Evaluation of Full-Resolution J-Resolved 1H NMR Projections of Biofluids for Metabonomics Information Retrieval and Biomarker Identification

• Published in: Analytical chemistry (Washington) 2010-03, Vol.82 (5), p.1811-1821
• Main Authors: Fonville, Judith M, Maher, Anthony D, Coen, Muireann, Holmes, Elaine, Lindon, John C, Nicholson, Jeremy K
• Format: Article
• Language: English
• Subjects: Analytical chemistry; Animals; Biomarkers - analysis; Body Fluids - chemistry; Chemistry; Exact sciences and technology; Metabolomics; Nuclear Magnetic Resonance, Biomolecular - methods; Rats; Spectrometric and optical methods
• ISSN: 0003-2700; 1520-6882
• DOI: 10.1021/ac902443k

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 1H 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 1H 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.