Practical genetic control strategies for industrial bioprocesses.

Optimization of metabolism to maximize production of bio-based chemicals must consistently balance cellular resources for biocatalyst growth and desired compound synthesis. This mini-review discusses synthetic biology strategies for dynamically controlling expression of genes to enable dual-phase fermentations in which growth and production are separated into dedicated phases. Emphasis is placed on practical examples which can be reliably scaled to commercial production with the current state of technology. Recent case studies are presented, and recommendations are provided for environmental signals and genetic control circuits.

Structural and functional insights into asymmetric enzymatic dehydration of alkenols.

The asymmetric dehydration of alcohols is an important process for the direct synthesis of alkenes. We report the structure and substrate specificity of the bifunctional linalool dehydratase isomerase (LinD) from the bacterium Castellaniella defragrans that catalyzes in nature the hydration of ß-myrcene to linalool and the subsequent isomerization to geraniol. Enzymatic kinetic resolutions of truncated and elongated aromatic and aliphatic tertiary alcohols (C5-C15) that contain a specific signature motif demonstrate the broad substrate specificity of LinD. The three-dimensional structure of LinD from Castellaniella defragrans revealed a pentamer with active sites at the protomer interfaces. Furthermore, the structure of LinD in complex with the product geraniol provides initial mechanistic insights into this bifunctional enzyme. Site-directed mutagenesis confirmed active site amino acid residues essential for its dehydration and isomerization activity. These structural and mechanistic insights facilitate the development of hydrating catalysts, enriching the toolbox for novel bond-forming biocatalysis.

Development of a commercial scale process for production of 1,4-butanediol from sugar.

A sustainable bioprocess for the production of 1,4-butanediol (BDO) from carbohydrate feedstocks was developed. BDO is a chemical intermediate that goes into a variety of products including automotive parts, electronics, and apparel, and is currently manufactured commercially through energy-intensive petrochemical processes using fossil raw materials. This review highlights the development of an Escherichia coli strain and an overall process that successfully performed at commercial scale for direct production of bio-BDO from dextrose. Achieving such high level performance required an integrated technology platform enabling detailed engineering of enzyme, pathway, metabolic network, and organism, as well as development of effective fermentation and downstream recovery processes.

Identification of metabolic engineering targets for the enhancement of 1,4-butanediol production in recombinant E. coli using large-scale kinetic models.

Rational metabolic engineering methods are increasingly employed in designing the commercially viable processes for the production of chemicals relevant to pharmaceutical, biotechnology, and food and beverage industries. With the growing availability of omics data and of methodologies capable to integrate the available data into models, mathematical modeling and computational analysis are becoming important in designing recombinant cellular organisms and optimizing cell performance with respect to desired criteria. In this contribution, we used the computational framework ORACLE (Optimization and Risk Analysis of Complex Living Entities) to analyze the physiology of recombinant Escherichia coli producing 1,4-butanediol (BDO) and to identify potential strategies for improved production of BDO. The framework allowed us to integrate data across multiple levels and to construct a population of large-scale kinetic models despite the lack of available information about kinetic properties of every enzyme in the metabolic pathways. We analyzed these models and we found that the enzymes that primarily control the fluxes leading to BDO production are part of central glycolysis, the lower branch of tricarboxylic acid (TCA) cycle and the novel BDO production route. Interestingly, among the enzymes between the glucose uptake and the BDO pathway, the enzymes belonging to the lower branch of TCA cycle have been identified as the most important for improving BDO production and yield. We also quantified the effects of changes of the target enzymes on other intracellular states like energy charge, cofactor levels, redox state, cellular growth, and byproduct formation. Independent earlier experiments on this strain confirmed that the computationally obtained conclusions are consistent with the experimentally tested designs, and the findings of the present studies can provide guidance for future work on strain improvement. Overall, these studies demonstrate the potential and effectiveness of ORACLE for the accelerated design of microbial cell factories.

Biotechnology for Chemical Production: Challenges and Opportunities.

Biotechnology offers a new sustainable approach to manufacturing chemicals, enabling the replacement of petroleum-based raw materials with renewable biobased feedstocks, thereby reducing greenhouse gas (GHG) emissions, toxic byproducts, and the safety risks associated with traditional petrochemical processing. Development of such bioprocesses is enabled by recent advances in genomics, molecular biology, and systems biology, and will continue to accelerate as access to these tools becomes faster and cheaper.

An integrated biotechnology platform for developing sustainable chemical processes.

Genomatica has established an integrated computational/experimental metabolic engineering platform to design, create, and optimize novel high performance organisms and bioprocesses. Here we present our platform and its use to develop E. coli strains for production of the industrial chemical 1,4-butanediol (BDO) from sugars. A series of examples are given to demonstrate how a rational approach to strain engineering, including carefully designed diagnostic experiments, provided critical insights about pathway bottlenecks, byproducts, expression balancing, and commercial robustness, leading to a superior BDO production strain and process.

From the first drop to the first truckload: commercialization of microbial processes for renewable chemicals.

Fermentation of carbohydrate substrates by microorganisms represents an attractive route for the manufacture of industrial chemicals from renewable resources. The technology to manipulate metabolism of bacteria and yeast, including the introduction of heterologous chemical pathways, has accelerated research in this field. However, the public literature contains very few examples of strains achieving the production metrics required for commercialization. This article presents the challenges in reaching commercial titer, yield, and productivity targets, along with other necessary strain and process characteristics. It then reviews various methods in systems biology, synthetic biology, enzyme engineering, and fermentation engineering which can be applied to strain improvement, and presents a strategy for using these tools to overcome the major hurdles on the path to commercialization.

Metabolic engineering of Escherichia coli for direct production of 1,4-butanediol.

1,4-Butanediol (BDO) is an important commodity chemical used to manufacture over 2.5 million tons annually of valuable polymers, and it is currently produced exclusively through feedstocks derived from oil and natural gas. Herein we report what are to our knowledge the first direct biocatalytic routes to BDO from renewable carbohydrate feedstocks, leading to a strain of Escherichia coli capable of producing 18 g l(-1) of this highly reduced, non-natural chemical. A pathway-identification algorithm elucidated multiple pathways for the biosynthesis of BDO from common metabolic intermediates. Guided by a genome-scale metabolic model, we engineered the E. coli host to enhance anaerobic operation of the oxidative tricarboxylic acid cycle, thereby generating reducing power to drive the BDO pathway. The organism produced BDO from glucose, xylose, sucrose and biomass-derived mixed sugar streams. This work demonstrates a systems-based metabolic engineering approach to strain design and development that can enable new bioprocesses for commodity chemicals that are not naturally produced by living cells.

Dynamic modeling of Escherichia coli metabolic and regulatory systems for amino-acid production.

Our aim is to construct a practical dynamic-simulation system that can model the metabolic and regulatory processes involved in the production of primary metabolites, such as amino acids. We have simulated the production of glutamate by transient batch-cultivation using a model of Escherichia coli central metabolism. Kinetic data were used to produce both the metabolic parts of the model, including the phosphotransferase system, glycolysis, the pentose-phosphate pathway, the tricarboxylic acid cycle, the glyoxylate shunt, and the anaplerotic pathways, and the regulatory parts of the model, including regulation by transcription factors, cyclic AMP receptor protein (CRP), making large colonies protein (Mlc), catabolite repressor/activator (Cra), pyruvate dehydrogenase complex repressor (PdhR), and acetate operon repressor (IclR). RNA polymerase and ribosome concentrations were expressed as a function of the specific growth rate, mu, corresponding to the changes in the growth rate during batch cultivation. Parameter fitting was performed using both extracellular concentration measurements and in vivo enzyme activities determined by (13)C flux analysis. By manual adjustment of the parameters, we simulated the batch fermentation of glucose or fructose by a wild-type strain (MG1655) and a glutamate-producing strain (MG1655 Delta sucA). The differences caused by the carbon source, and by wild-type and glutamate-producing strains, were clearly shown by the simulation. A sensitivity analysis revealed the factors that could be altered to improve the production process. Furthermore, an in silico deletion experiments could suggested the existence of uncharacterized regulation. We concluded that our simulation model could function as a new tool for the rational improvement and design of metabolic and regulatory networks.

Absolute metabolite concentrations and implied enzyme active site occupancy in Escherichia coli.

Absolute metabolite concentrations are critical to a quantitative understanding of cellular metabolism, as concentrations impact both the free energies and rates of metabolic reactions. Here we use LC-MS/MS to quantify more than 100 metabolite concentrations in aerobic, exponentially growing Escherichia coli with glucose, glycerol or acetate as the carbon source. The total observed intracellular metabolite pool was approximately 300 mM. A small number of metabolites dominate the metabolome on a molar basis, with glutamate being the most abundant. Metabolite concentration exceeds K(m) for most substrate-enzyme pairs. An exception is lower glycolysis, where concentrations of intermediates are near the K(m) of their consuming enzymes and all reactions are near equilibrium. This may facilitate efficient flux reversibility given thermodynamic and osmotic constraints. The data and analyses presented here highlight the ability to identify organizing metabolic principles from systems-level absolute metabolite concentration data.

Elucidation of an alternate isoleucine biosynthesis pathway in Geobacter sulfurreducens.

The central metabolic model for Geobacter sulfurreducens included a single pathway for the biosynthesis of isoleucine that was analogous to that of Escherichia coli, in which the isoleucine precursor 2-oxobutanoate is generated from threonine. 13C labeling studies performed in G. sulfurreducens indicated that this pathway accounted for a minor fraction of isoleucine biosynthesis and that the majority of isoleucine was instead derived from acetyl-coenzyme A and pyruvate, possibly via the citramalate pathway. Genes encoding citramalate synthase (GSU1798), which catalyzes the first dedicated step in the citramalate pathway, and threonine ammonia-lyase (GSU0486), which catalyzes the conversion of threonine to 2-oxobutanoate, were identified and knocked out. Mutants lacking both of these enzymes were auxotrophs for isoleucine, whereas single mutants were capable of growth in the absence of isoleucine. Biochemical characterization of the single mutants revealed deficiencies in citramalate synthase and threonine ammonia-lyase activity. Thus, in G. sulfurreducens, 2-oxobutanoate can be synthesized either from citramalate or threonine, with the former being the main pathway for isoleucine biosynthesis. The citramalate synthase of G. sulfurreducens constitutes the first characterized member of a phylogenetically distinct clade of citramalate synthases, which contains representatives from a wide variety of microorganisms.

Metabolic flux elucidation for large-scale models using 13C labeled isotopes.

A key consideration in metabolic engineering is the determination of fluxes of the metabolites within the cell. This determination provides an unambiguous description of metabolism before and/or after engineering interventions. Here, we present a computational framework that combines a constraint-based modeling framework with isotopic label tracing on a large scale. When cells are fed a growth substrate with certain carbon positions labeled with (13)C, the distribution of this label in the intracellular metabolites can be calculated based on the known biochemistry of the participating pathways. Most labeling studies focus on skeletal representations of central metabolism and ignore many flux routes that could contribute to the observed isotopic labeling patterns. In contrast, our approach investigates the importance of carrying out isotopic labeling studies using a more comprehensive reaction network consisting of 350 fluxes and 184 metabolites in Escherichia coli including global metabolite balances on cofactors such as ATP, NADH, and NADPH. The proposed procedure is demonstrated on an E. coli strain engineered to produce amorphadiene, a precursor to the antimalarial drug artemisinin. The cells were grown in continuous culture on glucose containing 20% [U-(13)C]glucose; the measurements are made using GC-MS performed on 13 amino acids extracted from the cells. We identify flux distributions for which the calculated labeling patterns agree well with the measurements alluding to the accuracy of the network reconstruction. Furthermore, we explore the robustness of the flux calculations to variability in the experimental MS measurements, as well as highlight the key experimental measurements necessary for flux determination. Finally, we discuss the effect of reducing the model, as well as shed light onto the customization of the developed computational framework to other systems.

Determination of metabolic flux changes during fed-batch cultivation from measurements of intracellular amino acids by LC-MS/MS.

Metabolic flux analysis using (13)C-labeled substrates is a well-developed method for investigating cellular behavior in steady-state culture condition. To extend its application, in particular to typical industrial conditions, such as batch and fed-batch cultivations, a novel method of (13)C metabolic flux analysis is proposed. An isotopomer balancing model was developed to elucidate flux distributions in the central metabolism and all amino acids synthetic pathways. A lysine-producing strain of Escherichia coli was cultivated by fed-batch mode in a growth medium containing yeast extract. Mass distribution data was derived from both intracellular free amino acids and proteinogenic amino acids measured by LC-MS/MS, and a correction parameter for the protein turnover effect on the mass distributions of intracellular amino acids was introduced. Metabolic flux distributions were determined in both exponential and stationary phases. Using this new approach, a culture phase-dependent metabolic shift was detected in the fed-batch culture. The approach presented here has great potential for investigating cellular behavior in industrial processes, independent of cultivation modes, metabolic phase and growth medium.

Theoretical analysis of amino acid-producing Escherichia coli using a stoichiometric model and multivariate linear regression.

This work demonstrates a novel computational approach combining flux balance modeling with statistical methods to identify correlations among fluxes in a metabolic network, providing insight as to how the fluxes should be redirected to achieve maximum product yield. The procedure is demonstrated using the example of amino acid production from an industrial Escherichia coli production strain and a hypothetical engineered strain overexpressing two heterologous genes. Regression analysis based on a random sampling of 5,000 points within the feasible solution space of the E. coli stoichiometric network suggested that increased activity of the glyoxylate cycle or PEP carboxylase and elimination of malic enzyme will improve lysine and arginine synthesis.

Flux analysis uncovers key role of functional redundancy in formaldehyde metabolism.

Genome-scale analysis of predicted metabolic pathways has revealed the common occurrence of apparent redundancy for specific functional units, or metabolic modules. In many cases, mutation analysis does not resolve function, and instead, direct experimental analysis of metabolic flux under changing conditions is necessary. In order to use genome sequences to build models of cellular function, it is important to define function for such apparently redundant systems. Here we describe direct flux measurements to determine the role of redundancy in three modules involved in formaldehyde assimilation and dissimilation in a bacterium growing on methanol. A combination of deuterium and (14)C labeling was used to measure the flux through each of the branches of metabolism for growth on methanol during transitions into and out of methylotrophy. The cells were found to differentially partition formaldehyde among the three modules depending on the flux of methanol into the cell. A dynamic mathematical model demonstrated that the kinetic constants of the enzymes involved are sufficient to account for this phenomenon. We demonstrate the role of redundancy in formaldehyde metabolism and have uncovered a new paradigm for coping with toxic, high-flux metabolic intermediates: a dynamic, interconnected metabolic loop.

Genetic characterization of the carotenoid biosynthetic pathway in Methylobacterium extorquens AM1 and isolation of a colorless mutant.

Genomic searches were used to reconstruct the putative carotenoid biosynthesis pathway in the pink-pigmented facultative methylotroph Methylobacterium extorquens AM1. Four genes for putative phytoene desaturases were identified. A colorless mutant was obtained by transposon mutagenesis, and the insertion was shown to be in one of the putative phytoene desaturase genes. Mutations in the other three did not affect color. The tetracycline marker was removed from the original transposon mutant, resulting in a pigment-free strain with wild-type growth properties useful as a tool for future experiments.

Deciphering environmental signal integration in sigma54-dependent promoters with a simple mathematical model.

A mathematical model was developed to describe the physiological co-regulation of two Pseudomonas sigma54-dependent promoter/regulator systems, Pu/XylR and Po/DmpR of Pseudomonas strains mt2 and CF600, respectively. Five ordinary differential equations and six algebraic equations were developed to describe the following processes of transcription initiation: binding of the activator protein to the upstream activating sequence, union of the sigma factor with the core polymerase, formation of the open complex, and escape of the transcription machinery from the promoter region. In addition, growth-phase control of the integration host factor (IHF), sigma-70 regulation during stationary phase, and the contribution of (p)ppGpp to both sigma factor selectivity and promoter escape were hypothesized. By including any three of these four effects, the model predicted that expression from both promoters is repressed during exponential growth and sharply increases as the cells enter stationary phase. The difference in behavior of the two systems during overexpression of either sigma54 or (p)ppGpp could be explained by different values of two model parameters. To accurately represent the behavior of both promoters in (p)ppGpp null strains, an additional parameter must be varied. Although numerical data available for this system is scarce, the model has proved useful for helping to interpret the experimental observations and to evaluate four hypotheses that have been proposed to explain the phenomenon of exponential silencing.

Quantification of central metabolic fluxes in the facultative methylotroph methylobacterium extorquens AM1 using 13C-label tracing and mass spectrometry.

The metabolic fluxes of central carbon metabolism were measured in chemostat-grown cultures of Methylobacterium extorquens AM1 with methanol as the sole organic carbon and energy source and growth-limiting substrate. Label tracing experiments were carried out using 70% (13)C-methanol in the feed, and the steady-state mass isotopomer distributions of amino acids derived from total cell protein were measured by gas chromatography coupled to mass spectrometry. Fluxes were calculated from the isotopomer distribution data using an isotopomer balance model and evolutionary error minimization algorithm. The combination of labeled methanol with unlabeled CO(2), which enters central metabolism in two different reactions, provided the discriminatory power necessary to allow quantification of the unknown fluxes within a reasonably small confidence interval. In wild-type M. extorquens AM1, no measurable flux was detected through pyruvate dehydrogenase or malic enzyme, and very little flux through alpha-ketoglutarate dehydrogenase (1.4% of total carbon). In contrast, the alpha-ketoglutarate dehydrogenase flux was 25.5% of total carbon in the regulatory mutant strain phaR, while the pyruvate dehydrogenase and malic enzyme fluxes remained insignificant. The success of this technique with growth on C(1) compounds suggests that it can be applied to help characterize the effects of other regulatory mutations, and serve as a diagnostic tool in the metabolic engineering of methylotrophic bacteria.

Reconstruction of C(3) and C(4) metabolism in Methylobacterium extorquens AM1 using transposon mutagenesis.

The growth of Methylobacterium extorquens AM1 on C(1) compounds has been well-studied, but little is known about how this methylotroph grows on multicarbon compounds. A Tn5 transposon mutagenesis procedure was performed to identify genes involved in the growth of M. extorquens AM1 on succinate and pyruvate. Of the 15000 insertion colonies screened, 71 mutants were found that grew on methanol but either grew slowly or were unable to grow on one or both of the multicarbon substrates. For each of these mutants, the chromosomal region adjacent to the insertion site was sequenced, and 55 different genes were identified and assigned putative functions. These genes fell into a number of predicted categories, including central carbon metabolism, carbohydrate metabolism, regulation, transport and non-essential housekeeping functions. This study focused on genes predicted to encode enzymes of central heterotrophic metabolism: 2-oxoglutarate dehydrogenase, pyruvate dehydrogenase and NADH : ubiquinone oxidoreductase. In each case, the mutants showed normal growth on methanol and impaired growth on pyruvate and succinate, consistent with a role specific to heterotrophic metabolism. For the first two cases, no detectable activity of the corresponding enzyme was found in the mutant, verifying the predictions. The results of this study were used to reconstruct multicarbon metabolism of M. extorquens AM1 during growth on methanol, succinate and pyruvate.

Stoichiometric model for evaluating the metabolic capabilities of the facultative methylotroph Methylobacterium extorquens AM1, with application to reconstruction of C(3) and C(4) metabolism.

A stoichiometric model of central metabolism was developed based on new information regarding metabolism in this bacterium to evaluate the steady-state growth capabilities of the serine cycle facultative methylotroph Methylobacterium extorquens AM1 during growth on methanol, succinate, and pyruvate. The model incorporates 20 reversible and 47 irreversible reactions, 65 intracellular metabolites, and experimentally-determined biomass composition. The flux space for this underdetermined system of equations was defined by finding the elementary modes, and constraints based on experimental observations were applied to determine which of these elementary modes give a reasonable description of the flux distribution for each growth substrate. The predicted biomass yield, on a carbon atom basis, is 49.8%, which agrees well with the range of published experimental yield measurements (37-50%). The model predicts the cell to be limited by reduced pyridine nucleotide availability during methylotrophic growth, but energy-limited when growing on multicarbon substrates. Mutation and phenotypic analysis was used to explore a previously unknown region of the metabolic map and to confirm the stoichiometry of the pathways in this region used in the metabolic model. Based on genome sequence data and simulation results, three enzymes involved in C(3)-C(4) interconversion pathways were predicted to be mutually redundant: malic enzyme, phosphoenolpyruvate carboxykinase, and phosphoenolpyruvate synthase. Insertion mutations in the genes predicted to encode these enzymes were made and these mutants were capable of growing on all substrates tested, confirming the redundancy of these pathways. Likewise, pathway analysis suggests that the TCA cycle enzymes citrate synthase and succinate dehydrogenase are essential for all growth substrates. In keeping with these predictions, null mutants could not be obtained in these genes. Finally, a similar model was developed for the ribulose monophosphate pathway obligate methylotroph Methylobacillus flagellatum KT to compare the efficiency of carbon utilization in the two types of methylotrophic carbon utilization pathways. The predicted yield for this organism on methanol is 65.9%.