Optimal cofactor swapping can increase the theoretical yield for chemical production in Escherichia coli and Saccharomyces cerevisiae

Deep learning for NAD/NADP cofactor prediction and engineering using transformer attention analysis in enzymes

Understanding and manipulating the cofactor preferences of NAD(P)-dependent oxidoreductases, the most widely distributed enzyme group in nature, is increasingly crucial in bioengineering. However, large-scale identification of the cofactor preferences and the design of mutants to switch cofactor specificity remain as complex tasks. Here, we introduce DISCODE (Deep learning-based Iterative pipeline to analyze Specificity of COfactors and to Design Enzyme), a novel transformer-based deep learning model to predict NAD(P) cofactor preferences. For model training, a total of 7,132 NAD(P)-dependent enzyme sequences were collected. Leveraging whole-length sequence information, DISCODE classifies the cofactor preferences of NAD(P)-dependent oxidoreductase protein sequences without structural or taxonomic limitation. The model showed 97.4% and 97.3% of accuracy and F1 score, respectively. A notable feature of DISCODE is the interpretability of its transformer layers. Analysis of attention layers in the model enables identification of several residues that showed significantly higher attention weights. They were well aligned with structurally important residues that closely interact with NAD(P), facilitating the identification of key residues for determining cofactor specificities. These key residues showed high consistency with verified cofactor switching mutants. Integrated into an enzyme design pipeline, DISCODE coupled with attention analysis, enables a fully automated approach to redesign cofactor specificity.

Computational analysis into the potential of azo dyes as a feedstock for actinorhodin biosynthesis in Pseudomonas putida

Fermentation-based biosynthesis in synthetic biology relies heavily on sugar-derived feedstocks, a limited and carbon-intensive commodity. Unconventional feedstocks from less-noble sources such as waste are being utilized to produce high-value chemical products. Azo dyes, a major pollutant commonly discharged by food, textile, and pharmaceutical industries, present significant health and environmental risks. We explore the potential of engineering Pseudomonas putida KT2440 to utilize azo dyes as a substrate to produce a polyketide, actinorhodin (ACT). Using the constrained minimal cut sets (cMCS) approach, we identified metabolic interventions that optimize ACT biosynthesis and compare the growth-coupling solutions attainable on an azo dye compared to glucose. Our results predicted that azo dyes could perform better as a feedstock for ACT biosynthesis than glucose as it allowed growth-coupling regimes that are unfeasible with glucose and generated an 18.28% higher maximum ACT flux. By examining the flux distributions enabled in different carbon sources, we observed that carbon fluxes from aromatic compounds like azo dyes have a unique capability to leverage gluconeogenesis to support both growth and production of secondary metabolites that produce excess NADH. Carbon sources are commonly chosen based on the host organism, availability, cost, and environmental implications. We demonstrated that careful selection of carbon sources is also crucial to ensure that the resulting flux distribution is suitable for further metabolic engineering of microbial cell factories.

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.

Network-wide thermodynamic constraints shape NAD(P)H cofactor specificity of biochemical reactions

The ubiquitous coexistence of the redox cofactors NADH and NADPH is widely considered to facilitate an efficient operation of cellular redox metabolism. However, it remains unclear what shapes the NAD(P)H specificity of specific redox reactions. Here, we present a computational framework to analyze the effect of redox cofactor swaps on the maximal thermodynamic potential of a metabolic network and use it to investigate key aspects of redox cofactor redundancy in Escherichia coli. As one major result, our analysis suggests that evolved NAD(P)H specificities are largely shaped by metabolic network structure and associated thermodynamic constraints enabling thermodynamic driving forces that are close or even identical to the theoretical optimum and significantly higher compared to random specificities. Furthermore, while redundancy of NAD(P)H is clearly beneficial for thermodynamic driving forces, a third redox cofactor would require a low standard redox potential to be advantageous. Our approach also predicts trends of redox-cofactor concentration ratios and could facilitate the design of optimal redox cofactor specificities.

OptDesign: Identifying Optimum Design Strategies in Strain Engineering for Biochemical Production

Computational tools have been widely adopted for strain optimization in metabolic engineering, contributing to numerous success stories of producing industrially relevant biochemicals. However, most of these tools focus on single metabolic intervention strategies (either gene/reaction knockout or amplification alone) and rely on hypothetical optimality principles (e.g., maximization of growth) and precise gene expression (e.g., fold changes) for phenotype prediction. This paper introduces OptDesign, a new two-step strain design strategy. In the first step, OptDesign selects regulation candidates that have a noticeable flux difference between the wild type and production strains. In the second step, it computes optimal design strategies with limited manipulations (combining regulation and knockout), leading to high biochemical production. The usefulness and capabilities of OptDesign are demonstrated for the production of three biochemicals in Escherichia coli using the latest genome-scale metabolic model iML1515, showing highly consistent results with previous studies while suggesting new manipulations to boost strain performance. The source code is available at https://github.com/chang88ye/OptDesign.

Redox metabolism for improving whole-cell P450-catalysed terpenoid biosynthesis

The growing preference for producing cytochrome P450-mediated natural products in microbial systems stems from the challenging nature of the organic chemistry approaches. The P450 enzymes are redox-dependent proteins, through which they source electrons from reducing cofactors to drive their activities. Widely researched in biochemistry, most of the previous studies have extensively utilised expensive cell-free assays to reveal mechanistic insights into P450 functionalities in presence of commercial redox partners. However, in the context of microbial bioproduction, the synergic activity of P450- reductase proteins in microbial systems have not been largely investigated. This is mainly due to limited knowledge about their mutual interactions in the context of complex systems. Hence, manipulating the redox potential for natural product synthesis in microbial chassis has been limited. As the potential of redox state as crucial regulator of P450 biocatalysis has been greatly underestimated by the scientific community, in this review, we re-emphasize their pivotal role in modulating the in vivo P450 activity through affecting the product profile and yield. Particularly, we discuss the applications of widely used in vivo redox engineering methodologies for natural product synthesis to provide further suggestions for patterning on P450-based terpenoids production in microbial platforms.

Metabolic engineering strategies for de novo biosynthesis of sterols and steroids in yeast

Steroidal compounds are of great interest in the pharmaceutical field, with steroidal drugs as the second largest category of medicine in the world. Advances in synthetic biology and metabolic engineering have enabled de novo biosynthesis of sterols and steroids in yeast, which is a green and safe production route for these valuable steroidal compounds. In this review, we summarize the metabolic engineering strategies developed and employed for improving the de novo biosynthesis of sterols and steroids in yeast based on the regulation mechanisms, and introduce the recent progresses in de novo synthesis of some typical sterols and steroids in yeast. The remaining challenges and future perspectives are also discussed.

Diamine Biosynthesis: Research Progress and Application Prospects

Diamines are important monomers for polyamide plastics; they include 1,3-diaminopropane, 1,4-diaminobutane, 1,5-diaminopentane, and 1,6-diaminohexane, among others. With increasing attention on environmental problems and green sustainable development, utilizing renewable raw materials for the synthesis of diamines is crucial for the establishment of a sustainable plastics industry. Recently, high-performance microbial factories, such as Escherichia coli and Corynebacterium glutamicum, have been widely used in the production of diamines. In particular, several synthetic pathways of 1,6-diaminohexane have been proposed based on glutamate or adipic acid. Here, we reviewed approaches for the biosynthesis of diamines, including metabolic engineering and biocatalysis, and the application of bio-based diamines in nylon materials. The related challenges and opportunities in the development of renewable bio-based diamines and nylon materials are also discussed.

NIHBA: a network interdiction approach for metabolic engineering design

MOTIVATION

Flux balance analysis (FBA) based bilevel optimization has been a great success in redesigning metabolic networks for biochemical overproduction. To date, many computational approaches have been developed to solve the resulting bilevel optimization problems. However, most of them are of limited use due to biased optimality principle, poor scalability with the size of metabolic networks, potential numeric issues or low quantity of design solutions in a single run.

RESULTS

Here, we have employed a network interdiction model free of growth optimality assumptions, a special case of bilevel optimization, for computational strain design and have developed a hybrid Benders algorithm (HBA) that deals with complicating binary variables in the model, thereby achieving high efficiency without numeric issues in search of best design strategies. More importantly, HBA can list solutions that meet users' production requirements during the search, making it possible to obtain numerous design strategies at a small runtime overhead (typically ∼1 h, e.g. studied in this article).

AVAILABILITY AND IMPLEMENTATION

Source code implemented in the MATALAB Cobratoolbox is freely available at https://github.com/chang88ye/NIHBA.

CONTACT

math4neu@gmail.com or natalio.krasnogor@ncl.ac.uk.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The relevance of enzyme specificity for coenzymes and the presence of 6-phosphogluconate dehydrogenase for polyhydroxyalkanoates production in the metabolism of Pseudomonas sp. LFM046

Reconstruction of genome-based metabolic model is a useful approach for the assessment of metabolic pathways, genes and proteins involved in the environmental fitness capabilities or pathogenic potential as well as for biotechnological processes development. Pseudomonas sp. LFM046 was selected as a good polyhydroxyalkanoates (PHA) producer from carbohydrates and plant oils. Its complete genome sequence and metabolic model were obtained. Analysis revealed that the gnd gene, encoding 6-phosphogluconate dehydrogenase, is absent in Pseudomonas sp. LFM046 genome. In order to improve the knowledge about LFM046 metabolism, the coenzyme specificities of different enzymes was evaluated. Furthermore, the heterologous expression of gnd genes from Pseudomonas putida KT2440 (NAD⁺ dependent) and Escherichia coli MG1655 (NADP⁺ dependent) in LFM046 was carried out and provoke a delay on cell growth and a reduction in PHA yield, respectively. The results indicate that the adjustment in cyclic Entner-Doudoroff pathway may be an interesting strategy for it and other bacteria to simultaneously meet divergent cell needs during cultivation phases of growth and PHA production.

Application of combinatorial optimization strategies in synthetic biology

In the first wave of synthetic biology, genetic elements, combined into simple circuits, are used to control individual cellular functions. In the second wave of synthetic biology, the simple circuits, combined into complex circuits, form systems-level functions. However, efforts to construct complex circuits are often impeded by our limited knowledge of the optimal combination of individual circuits. For example, a fundamental question in most metabolic engineering projects is the optimal level of enzymes for maximizing the output. To address this point, combinatorial optimization approaches have been established, allowing automatic optimization without prior knowledge of the best combination of expression levels of individual genes. This review focuses on current combinatorial optimization methods and emerging technologies facilitating their applications.

RNA accumulation in Candida tropicalis based on cofactor engineering

Redox cofactors play an important role in biosynthetic and catabolic reactions and the transfer of energy for the cell. Therefore, studying the relationship between cofactor perturbation and metabolism is a useful approach to improve the yield of target products. To study RNA accumulation and metabolism when intracellular cofactor balance was impaired, the water-forming NADH oxidase (NoxE) from Lactococcus lactis and membrane-bound transhydrogenase (PntAB) from Escherichia coli were expressed in Candidatropicalis no. 121, respectively. Expression of noxE significantly decreased the intracellular NADH/NAD+ ratio, but the NADPH/NADP+ ratio did not differ significantly. PntAB increased the intracellular NADH pool, while the NADPH/NADP+ ratio decreased. The perturbation of the cofactors caused a large redistribution of metabolic fluxes. The biomass and RNA content decreased by 11.0% and 10.6% in pAUR-noxE strain, respectively, while the RNA content increased by 5.5% and the biomass showed no signification difference in pAUR-pntAB strain. Expression of noxE and pntAB led to decreases and increases in the ATP concentration and yield of RNA, respectively, which also indicated that ATP plays an important role in the RNA biosynthesis.

A novel nicotinamide adenine dinucleotide control strategy for increasing the cell density of Haemophilus parasuis

Haemophilus parasuis is the causative agent of Glässer's disease and is a major source of economic losses in the swine industry each year. To enhance the production of an inactivated vaccine against H. parasuis, the availability of nicotinamide adenine dinucleotide (NAD) must be carefully controlled to ensure a sufficiently high cell density of H. parasuis. In the present study, the real-time viable cell density of H. parasuis was calculated based on the capacitance of the culture. By assessing the relationship between capacitance and viable cell density/NAD concentration, the NAD supply rate could be adjusted in real time to maintain the NAD concentration at a set value based on the linear relationship between capacitance and NAD consumption. The linear relationship between cell density and addition of NAD indicated that 7.138 × 10⁹ NAD molecules were required to satisfy per cell growth. Five types of NAD supply strategy were used to maintain different NAD concentration for H. parasuis cultivation, and the results revealed that the highest viable cell density (8.57, OD₆₀₀ ) and cell count (1.57 × 10¹⁰ CFU/mL) were obtained with strategy III (NAD concentration maintained at 30 mg/L), which were 1.46- and 1.45- times more, respectively, than cultures with using NAD supply strategy I (NAD concentration maintained at 10 mg/L). An extremely high cell density of H. parasuis was achieved using this NAD supply strategy, and the results demonstrated a convenient and reliable method for determining the real-time viable cell density relative to NAD concentration. Moreover, this method provides a theoretical foundation and an efficient approach for high cell density cultivation of other auxotroph bacteria.

Improving the production of isoprene and 1,3-propanediol by metabolically engineered Escherichia coli through recycling redox cofactor between the dual pathways

The biosynthesis of isoprene by microorganisms is a promising green route. However, the yield of isoprene is limited due to the generation of excess NAD(P)H via the mevalonate (MVA) pathway, which converts more glucose into CO₂ or undesired reduced by-products. The production of 1,3-propanediol (1,3-PDO) from glycerol is a typical NAD(P)H-consuming process, which restricts 1,3-PDO yield to ~ 0.7 mol/mol. In this study, we propose a strategy of redox cofactor balance by coupling the production of isoprene with 1,3-PDO fermentation. With the introduction and optimization of the dual pathways in an engineered Escherichia coli, ~ 85.2% of the excess NADPH from isoprene pathway was recycled for 1,3-PDO production. The best strain G05 simultaneously produced 665.2 mg/L isoprene and 2532.1 mg/L 1,3-PDO under flask fermentation conditions. The yields were 0.3 mol/mol glucose and 1.0 mol/mol glycerol, respectively, showing 3.3- and 4.3-fold improvements relative to either pathway independently. Since isoprene is a volatile organic compound (VOC) whereas 1,3-PDO is separated from the fermentation broth, their coproduction process does not increase the complexity or cost for the separation from each other. Hence, the presented strategy will be especially useful for developing efficient biocatalysts for other biofuels and biochemicals, which are driven by cofactor concentrations.

Understanding the impact of the cofactor swapping of isocitrate dehydrogenase over the growth phenotype of Escherichia coli on acetate by using constraint-based modeling

It has been proposed that NADP⁺-specificity of isocitrate dehydrogenase (ICDH) evolved as an adaptation of microorganisms to grow on acetate as the sole source of carbon and energy. In Escherichia coli, changing the cofactor specificity of ICDH from NADP⁺ to NAD⁺ (cofactor swapping) decreases the growth rate on acetate. However, the metabolic basis of this phenotype has not been analyzed. In this work, we used constraint-based modeling to investigate the effect of the cofactor swapping of ICDH in terms of energy production, response of alternative sources of NADPH, and partitioning of fluxes between ICDH and isocitrate lyase (ICL) -a crucial bifurcation when the bacterium grows on acetate-. We generated E. coli strains expressing NAD⁺-specific ICDH instead of the native enzyme, and bearing the deletion of the NADPH-producing transhydrogenase PntAB. We measured their growth rate and acetate uptake rate, modeled the distribution of metabolic fluxes by Flux Balance Analysis (FBA), and quantified the specific activities of NADPH-producing dehydrogenases in central pathways. The cofactor swapping of ICDH led to one-third decrease in biomass yield, irrespective of the presence of PntAB. According to our simulations, the diminution in growth rate observed upon cofactor swapping could be explained by one-half decrease in the total production of NADPH and a lower availability of carbon for biosynthesis because of a change in the partition at the isocitrate bifurcation. Together with an increased total ATP production, this scenario resulted in a 10-fold increment in the flux of ATP not used for growing purposes. PntAB was identified as the primary NADPH balancing response, with the dehydrogenases of the oxidative branch of the Pentose Phosphate Pathway and the malic enzyme playing a role in its absence. We propose that in the context of E. coli growing on acetate, the NADP⁺-specificity of ICDH is a trait that impacts not only NADPH production, but also the efficient allocation of carbon and energy.

Pathway Design, Engineering, and Optimization

The microbial metabolic versatility found in nature has inspired scientists to create microorganisms capable of producing value-added compounds. Many endeavors have been made to transfer and/or combine pathways, existing or even engineered enzymes with new function to tractable microorganisms to generate new metabolic routes for drug, biofuel, and specialty chemical production. However, the success of these pathways can be impeded by different complications from an inherent failure of the pathway to cell perturbations. Pursuing ways to overcome these shortcomings, a wide variety of strategies have been developed. This chapter will review the computational algorithms and experimental tools used to design efficient metabolic routes, and construct and optimize biochemical pathways to produce chemicals of high interest.

High-Throughput Screening of Coenzyme Preference Change of Thermophilic 6-Phosphogluconate Dehydrogenase from NADP(+) to NAD(.)

Coenzyme engineering that changes NAD(P) selectivity of redox enzymes is an important tool in metabolic engineering, synthetic biology, and biocatalysis. Here we developed a high throughput screening method to identify mutants of 6-phosphogluconate dehydrogenase (6PGDH) from a thermophilic bacterium Moorella thermoacetica with reversed coenzyme selectivity from NADP⁺ to NAD⁺. Colonies of a 6PGDH mutant library growing on the agar plates were treated by heat to minimize the background noise, that is, the deactivation of intracellular dehydrogenases, degradation of inherent NAD(P)H, and disruption of cell membrane. The melted agarose solution containing a redox dye tetranitroblue tetrazolium (TNBT), phenazine methosulfate (PMS), NAD⁺, and 6-phosphogluconate was carefully poured on colonies, forming a second semi-solid layer. More active 6PGDH mutants were examined via an enzyme-linked TNBT-PMS colorimetric assay. Positive mutants were recovered by direct extraction of plasmid from dead cell colonies followed by plasmid transformation into E. coli TOP10. By utilizing this double-layer screening method, six positive mutants were obtained from two-round saturation mutagenesis. The best mutant 6PGDH A30D/R31I/T32I exhibited a 4,278-fold reversal of coenzyme selectivity from NADP⁺ to NAD⁺. This screening method could be widely used to detect numerous redox enzymes, particularly for thermophilic ones, which can generate NAD(P)H reacted with the redox dye TNBT.

Synthetic and systems biology for microbial production of commodity chemicals

The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges start at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.

Increasing anaerobic acetate consumption and ethanol yields in Saccharomyces cerevisiae with NADPH-specific alcohol dehydrogenase

Saccharomyces cerevisiae has recently been engineered to use acetate, a primary inhibitor in lignocellulosic hydrolysates, as a cosubstrate during anaerobic ethanolic fermentation. However, the original metabolic pathway devised to convert acetate to ethanol uses NADH-specific acetylating acetaldehyde dehydrogenase and alcohol dehydrogenase and quickly becomes constrained by limited NADH availability, even when glycerol formation is abolished. We present alcohol dehydrogenase as a novel target for anaerobic redox engineering of S. cerevisiae. Introduction of an NADPH-specific alcohol dehydrogenase (NADPH-ADH) not only reduces the NADH demand of the acetate-to-ethanol pathway but also allows the cell to effectively exchange NADPH for NADH during sugar fermentation. Unlike NADH, NADPH can be freely generated under anoxic conditions, via the oxidative pentose phosphate pathway. We show that an industrial bioethanol strain engineered with the original pathway (expressing acetylating acetaldehyde dehydrogenase from Bifidobacterium adolescentis and with deletions of glycerol-3-phosphate dehydrogenase genes GPD1 and GPD2) consumed 1.9 g liter(-1) acetate during fermentation of 114 g liter(-1) glucose. Combined with a decrease in glycerol production from 4.0 to 0.1 g liter(-1), this increased the ethanol yield by 4% over that for the wild type. We provide evidence that acetate consumption in this strain is indeed limited by NADH availability. By introducing an NADPH-ADH from Entamoeba histolytica and with overexpression of ACS2 and ZWF1, we increased acetate consumption to 5.3 g liter(-1) and raised the ethanol yield to 7% above the wild-type level.

In silico model-driven cofactor engineering strategies for improving the overall NADP(H) turnover in microbial cell factories

Optimizing the overall NADPH turnover is one of the key challenges in various value-added biochemical syntheses. In this work, we first analyzed the NADPH regeneration potentials of common cell factories, including Escherichia coli, Saccharomyces cerevisiae, Bacillus subtilis, and Pichia pastoris across multiple environmental conditions and determined E. coli and glycerol as the best microbial chassis and most suitable carbon source, respectively. In addition, we identified optimal cofactor specificity engineering (CSE) enzyme targets, whose cofactors when switched from NAD(H) to NADP(H) improve the overall NADP(H) turnover. Among several enzyme targets, glyceraldehyde-3-phosphate dehydrogenase was recognized as a global candidate since its CSE improved the NADP(H) regeneration under most of the conditions examined. Finally, by analyzing the protein structures of all CSE enzyme targets via homology modeling, we established that the replacement of conserved glutamate or aspartate with serine in the loop region could change the cofactor dependence from NAD(H) to NADP(H).

Alleviating Redox Imbalance Enhances 7-Dehydrocholesterol Production in Engineered Saccharomyces cerevisiae

Maintaining redox balance is critical for the production of heterologous secondary metabolites, whereas on various occasions the native cofactor balance does not match the needs in engineered microorganisms. In this study, 7-dehydrocholesterol (7-DHC, a crucial precursor of vitamin D₃) biosynthesis pathway was constructed in Saccharomyces cerevisiae BY4742 with endogenous ergosterol synthesis pathway blocked by knocking out the erg5 gene (encoding C-22 desaturase). The deletion of erg5 led to redox imbalance with higher ratio of cytosolic free NADH/NAD⁺ and more glycerol and ethanol accumulation. To alleviate the redox imbalance, a water-forming NADH oxidase (NOX) and an alternative oxidase (AOX1) were employed in our system based on cofactor regeneration strategy. Consequently, the production of 7-dehydrocholesterol was increased by 74.4% in shake flask culture. In the meanwhile, the ratio of free NADH/NAD⁺ and the concentration of glycerol and ethanol were reduced by 78.0%, 50.7% and 7.9% respectively. In a 5-L bioreactor, the optimal production of 7-DHC reached 44.49(±9.63) mg/L. This study provides a reference to increase the production of some desired compounds that are restricted by redox imbalance.

Synthesis of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) from unrelated carbon sources in engineered Rhodospirillum rubrum

Different genes encoding pyridine nucleotide transhydrogenases (pntAB, udhA) and acetoacetyl-CoA reductases (phaB) were heterologously overexpressed in Rhodospirillum rubrum S1. A recombinant strain, which harbored the gene encoding the membrane-bound transhydrogenase PntAB from Escherichia coli MG1655 and the phaB1 gene coding for an NADPH-dependent acetoacetyl-CoA reductase from Ralstonia eutropha H16, accumulated poly(3-hydroxybutyrate-co-3-hydroxyvalerate) [Poly(3HB-co-3HV)] with a 3HV fraction of up to 13 mol% from fructose. This was a 13-fold increase of the 3HV content when compared to the wild-type strain. Higher contents of 3HV are known to reduce the brittleness of this polymer, which is advantageous for most applications. The engineered R. rubrum strain was also able to synthesize this industrially relevant copolymer from CO2 and CO from artificial synthesis gas (syngas) with a 3HV content of 56 mol%. The increased incorporation of 3HV was attributed to an excess of propionyl-CoA, which was generated from threonine and related amino acids to compensate for the intracellular redox imbalance resulting from the transhydrogenase reaction. Thereby, our study presents a novel, molecular approach to alter the composition of bacterial PHAs independently from external precursor supply. Moreover, this study also provides a promising production strain for syngas-derived second-generation biopolymers.

Genome-scale modeling for metabolic engineering

We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information-an area which we expect will become increasingly important for metabolic engineering-and present recent developments in the field of metabolic and regulatory integration.

Model-driven intracellular redox status modulation for increasing isobutanol production in Escherichia coli

BACKGROUND

Few strains have been found to produce isobutanol naturally. For building a high performance isobutanol-producing strain, rebalancing redox status of the cell was very crucial through systematic investigation of redox cofactors metabolism. Then, the metabolic model provided a powerful tool for the rational modulation of the redox status.

RESULTS

Firstly, a starting isobutanol-producing E. coli strain LA02 was engineered with only 2.7 g/L isobutanol produced. Then, the genome-scale metabolic modeling was specially carried out for the redox cofactor metabolism of the strain LA02 by combining flux balance analysis and minimization of metabolic adjustment, and the GAPD reaction catalyzed by the glyceraldehyde-3-phosphate dehydrogenase was predicted as the key target for redox status improvement. Under guidance of the metabolic model prediction, a gapN-encoding NADP(+) dependent glyceraldehyde-3-phosphate dehydrogenase pathway was constructed and then fine-tuned using five constitutive promoters. The best strain LA09 was obtained with the strongest promoter BBa_J23100. The NADPH/NADP + ratios of strain LA09 reached 0.67 at exponential phase and 0.64 at stationary phase. The redox modulations resulted in the decrease production of ethanol and lactate by 17.5 and 51.7% to 1.32 and 6.08 g/L, respectively. Therefore, the isobutanol titer was increased by 221% to 8.68 g/L.

CONCLUSIONS

This research has achieved rational redox status improvement of isobutanol-producing strain under guidance of the prediction and modeling of the genome-scale metabolic model of isobutanol-producing E. coli strain with the aid of synthetic promoters. Therefore, the production of isobutanol was dramatically increased by 2.21-fold from 2.7 to 8.68 g/L. Moreover, the developed model-driven method special for redox cofactor metabolism was of very helpful to the redox status modulation of other bio-products.

Cyanobacteria as photosynthetic biocatalysts: a systems biology perspective

A review of cyanobacterial biocatalysts highlighting their metabolic features that argues for the need for systems-level metabolic engineering.

Engineering Halomonas TD01 for the low-cost production of polyhydroxyalkanoates

The halophile Halomonas TD01 and its derivatives have been successfully developed as a low-cost platform for the unsterile and continuous production of chemicals. Therefore, to increase the genetic engineering stability of this platform, the DNA restriction/methylation system of Halomonas TD01 was partially inhibited. In addition, a stable and conjugative plasmid pSEVA341 with a high-copy number was constructed to contain a LacI(q)-Ptrc system for the inducible expression of multiple pathway genes. The Halomonas TD01 platform, was further engineered with its 2-methylcitrate synthase and three PHA depolymerases deleted within the chromosome, resulting in the production of the Halomonas TD08 strain. The overexpression of the threonine synthesis pathway and threonine dehydrogenase made the recombinant Halomonas TD08 able to produce poly(3-hydroxybutyrate-co-3-hydroxyvalerate) or PHBV consisting of 4-6 mol% 3-hydroxyvalerate or 3 HV, from various carbohydrates as the sole carbon source. The overexpression of the cell division inhibitor MinCD during the cell growth stationary phase in Halomonas TD08 elongated its shape to become at least 1.4-fold longer than its original size, resulting in enhanced PHB accumulation from 69 wt% to 82 wt% in the elongated cells, further promoting gravity-induced cell precipitations that simplify the downstream processing of the biomass. The resulted Halomonas strains contributed to further reducing the PHA production cost.