Biosensor for branched-chain amino acid metabolism in yeast and applications in isobutanol and isopentanol production

Microbial host engineering for sustainable isobutanol production from renewable resources

Due to the limited resources and environmental problems associated with fossil fuels, there is a growing interest in utilizing renewable resources for the production of biofuels through microbial fermentation. Isobutanol is a promising biofuel that could potentially replace gasoline. However, its production efficiency is currently limited by the use of naturally isolated microorganisms. These naturally isolated microorganisms often encounter problems such as a limited range of substrates, low tolerance to solvents or inhibitors, feedback inhibition, and an imbalanced redox state. This makes it difficult to improve their production efficiency through traditional process optimization methods. Fortunately, recent advancements in genetic engineering technologies have made it possible to enhance microbial hosts for the increased production of isobutanol from renewable resources. This review provides a summary of the strategies and synthetic biology approaches that have been employed in the past few years to improve naturally isolated or non-natural microbial hosts for the enhanced production of isobutanol by utilizing different renewable resources. Furthermore, it also discusses the challenges that are faced by engineered microbial hosts and presents future perspectives to enhancing isobutanol production. KEY POINTS: • Promising potential of isobutanol to replace gasoline • Engineering of native and non-native microbial host for isobutanol production • Challenges and opportunities for enhanced isobutanol production.

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.

Multidimensional combinatorial screening for high-level production of erythritol in Yarrowia lipolytica

Yarrowia lipolytica was successfully engineered to synthesize erythritol from crude glycerol, a cheap by-product of biodiesel production, but the yield remained low. Here, a biosensor-guided adaptive evolution screening platform was constructed to obtain mutant strains which could efficiently utilize crude glycerol to produce erythritol. Erythrose reductase D46A (M1) was identified as a key mutant through whole-genome sequencing of the strain G12, which exhibited higher catalytic activity (1.6-fold of the wild-type). M1 was further modified to obtain a combinatorial mutant with 4.1-fold enhancement of catalytic activity. Finally, the metabolic network was reconfigured to redirect carbon fluxes toward erythritol synthesis. The erythritol titer of the engineered strain G31 reached 220.5 g/L with a productivity of 1.8 g/L/h in a 5-L bioreactor. The study provides valuable guidance for biosensor-based ultra-high-throughput screening strategies in Y. lipolytica, as well as presenting a new paradigm for the sustainable valorization of crude glycerol.

Design and Characterization of a Generalist Biosensor for Indole Derivatives

Transcription factor (TF)-based biosensors are useful synthetic biology tools for applications in a variety of areas of biotechnology. A major challenge of biosensor circuits is the limited repertoire of identified and well-characterized TFs for applications of interest, in addition to the challenge of optimizing selected biosensors. In this work, we implement the IclR family repressor TF TtgV from Pseudomonas putida DOT-T1E as an indole-derivative biosensor in Escherichia coli. We optimize the genetic circuit utilizing different components, providing insights into biosensor design and expanding on previous studies investigating this TF. We discover novel physiologically relevant ligands of TtgV, such as skatole. The broad specificity of TtgV makes it a useful target for directed evolution and protein engineering toward desired specificity. TtgV, as an indole-derivative biosensor, is a promising genetic component for the detection of compounds with biological activities relevant to health and the gut microbiome.

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.

Transcription factor-based biosensor: A molecular-guided approach for advanced biofuel synthesis

As a sustainable and renewable alternative to petroleum fuels, advanced biofuels shoulder the responsibility of energy saving, emission reduction and environmental protection. Traditional engineering of cell factories for production of advanced biofuels lacks efficient high-throughput screening tools and regulating systems, impeding the improvement of cellular productivity and yield. Transcription factor-based biosensors have been widely applied to monitor and regulate microbial cell factory products due to the advantages of fast detection and in-situ screening. This review updates the design and application of transcription factor-based biosensors tailored for advanced biofuels and related intermediates. The construction and genetic parts selection principle of biosensors are discussed. Strategies to enhance the performance of biosensor, including regulating promoter strength and RBS strength, optimizing plasmid copy number, implementing genetic amplifier, and modulating the structure of transcription factor, have also been summarized. We further review the application of biosensors in high-throughput screening of new metabolic engineering targets, evolution engineering, confirmation of protein function, and dynamic regulation of metabolic flux for higher production of advanced biofuels. At last, we discuss the current limitations and future trends of transcription factor-based biosensors.

Combinatorial optimization of gene expression through recombinase-mediated promoter and terminator shuffling in yeast

Microbes are increasingly employed as cell factories to produce biomolecules. This often involves the expression of complex heterologous biosynthesis pathways in host strains. Achieving maximal product yields and avoiding build-up of (toxic) intermediates requires balanced expression of every pathway gene. However, despite progress in metabolic modeling, the optimization of gene expression still heavily relies on trial-and-error. Here, we report an approach for in vivo, multiplexed Gene Expression Modification by LoxPsym-Cre Recombination (GEMbLeR). GEMbLeR exploits orthogonal LoxPsym sites to independently shuffle promoter and terminator modules at distinct genomic loci. This approach facilitates creation of large strain libraries, in which expression of every pathway gene ranges over 120-fold and each strain harbors a unique expression profile. When applied to the biosynthetic pathway of astaxanthin, an industrially relevant antioxidant, a single round of GEMbLeR improved pathway flux and doubled production titers. Together, this shows that GEMbLeR allows rapid and efficient gene expression optimization in heterologous biosynthetic pathways, offering possibilities for enhancing the performance of microbial cell factories.

Coupling High-Throughput and Targeted Screening for Identification of Nonobvious Metabolic Engineering Targets

Identification of metabolic engineering targets is a fundamental challenge in strain development programs. While high-throughput (HTP) genetic engineering methodologies capable of generating vast diversity are being developed at a rapid rate, a majority of industrially interesting molecules cannot be screened at sufficient throughput to leverage these techniques. We propose a workflow that couples HTP screening of common precursors (e.g., amino acids) that can be screened either directly or by artificial biosensors, with low-throughput targeted validation of the molecule of interest to uncover nonintuitive beneficial metabolic engineering targets and combinations hereof. Using this workflow, we identified several nonobvious novel targets for improving p-coumaric acid (p-CA) and l-DOPA production from two large 4k gRNA libraries each deregulating 1000 metabolic genes in the yeast Saccharomyces cerevisiae. We initially screened yeast cells transformed with gRNA library plasmids for individual regulatory targets improving the production of l-tyrosine-derived betaxanthins, identifying 30 targets that increased intracellular betaxanthin content 3.5-5.7 fold. Hereafter, we screened the targets individually in a high-producing p-CA strain, narrowing down the targets to six that increased the secreted titer by up to 15%. To investigate whether any of the six targets could be additively combined to improve p-CA production further, we created a gRNA multiplexing library and subjected it to our proposed coupled workflow. The combination of regulating PYC1 and NTH2 simultaneously resulted in the highest (threefold) improvement of the betaxanthin content, and an additive trend was also observed in the p-CA strain. Lastly, we tested the initial 30 targets in a l-DOPA producing strain, identifying 10 targets that increased the secreted titer by up to 89%, further validating our screening by proxy workflow. This coupled approach is useful for strain development in the absence of direct HTP screening assays for products of interest.

Flow cytometry-based high-throughput screening of synthetic peptides for palladium adsorption

Conventionally, the measurement of metal ion adsorption capacity in biosorbent relies on expensive and time-consuming ICP-OES technique. Herein, a semi-quantitative method to measure Pd(II) adsorption capacity of single cells has been presented by analyzing side scatter (SSC) intensity in flow cytometry. Within the sensitive range and applicable conditions, excellent linearity correlation (R2 ranges from 0.89 to 0.96) between the amount of Pd(II) absorbed on yeast and the fold increase in SSC intensity has been observed. Using this method, six strains with high Pd adsorption capacities have sorted from a yeast library with metal-binding peptides displayed (up to 107 strains) based on SSC signal intensity. The optimal peptide (EF1) displayed on yeast and E. coli surface demonstrated Pd adsorption improvements of ∼32% and ∼200%, respectively. In summary, our study proposes an alternative high-throughput method for analyzing the Pd(II) adsorption capacity of individual yeast cells, enabling the screening of specific peptides/proteins with high Pd(II) affinity from extensive libraries.

Improving pathway prediction accuracy of constraints-based metabolic network models by treating enzymes as microcompartments

Metabolic network models have become increasingly precise and accurate as the most widespread and practical digital representations of living cells. The prediction functions were significantly expanded by integrating cellular resources and abiotic constraints in recent years. However, if unreasonable modeling methods were adopted due to a lack of consideration of biological knowledge, the conflicts between stoichiometric and other constraints, such as thermodynamic feasibility and enzyme resource availability, would lead to distorted predictions. In this work, we investigated a prediction anomaly of EcoETM, a constraints-based metabolic network model, and introduced the idea of enzyme compartmentalization into the analysis process. Through rational combination of reactions, we avoid the false prediction of pathway feasibility caused by the unrealistic assumption of free intermediate metabolites. This allowed us to correct the pathway structures of l-serine and l-tryptophan. A specific analysis explains the application method of the EcoETM-like model and demonstrates its potential and value in correcting the prediction results in pathway structure by resolving the conflict between different constraints and incorporating the evolved roles of enzymes as reaction compartments. Notably, this work also reveals the trade-off between product yield and thermodynamic feasibility. Our work is of great value for the structural improvement of constraints-based models.

High-throughput feedback-enabled optogenetic stimulation and spectroscopy in microwell plates

The ability to perform sophisticated, high-throughput optogenetic experiments has been greatly enhanced by recent open-source illumination devices that allow independent programming of light patterns in single wells of microwell plates. However, there is currently a lack of instrumentation to monitor such experiments in real time, necessitating repeated transfers of the samples to stand-alone analytical instruments, thus limiting the types of experiments that could be performed. Here we address this gap with the development of the optoPlateReader (oPR), an open-source, solid-state, compact device that allows automated optogenetic stimulation and spectroscopy in each well of a 96-well plate. The oPR integrates an optoPlate illumination module with a module called the optoReader, an array of 96 photodiodes and LEDs that allows 96 parallel light measurements. The oPR was optimized for stimulation with blue light and for measurements of optical density and fluorescence. After calibration of all device components, we used the oPR to measure growth and to induce and measure fluorescent protein expression in E. coli. We further demonstrated how the optical read/write capabilities of the oPR permit computer-in-the-loop feedback control, where the current state of the sample can be used to adjust the optical stimulation parameters of the sample according to pre-defined feedback algorithms. The oPR will thus help realize an untapped potential for optogenetic experiments by enabling automated reading, writing, and feedback in microwell plates through open-source hardware that is accessible, customizable, and inexpensive.

The latest advances on soy sauce research in the past decade: Emphasis on the advances in China

As an indispensable soybean-fermented condiment, soy sauce is extensively utilized in catering, daily cooking and food industry in East Asia and Southeast Asia and is becoming popular in the whole world. In the past decade, researchers began to pay great importance to the scientific research of soy sauce, which remarkably promoted the advances on fermentation strains, quality, safety, function and other aspects of soy sauce. Of them, the screening and reconstruction of Aspergillus oryzae with high-yield of salt and acid-tolerant proteases, mechanism of soy sauce flavor formation, improvement of soy sauce quality through the combination of novel physical processing technique and microbial/enzyme, separation and identification of soy sauce functional components are attracting more attention of researchers, and related achievements have been reported continually. Meanwhile, we pointed out the drawbacks of the above research and the future research directions based on published literature and our knowledge. We believe that this review can provide an insightful reference for international related researchers to understand the advances on soy sauce research.

Efficient Simultaneous Detection of Metabolites Based on Electroenzymatic Assembly Strategy

Objective and Impact Statement: We describe an electroenzymatic mediator (EM) sensor based on an electroenzymatic assembly peak separation strategy, which can efficiently realize the simultaneous detection of 3 typical cardiovascular disease (CVD) metabolites in 5 μl of plasma under one test. This work has substantial implications toward improving the efficiency of chronic CVD assessment. Introduction: Monitoring CVD of metabolites is strongly associated with disease risk. Independent and time-consuming detection in hospitals is unfavorable for chronic CVD management. Methods: The EM was flexibly designed by the cross-linking of electron mediators and enzymes, and 3 EM layers with different characteristics were assembled on one electrode. Electrons were transferred under tunable potential; 3 metabolites were quantitatively detected by 3 peak currents that correlated with metabolite concentrations. Results: In this study, the EM sensor showed high sensitivity for the simultaneous detection of 3 metabolites with a lower limit of 0.01 mM. The linear correlation between the sensor and clinical was greater than 0.980 for 242 patients, and the consistency of risk assessment was 94.6%. Conclusion: Metabolites could be expanded by the EM, and the sensor could be a promising candidate as a home healthcare tool for CVD risk assessment.

Analysis of acid-tolerance mechanism based on membrane microdomains in Saccharomyces cerevisiae

BACKGROUND

Saccharomyces cerevisiae has been used in the biosynthesis of acid products such as organic acids owing to its acid tolerance. Improving the acid tolerance of S. cerevisiae is beneficial for expanding its application range. Our previous study isolated the TAMC strain that was tolerant to a pH 2.3 through adaptive laboratory evolution; however, its mechanism underlying tolerance to low pH environment remains unclear.

RESULTS

In this study, through visual observation and order analysis of plasma membrane and membrane microdomains, we revealed that the membrane microdomains of TAMC strain play an indispensable role in acid tolerance. Transcriptomic analysis showed an increase in the expression of genes related to key components of membrane microdomains in TAMC strain. Furthermore, an obvious reduction was observed in the acid tolerance of the strain with sterol C-24 methyltransferase encoding gene ERG6 knockout for inhibiting membrane microdomain formation. Finally, colocalization analysis of H+-ATPase PMA1 and plasma membrane protein PMP1 showed that disruption of membrane microdomains could inhibit the formation of the H+-ATPase complex.

CONCLUSIONS

Membrane microdomains could provide a platform for forming H+-ATPase complexes to facilitate intracellular H+ homeostasis, and thereby improve cell acid resistance. This study proposed a novel acid tolerance mechanism, providing a new direction for the rational engineering of acid-tolerant strains.

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.

Genome-wide analysis reveals Hsf1 maintains high transcript abundance of target genes controlled by strong constitutive promoter in Saccharomyces cerevisiae

BACKGROUND

In synthetic biology, the strength of promoter elements is the basis for precise regulation of target gene transcription levels, which in turn increases the yield of the target product. However, the results of many researches proved that excessive transcription levels of target genes actually reduced the yield of the target product. This phenomenon has been found in studies using different microorganisms as chassis cells, thus, it becomes a bottleneck problem to improve the yield of the target product.

RESULTS

In this study, promoters PGK1p and TDH3p with different strengths were used to regulate the transcription level of alcohol acetyl transferase encoding gene ATF1. The results demonstrated that the strong promoter TDH3p decreased the production of ethyl acetate. The results of Real-time PCR proved that the transcription level of ATF1 decreased rapidly under the control of TDH3p, and the unfolded protein reaction was activated, which may be the reason for the abnormal production caused by the strong promoter. RNA-sequencing analysis showed that the overexpression of differential gene HSP30 increased the transcriptional abundance of ATF1 gene and production of ethyl acetate. Interestingly, deletion of the heat shock protein family (e.g., Hsp26, Hsp78, Hsp82) decreased the production of ethyl acetate, suggesting that the Hsp family was also involved in the regulation of ATF1 gene transcription. Furthermore, the results proved that the Hsf1, an upstream transcription factor of Hsps, had a positive effect on alleviating the unfolded protein response and that overexpression of Hsf1 reprogramed the pattern of ATF1 gene transcript levels. The combined overexpression of Hsf1 and Hsps further increased the production of ethyl acetate. In addition, kinase Rim15 may be involved in this regulatory pathway. Finally, the regulation effect of Hsf1 on recombinant strains constructed by other promoters was verified, which confirmed the universality of the strategy.

CONCLUSIONS

Our results elucidated the mechanism by which Rim15-Hsf1-Hsps pathway reconstructed the repression of high transcription level stress and increased the production of target products, thereby providing new insights and application strategies for the construction of recombinant strains in synthetic biology.

Metabolic reprogramming and biosensor-assisted mutagenesis screening for high-level production of L-arginine in Escherichia coli

L-arginine is a value-added amino acid with promising applications in the pharmaceutical and nutraceutical industries. Further unleashing the potential of microbial cell factories to make L-arginine production more competitive remains challenging due to the sophisticated intracellular interaction networks and the insufficient knowledge of global metabolic regulation. Here, we combined multilevel rational metabolic engineering with biosensor-assisted mutagenesis screening to exploit the L-arginine production potential of Escherichia coli. First, multiple metabolic pathways were systematically reprogrammed to redirect the metabolic flux into L-arginine synthesis, including the L-arginine biosynthesis, TCA cycle, and L-arginine export. Specifically, a toggle switch responding to special cellular physiological conditions was designed to dynamically control the expression of sucA and pull more carbon flux from the TCA cycle toward L-arginine biosynthesis. Subsequently, a biosensor-assisted high-throughput screening platform was designed and applied to further exploit the L-arginine production potential. The best-engineered ARG28 strain produced 132 g/L L-arginine in a 5-L bioreactor with a yield of 0.51 g/g glucose and productivity of 2.75 g/(L ⋅ h), which were the highest values reported so far. Through whole genome sequencing and reverse engineering, Frc frameshift mutant, PqiB A78P mutant, and RpoB P564T mutant were revealed for enhancing the L-arginine biosynthesis. Our study exhibited the power of coupling rational metabolic reprogramming and biosensor-assisted mutagenesis screening to unleash the cellular potential for value-added metabolite production.

Highly efficient neutralizer-free l-malic acid production using engineered Saccharomyces cerevisiae

In industrial bioproduction of organic acids, numerous neutralizers are required which substantially increases production costs and burdens the environment. To address this challenge, a Saccharomyces cerevisiae mutant (named TAMC) with a low pH tolerance (pH 2.3) was isolated by adaptive laboratory evolution. Taking the synthesis of l-malic acid as an example, the malate dehydrogenase 3 without signal peptide (MDHΔSKL) and pyruvate carboxylase 2 (PYC2) were overexpressed in cytoplasmic synthesis pathway, and the l-malic acid titer increased 5.6-fold. Subsequently, the malic acid transporter SpMae1 was designed, and the extracellular l-malic acid titer was increased from 7.3 to 73.6 g/L. Furthermore, by optimizing the synthesis of the precursor pyruvate, the titer reached 81.8 g/L. Finally, without any neutralizer, the titer in the 3-L bioreactor reached 232.9 g/L, the highest l-malic acid titer reported to date. Herein, the engineered l-malic acid overproducer paves the way for the large-scale green production of l-malic acid.

Combinatorial library design for improving isobutanol production in Saccharomyces cerevisiae

Saccharomyces cerevisiae is the dominant fermentative producer of ethanol in industry and a preferred host for production of other biofuels. That said, rewiring the metabolism of S. cerevisiae to produce other fermentation products, such as isobutanol, remains an academic challenge. Many studies report aerobic production of isobutanol, but ethanol remains a substantial by-product under these conditions due to the Crabtree effect. These studies indicate that the native isobutanol pathway is incapable of carrying sufficient flux to displace ethanol. In this report, we screened a combinatorial library of pathway enzymes to identify an isobutanol pathway cassette capable of supporting the growth of a non-ethanol producing S. cerevisiae. We began by identifying a diverse set of isobutanol pathway enzyme homologs and combined each open reading frame with varied-strength promoters in a combinatorial, pooled fashion. We applied a growth-coupled screen where a functional isobutanol pathway restored NAD⁺ regeneration during glucose catabolism that is otherwise repressed via the Crabtree effect. Using this screen, we isolated a cassette consisting of a mosaic of bacterial and cytosol-localized fungal enzymes that conferred under aerobic conditions the ability to produce 364 mg/L isobutanol (8.8% of the theoretical maximum yield). We next shifted the cofactor usage of the isolated ketol-acid reductoisomerase enzyme in the cassette from NADPH to NADH-preferring to improve redox balance. The approach used herein isolated isobutanol producing strains that approach the best in the literature without producing substantial ethanol titers. Still, the best isolated cassette was insufficient to support anaerobic growth in the absence of ethanol fermentation - indicating the presence of further fundamental gaps in our understanding of yeast fermentation.

Enhancing the Production of Pinene in Escherichia coli by Using a Combination of Shotgun, Product-Tolerance and I-SceI Cleavage Systems

Simple Summary

The limit screening method (LMS method) and product-tolerance engineering was proposed and applied. AcrB, flgFG, motB and ndk were found to be associated with an enhanced tolerance of E. coli to pinene. Using the I-SceI cleavage system, the promoters of acrB, flgFG, and ndk genes were replaced with P37, and pinene production was eventually increased 2.1 times. In general, a combination of shotgun, product-tolerance, and I-SceI cleavage systems provides a more convenient and efficient way of enhancing the synthesis of target products in a host strain.

Abstract

Tolerance breeding through genetic engineering, sequence and omics analyses, and gene identification processes are widely used to synthesize biofuels. The majority of related mechanisms have been shown to yield endogenous genes with high expression. However, the process was time-consuming and labor-intensive, meaning there is a need to address the problems associated with the low-throughput screening method and significant time and money consumption. In this study, a combination of the limit screening method (LMS method) and product-tolerance engineering was proposed and applied. The Escherichia coli MG1655 genomic DNA library was constructed using the shotgun method. Then, the cultures were incubated at concentrations of 0.25%, 0.5%, 0.75% and 1.0% of pinene with different inhibitory effects. Finally, the genes acrB, flgFG, motB and ndk were found to be associated with the enhanced tolerance of E. coli to pinene. Using the I-SceI cleavage system, the promoters of acrB, flgFG and ndk genes were replaced with P37. The final strain increased the production of pinene from glucose by 2.1 times.

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

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