Strain improvement by metabolic engineering: lysine production as a case study for systems biology

Model validation and selection in metabolic flux analysis and flux balance analysis

13C-Metabolic Flux Analysis (13C-MFA) and Flux Balance Analysis (FBA) are widely used to investigate the operation of biochemical networks in both biological and biotechnological research. Both methods use metabolic reaction network models of metabolism operating at steady state so that reaction rates (fluxes) and the levels of metabolic intermediates are constrained to be invariant. They provide estimated (MFA) or predicted (FBA) values of the fluxes through the network in vivo, which cannot be measured directly. These fluxes can shed light on basic biology and have been successfully used to inform metabolic engineering strategies. Several approaches have been taken to test the reliability of estimates and predictions from constraint-based methods and to compare alternative model architectures. Despite advances in other areas of the statistical evaluation of metabolic models, such as the quantification of flux estimate uncertainty, validation and model selection methods have been underappreciated and underexplored. We review the history and state-of-the-art in constraint-based metabolic model validation and model selection. Applications and limitations of the χ2 -test of goodness-of-fit, the most widely used quantitative validation and selection approach in 13C-MFA, are discussed, and complementary and alternative forms of validation and selection are proposed. A combined model validation and selection framework for 13C-MFA incorporating metabolite pool size information that leverages new developments in the field is presented and advocated for. Finally, we discuss how adopting robust validation and selection procedures can enhance confidence in constraint-based modeling as a whole and ultimately facilitate more widespread use of FBA in biotechnology.

Integrative teaching of metabolic modeling and flux analysis with interactive python modules

The modeling of rates of biochemical reactions-fluxes-in metabolic networks is widely used for both basic biological research and biotechnological applications. A number of different modeling methods have been developed to estimate and predict fluxes, including kinetic and constraint-based (Metabolic Flux Analysis and flux balance analysis) approaches. Although different resources exist for teaching these methods individually, to-date no resources have been developed to teach these approaches in an integrative way that equips learners with an understanding of each modeling paradigm, how they relate to one another, and the information that can be gleaned from each. We have developed a series of modeling simulations in Python to teach kinetic modeling, metabolic control analysis, 13C-metabolic flux analysis, and flux balance analysis. These simulations are presented in a series of interactive notebooks with guided lesson plans and associated lecture notes. Learners assimilate key principles using models of simple metabolic networks by running simulations, generating and using data, and making and validating predictions about the effects of modifying model parameters. We used these simulations as the hands-on computer laboratory component of a four-day metabolic modeling workshop and participant survey results showed improvements in learners' self-assessed competence and confidence in understanding and applying metabolic modeling techniques after having attended the workshop. The resources provided can be incorporated in their entirety or individually into courses and workshops on bioengineering and metabolic modeling at the undergraduate, graduate, or postgraduate level.

Microbial synthesis of bacitracin: Recent progress, challenges, and prospects

Microorganisms are important sources of various natural products that have been commercialized for human medicine and animal healthcare. Bacitracin is an important antibacterial natural product predominantly produced by Bacillus licheniformis and Bacillus subtilis, and it is characterized by a broad antimicrobial spectrum, strong activity and low resistance, thus bacitracin is extensively applied in animal feed and veterinary medicine industries. In recent years, various strategies have been proposed to improve bacitracin production. Herein, we systematically describe the regulation of bacitracin biosynthesis in genus Bacillus and its associated mechanism, to provide a theoretical basis for bacitracin overproduction. The metabolic engineering strategies applied for bacitracin production are explored, including improving substrate utilization, using an enlarged precursor amino acid pool, increasing ATP supply and NADPH generation, and engineering transcription regulators. We also present several approaches of fermentation process optimization to facilitate the industrial large-scale production of bacitracin. Finally, the challenges and prospects associated with microbial bacitracin synthesis are discussed to facilitate the establishment of high-yield and low-cost biological factories.

Identification and Molecular Characterization of the Operon Required for L-Asparagine Utilization in Corynebacterium glutamicum

Understanding the metabolic pathways of amino acids and their regulation is important for the rational metabolic engineering of amino acid production. The catabolic pathways of L-asparagine and L-aspartate are composed of transporters for amino acid uptake and asparaginase and aspartase, which are involved in the sequential deamination to fumarate. However, knowledge of the catabolic genes for asparagine in bacteria of the Actinobacteria class has been limited. In this study, we identified and characterized the ans operon required for L-Asn catabolism in Corynebacterium glutamicum R. The operon consisted of genes encoding a transcriptional regulator (AnsR), asparaginase (AnsA2), aspartase (AspA2), and permease (AnsP). The enzymes and permease encoded in the operon were shown to be essential for L-Asn utilization, but another asparaginase, AnsA1, and aspartase, AspA1, were not essential. Expression analysis revealed that the operon was induced in response to extracellular L-Asn and was transcribed as a leaderless mRNA. The DNA-binding assay demonstrated that AnsR acted as a transcriptional repressor of the operon by binding to the inverted repeat at its 5'-end region. The AnsR binding was inhibited by L-Asn. This study provides insights into the functions and regulatory mechanisms of similar operon-like clusters in related bacteria.

Systematic Engineering of Synechococcus elongatus UTEX 2973 for Photosynthetic Production of l-Lysine, Cadaverine, and Glutarate

Amino acids and related targets are typically produced by well-characterized heterotrophs including Corynebacterium glutamicum and Escherichia coli. Cyanobacteria offer an opportunity to supplant these sugar-intensive processes by instead directly utilizing atmospheric CO₂ and sunlight. Synechococcus elongatus UTEX 2973 (hereafter UTEX 2973) is a particularly promising photoautotrophic platform due to its fast growth rate. Here, we first engineered UTEX 2973 to overproduce l-lysine (hereafter lysine), after which both cadaverine and glutarate production were achieved through further pathway engineering. To facilitate metabolic engineering, the relative activities of a subset of previously uncharacterized promoters were investigated, in each case, while also comparing the effects of both chromosomal (from neutral site NS3) and episomal (from pAM4788) expressions. Using these parts, lysine overproduction in UTEX 2973 was engineered by introducing a feedback-resistant copy of aspartate kinase (encoded by lysC^fbr) and a lysine exporter (encoded by ybjE), both from E. coli. While chromosomal expression resulted in lysine production up to just 325.3 ± 14.8 mg/L after 120 h, this was then increased to 556.3 ± 62.3 mg/L via plasmid-based expression, also surpassing prior reports of photoautotrophic lysine bioproduction. Lastly, additional products of interest were then targeted by modularly extending the lysine pathway to glutarate and cadaverine, two 5-carbon, bioplastic monomers. By this approach, glutarate has so far been produced at final titers reaching 67.5 ± 2.2 mg/L by 96 h, whereas cadaverine has been produced at up to 55.3 ± 6.7 mg/L. Overcoming pathway and/or transport bottlenecks, meanwhile, will be important to improving upon these initial outputs.

Cascaded valorization of brown seaweed to produce l-lysine and value-added products using Corynebacterium glutamicum streamlined by systems metabolic engineering

Seaweeds emerge as promising third-generation renewable for sustainable bioproduction. In the present work, we valorized brown seaweed to produce l-lysine, the world's leading feed amino acid, using Corynebacterium glutamicum, which was streamlined by systems metabolic engineering. The mutant C. glutamicum SEA-1 served as a starting point for development because it produced small amounts of l-lysine from mannitol, a major seaweed sugar, because of the deletion of its arabitol repressor AtlR and its engineered l-lysine pathway. Starting from SEA-1, we systematically optimized the microbe to redirect excess NADH, formed on the sugar alcohol, towards NADPH, required for l-lysine synthesis. The mannitol dehydrogenase variant MtlD D75A, inspired by 3D protein homology modelling, partly generated NADPH during the oxidation of mannitol to fructose, leading to a 70% increased l-lysine yield in strain SEA-2C. Several rounds of strain engineering further increased NADPH supply and l-lysine production. The best strain, SEA-7, overexpressed the membrane-bound transhydrogenase pntAB together with codon-optimized gapN, encoding NADPH-dependent glyceraldehyde 3-phosphate dehydrogenase, and mak, encoding fructokinase. In a fed-batch process, SEA-7 produced 76 g L^-1l-lysine from mannitol at a yield of 0.26 mol mol^-1 and a maximum productivity of 2.1 g L^-1 h^-1. Finally, SEA-7 was integrated into seaweed valorization cascades. Aqua-cultured Laminaria digitata, a major seaweed for commercial alginate, was extracted and hydrolyzed enzymatically, followed by recovery and clean-up of pure alginate gum. The residual sugar-based mixture was converted to l-lysine at a yield of 0.27 C-mol C-mol^-1 using SEA-7. Second, stems of the wild-harvested seaweed Durvillaea antarctica, obtained as waste during commercial processing of the blades for human consumption, were extracted using acid treatment. Fermentation of the hydrolysate using SEA-7 provided l-lysine at a yield of 0.40 C-mol C-mol^-1. Our findings enable improvement of the efficiency of seaweed biorefineries using tailor-made C. glutamicum strains.

Increasing L-lysine production in Corynebacterium glutamicum by engineering amino acid transporters

Corynebacterium glutamicum has a long and successful history in the biotechnological production of L-lysine. Besides the adjustment of metabolic pathways, intracellular and extracellular transport systems are critical for the cellular metabolism of L-lysine or its by-products. Here, three amino acid transmembrane transporters, namely, GluE, BrnE/BrnF, and LysP, which are widely present in C. glutamicum strains, were each investigated by gene knockout. In comparison with that in the wild-type strain, the yield of L-lysine increased by 9.0%, 12.3%, and 10.0% after the deletion of the gluE, brnE/brnF, and lysP genes, respectively, in C. glutamicum 23,604. Moreover, the amount of by-product amino acids decreased significantly when the gluE and brnE/brnF genes were deleted. It was also demonstrated that there was no effect on the growth of the strain when the gluE or lysP gene was deleted, whereas the biomass of C. glutamicum WL1702 (ΔbrnE/ΔbrnF) in the fermentation medium was significantly reduced in comparison with that of the wild type. These results also provide useful information for enhancing the production of L-lysine or other amino acids by C. glutamicum.

A review on commercial-scale high-value products that can be produced alongside cellulosic ethanol

The demand for fossil derivate fuels and chemicals has increased, augmenting concerns on climate change, global economic stability, and sustainability on fossil resources. Therefore, the production of fuels and chemicals from alternative and renewable resources has attracted considerable and growing attention. Ethanol is a promising biofuel that can reduce the consumption of gasoline in the transportation sector and related greenhouse gas (GHG) emissions. Lignocellulosic biomass is a promising feedstock to produce bioethanol (cellulosic ethanol) because of its abundance and low cost. Since the conversion of lignocellulose to ethanol is complex and expensive, the cellulosic ethanol price cannot compete with those of the fossil derivate fuels. A promising strategy to lower the production cost of cellulosic ethanol is developing a biorefinery which produces ethanol and other high-value chemicals from lignocellulose. The selection of such chemicals is difficult because there are hundreds of products that can be produced from lignocellulose. Multiple reviews and reports have described a small group of lignocellulose derivate compounds that have the potential to be commercialized. Some of these products are in the bench scale and require extensive research and time before they can be industrially produced. This review examines chemicals and materials with a Technology Readiness Level (TRL) of at least 8, which have reached a commercial scale and could be shortly or immediately integrated into a cellulosic ethanol process.

Deep scanning lysine metabolism in Escherichia coli

Our limited ability to predict genotype-phenotype relationships has called for strategies that allow testing of thousands of hypotheses in parallel. Deep scanning mutagenesis has been successfully implemented to map genotype-phenotype relationships at a single-protein scale, allowing scientists to elucidate properties that are difficult to predict. However, most phenotypes are dictated by several proteins that are interconnected through complex and robust regulatory and metabolic networks. These sophisticated networks hinder our understanding of the phenotype of interest and limit our capabilities to rewire cellular functions. Here, we leveraged CRISPR-EnAbled Trackable genome Engineering to attempt a parallel and high-resolution interrogation of complex networks, deep scanning multiple proteins associated with lysine metabolism in Escherichia coli We designed over 16,000 mutations to perturb this pathway and mapped their contribution toward resistance to an amino acid analog. By doing so, we identified different routes that can alter pathway function and flux, uncovering mechanisms that would be difficult to rationally design. This approach sets a framework for forward investigation of complex multigenic phenotypes.

Isotopically nonstationary 13C flux analysis of cyanobacterial isobutyraldehyde production

We applied isotopically nonstationary ¹³C metabolic flux analysis (INST-MFA) to compare the pathway fluxes of wild-type (WT) Synechococcus elongatus PCC 7942 to an engineered strain (SA590) that produces isobutyraldehyde (IBA). The flux maps revealed a potential bottleneck at the pyruvate kinase (PK) reaction step that was associated with diversion of flux into a three-step PK bypass pathway involving the enzymes PEP carboxylase (PEPC), malate dehydrogenase (MDH), and malic enzyme (ME). Overexpression of pk in SA590 led to a significant improvement in IBA specific productivity. Single-gene overexpression of the three enzymes in the proposed PK bypass pathway also led to improvements in IBA production, although to a lesser extent than pk overexpression. Combinatorial overexpression of two of the three genes in the proposed PK bypass pathway (mdh and me) led to improvements in specific productivity that were similar to those achieved by single-gene pk overexpression. Our work demonstrates how ¹³C flux analysis can be used to identify potential metabolic bottlenecks and novel metabolic routes, and how these findings can guide rational metabolic engineering of cyanobacteria for increased production of desired molecules.

Evolving the L-lysine high-producing strain of Escherichia coli using a newly developed high-throughput screening method

This study provided a new method which applied a selected L-lysine-inducible promoter for evolving lysine industrial strains of E. coli. According to the intracellular levels of the enhanced green fluorescent protein (EGFP) whose expression was controlled by the promoter, 186 strains were preliminarily selected using fluorescence-activated cell sorting from a 10-million-mutant library generated from a L-lysine high-producing E. coli strain. By subsequent multiple parameter evaluation of the 186 selected strains according to the concentration and the yield of lysine, the productivity per unit of cell in 96-deep-well blocks, two mutants MU-1 and MU-2 were obtained. They produced 136.51 ± 1.55 and 133.2 9 ± 1.42 g/L of lysine, respectively, in 5-L jars. Compared with the lysine concentration and the yield of the original strain, those of strain MU-1 improved by 21.00 and 9.05 %, respectively, and those of strain MU-2 improved by 18.14 and 10.41 %, respectively. The mutant selection and evaluation system newly established in our study should be useful for continuous improvement of the current E. coli strains in the lysine industry.

Metabolic engineering of Escherichia coli for poly(3-hydroxybutyrate) production via threonine bypass

BACKGROUND

Poly(3-hydroxybutyrate) (PHB), have been considered to be good candidates for completely biodegradable polymers due to their similar mechanical properties to petroleum-derived polymers and complete biodegradability. Escherichia coli has been used to simulate the distribution of metabolic fluxes in recombinant E. coli producing poly(3-hydroxybutyrate) (PHB). Genome-scale metabolic network analysis can reveal unexpected metabolic engineering strategies to improve the production of biochemicals and biofuels.

RESULTS

In this study, we reported the discovery of a new pathway called threonine bypass by flux balance analysis of the genome-scale metabolic model of E. coli. This pathway, mainly containing the reactions for threonine synthesis and degradation, can potentially increase the yield of PHB and other acetyl-CoA derived products by reutilizing the CO2 released at the pyruvate dehydrogenase step. To implement the threonine bypass for PHB production in E. coli, we deregulated the threonine and serine degradation pathway and enhanced the threonine synthesis, resulting in 2.23-fold improvement of PHB titer. Then, we overexpressed glyA to enhance the conversion of glycine to serine and activated transhydrogenase to generate NADPH required in the threonine bypass.

CONCLUSIONS

The result strain TB17 (pBHR68) produced 6.82 g/L PHB with the yield of 0.36 g/g glucose in the shake flask fermentation and 35.92 g/L PHB with the yield of 0.23 g/g glucose in the fed-batch fermentation, which was almost 3.3-fold higher than the parent strain. The work outlined here shows that genome-scale metabolic network analysis can reveal novel metabolic engineering strategies for developing efficient microbial cell factories.

13 C flux analysis of cyanobacterial metabolism

(13)C metabolic flux analysis (MFA) has made important contributions to our understanding of the physiology of model strains of E. coli and yeast, and it has been widely used to guide metabolic engineering efforts in these microorganisms. Recent advancements in (13)C MFA methodology combined with publicly available software tools are creating new opportunities to extend this approach to examine less characterized microbes. In particular, growing interest in the use of cyanobacteria as industrial hosts for photosynthetic production of biofuels and biochemicals has led to a critical need to better understand how cyanobacterial metabolic fluxes are regulated in response to changes in growth conditions or introduction of heterologous pathways. In this contribution, we review several prior studies that have applied isotopic steady-state (13)C MFA to examine heterotrophic or mixotrophic growth of cyanobacteria, as well as recent studies that have pioneered the use of isotopically nonstationary MFA (INST-MFA) to study autotrophic cultures. We also provide recommendations for the design and analysis of INST-MFA experiments in cyanobacteria, based on our previous experience and a series of simulation studies used to assess the selection of measurements and sample time points. We anticipate that this emerging knowledgebase of prior (13)C MFA studies, optimized experimental protocols, and public software tools will catalyze increasing use of (13)C MFA techniques by the cyanobacteria research community.

CMRegNet-An interspecies reference database for corynebacterial and mycobacterial regulatory networks

Background

Organisms utilize a multitude of mechanisms for responding to changing environmental conditions, maintaining their functional homeostasis and to overcome stress situations. One of the most important mechanisms is transcriptional gene regulation. In-depth study of the transcriptional gene regulatory network can lead to various practical applications, creating a greater understanding of how organisms control their cellular behavior.

Description

In this work, we present a new database, CMRegNet for the gene regulatory networks of Corynebacterium glutamicum ATCC 13032 and Mycobacterium tuberculosis H37Rv. We furthermore transferred the known networks of these model organisms to 18 other non-model but phylogenetically close species (target organisms) of the CMNR group. In comparison to other network transfers, for the first time we utilized two model organisms resulting into a more diverse and complete network of the target organisms.

Conclusion

CMRegNet provides easy access to a total of 3,103 known regulations in C. glutamicum ATCC 13032 and M. tuberculosis H37Rv and to 38,940 evolutionary conserved interactions for 18 non-model species of the CMNR group. This makes CMRegNet to date the most comprehensive database of regulatory interactions of CMNR bacteria. The content of CMRegNet is publicly available online via a web interface found at http://lgcm.icb.ufmg.br/cmregnet.

Tailoring specialized metabolite production in streptomyces

Streptomycetes are prolific producers of a plethora of medically useful metabolites. These compounds are made by complex secondary (specialized) metabolic pathways, which utilize primary metabolic intermediates as building blocks. In this review we discuss the evolution of specialized metabolites and how expansion of gene families in primary metabolism has lead to the evolution of diversity in these specialized metabolic pathways and how developing a better understanding of expanded primary metabolic pathways can help enhance synthetic biology approaches to industrial pathway engineering.

Improvement of cell growth and L-lysine production by genetically modified Corynebacterium glutamicum during growth on molasses

Fructose-1,6-bisphosphatase (FBPase) and fructokinase (ScrK) have important roles in regenerating glucose-6-phosphate in the pentose phosphate pathway (PPP), and thus increasing L-lysine production. This article focuses on the development of L-lysine high-producing strains by heterologous expression of FBPase gene fbp and ScrK gene scrK in C. glutamicum lysC (fbr) with molasses as the sole carbon source. Heterologous expression of fbp and scrK lead to a decrease of residual sugar in fermentation broth, and heterologous expression of scrK prevents the fructose efflux. Heterologous expression of fbp and scrK not only increases significantly the activity of corresponding enzymes but also improves cell growth during growth on molasses. FBPase activities are increased tenfold by heterologous expression of fbp, whereas the FBPase activity is only increase fourfold during co-expression of scrK and fbp. Compared with glucose, the DCW of heterologous expression strains are higher on molasses except co-expression of fbp and scrK strain. In addition, heterologous expression of fbp and scrK can strongly increase the L-lysine production with molasses as the sole carbon source. The highest increase (88.4 %) was observed for C. glutamicum lysC (fbr) pDXW-8-fbp-scrK, but the increase was also significant for C. glutamicum lysC (fbr) pDXW-8-fbp (47.2 %) and C. glutamicum lysC (fbr) pDXW-8-scrK (36.8 %). By-products, such as glycerol and dihydroxyacetone, are decreased by heterologous expression of fbp and scrK, whereas trehalose is only slightly increased. The strategy for enhancing L-lysine production by regeneration of glucose-6-phosphate in PPP may provide a reference to enhance the production of other amino acids during growth on molasses or starch.

Metabolic engineering and in vitro biosynthesis of phytochemicals and non-natural analogues

Over the years, natural products from plants and their non-natural derivatives have shown to be active against different types of chronic diseases. However, isolation of such natural products can be limited due to their low bioavailability, and environmental restrictions. To address these issues, in vivo and in vitro reconstruction of plant metabolic pathways and the metabolic engineering of microbes and plants have been used to generate libraries of compounds. Significant advances have been made through metabolic engineering of microbes and plant cells to generate a variety of compounds (e.g. isoprenoids, flavonoids, or stilbenes) using a diverse array of methods to optimize these processes (e.g. host selection, operational variables, precursor selection, gene modifications). These approaches have been used also to generate non-natural analogues with different bioactivities. In vitro biosynthesis allows the synthesis of intermediates as well as final products avoiding post-translational limitations. Moreover, this strategy allows the use of substrates and the production of metabolites that could be toxic for cells, or expand the biosynthesis into non-conventional media (e.g. organic solvents, supercritical fluids). A perspective is also provided on the challenges for generating novel chemical structures and the potential of combining metabolic engineering and in vitro biocatalysis to produce metabolites with more potent biological activities.

Exploring antibiotic biosynthesis: Leo Vining's insights lead to new strategies in the quest for 'The 10 × '20 Initiative'

The late Professor Leo Vining began his antibiotics research career as a visiting scientist in the laboratory of Selman Waksman at Rutgers University during the golden age of antibiotics. Through six decades of his distinguished career, Vining explored the biosynthesis of dozens of antibacterial and antifungal compounds produced by microorganisms. A number of underlying mechanisms of antibiotic biosynthesis were unraveled through his holistic approach and the findings laid the foundation to our understanding of regulation of antibiotic biosynthesis. In this paper, we reflect on Professor Vining's antibiotic research philosophy from a personal perspective and connect this philosophy to new approaches for rapid development of the next generation of antibiotics, which is urgently needed to combat the threat of escalating antimicrobial resistance. Facing the urgency, The Infectious Disease Society of America launched 'The 10 × '20 Initiative' in 2010 and called for a global commitment to develop 10 new, safe and effective antibiotics by the year 2020.(1.)

A metabolite-centric view on flux distributions in genome-scale metabolic models

Background

Genome-scale metabolic models are important tools in systems biology. They permit the in-silico prediction of cellular phenotypes via mathematical optimisation procedures, most importantly flux balance analysis. Current studies on metabolic models mostly consider reaction fluxes in isolation. Based on a recently proposed metabolite-centric approach, we here describe a set of methods that enable the analysis and interpretation of flux distributions in an integrated metabolite-centric view. We demonstrate how this framework can be used for the refinement of genome-scale metabolic models.

Results

We applied the metabolite-centric view developed here to the most recent metabolic reconstruction of Escherichia coli. By compiling the balance sheets of a small number of currency metabolites, we were able to fully characterise the energy metabolism as predicted by the model and to identify a possibility for model refinement in NADPH metabolism. Selected branch points were examined in detail in order to demonstrate how a metabolite-centric view allows identifying functional roles of metabolites. Fructose 6-phosphate aldolase and the sedoheptulose bisphosphate bypass were identified as enzymatic reactions that can carry high fluxes in the model but are unlikely to exhibit significant activity in vivo. Performing a metabolite essentiality analysis, unconstrained import and export of iron ions could be identified as potentially problematic for the quality of model predictions.

Conclusions

The system-wide analysis of split ratios and branch points allows a much deeper insight into the metabolic network than reaction-centric analyses. Extending an earlier metabolite-centric approach, the methods introduced here establish an integrated metabolite-centric framework for the interpretation of flux distributions in genome-scale metabolic networks that can complement the classical reaction-centric framework. Analysing fluxes and their metabolic context simultaneously opens the door to systems biological interpretations that are not apparent from isolated reaction fluxes. Particularly powerful demonstrations of this are the analyses of the complete metabolic contexts of energy metabolism and the folate-dependent one-carbon pool presented in this work. Finally, a metabolite-centric view on flux distributions can guide the refinement of metabolic reconstructions for specific growth scenarios.

The role of membrane transport in metabolic engineering of plant primary metabolism

Plant cells are highly compartmentalized and so is their metabolism. Most metabolic pathways are distributed across several cellular compartments, which requires the activities of membrane transporters to catalyze the flux of precursors, intermediates, and end products between compartments. Metabolites such as sucrose and amino acids have to be transported between cells and tissues to supply, for example, metabolism in developing seeds or fruits with precursors and energy. Thus, rational engineering of plant primary metabolism requires a detailed and molecular understanding of the membrane transporters. This knowledge however still lags behind that of soluble enzymes. Recent advances include the molecular identification of pyruvate transporters at the chloroplast and mitochondrial membranes and of a new class of transporters called SWEET that are involved in the release of sugars to the apoplast.

An integrated computational and experimental study for overproducing fatty acids in Escherichia coli

Increasing demands for petroleum have stimulated sustainable ways to produce chemicals and biofuels. Specifically, fatty acids of varying chain lengths (C₆-C₁₆) naturally synthesized in many organisms are promising starting points for the catalytic production of industrial chemicals and diesel-like biofuels. However, bio-production of fatty acids from plants and other microbial production hosts relies heavily on manipulating tightly regulated fatty acid biosynthetic pathways. In addition, precursors for fatty acids are used along other central metabolic pathways for the production of amino acids and biomass, which further complicates the engineering of microbial hosts for higher yields. Here, we demonstrate an iterative metabolic engineering effort that integrates computationally driven predictions and metabolic flux analysis techniques to meet this challenge. The OptForce procedure was used for suggesting and prioritizing genetic manipulations that overproduce fatty acids of different chain lengths from C₆ to C₁₆ starting with wild-type E. coli. We identified some common but mostly chain-specific genetic interventions alluding to the possibility of fine-tuning overproduction for specific fatty acid chain lengths. In accordance with the OptForce prioritization of interventions, fabZ and acyl-ACP thioesterase were upregulated and fadD was deleted to arrive at a strain that produces 1.70 g/L and 0.14 g fatty acid/g glucose (∼39% maximum theoretical yield) of C₁₄₋₁₆ fatty acids in minimal M9 medium. These results highlight the benefit of using computational strain design and flux analysis tools in the design of recombinant strains of E. coli to produce free fatty acids.

Advancing biopharmaceutical process development by system-level data analysis and integration of omics data

Development of efficient bioprocesses is essential for cost-effective manufacturing of recombinant therapeutic proteins. To achieve further process improvement and process rationalization comprehensive data analysis of both process data and phenotypic cell-level data is essential. Here, we present a framework for advanced bioprocess data analysis consisting of multivariate data analysis (MVDA), metabolic flux analysis (MFA), and pathway analysis for mapping of large-scale gene expression data sets. This data analysis platform was applied in a process development project with an IgG-producing Chinese hamster ovary (CHO) cell line in which the maximal product titer could be increased from about 5 to 8 g/L.Principal component analysis (PCA), k-means clustering, and partial least-squares (PLS) models were applied to analyze the macroscopic bioprocess data. MFA and gene expression analysis revealed intracellular information on the characteristics of high-performance cell cultivations. By MVDA, for example, correlations between several essential amino acids and the product concentration were observed. Also, a grouping into rather cell specific productivity-driven and process control-driven processes could be unraveled. By MFA, phenotypic characteristics in glycolysis, glutaminolysis, pentose phosphate pathway, citrate cycle, coupling of amino acid metabolism to citrate cycle, and in the energy yield could be identified. By gene expression analysis 247 deregulated metabolic genes were identified which are involved, inter alia, in amino acid metabolism, transport, and protein synthesis.

Synergy between (13)C-metabolic flux analysis and flux balance analysis for understanding metabolic adaptation to anaerobiosis in E. coli

Genome-based Flux Balance Analysis (FBA) and steady-state isotopic-labeling-based Metabolic Flux Analysis (MFA) are complimentary approaches to predicting and measuring the operation and regulation of metabolic networks. Here, genome-derived models of Escherichia coli (E. coli) metabolism were used for FBA and ¹³C-MFA analyses of aerobic and anaerobic growths of wild-type E. coli (K-12 MG1655) cells. Validated MFA flux maps reveal that the fraction of maintenance ATP consumption in total ATP production is about 14% higher under anaerobic (51.1%) than aerobic conditions (37.2%). FBA revealed that an increased ATP utilization is consumed by ATP synthase to secrete protons from fermentation. The TCA cycle is shown to be incomplete in aerobically growing cells and submaximal growth is due to limited oxidative phosphorylation. An FBA was successful in predicting product secretion rates in aerobic culture if both glucose and oxygen uptake measurement were constrained, but the most-frequently predicted values of internal fluxes yielded from sampling the feasible space differ substantially from MFA-derived fluxes.

Utilizing elementary mode analysis, pathway thermodynamics, and a genetic algorithm for metabolic flux determination and optimal metabolic network design

BACKGROUND

Microbial hosts offer a number of unique advantages when used as production systems for both native and heterologous small-molecules. These advantages include high selectivity and benign environmental impact; however, a principal drawback is low yield and/or productivity, which limits economic viability. Therefore a major challenge in developing a microbial production system is to maximize formation of a specific product while sustaining cell growth. Tools to rationally reconfigure microbial metabolism for these potentially conflicting objectives remain limited. Exhaustively exploring combinations of genetic modifications is both experimentally and computationally inefficient, and can become intractable when multiple gene deletions or insertions need to be considered. Alternatively, the search for desirable gene modifications may be solved heuristically as an evolutionary optimization problem. In this study, we combine a genetic algorithm and elementary mode analysis to develop an optimization framework for evolving metabolic networks with energetically favorable pathways for production of both biomass and a compound of interest.

RESULTS

Utilization of thermodynamically-weighted elementary modes for flux reconstruction of E. coli central metabolism revealed two clusters of EMs with respect to their Delta Gp degrees. For proof of principle testing, the algorithm was applied to ethanol and lycopene production in E. coli. The algorithm was used to optimize product formation, biomass formation, and product and biomass formation simultaneously. Predicted knockouts often matched those that have previously been implemented experimentally for improved product formation. The performance of a multi-objective genetic algorithm showed that it is better to couple the two objectives in a single objective genetic algorithm.

CONCLUSION

A computationally tractable framework is presented for the redesign of metabolic networks for maximal product formation combining elementary mode analysis (a form of convex analysis), pathway thermodynamics, and a genetic algorithm to optimize the production of two industrially-relevant products, ethanol and lycopene, from E. coli. The designed algorithm can be applied to any small-scale model of cellular metabolism theoretically utilizing any substrate and applied towards the production of any product.

Analysis and engineering of metabolic pathway fluxes in Corynebacterium glutamicum

The Gram-positive soil bacterium Corynebacterium glutamicum was discovered as a natural overproducer of glutamate about 50 years ago. Linked to the steadily increasing economical importance of this microorganism for production of glutamate and other amino acids, the quest for efficient production strains has been an intense area of research during the past few decades. Efficient production strains were created by applying classical mutagenesis and selection and especially metabolic engineering strategies with the advent of recombinant DNA technology. Hereby experimental and computational approaches have provided fascinating insights into the metabolism of this microorganism and directed strain engineering. Today, C. glutamicum is applied to the industrial production of more than 2 million tons of amino acids per year. The huge achievements in recent years, including the sequencing of the complete genome and efficient post genomic approaches, now provide the basis for a new, fascinating era of research - analysis of metabolic and regulatory properties of C. glutamicum on a global scale towards novel and superior bioprocesses.

Metabolic flux analysis in plants: coping with complexity

Theory and experience in metabolic engineering both show that metabolism operates at the network level. In plants, this complexity is compounded by a high degree of compartmentation and the synthesis of a very wide array of secondary metabolic products. A further challenge to understanding and predicting plant metabolic function is posed by our ignorance about the structure of metabolic networks even in well-studied systems. Metabolic flux analysis (MFA) provides tools to measure and model the functioning of metabolism, and is making significant contributions to coping with their complexity. This review gives an overview of different MFA approaches, the measurements required to implement them and the information they yield. The application of MFA methods to plant systems is then illustrated by several examples from the recent literature. Next, the challenges that plant metabolism poses for MFA are discussed together with ways that these can be addressed. Lastly, new developments in MFA are described that can be expected to improve the range and reliability of plant MFA in the coming years.

Mutagenesis of the bacterial RNA polymerase alpha subunit for improvement of complex phenotypes

Combinatorial or random methods for strain engineering have been extensively used for the improvement of multigenic phenotypes and other traits for which the underlying mechanism is not fully understood. Although the preferred method has traditionally been mutagenesis and selection, our laboratory has successfully used mutant transcription factors, which direct the RNA polymerase (RNAP) during transcription, to engineer complex phenotypes in microbial cells. Here, we show that it is also possible to impart new phenotypes by altering the RNAP core enzyme itself, in particular through mutagenesis of the alpha subunit of the bacterial polymerase. We present the use of this tool for improving tolerance of Escherichia coli to butanol and other solvents and for increasing the titers of two commercially relevant products, L-tyrosine and hyaluronic acid. In addition, we explore the underlying physiological changes that give rise to the solvent-tolerant mutant.

Metabolic capacity estimation of Escherichia coli as a platform for redox biocatalysis: constraint-based modeling and experimental verification

Whole-cell redox biocatalysis relies on redox cofactor regeneration by the microbial host. Here, we applied flux balance analysis based on the Escherichia coli metabolic network to estimate maximal NADH regeneration rates. With this optimization criterion, simulations showed exclusive use of the pentose phosphate pathway at high rates of glucose catabolism, a flux distribution usually not found in wild-type cells. In silico, genetic perturbations indicated a strong dependency of NADH yield and formation rate on the underlying metabolic network structure. The linear dependency of measured epoxidation activities of recombinant central carbon metabolism mutants on glucose uptake rates and the linear correlation between measured activities and simulated NADH regeneration rates imply intracellular NADH shortage. Quantitative comparison of computationally predicted NADH regeneration and experimental epoxidation rates indicated that the achievable biocatalytic activity is determined by metabolic and enzymatic limitations including non-optimal flux distributions, high maintenance energy demands, energy spilling, byproduct formation, and uncoupling. The results are discussed in the context of cellular optimization of biotransformation processes and may guide a priori design of microbial cells as redox biocatalysts.