Use of semiselective TOCSY and the pearson correlation for the metabonomic analysis of biofluid mixtures: application to urine.
The authors recently proposed an approach to the metabonomic analysis of biofluid mixtures based on the use of the selective TOCSY experiment (Sandusky, P.; Raftery, D. Anal. Chem. 2005, 77, 2455). This method has some significant advantages over standard metabonomic analysis. However, when analyzing overlapped components, the selective TOCSY method can suffer from the relatively high likelihood of simultaneous excitation of several spin systems at once. This multiple excitation can cause problems both with the purity of the individual TOCSY peaks observed and with their assignment into specific spin systems. To address this problem, the possibility of using a more selective excitation is initially explored. Unfortunately, in most cases, greater spin system selectivity can only be gained at the expense of sensitivity. This is obviously an unacceptable tradeoff when dealing with biofluid samples. However, the application of the Pearson product moment correlation to the TOCSY peak integral intensities provides a test for individual TOCSY peak purity and allows for the assignment of the peaks into spin systems. The specific application of this two-stage "semiselective" TOCSY method to rat and human urine is presented. Significantly, it is also demonstrated that the use of semiselective TOCSY spectra as data inputs for PCA calculations provides a more sensitive and reliable method of distinguishing small differences in biofluid composition than the standard metabonomic approach using complete 1D proton NMR spectra of urine samples.
Sandusky
Peter
P
Department of Chemistry, Purdue University, West Lafayette, Indiana 47907, USA.
Raftery
Daniel
D
D000596:Amino Acids / Q000737:chemistry / Q000652:urine; D000818:Animals; D006801:Humans; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D051381:Rats; D012680:Sensitivity and Specificity; D014556:Urine / Q000737:chemistry*
D000596:Amino Acids