Evaluation of full-resolution J-resolved 1H NMR projections of biofluids for metabonomics information retrieval and biomarker identification.

TitleEvaluation of full-resolution J-resolved 1H NMR projections of biofluids for metabonomics information retrieval and biomarker identification.
Publication TypeJournal Article
Year of Publication2010
AuthorsFonville JM, Maher AD, Coen M, Holmes E, Lindon JC, Nicholson JK
JournalAnal Chem
Volume82
Issue5
Pagination1811-21
Date Published2010 Mar 1
ISSN1520-6882
KeywordsAnimals, Biological Markers, Body Fluids, Metabolomics, Nuclear Magnetic Resonance, Biomolecular, Rats
Abstract

Spectroscopic profiling of biological samples is an integral part of metabolically driven top-down systems biology and can be used for identifying biomarkers of toxicity and disease. However, optimal biomarker information recovery and resonance assignment still pose significant challenges in NMR-based complex mixture analysis. The reduced signal overlap as achieved when projecting two-dimensional (2D) J-resolved (JRES) NMR spectra can be exploited to mitigate this problem and, here, full-resolution (1)H JRES projections have been evaluated as a tool for metabolic screening and biomarker identification. We show that the recoverable information content in JRES projections is intrinsically different from that in the conventional one-dimensional (1D) and Carr-Purcell-Meiboom-Gill (CPMG) spectra, because of the combined result of reduction of the over-representation of highly split multiplet peaks and relaxation editing. Principal component and correlation analyses of full-resolution JRES spectral data demonstrated that peak alignment is necessary. The application of statistical total correlation spectroscopy (STOCSY) to JRES projections improved the identification of previously overlapped small molecule resonances in JRES (1)H NMR spectra, compared to conventional 1D and CPMG spectra. These approaches are demonstrated using a galactosamine-induced hepatotoxicity study in rats and show that JRES projections have a useful and complementary role to standard one-dimensional experiments in complex mixture analysis for improved biomarker identification.

DOI10.1021/ac902443k
Alternate JournalAnal. Chem.
PubMed ID20131799