Genome-scale modeling using flux ratio constraints to enable metabolic engineering of clostridial metabolism in silico

ABSTRACT: BACKGROUND: Genome-scale metabolic networks and flux models are an effective platform for linking an organism genotype to its phenotype. However, few modeling approaches offer predictive capabilities to evaluate potential metabolic engineering strategies in silico. METHODS: A new method called "flux balance analysis with flux ratios (FBrAtio)" was developed in this research and applied to a new genome-scale model of Clostridium acetobutylicum ATCC 824 (iCAC794) that contains 707 metabolites and 794 reactions. FBrAtio was used to model wild-type metabolism and metabolically engineered strains of C. acetobutylicum where only flux ratio constraints and thermodynamic reversibility of reactions were required. The FBrAtio approach allows solutions to be found through standard linear programming. RESULTS: Five flux ratio constraints were required to achieve a qualitative picture of wild-type metabolism for C. acetobutylicum for the production of: (i) acetate, (ii) lactate, (iii) butyrate, (iv) acetone, (v) butanol, (vi) ethanol, (vii) CO2 and (viii) H2. Results of this simulation study coincide with published experimental results and show the knockdown of the acetylacetyl-CoA transferase increases butanol to acetone selectivity, while the simultaneous over-expression of the aldehyde/alcohol dehydrogenase greatly increases ethanol production. CONCLUSIONS: FBrAtio is a promising new method for constraining genome-scale models using internal flux ratios. The method was effective for modeling wild-type and engineered strains of C. acetobutylicum.     

OpenFLUX: efficient modelling software for 13C-based metabolic flux analysis

Background  

The quantitative analysis of metabolic fluxes, i.e., in vivo activities of intracellular enzymes and pathways, provides key information on biological systems in systems biology and metabolic engineering. It is based on a comprehensive approach combining (i) tracer cultivation on ¹³C substrates, (ii) ¹³C labelling analysis by mass spectrometry and (iii) mathematical modelling for experimental design, data processing, flux calculation and statistics. Whereas the cultivation and the analytical part is fairly advanced, a lack of appropriate modelling software solutions for all modelling aspects in flux studies is limiting the application of metabolic flux analysis.     

Metabolic engineering of Torulopsis glabrata for malate production

The yeast Torulopsis glabrata CCTCC M202019, which is used for industrial pyruvate production, was chosen to explore the suitability of engineering this multi-vitamin auxotrophic yeast for increased malate production. Various metabolic engineering strategies were used to manipulate carbon flux from pyruvate to malate: (i) overexpression of pyruvate carboxylase and malate dehydrogenase; (ii) identification of the bottleneck in malate production by model iNX804; (iii) simultaneous overexpression of genes RoPYC, RoMDH and SpMAE1. Using these strategies, 8.5 g L^–1 malate was accumulated in the engineered strain T.G-PMS, which was about 10-fold greater than that of the control strain T.G-26. The results presented here suggest that T. glabrata CCTCC M202019 is a promising candidate for industrial malate production.     

A synthetic C2 auxotroph of Pseudomonas putida for evolutionary engineering of alternative sugar catabolic routes

Acetyl-coenzyme A (AcCoA) is a metabolic hub in virtually all living cells, serving as both a key precursor of essential biomass components and a metabolic sink for catabolic pathways for a large variety of substrates. Owing to this dual role, tight growth-production coupling schemes can be implemented around the AcCoA node. Building on this concept, a synthetic C2 auxotrophy was implemented in the platform bacterium Pseudomonas putida through an in silico-informed engineering approach. A growth-coupling strategy, driven by AcCoA demand, allowed for direct selection of an alternative sugar assimilation route—the phosphoketolase (PKT) shunt from bifidobacteria. Adaptive laboratory evolution forced the synthetic P. putida auxotroph to rewire its metabolic network to restore C2 prototrophy via the PKT shunt. Large-scale structural chromosome rearrangements were identified as possible mechanisms for adjusting the network-wide proteome profile, resulting in improved PKT-dependent growth phenotypes. ¹³C-based metabolic flux analysis revealed an even split between the native Entner-Doudoroff pathway and the synthetic PKT bypass for glucose processing, leading to enhanced carbon conservation. These results demonstrate that the P. putida metabolism can be radically rewired to incorporate a synthetic C2 metabolism, creating novel network connectivities and highlighting the importance of unconventional engineering strategies to support efficient microbial production.     

Strain engineering for high‐level 5‐aminolevulinic acid production in Escherichia coli

Herein, we report the development of a microbial bioprocess for high‐level production of 5‐aminolevulinic acid (5‐ALA), a valuable non‐proteinogenic amino acid with multiple applications in medical, agricultural, and food industries, using Escherichia coli as a cell factory. We first implemented the Shemin (i.e., C4) pathway for heterologous 5‐ALA biosynthesis in E. coli. To reduce, but not to abolish, the carbon flux toward essential tetrapyrrole/porphyrin biosynthesis, we applied clustered regularly interspersed short palindromic repeats interference (CRISPRi) to repress hemB expression, leading to extracellular 5‐ALA accumulation. We then applied metabolic engineering strategies to direct more dissimilated carbon flux toward the key precursor of succinyl‐CoA for enhanced 5‐ALA biosynthesis. Using these engineered E. coli strains for bioreactor cultivation, we successfully demonstrated high‐level 5‐ALA biosynthesis from glycerol (~30 g L^?1) under both microaerobic and aerobic conditions, achieving up to 5.95 g L^?1 (36.9% of the theoretical maximum yield) and 6.93 g L^?1 (50.9% of the theoretical maximum yield) 5‐ALA, respectively. This study represents one of the most effective bio‐based production of 5‐ALA from a structurally unrelated carbon to date, highlighting the importance of integrated strain engineering and bioprocessing strategies to enhance bio‐based production.     

Cover Image,Volume 116, Number 6, June 2019

Metabolic engineering consistently demands to produce the maximum carbon and energy flux to target chemicals. To balance metabolic flux, gene expression levels of artificially synthesized pathways usually fine-tuned using multimodular optimization strategy. However, forward construction is an engineering conundrum because a vast number of possible pathway combinations need to be constructed and analyzed. Here, an iterative high-throughput balancing (IHTB) strategy was established to thoroughly fine-tune the (2S)-naringenin biosynthetic pathway. A series of gradient constitutive promoters from Escherichia coli were randomly cloned upstream of pathway genes, and the resulting library was screened using an ultraviolet spectrophotometry–fluorescence spectrophotometry high-throughput method, which was established based on the interactions between AlCl₃ and (2S)-naringenin. The metabolic flux of the screened high-titer strains was analyzed and iterative rounds of screening were performed based on the analysis results. After several rounds, the metabolic flux of the (2S)-naringenin synthetic pathway was balanced, reaching a final titer of 191.9 mg/L with 29.2 mg/L p-coumaric acid accumulation. Chalcone synthase was speculated to be the rate-limiting enzyme because its expression level was closely related to the production of both (2S)-naringenin and p-coumaric acid. The established IHTB strategy can be used to efficiently balance multigene pathways, which will accelerate the development of efficient recombinant strains.     

A review on metabolic pathway analysis with emphasis on isotope labeling approach

The recent progress on metabolic systems engineering was reviewed based on our recent research results in terms of (1) metabolic signal flow diagram approach, (2) metabolic flux analysis (MFA) in particular with intracellular isotopomer distribution using NMR and/or GC-MS, (3) synthesis and optimization of metabolic flux distribution (MFD), (4) modification of MFD by gene manipulation and by controlling culture environment, (5) metabolic control analysis (MCA), (6) design of metabolic regulation structure, and (7) identification of unknown pathways with isotope tracing by NMR. The main characteristics of metabolic engineering is to treat metabolism as a network or entirety instead of individual reactions. The applications were made for poly-3-hydroxybutyrate (PHB) production usingRalstonia eutropha and recombinantEscherichia coli, lactate production by recombinantSaccharomyces cerevisiae, pyruvate production by vitamin auxotrophic yeastToluropsis glabrata, lysine production usingCorynebacterium glutamicum, and energetic analysis of photosynthesic microorganisms such as Cyanobateria. The characteristics of each approach were reviewed with their applications. The approach based on isotope labeling experiments gives reliable and quantitative results for metabolic flux analysis. It should be recognized that the next stage should be toward the investigation of metabolic flux analysis with gene and protein expressions to uncover the metabolic regulation in relation to genetic modification and/or the change in the culture condition.     

Extracellular products from Chlorococcum ellipsoideum and Chlamydomonas globosa

Summary Extracellular products of Chlorococcum and Chlamydomonas were isolated from culture filtrates. Five groups of substances were found in both species: (i) steam-volatile acids, (ii) yellow water-soluble phenolic compounds, (iii) lipophilic substances, (iv) proteins and (v) polysaccharides. Chlorococcum had higher concentrations of all groups than Chlamydomonas; moreover, the two species differed slightly in the composition of groups (ii) and (iii). Probably, these is a great similarity between green algae in the production of extracellular compounds.     

Flux balance analysis in the production of clavulanic acid by Streptomyces clavuligerus

In this work, in silico flux balance analysis is used for predicting the metabolic behavior of Streptomyces clavuligerus during clavulanic acid production. To choose the best objective function for use in the analysis, three different optimization problems are evaluated inside the flux balance analysis formulation: (i) maximization of the specific growth rate, (ii) maximization of the ATP yield, and (iii) maximization of clavulanic acid production. Maximization of ATP yield showed the best predictions for the cellular behavior. Therefore, flux balance analysis using ATP as objective function was used for analyzing different scenarios of nutrient limitations toward establishing the effect of limiting the carbon, nitrogen, phosphorous, and oxygen sources on the growth and clavulanic acid production rates. Obtained results showed that ammonia and phosphate limitations are the ones most strongly affecting clavulanic acid biosynthesis. Furthermore, it was possible to identify the ornithine flux from the urea cycle and the α‐ketoglutarate flux from the TCA cycle as the most determinant internal fluxes for promoting clavulanic acid production. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1226–1236, 2015     

Elucidation of metabolism in hybridoma cells grown in fed‐batch culture by genome‐scale modeling

Genome‐scale modeling of mouse hybridoma cells producing monoclonal antibodies (mAb) was performed to elucidate their physiological and metabolic states during fed‐batch cell culture. Initially, feed media nutrients were monitored to identify key components among carbon sources and amino acids with significant impact on the desired outcome, for example, cell growth and antibody production. The monitored profiles indicated rapid assimilation of glucose and glutamine during the exponential growth phase. Significant increase in mAb concentration was also observed when glutamine concentration was controlled at 0.5 mM as a feeding strategy. Based on the reconstructed genome‐scale metabolic network of mouse hybridoma cells and fed‐batch profiles, flux analysis was then implemented to investigate the cellular behavior and changes in internal fluxes during the cell culture. The simulated profile of the cell growth was consistent with experimentally measured specific growth rate. The in silico simulation results indicated (i) predominant utilization of glycolytic pathway for ATP production, (ii) importance of pyruvate node in metabolic shifting, and (iii) characteristic pattern in lactate to glucose ratio during the exponential phase. In future, experimental and in silico analyses can serve as a promising approach to identifying optimal feeding strategies and potential cell engineering targets as well as facilitate media optimization for the enhanced production of mAb or recombinant proteins in mammalian cells. Biotechnol. Bioeng. 2009;102: 1494–1504. © 2008 Wiley Periodicals, Inc.     

Constraint-based strain design using continuous modifications (CosMos) of flux bounds finds new strategies for metabolic engineering

In recent years, a growing number of metabolic engineering strain design techniques have employed constraint-based modeling to determine metabolic and regulatory network changes which are needed to improve chemical production. These methods use systems-level analysis of metabolism to help guide experimental efforts by identifying deletions, additions, downregulations, and upregulations of metabolic genes that will increase biological production of a desired metabolic product. In this work, we propose a new strain design method with continuous modifications (CosMos) that provides strategies for deletions, downregulations, and upregulations of fluxes that will lead to the production of the desired products. The method is conceptually simple and easy to implement, and can provide additional strategies over current approaches. We found that the method was able to find strain design strategies that required fewer modifications and had larger predicted yields than strategies from previous methods in example and genome-scale networks. Using CosMos, we identified modification strategies for producing a variety of metabolic products, compared strategies derived from Escherichia coli and Saccharomyces cerevisiae metabolic models, and examined how imperfect implementation may affect experimental outcomes. This study gives a powerful and flexible technique for strain engineering and examines some of the unexpected outcomes that may arise when strategies are implemented experimentally.     

Xylose assimilation enhances the production of isobutanol in engineered Saccharomyces cerevisiae

Bioconversion of xylose—the second most abundant sugar in nature—into high-value fuels and chemicals by engineered Saccharomyces cerevisiae has been a long-term goal of the metabolic engineering community. Although most efforts have heavily focused on the production of ethanol by engineered S. cerevisiae, yields and productivities of ethanol produced from xylose have remained inferior as compared with ethanol produced from glucose. However, this entrenched focus on ethanol has concealed the fact that many aspects of xylose metabolism favor the production of nonethanol products. Through reduced overall metabolic flux, a more respiratory nature of consumption, and evading glucose signaling pathways, the bioconversion of xylose can be more amenable to redirecting flux away from ethanol towards the desired target product. In this report, we show that coupling xylose consumption via the oxidoreductive pathway with a mitochondrially-targeted isobutanol biosynthesis pathway leads to enhanced product yields and titers as compared to cultures utilizing glucose or galactose as a carbon source. Through the optimization of culture conditions, we achieve 2.6 g/L of isobutanol in the fed-batch flask and bioreactor fermentations. These results suggest that there may be synergistic benefits of coupling xylose assimilation with the production of nonethanol value-added products.     

Fed-batch culture of Escherichia coli for L-valine production based on in silico flux response analysis

We have previously reported the development of a 100% genetically defined engineered Escherichia coli strain capable of producing L ‐valine from glucose with a high yield of 0.38 g L ‐valine per gram glucose (0.58 mol L ‐valine per mol glucose) by batch culture. Here we report a systems biological strategy of employing flux response analysis in bioprocess development using L ‐valine production by fed‐batch culture as an example. Through the systems‐level analysis, the source of ATP was found to be important for efficient L ‐valine production. There existed a trade‐off between L ‐valine production and biomass formation, which was optimized for the most efficient L ‐valine production. Furthermore, acetic acid feeding strategy was optimized based on flux response analysis. The final fed‐batch cultivation strategy allowed production of 32.3 g/L L ‐valine, the highest concentration reported for E. coli. This approach of employing systems‐level analysis of metabolic fluxes in developing fed‐batch cultivation strategy would also be applicable in developing strategies for the efficient production of other bioproducts. Biotechnol. Bioeng. 2011; 108:934–946. © 2010 Wiley Periodicals, Inc.     

Systems-level analysis of genome-scalein silico metabolic models using MetaFluxNet

The systems-level analysis of microbes with myriad of heterologous data generated by omics technologies has been applied to improve our understanding of cellular function and physiology and consequently to enhance production of various bioproducts. At the heart of this revolution residesin silico genome-scale metabolic model. In order to fully exploit the power of genome-scale model, a systematic approach employing user-friendly software is required. Metabolic flux analysis of genome-scale metabolic network is becoming widely employed to quantify the flux distribution and validate model-driven hypotheses. Here we describe the development of an upgraded MetaFluxNet which allows (1) construction of metabolic models connected to metabolic databases, (2) calculation of fluxes by metabolic flux analysis, (3) comparative flux analysis with flux-profile visualization, (4) the use of metabolic flux analysis markup language to enable models to be exchanged efficiently, and (5) the exporting of data from constraints-based flux analysis into various formats. MetaFluxNet also allows cellular physiology to be predicted and strategies for strain improvement to be developed from genome-based information on flux distributions. This integrated software environment promises to enhance our understanding on metabolic network at a whole organism level and to establish novel strategies for improving the properties of organisms for various biotechnological applications.     

Engineering high-level production of fatty alcohols by Saccharomyces cerevisiae from lignocellulosic feedstocks

Fatty alcohols in the C12-C18 range are used in personal care products, lubricants, and potentially biofuels. These compounds can be produced from the fatty acid pathway by a fatty acid reductase (FAR), yet yields from the preferred industrial host Saccharomyces cerevisiae remain under 2% of the theoretical maximum from glucose. Here we improved titer and yield of fatty alcohols using an approach involving quantitative analysis of protein levels and metabolic flux, engineering enzyme level and localization, pull-push-block engineering of carbon flux, and cofactor balancing. We compared four heterologous FARs, finding highest activity and endoplasmic reticulum localization from a Mus musculus FAR. After screening an additional twenty-one single-gene edits, we identified increasing FAR expression; deleting competing reactions encoded by DGA1, HFD1, and ADH6; overexpressing a mutant acetyl-CoA carboxylase; limiting NADPH and carbon usage by the glutamate dehydrogenase encoded by GDH1; and overexpressing the Δ9-desaturase encoded by OLE1 as successful strategies to improve titer. Our final strain produced 1.2 g/L fatty alcohols in shake flasks, and 6.0 g/L in fed-batch fermentation, corresponding to ~ 20% of the maximum theoretical yield from glucose, the highest titers and yields reported to date in S. cerevisiae. We further demonstrate high-level production from lignocellulosic feedstocks derived from ionic-liquid treated switchgrass and sorghum, reaching 0.7 g/L in shake flasks. Altogether, our work represents progress towards efficient and renewable microbial production of fatty acid-derived products.     

Genome-scale metabolic models as platforms for strain design and biological discovery

Genome-scale metabolic models (GEMs) have been developed and used in guiding systems’ metabolic engineering strategies for strain design and development. This strategy has been used in fermentative production of bio-based industrial chemicals and fuels from alternative carbon sources. However, computer-aided hypotheses building using established algorithms and software platforms for biological discovery can be integrated into the pipeline for strain design strategy to create superior strains of microorganisms for targeted biosynthetic goals. Here, I described an integrated workflow strategy using GEMs for strain design and biological discovery. Specific case studies of strain design and biological discovery using Escherichia coli genome-scale model are presented and discussed. The integrated workflow presented herein, when applied carefully would help guide future design strategies for high-performance microbial strains that have existing and forthcoming genome-scale metabolic models.     

Klebsiella spp as a 1, 3-propanediol producer – the metabolic engineering approach

Klebsiella spp are one of the best natural producers of 1,3-propanediol (1,3-PD). However, their usage in the biotechnological production of the diol is limited, since the species belong to the second hazard group. Nevertheless, multiple advantageous traits of Klebsiella spp justify the international effort devoted to develop a biotechnological process of 1,3-PD production with these microorganisms. Apart from the process engineering approach aiming at improvement of 1,3-PD production by Klebsiella spp, plethora of metabolic engineering approaches have been reported. Different strategies have been undertaken to genetically improve Klebsiella strains and provide them with the ability to synthesize 1,3-PD more efficiently. These include over-expression of both homologous and heterologous genes of the 1,3-PD synthesis pathway, protein and cofactor engineering, deletion of the genes involved in by-products formation. This review provides an overview of the initial and most recent reports on the metabolic engineering of Klebsiella spp with the aim of improvement of 1,3-PD biosynthesis.     

A modular modulation method for achieving increases in metabolite production

Increasing the production of overproducing strains represents a great challenge. Here, we develop a modular modulation method to determine the key steps for genetic manipulation to increase metabolite production. The method consists of three steps: (i) modularization of the metabolic network into two modules connected by linking metabolites, (ii) change in the activity of the modules using auxiliary rates producing or consuming the linking metabolites in appropriate proportions and (iii) determination of the key modules and steps to increase production. The mathematical formulation of the method in matrix form shows that it may be applied to metabolic networks of any structure and size, with reactions showing any kind of rate laws. The results are valid for any type of conservation relationships in the metabolite concentrations or interactions between modules. The activity of the module may, in principle, be changed by any large factor. The method may be applied recursively or combined with other methods devised to perform fine searches in smaller regions. In practice, it is implemented by integrating to the producer strain heterologous reactions or synthetic pathways producing or consuming the linking metabolites. The new procedure may contribute to develop metabolic engineering into a more systematic practice. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:656–667, 2015     

Perspectives of engineering lactic acid bacteria for biotechnological polyol production

Polyols are sugar alcohols largely used as sweeteners and they are claimed to have several health-promoting effects (low-caloric, low-glycemic, low-insulinemic, anticariogenic, and prebiotic). While at present chemical synthesis is the only strategy able to assure the polyol market demand, the biotechnological production of polyols has been implemented in yeasts, fungi, and bacteria. Lactic acid bacteria (LAB) are a group of microorganisms particularly suited for polyol production as they display a fermentative metabolism associated with an important redox modulation and a limited biosynthetic capacity. In addition, LAB participate in food fermentation processes, where in situ production of polyols during fermentation may be useful in the development of novel functional foods. Here, we review the polyol production by LAB, focusing on metabolic engineering strategies aimed to redirect sugar fermentation pathways towards the synthesis of biotechnologically important sugar alcohols such as sorbitol, mannitol, and xylitol. Furthermore, possible approaches are presented for engineering new fermentation routes in LAB for production of arabitol, ribitol, and erythritol.