Hard Modeling Methods for the Curve Resolution of Data from Liquid Chromatography with a Diode Array Detector and On-Flow Liquid Chromatography with Nuclear Magnetic Resonance Spectroscopy

Nuclear magnetic resonance and liquid chromatography-mass spectrometry combined with an incompleted separation strategy for identifying the natural products in crude extract

NMR and LC-MS combined with an incompleted separation strategy were proposed to the simultaneous structure identification of natural products in crude extracts, and a novel method termed as NMR/LC-MS parallel dynamic spectroscopy (NMR/LC-MS PDS) was developed to discover the intrinsic correlation between retention time (Rt), mass/charge (m/z) and chemical shift (delta) data of the same constituent from mixture spectra by the co-analysis of parallelly visualized multispectroscopic datasets from LC-MS and (1)H NMR. The extracted ion chromatogram (XIC) and (1)H NMR signals deriving from the same individual constituent were correlated through fraction ranges and intensity changing profiles in NMR/LC-MS PDS spectrum due to the signal amplitude co-variation resulted from the concentration variation of constituents in a series of incompletely separated fractions. NMR/LC-MS PDS was applied to identify 12 constituents in an active herbal extract including flavonol glycosides, which was separated into a series of fractions by flash column chromatography. The complementary spectral information of the same individual constituent in the crude extract was discovered simultaneously from mixture spectra. Especially, two groups of co-eluted isomers were identified successfully. The results demonstrated that NMR/LC-MS PDS combined with the incompleted separation strategy achieved the similar function of on-line LC-NMR-MS analysis in off-line mode and had the potential for simplifying and accelerating the analytical routes for structure identification of constituents in herbs or their active extracts.

An Information-Based Computational Technique for Estimation of Chromatographic Peak Purity

Assessment of the purity of chromatographic peaks is an important step in developing and validating purification procedures for complex mixtures. While curve-fitting techniques can be useful for determining the retention times and relative concentrations of the components of a chromatographic peak, their utility is limited by the lack of unambiguous criteria for determining the number of such components. In this work, we present a computational technique for analyzing chromatograms to estimate the number of components, their retention times, and their relative concentrations. In contrast to Fourier-transform-based techniques, the technique we present does not require manual peak identification. It is based on curve-fitting and uses the Akaike information criterion to estimate the number of components. Application of the technique to chromatograms obtained from size-exclusion and reverse-phase chromatography of test mixtures indicates that it is useful for the characterization of complex mixtures.

Factor analysis of hyphenated chromatographic data

Factor analysis (FA) is a family of widely used methods to obtain the underlying sources of variation of data tables. Typically, hyphenated chromatographic data provide data tables with one elution direction and another linked to the detector response. In this context, the factors are the eluting compounds and the profiles defining each factor are the elution profile and the pure response of the compound. This article describes the use of FA in chromatography through diverse tools and problems. Examples of determination of number of compounds, peak purity problems, resolution of overlapped compounds or extension to simultaneous analysis of multiple runs (higher-order data structures) to obtain qualitative and quantitative information are reviewed.

Virtual Chromatographic Resolution Enhancement in Cryoflow LC−NMR Experiments via Statistical Total Correlation Spectroscopy

A new approach to enhancing information recovery from cryogenic probe "on-flow" LC-NMR spectroscopic analyses of complex biological mixtures is demonstrated using a variation on the statistical total correlation spectroscopy (STOCSY) method. Cryoflow probe technology enables sensitive and efficient NMR detection of metabolites on-flow, and the rapid spectral scanning allows multiple spectra to be collected over chromatographic peaks containing several species with similar, but nonidentical, retention times. This enables 1H NMR signal connectivities between close-eluting metabolites to be identified resulting in a "virtual" chromatographic resolution enhancement visualized directly in the NMR spectral projection. We demonstrate the applicability of the approach for structure assignment of drug and endogenous metabolites in urine. This approach is of wide general applicability to any complex mixture analysis problem involving chromatographic peak overlap and with particular application in metabolomics and metabonomics.