Analysis of progress curves. Rate law of pyruvate kinase type I from <i>Escherichia coli</i>

Markus, Mario; Plesser, Theo; Boiteux, Arnold; Hess, Benno; Malcovati, Massimo

doi:10.1042/bj1890421

Cited by 41 publications

(29 citation statements)

References 20 publications

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“…The equation dependent on ATP, phosphoenolpyruvate and fructose, 1,6-bisphosphate is used to derive the enzymatic kinetic of the E 3 (pyruvatekinase), which is also constructed on the allosteric model of concerted transitions (Markus et al, 1980). For a spatially homogeneous system the time-evolution of α, β and γ , which denote the normalized concentrations of P 1 , P 2 and P 3 , is described by the following three ordinary differential equations:…”

Section: The Modelmentioning

confidence: 99%

Persistent Behavior in a Phase-shift Sequence of Periodical Biochemical Oscillations

Fuente

Martínez

Benítez

et al. 1998

Bulletin of Mathematical Biology

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We present the analysis of a phase-shift sequence obtained from random transitions between periodic solutions of a biochemical dynamical model, formed by a system of three differential equations and which represent an instability-generating multienzymatic mechanism. The phase-shift series was studied in terms of Hurst's rescaled range analysis. We found that the data were characterized by a Hurst exponent H = 0.69, which was clearly indicative of long-term trends. This result had a high significance level, as was confirmed through Monte Carlo simulations in which the data were scrambled in the series, destroying its original ordering. For these series we obtained a Hurst exponent which was consistent with the expectation of H = 0.5 for a random independent process. This clearly showed that, although the

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Section: The Modelmentioning

confidence: 99%

Persistent Behavior in a Phase-shift Sequence of Periodical Biochemical Oscillations

Fuente

Martínez

Benítez

et al. 1998

Bulletin of Mathematical Biology

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“…We used the rate expression reported by Markus et al (1980) and Boiteux et al (1983) and presented in Table 5. We assumed the total Mg concentration, [Mg total ], to be in the range 5-10 mM (Neidhardt et al, 1990), the total adenylate concentration ([AN] ) [ATP] + [ADP] + [AMP]) in the range 3-4 mM (Chapman et al, 1971), and the adenylate kinase equilibrium constant (K eq ) ([ADP] 2 /[ATP][AMP]) in the range 1-1.5.…”

Section: Resultsmentioning

confidence: 99%

Metabolic Consequences of Phosphotransferase (PTS) Mutation in a Phenylalanine-Producing Recombinant Escherichia coli

et al. 1997

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E. coli strain PPA305, which has a wild-type PTS system, and PPA316, which utilizes a proton-galactose symport system for glucose uptake, were used as host strains to harbor a phenylalanine overproduction plasmid pSY130-14 and to study the effects of using different glucose uptake systems on phenylalanine production. The non-PTS strain (PPA316/pSY130-14) produced much less phenylalanine, ranging from 0 to 67% of that produced by the PTS strain (PPA305/pSY130-14) depending on cultivation conditions used. The non-PTS strain PPA316/pSY130-14 had an intracellular PEP concentration only one-sixth that of the PTS strain, PPA305/pSY130-14. Additionally, PPA316/pSY130-14 had a substantially lower energy state in terms of the size of the pool of high-energy phosphate compounds and the magnitude of the pH difference across the cytoplasmic membrane. The non-PTS strain consumed oxygen at a higher rate, attained lower biomass concentration, and produced no acetate and phenylalanine during fermentation, suggesting more carbon was oxidized to CO 2 , most likely through the TCA cycle. Analysis of intracellular fluxes through the central carbon pathways was performed for each strain utilizing exponential phase data on extracellular components and assuming quasi-steady state for intermediate metabolites. The non-PTS strain had a higher flux through pyruvate kinase (PYK) and TCA cycle which, in agreement with the observed higher oxygen uptake rate, suggests that more carbon was oxidized to CO 2 through the TCA cycle. Further analysis using rate expression data for PYK and NMR data for the intracellular metabolites identified the regulatory properties of PYK as the probable cause for lower intracellular PEP levels in PPA316/ pSY130-14.

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“…These enzymatic activity functions were previously modeled and tested experimentally by other different groups [3], [28], [29].…”

Section: Introductionmentioning

confidence: 99%

Quantitative Analysis of the Effective Functional Structure in Yeast Glycolysis

Fuente

Cortes

2012

PLoS ONE

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The understanding of the effective functionality that governs the enzymatic self-organized processes in cellular conditions is a crucial topic in the post-genomic era. In recent studies, Transfer Entropy has been proposed as a rigorous, robust and self-consistent method for the causal quantification of the functional information flow among nonlinear processes. Here, in order to quantify the functional connectivity for the glycolytic enzymes in dissipative conditions we have analyzed different catalytic patterns using the technique of Transfer Entropy. The data were obtained by means of a yeast glycolytic model formed by three delay differential equations where the enzymatic rate equations of the irreversible stages have been explicitly considered. These enzymatic activity functions were previously modeled and tested experimentally by other different groups. The results show the emergence of a new kind of dynamical functional structure, characterized by changing connectivity flows and a metabolic invariant that constrains the activity of the irreversible enzymes. In addition to the classical topological structure characterized by the specific location of enzymes, substrates, products and feedback-regulatory metabolites, an effective functional structure emerges in the modeled glycolytic system, which is dynamical and characterized by notable variations of the functional interactions. The dynamical structure also exhibits a metabolic invariant which constrains the functional attributes of the enzymes. Finally, in accordance with the classical biochemical studies, our numerical analysis reveals in a quantitative manner that the enzyme phosphofructokinase is the key-core of the metabolic system, behaving for all conditions as the main source of the effective causal flows in yeast glycolysis.

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Analysis of progress curves. Rate law of pyruvate kinase type I from Escherichia coli

Cited by 41 publications

References 20 publications

Persistent Behavior in a Phase-shift Sequence of Periodical Biochemical Oscillations

Persistent Behavior in a Phase-shift Sequence of Periodical Biochemical Oscillations

Metabolic Consequences of Phosphotransferase (PTS) Mutation in a Phenylalanine-Producing Recombinant Escherichia coli

Quantitative Analysis of the Effective Functional Structure in Yeast Glycolysis

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