Glucose conversion by multiple pathways in brain extract: theoretical and experimental analysis

Experimental and model studies were performed to characterize the flux of glucose metabolism and the sharing of glucose-6-phosphate (Glu6P) by the upper parts of glycolytic and pentosephosphate pathways in the brain extract. A mathematical model based upon the kinetic equations of the individual enzymes was evaluated to fit the experimental data. Glucose is converted to glucose-6-phosphate by hexokinase that controls almost exclusively the glucose metabolism. Experiments showed that this crossroad-metabolite was shared between glycolysis and pentosephosphate pathway in the brain extract in a ratio of 1.5:1. This ratio was favorable to the pentosephosphate pathway by the addition of high excess of exogenous glucose-6-phosphate dehydrogenase, standardly used for the activity assay of hexokinase, but still a significant part (17+/-3%) of the common intermediate was converted into the direction of glycolysis. Stimulation of glucose-6-phosphate formation via moderate (30-50%) increase of hexokinase activity by adding exogenous hexokinase or tubulin resulted in the slight increase of the relative flux into direction of glycolysis. The model correctly described all of these observations. However, when the activity of hexokinase was doubled with exogenous enzyme, significantly less glucose-6-phosphate was converted into direction of glycolysis than predicted. This discrepancy shows that the system did not behave in this case as an ideal one, which could be due to the formation of distinct pools for the intermediate.     

Metabolic Analysis of Wild-type Escherichia coli and a Pyruvate Dehydrogenase Complex (PDHC)-deficient Derivative Reveals the Role of PDHC in the Fermentative Metabolism of Glucose

Pyruvate is located at a metabolic junction of assimilatory and dissimilatory pathways and represents a switch point between respiratory and fermentative metabolism. In Escherichia coli, the pyruvate dehydrogenase complex (PDHC) and pyruvate formate-lyase are considered the primary routes of pyruvate conversion to acetyl-CoA for aerobic respiration and anaerobic fermentation, respectively. During glucose fermentation, the in vivo activity of PDHC has been reported as either very low or undetectable, and the role of this enzyme remains unknown. In this study, a comprehensive characterization of wild-type E. coli MG1655 and a PDHC-deficient derivative (Pdh) led to the identification of the role of PDHC in the anaerobic fermentation of glucose. The metabolism of these strains was investigated by using a mixture of ¹³C-labeled and -unlabeled glucose followed by the analysis of the labeling pattern in protein-bound amino acids via two-dimensional ¹³C,¹H NMR spectroscopy. Metabolite balancing, biosynthetic ¹³C labeling of proteinogenic amino acids, and isotopomer balancing all indicated a large increase in the flux of the oxidative branch of the pentose phosphate pathway (ox-PPP) in response to the PDHC deficiency. Because both ox-PPP and PDHC generate CO₂ and the calculated CO₂ evolution rate was significantly reduced in Pdh, it was hypothesized that the role of PDHC is to provide CO₂ for cell growth. The similarly negative impact of either PDHC or ox-PPP deficiencies, and an even more pronounced impairment of cell growth in a strain lacking both ox-PPP and PDHC, provided further support for this hypothesis. The three strains exhibited similar phenotypes in the presence of an external source of CO₂, thus confirming the role of PDHC. Activation of formate hydrogen-lyase (which converts formate to CO₂ and H₂) rendered the PDHC deficiency silent, but its negative impact reappeared in a strain lacking both PDHC and formate hydrogen-lyase. A stoichiometric analysis of CO₂ generation via PDHC and ox-PPP revealed that the PDHC route is more carbon- and energy-efficient, in agreement with its beneficial role in cell growth.     

Metabolic isotopomer labeling systems. Part II: structural flux identifiability analysis

Metabolic flux analysis using carbon labeling experiments (CLEs) is an important tool in metabolic engineering where the intracellular fluxes have to be computed from the measured extracellular fluxes and the partially measured distribution of 13C labeling within the intracellular metabolite pools. The relation between unknown fluxes and measurements is described by an isotopomer labeling system (ILS) (see Part I [Math. Biosci. 169 (2001) 173]). Part II deals with the structural flux identifiability of measured ILSs in the steady state. The central question is whether the measured data contains sufficient information to determine the unknown intracellular fluxes. This question has to be decided a priori, i.e. before the CLE is carried out. In structural identifiability analysis the measurements are assumed to be noise-free. A general theory of structural flux identifiability for measured ILSs is presented and several algorithms are developed to solve the identifiability problem. In the particular case of maximal measurement information, a symbolical algorithm is presented that decides the identifiability question by means of linear methods. Several upper bounds of the number of identifiable fluxes are derived, and the influence of the chosen inputs is evaluated. By introducing integer arithmetic this algorithm can even be applied to large networks. For the general case of arbitrary measurement information, identifiability is decided by a local criterion. A new algorithm based on integer arithmetic enables an a priori local identifiability analysis to be performed for networks of arbitrary size. All algorithms have been implemented and flux identifiability is investigated for the network of the central metabolic pathways of a microorganism. Moreover, several small examples are worked out to illustrate the influence of input metabolite labeling and the paradox of information loss due to network simplification.     

Isotopomer enrichment assay for very short chain fatty acids and its metabolic applications

The present work illustrated an accurate GC/MS measurement for the low isotopomer enrichment assay of formic acid, acetic acid, propionic aicd, butyric acid, and pentanoic acid. The pentafluorobenzyl bromide derivatives of these very short chain fatty acids have high sensitivity of isotopoic enrichment due to their low natural isotopomer distribution in negative chemical ionization mass spectrometric mode. Pentafluorobenzyl bromide derivatization reaction was optimized in terms of pH, temperature, reaction time, and the amount of pentafluorobenzyl bromide versus sample. The precision, stability, and accuracy of this method for the isotopomer analysis were validated. This method was applied to measure the enrichments of formic acid, acetic acid, and propionic acid in the perfusate from rat liver exposed to Krebs–Ringer bicarbonate buffer only, 0–1 mM [3,4-¹³C₂]-4-hydroxynonanoate, and 0–2 mM [5,6,7-¹³C₃]heptanoate. The enrichments of acetic acid and propionic acid in the perfusate are comparable to the labeling pattern of acetyl-CoA and propionyl-CoA in the rat liver tissues. The enrichment of the acetic acid assay is much more sensitive and precise than the enrichment of acetyl-CoA by LC-MS/MS. The reversibility of propionyl-CoA from succinyl-CoA was confirmed by the low labeling of M1 and M2 of propionic acid from [5,6,7-¹³C₃]heptanoate perfusates.     

Metabolomics, pathway regulation, and pathway discovery

Metabolomics is a data-based research strategy, the aims of which are to identify biomarker pictures of metabolic systems and metabolic perturbations and to formulate hypotheses to be tested. It involves the assay by mass spectrometry or NMR of many metabolites present in the biological system investigated. In this minireview, we outline studies in which metabolomics led to useful biomarkers of metabolic processes. We also illustrate how the discovery potential of metabolomics is enhanced by associating it with stable isotopic techniques.     

Lethality and synthetic lethality in the genome-wide metabolic network of Escherichia coli

Recent genomic analyses on the cellular metabolic network show that reaction flux across enzymes are diverse and exhibit power-law behavior in its distribution. While intuition might suggest that the reactions with larger fluxes are more likely to be lethal under the blockade of its catalysing gene products or gene knockouts, we find, by in silico flux analysis, that the lethality rarely has correlations with the flux level owing to the widespread backup pathways innate in the genome-wide metabolism of Escherichia coli. Lethal reactions, of which the deletion generates cascading failure of following reactions up to the biomass reaction, are identified in terms of the Boolean network scheme as well as the flux balance analysis. The avalanche size of a reaction, defined as the number of subsequently blocked reactions after its removal, turns out to be a useful measure of lethality. As a means to elucidate phenotypic robustness to a single deletion, we investigate synthetic lethality in reaction level, where simultaneous deletion of a pair of nonlethal reactions leads to the failure of the biomass reaction. Synthetic lethals identified via flux balance and Boolean scheme are consistently shown to act in parallel pathways, working in such a way that the backup machinery is compromised.     

整合转录组学数据的代谢网络研究进展

高通量测序技术的快速发展催生了涵盖各层次细胞生命活动的组学数据,如转录组学数据、蛋白质组学数据和互作组学数据等。同时,全基因组代谢网络模型在不断完善和增多。整合组学数据,对生物细胞的代谢网络进行更深入的模拟分析成为目前微生物系统生物学研究的热点。目前整合转录组学数据进行全基因组代谢网络分析的方法主要以流量平衡分析(FBA)为基础,通过辨识不同条件下基因表达的变化,进而优化目标函数以得到相应的流量分布或代谢模型。本文对整合转录组学数据的FBA分析方法进行总结和比较,并详细阐述了不同方法的优缺点,为分析特定问题选择合适的方法提供参考。     

Reaction of vascular adhesion protein-1 (VAP-1) with primary amines: mechanistic insights from isotope effects and quantitative structure-activity relationships

Human vascular adhesion protein-1 (VAP-1) is an endothelial copper-dependent amine oxidase involved in the recruitment and extravasation of leukocytes at sites of inflammation. VAP-1 is an important therapeutic target for several pathological conditions. We expressed soluble VAP-1 in HEK293 EBNA1 cells at levels suitable for detailed mechanistic studies with model substrates. Using the model substrate benzylamine, we analyzed the steady-state kinetic parameters of VAP-1 as a function of solution pH. We found two macroscopic pK(a) values that defined a bell-shaped plot of turnover number k(cat,app) as a function of pH, representing ionizable groups in the enzyme-substrate complex. The dependence of (k(cat)/K(m))(app) on pH revealed a single pK(a) value (～9) that we assigned to ionization of the amine group in free benzylamine substrate. A kinetic isotope effect (KIE) of 6 to 7.6 on (k(cat)/K(m))(app) over the pH range of 6 to 10 was observed with d(2)-benzylamine. Over the same pH range, the KIE on k(cat) was found to be close to unity. The unusual KIE values on (k(cat)/K(m))(app) were rationalized using a mechanistic scheme that includes the possibility of multiple isotopically sensitive steps. We also report the analysis of quantitative structure-activity relationships (QSAR) using para-substituted protiated and deuterated phenylethylamines. With phenylethylamines we observed a large KIE on k(cat,app) (8.01 ± 0.28 with phenylethylamine), indicating that C-H bond breakage is limiting for 2,4,5-trihydroxyphenylalanine quinone reduction. Poor correlations were observed between steady-state rate constants and QSAR parameters. We show the importance of combining KIE, QSAR, and structural studies to gain insight into the complexity of the VAP-1 steady-state mechanism.     

Ensemble modeling for strain development of l-lysine-producing Escherichia coli

One of the main strategies to improve the production of relevant metabolites has been the manipulation of single or multiple key genes in the metabolic pathways. This kind of strategy requires several rounds of experiments to identify enzymes that impact either yield or productivity. The use of mathematical tools to facilitate this process is desirable. In this work, we apply the Ensemble Modeling (EM) framework, which uses phenotypic data (effects of enzyme overexpression or genetic knockouts on the steady-state production rate) to screen for potential models capable of describe existing data and thus gaining insight to improve strains for l-lysine production. Described herein is a strategy to generate a set of kinetic models that describe a set of enzyme overexpression phenotypes previously determined in an Escherichia coli strain that produces increased levels of l-lysine in an industrial laboratory. This final ensemble of models captures the kinetic characteristics of the cell through screening of phenotypes after sequential overexpression of enzymes. Furthermore, these models demonstrate some predictive capability, as starting from the reference producing strain (overexpressing desensitized dihydrodipicolinate synthetase (dapA*)) this set of models is able to predict that the desensitization of aspartate kinase (lysC*) is the next rate-controlling step in the l-lysine pathway. Moreover, this set of models allows for the generation of further targets for testing, for example, phosphoenolpyruvate (Ppc), aspartate aminotransferase (AspC), and glutamate dehydrogenase (GdhA). This work demonstrates the usefulness, applicability, and scope that the Ensemble Modeling framework offers to build production strains.     

Regulatory effects on central carbon metabolism from poly-3-hydroxybutryate synthesis

Poly-3-hydroxybutyrate (PHB) synthesis in Escherichia coli elicits regulatory responses that affect product yield and productivity. We used controlled, steady-state cultures (chemostats) of a genetically stable strain to determine growth-independent metabolic flux regulation. We measured flux and steady-state intracellular metabolite concentrations across different dilution rates (0.05, 0.15, 0.3 h⁻¹), limitations (glucose, gluconate and nitrogen), and operon copy counts of the PHB pathway (0, 6, 17, and 29). As PHB flux increases, specific substrate consumption and lactate secretion increase while formate and acetate secretion decreases in N-limited, glucose-fed conditions.To understand the regulatory mechanisms that resulted in these macroscopic changes, we used a flux balance analysis model to analyze intracellular redox conditions. Our model shows that under N-limited conditions, synthesis of PHB creates excess reducing equivalents. Cells, under these conditions, secrete more reduced metabolites in order to recycle reducing equivalents. By switching to a more oxidized substrate (gluconate) that decreased excess reducing equivalents, PHB flux yield increased 1.6 fold compared to glucose-fed fermentations. High flux of PHB (~1.2 mmol/g DCW h) was maintained under these steady-state, oxidized conditions. These results imply redox imbalance is a driving force in industrial production of PHB, and substrates that are more oxidized than glucose can increase productivity.     

“新工科”背景下“代谢工程”课程建设的思考

“代谢工程”是生物工程专业本科生与研究生的专业核心课程,无论是应对新兴产业的“智能制造”,还是针对传统发酵工业的升级改造,都能体现其“新工科”的特点.“代谢工程”更注重于培养学生综合运用专业知识来解决实践问题的能力,即合理进行代谢途径与调控网络的设计,实现目的产物的“生物智造”.基于“代谢工程”综合性、时效性、应用性都...