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Motivation: Metabolic flux analysis of biochemical reaction networks using isotope tracers requires software tools that can analyze the dynamics of isotopic isomer (isotopomer) accumulation in metabolites and reveal the underlying kinetic mechanisms of metabolism regulation. Since existing tools are restricted by the isotopic steady state and remain disconnected from the underlying kinetic mechanisms, we have recently developed a novel approach for the analysis of tracer-based metabolomic data that meets these requirements. The present contribution describes the last step of this development: implementation of (i) the algorithms for the determination of the kinetic parameters and respective metabolic fluxes consistent with the experimental data and (ii) statistical analysis of both fluxes and parameters, thereby lending it a practical application., Results: The C++ applications package for dynamic isotopomer distribution data analysis was supplemented by (i) five distinct methods for resolving a large system of differential equations; (ii) the 'simulated annealing' algorithm adopted to estimate the set of parameters and metabolic fluxes, which corresponds to the global minimum of the difference between the computed and measured isotopomer distributions; and (iii) the algorithms for statistical analysis of the estimated parameters and fluxes, which use the covariance matrix evaluation, as well as Monte Carlo simulations. An example of using this tool for the analysis of (13)C distribution in the metabolites of glucose degradation pathways has demonstrated the evaluation of optimal set of parameters and fluxes consistent with the experimental pattern, their range and statistical significance, and also the advantages of using dynamic rather than the usual steady-state method of analysis., Availability: Software is available free from http://www.bq.ub.es/bioqint/selivanov.htm

To determine mechanisms underlying the transgenerational presence of metabolic perturbations in the intrauterine growth-restricted second-generation adult females (F2 IUGR) despite normalizing the in utero metabolic environment, we examined in vivo glucose kinetics and in vitro skeletal muscle postinsulin receptor signaling after embryo transfer of first generation (F1 IUGR) to control maternal environment. Female F2 rats, procreated by F1 pre- and postnatally nutrient- and growth-restricted (IUGR) mothers but embryo transferred to gestate in control mothers, were compared with similarly gestating age- and sex-matched control (CON) F2 progeny. Although there were no differences in birth weight or postnatal growth patterns, the F2 IUGR had increased hepatic weight, fasting hyperglycemia, hyperinsulinemia, and unsuppressed hepatic glucose production, with no change in glucose futile cycling or clearance, compared with F2 CON. These hormonal and metabolic aberrations were associated with increased skeletal muscle total GLUT4 and pAkt concentrations but decreased plasma membrane-associated GLUT4, total pPKCζ, and PKCζ enzyme activity, with no change in total SHP2 and PTP1B concentrations in IUGR F2 compared with F2 CON. We conclude that transgenerational presence of aberrant glucose/insulin metabolism and skeletal muscle insulin signaling of the adult F2 IUGR female offspring is independent of the immediate intrauterine environment, supporting nutritionally induced heritable mechanisms contributing to the epidemic of type 2 diabetes mellitus. [ABSTRACT FROM AUTHOR]

A current trend in neuroscience research is the use of stable isotope tracers in order to address metabolic processes in vivo. The tracers produce a huge number of metabolite forms that differ according to the number and position of labeled isotopes in the carbon skeleton (isotopomers) and such a large variety makes the analysis of isotopomer data highly complex. On the other hand, this multiplicity of forms does provide sufficient information to address cell operation in vivo. By the end of last millennium, a number of tools have been developed for estimation of metabolic flux profile from any possible isotopomer distribution data. However, although well elaborated, these tools were limited to steady state analysis, and the obtained set of fluxes remained disconnected from their biochemical context. In this review we focus on a new numerical analytical approach that integrates kinetic and metabolic flux analysis. The related computational algorithm estimates the dynamic flux based on the time-dependent distribution of all possible isotopomers of metabolic pathway intermediates that are generated from a labeled substrate. The new algorithm connects specific tracer data with enzyme kinetic characteristics, thereby extending the amount of data available for analysis: it uses enzyme kinetic data to estimate the flux profile, and vice versa, for the kinetic analysis it uses in vivo tracer data to reveal the biochemical basis of the estimated metabolic fluxes. [ABSTRACT FROM AUTHOR]