The future of metabolic engineering and synthetic biology: towards a systematic practice

Semi-continuous biomanufacturing for maximizing the production of complex chemicals and fuels: a case study of amorpha-4,11-diene

Biomanufacturing is emerging as a key technology for the sustainable production of chemicals, materials, and food ingredients using engineered microbes. However, despite billions of dollars of investment, few processes have been successfully commercialized due to a lack of attention on industrial-scale bioprocess design and innovation. In this study, we address this challenge through the development of a novel semi-continuous bioprocess for the production of the terpene amorpha-4,11-diene (AMD4,11) using engineered Escherichia coli. Using a hydrophilic membrane for product and biomass retention, we successfully decoupled production at low growth rates (~0.01 1/h) and improved reactor productivity up to 166 mg/lReactor h, threefold compared with traditional fed-batch fermentations. When cell recycling was implemented, we showed sustained production at the highest conversion yield and production rate for up to three cycles, demonstrating the robustness of both the strain and the process and highlighting the potential for new bioprocess strategies to improve the economic viability of industrial biomanufacturing.

Identification of an Endogenous Strong Promoter in Burkholderia sp. JP2-270

Burkholderia is the second largest source of natural product bacteria after Actinomyces and can produce many secondary metabolites including pyrrolnitrin (PRN). Natural products of microbial origin are usually found in trace amounts, so in metabolic engineering, promoter engineering is often used to regulate gene expression to increase yield. In this study, an endogenous strong promoter was identified based on RNA-seq to overexpress biosynthetic genes to increase the production of PRN. By analyzing the transcriptomic data of the antagonistic bacterium Burkholderia sp. JP2-270 in three different development periods, we screened 50 endogenous promoters with high transcriptional activity, nine of which were verified by an obvious fluorescent signal via fluorescence observation. Then, combined with RT-qPCR analysis, Php, the promoter of a hypothetical protein, was found to be significantly expressed in all three periods. In order to increase the suitability of endogenous promoters, the promoter Php was shortened at different lengths, and the results show that a sequence length of 173 bp was necessary for its activity. Moreover, this promoter was used to overexpress the PRN biosynthesis genes (prnA, prnB, prnC and prnD) in JP2-270, resulting in a successful increase in gene expression levels by 40-80 times. Only the overexpression of the prnB gene successfully increased PRN production to 1.46 times that of the wild type. Overall, the endogenous strong promoters screened in this study can improve gene expression and increase the production of secondary metabolites in JP2-270 and other strains.

Machine learning analysis of RB-TnSeq fitness data predicts functional gene modules in Pseudomonas putida KT2440

There is growing interest in engineering Pseudomonas putida KT2440 as a microbial chassis for the conversion of renewable and waste-based feedstocks, and metabolic engineering of P. putida relies on the understanding of the functional relationships between genes. In this work, independent component analysis (ICA) was applied to a compendium of existing fitness data from randomly barcoded transposon insertion sequencing (RB-TnSeq) of P. putida KT2440 grown in 179 unique experimental conditions. ICA identified 84 independent groups of genes, which we call fModules ("functional modules"), where gene members displayed shared functional influence in a specific cellular process. This machine learning-based approach both successfully recapitulated previously characterized functional relationships and established hitherto unknown associations between genes. Selected gene members from fModules for hydroxycinnamate metabolism and stress resistance, acetyl coenzyme A assimilation, and nitrogen metabolism were validated with engineered mutants of P. putida. Additionally, functional gene clusters from ICA of RB-TnSeq data sets were compared with regulatory gene clusters from prior ICA of RNAseq data sets to draw connections between gene regulation and function. Because ICA profiles the functional role of several distinct gene networks simultaneously, it can reduce the time required to annotate gene function relative to manual curation of RB-TnSeq data sets.

IMPORTANCE

This study demonstrates a rapid, automated approach for elucidating functional modules within complex genetic networks. While Pseudomonas putida randomly barcoded transposon insertion sequencing data were used as a proof of concept, this approach is applicable to any organism with existing functional genomics data sets and may serve as a useful tool for many valuable applications, such as guiding metabolic engineering efforts in other microbes or understanding functional relationships between virulence-associated genes in pathogenic microbes. Furthermore, this work demonstrates that comparison of data obtained from independent component analysis of transcriptomics and gene fitness datasets can elucidate regulatory-functional relationships between genes, which may have utility in a variety of applications, such as metabolic modeling, strain engineering, or identification of antimicrobial drug targets.

Directed Evolution of 4-Hydroxyphenylpyruvate Biosensors Based on a Dual Selection System

Biosensors based on allosteric transcription factors have been widely used in synthetic biology. In this study, we utilized the Acinetobacter ADP1 transcription factor PobR to develop a biosensor activating the PpobA promoter when bound to its natural ligand, 4-hydroxybenzoic acid (4HB). To screen for PobR mutants responsive to 4-hydroxyphenylpyruvate(HPP), we developed a dual selection system in E. coli. The positive selection of this system was used to enrich PobR mutants that identified the required ligands. The following negative selection eliminated or weakened PobR mutants that still responded to 4HB. Directed evolution of the PobR library resulted in a variant where PobRW177R was 5.1 times more reactive to 4-hydroxyphenylpyruvate than PobRWT. Overall, we developed an efficient dual selection system for directed evolution of biosensors.

Light-Driven Metabolic Pathways in Non-Photosynthetic Biohybrid Bacteria

Biomanufacturing via microorganisms relies on carbon substrates for molecular feedstocks and a source of energy to carry out enzymatic reactions. This creates metabolic bottlenecks and lowers the efficiency for substrate conversion. Nanoparticle biohybridization with proteins and whole cell surfaces can bypass the need for redox cofactor regeneration for improved secondary metabolite production in a non-specific manner. Here we propose using nanobiohybrid organisms (Nanorgs), intracellular protein-nanoparticle hybrids formed through the spontaneous coupling of core-shell quantum dots (QDs) with histidine-tagged enzymes in non-photosynthetic bacteria, for light-mediated control of bacterial metabolism. This proved to eliminate metabolic constrictions and replace glucose with light as the source of energy in Escherichia coli, with an increase in growth by 1.7-fold in 75 % reduced nutrient media. Metabolomic tracking through carbon isotope labeling confirmed flux shunting through targeted pathways, with accumulation of metabolites downstream of respective targets. Finally, application of Nanorgs with the Ehrlich pathway improved isobutanol titers/yield by 3.9-fold in 75 % less sugar from E. coli strains with no genetic alterations. These results demonstrate the promise of Nanorgs for metabolic engineering and low-cost biomanufacturing.

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.

Challenges and opportunities for engineered Escherichia coli as a pivotal chassis toward versatile tyrosine-derived chemicals production

Growing concerns over limited fossil resources and associated environmental problems are motivating the development of sustainable processes for the production of high-volume fuels and high-value-added compounds. The shikimate pathway, an imperative pathway in most microorganisms, is branched with tyrosine as the rate-limiting step precursor of valuable aromatic substances. Such occurrence suggests the shikimate pathway as a promising route in developing microbial cell factories with multiple applications in the nutraceutical, pharmaceutical, and chemical industries. Therefore, an increasing number of studies have focused on this pathway to enable the biotechnological manufacture of pivotal and versatile aromatic products. With advances in genome databases and synthetic biology tools, genetically programmed Escherichia coli strains are gaining immense interest in the sustainable synthesis of chemicals. Engineered E. coli is expected to be the next bio-successor of fossil fuels and plants in commercial aromatics synthesis. This review summarizes successful and applicable genetic and metabolic engineering strategies to generate new chassis and engineer the iterative pathway of the tyrosine route in E. coli, thus addressing the opportunities and current challenges toward the realization of sustainable tyrosine-derived aromatics.

Deciphering cell wall sensors enabling the construction of robust P. pastoris for single-cell protein production

Single-cell protein (SCP) production in the methylotrophic yeast Pichia pastoris has the potential to achieve a sustainable protein supply. However, improving the methanol fermentation efficiency and reducing carbon loss has been a long-standing challenge with far-reaching scientific and practical implications. Here, comparative transcriptomics revealed that PAS_0305, a gene directly associated with cell wall thickness under methanol stress, can be used as a target for unlocking cell wall sensors. Intracellular trehalose accumulation confirmed that cell wall sensors were activated after knocking out PAS_0305, which resulted in increased cell wall permeability. Genome-wide signal perturbations were transduced through the HOG module and the CWI pathway, which was confirmed to connected by Pbs2-Mkk. As a consequence of CWI pathway activation, ΔPAS_0305 elicited a rescue response of cell wall remodeling by increasing the β-1,3-glucan content and decreasing the chitin/mannose content. Remarkably, perturbations in global stress signals led to a fine-tuning of the metabolic network of ΔPAS_0305, resulting in a superior phenotype with highest crude protein and methanol conversion rate of 67.21% and 0.46 gDCW/g. Further genome-scale metabolic models were constructed to validate the experimental results, confirming that unlocking cell wall sensors resulted in maximized flux from methanol towards SCP and effectively addressing the issue of carbon loss in methanol fermentation. This work sheds new light on the potential of manipulating cellular signaling pathways to optimize metabolic networks and achieve exceptional phenotypic characteristics, providing new strategies for constructing versatile cell factories in P. pastoris.

Research progress on the application of cell-free synthesis systems for enzymatic processes

Cell-free synthesis systems can complete the transcription and translation process in vitro to produce complex proteins that are difficult to be expressed in traditional cell-based systems. Such systems also can be used for the assembly of efficient localized multienzyme cascades to synthesize products that are toxic to cells. Cell-free synthesis systems provide a simpler and faster engineering solution than living cells, allowing unprecedented design freedom. This paper reviews the latest progress on the application of cell-free synthesis systems in the field of enzymatic catalysis, including cell-free protein synthesis and cell-free metabolic engineering. In cell-free protein synthesis: complex proteins, toxic proteins, membrane proteins, and artificial proteins containing non-natural amino acids can be easily synthesized by directly controlling the reaction conditions in the cell-free system. In cell-free metabolic engineering, the synthesis of desired products can be made more specific and efficient by designing metabolic pathways and screening biocatalysts based on purified enzymes or crude extracts. Through the combination of cell-free synthesis systems and emerging technologies, such as: synthetic biology, microfluidic control, cofactor regeneration, and artificial scaffolds, we will be able to build increasingly complex biomolecule systems. In the next few years, these technologies are expected to mature and reach industrialization, providing innovative platforms for a wide range of biotechnological applications.

67 million natural product-like compound database generated via molecular language processing

Natural products are a rich resource of bioactive compounds for valuable applications across multiple fields such as food, agriculture, and medicine. For natural product discovery, high throughput in silico screening offers a cost-effective alternative to traditional resource-heavy assay-guided exploration of structurally novel chemical space. In this data descriptor, we report a characterized database of 67,064,204 natural product-like molecules generated using a recurrent neural network trained on known natural products, demonstrating a significant 165-fold expansion in library size over the approximately 400,000 known natural products. This study highlights the potential of using deep generative models to explore novel natural product chemical space for high throughput in silico discovery.

Exploring the Feasibility of Cell-Free Synthesis as a Platform for Polyhydroxyalkanoate (PHA) Production: Opportunities and Challenges

The extensive utilization of traditional petroleum-based plastics has resulted in significant damage to the natural environment and ecological systems, highlighting the urgent need for sustainable alternatives. Polyhydroxyalkanoates (PHAs) have emerged as promising bioplastics that can compete with petroleum-based plastics. However, their production technology currently faces several challenges, primarily focused on high costs. Cell-free biotechnologies have shown significant potential for PHA production; however, despite recent progress, several challenges still need to be overcome. In this review, we focus on the status of cell-free PHA synthesis and compare it with microbial cell-based PHA synthesis in terms of advantages and drawbacks. Finally, we present prospects for the development of cell-free PHA synthesis.

Recent advances and perspectives on production of value-added organic acids through metabolic engineering

Organic acids are important consumable materials with a wide range of applications in the food, biopolymer and chemical industries. The global consumer organic acids market is estimated to increase to $36.86 billion by 2026. Conventionally, organic acids are produced from the chemical catalysis process with petrochemicals as raw materials, which posts severe environmental concerns and conflicts with our sustainable development goals. Most of the commonly used organic acids can be produced from various organisms. As a state-of-the-art technology, large-scale fermentative production of important organic acids with genetically-modified microbes has become an alternative to the chemical route to meet the market demand. Despite the fact that bio-based organic acid production from renewable cheap feedstock provides a viable solution, low productivity has impeded their industrial-scale application. With our deeper understanding of strain genetics, physiology and the availability of strain engineering tools, new technologies including synthetic biology, various metabolic engineering strategies, omics-based system biology tools, and high throughput screening methods are gradually established to bridge our knowledge gap. And they were further applied to modify the cellular reaction networks of potential microbial hosts and improve the strain performance, which facilitated the commercialization of consumable organic acids. Here we present the recent advances of metabolic engineering strategies to improve the production of important organic acids including fumaric acid, citric acid, itaconic acid, adipic acid, muconic acid, and we also discuss the current challenges and future perspectives on how we can develop a cost-efficient, green and sustainable process to produce these important chemicals from low-cost feedstocks.

Biosynthesis of cannabinoid precursor olivetolic acid in genetically engineered Yarrowia lipolytica

Engineering microbes to produce plant-derived natural products provides an alternate solution to obtain bioactive products. Here we report a systematic approach to sequentially identify the rate-limiting steps and improve the biosynthesis of the cannabinoid precursor olivetolic acid (OLA) in Yarrowia lipolytica. We find that Pseudomonas sp LvaE encoding a short-chain acyl-CoA synthetase can efficiently convert hexanoic acid to hexanoyl-CoA. The co-expression of the acetyl-CoA carboxylase, the pyruvate dehydrogenase bypass, the NADPH-generating malic enzyme, as well as the activation of peroxisomal β-oxidation pathway and ATP export pathway are effective strategies to redirect carbon flux toward OLA synthesis. Implementation of these strategies led to an 83-fold increase in OLA titer, reaching 9.18 mg/L of OLA in shake flask culture. This work may serve as a baseline for engineering cannabinoids biosynthesis in oleaginous yeast species.

Engineering of global transcription factor FruR to redirect the carbon flow in Escherichia coli for enhancing L-phenylalanine biosynthesis

BACKGROUND

The catabolite repressor/activator protein (FruR) is a global regulatory protein known to control the expression of several genes concerned with carbon utilization and energy metabolism. This study aimed to illustrate effects of the FruR mutant on the _L-phenylalanine (_L-PHE) producing strain PHE01.

RESULTS

Random mutagenesis libraries of fruR generated in vitro were first integrated into the chromosome of PHE01 by CRISPR/Cas9 technique, and then the best mutant PHE07 (FruR^E173K) was obtained. With this mutant, a final _L-PHE concentration of 70.50 ± 1.02 g/L was achieved, which was 23.34% higher than that of PHE01. To better understand the mechanism, both transcriptomes and metabolomes of PHE07 were carried out and compared to that of PHE01. Specifically, the transcript levels of genes involved in gluconeogenesis pathway, pentose phosphate pathway, Krebs cycle, and glyoxylate shunt were up-regulated in the FruR^E173K mutant, whereas genes aceEF, acnB, and icd were down-regulated. From the metabolite level, the FruR^E173K mutation led to an accumulation of pentose phosphate pathway and Krebs cycle products, whereas the products of pyruvate metabolism pathway: acetyl-CoA and cis-aconic acid, were down-regulated. As a result of the altered metabolic flows, the utilization of carbon sources was improved and the supply of precursors (phosphoenolpyruvate and erythrose 4-phosphate) for _L-PHE biosynthesis was increased, which together led to the enhanced production of _L-PHE.

CONCLUSION

A novel strategy for _L-PHE overproduction by modification of the global transcription factor FruR in E. coli was reported. Especially, these findings expand the scope of pathways affected by the fruR regulon and illustrate its importance as a global regulator in _L-PHE production.

Strategies for Enhancing Microbial Production of 2'-Fucosyllactose, the Most Abundant Human Milk Oligosaccharide

Human milk oligosaccharides (HMOs), a group of structurally diverse unconjugated glycans in breast milk, act as important prebiotics and have plenty of unique health effects for growing infants. 2'-Fucosyllactose (2'-FL) is the most abundant HMO, accounting for approximately 30%, among approximately 200 identified HMOs with different structures. 2'-FL can be enzymatically produced by α1,2-fucosyltransferase, using GDP-l-fucose as donor and lactose as acceptor. Metabolic engineering strategies have been widely used for enhancement of GDP-l-fucose supply and microbial production of 2'-FL with high productivity. GDP-l-fucose supply can be enhanced by two main pathways, including de novo and salvage pathways. 2'-FL-producing α1,2-fucosyltransferases have widely been identified from various microorganisms. Metabolic pathways for 2'-FL synthesis can be basically constructed by enhancing GDP-l-fucose supply and introducing α1,2-fucosyltransferase. Various strategies have been attempted to enhance 2'-FL production, such as acceptor enhancement, donor enhancement, and improvement of the functional expression of α1,2-fucosyltransferase. In this review, current progress in GDP-l-fucose synthesis and bacterial α1,2-fucosyltransferases is described in detail, various metabolic engineering strategies for enhancing 2'-FL production are comprehensively reviewed, and future research focuses in biotechnological production of 2'-FL are suggested.

Escherichia coli minicells with targeted enzymes as bioreactors for producing toxic compounds

Formed by aberrant cell division, minicells possess functional metabolism despite their inability to grow and divide. Minicells exhibit not only superior stability when compared with bacterial cells but also exceptional tolerance-characteristics that are essential for a de novo bioreactor platform. Accordingly, we engineered minicells to accumulate protein, ensuring sufficient production capability. When tested with chemicals regarded as toxic against cells, the engineered minicells produced titers of C6-C10 alcohols and esters, far surpassing the corresponding production from bacterial cells. Additionally, microbial autoinducer production that is limited in expanding bacterial population was conducted in the minicells. Because bacterial population growth was nonexistent, the minicells produced autoinducers in constant amounts, which allowed precise control of the bacterial population having autoinducer-responsive gene circuits. When bacterial population growth was nonexistent, the minicells produced autoinducers in constant amounts, which allowed precise control of the bacterial population having autoinducer-based gene circuits with the minicells. This study demonstrates the potential of minicells as bioreactors suitable for products with known limitations in microbial production, thus providing new possibilities for bioreactor engineering.

Repurposing CRISPR RNA-guided integrases system for one-step, efficient genomic integration of ultra-long DNA sequences

Genomic integration techniques offer opportunities for generation of engineered microorganisms with improved or even entirely new functions but are currently limited by inability for efficient insertion of long genetic payloads due to multiplexing. Herein, using Shewanella oneidensis MR-1 as a model, we developed an optimized CRISPR-associated transposase from cyanobacteria Scytonema hofmanni (ShCAST system), which enables programmable, RNA-guided transposition of ultra-long DNA sequences (30 kb) onto bacterial chromosomes at ∼100% efficiency in a single orientation. In this system, a crRNA (CRISPR RNA) was used to target multicopy loci like insertion-sequence elements or combining I-SceI endonuclease, thereby allowing efficient single-step multiplexed or iterative DNA insertions. The engineered strain exhibited drastically improved substrate diversity and extracellular electron transfer ability, verifying the success of this system. Our work greatly expands the application range and flexibility of genetic engineering techniques and may be readily extended to other bacteria for better controlling various microbial processes.

An update on the progress of microbial biotransformation of commercial monoterpenes

Monoterpenes, a class of isoprenoid compounds, are extensively used in flavor, fragrance, perfumery, and cosmetics. They display many astonishing bioactive properties of biological and pharmacological significance. All monoterpenes are derived from universal precursor geranyl diphosphate. The demand for new monoterpenoids has been increasing in flavor, fragrances, perfumery, and pharmaceuticals. Chemical methods, which are harmful for human and the environment, synthesize most of these products. Over the years, researchers have developed alternative methods for the production of newer monoterpenoids. Microbial biotransformation is one of them, which relied on microbes and their enzymes. It has produced many new desirable commercially important monoterpenoids. A growing number of reports reflect an ever-expanding scope of microbial biotransformation in food and aroma industries. Simultaneously, our knowledge of the enzymology of monoterpene biosynthetic pathways has been increasing, which facilitated the biotransformation of monoterpenes. In this article, we have covered the progress made on microbial biotransformation of commercial monoterpenes with a brief introduction to their biosynthesis. We have collected several reports from authentic web sources, including Google Scholar, Pubmed, Web of Science, and Scopus published in the past few years to extract information on the topic.

PASIV: A Pooled Approach-Based Workflow to Overcome Toxicity-Induced Design of Experiments Failures and Inefficiencies

We present here a newly developed workflow—which we have called PASIV—designed to provide a solution to a practical problem with design of experiments (DoE) methodology: i.e., what can be done if the scoping phase of the DoE cycle is severely hampered by burden and toxicity issues (caused by either the metabolite or an intermediary), making it unreliable or impossible to proceed to the screening phase? PASIV—standing for pooled approach, screening, identification, and visualization—was designed so the (viable) region of interest can be made to appear through an interplay between biology and software. This was achieved by combining multiplex construction in a pooled approach (one-pot reaction) with a viability assay and with a range of bioinformatics tools (including a novel construct matching tool). PASIV was tested on the exemplar of the lycopene pathway—under stressful constitutive expression—yielding a region of interest with comparatively stronger producers.

Fate of carotenoids in yeasts: synthesis and cleavage

Carotenoids and their cleavage products (norisoprenoids) have excellent functional properties with diverse applications in foods, medicaments, cosmetics, etc. Carotenoids can be oxidatively cleaved through nonspecific reactions or by carotenoid cleavage oxygenases (CCOs), the product of which could further modify food flavor. This review provides comprehensive information on both carotenoid synthesis and cleavage processes with emphasis on enzyme characterization and biosynthetic pathway optimization. The use of interdisciplinary approaches of bioengineering and computer-aided experimental technology for key enzyme modification and systematic pathway design is beneficial to monitor metabolic pathways and assess pathway bottlenecks, which could efficiently lead to accumulation of carotenoids in microorganisms. The identification of CCOs spatial structures isolated from different species has made a significant contribution to the current state of knowledge. Current trends in carotenoid-related flavor modification are also discussed. In particular, we propose the carotenoid-synthesizing yeast Rhodotorula spp. for the production of food bioactive compounds. Understanding the behavior underlying the formation of norisoprenoids from carotenoids using interdisciplinary approaches may point toward other areas of investigation that could lead to better exploiting the potential use of autochthonous yeast in flavor enhancement.

Removing the Bottleneck: Introducing cMatch - A Lightweight Tool for Construct-Matching in Synthetic Biology

We present a software tool, called cMatch, to reconstruct and identify synthetic genetic constructs from their sequences, or a set of sub-sequences—based on two practical pieces of information: their modular structure, and libraries of components. Although developed for combinatorial pathway engineering problems and addressing their quality control (QC) bottleneck, cMatch is not restricted to these applications. QC takes place post assembly, transformation and growth. It has a simple goal, to verify that the genetic material contained in a cell matches what was intended to be built - and when it is not the case, to locate the discrepancies and estimate their severity. In terms of reproducibility/reliability, the QC step is crucial. Failure at this step requires repetition of the construction and/or sequencing steps. When performed manually or semi-manually QC is an extremely time-consuming, error prone process, which scales very poorly with the number of constructs and their complexity. To make QC frictionless and more reliable, cMatch performs an operation we have called “construct-matching” and automates it. Construct-matching is more thorough than simple sequence-matching, as it matches at the functional level-and quantifies the matching at the individual component level and across the whole construct. Two algorithms (called CM_1 and CM_2) are presented. They differ according to the nature of their inputs. CM_1 is the core algorithm for construct-matching and is to be used when input sequences are long enough to cover constructs in their entirety (e.g., obtained with methods such as next generation sequencing). CM_2 is an extension designed to deal with shorter data (e.g., obtained with Sanger sequencing), and that need recombining. Both algorithms are shown to yield accurate construct-matching in a few minutes (even on hardware with limited processing power), together with a set of metrics that can be used to improve the robustness of the decision-making process. To ensure reliability and reproducibility, cMatch builds on the highly validated pairwise-matching Smith-Waterman algorithm. All the tests presented have been conducted on synthetic data for challenging, yet realistic constructs - and on real data gathered during studies on a metabolic engineering example (lycopene production).

Toward improved terpenoids biosynthesis: strategies to enhance the capabilities of cell factories

Terpenoids form the most diversified class of natural products, which have gained application in the pharmaceutical, food, transportation, and fine and bulk chemical industries. Extraction from naturally occurring sources does not meet industrial demands, whereas chemical synthesis is often associated with poor enantio-selectivity, harsh working conditions, and environmental pollutions. Microbial cell factories come as a suitable replacement. However, designing efficient microbial platforms for isoprenoid synthesis is often a challenging task. This has to do with the cytotoxic effects of pathway intermediates and some end products, instability of expressed pathways, as well as high enzyme promiscuity. Also, the low enzymatic activity of some terpene synthases and prenyltransferases, and the lack of an efficient throughput system to screen improved high-performing strains are bottlenecks in strain development. Metabolic engineering and synthetic biology seek to overcome these issues through the provision of effective synthetic tools. This review sought to provide an in-depth description of novel strategies for improving cell factory performance. We focused on improving transcriptional and translational efficiencies through static and dynamic regulatory elements, enzyme engineering and high-throughput screening strategies, cellular function enhancement through chromosomal integration, metabolite tolerance, and modularization of pathways.

Diversifying Isoprenoid Platforms via Atypical Carbon Substrates and Non-model Microorganisms

Isoprenoid compounds are biologically ubiquitous, and their characteristic modularity has afforded products ranging from pharmaceuticals to biofuels. Isoprenoid production has been largely successful in Escherichia coli and Saccharomyces cerevisiae with metabolic engineering of the mevalonate (MVA) and methylerythritol phosphate (MEP) pathways coupled with the expression of heterologous terpene synthases. Yet conventional microbial chassis pose several major obstacles to successful commercialization including the affordability of sugar substrates at scale, precursor flux limitations, and intermediate feedback-inhibition. Now, recent studies have challenged typical isoprenoid paradigms by expanding the boundaries of terpene biosynthesis and using non-model organisms including those capable of metabolizing atypical C1 substrates. Conversely, investigations of non-model organisms have historically informed optimization in conventional microbes by tuning heterologous gene expression. Here, we review advances in isoprenoid biosynthesis with specific focus on the synergy between model and non-model organisms that may elevate the commercial viability of isoprenoid platforms by addressing the dichotomy between high titer production and inexpensive substrates.

Microbial production of advanced biofuels

Concerns over climate change have necessitated a rethinking of our transportation infrastructure. One possible alternative to carbon-polluting fossil fuels is biofuels produced by engineered microorganisms that use a renewable carbon source. Two biofuels, ethanol and biodiesel, have made inroads in displacing petroleum-based fuels, but their uptake has been limited by the amounts that can be used in conventional engines and by their cost. Advanced biofuels that mimic petroleum-based fuels are not limited by the amounts that can be used in existing transportation infrastructure but have had limited uptake due to costs. In this Review, we discuss engineering metabolic pathways to produce advanced biofuels, challenges with substrate and product toxicity with regard to host microorganisms and methods to engineer tolerance, and the use of functional genomics and machine learning approaches to produce advanced biofuels and prospects for reducing their costs.

Advances in engineering microbial biosynthesis of aromatic compounds and related compounds

Aromatic compounds have broad applications and have been the target of biosynthetic processes for several decades. New biomolecular engineering strategies have been applied to improve production of aromatic compounds in recent years, some of which are expected to set the stage for the next wave of innovations. Here, we will briefly complement existing reviews on microbial production of aromatic compounds by focusing on a few recent trends where considerable work has been performed in the last 5 years. The trends we highlight are pathway modularization and compartmentalization, microbial co-culturing, non-traditional host engineering, aromatic polymer feedstock utilization, engineered ring cleavage, aldehyde stabilization, and biosynthesis of non-standard amino acids. Throughout this review article, we will also touch on unmet opportunities that future research could address.

Construction and Characterization of a Gradient Strength Promoter Library for Fine-Tuned Gene Expression in Bacillus licheniformis

Bacillus licheniformis DW2 is an important industrial strain for bacitracin production, and it is also used for biochemical production, however, the lack of effective toolkit for precise regulation of gene expression hindered its application seriously. Here, a gradient strength promoter library was constructed based on bacitracin synthetase gene cluster promoter PbacA. First, different PbacA promoter variants were constructed via coupling PbacA with various 5'-UTRs, and expression ranges of 32.6-741.8% were attained among these promoters. Then, three promoters, PUbay (strong), PbacA (middle), and PUndh (weakest), were applied for red fluorescent protein (RFP) and keratinase expression assays, and these promoters were proven to have good universality for different proteins. Second, the promoter of bacitracin synthetase gene cluster was replaced by these three promoters, and bacitraicn titer was enhanced by 14.62% when PUbay was applied, which was decreased by 98.05% under the mediation of PUndh compared with that of the original strain DW2. Third, promoters PUbay, PUyvgO, and PUndh were selected to regulate the expression levels of critical genes that are responsible for pucheriminic acid synthesis, and pucheriminic acid yield was increased by 194.1% via manipulating synthetic and competitive pathways. Finally, promoters PUbay, PbacA, and PUndh were applied for green fluorescent protein (GFP) and RFP expression in Escherichia coli, and consistent effects were attained based on our results. Taken together, a gradient strength promoter library was constructed in this research, which provided an effective toolkit for fine-tuning gene expression and reprogramming metabolite metabolic flux in B. licheniformis.

Enzymes, In Vivo Biocatalysis, and Metabolic Engineering for Enabling a Circular Economy and Sustainability

Since the industrial revolution, the rapid growth and development of global industries have depended largely upon the utilization of coal-derived chemicals, and more recently, the utilization of petroleum-based chemicals. These developments have followed a linear economy model (produce, consume, and dispose). As the world is facing a serious threat from the climate change crisis, a more sustainable solution for manufacturing, i.e., circular economy in which waste from the same or different industries can be used as feedstocks or resources for production offers an attractive industrial/business model. In nature, biological systems, i.e., microorganisms routinely use their enzymes and metabolic pathways to convert organic and inorganic wastes to synthesize biochemicals and energy required for their growth. Therefore, an understanding of how selected enzymes convert biobased feedstocks into special (bio)chemicals serves as an important basis from which to build on for applications in biocatalysis, metabolic engineering, and synthetic biology to enable biobased processes that are greener and cleaner for the environment. This review article highlights the current state of knowledge regarding the enzymatic reactions used in converting biobased wastes (lignocellulosic biomass, sugar, phenolic acid, triglyceride, fatty acid, and glycerol) and greenhouse gases (CO₂ and CH₄) into value-added products and discusses the current progress made in their metabolic engineering. The commercial aspects and life cycle assessment of products from enzymatic and metabolic engineering are also discussed. Continued development in the field of metabolic engineering would offer diversified solutions which are sustainable and renewable for manufacturing valuable chemicals.

Structure of a Minimal α-Carboxysome-Derived Shell and Its Utility in Enzyme Stabilization

Bacterial microcompartments are proteinaceous shells that encase specialized metabolic processes in bacteria. Recent advances in simplification of these intricate shells have encouraged bioengineering efforts. Here, we construct minimal shells derived from the Halothiobacillus neapolitanus α-carboxysome, which we term Cso-shell. Using cryogenic electron microscopy, the atomic-level structures of two shell forms were obtained, reinforcing notions of evolutionarily conserved features in bacterial microcompartment shell architecture. Encapsulation peptide sequences that facilitate loading of heterologous protein cargo within the shells were identified. We further provide a first demonstration in utilizing minimal bacterial microcompartment-derived shells for hosting heterologous enzymes. Cso-shells were found to stabilize enzymatic activities against heat shock, presence of methanol co-solvent, consecutive freeze-thawing, and alkaline environments. This study yields insights into α-carboxysome assembly and advances the utility of synthetic bacterial microcompartments as nanoreactors capable of stabilizing enzymes with varied properties and reaction chemistries.

Challenges and opportunities in biological funneling of heterogeneous and toxic substrates beyond lignin

Significant developments in the understanding and manipulation of microbial metabolism have enabled the use of engineered biological systems toward a more sustainable energy and materials economy. While developments in metabolic engineering have primarily focused on the conversion of carbohydrates, substantial opportunities exist for using these same principles to extract value from more heterogeneous and toxic waste streams, such as those derived from lignin, biomass pyrolysis, or industrial waste. Funneling heterogeneous substrates from these streams toward valuable products, termed biological funneling, presents new challenges in balancing multiple catabolic pathways competing for shared cellular resources and engineering against perturbation from toxic substrates. Solutions to many of these challenges have been explored within the field of lignin valorization. This perspective aims to extend beyond lignin to highlight the challenges and discuss opportunities for use of biological systems to upgrade previously inaccessible waste streams.

Engineering microalgae: transition from empirical design to programmable cells

Domesticated microalgae hold great promise for the sustainable provision of various bioresources for human domestic and industrial consumption. Efforts to exploit their potential are far from being fully realized due to limitations in the know-how of microalgal engineering. The associated technologies are not as well developed as those for heterotrophic microbes, cyanobacteria, and plants. However, recent studies on microalgal metabolic engineering, genome editing, and synthetic biology have immensely helped to enhance transformation efficiencies and are bringing new insights into this field. Therefore, this article, summarizes recent developments in microalgal biotechnology and examines the prospects for generating specialty and commodity products through the processes of metabolic engineering and synthetic biology. After a brief examination of empirical engineering methods and vector design, this article focuses on quantitative transformation cassette design, elaborates on target editing methods and emerging digital design of algal cellular metabolism to arrive at high yields of valuable products. These advances have enabled a transition of manners in microalgal engineering from single-gene and enzyme-based metabolic engineering to systems-level precision engineering, from cells created with genetically modified (GM) tags to that without GM tags, and ultimately from proof of concept to tangible industrial applications. Finally, future trends are proposed in microalgal engineering, aiming to establish individualized transformation systems in newly identified species for strain-specific specialty and commodity products, while developing sophisticated universal toolkits in model algal species.

Rationally optimized generation of integrated Escherichia coli with stable and high yield lycopene biosynthesis from heterologous mevalonate (MVA) and lycopene expression pathways

The stability and high productivity of heterogeneous terpenoid production in Escherichia coli expression system is one of the most key issues for its large scale industrialization. In the current study on taking lycopene biosynthesis as an example, an integrated Escherichia coli system has been generated successfully, which resulted into stable and high lycopene production. In this process, two modules of mevalonate (MVA) pathway and one module of lycopene expression pathway were completely integrated in the chromosome. Firstly, the copy number and integrated position of three modules of heterologous pathways were rationally optimized. Later, a strain DH416 equipped with heterogeneous expression pathways through chromosomal integration was efficiently derived from parental strain DH411. The evolving DH416 strain efficiently produced the lycopene level of 1.22 g/L (49.9 mg/g DCW) in a 5 L fermenter with mean productivity of 61.0 mg/L/h. Additionally, the integrated strain showed more genetic stability than the plasmid systems after successive 21st passage.

A platform for post-translational spatiotemporal control of cellular proteins

Mammalian cells process information through coordinated spatiotemporal regulation of proteins. Engineering cellular networks thus relies on efficient tools for regulating protein levels in specific subcellular compartments. To address the need to manipulate the extent and dynamics of protein localization, we developed a platform technology for the target-specific control of protein destination. This platform is based on bifunctional molecules comprising a target-specific nanobody and universal sequences determining target subcellular localization or degradation rate. We demonstrate that nanobody-mediated localization depends on the expression level of the target and the nanobody, and the extent of target subcellular localization can be regulated by combining multiple target-specific nanobodies with distinct localization or degradation sequences. We also show that this platform for nanobody-mediated target localization and degradation can be regulated transcriptionally and integrated within orthogonal genetic circuits to achieve the desired temporal control over spatial regulation of target proteins. The platform reported in this study provides an innovative tool to control protein subcellular localization, which will be useful to investigate protein function and regulate large synthetic gene circuits.

Statistical Design of Experiments for Synthetic Biology

The design and optimization of biological systems is an inherently complex undertaking that requires careful balancing of myriad synergistic and antagonistic variables. However, despite this complexity, much synthetic biology research is predicated on One Factor at A Time (OFAT) experimentation; the genetic and environmental variables affecting the activity of a system of interest are sequentially altered while all other variables are held constant. Beyond being time and resource intensive, OFAT experimentation crucially ignores the effect of interactions between factors. Given the ubiquity of interacting genetic and environmental factors in biology this failure to account for interaction effects in OFAT experimentation can result in the development of suboptimal systems. To address these limitations, an increasing number of studies have turned to Design of Experiments (DoE), a suite of methods that enable efficient, systematic exploration and exploitation of complex design spaces. This review provides an overview of DoE for synthetic biologists. Key concepts and commonly used experimental designs are introduced, and we discuss the advantages of DoE as compared to OFAT experimentation. We dissect the applicability of DoE in the context of synthetic biology and review studies which have successfully employed these methods, illustrating the potential of statistical experimental design to guide the design, characterization, and optimization of biological protocols, pathways, and processes.

Balancing glucose and oxygen uptake rates to enable high amorpha-4,11-diene production in Escherichia coli via the methylerythritol phosphate pathway

Amorpha-4,11-diene (AMD4,11) is a precursor to artemisinin, a potent antimalarial drug that is traditionally extracted from the shrubs of Artemisia annua. Despite significant prior efforts to produce artemisinin and its precursors through biotechnology, there remains a dire need for more efficient biosynthetic routes for its production. Here, we describe the optimization of key process conditions for an Escherichia coli strain producing AMD4,11 via the native methylerythritol phosphate (MEP) pathway. By studying the interplay between glucose uptake rates and oxygen demand, we were able to identify optimal conditions for increasing carbon flux through the MEP pathway by manipulating the availability of NADPH required for terpenoid production. Installation of an optimal q_O2 /q_glucose led to a 6.7-fold increase in product titers and a 6.5-fold increase in carbon yield.

Complex natural product production methods and options

Natural products have had a major impact upon quality of life, with antibiotics as a classic example of having a transformative impact upon human health. In this contribution, we will highlight both historic and emerging methods of natural product bio-manufacturing. Traditional methods of natural product production relied upon native cellular host systems. In this context, pragmatic and effective methodologies were established to enable widespread access to natural products. In reviewing such strategies, we will also highlight the development of heterologous natural product biosynthesis, which relies instead on a surrogate host system theoretically capable of advanced production potential. In comparing native and heterologous systems, we will comment on the base organisms used for natural product biosynthesis and how the properties of such cellular hosts dictate scaled engineering practices to facilitate compound distribution. In concluding the article, we will examine novel efforts in production practices that entirely eliminate the constraints of cellular production hosts. That is, cell free production efforts will be introduced and reviewed for the purpose of complex natural product biosynthesis. Included in this final analysis will be research efforts made on our part to test the cell free biosynthesis of the complex polyketide antibiotic natural product erythromycin.

Reverse Engineering Targets for Recombinant Protein Production in Corynebacterium glutamicum Inspired by a Fast-Growing Evolved Descendant

We previously reported a Corynebacterium glutamicum JH41 strain with a 58% faster growth rate through application of adaptive laboratory evolution. To verify that the fast-reproducing strain was useful as a host for recombinant protein expression, we introduced a plasmid responsible for the secretory production of a recombinant protein. The JH41 strain harboring the plasmid indeed produced the secretory recombinant protein at a 2.7-fold greater rate than its ancestral strain. To provide the reverse engineering targets responsible for boosting recombinant protein production and cell reproduction, we compared the genome sequence of the JH41 strain with its ancestral strain. Among the 15 genomic variations, a point mutation was confirmed in the 14 bases upstream of NCgl1959 (encoding a presumed siderophore-binding protein). This mutation allowed derepression of NCgl1959, thereby increasing iron consumption and ATP generation. A point mutation in the structural gene ramA (A239G), a LuxR-type global transcription regulator involved in central metabolism, allowed an increase in glucose consumption. Therefore, mutations to increase the iron and carbon consumption were concluded as being responsible for the enhanced production of recombinant protein and cell reproduction in the evolved host.

Systems biology approaches integrated with artificial intelligence for optimized metabolic engineering

Metabolic engineering aims to maximize the production of bio-economically important substances (compounds, enzymes, or other proteins) through the optimization of the genetics, cellular processes and growth conditions of microorganisms. This requires detailed understanding of underlying metabolic pathways involved in the production of the targeted substances, and how the cellular processes or growth conditions are regulated by the engineering. To achieve this goal, a large system of experimental techniques, compound libraries, computational methods and data resources, including multi-omics data, are used. The recent advent of multi-omics systems biology approaches significantly impacted the field by opening new avenues to perform dynamic and large-scale analyses that deepen our knowledge on the manipulations. However, with the enormous transcriptomics, proteomics and metabolomics available, it is a daunting task to integrate the data for a more holistic understanding. Novel data mining and analytics approaches, including Artificial Intelligence (AI), can provide breakthroughs where traditional low-throughput experiment-alone methods cannot easily achieve. Here, we review the latest attempts of combining systems biology and AI in metabolic engineering research, and highlight how this alliance can help overcome the current challenges facing industrial biotechnology, especially for food-related substances and compounds using microorganisms.

A machine learning Automated Recommendation Tool for synthetic biology

Synthetic biology allows us to bioengineer cells to synthesize novel valuable molecules such as renewable biofuels or anticancer drugs. However, traditional synthetic biology approaches involve ad-hoc engineering practices, which lead to long development times. Here, we present the Automated Recommendation Tool (ART), a tool that leverages machine learning and probabilistic modeling techniques to guide synthetic biology in a systematic fashion, without the need for a full mechanistic understanding of the biological system. Using sampling-based optimization, ART provides a set of recommended strains to be built in the next engineering cycle, alongside probabilistic predictions of their production levels. We demonstrate the capabilities of ART on simulated data sets, as well as experimental data from real metabolic engineering projects producing renewable biofuels, hoppy flavored beer without hops, fatty acids, and tryptophan. Finally, we discuss the limitations of this approach, and the practical consequences of the underlying assumptions failing.

Optogenetic Control of Heterologous Metabolism in E. coli

Multiobjective optimization of microbial chassis for the production of xenobiotic compounds requires the implementation of metabolic control strategies that permit dynamic distribution of cellular resources between biomass and product formation. We addressed this need in a previous study by engineering the T7 RNA polymerase to be thermally responsive. The modified polymerase is activated only after the temperature of the host cell falls below 18 °C, and Escherichia coli cells that employ the protein to transcribe the heterologous lycopene biosynthetic pathway exhibit impressive improvements in productivity. We have expanded our toolbox of metabolic switches in the current study by engineering a version of the T7 RNA polymerase that drives the transition between biomass and product formation upon stimulation with red light. The engineered polymerase is expressed as two distinct polypeptide chains. Each chain comprises one of two photoactive components from Arabidopsis thaliana, phytochrome B (PhyB) and phytochrome-integrating factor 3 (PIF3), as well as the N- or C-terminus domains of both, the vacuolar ATPase subunit (VMA) intein of Saccharomyces cerevisiae and the polymerase. Red light drives photodimerization of PhyB and PIF3, which then brings together the N- and C-terminus domains of the VMA intein. Trans-splicing of the intein follows suit and produces an active form of the polymerase that subsequently transcribes any sequence that is under the control of a T7 promoter. The photodimerization also involves a third element, the cyanobacterial chromophore phycocyanobilin (PCB), which too is expressed heterologously by E. coli. We deployed this version of the T7 RNA polymerase to control the production of lycopene in E. coli and observed tight control of pathway expression. We tested a variety of expression configurations to identify one that imposes the lowest metabolic burden on the strain, and we subsequently optimized key parameters such as the source, moment, and duration of photostimulation. We also identified targets for future refinement of the circuit. In summary, our work is a significant advance for the field and greatly expands on previous work by other groups that have used optogenetic circuits to control heterologous metabolism in prokaryotic hosts.

Unlocking the biosynthesis of sesquiterpenoids from methane via the methylerythritol phosphate pathway in methanotrophic bacteria, using α-humulene as a model compound

Isoprenoids are an abundant and diverse class of natural products with various applications in the pharmaceutical, cosmetics and biofuel industries. A methanotroph-based biorefinery is an attractive scenario for the production of a variety of value-added compounds from methane, because methane is a promising alternative feedstock for industrial biomanufacturing. In this study, we metabolically engineered Methylotuvimicrobium alcaliphilum 20Z for de novo synthesis of a sesquiterpenoid from methane, using α-humulene as a model compound, via optimization of the native methylerythritol phosphate (MEP) pathway. Expression of codon-optimized α-humulene synthase from Zingiber zerumbet in M. alcaliphilum 20Z resulted in an initial yield of 0.04 mg/g dry cell weight. Overexpressing key enzymes (IspA, IspG, and Dxs) for debottlenecking of the MEP pathway increased α-humulene production 5.2-fold compared with the initial strain. Subsequently, redirecting the carbon flux through the Embden-Meyerhof-Parnas pathway resulted in an additional 3-fold increase in α-humulene production. Additionally, a genome-scale model using flux scanning based on enforced objective flux method was used to identify potential overexpression targets to increase flux towards isoprenoid production. Several target reactions from cofactor synthesis pathways were probed and evaluated for their effects on α-humulene synthesis, resulting in α-humulene yield up to 0.75 mg/g DCW with 18.8-fold enhancement from initial yield. This study first demonstrates production of a sesquiterpenoid from methane using methanotrophs as the biocatalyst and proposes potential strategies to enhance production of sesquiterpenoid and related isoprenoid products in engineered methanotrophic bacteria.

Metabolic pathway engineering: Perspectives and applications

BACKGROUND

Metabolic engineering aims at contriving microbes as biocatalysts for enhanced and cost-effective production of countless secondary metabolites. These secondary metabolites can be treated as the resources of industrial chemicals, pharmaceuticals and fuels. Plants are also crucial targets for metabolic engineers to produce necessary secondary metabolites. Metabolic engineering of both microorganism and plants also contributes towards drug discovery. In order to implement advanced metabolic engineering techniques efficiently, metabolic engineers should have detailed knowledge about cell physiology and metabolism. Principle behind methodologies: Genome-scale mathematical models of integrated metabolic, signal transduction, gene regulatory and protein-protein interaction networks along with experimental validation can provide such knowledge in this context. Incorporation of omics data into these models is crucial in the case of drug discovery. Inverse metabolic engineering and metabolic control analysis (MCA) can help in developing such models. Artificial intelligence methodology can also be applied for efficient and accurate metabolic engineering.

CONCLUSION

In this review, we discuss, at the beginning, the perspectives of metabolic engineering and its application on microorganism and plant leading to drug discovery. At the end, we elaborate why inverse metabolic engineering and MCA are closely related to modern metabolic engineering. In addition, some crucial steps ensuring efficient and optimal metabolic engineering strategies have been discussed. Moreover, we explore the use of genomics data for the activation of silent metabolic clusters and how it can be integrated with metabolic engineering. Finally, we exhibit a few applications of artificial intelligence to metabolic engineering.

Biocatalysis and biomass conversion: enabling a circular economy

This paper is based on a lecture presented to the Royal Society in London on 24 June 2019. Two of the grand societal and technological challenges of the twenty-first century are the 'greening' of chemicals manufacture and the ongoing transition to a sustainable, carbon neutral economy based on renewable biomass as the raw material, a so-called bio-based economy. These challenges are motivated by the need to eliminate environmental degradation and mitigate climate change. In a bio-based economy, ideally waste biomass, particularly agricultural and forestry residues and food supply chain waste, are converted to liquid fuels, commodity chemicals and biopolymers using clean, catalytic processes. Biocatalysis has the right credentials to achieve this goal. Enzymes are biocompatible, biodegradable and essentially non-hazardous. Additionally, they are derived from inexpensive renewable resources which are readily available and not subject to the large price fluctuations which undermine the long-term commercial viability of scarce precious metal catalysts. Thanks to spectacular advances in molecular biology the landscape of biocatalysis has dramatically changed in the last two decades. Developments in (meta)genomics in combination with 'big data' analysis have revolutionized new enzyme discovery and developments in protein engineering by directed evolution have enabled dramatic improvements in their performance. These developments have their confluence in the bio-based circular economy. This article is part of a discussion meeting issue 'Science to enable the circular economy'.

Modular engineering for microbial production of carotenoids

There is an increasing demand for carotenoids due to their applications in the food, flavor, pharmaceutical and feed industries, however, the extraction and synthesis of these compounds can be expensive and technically challenging. Microbial production of carotenoids provides an attractive alternative to the negative environmental impacts and cost of chemical synthesis or direct extraction from plants. Metabolic engineering and synthetic biology approaches have been widely utilized to reconstruct and optimize pathways for carotenoid overproduction in microorganisms. This review summarizes the current advances in microbial engineering for carotenoid production and divides the carotenoid biosynthesis building blocks into four distinct metabolic modules: 1) central carbon metabolism, 2) cofactor metabolism, 3) isoprene supplement metabolism and 4) carotenoid biosynthesis. These four modules focus on redirecting carbon flux and optimizing cofactor supplements for isoprene precursors needed for carotenoid synthesis. Future perspectives are also discussed to provide insights into microbial engineering principles for overproduction of carotenoids.

Efficient production of myo-inositol in Escherichia coli through metabolic engineering

BACKGROUND

The biosynthesis of high value-added compounds using metabolically engineered strains has received wide attention in recent years. Myo-inositol (inositol), an important compound in the pharmaceutics, cosmetics and food industries, is usually produced from phytate via a harsh set of chemical reactions. Recombinant Escherichia coli strains have been constructed by metabolic engineering strategies to produce inositol, but with a low yield. The proper distribution of carbon flux between cell growth and inositol production is a major challenge for constructing an efficient inositol-synthesis pathway in bacteria. Construction of metabolically engineered E. coli strains with high stoichiometric yield of inositol is desirable.

RESULTS

In the present study, we designed an inositol-synthesis pathway from glucose with a theoretical stoichiometric yield of 1 mol inositol/mol glucose. Recombinant E. coli strains with high stoichiometric yield (> 0.7 mol inositol/mol glucose) were obtained. Inositol was successfully biosynthesized after introducing two crucial enzymes: inositol-3-phosphate synthase (IPS) from Trypanosoma brucei, and inositol monophosphatase (IMP) from E. coli. Based on starting strains E. coli BW25113 (wild-type) and SG104 (ΔptsG::glk, ΔgalR::zglf, ΔpoxB::acs), a series of engineered strains for inositol production was constructed by deleting the key genes pgi, pfkA and pykF. Plasmid-based expression systems for IPS and IMP were optimized, and expression of the gene zwf was regulated to enhance the stoichiometric yield of inositol. The highest stoichiometric yield (0.96 mol inositol/mol glucose) was achieved from recombinant strain R15 (SG104, Δpgi, Δpgm, and RBSL5-zwf). Strain R04 (SG104 and Δpgi) reached high-density in a 1-L fermenter when using glucose and glycerol as a mixed carbon source. In scaled-up fed-batch bioconversion in situ using strain R04, 0.82 mol inositol/mol glucose was produced within 23 h, corresponding to a titer of 106.3 g/L (590.5 mM) inositol.

CONCLUSIONS

The biosynthesis of inositol from glucose in recombinant E. coli was optimized by metabolic engineering strategies. The metabolically engineered E. coli strains represent a promising method for future inositol production. This study provides an essential reference to obtain a suitable distribution of carbon flux between glycolysis and inositol synthesis.