Systems Metabolic Engineering Strategies: Integrating Systems and Synthetic Biology with Metabolic Engineering

Facilitating stable gene integration expression and copy number amplification in Bacillus subtilis through a reversible homologous recombination switch

Strengthening the expression level of integrated genes on the genome is crucial for consistently expressing key enzymes in microbial cell factories for efficient bioproduction in synthetic biology. In comparison to plasmid-based multi-copy expression, the utilization of chromosomal multi-copy genes offers increased stability of expression level, diminishes the metabolic burden on host cells, and enhances overall genetic stability. In this study, we developed the "BacAmp", a stabilized gene integration expression and copy number amplification system for high-level expression in Bacillus subtilis, which was achieved by employing a combination of repressor and non-natural amino acids (ncAA)-dependent expression system to create a reversible switch to control the key gene recA for homologous recombination. When the reversible switch is turned on, genome editing and gene amplification can be achieved. Subsequently, the reversible switch was turned off therefore stabilizing the gene copy number. The stabilized gene amplification system marked by green fluorescent protein, achieved a 3-fold increase in gene expression by gene amplification and maintained the average gene copy number at 10 after 110 generations. When we implemented the gene amplification system for the regulation of N-acetylneuraminic acid (NeuAc) synthesis, the copy number of the critical gene increased to an average of 7.7, which yielded a 1.3-fold NeuAc titer. Our research provides a new avenue for gene expression in synthetic biology and can be applied in metabolic engineering in B. subtilis.

Debottlenecking the L-DOPA 4,5-dioxygenase step with enhanced tyrosine supply boosts betalain production in Nicotiana benthamiana

Synthetic biology provides emerging tools to produce valuable compounds in plant hosts as sustainable chemical production platforms. However, little is known about how supply and utilization of precursors is coordinated at the interface of plant primary and specialized metabolism, limiting our ability to efficiently produce high levels of target specialized metabolites in plants. L-Tyrosine is an aromatic amino acid precursor of diverse plant natural products including betalain pigments, which are used as the major natural food red colorants and more recently a visual marker for plant transformation. Here, we studied the impact of enhanced L-tyrosine supply on the production of betalain pigments by expressing arogenate dehydrogenase (TyrA) from table beet (Beta vulgaris, BvTyrAα), which has relaxed feedback inhibition by L-tyrosine. Unexpectedly, betalain levels were reduced when BvTyrAα was coexpressed with the betalain pathway genes in Nicotiana benthamiana leaves; L-tyrosine and 3,4-dihydroxy-L-phenylalanine (L-DOPA) levels were drastically elevated but not efficiently converted to betalains. An additional expression of L-DOPA 4,5-dioxygenase (DODA), but not CYP76AD1 or cyclo-DOPA 5-O-glucosyltransferase, together with BvTyrAα and the betalain pathway, drastically enhanced betalain production, indicating that DODA is a major rate-limiting step of betalain biosynthesis in this system. Learning from this initial test and further debottlenecking the DODA step maximized betalain yield to an equivalent or higher level than that in table beet. Our data suggest that balancing between enhanced supply ("push") and effective utilization ("pull") of precursor by alleviating a bottleneck step is critical in successful plant synthetic biology to produce high levels of target compounds.

Microbial synthesis of anthocyanins and pyranoanthocyanins: current bottlenecks and potential solutions

Anthocyanins (ACNs) are secondary metabolites found in plants. Due to their impressive biological activities, ACNs have gained significant popularity and extensive application within the food, pharmaceutical, and nutraceutical industries. A derivative of ACNs: pyranoanthocyanins (PACNs) possesses more stable properties and interesting biological activities. However, conventional methods for the production of ACNs, including chemical synthesis and plant extraction, involve organic solvents. Microbial synthesis of ACNs from renewable biomass, such as amino acids or flavonoids, is considered a sustainable and environmentally friendly method for large-scale production of ACNs. Recently, the construction of microbial cell factories (MCFs) for the efficient biosynthesis of ACNs and PACNs has attracted much attention. In this review, we summarize the cases of microbial synthesis of ACNs, and analyze the bottlenecks in reconstructing the metabolic pathways for synthesizing PACNs in microorganisms. Consequently, there is an urgent need to investigate the mechanisms behind the development of MCFs for PACNs synthesis. Such research also holds significant promise for advancing the production of food pigments. Meanwhile, we propose potential solutions to the bottleneck problem based on metabolic engineering and enzyme engineering. Finally, the development prospects of natural food and biotechnology are discussed.

Advancing microbial production through artificial intelligence-aided biology

Microbial cell factories (MCFs) have been leveraged to construct sustainable platforms for value-added compound production. To optimize metabolism and reach optimal productivity, synthetic biology has developed various genetic devices to engineer microbial systems by gene editing, high-throughput protein engineering, and dynamic regulation. However, current synthetic biology methodologies still rely heavily on manual design, laborious testing, and exhaustive analysis. The emerging interdisciplinary field of artificial intelligence (AI) and biology has become pivotal in addressing the remaining challenges. AI-aided microbial production harnesses the power of processing, learning, and predicting vast amounts of biological data within seconds, providing outputs with high probability. With well-trained AI models, the conventional Design-Build-Test (DBT) cycle has been transformed into a multidimensional Design-Build-Test-Learn-Predict (DBTLP) workflow, leading to significantly improved operational efficiency and reduced labor consumption. Here, we comprehensively review the main components and recent advances in AI-aided microbial production, focusing on genome annotation, AI-aided protein engineering, artificial functional protein design, and AI-enabled pathway prediction. Finally, we discuss the challenges of integrating novel AI techniques into biology and propose the potential of large language models (LLMs) in advancing microbial production.

Microbial Synthetic Epigenetic Tools Design and Applications

Microbial synthetic epigenetics offers significant opportunities for the design of synthetic biology tools by leveraging reversible gene control mechanisms without altering DNA sequences. However, limited understanding and a lack of technologies for thorough analysis of the mechanisms behind epigenetic modifications have hampered their utilization in biotechnological applications. In this review, we explore advancements in developing epigenetic-based synthetic gene regulatory tools at both transcriptional and post-transcriptional levels. Furthermore, we examine strategies developed to construct epigenetic-based circuits that provide controllable and stable gene regulation, aiming to boost the performance of microbial chassis cells. Finally, we discuss the current challenges and perspectives in the development of synthetic epigenetic tools.

Bridging Nature and Engineering: Protein-Derived Materials for Bio-Inspired Applications

The sophisticated, elegant protein-polymers designed by nature can serve as inspiration to redesign and biomanufacture protein-based materials using synthetic biology. Historically, petro-based polymeric materials have dominated industrial activities, consequently transforming our way of living. While this benefits humans, the fabrication and disposal of these materials causes environmental sustainability challenges. Fortunately, protein-based biopolymers can compete with and potentially surpass the performance of petro-based polymers because they can be biologically produced and degraded in an environmentally friendly fashion. This paper reviews four groups of protein-based polymers, including fibrous proteins (collagen, silk fibroin, fibrillin, and keratin), elastomeric proteins (elastin, resilin, and wheat glutenin), adhesive/matrix proteins (spongin and conchiolin), and cyanophycin. We discuss the connection between protein sequence, structure, function, and biomimetic applications. Protein engineering techniques, such as directed evolution and rational design, can be used to improve the functionality of natural protein-based materials. For example, the inclusion of specific protein domains, particularly those observed in structural proteins, such as silk and collagen, enables the creation of novel biomimetic materials with exceptional mechanical properties and adaptability. This review also discusses recent advancements in the production and application of new protein-based materials through the approach of synthetic biology combined biomimetics, providing insight for future research and development of cutting-edge bio-inspired products. Protein-based polymers that utilize nature's designs as a base, then modified by advancements at the intersection of biology and engineering, may provide mankind with more sustainable products.

Engineering principles for rationally design therapeutic strategies against hepatocellular carcinoma

The search for new therapeutic strategies against cancer has favored the emergence of rationally designed treatments. These treatments have focused on attacking cell plasticity mechanisms to block the transformation of epithelial cells into cancerous cells. The aim of these approaches was to control particularly lethal cancers such as hepatocellular carcinoma. However, they have not been able to control the progression of cancer for unknown reasons. Facing this scenario, emerging areas such as systems biology propose using engineering principles to design and optimize cancer treatments. Beyond the possibilities that this approach might offer, it is necessary to know whether its implementation at a clinical level is viable or not. Therefore, in this paper, we will review the engineering principles that could be applied to rationally design strategies against hepatocellular carcinoma, and discuss whether the necessary elements exist to implement them. In particular, we will emphasize whether these engineering principles could be applied to fight hepatocellular carcinoma.

Increasing the efficiency of gene editing with CRISPR-Cas9 via concurrent expression of the Beta protein

Escherichia coli has emerged as an important host for the production of biopharmaceuticals or other industrially relevant molecules. An efficient gene editing tool is indispensable for ensuring high production levels and optimal release of target products. However, in Escherichia coli, the CRISPR-Cas9 system has been shown to achieve gene modifications with relatively low frequency. Large-scale PCR screening is required, hindering the identification of positive clones. The beta protein, which weakly binds to single-stranded DNA but tightly associates with complementary strand annealing products, offers a promising solution to this issue. In the present study, we describe a targeted and continuous gene editing strategy for the Escherichia coli genome. This strategy involves the coexpression of the beta protein alongside the CRISPR-Cas9 system, enabling a variety of genome modifications such as gene deletion and insertion with an efficiency exceeding 80 %. The integrity of beta proteins is essential for the CRISPR-Cas9/Beta-based gene editing system. In this work, the deletion of either the N- or C-terminal domain significantly impaired system efficiency. Overall, our findings established the CRISPR-Cas9/Beta system as a suitable gene editing tool for various applications in Escherichia coli.

Can digital twin efforts shape microorganism-based alternative food?

With the continuous increment in global population growth, compounded by post-pandemic food security challenges due to labor shortages, effects of climate change, political conflicts, limited land for agriculture, and carbon emissions control, addressing food production in a sustainable manner for future generations is critical. Microorganisms are potential alternative food sources that can help close the gap in food production. For the development of more efficient and yield-enhancing products, it is necessary to have a better understanding on the underlying regulatory molecular pathways of microbial growth. Nevertheless, as microbes are regulated at multiomics scales, current research focusing on single omics (genomics, proteomics, or metabolomics) independently is inadequate for optimizing growth and product output. Here, we discuss digital twin (DT) approaches that integrate systems biology and artificial intelligence in analyzing multiomics datasets to yield a microbial replica model for in silico testing before production. DT models can thus provide a holistic understanding of microbial growth, metabolite biosynthesis mechanisms, as well as identifying crucial production bottlenecks. Our argument, therefore, is to support the development of novel DT models that can potentially revolutionize microorganism-based alternative food production efficiency.

Metabolic engineering and fermentation of microorganisms for carotenoids production

Carotenoids are natural pigments that exhibit a wide range of red, orange, and yellow colors and are extensively used in the food, nutraceuticals, cosmetics, and aquaculture industries. While advances in systems metabolic engineering have established a foundation for constructing carotenoid-producing microbial cell factories at a laboratory scale, translating these technologies to industrial scales remains a big challenge. Moreover, there is a need to devise cost-effective methods for downstream processing and purification of carotenoids. In this review, we discuss recent strategies in metabolic engineering, such as metabolic flux optimization, enzyme assembly, and storage capacity engineering, aimed at constructing high-performance carotenoid-producing microbial strains. We also review recent approaches for cost-effective downstream processing and purification of carotenoids.

Expanding the structural diversity of terpenes by synthetic biology approaches

Terpenoids display chemical and structural diversities as well as important biological activities. Despite their extreme variability, the range of these structures is limited by the scope of natural products that canonically derive from interconvertible five-carbon (C5) isoprene units. New approaches have recently been developed to expand their structural diversity. This review systematically explores the combinatorial biosynthesis of noncanonical building blocks via the coexpression of the canonical mevalonate (MVA) pathway and C-methyltransferases (C-MTs), or by using the lepidopteran mevalonate (LMVA) pathway. Unnatural terpenoids can be created from farnesyl diphosphate (FPP) analogs by chemobiological synthesis and terpene cyclopropanation by artificial metalloenzymes (ArMs). Advanced technologies to accelerate terpene biosynthesis are discussed. This review provides a valuable reference for increasing the diversity of valuable terpenoids and their derivatives, as well as for expanding their potential applications.

LowTempGAL: a highly responsive low temperature-inducible GAL system in Saccharomyces cerevisiae

Temperature is an important control factor for biologics biomanufacturing in precision fermentation. Here, we explored a highly responsive low temperature-inducible genetic system (LowTempGAL) in the model yeast Saccharomyces cerevisiae. Two temperature biosensors, a heat-inducible degron and a heat-inducible protein aggregation domain, were used to regulate the GAL activator Gal4p, rendering the leaky LowTempGAL systems. Boolean-type induction was achieved by implementing a second-layer control through low-temperature-mediated repression on GAL repressor gene GAL80, but suffered delayed response to low-temperature triggers and a weak response at 30°C. Application potentials were validated for protein and small molecule production. Proteomics analysis suggested that residual Gal80p and Gal4p insufficiency caused suboptimal induction. 'Turbo' mechanisms were engineered through incorporating a basal Gal4p expression and a galactose-independent Gal80p-supressing Gal3p mutant (Gal3Cp). Varying Gal3Cp configurations, we deployed the LowTempGAL systems capable for a rapid stringent high-level induction upon the shift from a high temperature (37-33°C) to a low temperature (≤30°C). Overall, we present a synthetic biology procedure that leverages 'leaky' biosensors to deploy highly responsive Boolean-type genetic circuits. The key lies in optimisation of the intricate layout of the multi-factor system. The LowTempGAL systems may be applicable in non-conventional yeast platforms for precision biomanufacturing.

Transcending membrane barriers: advances in membrane engineering to enhance the production capacity of microbial cell factories

Microbial cell factories serve as pivotal platforms for the production of high-value natural products, which tend to accumulate on the cell membrane due to their hydrophobic properties. However, the limited space of the cell membrane presents a bottleneck for the accumulation of these products. To enhance the production of intracellular natural products and alleviate the burden on the cell membrane caused by product accumulation, researchers have implemented various membrane engineering strategies. These strategies involve modifying the membrane components and structures of microbial cell factories to achieve efficient accumulation of target products. This review summarizes recent advances in the application of membrane engineering technologies in microbial cell factories, providing case studies involving Escherichia coli and yeast. Through these strategies, researchers have not only improved the tolerance of cells but also optimized intracellular storage space, significantly enhancing the production efficiency of natural products. This article aims to provide scientific evidence and references for further enhancing the efficiency of similar cell factories.

Using metabolic networks to predict cross-feeding and competition interactions between microorganisms

Understanding the interactions between microorganisms and their impact on bacterial behavior at the community level is a key research topic in microbiology. Different methods, relying on experimental or mathematical approaches based on the diverse properties of bacteria, are currently employed to study these interactions. Recently, the use of metabolic networks to understand the interactions between bacterial pairs has increased, highlighting the relevance of this approach in characterizing bacteria. In this study, we leverage the representation of bacteria through their metabolic networks to build a predictive model aimed at reducing the number of experimental assays required for designing bacterial consortia with specific behaviors. Our novel method for predicting cross-feeding or competition interactions between pairs of microorganisms utilizes metabolic network features. Machine learning classifiers are employed to determine the type of interaction from automatically reconstructed metabolic networks. Several algorithms were assessed and selected based on comprehensive testing and careful separation of manually compiled data sets obtained from literature sources. We used different classification algorithms, including K Nearest Neighbors, XGBoost, Support Vector Machine, and Random Forest, tested different parameter values, and implemented several data curation approaches to reduce the biological bias associated with our data set, ultimately achieving an accuracy of over 0.9. Our method holds substantial potential to advance the understanding of community behavior and contribute to the development of more effective approaches for consortia design.IMPORTANCEUnderstanding bacterial interactions at the community level is critical for microbiology, and leveraging metabolic networks presents an efficient and effective approach. The introduction of this novel method for predicting interactions through machine learning classifiers has the potential to advance the field by reducing the number of experimental assays required and contributing to the development of more effective bacterial consortia.

Bioproduction of porphyrins, phycobilins, and their proteins using microbial cell factories: engineering, metabolic regulations, challenges, and perspectives

Porphyrins, phycobilins, and their proteins have abundant π-electrons and strongly absorb visible light, some of which bind a metal ion in the center. Because of the structural and optical properties, they not only play critical roles as an essential component in natural systems but also have attracted much attention as a high value specialty chemical in various fields, including renewable energy, cosmetics, medicines, and foods. However, their commercial application seems to be still limited because the market price of porphyrins and phycobilins is generally expensive to apply them easily. Furthermore, their petroleum-based chemical synthesis is energy-intensive and emits a pollutant. Recently, to replace petroleum-based production, many studies on the bioproduction of metalloporphyrins, including Zn-porphyrin, Co-porphyrin, and heme, porphyrin derivatives including chlorophyll, biliverdin, and phycobilins, and their proteins including hemoproteins, phycobiliproteins, and phytochromes from renewable carbon sources using microbial cell factories have been reported. This review outlines recent advances in the bioproduction of porphyrins, phycobilins, and their proteins using microbial cell factories developed by various microbial biotechnology techniques, provides well-organized information on metabolic regulations of the porphyrin metabolism, and then critically discusses challenges and future perspectives. Through these, it is expected to be able to achieve possible solutions and insights and to develop an outstanding platform to be applied to the industry in future research.

Building Synthetic Cells─From the Technology Infrastructure to Cellular Entities

The de novo construction of a living organism is a compelling vision. Despite the astonishing technologies developed to modify living cells, building a functioning cell "from scratch" has yet to be accomplished. The pursuit of this goal alone has─and will─yield scientific insights affecting fields as diverse as cell biology, biotechnology, medicine, and astrobiology. Multiple approaches have aimed to create biochemical systems manifesting common characteristics of life, such as compartmentalization, metabolism, and replication and the derived features, evolution, responsiveness to stimuli, and directed movement. Significant achievements in synthesizing each of these criteria have been made, individually and in limited combinations. Here, we review these efforts, distinguish different approaches, and highlight bottlenecks in the current research. We look ahead at what work remains to be accomplished and propose a "roadmap" with key milestones to achieve the vision of building cells from molecular parts.

Programming Dynamic Division of Labor Using Horizontal Gene Transfer

The metabolic engineering of microbes has broad applications, including biomanufacturing, bioprocessing, and environmental remediation. The introduction of a complex, multistep pathway often imposes a substantial metabolic burden on the host cell, restraining the accumulation of productive biomass and limiting pathway efficiency. One strategy to alleviate metabolic burden is the division of labor (DOL) in which different subpopulations carry out different parts of the pathway and work together to convert a substrate into a final product. However, the maintenance of different engineered subpopulations is challenging due to competition and convoluted interstrain population dynamics. Through modeling, we show that dynamic division of labor (DDOL), which we define as the DOL between indiscrete populations capable of dynamic and reversible interchange, can overcome these limitations and enable the robust maintenance of burdensome, multistep pathways. We propose that DDOL can be mediated by horizontal gene transfer (HGT) and use plasmid genomics to uncover evidence that DDOL is a strategy utilized by natural microbial communities. Our work suggests that bioengineers can harness HGT to stabilize synthetic metabolic pathways in microbial communities, enabling the development of robust engineered systems for deployment in a variety of contexts.

Siraitia grosvenorii As a Homologue of Food and Medicine: A Review of Biological Activity, Mechanisms of Action, Synthetic Biology, and Applications in Future Food

Siraitia grosvenorii (SG), also known as Luo Han Guo or Monk fruit, boasts a significant history in food and medicine. This review delves into SG's historical role and varied applications in traditional Chinese culture, examining its phytochemical composition and the health benefits of its bioactive compounds. It further explores SG's biological activities, including antioxidant, anti-inflammatory, and antidiabetic properties and elucidates the mechanisms behind these effects. The review also highlights recent synthetic biology advances in enhancing the production of SG's bioactive compounds, presenting new opportunities for broadening their availability. Ultimately, this review emphasizes SG's value in food and medicine, showcasing its historical and cultural importance, phytochemistry, biological functions, action mechanisms, and the role of synthetic biology in its sustainable use.

Mid-Long Chain Dicarboxylic Acid Production via Systems Metabolic Engineering: Progress and Prospects

Mid-to-long-chain dicarboxylic acids (DCAi, i ≥ 6) are organic compounds in which two carboxylic acid functional groups are present at the terminal position of the carbon chain. These acids find important applications as structural components and intermediates across various industrial sectors, including organic compound synthesis, food production, pharmaceutical development, and agricultural manufacturing. However, conventional petroleum-based DCA production methods cause environmental pollution, making sustainable development challenging. Hence, the demand for eco-friendly processes and renewable raw materials for DCA production is rising. Owing to advances in systems metabolic engineering, new tools from systems biology, synthetic biology, and evolutionary engineering can now be used for the sustainable production of energy-dense biofuels. Here, we explore systems metabolic engineering strategies for DCA synthesis in various chassis via the conversion of different raw materials into mid-to-long-chain DCAs. Subsequently, we discuss the future challenges in this field and propose synthetic biology approaches for the efficient production and successful commercialization of these acids.

Enhancing 2-Pyrone Synthase Efficiency by High-Throughput Mass-Spectrometric Quantification and In Vitro/In Vivo Catalytic Performance Correlation

Engineering efficient biocatalysts is essential for metabolic engineering to produce valuable bioproducts from renewable resources. However, due to the complexity of cellular metabolic networks, it is challenging to translate success in vitro into high performance in cells. To meet such a challenge, an accurate and efficient quantification method is necessary to screen a large set of mutants from complex cell culture and a careful correlation between the catalysis parameters in vitro and performance in cells is required. In this study, we employed a mass-spectrometry based high-throughput quantitative method to screen new mutants of 2-pyrone synthase (2PS) for triacetic acid lactone (TAL) biosynthesis through directed evolution in E. coli. From the process, we discovered two mutants with the highest improvement (46 fold) in titer and the fastest kcat (44 fold) over the wild type 2PS, respectively, among those reported in the literature. A careful examination of the correlation between intracellular substrate concentration, Michaelis-Menten parameters and TAL titer for these two mutants reveals that a fast reaction rate under limiting intracellular substrate concentrations is important for in-cell biocatalysis. Such properties can be tuned by protein engineering and synthetic biology to adopt these engineered proteins for the maximum activities in different intracellular environments.

Coupled strategy based on regulator manipulation and medium optimization empowers the biosynthetic overproduction of lincomycin

The biosynthesis of bioactive secondary metabolites, specifically antibiotics, is of great scientific and economic importance. The control of antibiotic production typically involves different processes and molecular mechanism. Despite numerous efforts to improve antibiotic yields, joint engineering strategies for combining genetic manipulation with fermentation optimization remain finite. Lincomycin A (Lin-A), a lincosamide antibiotic, is industrially fermented by Streptomyces lincolnensis. Herein, the leucine-responsive regulatory protein (Lrp)-type regulator SLCG_4846 was confirmed to directly inhibit the lincomycin biosynthesis, whereas indirectly controlled the transcription of SLCG_2919, the first reported repressor in S. lincolnensis. Inactivation of SLCG_4846 in the high-yield S. lincolnensis LA219X (LA219XΔ4846) increases the Lin-A production and deletion of SLCG_2919 in LA219XΔ4846 exhibits superimposed yield increment. Given the effect of the double deletion on cellular primary metabolism of S. lincolnensis, Plackett-Burman design, steepest ascent and response surface methodologies were utilized and employed to optimize the seed medium of this double mutant in shake flask, and Lin-A yield using optimal seed medium was significantly increased over the control. Above strategies were performed in a 15-L fermenter. The maximal yield of Lin-A in LA219XΔ4846-2919 reached 6.56 g/L at 216 h, 55.1 % higher than that in LA219X at the parental cultivation (4.23 g/L). This study not only showcases the potential of this strategy to boost lincomycin production, but also could empower the development of high-performance actinomycetes for other antibiotics.

Repurposing the mammalian RNA-binding protein Musashi-1 as an allosteric translation repressor in bacteria

The RNA recognition motif (RRM) is the most common RNA-binding protein domain identified in nature. However, RRM-containing proteins are only prevalent in eukaryotic phyla, in which they play central regulatory roles. Here, we engineered an orthogonal post-transcriptional control system of gene expression in the bacterium Escherichia coli with the mammalian RNA-binding protein Musashi-1, which is a stem cell marker with neurodevelopmental role that contains two canonical RRMs. In the circuit, Musashi-1 is regulated transcriptionally and works as an allosteric translation repressor thanks to a specific interaction with the N-terminal coding region of a messenger RNA and its structural plasticity to respond to fatty acids. We fully characterized the genetic system at the population and single-cell levels showing a significant fold change in reporter expression, and the underlying molecular mechanism by assessing the in vitro binding kinetics and in vivo functionality of a series of RNA mutants. The dynamic response of the system was well recapitulated by a bottom-up mathematical model. Moreover, we applied the post-transcriptional mechanism engineered with Musashi-1 to specifically regulate a gene within an operon, implement combinatorial regulation, and reduce protein expression noise. This work illustrates how RRM-based regulation can be adapted to simple organisms, thereby adding a new regulatory layer in prokaryotes for translation control.

Rapid screening of point mutations by mismatch amplification mutation assay PCR

Metabolic engineering frequently makes use of point mutation and saturation mutation library creation. At present, sequencing is the only reliable and direct technique to detect point mutation and screen saturation mutation library. In this study, mismatch amplification mutation assay (MAMA) PCR was used to detect point mutation and screen saturation mutation library. In order to fine-tune the expression of odhA encoding 2-oxoglutarate dehydrogenase E1 component, a saturating mutant library of the RBS of odhA was created in Corynebacterium glutamicum P12 based on the CRISPR-Cas2a genome editing system, which increased the L-proline production by 81.3%. MAMA PCR was used to filter out 42% of the non-mutant transformants in the mutant library, which effectively reduced the workload of the subsequent fermentation test and the number of sequenced samples. The rapid and sensitive MAMA-PCR method established in this study provides a general strategy for detecting point mutations and improving the efficiency of mutation library screening. KEY POINTS: • MAMA PCR was optimized and developed to detect point mutation. • MAMA PCR greatly improves the screening efficiency of point mutation. • Attenuation of odhA expression in P12 effectively improves proline production.

Pseudomonas putida as a synthetic biology chassis and a metabolic engineering platform

The soil bacterium Pseudomonas putida, especially the KT2440 strain, is increasingly being utilized as a host for biotransformations of both industrial and environmental interest. The foundations of such performance include its robust redox metabolism, ability to tolerate a wide range of physicochemical stresses, rapid growth, versatile metabolism, nonpathogenic nature, and the availability of molecular tools for advanced genetic programming. These attributes have been leveraged for hosting engineered pathways for production of valuable chemicals or degradation/valorization of environmental pollutants. This has in turn pushed the boundaries of conventional enzymology toward previously unexplored reactions in nature. Furthermore, modifications to the physical properties of the cells have been made to enhance their catalytic performance. These advancements establish P. putida as bona fide chassis for synthetic biology, on par with more traditional metabolic engineering platforms.

Metabolic engineering of Geobacillus thermoglucosidasius for polymer-grade lactic acid production at high temperature

The production and application of biodegradable polylactic acid are still severely hindered by the cost of its polymer-grade lactic acid monomers. High-temperature biomanufacturing has emerged as an increasingly attractive approach to enable low-cost and high-efficiency bulk chemical production. In this study, thermophilic Geobacillus thermoglucosidasius was reprogrammed to obtain optically pure l-lactic acid- and d-lactic acid-producing strains, G. thermoglucosidasius GTD17 and GTD7, by using rational metabolic engineering strategies including pathway construction, by-product elimination, and production enhancing. Moreover, semi-rational adaptive evolution was carried out to further improve their lactic acid synthesis performance. The final strains GTD17-55 and GTD7-144 produce 151.1 g/L of l-lactic acid and 153.1 g/L of d-lactic acid at 60 °C, respectively. In consideration of the high temperature, productive performance of these strains is superior compared to the state-of-the-art industrial strains. This study lays the foundation for the low-cost and efficient production of biodegradable plastic polylactic acid.

Systems Metabolic Engineering of Saccharomyces cerevisiae for the High-Level Production of (2S)-Eriodictyol

(2S)-eriodictyol (ERD) is a flavonoid widely found in citrus fruits, vegetables, and important medicinal plants with neuroprotective, cardioprotective, antidiabetic, and anti-obesity effects. However, the microbial synthesis of ERD is limited by complex metabolic pathways and often results in a low production performance. Here, we engineered Saccharomyces cerevisiae by fine-tuning the metabolism of the ERD synthesis pathway. The results showed that the ERD titer was effectively increased, and the intermediate metabolites levels were reduced. First, we successfully reconstructed the de novo synthesis pathway of p-coumaric acid in S. cerevisiae and fine-tuned the metabolic pathway using promoter engineering and terminator engineering for the high-level production of (2S)-naringenin. Subsequently, the synthesis of ERD was achieved by introducing the ThF3'H gene from Tricyrtis hirta. Finally, by multiplying the copy number of the ThF3'H gene, the production of ERD was further increased, reaching 132.08 mg L-1. Our work emphasizes the importance of regulating the metabolic balance to produce natural products in microbial cell factories.

FastKnock: an efficient next-generation approach to identify all knockout strategies for strain optimization

Overproduction of desired native or nonnative biochemical(s) in (micro)organisms can be achieved through metabolic engineering. Appropriate rewiring of cell metabolism is performed by making rational changes such as insertion, up-/down-regulation and knockout of genes and consequently metabolic reactions. Finding appropriate targets (including proper sets of reactions to be knocked out) for metabolic engineering to design optimal production strains has been the goal of a number of computational algorithms. We developed FastKnock, an efficient next-generation algorithm for identifying all possible knockout strategies (with a predefined maximum number of reaction deletions) for the growth-coupled overproduction of biochemical(s) of interest. We achieve this by developing a special depth-first traversal algorithm that allows us to prune the search space significantly. This leads to a drastic reduction in execution time. We evaluate the performance of the FastKnock algorithm using various Escherichia coli genome-scale metabolic models in different conditions (minimal and rich mediums) for the overproduction of a number of desired metabolites. FastKnock efficiently prunes the search space to less than 0.2% for quadruple- and 0.02% for quintuple-reaction knockouts. Compared to the classic approaches such as OptKnock and the state-of-the-art techniques such as MCSEnumerator methods, FastKnock found many more beneficial and important practical solutions. The availability of all the solutions provides the opportunity to further characterize, rank and select the most appropriate intervention strategy based on any desired evaluation index. Our implementation of the FastKnock method in Python is publicly available at https://github.com/leilahsn/FastKnock .

Ultrahigh-throughput screening-assisted in vivo directed evolution for enzyme engineering

BACKGROUND

Classical directed evolution is a powerful approach for engineering biomolecules with improved or novel functions. However, it traditionally relies on labour- and time-intensive iterative cycles, due in part to the need for multiple molecular biology steps, including DNA transformation, and limited screening throughput.

RESULTS

In this study, we present an ultrahigh throughput in vivo continuous directed evolution system with thermosensitive inducible tunability, which is based on error-prone DNA polymerase expression modulated by engineered thermal-responsive repressor cI857, and genomic MutS mutant with temperature-sensitive defect for fixation of mutations in Escherichia coli. We demonstrated the success of the in vivo evolution platform with β-lactamase as a model, with an approximately 600-fold increase in the targeted mutation rate. Furthermore, the platform was combined with ultrahigh-throughput screening methods and employed to evolve α-amylase and the resveratrol biosynthetic pathway. After iterative rounds of enrichment, a mutant with a 48.3% improvement in α-amylase activity was identified via microfluidic droplet screening. In addition, when coupled with an in vivo biosensor in the resveratrol biosynthetic pathway, a variant with 1.7-fold higher resveratrol production was selected by fluorescence-activated cell sorting.

CONCLUSIONS

In this study, thermal-responsive targeted mutagenesis coupled with ultrahigh-throughput screening was developed for the rapid evolution of enzymes and biosynthetic pathways.

Systemic metabolic engineering of Enterobacter aerogenes for efficient 2,3-butanediol production

2,3-Butanediol (2,3-BDO) is an important gateway molecule for many chemical derivatives. Currently, microbial production is gradually being recognized as a green and sustainable alternative to petrochemical synthesis, but the titer, yield, and productivity of microbial 2,3-BDO remain suboptimal. Here, we used systemic metabolic engineering strategies to debottleneck the 2,3-BDO production in Enterobacter aerogenes. Firstly, the pyruvate metabolic network was reconstructed by deleting genes for by-product synthesis to improve the flux toward 2,3-BDO synthesis, which resulted in a 90% increase of the product titer. Secondly, the 2,3-BDO productivity of the IAM1183-LPCT/D was increased by 55% due to the heterologous expression of DR1558 which boosted cell resistance to abiotic stress. Thirdly, carbon sources were optimized to further improve the yield of target products. The IAM1183-LPCT/D showed the highest titer of 2,3-BDO from sucrose, 20% higher than that from glucose, and the yield of 2,3-BDO reached 0.49 g/g. Finally, the titer of 2,3-BDO of IAM1183-LPCT/D in a 5-L fermenter reached 22.93 g/L, 85% higher than the wild-type strain, and the titer of by-products except ethanol was very low. KEY POINTS: Deletion of five key genes in E. aerogenes improved 2,3-BDO production The titer of 2,3-BDO was increased by 90% by regulating metabolic flux Response regulator DR1558 was expressed to increase 2,3-BDO productivity.

Enabling pathway design by multiplex experimentation and machine learning

The remarkable metabolic diversity observed in nature has provided a foundation for sustainable production of a wide array of valuable molecules. However, transferring the biosynthetic pathway to the desired host often runs into inherent failures that arise from intermediate accumulation and reduced flux resulting from competing pathways within the host cell. Moreover, the conventional trial and error methods utilized in pathway optimization struggle to fully grasp the intricacies of installed pathways, leading to time-consuming and labor-intensive experiments, ultimately resulting in suboptimal yields. Considering these obstacles, there is a pressing need to explore the enzyme expression landscape and identify the optimal pathway configuration for enhanced production of molecules. This review delves into recent advancements in pathway engineering, with a focus on multiplex experimentation and machine learning techniques. These approaches play a pivotal role in overcoming the limitations of traditional methods, enabling exploration of a broader design space and increasing the likelihood of discovering optimal pathway configurations for enhanced production of molecules. We discuss several tools and strategies for pathway design, construction, and optimization for sustainable and cost-effective microbial production of molecules ranging from bulk to fine chemicals. We also highlight major successes in academia and industry through compelling case studies.

Engineering of a Substrate Affinity Reduced S-Adenosyl-methionine Synthetase as a Novel Biosensor for Growth-Coupling Selection of L-Methionine Overproducers

Biosensors are powerful tools for monitoring specific metabolites or controlling metabolic flux towards the products in a single cell, which play important roles in microbial cell factory construction. Despite their potential role in metabolic flux monitoring, the development of biosensors for small molecules is still limited. Reported biosensors often exhibit bottlenecks of poor specificity and a narrow dynamic range. Moreover, fine-tuning the substrate binding affinity of a crucial enzyme can decrease its catalytic activity, which ultimately results in the repression of the corresponding essential metabolite biosynthesis and impairs cell growth. However, increasing intracellular substrate concentration can elevate the availability of the essential metabolite and may lead to restore cellular growth. Herein, a new strategy was proposed for constructing whole-cell biosensors based on enzyme encoded by essential gene that offer inherent specificity and universality. Specifically, S-adenosyl-methionine synthetase (MetK) in E. coli was chosen as the crucial enzyme, and a series of MetK variants were identified that were sensitive to L-methionine concentration. This occurrence enabled the engineered cell to sense L-methionine and exhibit L-methionine dose-dependent cell growth. To improve the biosensor's dynamic range, an S-adenosyl-methionine catabolic enzyme was overexpressed to reduce the intracellular availability of S-adenosyl-methionine. The resulting whole-cell biosensor effectively coupled the intracellular concentration of L-methionine with growth and was successfully applied to select strains with enhanced L-methionine biosynthesis from random mutagenesis libraries. Overall, our study presents a universal strategy for designing and constructing growth-coupled biosensors based on crucial enzyme, which can be applied to select strains overproducing high value-added metabolites in cellular metabolism.

Exploring the role of microbial proteins in controlling environmental pollutants based on molecular simulation

Molecular simulation has been widely used to study microbial proteins' structural composition and dynamic properties, such as volatility, flexibility, and stability at the microscopic scale. Herein, this review describes the key elements of molecular docking and molecular dynamics (MD) simulations in molecular simulation; reviews the techniques combined with molecular simulation, such as crystallography, spectroscopy, molecular biology, and machine learning, to validate simulation results and bridge information gaps in the structure, microenvironmental changes, expression mechanisms, and intensity quantification; illustrates the application of molecular simulation, in characterizing the molecular mechanisms of interaction of microbial proteins with four different types of contaminants, namely heavy metals (HMs), pesticides, dyes and emerging contaminants (ECs). Finally, the review outlines the important role of molecular simulations in the study of microbial proteins for controlling environmental contamination and provides ideas for the application of molecular simulation in screening microbial proteins and incorporating targeted mutagenesis to obtain more effective contaminant control proteins.

Development of a CRISPR-Cas12a system for efficient genome engineering in clostridia

IMPORTANCE

Continued efforts in developing the CRISPR-Cas systems will further enhance our understanding and utilization of Clostridium species. This study demonstrates the development and application of a genome-engineering tool in two Clostridium strains, Clostridium butyricum and Clostridium sporogenes, which have promising potential as probiotics and oncolytic agents. Particular attention was given to the folding of precursor crRNA and the role of this process in off-target DNA cleavage by Cas12a. The results provide the guidelines necessary for efficient genome engineering using this system in clostridia. Our findings not only expand our fundamental understanding of genome-engineering tools in clostridia but also improve this technology to allow use of its full potential in a plethora of biotechnological applications.

Efficient Production of Triacetic Acid Lactone from Lignocellulose Hydrolysate by Metabolically Engineered Yarrowia lipolytica

Lignocellulose is a promising renewable feedstock for the bioproduction of high-value biochemicals. The poorly expressed xylose catabolic pathway was the bottleneck in the efficient utilization of the lignocellulose feedstock in yeast. Herein, multiple genetic and process engineering strategies were explored to debottleneck the conversion of xylose to the platform chemical triacetic acid lactone (TAL) in Yarrowia lipolytica. We identified that xylose assimilation generating more cofactor NADPH was favorable for the TAL synthesis. pH control improved the expression of acetyl-CoA carboxylase and generated more precursor malonyl-CoA. Combined with the suppression of the lipid synthesis pathway, 5.03 and 4.18 g/L TAL were produced from pure xylose and xylose-rich wheat straw hydrolysate, respectively. Our work removed the bottleneck of the xylose assimilation pathway and effectively upgraded wheat straw hydrolysate to TAL, which enabled us to build a sustainable oleaginous yeast cell factory to cost-efficiently produce green chemicals from low-cost lignocellulose by Y. lipolytica.

Regulatory-systemic approach in Aspergillus niger for bioleaching improvement by controlling precipitation

In the context of e-waste recycling by fungal bioleaching, nickel and cobalt precipitate as toxic metals by oxalic acid, whereas organic acids, such as citric, act as a high-performance chelating agent in dissolving these metals. Oxalic acid elimination requires an excess and uneconomical carbon source concentration in culture media. To resolve this issue, a novel and straightforward systems metabolic engineering method was devised to switch metabolic flux from oxalic acid to citric acid. In this technique, the genome-scale metabolic model of Aspergillus niger was applied to predicting flux variability and key reactions through the calculation of multiple optimal solutions for cellular regulation. Accordingly, BRENDA regulators and a novel molecular docking-oriented approach were defined a regulatory medium for this end. Then, ligands were evaluated in fungal culture to assess their impact on organic acid production for bioleaching of copper and nickel from waste telecommunication printed circuit boards. The protein structure of oxaloacetate hydrolase was modeled based on homology modeling for molecular docking. Metformin, glutathione, and sodium fluoride were found to be effective as inhibitors of oxalic acid production, enabling the production of 8100 ppm citric acid by controlling cellular metabolism. Indirect bioleaching demonstrated that nickel did not precipitate, and the bioleaching efficiency of copper and nickel increased from 40% and 24% to 61% and 100%, respectively. Bioleaching efficiency was evaluated qualitatively by FE-SEM, EDX, mapping, and XRD analysis. KEY POINTS: • A regulatory-systemic procedure for controlling cellular metabolism was introduced • Metformin inhibited oxalic acid, leading to 8100 ppm citric acid production • Bioleaching of copper and nickel in TPCBs improved by 21% and 76.

Fighting the battle against evolution: designing genetically modified organisms for evolutionary stability

Synthetic biology has made significant progress in many areas, but a major challenge that has received limited attention is the evolutionary stability of synthetic constructs made of heterologous genes. The expression of these constructs in microorganisms, that is, production of proteins that are not necessary for the organism, is a metabolic burden, leading to a decrease in relative fitness and make the synthetic constructs unstable over time. This is a significant concern for the synthetic biology community, particularly when it comes to bringing this technology out of the laboratory. In this review, we discuss the issue of evolutionary stability in synthetic biology and review the available tools to address this challenge.

Microbial production of L-methionine and its precursors using systems metabolic engineering

L-methionine is an essential amino acid with versatile applications in food, feed, cosmetics and pharmaceuticals. At present, the production of L-methionine mainly relies on chemical synthesis, which conflicts with the concern over serious environmental problems and sustainable development goals. In recent years, microbial production of natural products has been amply rewarded with the emergence and rapid development of system metabolic engineering. However, efficient L-methionine production by microbial fermentation remains a great challenge due to its complicated biosynthetic pathway and strict regulatory mechanism. Additionally, the engineered production of L-methionine precursors, L-homoserine, O-succinyl-L-homoserine (OSH) and O-acetyl-L-homoserine (OAH), has also received widespread attention because they can be catalyzed to L-methionine via a high-efficiently enzymatic reaction in vitro, which is also a promising alternative to chemical route. This review provides a comprehensive overview on the recent advances in the microbial production of L-methionine and its precursors, highlighting the challenges and potential solutions for developing L-methionine microbial cell factories from the perspective of systems metabolic engineering, aiming to offer guidance for future engineering.

Synthesizing biomaterials in living organisms

Living organisms fabricate biomacromolecules such as DNA, RNA, and proteins by the self-assembly process. The research on the mechanism of biomacromolecule formation also inspires the exploration of in vivo synthesized biomaterials. By elaborate design, artificial building blocks or precursors can self-assemble or polymerize into functional biomaterials within living organisms. In recent decades, these so-called in vivo synthesized biomaterials have achieved extensive applications in cell-fate manipulation, disease theranostics, bioanalysis, cellular surface engineering, and tissue regeneration. In this review, we classify strategies for in vivo synthesis into non-covalent, covalent, and genetic types. The development of these approaches is based on the chemical principles of supramolecular chemistry and synthetic chemistry, biological cues such as enzymes and microenvironments, and the means of synthetic biology. By summarizing the design principles in detail, some insights into the challenges and opportunities in this field are provided to  enlighten further research.

Genome-wide identification of overexpression and downregulation gene targets based on the sum of covariances of the outgoing reaction fluxes

In metabolic engineering, predicting gene overexpression targets remains challenging because both endogenous and heterologous genes in a large metabolic space can be candidates, in contrast to gene knockout targets that are confined to endogenous genes. We report the development of iBridge that identifies positive and negative metabolites exerting positive and negative impacts on product formation, respectively, based on the sum of covariances of their outgoing (consuming) reaction fluxes for a target chemical. Then, "bridge" reactions converting negative metabolites to positive metabolites are identified as overexpression targets, while the opposites as downregulation targets. Using iBridge, overexpression and downregulation targets are suggested for the production of 298 chemicals and validated for 36 chemicals experimentally demonstrated in previous studies. Finally, iBridge is employed to engineer Escherichia coli strains capable of producing 10.3 g/L of D-panthenol, a compound not previously produced, as well as putrescine and 4-hydroxyphenyllactate at enhanced titers, 63.7 and 8.3 g/L, respectively.

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 flux phenotyping of secondary metabolism in cyanobacteria

Cyanobacteria generate energy from photosynthesis and produce various secondary metabolites with diverse commercial and pharmaceutical applications. Unique metabolic and regulatory pathways in cyanobacteria present new challenges for researchers to enhance their product yields, titers, and rates. Therefore, further advancements are critically needed to establish cyanobacteria as a preferred bioproduction platform. Metabolic flux analysis (MFA) quantitatively determines the intracellular flows of carbon within complex biochemical networks, which elucidate the control of metabolic pathways by transcriptional, translational, and allosteric regulatory mechanisms. The emerging field of systems metabolic engineering (SME) involves the use of MFA and other omics technologies to guide the rational development of microbial production strains. This review highlights the potential of MFA and SME to optimize the production of cyanobacterial secondary metabolites and discusses the technical challenges that lie ahead.

A potential paradigm in CRISPR/Cas systems delivery: at the crossroad of microalgal gene editing and algal-mediated nanoparticles

Microalgae as the photosynthetic organisms offer enormous promise in a variety of industries, such as the generation of high-value byproducts, biofuels, pharmaceuticals, environmental remediation, and others. With the rapid advancement of gene editing technology, CRISPR/Cas system has evolved into an effective tool that revolutionised the genetic engineering of microalgae due to its robustness, high target specificity, and programmability. However, due to the lack of robust delivery system, the efficacy of gene editing is significantly impaired, limiting its application in microalgae. Nanomaterials have become a potential delivery platform for CRISPR/Cas systems due to their advantages of precise targeting, high stability, safety, and improved immune system. Notably, algal-mediated nanoparticles (AMNPs), especially the microalgae-derived nanoparticles, are appealing as a sustainable delivery platform because of their biocompatibility and low toxicity in a homologous relationship. In addition, living microalgae demonstrated effective and regulated distribution into specified areas as the biohybrid microrobots. This review extensively summarised the uses of CRISPR/Cas systems in microalgae and the recent developments of nanoparticle-based CRISPR/Cas delivery systems. A systematic description of the properties and uses of AMNPs, microalgae-derived nanoparticles, and microalgae microrobots has also been discussed. Finally, this review highlights the challenges and future research directions for the development of gene-edited microalgae.

Programming dynamic division of labor using horizontal gene transfer

The metabolic engineering of microbes has broad applications, including in biomanufacturing, bioprocessing, and environmental remediation. The introduction of a complex, multi-step pathway often imposes a substantial metabolic burden on the host cell, restraining the accumulation of productive biomass and limiting pathway efficiency. One strategy to alleviate metabolic burden is division of labor (DOL), in which different subpopulations carry out different parts of the pathway and work together to convert a substrate into a final product. However, the maintenance of different engineered subpopulations is challenging due to competition and convoluted inter-strain population dynamics. Through modeling, we show that dynamic division of labor (DDOL) mediated by horizontal gene transfer (HGT) can overcome these limitations and enable the robust maintenance of burdensome, multi-step pathways. We also use plasmid genomics to uncover evidence that DDOL is a strategy utilized by natural microbial communities. Our work suggests that bioengineers can harness HGT to stabilize synthetic metabolic pathways in microbial communities, enabling the development of robust engineered systems for deployment in a variety of contexts.

Characterization of an efficient CRISPR-iCas9 system in Yarrowia lipolytica for the biosynthesis of carotenoids

The application of clustered regularly interspaced short palindromic repeats-Cas (CRISPR-Cas9) technology in the genetic modification of Yarrowia lipolytica is challenged by low efficiency and low throughput. Here, a highly efficient CRISPR-iCas9 (with D147Y and P411T mutants) genetic manipulation tool was established for Y. lipolytica, which was further utilized to integrate carotene synthetic key genes and significantly improve the target product yield. First, CRISPR-iCas9 could shorten the time of genetic modification and enable the rapid knockout of nonsense suppressors. iCas9 can lead to more than 98% knockout efficiency for NHEJ-mediated repair after optimal target disruption of a single gene, 100% knockout efficiency for a single gene-guided version, and more than 80% knockout efficiency for multiple genes simultaneously in Y. lipolytica. Subsequently, this technology allowed for rapid one-step integration of large fragments (up to 9902-bp) of genes into chromosomes. Finally, YL-ABTG and YL-ABTG2Z were further constructed through CRISPR-iCas9 integration of key genes in a one-step process, resulting in a maximum β-carotene and zeaxanthin content of 3.12 mg/g and 2.33 mg/g dry cell weight, respectively. Therefore, CRISPR-iCas9 technology provides a feasible approach to genetic modification for efficient biosynthesis of biological compounds in Y. lipolytica. KEY POINTS: • iCas9 with D147Y and P411T mutants improved the CRISPR efficiency in Y. lipolytica. • CRISPR-iCas9 achieved efficient gene knockout and integration in Y. lipolytica. • CRISPR-iCas9 rapidly modified Y. lipolytica for carotenoid bioproduction.

Bacterial glycobiotechnology: A biosynthetic route for the production of biopharmaceutical glycans

The recent advancement in the human glycome and progress in the development of an inclusive network of glycosylation pathways allow the incorporation of suitable machinery for protein modification in non-natural hosts and explore novel opportunities for constructing next-generation tailored glycans and glycoconjugates. Fortunately, the emerging field of bacterial metabolic engineering has enabled the production of tailored biopolymers by harnessing living microbial factories (prokaryotes) as whole-cell biocatalysts. Microbial catalysts offer sophisticated means to develop a variety of valuable polysaccharides in bulk quantities for practical clinical applications. Glycans production through this technique is highly efficient and cost-effective, as it does not involve expensive initial materials. Metabolic glycoengineering primarily focuses on utilizing small metabolite molecules to alter biosynthetic pathways, optimization of cellular processes for glycan and glycoconjugate production, characteristic to a specific organism to produce interest tailored glycans in microbes, using preferably cheap and simple substrate. However, metabolic engineering faces one of the unique challenges, such as the need for an enzyme to catalyze desired substrate conversion when natural native substrates are already present. So, in metabolic engineering, such challenges are evaluated, and different strategies have been developed to overcome them. The generation of glycans and glycoconjugates via metabolic intermediate pathways can still be supported by glycol modeling achieved through metabolic engineering. It is evident that modern glycans engineering requires adoption of improved strain engineering strategies for creating competent glycoprotein expression platforms in bacterial hosts, in the future. These strategies include logically designing and introducing orthogonal glycosylation pathways, identifying metabolic engineering targets at the genome level, and strategically improving pathway performance (for example, through genetic modification of pathway enzymes). Here, we highlight current strategies, applications, and recent progress in metabolic engineering for producing high-value tailored glycans and their applications in biotherapeutics and diagnostics.

Microbial engineering for shikimate biosynthesis

Shikimate, a precursor to the antiviral drug oseltamivir (Tamiflu®), can influence aromatic metabolites and finds extensive use in antimicrobial, antitumor, and cardiovascular applications. Consequently, various strategies have been developed for chemical synthesis and plant extraction to enhance shikimate biosynthesis, potentially impacting environmental conditions, economic sustainability, and separation and purification processes. Microbial engineering has been developed as an environmentally friendly approach for shikimate biosynthesis. In this review, we provide a comprehensive summary of microbial strategies for shikimate biosynthesis. These strategies primarily include chassis construction, biochemical optimization, pathway remodelling, and global regulation. Furthermore, we discuss future perspectives on shikimate biosynthesis and emphasize the importance of utilizing advanced metabolic engineering tools to regulate microbial networks for constructing robust microbial cell factories.

Construction of a plasmid-free L-leucine overproducing Escherichia coli strain through reprogramming of the metabolic flux

BACKGROUND

L-Leucine is a high-value amino acid with promising applications in the medicine and feed industries. However, the complex metabolic network and intracellular redox imbalance in fermentative microbes limit their efficient biosynthesis of L-leucine.

RESULTS

In this study, we applied rational metabolic engineering and a dynamic regulation strategy to construct a plasmid-free, non-auxotrophic Escherichia coli strain that overproduces L-leucine. First, the L-leucine biosynthesis pathway was strengthened through multi-step rational metabolic engineering. Then, a cooperative cofactor utilization strategy was designed to ensure redox balance for L-leucine production. Finally, to further improve the L-leucine yield, a toggle switch for dynamically controlling sucAB expression was applied to accurately regulate the tricarboxylic acid cycle and the carbon flux toward L-leucine biosynthesis. Strain LEU27 produced up to 55 g/L of L-leucine, with a yield of 0.23 g/g glucose.

CONCLUSIONS

The combination of strategies can be applied to the development of microbial platforms that produce L-leucine and its derivatives.

Simulated Design-Build-Test-Learn Cycles for Consistent Comparison of Machine Learning Methods in Metabolic Engineering

Combinatorial pathway optimization is an important tool in metabolic flux optimization. Simultaneous optimization of a large number of pathway genes often leads to combinatorial explosions. Strain optimization is therefore often performed using iterative design-build-test-learn (DBTL) cycles. The aim of these cycles is to develop a product strain iteratively, every time incorporating learning from the previous cycle. Machine learning methods provide a potentially powerful tool to learn from data and propose new designs for the next DBTL cycle. However, due to the lack of a framework for consistently testing the performance of machine learning methods over multiple DBTL cycles, evaluating the effectiveness of these methods remains a challenge. In this work, we propose a mechanistic kinetic model-based framework to test and optimize machine learning for iterative combinatorial pathway optimization. Using this framework, we show that gradient boosting and random forest models outperform the other tested methods in the low-data regime. We demonstrate that these methods are robust for training set biases and experimental noise. Finally, we introduce an algorithm for recommending new designs using machine learning model predictions. We show that when the number of strains to be built is limited, starting with a large initial DBTL cycle is favorable over building the same number of strains for every cycle.

Metabolic engineering in hairy roots: An outlook on production of plant secondary metabolites

Plants are one of the vital sources of secondary metabolites. These secondary metabolites have diverse roles in human welfare, including therapeutic implication. Nevertheless, secondary metabolite yields obtained through the exploitation of natural plant populations is insufficient to meet the commercial demand due to their accumulation in low volumes. Besides, in-planta synthesis of these important metabolites is directly linked with the age and growing conditions of the plant. Such limitations have paved the way for the exploration of alternative production methodologies. Hairy root cultures, induced after the interaction of plants with Rhizobium rhizogenes (Agrobacterium rhizogenes), are a practical solution for producing valuable secondary metabolite at low cost and without the influence of seasonal, geographic or climatic variations. Hairy root cultures also offer the opportunity to get combined with other yield enhancements strategies (precursor feeding, elicitation and metabolic engineering) to further stimulate and/or enhance their production potential. Applications of metabolic engineering in exploiting hairy root cultures attracted the interest of several research groups as a means of yield enhancement. Currently, several engineering approaches like overexpression and silencing of pathway genes, and transcription factor overexpression are used to boost metabolite production, along with the contextual success of genome editing. This review attempts to cover metabolic engineering in hairy roots for the production of secondary metabolites, with a primary emphasis on alkaloids, and discusses prospects for taking this research forward to meet desired production demands.

Engineered Escherichia coli platforms for tyrosine-derivative production from phenylalanine using phenylalanine hydroxylase and tetrahydrobiopterin-regeneration system

BACKGROUND

Aromatic compounds derived from tyrosine are important and diverse chemicals that have industrial and commercial applications. Although these aromatic compounds can be obtained by extraction from natural producers, their growth is slow, and their content is low. To overcome these problems, many of them have been chemically synthesized from petroleum-based feedstocks. However, because of the environmental burden and depleting availability of feedstock, microbial cell factories are attracting much attention as sustainable and environmentally friendly processes.

RESULTS

To facilitate development of microbial cell factories for producing tyrosine derivatives, we developed simple and convenient tyrosine-producing Escherichia coli platforms with a bacterial phenylalanine hydroxylase, which converted phenylalanine to tyrosine with tetrahydromonapterin as a cofactor, using a synthetic biology approach. By introducing a tetrahydrobiopterin-regeneration system, the tyrosine titer of the plasmid-based engineered strain was 4.63 g/L in a medium supplemented with 5.00 g/L phenylalanine with a test tube. The strains were successfully used to produce industrially attractive compounds, such as tyrosol with a yield of 1.58 g/L by installing a tyrosol-producing module consisting of genes encoding tyrosine decarboxylase and tyramine oxidase on a plasmid. Gene integration into E. coli chromosomes has an advantage over the use of plasmids because it increases genetic stability without antibiotic feeding to the culture media and enables more flexible pathway engineering by accepting more plasmids with artificial pathway genes. Therefore, we constructed a plasmid-free tyrosine-producing platform by integrating five modules, comprising genes encoding the phenylalanine hydroxylase and tetrahydrobiopterin-regeneration system, into the chromosome. The platform strain could produce 1.04 g/L of 3,4-dihydroxyphenylalanine, a drug medicine, by installing a gene encoding tyrosine hydroxylase and the tetrahydrobiopterin-regeneration system on a plasmid. Moreover, by installing the tyrosol-producing module, tyrosol was produced with a yield of 1.28 g/L.

CONCLUSIONS

We developed novel E. coli platforms for producing tyrosine from phenylalanine at multi-gram-per-liter levels in test-tube cultivation. The platforms allowed development and evaluation of microbial cell factories installing various designed tyrosine-derivative biosynthetic pathways at multi-grams-per-liter levels in test tubes.