title: Line-shape analysis of J-resolved NMR spectra: application to metabolomics and quantification of intensity errors from signal processing and high signal congestion.
abstract: NMR spectroscopy remains one of the primary analytical approaches in metabolomics. Although 1D (1)H NMR spectroscopy is versatile, highly reproducible and currently the most widely used technique in NMR metabolomics, analysis of complex biological samples typically yields highly congested spectra with severely overlapping signals making unambiguous metabolite identification and quantification almost impossible. Consequently there is a growing use of 2D NMR methods, in particular (1)H J-resolved (JRES) spectroscopy, which spreads the high signal density into a second dimension. One potentially powerful method to deconvolute these JRES spectra, facilitating metabolite quantification, is via line-shape fitting. However, the mathematical functions describing the JRES NMR line-shape, in particular after applying apodisation functions and JRES specific processing, including tilting and symmetrisation, remain uncharacterised. Furthermore, possible quantitation errors arising from processing JRES spectra have not been evaluated, nor have the potentially adverse quantitative effects of overlapping dispersive tails of closely spaced signals in the 2D spectrum. Here we address these issues and evaluate the suitability of the JRES experiment for accurate complex mixture analysis. Specifically, we have examined changes in NMR line-shape and signal intensity after application of different apodisation functions (SINE and SEM) and JRES specific processing (tilting and symmetrising), comparing simulated and experimental data. We also report a significant quantitation error of up to 33%, dependent upon apodisation, due to overlap of the dispersive tails of closely spaced resonances. Finally, we have validated the use of these mathematical line-shape functions for metabolite quantitation of 2D JRES spectra, by comparison to corresponding 1D NMR datasets, using both gravimetrically-prepared chemically defined mixtures as well as biological tissue extracts.
authors.affiliation: Centre for Systems Biology, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
authors.forename: Helen M
authors.initials: HM
authors.lastname: Parsons
authors.forename: Christian
authors.initials: C
authors.lastname: Ludwig
authors.forename: Mark R
authors.initials: MR
authors.lastname: Viant
mesh_terms: D000465:Algorithms; D000818:Animals; D002478:Cells, Cultured; D019411:Clinical Laboratory Techniques / Q000592:standards*; D003951:Diagnostic Errors; D006801:Humans; D009682:Magnetic Resonance Spectroscopy; D055432:Metabolomics