Minimal reaction sets for Escherichia coli metabolism under different growth requirements and uptake environments

A computational procedure for identifying the minimal set of metabolic reactions capable of supporting various growth rates on different substrates is introduced and applied to a flux balance model of the Escherichia coli metabolic network. This task is posed mathematically as a generalized network optimization problem. The minimal reaction sets capable of supporting specified growth rates are determined for two different uptake conditions: (i) limiting the uptake of organic material to a single organic component (e.g., glucose or acetate) and (ii) allowing the importation of any metabolite with available cellular transport reactions. We find that minimal reaction network sets are highly dependent on the uptake environment and the growth requirements imposed on the network. Specifically, we predict that the E. coli network, as described by the flux balance model, requires 224 metabolic reactions to support growth on a glucose-only medium and 229 for an acetate-only medium, while only 122 reactions enable growth on a specially engineered growth medium.     

Metabolic modeling of polyhydroxybutyrate biosynthesis

A mathematical model describing intracellular polyhydroxybutyrate (PHB) synthesis in Alcaligenes eutrophus has been constructed. The model allows investigation of issues such as the existence of rate-limiting enzymatic steps, possible regulatory mechanisms in PHB synthesis, and the effects different types of rate expressions have on model behavior. Simulations with the model indicate that activities of all PHB pathway enzymes influence overall PHB flux and that no single enzymatic step can easily be identified as rate limiting. Simulations also support regulatory roles for both thiolase and reductase, mediated through AcCoA/CoASH and NADPH/NADP+ ratios, respectively. To make the model more realistic, complex rate expressions for enzyme-catalyzed reactions were used which reflect both the reversibility of the reactions and the reaction mechanisms. Use of the complex kinetic expressions dramatically changed the behavior of the system compared to a simple model containing only Michaelis-Menten kinetic expressions; the more complicated model displayed different responses to changes in enzyme activities as well as inhibition of flux by the reaction products CoASH and NADP+. These effects can be attributed to reversible rate expressions, which allow prediction of reaction rates under conditions both near and far from equilibrium.     

A mathematical model for the branched chain amino acid biosynthetic pathways of Escherichia coli K12

As a first step toward the elucidation of the systems biology of the model organism Escherichia coli, it was our goal to mathematically model a metabolic system of intermediate complexity, namely the well studied end product-regulated pathways for the biosynthesis of the branched chain amino acids L-isoleucine, L-valine, and L-leucine. This has been accomplished with the use of kMech (Yang, C.-R., Shapiro, B. E., Mjolsness, E. D., and Hatfield, G. W. (2005) Bioinformatics 21, in press), a Cellerator (Shapiro, B. E., Levchenko, A., Meyerowitz, E. M., Wold, B. J., and Mjolsness, E. D. (2003) Bioinformatics 19, 677-678) language extension that describes a suite of enzyme reaction mechanisms. Each enzyme mechanism is parsed by kMech into a set of fundamental association-dissociation reactions that are translated by Cellerator into ordinary differential equations. These ordinary differential equations are numerically solved by Mathematica. Any metabolic pathway can be simulated by stringing together appropriate kMech models and providing the physical and kinetic parameters for each enzyme in the pathway. Writing differential equations is not required. The mathematical model of branched chain amino acid biosynthesis in E. coli K12 presented here incorporates all of the forward and reverse enzyme reactions and regulatory circuits of the branched chain amino acid biosynthetic pathways, including single and multiple substrate (Ping Pong and Bi Bi) enzyme kinetic reactions, feedback inhibition (allosteric, competitive, and non-competitive) mechanisms, the channeling of metabolic flow through isozymes, the channeling of metabolic flow via transamination reactions, and active transport mechanisms. This model simulates the results of experimental measurements.     

A mathematical model of N-linked glycosylation

Metabolic engineering of N-linked oligosaccharide biosynthesis to produce novel glycoforms or glycoform distributions of a recombinant glycoprotein can potentially lead to an improved therapeutic performance of the glycoprotein product. A mathematical model for the initial stages of this process, up to the first galactosylation of an oligosaccharide, was previously developed by Umana and Bailey (1997) (UB1997). Building on this work, an extended model is developed to include further galactosylation, fucosylation, extension of antennae by N-acetyllactosamine repeats, and sialylation. This allows many more structural features to be predicted. A number of simplifying assumptions are also relaxed to incorporate more variables for the control of glycoforms. The full model generates 7565 oligosaccharide structures in a network of 22,871 reactions. Methods for solving the model for the complete product distribution and adjusting the parameters to match experimental data are also developed. A basal set of kinetic parameters for the enzyme-catalyzed reactions acting on free oligosaccharide substrates is obtained from the previous model and existing literature. Enzyme activities are adjusted to match experimental glycoform distributions for Chinese Hamster Ovary (CHO). The model is then used to predict the effect of increasing expression of a target glycoprotein on the product glycoform distribution and evaluate appropriate metabolic engineering strategies to return the glycoform profile to its original distribution pattern. This model may find significant utility in the future to predict glycosylation patterns and direct glycoengineering projects to optimize glycoform distributions.     

A metabolic model of cellular energetics and carbon flux during aerobic Escherichia coli fermentation

An integrated metabolic model for the production of acetate by Escherichia coli growing on glucose under aerobic conditions was presented previously (Ko et al., 1993). The resulting model equations can be used to explain phenomena often observed with industrial fermentations, i.e., increased acetate production which follows from high glucose uptake rate, a low dissolved oxygen concentration, a high specific growth rate, or a combination of these conditions. However, several questions still need to be addressed. First, cell composition is growth rate and media dependent. Second, the macromolecular composition varied between E. coli strains. And finally, a model that represents the carbon fluxes between the Embden-Meyerhof-Parnas (EMP) and the hexose monophosphate (HMP) pathways when cells are subject to internal and/or external stresses is still not well defined. In the present work, we have made an effort to account for these effects, and the resulting model equations show good agreement for wild-type and recombinant E. coli experimental data for the acetate concentration, the onset of acetate secretion, and cell yield based on glucose. These results are useful for optimizing aerobic E. coli fermentation processes. More specifically, we have determined the EMP pathway carbon flux profiles required by the integrated metabolic model for an accurate fit of the acetic acid profile data from a wild-type E. coli strain ML308. These EMP carbon flux profiles were correlated with a dimensionless measurement of biomass and then used to predict the acetic acid profiles for E. coli strain F-122 expressing human immunodeficiency virus-(HIV(528)) beta-galactosidase fusion protein. The effect of different macromolecular compositions and growth rates between these two E. coli strains required a constant scaling factor for improved quantitative predictions.     

Analyzing the effect of decreasing cytosolic triosephosphate isomerase on Solanum tuberosum hairy root cells using a kinetic–metabolic model

A kinetic–metabolic model of Solanum tuberosum hairy roots is presented in the interest of understanding the effect on the plant cell metabolism of a 90% decrease in cytosolic triosephosphate isomerase (cTPI, EC 5.3.1.1) expression by antisense RNA. The model considers major metabolic pathways including glycolysis, pentose phosphate pathway, and TCA cycle, as well as anabolic reactions leading to lipids, nucleic acids, amino acids, and structural hexoses synthesis. Measurements were taken from shake flask cultures for six extracellular nutrients (sucrose, fructose, glucose, ammonia, nitrate, and inorganic phosphate) and 15 intracellular compounds including sugar phosphates (G6P, F6P, R5P, E4P) and organic acids (PYR, aKG, SUCC, FUM, MAL) and the six nutrients. From model simulations and experimental data it can be noted that plant cell metabolism redistributes metabolic fluxes to compensate for the cTPI decrease, leading to modifications in metabolites levels. Antisense roots showed increased exchanges between the pentose phosphate pathway and the glycolysis, an increased oxygen uptake and growth rate. Biotechnol. Bioeng. 2013; 110: 924–935. © 2012 Wiley Periodicals, Inc.     

Kinetic model for bifunctional multisubstrate enzymes. steady-state approximation

The steady-state approximation of the generalized model of a bifunctional multisubstrate enzyme is considered. Cases when the reactions catalyzed by the bifunctional enzyme are independent of one another and when one reaction influences the other are considered. Shunting of the kinetic mechanisms and activation of one reaction by the second reaction catalyzed by the bifunctional enzyme are analyzed. The kinetic equations are derived and qualitatively analyzed. It is shown in all cases discussed that the functional relationships between the kinetic parameters observed and the concentrations of the substrates participating in the reactions can be unambiguously defined on the basis of the concept of relationship of the intermediate enzyme forms in the enzymatic process.     

A mathematical model of N-linked glycoform biosynthesis

Metabolic engineering of N-linked oligosaccharide biosynthesis to produce novel glycoforms or glycoform distributions of a recombinant glycoprotein can potentially lead to an improved therapeutic performance of the glycoprotein product. Effective engineering of this pathway to maximize the fractions of beneficial glycoforms within the glycoform population of a target glycoprotein can be aided by a mathematical model of the N-linked glycosylation process. A mathematical model is presented here, whose main function is to calculate the expected qualitative trends in the N-linked oligosaccharide distribution resulting from changes in the levels of one or more enzymes involved in the network of enzyme-catalyzed reactions that accomplish N-linked oligosaccharide biosynthesis. It consists of mass balances for 33 different oligosaccharide species N-linked to a specified protein that is being transported through the different compartments of the Golgi complex. Values of the model parameters describing Chinese hamster ovary (CHO) cells were estimated from literature information. A basal set of kinetic parameters for the enzyme-catalyzed reactions acting on free oligosaccharide substrates was also obtained from the literature. The solution of the system for this basal set of parameters gave a glycoform distribution consisting mainly of complex-galactosylated oligosaccharides distributed in structures with different numbers of antennae in a fashion similar to that observed for various recombinant proteins produced in CHO cells. Other simulations indicate that changes in the oligosaccharide distribution could easily result from alteration in glycoprotein productivity within the range currently attainable in industry. The overexpression of N-acetylglucosaminyltransferase III in CHO cells was simulated under different conditions to test the main function of the model. These simulations allow a comparison of different strategies, such as simultaneous overexpression of several enzymes or spatial relocation of enzymes, when trying to optimize a particular glycoform distribution. (c) 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 55:890-908, 1997.     

Hydrogen donor-acceptor fluctuations from kinetic isotope effects: a phenomenological model

Kinetic isotope effects (KIEs) and their temperature dependence can probe the structural and dynamic nature of enzyme-catalyzed proton or hydride transfers. The molecular interpretation of their temperature dependence requires expensive and specialized quantum mechanics/molecular mechanics (QM/MM) calculations to provide a quantitative molecular understanding. Currently available phenomenological models use a nonadiabatic assumption that is not appropriate for most hydride and proton-transfer reactions, while others require more parameters than the experimental data justify. Here we propose a phenomenological interpretation of KIEs based on a simple method to quantitatively link the size and temperature dependence of KIEs to a conformational distribution of the catalyzed reaction. This model assumes adiabatic hydrogen tunneling, and by fitting experimental KIE data, the model yields a population distribution for fluctuations of the distance between donor and acceptor atoms. Fits to data from a variety of proton and hydride transfers catalyzed by enzymes and their mutants, as well as nonenzymatic reactions, reveal that steeply temperature-dependent KIEs indicate the presence of at least two distinct conformational populations, each with different kinetic behaviors. We present the results of these calculations for several published cases and discuss how the predictions of the calculations might be experimentally tested. This analysis does not replace molecular QM/MM investigations, but it provides a fast and accessible way to quantitatively interpret KIEs in the context of a Marcus-like model.     

The analysis of cell division and cell wall synthesis genes reveals mutationally inactivated ftsQ and mraY in a protoplast-type L-form of Escherichia coli

Cell division and cell wall synthesis are tightly linked cellular processes for bacterial growth. A protoplast-type L-form Escherichia coli, strain LW1655F+, indicated that bacteria can divide without assembling a cell wall. However, the molecular basis of its phenotype remained unknown. To establish a first phenotype-genotype correlation, we analyzed its dcw locus, and other genes involved in division of E. coli. The analysis revealed defective ftsQ and mraY genes, truncated by a nonsense and a frame-shift mutation, respectively. Missense mutations were determined in the ftsA and ftsW products yielding amino-acid replacements at conserved positions. FtsQ and MraY, obviously nonfunctional in the L-form, are essential for cell division and cell wall synthesis, respectively, in all bacteria with a peptidoglycan-based cell wall. LW1655F+ is able to survive their loss-of-functions. This points to compensatory mechanisms for cell division in the absence of murein sacculus formation. Hence, this L-form represents an interesting model to investigate the plasticity of cell division in E. coli, and to demonstrate how concepts fundamental for bacterial life can be bypassed.     

Comprehensive analysis of the effects of Escherichia coli ORFs on protein translation reaction

Protein synthesis is one of the most important reactions in the cell. Recent experimental studies indicated that this complex reaction can be achieved with a minimum complement of 36 proteins and ribosomes by reconstituting an Escherichia coli-based in vitro translation system with these protein components highly purified on an individual basis. From the protein-protein interaction (PPI) network of E. coli proteins, these minimal protein components are known to interact physically with large numbers of proteins. However, it is unclear what fraction of E. coli proteins are linked functionally with the minimal protein synthesis system. We investigated the effects of each of the 4194 E. coli ORF products on the minimal protein synthesis system; at least 12% of the entire ORF products, a significant fraction of the gene product of E. coli, affect the activity of this system. Furthermore 34% of these functional modifiers present in the PPI network were shown by mapping to be directly linked (i.e. to interact physically) with the minimal components of the PPI network. Topological analysis of the relationships between modifiers and the minimal components in the PPI network indicated clustering of the minimal components. The modifiers showed no such clustering, indicating that the location of functional modifiers is spread across the PPI network rather than clustering close to the minimal protein components. These observations may reflect the evolutionary process of the protein synthesis system.     

Survival of a Shiga toxin-encoding bacteriophage in a compost model

Bacteriophages that carry the Shiga toxin gene (stx) represent an additional hazard in cattle manure-based fertilizers in that their survival could lead to toxigenic conversion of Escherichia coli and other bacteria post-composting. A Stx-phage in which the Shiga toxin (stx(2)) gene was inactivated by insertion of a chloramphenicol resistance gene was used in combination with a rifampicin-resistant E. coli host where RecA is constitutively activated so that all infectious phage particles could be enumerated by plaque assay. PCR-based confirmation methods and the additional application of a host enrichment protocol ensured that very low numbers of surviving bacteriophage could be detected and unequivocally identified. Stx-bacteriophage numbers declined rapidly over the first 48 h and none could be detected after 3 days. The host enrichment method was applied after 6 days and no bacteriophages were recovered. While addition of fresh E. coli cells at intervals after the compost temperature had reduced below 40 degrees C demonstrated that E. coli growth could be supported in the compost, Stx-phages or their lysogens were never detected. Here, we demonstrate that composting animal manure for 40 days during which a temperature of >60 degrees C is maintained for at least 5 days is effective at removing both E. coli and a model infectious Stx-encoding bacteriophage.     

Deuterium isotope effect on enantioselectivity in the Comamonas testosteroni quinohemoprotein alcohol dehydrogenase-catalyzed kinetic resolution of rac-2,2-dimethyl-4-hydroxymethyl-1,3-dioxolane,solketal

Isotopic substitution provides an effective tool to probe the mechanism of enzyme-catalyzed reactions. To our knowledge, kinetic isotope effects on the enantioselectivity of enzymes have not been reported. We investigated the effect of deuterium substitution on the enantiomeric ratio, E, of PQQ-containing quinohemoprotein alcohol dehydrogenase, QH-ADH, from Comamonas testosteroni in the ferricyanide-coupled kinetic resolution of rac-2,2-dimethyl-4-hydroxymethyl-1,3-dioxolane, solketal. Under otherwise identical conditions, we measured E=30 for solketal and E=6 for rac-2,2-dimethyl-4-[1,1-2H]hydroxymethyl-1,3-[5,5,4-2H]dioxolane, d(5)-solketal. It is proposed that isotopic substitution affects the relative kinetic weights of the initial hydron/deuteron transfer from substrate to cofactor and the subsequent proton/deuteron shift in the cofactor-product complex. The latter step becomes more important in the deuterated complex to the extent that the enantiomer discrimination in the first step is partially overruled.     

An automated microscale platform for evaluation and optimization of oxidative bioconversion processes

In this work an integrated robotic platform has been used for the development of a fully automated microscale process sequence comprising fermentation and bioconversion using E. coli TOP10 [pQR210] expressing cyclohexanone monooxygenase (CHMO). Ninety six-Deep Square Well (96-DSW) microtiter plates were used for microbial culture and enzyme-catalyzed conversion, where plate preparation, reagent addition, and sampling were all carried out without manual intervention. The adoption of automated robotic procedures has enabled the rapid collection of kinetic data for whole process optimization at the microscale. This high-throughput approach enabled a range of amino acid sources for media formulation and well fill volumes to be investigated highlighting when nutritional limitation and oxygen limitations took place. The automated process sequence has been applied to test six CHMO substrates including norcamphor and cycloheptanone all of which to the best of our knowledge have yet to be tested with E. coli TOP10 [pQR210]. Substrate specificity and product selectivity were effectively demonstrated and compared to both the natural substrate cyclohexanone and the model substrate bicyclo[3.2.0]hept-2-en-6-one used to demonstrate asymmetric synthesis. The results obtained using the developed process sequence could be reproduced at 75 L scale when a matched oxygen transfer coefficient k(L) a approach was used. The study demonstrates how automated microscale processing enables the rapid collection of kinetic quantitative data in a robust manner with clear implications for accelerating bioprocess development, optimization, and scale-up.     

Cloning of genes for bacterial glycosyltransferases. II. Selection of a hybrid plasmid carrying the rfah gene.

A hybrid ColE1 plasmid containing DNA from Escherichia coli K12 were identified which was capable of correcting the defect in UDP-galactose:lipopolysaccharide alpha1,3-galactosyltransferase in an rfaH mutant of Salmonella typhimurium. Expression of the gene for this enzyme was also demonstrated in several strains of E. coli by direct assay. The E. coli and S. typhimurium enzymes are similar in catalytic properties and immunologic specificity. The finding of the galactosyltransferase activity in E. coli extracts is surprising since the alpha1,3-galactosylglucose disaccharide which is the product of the enzyme-catalyzed reaction does not appear to be present in the E. coli lipopolysaccharide.