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MagMet: A fully automated web server for targeted nuclear magnetic resonance metabolomics of plasma and serum.
Rout, Manoj; Lipfert, Matthias; Lee, Brian L; Berjanskii, Mark; Assempour, Nazanin; Fresno, Rosa Vazquez; Cayuela, Arnau Serra; Dong, Ying; Johnson, Mathew; Shahin, Honeya; Gautam, Vasuk; Sajed, Tanvir; Oler, Eponine; Peters, Harrison; Mandal, Rupasri; Wishart, David S.
Afiliación
  • Rout M; Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
  • Lipfert M; Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
  • Lee BL; Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
  • Berjanskii M; Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
  • Assempour N; Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
  • Fresno RV; Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
  • Cayuela AS; Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
  • Dong Y; Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
  • Johnson M; Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
  • Shahin H; Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
  • Gautam V; Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
  • Sajed T; Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
  • Oler E; Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
  • Peters H; Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
  • Mandal R; Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
  • Wishart DS; Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
Magn Reson Chem ; 61(12): 681-704, 2023 12.
Article en En | MEDLINE | ID: mdl-37265034
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.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Imagen por Resonancia Magnética / Metabolómica Límite: Humans Idioma: En Revista: Magn Reson Chem Asunto de la revista: QUIMICA Año: 2023 Tipo del documento: Article País de afiliación: Canadá

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Imagen por Resonancia Magnética / Metabolómica Límite: Humans Idioma: En Revista: Magn Reson Chem Asunto de la revista: QUIMICA Año: 2023 Tipo del documento: Article País de afiliación: Canadá