IsoSolve

IsoSolve integrates mass spectrometry (MS) and nuclear magnetic resonance (NMR) isotopic data using symbolic calculus to expand isotopic coverage and consolidate measurements for stable-isotope labeling experiments probing metabolic networks.

Key Features:

• Integrative framework: Integrates heterogeneous isotopic datasets from MS and NMR to produce consolidated isotopic measurements.
• Isotopic coverage enhancement: Enhances isotopic space coverage by increasing the number of quantifiable isotopic species across methods.
• Symbolic calculus linkage: Uses symbolic calculus to link isotopic measurements directly to chemical structures of molecules.
• Stable-isotope labeling focus: Addresses incomplete isotopic space coverage in stable-isotope labeling experiments.
• Multi-method combination: Combines data from various MS and NMR methods to leverage complementary information and reduce redundancy.
• Small metabolite applicability: Targets small metabolites, with demonstrated application to amino acid isotopic analyses.
• Dataset consolidation: Consolidates disparate isotopic datasets to produce unified distributions.
• Experimental design support: Provides analyses that inform experimental design and assessment of methodological complementarity.
• Cross-tracer and cross-platform versatility: Applies across various labeled elements, isotopic tracers, metabolites, and analytical platforms.
• Implementation: Implemented as a Python module.

Scientific Applications:

• Metabolic network probing: Supports investigation of metabolic network topology and functionality using stable-isotope labeling data.
• Isotopic distribution clarification: Clarifies isotopic distributions for small metabolites, including amino acids.
• Method complementarity evaluation: Enables evaluation of complementarity and redundancy between MS and NMR analytical techniques.
• Quantification improvement: Improves quantification of isotopic species by combining measurements from multiple analytical methods.
• Cross-tracer analyses: Facilitates analyses across different labeled elements and isotopic tracers.

Methodology:

Implements symbolic calculus to map isotopic measurements to chemical structures and integrates heterogeneous MS and NMR isotopic datasets; implemented as a Python module.