Use of optimized 1D TOCSY NMR for improved quantitation and metabolomic analysis of biofluids.

One dimensional selective TOCSY experiments have been shown to be advantageous in providing improved data inputs for principle component analysis (PCA) (Sandusky and Raftery 2005a, b). Better subpopulation cluster resolution in the observed scores plots results from the ability to isolate metabolite signals of interest via the TOCSY based filtering approach. This report reexamines the quantitative aspects of this approach, first by optimizing the 1D TOCSY experiment as it relates to the measurement of biofluid constituent concentrations, and second by comparing the integration of 1D TOCSY read peaks to the bucket integration of 1D proton NMR spectra in terms of precision and accuracy. This comparison indicates that, because of the extensive peak overlap that occurs in the 1D proton NMR spectra of biofluid samples, bucket integrals are often far less accurate as measures of individual constituent concentrations than 1D TOCSY read peaks. Even spectral fitting approaches have proven difficult in the analysis of significantly overlapped spectral regions. Measurements of endogenous taurine made over a sample population of human urine demonstrates that, due to background signals from other constituents, bucket integrals of 1D proton spectra routinely overestimate the taurine concentrations and distort its variation over the sample population. As a result, PCA calculations performed using data matrices incorporating 1D TOCSY determined taurine concentrations produce better scores plot subpopulation cluster resolution.

Biotransformations of (+/-)-geosmin by terpene-degrading bacteria.

Two terpene-degrading bacteria able to transform (+/-)-geosmin have been identified. Pseudomonas sp. SBR3-tpnb, following growth on gamma-terpinene, converts (+/-)-geosmin to several products; the major products are ketogeosmins. Rhodococcus wratislaviensis DLC-cam, isolated on D-camphor, also converts (+/-)-geosmin to several oxidation products, primarily ketogeosmins identical to those produced by strain SBR3-tpnb as well as hydroxygeosmins. This conversion appears to be inducible by (+/-)-geosmin and not by D-camphor.

Biotransformations of 2-methylisoborneol by camphor-degrading bacteria.

Many camphor-degrading bacteria that are able to transform 2-methylisoborneol (2-MIB) have been identified. Three of these strains have been examined in detail. Rhodococcus ruber T1 metabolizes camphor through 6-hydroxycamphor but converts 2-MIB to 3-hydroxy-2-MIB. Pseudomonas putida G1, which metabolizes camphor through 5-hydroxycamphor, converts MIB primarily to 6-hydroxy-2-MIB. Rhodococcus wratislaviensis DLC-cam converts 2-MIB through 5-hydroxy-2-MIB to 5-keto-2-MIB. Together, these three strains produce metabolites resulting from hydroxylation at all of the three available secondary carbons on the six-member ring of 2-MIB.

Limitations in the deduction of carbon NMR spectra from the f1 dimension of standard 2D heteronuclear experiments when applied to natural products.

The structure elucidation of a natural product requires a set of NMR spectra that includes both carbon observe experiments, such as 1D carbon and DEPT, and proton observe experiments, such as HSQC, HMBC, and COSY. Because NMR probes are optimized for either proton or carbon observe experiments, but not both, this often results in some experiments being acquired at a very suboptimal level of efficiency. An alternative is to deduce the carbon spectrum from the indirect, or f 1, dimension of the heteronuclear 2D experiments. This approach is sometimes being employed for the structure elucidation of newly isolated natural products in cases where the amount of material available precludes carbon observe experiments. However whether this approach is reliable in every case has not yet been established. This study applies the "indirect dimension" approach to a representative set of known natural products. The results are mixed. Analysis of E-HSQC spectra, in conjunction with COSY spectra, reliably defines the carbon spectra of the methyl, methylene, and methine carbons present. However, due to limits in resolution in the f 1 dimension of standard HMBC experiments, the presence and chemical shift positions of some quaternary carbons are fairly frequently obscured by those of other carbons. Thus it is often necessary to acquire a 1D carbon NMR spectrum to support the structure elucidation of a natural product.

NMR study of the solution structure of curcumin.

Curcumin [1,7-bis(4-hydroxy-3-methoxyphenyl)-1,6-heptadiene-3,5-dione] is derived from the rhizomes of Curcuma longa. Although early studies concluded that curcumin exists predominantly as a keto-enol tautomer, 1b, in several recent articles the solution structure of curcumin has been represented as a beta-diketone tautomer, 1a. We have investigated the structure of curcumin in solvents ranging in polarity from CDCl3 to mixtures of DMSO-d6 in water, and in buffered aqueous DMSO-d6 solutions with pH values varying from 3 to 9. The solution structure of curcumin was determined on the basis of NMR techniques, including DEPT, HMQC, HMBC, and COSY. The results of the NMR studies show definitely that curcumin exists in solution as keto-enol tautomers, 1b.

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.

Use of selective TOCSY NMR experiments for quantifying minor components in complex mixtures: application to the metabonomics of amino acids in honey.

The application of the traditional methods of multivariate statistics, such as the calculation of principle components, to the analysis of NMR spectra taken on sets of biofluid samples is one of the central approaches in the field of metabonomics. While this approach has proven to be a powerful and widely applicable technique, it has an inherent weakness, in that it tends to be dominated by those chemical species present at relatively higher concentrations. Using a set of commercial honey samples, a comparison of this classical metabonomics approach to one based on the use of the selective TOCSY experiment is presented. While the NMR spectrum of honey and its classical metabonomic analysis is completely dominated by a very few chemical species, specifically alpha-glucose and fructose, the statistical signal carried by minor honey components, such as amino acids, may be accessed using a selective TOCSY-based approach. This approach has the intrinsic virtue that it focuses the statistical analysis on a set of predefined chemical species, which might be chosen for their metabolic significance, and could be composed of either major or minor mixture constituents. Furthermore, the selective TOCSY method allows for more certain chemical identification, acquisition times of approximately 1 min, and accurate quantification of the species contributing to the statistical discriminatory signal.