phosphate (GlcN6P) in Bacillus subtilis as an example, a 'design-build-test-learn' framework was proposed to achieve efficient multiplexed optimization of metabolic pathways. A platform strain was built to carry biosensor signal-amplifying circuits and two genetic regulation circuits. Then, a synthetic CRISPR RNA array blend for boosting and leading (ScrABBLE) device was integrated into the platform strain, which generated 5,184 combinatorial assemblies targeting three genes. The best GlcN6P producer was screened and engineered for the synthesis of valuable pharmaceuticals N-acetylglucosamine and N-acetylmannosamine. The N-acetylglucosamine titer reached 183.9 g liter-1 in a 15-liter bioreactor. In addition, the potential generic application of the ScrABBLE device was also verified using three fluorescent proteins as a case study.

Strengthening microbial cell factories for efficient production of bioactive molecules

High demand of bioactive molecules (food additives, antibiotics, plant growth enhancers, cosmetics, pigments and other commercial products) is the prime need for the betterment of human life where the applicability of the synthetic chemical product is on the saturation due to associated toxicity and ornamentations. It has been noticed that the discovery and productivity of such molecules in natural scenarios are limited due to low cellular yields as well as less optimized conventional methods. In this respect, microbial cell factories timely fulfilling the requirement of synthesizing bioactive molecules by improving production yield and screening more promising structural homologues of the native molecule. Where the robustness of the microbial host can be potentially achieved by taking advantage of cell engineering approaches such as tuning functional and adjustable factors, metabolic balancing, adapting cellular transcription machinery, applying high throughput OMICs tools, stability of genotype/phenotype, organelle optimizations, genome editing (CRISPER/Cas mediated system) and also by developing accurate model systems via machine-learning tools. In this article, we provide an overview from traditional to recent trends and the application of newly developed technologies, for strengthening the systemic approaches and providing future directions for enhancing the robustness of microbial cell factories to speed up the production of biomolecules for commercial purposes.

Distinct Molecular Patterns of Two-Component Signal Transduction Systems in Thermophilic Cyanobacteria as Revealed by Genomic Identification

Two-component systems (TCSs) play crucial roles in sensing and responding to environmental signals, facilitating the acclimation of cyanobacteria to hostile niches. To date, there is limited information on the TCSs of thermophilic cyanobacteria. Here, genome-based approaches were used to gain insights into the structure and architecture of the TCS in 17 well-described thermophilic cyanobacteria, namely strains from the genus Leptodesmis, Leptolyngbya, Leptothermofonsia, Thermoleptolyngbya, Thermostichus, and Thermosynechococcus. The results revealed a fascinating complexity and diversity of the TCSs. A distinct composition of TCS genes existed among these thermophilic cyanobacteria. A majority of TCS genes were classified as orphan, followed by the paired and complex cluster. A high proportion of histidine kinases (HKs) were predicted to be cytosolic subcellular localizations. Further analyses suggested diversified domain architectures of HK and response regulators (RRs), putatively in association with various functions. Comparative and evolutionary genomic analyses indicated that the horizontal gene transfer, as well as duplications events, might be involved in the evolutionary history of TCS genes in Thermostichus and Thermosynechococcus strains. A comparative analysis between thermophilic and mesophilic cyanobacteria indicated that one HK cluster and one RR cluster were uniquely shared by all the thermophilic cyanobacteria studied, while two HK clusters and one RR cluster were common to all the filamentous thermophilic cyanobacteria. These results suggested that these thermophile-unique clusters may be related to thermal characters and morphology. Collectively, this study shed light on the TCSs of thermophilic cyanobacteria, which may confer the necessary regulatory flexibility; these findings highlight that the genomes of thermophilic cyanobacteria have a broad potential for acclimations to environmental fluctuations.

Engineering of a probiotic yeast for the production and secretion of medium-chain fatty acids antagonistic to an opportunistic pathogen Candida albicans

Candida albicans is an opportunistic pathogen, with its infection as one of the causes of morbidity or mortality. Notably, the probiotic yeast Saccharomyces cerevisiae var. boulardii has shown the potential to fight against Candida infections. In this study, we aimed to engineer a commercial boulardii strain to produce medium-chain fatty acids (MCFAs) with antagonistic effects against C. albicans. First, we identified and characterized a boulardii strain and created its auxotrophic strain Δura3. Next, we constructed and expressed a heterologous MCFA biosynthetic pathway under the control of inducible and constitutive promoters. Aside from examining MCFA production and secretion, we confirmed MCFAs' effects on C. albicans' anti-biofilm and anti-hyphal formations and the immunomodulatory effect of MCFA-containing supernatants on Caco-2 cells. We found that under constitutive promoters, the engineered boulardii strain constitutively produced and secreted a mixture of C6:0, C8:0, and C10:0. The secreted MCFAs then reduced biofilm and hyphal formations in C. albicans SC5314. We also confirmed that MCFAs upregulated the expression of virulence-related genes in SC5314. Furthermore, we found that the constitutively produced MCFAs in the supernatant induced the upregulation of immune response genes in Caco-2 cells co-cultured with SC5314, indicating MCFAs' roles in immunomodulation. Overall, the engineered boulardii strain produced and secreted MCFAs, as well as demonstrated antagonistic effects against C. albicans SC5314 and immune-modulatory effects in Caco-2. To our knowledge, this represents the first study tackling the metabolic engineering of a commercial probiotic yeast strain to constitutively produce and secrete MCFAs showing anti-Candida effects. Our study forms the basis of the potential development of a live biotherapeutics probiotic yeast against Candida infections through metabolic engineering strategies.

Genetically encoded biosensors for microbial synthetic biology: From conceptual frameworks to practical applications

Genetically encoded biosensors are the vital components of synthetic biology and metabolic engineering, as they are regarded as powerful devices for the dynamic control of genotype metabolism and evolution/screening of desirable phenotypes. This review summarized the recent advances in the construction and applications of different genetically encoded biosensors, including fluorescent protein-based biosensors, nucleic acid-based biosensors, allosteric transcription factor-based biosensors and two-component system-based biosensors. First, the construction frameworks of these biosensors were outlined. Then, the recent progress of biosensor applications in creating versatile microbial cell factories for the bioproduction of high-value chemicals was summarized. Finally, the challenges and prospects for constructing robust and sophisticated biosensors were discussed. This review provided theoretical guidance for constructing genetically encoded biosensors to create desirable microbial cell factories for sustainable bioproduction.

Metabolic Engineering: Methodologies and Applications

Metabolic engineering aims to improve the production of economically valuable molecules through the genetic manipulation of microbial metabolism. While the discipline is a little over 30 years old, advancements in metabolic engineering have given way to industrial-level molecule production benefitting multiple industries such as chemical, agriculture, food, pharmaceutical, and energy industries. This review describes the design, build, test, and learn steps necessary for leading a successful metabolic engineering campaign. Moreover, we highlight major applications of metabolic engineering, including synthesizing chemicals and fuels, broadening substrate utilization, and improving host robustness with a focus on specific case studies. Finally, we conclude with a discussion on perspectives and future challenges related to metabolic engineering.

Characterization of Eight Bacterial Biosensors for Microbial Diagnostic and Therapeutic Applications

The engineering of microbial cells to produce and secrete therapeutics directly in the human body, known as advanced microbial therapeutics, is an exciting alternative to current drug delivery routes. These living therapeutics can be engineered to sense disease biomarkers and, in response, deliver a therapeutic activity. This strategy allows for precise and self-regulating delivery of a therapeutic that adapts to the disease state of the individual patient. Numerous sensing systems have been characterized for use in prokaryotes, but a very limited number of advanced microbial therapeutics have incorporated such sensors. We characterized eight different sensors that respond to physiologically relevant conditions and molecules found in the human body in the probiotic strain Escherichia coli Nissle 1917. The resulting sensors were characterized under aerobic and anaerobic conditions and were demonstrated to be functional under gut-like conditions using the nematode Caenorhabditis elegans as an in vivo model. We show for the first time how a biosensor is able to detect in vivo the bile acid-like molecule Δ⁴-dafachronic acid, a small molecule in C. elegans that regulates lifespan. Furthermore, we exemplify how bacterial sensors can be used to dynamically report on changes in the intestinal environment of C. elegans, by demonstrating the use of a biosensor able to detect changes in lactate concentrations in the gut lumen of individual C. elegans. The biosensors presented in this study allow for dynamic control of expression in vivo and represent a valuable tool in further developing advanced microbiome therapeutics.

Olfactory Receptors as an Emerging Chemical Sensing Scaffold

Chemical biosensors are an increasingly ubiquitous part of our lives. Beyond enzyme-coupled assays, recent synthetic biology advances now allow us to hijack more complex biosensing systems to respond to difficult to detect analytes, such as chemical small molecules. Here, we briefly overview recent advances in the biosensing of small molecules, including nucleic acid aptamers, allosteric transcription factors, and two-component systems. We then look more closely at a recently developed chemical sensing system, G protein-coupled receptor (GPCR)-based sensors. Finally, we consider the chemical sensing capabilities of the largest GPCR subfamily, olfactory receptors (ORs). We examine ORs' role in nature, their potential as a biomedical target, and their ability to detect compounds not amenable for detection using other biological scaffolds. We conclude by evaluating the current challenges, opportunities, and future applications of GPCR- and OR-based sensors.

How far are the new wave of mRNA drugs from us? mRNA product current perspective and future development

mRNA products are therapies that are regulated from the post-transcriptional, pre-translational stage of a gene and act upstream of protein synthesis. Compared with traditional small molecule drugs and antibody drugs, mRNA drugs had the advantages of simple design, short development cycle, strong target specificity, wide therapeutic field, and long-lasting effect. mRNA drugs were now widely used in the treatment of genetic diseases, tumors, and viral infections, and are expected to become the third major class of drugs after small molecule drugs and antibody drugs. The delivery system technology was the key to ensuring the efficacy and safety of mRNA drugs, which plays an important role in protecting RNA structure, enhancing targeting ability, reducing the dose of drug delivery, and reducing toxic side effects. Lipid nanoparticles (LNP) were the most common delivery system for mRNA drugs. In recent years, mRNA drugs have seen rapid development, with the number of drugs on the market increasing each year. The success of commercializing mRNA vaccines has driven a wave of nucleic acid drug development. mRNA drugs were clinically used in genetic diseases, oncology, and infectious diseases worldwide, while domestic mRNA clinical development was focused on COVID-19 vaccines, with more scope for future indication expansion.

Common Pathogens and Drug Resistance of Neonatal Pneumonia with New Multichannel Sensor

This study aimed to study the application value of a new multichannel sensor in pathogen detection and drug resistance analysis of neonatal pneumonia. 180 newborns with infectious pneumonia were selected, and a new multichannel piezoelectric sensor was constructed. The traditional Kirby–Bauer (K–B) method and the piezoelectric sensor were adopted to detect the pathogens and drug resistance in newborn samples, respectively. The results showed that the sensitivity and specificity under the K–B method (99.58% and 99.32%) and the multichannel piezoelectric sensor (99.43% and 94.29%) were not statistically different (P > 0.05). The detection time (17.25 h) of the K–B method was significantly longer than that (7.43 h) of the multichannel piezoelectric sensor (P < 0.05). From the results of pathogen detection, it was found that Klebsiella pneumoniae accounted for a relatively high proportion of 25.1%, followed by Staphylococcus aureus and Haemophilus influenzae of 13.4% and 12.33%, respectively. The resistance rate of the Staphylococcus aureus to vancomycin and rifampicin was as high as 100% and that to gentamicin, ciprofloxacin, and erythromycin reached more than 50%. In short, the new multichannel piezoelectric sensor had the high sensitivity and specificity for the pathogens' detection of neonatal pneumonia, and it required a shorter time. The pathogens were mostly Gram-negative bacteria, followed by Gram-positive bacteria and fungi. Klebsiella pneumoniae, Staphylococcus aureus, and Haemophilus influenzae were the main ones. The neonatal pneumonia pathogens had also strong drug resistance against vancomycin, rifampicin, chloramphenicol, meropenem, amikacin sulfate, chloramphenicol, and many other antibacterial drugs.

Advances in Metabolic Engineering Paving the Way for the Efficient Biosynthesis of Terpenes in Yeasts

Terpenes are a large class of secondary metabolites with diverse structures and functions that are commonly used as valuable raw materials in food, cosmetics, and medicine. With the development of metabolic engineering and emerging synthetic biology tools, these important terpene compounds can be sustainably produced using different microbial chassis. Currently, yeasts such as Saccharomyces cerevisiae and Yarrowia lipolytica have received extensive attention as potential hosts for the production of terpenes due to their clear genetic background and endogenous mevalonate pathway. In this review, we summarize the natural terpene biosynthesis pathways and various engineering strategies, including enzyme engineering, pathway engineering, and cellular engineering, to further improve the terpene productivity and strain stability in these two widely used yeasts. In addition, the future prospects of yeast-based terpene production are discussed in light of the current progress, challenges, and trends in this field. Finally, guidelines for future studies are also emphasized.

Engineering whole-cell microbial biosensors: Design principles and applications in monitoring and treatment of heavy metals and organic pollutants

Biosensors have been widely used as cost-effective, rapid, in situ, and real-time analytical tools for monitoring environments. The development of synthetic biology has enabled emergence of genetically engineered whole-cell microbial biosensors. This review updates the design and optimization principles for a diverse array of whole-cell biosensors based on transcription factors (TF) including activators or repressors derived from heavy metal resistance systems, alkanes, and aromatics metabolic pathways of bacteria. By designing genetic circuits, the whole-cell biosensors could be engineered to intelligently sense heavy metals (Hg²⁺, Zn²⁺, Pb²⁺, Au³⁺, Cd²⁺, As³⁺, Ni²⁺, Cu²⁺, and UO₂²⁺) or organic compounds (alcohols, alkanes, phenols, and benzenes) through one-component or two-component system-based TFs, transduce signals through genetic amplifiers, and response as various outputs such as cell fluorescence and bioelectricity for monitoring heavy metals and organic pollutants in real conditions, synthetic curli and surface metal-binding peptides for in situ bio-sorption of heavy metals. We further review strategies that have been implemented to optimize the selectivity and correlation between ligand concentration and output signal of the TF-based biosensors, so as to meet requirements of practical applications. The optimization strategies include protein engineering to change specificities, promoter engineering to improve sensitivities, and genetic circuit-based amplification to enhance dynamic ranges via designing transcriptional amplifiers, logic gates, and feedback loops. At last, we outlook future trends in developing novel forms of biosensors.

Using fungible biosensors to evolve improved alkaloid biosyntheses

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 (EC₅₀) < 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.

Signal Amplification of araC pBAD Using a Standardised Translation Initiation Region

araC pBAD is a genetic fragment that regulates the expression of the araBAD operon in bacteria, which is required for the metabolism of L-arabinose. It is widely used in bioengineering applications because it can drive regulatable and titratable expression of genes and genetic pathways in microbial cell factories. A notable limitation of araC pBAD is that it generates a low signal when induced with high concentrations of L-arabinose (the maximum ON state). Herein we have amplified the maximum ON state of araC pBAD by coupling it to a synthetically evolved translation initiation region (TIR^EVOL). The coupling maintains regulatable and titratable expression from araC pBAD and yet increases the maximal ON state by >5-fold. The general principle demonstrated in the study can be applied to amplify the signal from similar genetic modules.

Graphical Abstract

Engineering of a TrpR-Based Biosensor for Altered Dynamic Range and Ligand Preference

Transcriptional factors play a crucial role in regulating cellular functions. Understanding and altering the dynamic behavior of the transcriptional factor-based biosensors will expand our knowledge in investigating biomolecular interactions and facilitating biosynthetic applications. In this study, we characterized and engineered a TrpR-based tryptophan repressor system in Escherichia coli. We found that the reconstructed TrpR1-PtrpO1 biosensor system exhibited low basal expression and narrow dynamic range in the presence of tryptophan or its analogue 5-hydroxytryptophan (5-HTP). Given the application potential of the biosensor, we introduced engineering approaches in multiple levels to optimize its dynamic behavior. First, the I57 and V58 residues in the ligand-binding pocket were rationally mutated in search of variants with altered ligand specificity. Two TrpR1 variants, V58E and V58K, successfully acquired ligand preference toward tryptophan and 5-HTP, respectively. The biosensor-induced expression levels were increased up to 10-fold with those variants. Furthermore, to pursue broader operational range, we tuned the regulator-operator binding affinity by mutating the binding box of TrpR1. Collectively, we demonstrated that the biosynthesis-significant biosensor TrpR1-PtrpO1 can be engineered to acquire extended dynamic ranges and improved ligand preference. The engineered biosensor variants with remarkable dynamic behavior can serve as key genetic elements in high-throughput screening and dynamic regulation in biosynthetic scenarios.

Potential use of microbial engineering in single-cell protein production

Single-cell proteins (SCPs) have been widely used in human food and animal feed applications, still, there are challenges in their production and commercialization. Recently, advances in microbial synthetic biology, genomic engineering, and biofoundry technologies have offered capabilities to effectively and rapidly engineer microorganisms for improving the productivity, nutritional, and functional quality of SCPs. In this review, we discuss various synthetic biology, genomic engineering, and biofoundry tools that can be harnessed for SCP production and genetic modification. We also describe the current and potential applications of genetic modification in producing intermediate feedstocks, as well as biomass-based and multifunctional SCPs. Finally, we discuss the technological and policy-control related challenges encountered when deploying genetic modification in SCP production for animal feed and human food applications.

Dynamic Regulation of Transporter Expression to Increase L-Threonine Production Using L-Threonine Biosensors

The cytotoxicity of overexpressed transporters limits their application in biochemical production. To overcome this problem, we developed a feedback circuit for L-threonine production that uses a biosensor to regulate transporter expression. First, we used IPTG-induced rhtA regulation, L-threonine exporter, to simulate dynamic regulation for improving L-threonine production, and the results show that it had significant advantages compared with the constitutive overexpression of rhtA. To further construct a feedback circuit for rhtA auto-regulation, three L-threonine sensing promoters, PcysJ, PcysD, and PcysJH, were characterized with gradually decreasing strength. The dynamic expression of rhtA with a threonine-activated promoter considerably increased L-threonine production (21.19 g/L) beyond that attainable by the constitutive expression of rhtA (8.55 g/L). Finally, the autoregulation method was used in regulating rhtB and rhtC to improve L-threonine production and achieve a high titer of 26.78 g/L (a 161.01% increase), a yield of 0.627 g/g glucose, and a productivity of 0.743 g/L/h in shake-flask fermentation. This study analyzed in detail the influence of dynamic regulation and the constitutive expression of transporters on L-threonine production. For the first time, we confirmed that dynamically regulating transporter levels can efficiently promote L-threonine production by using the end-product biosensor.

Recent advances in high-throughput metabolic engineering: Generation of oligonucleotide-mediated genetic libraries

The preparation of genetic libraries is an essential step to evolve microorganisms and study genotype-phenotype relationships by high-throughput screening/selection. As the large-scale synthesis of oligonucleotides becomes easy, cheap, and high-throughput, numerous novel strategies have been developed in recent years to construct high-quality oligo-mediated libraries, leveraging state-of-art molecular biology tools for genome editing and gene regulation. This review presents an overview of recent advances in creating and characterizing in vitro and in vivo genetic libraries, based on CRISPR/Cas, regulatory RNAs, and recombineering, primarily for Escherichia coli and Saccharomyces cerevisiae. These libraries' applications in high-throughput metabolic engineering, strain evolution and protein engineering are also discussed.

Intracellular biosensor-based dynamic regulation to manipulate gene expression at the spatiotemporal level

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.

Transporter-Driven Engineering of a Genetic Biosensor for the Detection and Production of Short-Branched Chain Fatty Acids in Saccharomyces cerevisiae

Biosensors can be used for real-time monitoring of metabolites and high-throughput screening of producer strains. Use of biosensors has facilitated strain engineering to efficiently produce value-added compounds. Following our recent work on the production of short branched-chain fatty acids (SBCFAs) in engineered Saccharomyces cerevisiae, here we harnessed a weak organic acid transporter Pdr12p, engineered a whole-cell biosensor to detect exogenous and intracellular SBCFAs and optimized the biosensor’s performance by varying PDR12 expression. We firstly constructed the biosensor and evaluated its response to a range of short-chain carboxylic acids. Next, we optimized its sensitivity and operational range by deletion and overexpression of PDR12. We found that the biosensor responded to exogenous SBCFAs including isovaleric acid, isobutyric acid and 2-methylbutanoic acid. PDR12 deletion enhanced the biosensor’s sensitivity to isovaleric acid at a low concentration and PDR12 overexpression shifted the operational range towards a higher concentration. Lastly, the deletion of PDR12 improved the biosensor’s sensitivity to the SBCFAs produced in our previously engineered SBCFA-overproducing strain. To our knowledge, our work represents the first study on employing an ATP-binding-cassette transporter to engineer a transcription-factor-based genetic biosensor for sensing SBCFAs in S. cerevisiae. Our findings provide useful insights into SBCFA detection by a genetic biosensor that will facilitate the screening of SBCFA-overproducing strains.

Engineering Transcription Factor BmoR Mutants for Constructing Multifunctional Alcohol Biosensors

Native transcription factor-based biosensors (TFBs) have the potential for the in situ detection of value-added chemicals or byproducts. However, their industrial application is limited by their ligand promiscuity, low sensitivity, and narrow detection range. Alcohols exhibit similar structures, and no reported TFB can distinguish a specific alcohol from its analogues. Here, we engineered an alcohol-regulated transcription factor, BmoR, and obtained various mutants with remarkable properties. For example, the generated signal-molecule-specific BmoRs could distinguish the constitutional isomers n-butanol and isobutanol, with insensitivity up to an ethanol concentration of 800 mM (36.9 g/L). Linear detection of 0-60 mM of a specific higher alcohol could be achieved in the presence of up to 500 mM (23.0 g/L) ethanol as background noise. Furthermore, we obtained two mutants with raised outputs and over 10⁷-fold higher sensitivity and one mutant with an increased upper detection limit (14.8 g/L n-butanol or isobutanol). Using BmoR as an example, this study systematically explored the ultimate detection limit of a TFB toward its small-molecule ligands, paving the way for in situ detection in biofuel and wine industries.

Polymer Encapsulation of Bacterial Biosensors Enables Coculture with Mammalian Cells

Coexistence of different populations of cells and isolation of tasks can provide enhanced robustness and adaptability or impart new functionalities to a culture. However, generating stable cocultures involving cells with vastly different growth rates can be challenging. To address this, we developed living analytics in a multilayer polymer shell (LAMPS), an encapsulation method that facilitates the coculture of mammalian and bacterial cells. We leverage LAMPS to preprogram a separation of tasks within the coculture: growth and therapeutic protein production by the mammalian cells and l-lactate biosensing by Escherichia coli encapsulated within LAMPS. LAMPS enable the formation of a synthetic bacterial-mammalian cell interaction that enables a living biosensor to be integrated into a biomanufacturing process. Our work serves as a proof-of-concept for further applications in bioprocessing since LAMPS combine the simplicity and flexibility of a bacterial biosensor with a viable method to prevent runaway growth that would disturb mammalian cell physiology.