Publication Details
ID: 37MagMet: A fully automated web server for targeted nuclear magnetic resonance metabolomics of plasma and serum.
Authors
Rout M; Lipfert M; Lee BL; Berjanskii M; Assempour N; Fresno RV; Cayuela AS; Dong Y; Johnson M; Shahin H; Gautam V; Sajed T; Oler E; Peters H; Mandal R; Wishart DS
Journal/Conference
Magnetic resonance in chemistry : MRC Vol. 61 (12) , pp. 681-704
Abstract
Nuclear magnetic resonance (NMR) spectral analysis of biofluids can be a time-consuming process, requiring the expertise of a trained operator. With NMR becoming increasingly popular in the field of metabolomics, there is a growing need to change this paradigm and to automate the process. Here we introduce MagMet, an online web server, that automates the processing and quantification of 1D (1) H NMR spectra from biofluids-specifically, human serum/plasma metabolites, including those associated with inborn errors of metabolism (IEM). MagMet uses a highly efficient data processing procedure that performs automatic Fourier Transformation, phase correction, baseline optimization, chemical shift referencing, water signal removal, and peak picking/peak alignment. MagMet then uses the peak positions, linewidth information, and J-couplings from its own specially prepared standard metabolite reference spectral NMR library of 85 serum/plasma compounds to identify and quantify compounds from experimentally acquired NMR spectra of serum/plasma. MagMet employs linewidth adjustment for more consistent quantification of metabolites from higher field instruments and incorporates a highly efficient data processing procedure for more rapid and accurate detection and quantification of metabolites. This optimized algorithm allows the MagMet webserver to quickly detect and quantify 58 serum/plasma metabolites in 2.6 min per spectrum (when processing a dataset of 50-100 spectra). MagMet's performance was also assessed using spectra collected from defined mixtures (simulating other biofluids), with >100 previously measured plasma spectra, and from spiked serum/plasma samples simulating known IEMs. In all cases, MagMet performed with precision and accuracy matching the performance of human spectral profiling experts. MagMet is available at http://magmet.ca.
Publication Info
- Year: 2023
- Publication Date: June 2, 2023
- Citations: 20
- Source: Google Scholar
Identifiers
- DOI: 10.1002/mrc.5371
- PubMed ID: 37265034
- ISSN: 1097-458X (Electronic) 0749-1581 (Linking)
- Google Scholar ID: 3vbIHxFL9FgC
PubMed Data
Additional Information
- Publication Type: Journal Article; Research Support, N.I.H., Extramu
- Language: eng
- Last PubMed Update: April 22, 2025