NMR spectroscopy
Definition
NMR spectroscopy (Nuclear Magnetic Resonance spectroscopy) is an analytical technique used in metabolomics to identify and quantify metabolites in biological samples by measuring the magnetic properties of atomic nuclei. When placed in a strong magnetic field, certain nuclei absorb and re-emit electromagnetic radiation at specific frequencies, producing characteristic spectra that serve as molecular fingerprints. NMR is particularly valuable for metabolomics because it is non-destructive, requires minimal sample preparation, provides structural information, and can simultaneously detect hundreds of metabolites including amino acids, organic acids, sugars, and lipids. Unlike mass spectrometry, NMR offers excellent reproducibility and quantitative accuracy, making it essential for understanding metabolic phenotypes, biomarker discovery, and systems biology studies.
Visualize NMR spectroscopy in Nodes Bio
Researchers can use Nodes Bio to visualize metabolite correlation networks derived from NMR spectroscopy data, where nodes represent individual metabolites and edges indicate statistical correlations or biochemical relationships. This enables identification of metabolic pathway perturbations, co-regulated metabolite clusters, and biomarker signatures. Integration with genomic or proteomic data creates multi-omics networks revealing how genetic variations or protein expression changes affect metabolic profiles.
Visualization Ideas:
- Metabolite correlation networks showing co-regulated compounds across experimental conditions
- Metabolic pathway maps with NMR-detected metabolites highlighted by abundance or significance
- Multi-omics integration networks connecting NMR metabolites with genes, proteins, and clinical phenotypes
Example Use Case
A pharmaceutical research team uses NMR spectroscopy to profile plasma metabolites from patients with type 2 diabetes versus healthy controls. They detect significant alterations in branched-chain amino acids, glucose metabolites, and lipid species. By importing their NMR-derived metabolite abundance data into Nodes Bio, they construct a metabolic correlation network that reveals unexpected connections between disrupted amino acid metabolism and inflammatory markers. This network analysis identifies a novel metabolite cluster associated with insulin resistance, providing new therapeutic targets for drug development.