Development of bifunctional biosensors for sensing and dynamic control of glycolysis flux in metabolic engineering

Insights into the regulatory mechanisms and application prospects of the transcription factor Cra

Cra (catabolite repressor/activator) is a global transcription factor (TF) that plays a pleiotropic role in controlling the transcription of several genes involved in carbon utilization and energy metabolism. Multiple studies have investigated the regulatory mechanism of Cra and its rational use for metabolic regulation, but due to the complexity of its regulation, there remain challenges in the efficient use of Cra. Here, the structure, mechanism of action, and regulatory function of Cra in carbon and nitrogen flow are reviewed. In addition, this paper highlights the application of Cra in metabolic engineering, including the promotion of metabolite biosynthesis, the regulation of stress tolerance and virulence, the use of a Cra-based biosensor, and its coupling with other transcription factors. Finally, the prospects of Cra-related regulatory strategies are discussed. This review provides guidance for the rational design and construction of Cra-based metabolic regulation systems.

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.

Genome analysis of a newly isolated Bacillus velezensis-YW01 for biodegrading acetaldehyde

Acetaldehyde (AL), a primary carcinogen, not only pollutes the environment, but also endangers human health after drinking alcohol. Here a promising bacterial strain was successfully isolated from a white wine cellar pool in the province of Shandong, China, and identified as Bacillus velezensis-YW01 with 16 S rDNA sequence. Using AL as sole carbon source, initial AL of 1 g/L could be completely biodegraded by YW01 within 84 h and the cell-free extracts of YW01 has also been detected to biodegrade the AL, which indicate that YW01 is a high-potential strain for the biodegradation of AL. The optimal culture conditions and the biodegradation of AL of YW01 are at pH 7.0 and 38 °C, respectively. To further analyze the biodegradation mechanism of AL, the whole genome of YW01 was sequenced. Genes ORF1040, ORF1814 and ORF0127 were revealed in KEGG, which encode for acetaldehyde dehydrogenase. Furthermore, ORF0881 and ORF052 encode for ethanol dehydrogenase. This work provides valuable information for exploring metabolic pathway of converting ethanol to AL and subsequently converting AL to carboxylic acid compounds, which opened up potential pathways for the development of microbial catalyst against AL.

AI-Assisted Rational Design and Activity Prediction of Biological Elements for Optimizing Transcription-Factor-Based Biosensors

The rational design, activity prediction, and adaptive application of biological elements (bio-elements) are crucial research fields in synthetic biology. Currently, a major challenge in the field is efficiently designing desired bio-elements and accurately predicting their activity using vast datasets. The advancement of artificial intelligence (AI) technology has enabled machine learning and deep learning algorithms to excel in uncovering patterns in bio-element data and predicting their performance. This review explores the application of AI algorithms in the rational design of bio-elements, activity prediction, and the regulation of transcription-factor-based biosensor response performance using AI-designed elements. We discuss the advantages, adaptability, and biological challenges addressed by the AI algorithms in various applications, highlighting their powerful potential in analyzing biological data. Furthermore, we propose innovative solutions to the challenges faced by AI algorithms in the field and suggest future research directions. By consolidating current research and demonstrating the practical applications and future potential of AI in synthetic biology, this review provides valuable insights for advancing both academic research and practical applications in biotechnology.

Engineering microbial metabolic homeostasis for chemicals production

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

Bacterial genome reduction for optimal chassis of synthetic biology: a review

Bacteria with streamlined genomes, that harbor full functional genes for essential metabolic networks, are able to synthesize the desired products more effectively and thus have advantages as production platforms in industrial applications. To obtain streamlined chassis genomes, a large amount of effort has been made to reduce existing bacterial genomes. This work falls into two categories: rational and random reduction. The identification of essential gene sets and the emergence of various genome-deletion techniques have greatly promoted genome reduction in many bacteria over the past few decades. Some of the constructed genomes possessed desirable properties for industrial applications, such as: increased genome stability, transformation capacity, cell growth, and biomaterial productivity. The decreased growth and perturbations in physiological phenotype of some genome-reduced strains may limit their applications as optimized cell factories. This review presents an assessment of the advancements made to date in bacterial genome reduction to construct optimal chassis for synthetic biology, including: the identification of essential gene sets, the genome-deletion techniques, the properties and industrial applications of artificially streamlined genomes, the obstacles encountered in constructing reduced genomes, and the future perspectives.

Minimizing endogenous cryptic plasmids to construct antibiotic-free expression systems for Escherichia coli Nissle 1917

The probiotic bacterium Escherichia coli Nissle 1917 (EcN) holds significant promise for use in clinical and biological industries. However, the reliance on antibiotics to maintain plasmid-borne genes has overshadowed its benefits. In this study, we addressed this issue by engineering the endogenous cryptic plasmids pMUT1 and pMUT2. The non-essential elements were removed to create more stable derivatives pMUT1NR△ and pMUT2HBC△. Synthetic promoters by integrating binding motifs on sigma factors were further constructed and applied for expression of Bacteroides thetaiotaomicron heparinase III and the biosynthesis of ectoine. Compared to traditional antibiotic-dependent expression systems, our newly constructed antibiotic-free expression systems offer considerable advantages for clinical and synthetic biology applications.

Flux optimization using multiple promoters in Halomonas bluephagenesis as a model chassis of the next generation industrial biotechnology

Predictability and robustness are challenges for bioproduction because of the unstable intracellular synthetic activities. With the deeper understanding of the gene expression process, fine-tuning has become a meaningful tool for biosynthesis optimization. This study characterized several gene expression elements and constructed a multiple inducible system that responds to ten different small chemical inducers in halophile bacterium Halomonas bluephagenesis. Genome insertion of regulators was conducted for the purpose of gene cluster stabilization and regulatory plasmid simplification. Additionally, dynamic ranges of the multiple inducible systems were tuned by promoter sequence mutations to achieve diverse scopes for high-resolution gene expression control. The multiple inducible system was successfully employed to precisely control chromoprotein expression, lycopene and poly-3-hydroxybutyrate (PHB) biosynthesis, resulting in colorful bacterial pictures, optimized cell growth, lycopene and PHB accumulation. This study demonstrates a desirable approach for fine-tuning of rational and efficient gene expressions, displaying the significance for metabolic pathway optimization.

Mechanisms and biotechnological applications of transcription factors

Transcription factors play an indispensable role in maintaining cellular viability and finely regulating complex internal metabolic networks. These crucial bioactive functions rely on their ability to respond to effectors and concurrently interact with binding sites. Recent advancements have brought innovative insights into the understanding of transcription factors. In this review, we comprehensively summarize the mechanisms by which transcription factors carry out their functions, along with calculation and experimental-based methods employed in their identification. Additionally, we highlight recent achievements in the application of transcription factors in various biotechnological fields, including cell engineering, human health, and biomanufacturing. Finally, the current limitations of research and provide prospects for future investigations are discussed. This review will provide enlightening theoretical guidance for transcription factors engineering.

Biosensors in microalgae: A roadmap for new opportunities in synthetic biology and biotechnology

Biosensors are powerful tools to investigate, phenotype, improve and prototype microbial strains, both in fundamental research and in industrial contexts. Genetic and biotechnological developments now allow the implementation of synthetic biology approaches to novel different classes of microbial hosts, for example photosynthetic microalgae, which offer unique opportunities. To date, biosensors have not yet been implemented in phototrophic eukaryotic microorganisms, leaving great potential for novel biological and technological advancements untapped. Here, starting from selected biosensor technologies that have successfully been implemented in heterotrophic organisms, we project and define a roadmap on how these could be applied to microalgae research. We highlight novel opportunities for the development of new biosensors, identify critical challenges, and finally provide a perspective on the impact of their eventual implementation to tackle research questions and bioengineering strategies. From studying metabolism at the single-cell level to genome-wide screen approaches, and assisted laboratory evolution experiments, biosensors will greatly impact the pace of progress in understanding and engineering microalgal metabolism. We envision how this could further advance the possibilities for unraveling their ecological role, evolutionary history and accelerate their domestication, to further drive them as resource-efficient production hosts.

L-lysine production by systems metabolic engineering of an NADPH auto-regulated Corynebacterium glutamicum

Here, the systems metabolic engineering of L-lysine-overproducing Corynebacterium glutamicum is described to create a highly efficient microorganism producer. The key chromosomal mutations associated with L-lysine synthesis were identified based on whole-genome sequencing. The carbon flux was subsequently redirected into the L-lysine synthesis pathway and increased the availability of energy and product transport systems required for L-lysine synthesis. In addition, a promoter library sensitive to intracellular L-lysine concentration was constructed and applied to regulate the NADPH pool dynamically. In the fed-batch fermentation experiment, the L-lysine titer of the final engineered strain was 223.4 ± 6.5 g/L. This study is the first to improve L-lysine production by enhancing ATP supply and NADPH self-regulation to improve the intracellular environment.

Metabolic engineering and synthetic biology strategies for producing high-value natural pigments in Microalgae

Microalgae are microorganisms capable of producing bioactive compounds using photosynthesis. Microalgae contain a variety of high value-added natural pigments such as carotenoids, phycobilins, and chlorophylls. These pigments play an important role in many areas such as food, pharmaceuticals, and cosmetics. Natural pigments have a health value that is unmatched by synthetic pigments. However, the current commercial production of natural pigments from microalgae is not able to meet the growing market demand. The use of metabolic engineering and synthetic biological strategies to improve the production performance of microalgal cell factories is essential to promote the large-scale production of high-value pigments from microalgae. This paper reviews the health and economic values, the applications, and the synthesis pathways of microalgal pigments. Overall, this review aims to highlight the latest research progress in metabolic engineering and synthetic biology in constructing engineered strains of microalgae with high-value pigments and the application of CRISPR technology and multi-omics in this context. Finally, we conclude with a discussion on the bottlenecks and challenges of microalgal pigment production and their future development prospects.

Metabolic engineering of Halomonas bluephagenesis for high-level mevalonate production from glucose and acetate mixture

Mevalonate (MVA) plays a crucial role as a building block for the biosynthesis of isoprenoids. In this study, we engineered Halomonas bluephagenesis to efficiently produce MVA. Firstly, by screening MVA synthetases from eight different species, the two efficient candidate modules, specifically NADPH-dependent mvaESEfa from Enterococcus faecalis and NADH-dependent mvaESLca from Lactobacillus casei, were integrated into the chromosome, leading to the construction of the H. bluephagenesis MVA11. Through the synergetic utilization of glucose and acetate as mixed carbon sources, MVA11 produced 11.2 g/L MVA with a yield of 0.45 g/g (glucose + acetic acid) in the shake flask. Subsequently, 10 beneficial genes out of 50 targets that could promote MVA production were identified using CRISPR interference. The simultaneous repression of rpoN (encoding RNA polymerase sigma-54 factor) and IldD (encoding L-lactate dehydrogenase) increased MVA titer (13.3 g/L) by 19.23% and yield (0.53 g/g (glucose + acetic acid)) by 17.78%, respectively. Furthermore, introducing the non-oxidative glycolysis (NOG) pathway into MVA11 enhanced MVA yield by 12.20%. Ultimately, by combining these strategies, the resultant H. bluephagenesis MVA13/pli-63 produced 13.9 g/L MVA in the shake flask, and the yield increased to 0.56 g/g (glucose + acetic acid), which was the highest reported so far. Under open fed-batch fermentation conditions, H. bluephagenesis MVA13/pli-63 produced 121 g/L of MVA with a yield of 0.42 g/g (glucose + acetic acid), representing the highest reported titer and yield in the bioreactor to date. This study demonstrates that H. bluephagenesis is one of the most favorable chassis for MVA production.

Bayesian Optimization for Design of Multiscale Biological Circuits

Recent advances in synthetic biology have enabled the construction of molecular circuits that operate across multiple scales of cellular organization, such as gene regulation, signaling pathways, and cellular metabolism. Computational optimization can effectively aid the design process, but current methods are generally unsuited for systems with multiple temporal or concentration scales, as these are slow to simulate due to their numerical stiffness. Here, we present a machine learning method for the efficient optimization of biological circuits across scales. The method relies on Bayesian optimization, a technique commonly used to fine-tune deep neural networks, to learn the shape of a performance landscape and iteratively navigate the design space toward an optimal circuit. This strategy allows the joint optimization of both circuit architecture and parameters, and provides a feasible approach to solve a highly nonconvex optimization problem in a mixed-integer input space. We illustrate the applicability of the method on several gene circuits for controlling biosynthetic pathways with strong nonlinearities, multiple interacting scales, and using various performance objectives. The method efficiently handles large multiscale problems and enables parametric sweeps to assess circuit robustness to perturbations, serving as an efficient in silico screening method prior to experimental implementation.

Microbial Production of Mevalonate

Mevalonate, an important intermediate product of the mevalonate pathway, has a broad spectrum of applications. With the rapid growth of metabolic engineering and synthetic biology, mevalonate biosynthesis by microorganisms is feasible and holds great promise in the future. In this review, we summarize the applications of mevalonate and its derivatives and describe the biosynthesis pathways of mevalonate. The current status of mevalonate biosynthesis is also detailed with an emphasis on metabolic engineering strategies to enhance mevalonate production in typical industrial organisms, including Escherichia coli, Saccharomyces cerevisiae, and Pseudomonas putida, suggesting new insights for the efficient production of biosynthesized mevalonate.

A synthetic population-level oscillator in non-microfluidic environments

Synthetic oscillators have become a research hotspot because of their complexity and importance. The construction and stable operation of oscillators in large-scale environments are important and challenging. Here, we introduce a synthetic population-level oscillator in Escherichia coli that operates stably during continuous culture in non-microfluidic environments without the addition of inducers or frequent dilution. Specifically, quorum-sensing components and protease regulating elements are employed, which form delayed negative feedback to trigger oscillation and accomplish the reset of signals through transcriptional and post-translational regulation. We test the circuit in devices with 1 mL, 50 mL, 400 mL of medium, and demonstrate that the circuit could maintain stable population-level oscillations. Finally, we explore potential applications of the circuit in regulating cellular morphology and metabolism. Our work contributes to the design and testing of synthetic biological clocks that function in large populations.

Metabolic Engineering of Model Microorganisms for the Production of Xanthophyll

Xanthophyll is an oxidated version of carotenoid. It presents significant value to the pharmaceutical, food, and cosmetic industries due to its specific antioxidant activity and variety of colors. Chemical processing and conventional extraction from natural organisms are still the main sources of xanthophyll. However, the current industrial production model can no longer meet the demand for human health care, reducing petrochemical energy consumption and green sustainable development. With the swift development of genetic metabolic engineering, xanthophyll synthesis by the metabolic engineering of model microorganisms shows great application potential. At present, compared to carotenes such as lycopene and β-carotene, xanthophyll has a relatively low production in engineering microorganisms due to its stronger inherent antioxidation, relatively high polarity, and longer metabolic pathway. This review comprehensively summarized the progress in xanthophyll synthesis by the metabolic engineering of model microorganisms, described strategies to improve xanthophyll production in detail, and proposed the current challenges and future efforts needed to build commercialized xanthophyll-producing microorganisms.

De novo design of the global transcriptional factor Cra-regulated promoters enables highly sensitive glycolysis flux biosensor for dynamic metabolic control

Glycolytic flux is a fundamental index in microbial cell factories. A glycolytic flux biosensor that can monitor glucose metabolism efficiency is a promising strategy in rewiring metabolic flux to balance growth and biosynthesis. A key design feature of the glycolytic flux biosensors is the interaction between the global transcriptional factor Cra and its regulated promoters. However, overexpression and mutation of Cra has unpredictable effects on global metabolism in Escherichia coli. Therefore, new orthogonal biosensor design strategies should be developed to circumvent metabolic issues. In this report, the promoters in glycolytic flux biosensor were replaced with synthetic promoters of varying strengths or phage-derived promoters, and the Cra DNA-binding sites were deployed into promoters at different positions and distances to yield biosensors. The de nova biosensors that depended on Cra could sense Fructose-1,6-diphosphate (FBP) with broad dynamic ranges and low basal leakage. Then the negative-response biosensors were applied to fine-tune the target ATP synthesis gene, leading to the desired increase in pyruvate production (the highest 9.66 g/L) and cell growth. Moreover, the membrane synthesis gene plsC was also dynamically activated by the positive-response biosensor, leading to effective accumulation of lycopene in the cell membrane and a 50-fold increase in lycopene titre (100.3 mg/L) when compared with the control strain, demonstrating the effective and broader usages of our biosensors.

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.

Spatial-temporal regulation of fatty alcohol biosynthesis in yeast

BACKGROUND

Construction of efficient microbial cell factories is one of the core steps for establishing green bio-manufacturing processes. However, the complex metabolic regulation makes it challenging in driving the metabolic flux toward the product biosynthesis. Dynamically coupling the biosynthetic pathways with the cellular metabolism at spatial-temporal manner should be helpful for improving the production with alleviating the cellular stresses.

RESULTS

In this study, we observed the mismatch between fatty alcohol biosynthesis and cellular metabolism, which compromised the fatty alcohol production in Saccharomyces cerevisiae. To enhance the fatty alcohol production, we spatial-temporally regulated fatty alcohol biosynthetic pathway by peroxisomal compartmentalization (spatial) and dynamic regulation of gene expression (temporal). In particular, fatty acid/acyl-CoA responsive promoters were identified by comparative transcriptional analysis, which helped to dynamically regulate the expression of acyl-CoA reductase gene MaFAR1 and improved fatty alcohol biosynthesis by 1.62-fold. Furthermore, enhancing the peroxisomal supply of acyl-CoA and NADPH further improved fatty alcohol production to 282 mg/L, 2.52 times higher than the starting strain.

CONCLUSIONS

This spatial-temporal regulation strategy partially coordinated fatty alcohol biosynthesis with cellular metabolism including peroxisome biogenesis and precursor supply, which should be applied for production of other products in microbes.

Advances in the synthesis of three typical tetraterpenoids including β-carotene, lycopene and astaxanthin

Carotenoids are natural pigments that widely exist in nature. Due to their excellent antioxidant, anticancer and anti-inflammatory properties, carotenoids are commonly used in food, medicine, cosmetic and other fields. At present, natural carotenoids are mainly extracted from plants, algae and microorganisms. With the rapid development of metabolic engineering and molecular biology as well as the continuous in-depth study of carotenoids synthesis pathways, industrial microorganisms have showed promising applications in the synthesis of carotenoids. In this review, we introduced the properties of several carotenoids and their biosynthetic metabolism process. Then, the microorganisms synthesizing carotenoids through the natural and non-natural pathways and the extraction methods of carotenoids were summarized and compared. Meanwhile, the influence of substrates on the carotenoids production was also listed. The methods and strategies for achieving high carotenoid production are categorized to help with future research.

Recent Advances Regarding the Physiological Functions and Biosynthesis of D-Allulose

D-Allulose, a generally regarded as safe (GRAS) sugar, is rare in nature. It is among the most promising sweeteners for future use due to its low caloric content, sucrose-like taste, and unique functions. D-Allulose has many physiological effects, such as antiobesity, antihyperglycemia, antidiabetes, anti-inflammatory, antioxidant, and neuroprotective effects. Therefore, D-allulose has important application value in the food, pharmaceutical, and healthcare industries. However, the high cost of D-allulose production limits its large-scale application. Currently, biotransformation is very attractive for D-allulose synthesis, with the two main methods of biosynthesis being the Izumoring strategy and the DHAP-dependent aldolase strategy. This article reviews recent advances regarding the physiological functions and biosynthesis of D-allulose. In addition, future perspectives on the production of D-allulose are presented.

Refactoring transcription factors for metabolic engineering

Due to the ability to regulate target metabolic pathways globally and dynamically, metabolic regulation systems composed of transcription factors have been widely used in metabolic engineering and synthetic biology. This review introduced the categories, action principles, prediction strategies, and related databases of transcription factors. Then, the application of global transcription machinery engineering technology and the transcription factor-based biosensors and quorum sensing systems are overviewed. In addition, strategies for optimizing the transcriptional regulatory tools' performance by refactoring transcription factors are summarized. Finally, the current limitations and prospects of constructing various regulatory tools based on transcription factors are discussed. This review will provide theoretical guidance for the rational design and construction of transcription factor-based metabolic regulation systems.