Isodyn

Isodyn models and analyzes the dynamics of metabolites and 13C isotopomer distributions in central metabolic networks to support kinetic 13C-assisted fluxomic analysis.

Key Features:

• Kinetic modeling: Uses ordinary differential equation (ODE)–based kinetic models to simulate dynamic isotopomer concentrations and metabolic fluxes.
• Mass spectrometry data processing: Extracts metabolite spectra from raw MS data and corrects mass isotopomer distributions for natural isotope abundance.
• Isotopomer-product distribution algorithms: Implements methods for determining isotopomer-to-product distributions for isotopomer simulation and comparison to experimental data.
• ODE solving and performance optimization: Solves large systems of differential equations with algorithmic optimizations, including assembly-level enhancements to reduce computation time.
• Statistical parameter estimation: Applies simulated annealing for global parameter search and uses Monte Carlo simulations and covariance matrix evaluations for uncertainty analysis.
• Integration with complementary tools: Complements and interoperates conceptually with Ramid, Midcor, and Isoform by operating on corrected isotopomer data for flux evaluation.
• Implementation: Provided as a C++ standalone implementation and as a version linked to Mathematica for computational flexibility.

Scientific Applications:

• Stable isotope-resolved metabolomics (SIRM): Maps biochemical reaction rates by analyzing isotopomer distributions from 13C-labeled substrates.
• Glycolysis and pentose phosphate pathway analysis: Quantifies fluxes and isotopomer redistributions within glycolysis and the pentose phosphate cycle.
• Enzyme-specific isotopomer redistribution studies: Resolves isotopomer effects induced by transketolase and transaldolase activities.
• Flux estimation in complex systems: Supports kinetic- and equilibrium-constrained metabolic flux estimation in complex contexts such as cancer cell metabolism.

Methodology:

Computational methods include ODE-based kinetic isotopomer modeling, extraction and natural-abundance correction of MS-derived spectra, algorithms for isotopomer-product distributions, large-system ODE solvers with assembly-level optimizations, simulated annealing for parameter search, and Monte Carlo plus covariance-matrix analyses for uncertainty assessment.