Brett A. Boghigian

Metabolic flux analysis and pharmaceutical production.

Rational engineering of biological systems is an inherently complex process due to their evolved nature. Metabolic engineering emerged and developed over the past 20 years as a field in which methodologies for the rational engineering of biological systems is now being applied to specific industrial, medical, or scientific problems. Of considerable interest is the determination of metabolic fluxes within the cell itself, called metabolic flux analysis. This special issue and this review have a particular interest in the application of metabolic flux analysis for improving the pharmaceutical production process (for both small and large molecules). Though metabolic flux analysis has been somewhat limited in application towards pharmaceutical production, the overall goal is to: (1) have a better understanding of the organism and/or process in question, and (2) provide a rational basis to further engineer (on both metabolic and process scales) improved pharmaceutical production in these organisms. The focus of this review article is to present how experimental and computational methods of metabolic flux analysis have matured, mirroring the maturation of the metabolic engineering field itself, while highlighting some of the successful applications towards both small- and large-molecule pharmaceuticals.

Investigating the role of native propionyl-CoA and methylmalonyl-CoA metabolism on heterologous polyketide production in Escherichia coli

6‐Deoxyerythronolide B (6dEB) is the macrocyclic aglycone precursor of the antibiotic natural product erythromycin. Heterologous production of 6dEB in Escherichia coli was accomplished, in part, by designed over‐expression of a native prpE gene (encoding a propionyl‐CoA synthetase) and heterologous pcc genes (encoding a propionyl‐CoA carboxylase) to supply the needed propionyl‐CoA and (2S)‐methylmalonyl‐CoA biosynthetic substrates. Separate E. coli metabolism includes three enzymes, Sbm (a methylmalonyl‐CoA mutase), YgfG (a methylmalonyl‐CoA decarboxylase), and YgfH (a propionyl‐CoA:succinate CoA transferase), also involved in propionyl‐CoA and methylmalonyl‐CoA metabolism. In this study, the sbm, ygfG, and ygfH genes were individually deleted and over‐expressed to investigate their effect on heterologous 6dEB production. Our results indicate that the deletion and over‐expression of sbm did not influence 6dEB production; ygfG over‐expression reduced 6dEB production by fourfold while ygfH deletion increased 6dEB titers from 65 to 129 mg/L in shake flask experiments. It was also found that native E. coli metabolism could support 6dEB biosynthesis in the absence of exogenous propionate and the substrate provision pcc genes. Lastly, the effect of the ygfH deletion was tested in batch bioreactor cultures in which 6dEB titers improved from 206 to 527 mg/L. Biotechnol. Bioeng. 2010; 105: 567–573.

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

BackgroundMicrobial 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.ResultsUtilization of thermodynamically-weighted elementary modes for flux reconstruction of E. coli central metabolism revealed two clusters of EMs with respect to their ΔGp°. 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.ConclusionA 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.

Computational identification of gene over-expression targets for metabolic engineering of taxadiene production.

Taxadiene is the first dedicated intermediate in the biosynthetic pathway of the anticancer compound Taxol. Recent studies have taken advantage of heterologous hosts to produce taxadiene and other isoprenoid compounds, and such ventures now offer research opportunities that take advantage of the engineering tools associated with the surrogate host. In this study, metabolic engineering was applied in the context of over-expression targets predicted to improve taxadiene production. Identified targets included genes both within and outside of the isoprenoid precursor pathway. These targets were then tested for experimental over-expression in a heterologous Escherichia coli host designed to support isoprenoid biosynthesis. Results confirmed the computationally predicted improvements and indicated a synergy between targets within the expected isoprenoid precursor pathway and those outside this pathway. The presented algorithm is broadly applicable to other host systems and/or product choices.

Analysis of heterologous taxadiene production in K- and B-derived Escherichia coli

Taxa-4(5),11(12)-diene is the first dedicated intermediate in the metabolic pathway responsible for synthesizing the anticancer compound Taxol. In this study, the heterologous production of taxadiene was established in and analyzed between K- and B-derived Escherichia coli strains. First, recombinant parameters associated with precursor metabolism (the upstream methylerythritol phosphate (MEP) pathway) and taxadiene biosynthesis (the downstream pathway) were varied to probe the effect different promoters and cellular backgrounds have on taxadiene production. Specifically, upstream MEP pathway genes responsible for the taxadiene precursors, dimethylallyl diphosphate and isopentenyl diphosphate, were tested with an inducible T7 promoter system within K and B E. coli strains. Whereas, inducible T7, Trc, and T5 promoters were tested with the plasmid-borne geranylgeranyl diphosphate synthase and taxadiene synthase genes responsible for the downstream pathway. The K-derivative produced taxadiene roughly 2.5-fold higher than the B-derivative. A transcriptomics study revealed significant differences in pyruvate metabolism between the K and B strains, providing insight into the differences observed in taxadiene biosynthesis and targets for future metabolic engineering efforts. Next, the effect of temperature on cell growth and taxadiene production was analyzed in these two strains, revealing similar phenotypes between the two with 22°C as the optimal production temperature. Lastly, the effect of indole on cell growth was investigated between the two strains, showing that the K-derivative demonstrated greater growth inhibition compared to the B-derivative.

Current status, strategies, and potential for the metabolic engineering of heterologous polyketides in Escherichia coli

Heterologous natural product biosynthesis has emerged as a strategy to produce medicinal compounds that pose challenges to conventional production routes. Polyketide compounds, an important class of natural products with wide-ranging therapeutic value, have been heterologously produced through Escherichia coli, presenting new opportunities to realize the medicinal potential of polyketide natural products. However, current production levels are often suboptimal when compared to native strain producers or heterologous theoretical yields. This problem provides an excellent opportunity to apply and further develop current metabolic engineering tools.

Multi‐factorial engineering of heterologous polyketide production in Escherichia coli reveals complex pathway interactions

Polyketides represent a significant fraction of all natural products. Many possess pharmacological activity which makes them attractive drug candidates. The production of the parent macrocyclic aglycones is catalyzed by multi‐modular polyketide synthases utilizing short‐chain acyl‐CoA monomers. When producing polyketides through heterologous hosts, one must not only functionally express the synthase itself, but activate the machinery used to generate the required substrate acyl‐CoAs. As a result, metabolic engineering of these pathways is necessary for high‐level production of heterologous polyketides. In this study, we over‐express three different pathways for provision of the two substrates (propionyl‐CoA and (2S)‐methylmalonyl‐CoA) utilized for the biosynthesis of 6‐deoxyerythronolide B (6‐dEB; the macrolactone precursor of erythromycin): (1) a propionate → propionyl‐CoA → (2S)‐methylmalonyl‐CoA pathway, (2) a methylmalonate → methylmalonyl‐CoA → propionyl‐CoA pathway, and (3) a succinate → succinyl‐CoA → (2R)‐methylmalonyl‐CoA → (2S)‐methylmalonyl‐CoA → propionyl‐CoA pathway. The current study revealed that propionate is a necessary component for greater than 5 mg L−1 titers. Deletion of the propionyl‐CoA:succinate CoA transferase (ygfH) or over‐expression of the transcriptional activator of short chain fatty acid uptake improved titer to over 100 mg L−1, while the combination of the two improved titer to over 130 mg L−1. The addition of exogenous methylmalonate could also improve titer to over 100 mg L−1. Expression of a Streptomyces coelicolor A3(2) methylmalonyl‐CoA epimerase, in conjunction with over‐expression of Escherichia colis native methylmalonyl‐CoA mutase, allowed for the incorporation of exogenously fed succinate into the 6‐dEB core. Biotechnol. Bioeng. 2011; 108:1360–1371.

LC-MS/MS quantification of short-chain acyl-CoA's in Escherichia coli demonstrates versatile propionyl-CoA synthetase substrate specificity

Aims:  This paper utilized quantitative LC‐MS/MS to profile the short‐chain acyl‐CoA levels of several strains of Escherichia coli engineered for heterologous polyketide production. To further compare and potentially expand the levels of available acyl‐CoA molecules, a propionyl‐CoA synthetase gene from Ralstonia solanacearum (prpE‐RS) was synthesized and expressed in the engineered strain BAP1.

LC-MS/MS quantification of short-chain acyl-CoA's in Escherichia coli demonstrates versatile propionyl-CoA synthetase substrate specificity.

Aims:  This paper utilized quantitative LC‐MS/MS to profile the short‐chain acyl‐CoA levels of several strains of Escherichia coli engineered for heterologous polyketide production. To further compare and potentially expand the levels of available acyl‐CoA molecules, a propionyl‐CoA synthetase gene from Ralstonia solanacearum (prpE‐RS) was synthesized and expressed in the engineered strain BAP1.

Computational analysis of phenotypic space in heterologous polyketide biosynthesis--applications to Escherichia coli, Bacillus subtilis, and Saccharomyces cerevisiae.

Polyketides represent a class of natural product small molecules with an impressive range of medicinal activities. In order to improve access to therapeutic polyketide compounds, heterologous metabolic engineering has been applied to transfer polyketide genetic pathways from often fastidious native hosts to more industrially-amenable heterologous hosts such as Escherichia coli, Saccharomyces cerevisiae, or Streptomyces coelicolor. Efforts thus far have resulted in titers either inferior to the native host and significantly below the theoretical yield, emphasizing the need to computationally investigate and engineer the interaction between native and heterologous metabolism for the improved production of heterologous polyketide compounds. In this work, we applied flux balance analysis on genome-scale models to simulate cellular metabolism and 6-deoxyerythronolide B (the cyclized polyketide precursor to erythromycin) production in three common heterologous hosts (E. coli, Bacillus subtilis, and S. cerevisiae) under a variety of carbon-source and medium compositions. We then undertook minimization of metabolic adjustment optimization to identify single and double gene-knockouts that resulted in increased polyketide production while maintaining cellular growth. For the production of 6-deoxyerythronolide B, the results suggest B. subtilis and E. coli are better heterologous hosts when compared to S. cerevisiae and that several single and multiple gene-knockout mutants are computationally predicted to improve specific production, in some cases, over 25-fold.