Exploring the Tunability and Dynamic Properties of MarR-PmarO Sensor System in Escherichia coli

Stress-driven dynamic regulation of multiple genes to reduce accumulation of toxic aldehydes

Aldehydes are ubiquitous metabolites in living cells. As reactive electrophiles, they have the capacity to form adducts with cellular protein thiols and amines, leading to potential toxicity. Dynamic regulation has proven to be an effective strategy for addressing the accumulation of toxic metabolites. However, there are limited reports on applying dynamic control specifically to mitigate aldehyde accumulation. In this study, the cinnamaldehyde accumulation in the biosynthesis of cinnamylamine was used as a model to evaluate a two-way dynamic regulation strategy. First, we utilized whole-genome transcript arrays to identify the cinnamaldehyde-responsive promoters: the upregulated promoter P4 and the downregulated promoter Pd. They were then employed as biosensors to dynamically regulate the synthesis and consumption of cinnamaldehyde, mitigating its toxic effects on the host. This strategy successfully reduced cinnamaldehyde accumulation by 50 % and increased the production of cinnamylamine by 2.9 times. This study demonstrated a cinnamaldehyde-induced autoregulatory system that facilitated the conversion of cinnamic acid into cinnamylamine without the need for costly external inducers, presenting a promising and economically viable approach. The strategy also serves as a reference for alleviating the inhibitory effects of other toxic aldehydes on microorganisms. Additionally, the biosensors (Pd and P4) can respond to a range of aldehyde compounds, offering a rapid and sensitive method for detecting toxic aldehydes in both environmental samples and microorganisms, thus provide a valuable tool for screening strains enhanced aldehyde yield.

Microbial Transcription Factor-Based Biosensors: Innovations from Design to Applications in Synthetic Biology

Transcription factor-based biosensors (TFBs) are powerful tools in microbial biosensor applications, enabling dynamic control of metabolic pathways, real-time monitoring of intracellular metabolites, and high-throughput screening (HTS) for strain engineering. These systems use transcription factors (TFs) to convert metabolite concentrations into quantifiable outputs, enabling precise regulation of metabolic fluxes and biosynthetic efficiency in microbial cell factories. Recent advancements in TFB, including improved sensitivity, specificity, and dynamic range, have broadened their applications in synthetic biology and industrial biotechnology. Computational tools such as Cello have further revolutionized TFB design, enabling in silico optimization and construction of complex genetic circuits for integrating multiple signals and achieving precise gene regulation. This review explores innovations in TFB systems for microbial biosensors, their role in metabolic engineering and adaptive evolution, and their future integration with artificial intelligence and advanced screening technologies to overcome critical challenges in synthetic biology and industrial bioproduction.

Efficient production of salicylic acid through CmeR-PcmeO biosensor-assisted multiplexing pathway optimization in Escherichia coli

To address the challenge of microbial tolerance in industrial biomanufacturing, we developed an adaptive evolution strategy for Escherichia coli W3110 to enhance its salicylic acid (SA) tolerance. Utilizing a CmeR-PcmeO biosensor-enabled high-throughput screening system, we isolated an SA-tolerant variant (W3110K-4) that exhibited a 2.3-fold increase in tolerance (from 0.9 to 2.1 g/L) and a 2.1-fold improvement in SA production (from 283 to 588.1 mg/L). Subsequently, the designed sensors were combined with multi-pathway sgRNA arrays to dynamically modulate the other three branched-chain acid derivatives, achieving a balance between biomass growth and rapid SA production in the adaptively evolved strain, resulting in a maximum SA yield of 1477.8 mg/L, which represents a 30% improvement over the non-evolved control strain W3110K-W2 (1138.2 mg/L) using the same metabolic strategy. Whole-genome sequencing revealed that adaptive mutations in genes such as ducA* and anti-drug resistance C2 mutation genes (ymdA*, ymdB*, clsC*, csgB*, csgA*, and csgC*) play a key role in enhancing SA tolerance and productivity. Notably, the evolved strain W3110K-4 exhibits significant resistance to bacteriophages, making it a promising candidate for large-scale SA fermentation. This work develops and expands the CmeR-PcmeO system, proposes new insights into improved strains through biosensor screening, guided multi-pathway metabolism, and adaptive evolution, and provides a paradigm for engineers to obtain engineered strains.

Genetically encoded biosensors for the circular plastics bioeconomy

Current plastic production and consumption routes are unsustainable due to impact upon climate change and pollution, and therefore reform across the entire value chain is required. Biotechnology offers solutions for production from renewable feedstocks, and to aid end of life recycling/upcycling of plastics. Biology sequence/design space is complex requiring high-throughput analytical methods to facilitate the iterative optimisation, design-build, test-learn (DBTL), cycle of Synthetic Biology. Furthermore, genetic regulatory tools can enable harmonisation between biotechnological demands and the physiological constraints of the selected production host. Genetically encoded biosensors offer a solution for both requirements to facilitate the circular plastic bioeconomy. In this review we present a summary of biosensors developed to date reported to be responsive to plastic precursors/monomers. In addition, we provide a summary of the demonstrated and prospective applications of these biosensors for the construction and deconstruction of plastics. Collectively, this review provides a valuable resource of biosensor tools and enabled applications to support the development of the circular plastics bioeconomy.

A self-regulated network for dynamically balancing multiple precursors in complex biosynthetic pathways

Microbial synthesis has emerged as a promising and sustainable alternative to traditional chemical synthesis and plant extraction. However, the competition between synthetic pathways and central metabolic pathways for cellular resources may impair final production efficiency. Moreover, when the synthesis of target product requires multiple precursors from the same node, the conflicts of carbon flux have further negative impacts on yields. In this study, a self-regulated network was developed to relieve the competition of precursors in complex synthetic pathways. Using 4-hydroxycoumarin (4-HC) synthetic pathway as a proof of concept, we employed an intermediate as a trigger to dynamically rewire the metabolic flux of pyruvate and control the expression levels of genes in 4-HC synthetic pathway, achieving self-regulation of multiple precursors and enhanced titer. Transcriptomic analysis results additionally demonstrated that the gene transcriptional levels of both pyruvate kinase PykF and synthetic pathway enzyme SdgA dynamically changed according to the intermediate concentrations. Overall, our work established a self-regulated network to dynamically balance the metabolic flux of two precursors in 4-HC biosynthesis, providing insight into balancing biosynthetic pathways where multiple precursors compete and interfere with each other.

Impact of cell wall polysaccharide modifications on the performance of Pichia pastoris: novel mutants with enhanced fitness and functionality for bioproduction applications

BACKGROUND

Pichia pastoris is a widely utilized host for heterologous protein expression and biotransformation. Despite the numerous strategies developed to optimize the chassis host GS115, the potential impact of changes in cell wall polysaccharides on the fitness and performance of P. pastoris remains largely unexplored. This study aims to investigate how alterations in cell wall polysaccharides affect the fitness and function of P. pastoris, contributing to a better understanding of its overall capabilities.

RESULTS

Two novel mutants of GS115 chassis, H001 and H002, were established by inactivating the PAS_chr1-3_0225 and PAS_chr1-3_0661 genes involved in β-glucan biosynthesis. In comparison to GS115, both modified hosts exhibited a looser cell surface and larger cell size, accompanied by faster growth rates and higher carbon-to-biomass conversion ratios. When utilizing glucose, glycerol, and methanol as exclusive carbon sources, the carbon-to-biomass conversion rates of H001 surpassed GS115 by 10.00%, 9.23%, and 33.33%, respectively. Similarly, H002 exhibited even higher increases of 32.50%, 12.31%, and 53.33% in carbon-to-biomass conversion compared to GS115 under the same carbon sources. Both chassis displayed elevated expression levels of green fluorescent protein (GFP) and human epidermal growth factor (hegf). Compared to GS115/pGAPZ A-gfp, H002/pGAPZ A-gfp showed a 57.64% higher GFP expression, while H002/pPICZα A-hegf produced 66.76% more hegf. Additionally, both mutant hosts exhibited enhanced biosynthesis efficiencies of S-adenosyl-L-methionine and ergothioneine. H001/pGAPZ A-sam2 synthesized 21.28% more SAM at 1.14 g/L compared to GS115/pGAPZ A-sam2, and H001/pGAPZ A-egt1E obtained 45.41% more ERG at 75.85 mg/L. The improved performance of H001 and H002 was likely attributed to increased supplies of NADPH and ATP. Specifically, H001 and H002 exhibited 5.00-fold and 1.55-fold higher ATP levels under glycerol, and 6.64- and 1.47-times higher ATP levels under methanol, respectively, compared to GS115. Comparative lipidomic analysis also indicated that the mutations generated richer unsaturated lipids on cell wall, leading to resilience to oxidative damage.

CONCLUSIONS

Two novel P. pastoris chassis hosts with impaired β-1,3-D-glucan biosynthesis were developed, showcasing enhanced performances in terms of growth rate, protein expression, and catalytic capabilities. These hosts exhibit the potential to serve as attractive alternatives to P. pastoris GS115 for various bioproduction applications.

A novel Escherichia coli cell-based bioreporter for quantification of salicylic acid in cosmetics

Transcription factor-based bioreporters have been extensively studied for monitoring and detecting environmental toxicants. In Escherichia coli, the multiple antibiotic resistance regulator (MarR) induces transcription upon binding to salicylic acid (SA). We generated SA-specific E. coli cell-based bioreporters utilizing the operator region of the mar operon and MarR as components of the reporter and sensing domains, respectively. Although bioreporters based on endogenous MarR and wild-type E. coli cells responded to SA, their sensitivity and selectivity were insufficient for practical sample monitoring. To improve these parameters, we genetically engineered host strains for optimal MarR expression, which enhanced the sensitivity of the biosensor to micromolar quantities of SA with increased selectivity. Under the optimized experimental conditions, the biosensor could quantify SA in environmental samples. For validation, the SA concentration in artificially contaminated SA-containing cosmetic samples was determined using the developed biosensor. Reliability assessment by comparing the concentrations determined using LC-MS/MS revealed > 90% accuracy of the bioreporters. Although bioreporters are not considered standard tools for environmental monitoring, bacterial cell-based bioreporters may serve as alternative tools owing to their affordability and simplicity. The SA biosensor developed in this study can potentially be a valuable tool for monitoring SA in environmental systems. KEY POINTS: • SA-responsive bioreporter is generated by employing mar operon system in E. coli • SA specificity and selectivity were enhanced by genetic/biochemical engineering • The novel bioreporter would be valuable for SA monitoring in environmental systems.

An Intelligent Synthetic Bacterium for Chronological Toxicant Detection, Biodegradation, and Its Subsequent Suicide

Modules, toolboxes, and synthetic biology systems may be designed to address environmental bioremediation. However, weak and decentralized functional modules require complex control. To address this issue, an integrated system for toxicant detection and biodegradation, and subsequent suicide in chronological order without exogenous inducers is constructed. Salicylic acid, a typical pollutant in industrial wastewater, is selected as an example to demonstrate this design. Biosensors are optimized by regulating the expression of receptors and reporters to get 2-fold sensitivity and 6-fold maximum output. Several stationary phase promoters are compared, and promoter Pfic is chosen to express the degradation enzyme. Two concepts for suicide circuits are developed, with the toxin/antitoxin circuit showing potent lethality. The three modules are coupled in a stepwise manner. Detection and biodegradation, and suicide are sequentially completed with partial attenuation compared to pre-integration, except for biodegradation, being improved by the replacements of ribosome binding site. Finally, a long-term stability test reveals that the engineered strain maintained its function for ten generations. The study provides a novel concept for integrating and controlling functional modules that can accelerate the transition of synthetic biology from conceptual to practical applications.

Dynamic Metabolic Control: From the Perspective of Regulation Logic

Establishing microbial cell factories has become a sustainable and increasingly promising approach for the synthesis of valuable chemicals. However, introducing heterologous pathways into these cell factories can disrupt the endogenous cellular metabolism, leading to suboptimal production performance. To address this challenge, dynamic pathway regulation has been developed and proven effective in improving microbial biosynthesis. In this review, we summarized typical dynamic regulation strategies based on their control logic. The applicable scenarios for each control logic were highlighted and perspectives for future research direction in this area were discussed.

Transcription Factor-Based Biosensors for Detecting Pathogens

Microorganisms are omnipresent and inseparable from our life. Many of them are beneficial to humans, while some are not. Importantly, foods and beverages are susceptible to microbial contamination, with their toxins causing illnesses and even death in some cases. Therefore, monitoring and detecting harmful microorganisms are critical to ensuring human health and safety. For several decades, many methods have been developed to detect and monitor microorganisms and their toxicants. Conventionally, nucleic acid analysis and antibody-based analysis were used to detect pathogens. Additionally, diverse chromatographic methods were employed to detect toxins based on their chemical and structural properties. However, conventional techniques have several disadvantages concerning analysis time, sensitivity, and expense. With the advances in biotechnology, new approaches to detect pathogens and toxins have been reported to compensate for the disadvantages of conventional analysis from different research fields, including electrochemistry, nanotechnology, and molecular biology. Among them, we focused on the recent studies of transcription factor (TF)-based biosensors to detect microorganisms and discuss their perspectives and applications. Additionally, the other biosensors for detecting microorganisms reported in recent studies were also introduced in this review.

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.