Heteronuclear 1H-31P statistical total correlation NMR spectroscopy of intact liver for metabolic biomarker assignment: application to galactosamine-induced hepatotoxicity

As part of our ongoing development of methods for enhanced biomarker information recovery from spectroscopic data we present the first example of a new hetero-nuclear statistical total correlation spectroscopy (HET-STOCSY) approach applied to intact tissue samples collected as part of a toxicological study. One-dimensional 1H and 31P-{1H} magic angle spinning (MAS) NMR spectra of intact liver samples after galactosamine (galN) treatment to rats and after cotreatment of galN plus uridine were collected at 275 K. Individual samples were also followed by 1H and 31P-{1H} MAS NMR through time generating time dependent modulations in metabolite signatures relating to toxicity. High-resolution 1H NMR spectra of urine and plasma and clinical chemical data were also collected to establish a biological framework in which to place these novel statistical heterospectroscopic data. In HET-STOCSY, calculation of the covariance between the 31P-{1H} and 1H NMR signals of phosphorus containing metabolites allows their molecular connectivities to be established and the construction of virtual two-dimensional heteronuclear correlation spectra that connect all protons on the molecule to the heteroatom. We show how HET-STOCSY applied to MAS NMR spectra of liver samples can be used to augment biomarker detection. This approach is generic and can be applied to correlate the covarying signals for any spin-active nuclei where there is parallel or serial collection of data.     

Heteronuclear 19F-1H statistical total correlation spectroscopy as a tool in drug metabolism: study of flucloxacillin biotransformation

We present a novel application of the heteronuclear statistical total correlation spectroscopy (HET-STOCSY) approach utilizing statistical correlation between one-dimensional 19F/1H NMR spectroscopic data sets collected in parallel to study drug metabolism. Parallel one-dimensional (1D) 800 MHz 1H and 753 MHz 19F{1H} spectra (n = 21) were obtained on urine samples collected from volunteers (n = 6) at various intervals up to 24 h after oral dosing with 500 mg of flucloxacillin. A variety of statistical relationships between and within the spectroscopic datasets were explored without significant loss of the typically high 1D spectral resolution, generating 1H-1H STOCSY plots, and novel 19F-1H HET-STOCSY, 19F-19F STOCSY, and 19F-edited 1H-1H STOCSY (X-STOCSY) spectroscopic maps, with a resolution of approximately 0.8 Hz/pt for both nuclei. The efficient statistical editing provided by these methods readily allowed the collection of drug metabolic data and assisted structure elucidation. This approach is of general applicability for studying the metabolism of other fluorine-containing drugs, including important anticancer agents such as 5-fluorouracil and flutamide, and is extendable to any drug metabolism study where there is a spin-active X-nucleus (e.g., 13C, 15N, 31P) label present.     

Statistical total correlation spectroscopy: an exploratory approach for latent biomarker identification from metabolic 1H NMR data sets

We describe here the implementation of the statistical total correlation spectroscopy (STOCSY) analysis method for aiding the identification of potential biomarker molecules in metabonomic studies based on NMR spectroscopic data. STOCSY takes advantage of the multicollinearity of the intensity variables in a set of spectra (in this case 1H NMR spectra) to generate a pseudo-two-dimensional NMR spectrum that displays the correlation among the intensities of the various peaks across the whole sample. This method is not limited to the usual connectivities that are deducible from more standard two-dimensional NMR spectroscopic methods, such as TOCSY. Moreover, two or more molecules involved in the same pathway can also present high intermolecular correlations because of biological covariance or can even be anticorrelated. This combination of STOCSY with supervised pattern recognition and particularly orthogonal projection on latent structure-discriminant analysis (O-PLS-DA) offers a new powerful framework for analysis of metabonomic data. In a first step O-PLS-DA extracts the part of NMR spectra related to discrimination. This information is then cross-combined with the STOCSY results to help identify the molecules responsible for the metabolic variation. To illustrate the applicability of the method, it has been applied to 1H NMR spectra of urine from a metabonomic study of a model of insulin resistance based on the administration of a carbohydrate diet to three different mice strains (C57BL/6Oxjr, BALB/cOxjr, and 129S6/SvEvOxjr) in which a series of metabolites of biological importance can be conclusively assigned and identified by use of the STOCSY approach.     

Optimization of human plasma 1H NMR spectroscopic data processing for high-throughput metabolic phenotyping studies and detection of insulin resistance related to type 2 diabetes

Optimizing NMR experimental parameters for high-throughput metabolic phenotyping requires careful examination of the total biochemical information obtainable from (1)H NMR data, which includes concentration and molecular dynamics information. Here we have applied two different types of mathematical transformation (calculation of the first derivative of the NMR spectrum and Gaussian shaping of the free-induction decay) to attenuate broad spectral features from macromolecules and enhance the signals of small molecules. By application of chemometric methods such as principal component analysis (PCA), orthogonal projections to latent structures discriminant analysis (O-PLS-DA) and statistical spectroscopic tools such as statistical total correlation spectroscopy (STOCSY), we show that these methods successfully identify the same potential biomarkers as spin-echo (1)H NMR spectra in which broad lines are suppressed via T2 relaxation editing. Finally, we applied these methods for identification of the metabolic phenotype of patients with type 2 diabetes. This "virtual" relaxation-edited spectroscopy (RESY) approach can be particularly useful for high-throughput screening of complex mixtures such as human plasma and may be useful for extraction of latent biochemical information from legacy or archived NMR data sets for which only standard 1D data sets exist.     

Statistical total correlation spectroscopy scaling for enhancement of metabolic information recovery in biological NMR spectra

The high level of complexity in nuclear magnetic resonance (NMR) metabolic spectroscopic data sets has fueled the development of experimental and mathematical techniques that enhance latent biomarker recovery and improve model interpretability. We previously showed that statistical total correlation spectroscopy (STOCSY) can be used to edit NMR spectra to remove drug metabolite signatures that obscure metabolic variation of diagnostic interest. Here, we extend this "STOCSY editing" concept to a generalized scaling procedure for NMR data that enhances recovery of latent biochemical information and improves biological classification and interpretation. We call this new procedure STOCSY-scaling (STOCSY(S)). STOCSY(S) exploits the fixed proportionality in a set of NMR spectra between resonances from the same molecule to suppress or enhance features correlated with a resonance of interest. We demonstrate this new approach using two exemplar data sets: (a) a streptozotocin rat model (n = 30) of type 1 diabetes and (b) a human epidemiological study utilizing plasma NMR spectra of patients with metabolic syndrome (n = 67). In both cases significant biomarker discovery improvement was observed by using STOCSY(S): the approach successfully suppressed interfering NMR signals from glucose and lactate that otherwise dominate the variation in the streptozotocin study, which then allowed recovery of biomarkers such as glycine, which were otherwise obscured. In the metabolic syndrome study, we used STOCSY(S) to enhance variation from the high-density lipoprotein cholesterol peak, improving the prediction of individuals with metabolic syndrome from controls in orthogonal projections to latent structures discriminant analysis models and facilitating the biological interpretation of the results. Thus, STOCSY(S) is a versatile technique that is applicable in any situation in which variation, either biological or otherwise, dominates a data set at the expense of more interesting or important features. This approach is generally appropriate for many types of NMR-based complex mixture analyses and hence for wider applications in bioanalytical science.     

Statistical correlation and projection methods for improved information recovery from diffusion-edited NMR spectra of biological samples

Although NMR spectroscopic techniques coupled with multivariate statistics can yield much useful information for classifying biological samples based on metabolic profiles, biomarker identification remains a time-consuming and complex procedure involving separation methods, two-dimensional NMR, and other spectroscopic tools. We present a new approach to aid complex biomixture analysis that combines diffusion ordered (DO) NMR spectroscopy with statistical total correlation spectroscopy (STOCSY) and demonstrate its application in the characterization of urinary biomarkers and enhanced information recovery from plasma NMR spectra. This method relies on calculation and display of the covariance of signal intensities from the various nuclei on the same molecule across a series of spectra collected under different pulsed field gradient conditions that differentially attenuate the signal intensities according to translational molecular diffusion rates. We term this statistical diffusion-ordered spectroscopy (S-DOSY). We also have developed a new visualization tool in which the apparent diffusion coefficients from DO spectra are projected onto a 1D NMR spectrum (diffusion-ordered projection spectroscopy, DOPY). Both methods either alone or in combination have the potential for general applications to any complex mixture analysis where the sample contains compounds with a range of diffusion coefficients.     

Metabonomic study of host-phage interaction by nuclear magnetic resonance- and statistical total correlation spectroscopy-based analysis

We present a method for the qualitative and quantitative study of transient metabolic flux of phage infection at the molecular level. The method is based on statistical total correlation spectroscopy (STOCSY) and partial least squares discriminant analysis (PLS-DA) applied to nuclear magnetic resonance (NMR) metabonomic data sets. An algorithm for this type of study is developed and demonstrated. The method has been implemented on (1)H NMR data sets of growth media in planktonic cultures of Pseudomonas aeruginosa infected with bacteriophage pf1. Transient metabolic flux of various important metabolites, identified by STOCSY and PLS-DA analysis applied to the NMR data set, are estimated at various stages of growth. The opportunistic and nosocomial pathogen P. aeruginosa is one of the best-studied model organism for bacterial biofilms. Complete information regarding metabolic connectivity of this system is not possible by conventional spectroscopic approach. Our study presents temporal comparative (1)H NMR metabonomic analyses of filamentous phage pf1 infection in planktonic cultures of P. aeruginosa K strain (PAK). We exemplify here the potential of STOCSY and PLS-DA tools to gain mechanistic insight into subtle changes and to determine the transient flux associated with metabolites following metabolic perturbations resulting from phage infection. Our study has given new avenues in correlating existing postgenomic data with current metabonomic results in P. aeruginosa biofilms research.     

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.     

Data-driven approach for metabolite relationship recovery in biological 1H NMR data sets using iterative statistical total correlation spectroscopy

Statistical total correlation spectroscopy (STOCSY) is a well-established and valuable method in the elucidation of both inter- and intrametabolite correlations in NMR metabonomic data sets. Here, the STOCSY approach is extended in a novel Iterative-STOCSY (I-STOCSY) tool in which correlations are calculated initially from a driver peak of interest and subsequently for all peaks identified as correlating with a correlation coefficient greater than a set threshold. Consequently, in a single automated run, the majority of information contained in multiple STOCSY calculations from all peaks recursively correlated to the original user defined driver peak of interest are recovered. In addition, highly correlating peaks are clustered into putative structurally related sets, and the results are presented in a fully interactive plot where each set is represented by a node; node-to-node connections are plotted alongside corresponding spectral data colored by the strength of connection, thus allowing the intuitive exploration of both inter- and intrametabolite connections. The I-STOCSY approach has been here applied to a (1)H NMR data set of 24 h postdose aqueous liver extracts from rats treated with the model hepatotoxin galactosamine and has been shown both to recover the previously deduced major metabolic effects of treatment and to generate new hypotheses even on this well-studied model system. I-STOCSY, thus, represents a significant advance in correlation based analysis and visualization, providing insight into inter- and intrametabolite relationships following metabolic perturbations.     

Hierarchical Alignment and Full Resolution Pattern Recognition of 2D NMR Spectra: Application to Nematode Chemical Ecology

Nuclear magnetic resonance (NMR) is the most widely used nondestructive technique in analytical chemistry. In recent years, it has been applied to metabolic profiling due to its high reproducibility, capacity for relative and absolute quantification, atomic resolution, and ability to detect a broad range of compounds in an untargeted manner. While one-dimensional (1D) (1)H NMR experiments are popular in metabolic profiling due to their simplicity and fast acquisition times, two-dimensional (2D) NMR spectra offer increased spectral resolution as well as atomic correlations, which aid in the assignment of known small molecules and the structural elucidation of novel compounds. Given the small number of statistical analysis methods for 2D NMR spectra, we developed a new approach for the analysis, information recovery, and display of 2D NMR spectral data. We present a native 2D peak alignment algorithm we term HATS, for hierarchical alignment of two-dimensional spectra, enabling pattern recognition (PR) using full-resolution spectra. Principle component analysis (PCA) and partial least squares (PLS) regression of full resolution total correlation spectroscopy (TOCSY) spectra greatly aid the assignment and interpretation of statistical pattern recognition results by producing back-scaled loading plots that look like traditional TOCSY spectra but incorporate qualitative and quantitative biological information of the resonances. The HATS-PR methodology is demonstrated here using multiple 2D TOCSY spectra of the exudates from two nematode species: Pristionchus pacificus and Panagrellus redivivus. We show the utility of this integrated approach with the rapid, semiautomated assignment of small molecules differentiating the two species and the identification of spectral regions suggesting the presence of species-specific compounds. These results demonstrate that the combination of 2D NMR spectra with full-resolution statistical analysis provides a platform for chemical and biological studies in cellular biochemistry, metabolomics, and chemical ecology.     

Kinetic and J-resolved statistical total correlation NMR spectroscopy approaches to structural information recovery in complex reacting mixtures: application to acyl glucuronide intramolecular transacylation reactions

We demonstrate here a new variant on a statistical spectroscopic method for recovering structural information on unstable intermediates formed in reaction mixtures. We exemplify this approach with respect to the internal acyl migration reactions of 1-beta-O-acyl glucuronides (AGs), which rearrange at neutral or slightly alkaline pH on a minute to hour time scale to yield a series of positional glucuronide ring isomers and alpha/beta anomers from the 1-beta (starting material), i.e. 2-beta, 2-alpha, 1-alpha, 3-beta, 3-alpha, and 4-beta, 4-alpha isomers together with the aglycon and alpha- and beta-glucuronic acid hydrolysis products. Multiple sequential 800 MHz cryoprobe (1)H NMR spectra (1D and 2D J-resolved, JRES) were collected on a 5.1 mM solution of a synthetic model drug glucuronide, 1-beta-O-acyl (S)-alpha-methyl phenylacetyl glucuronide (MPG) in 0.1 M sodium phosphate buffer in D2O at pD 7.4 over 18 h to monitor the reaction which leads to the formation of the eight positional isomers and hydrolysis products. As the reaction proceeds and new isomers form, the NMR signal intensities vary accordingly allowing the application of a novel kinetic variant on statistical total correlation spectroscopy (K-STOCSY) method to recover the connectivities between proton signals on the same reacting molecule based on their intensity covariance through time. We performed K-STOCSY analysis on both the standard 1D NMR spectra and the skyline projected singlets of the (1)H-(1)H JRES NMR spectra through time, i.e. the K-JRES-STOCSY experimental variant, which increases the effective spectral dispersion and is ideally suited for the analysis of heavily overlapped spin systems. High statistical correlations were observed between mutarotated alpha- and beta-anomers of individual positional isomers, as well as directly acyl migrated products and anticorrelation observed between signals from compounds that were being depleted as others increased, e.g. between the 1-beta and 2-alpha/2-beta isomers. This statistical kinetic approach enabled the recovery of structural connectivity information on all isomers allowing unequivocal resonance assignment, and this approach to spectroscopic information recovery has wider potential uses in the study of reactions that occur on the second-to-minute time scale in conditions where multiple sequential NMR spectra can be collected. JRES-STOCSY is also of potential use as a method for recovering spectroscopic information in highly overlapped NMR signals and spin systems in other types of complex mixture analysis.     

"Add to subtract": a simple method to remove complex background signals from the 1H nuclear magnetic resonance spectra of mixtures

Because of its highly reproducible and quantitative nature and minimal requirements for sample preparation or separation, (1)H nuclear magnetic resonance (NMR) spectroscopy is widely used for profiling small-molecule metabolites in biofluids. However (1)H NMR spectra contain many overlapped peaks. In particular, blood serum/plasma and diabetic urine samples contain high concentrations of glucose, which produce strong peaks between 3.2 ppm and 4.0 ppm. Signals from most metabolites in this region are overwhelmed by the glucose background signals and become invisible. We propose a simple "Add to Subtract" background subtraction method and show that it can reduce the glucose signals by 98% to allow retrieval of the hidden information. This procedure includes adding a small drop of concentrated glucose solution to the sample in the NMR tube, mixing, waiting for an equilibration time, and acquisition of a second spectrum. The glucose-free spectra are then generated by spectral subtraction using Bruker Topspin software. Subsequent multivariate statistical analysis can then be used to identify biomarker candidate signals for distinguishing different types of biological samples. The principle of this approach is generally applicable for all quantitative spectral data and should find utility in a variety of NMR-based mixture analyses as well as in metabolite profiling.     

Application of a microcoil probe head in NMR analysis of chemicals related to the chemical weapons convention

A 1.7-mm microcoil probe head was tested in the analysis of organophosphorus compounds related to the Chemical Weapons Convention. The microcoil probe head demonstrated a high mass sensitivity in the detection of traces of organophosphorus compounds in samples. Methylphosphonic acid, the common secondary degradation product of sarin, soman, and VX, was detected at level 50 ng (0.52 nmol) from a 30-microL water sample using proton-observed experiments. Direct phosphorus observation of methylphosphonic acid with (31)P{(1)H} NMR experiment was feasible at the 400-ng (4.17 nmol) level. Application of the microcoil probe head in the spiked sample analysis was studied with a test water sample containing 2-10 microg/mL of three organophosphorus compounds. High-quality (1)H NMR, (31)P{(1)H} NMR, 2D (1)H-(31)P fast-HMQC, and 2D TOCSY spectra were obtained in 3 h from the concentrated 1.7-mm NMR sample prepared from 1 mL of the water solution. Furthermore, a 2D (1)H-(13)C fast-HMQC spectrum with sufficient quality was possible to measure in 5 h. The microcoil probe head demonstrated a considerable sensitivity improvement and reduction of measurement times for the NMR spectroscopy in identification of chemicals related to the Chemical Weapons Convention.     

Preparation of ultrafine chalcopyrite nanoparticles via the photochemical decomposition of molecular single-source precursors

The synthesis and characterization of ultrafine CuInS2 nanoparticles are described. Ultraviolet irradiation was used to decompose a molecular single source precursor, yielding organic soluble approximately 2 nm sized nanoparticles with a narrow size distribution. UV-vis absorption, 1H and 31P{1H} NMR, and fluorescence spectroscopies and mass spectrometry were used to characterize decomposition of the precursors and nanoparticle formation. The nanoparticles were characterized by high-resolution transmission electron microscopy (HRTEM), scanning electron microscopy energy dispersive X-ray spectroscopy, powder X-ray diffraction (XRD), electron diffraction, inductively coupled plasma analysis, UV-vis absorption spectroscopy, and fluorescence spectroscopy. They have a wurzite-type crystal structure with a copper-rich composition. The hypsochromic shift in their emission band due to quantum confinement effects is consistent with the size of the nanocrystals indicated in the HRTEM and XRD analyses.     

Si cross-polarization magic-angle spinning NMR spectroscopy––an efficient tool for quantification of thaumasite in cement-based materials

²⁹Si{¹H} cross-polarization (CP) magic-angle spinning (MAS) NMR spectroscopy is a powerful and reliable tool for the quantification of thaumasite in cement-based materials. The most efficient method for quantifying thaumasite from ²⁹Si{¹H} CP/MAS NMR spectra is described and it is shown that the method allows detection of thaumasite contents below approximately 10 wt.% with a relative precision of 15% and contents above 10 wt.% with a relative precision of 10%. The applicability of ²⁹Si{¹H} CP/MAS NMR for quantification of thaumasite is demonstrated for different Portland cement pastes and shows that thaumasite contents as low as 0.2–0.5 wt.% can be detected in cementitious systems with low concentrations of paramagnetic impurities. For a Portland cement containing various amounts of limestone dust and stored at 5 °C in a MgSO₄ solution, large quantities of thaumasite have been detected. Furthermore, the quantity of thaumasite is found to be less sensitive to the amount of added limestone dust. For samples of a Portland cement with a fixed content of limestone dust but different quantities of added gypsum, the increased contents of gypsum are observed to result in larger quantities of thaumasite after prolonged hydration.     

Application of directly coupled HPLC NMR to separation and characterization of lipoproteins from human serum

Disorders in lipoprotein metabolism are critical in the etiology of several disease states such as coronary heart disease and atherosclerosis. Thus, there is considerable interest in the development of novel methods for the analysis of lipoprotein complexes. We report here a simple chromatographic method for the separation of high-density lipoprotein, low-density lipoprotein, and very low-density lipoprotein from intact serum or plasma. The separation was achieved using a hydroxyapatite column and elution with pH 7.4 phosphate buffer with 100-microL injections of whole plasma. Coelution of HDL with plasma proteins such as albumin occurred, and this clearly limits quantitation of that species by HPLC peak integration. We also show, for the first time, the application of directly coupled HPLC 1H NMR spectroscopy to confirm the identification of the three major lipoproteins. The full chromatographic run time was 90 min with stopped-flow 600-MHz NMR spectra of each lipoprotein being collected using 128 scans, in 7 min. The 1H NMR chemical shifts of lipid signals were identical to conventional NMR spectra of freshly prepared lipoprotein standards, confirming that the lipoproteins were not degraded by the HPLC separation and that their gross supramolecular organization was intact.     

(Na4BH4) guests inside aluminosilicate, gallosilicate and aluminogermanate sodalite host frameworks studied by H, B, and Na MAS NMR spectroscopy

We report tetrahydroborate aluminosilicate, gallosilicate and aluminogermanate sodalites studied by ¹¹B, ¹H and ²³Na MAS NMR spectroscopy. The spectral parameters are consistent with the local environments of each investigated nucleus obtained from the crystal structures. The ¹¹B MAS NMR spectra exhibit a sharp narrow line at about −49.0 ppm, which is assigned to BH₄⁻ enclathrated into the sodalite framework matrix. The lineshape of the signal shows no quadrupolar interactions due to discreteness and high symmetry of the BH₄⁻ unit as well as possible fast dynamic site exchange of hydrogen atoms. The ²³Na MAS NMR signals also show a narrow Gaussian lineshape, which clearly indicates a single type of sodium coordination, and a centrosymmetrical charge distribution around the sodium atom. The ¹H MAS NMR spectra can clearly distinguish between hydrogen in BH₄⁻ anions (−0.6 ppm), H₃O₂⁻ anions (1.2 ppm) and H₂O molecules (5.0 ppm). The structural properties of BH₄⁻ intercalation into sodalite framework matrix help connect the microporous materials to hydride-containing A, X and Y type zeolites.     

Chain order and mobility of high-density c(18) phases by solid-state NMR spectroscopy and liquid chromatography

C(18) phases prepared by different synthetic pathways are examined by solid-state NMR spectroscopy. Silane functionality is clearly indicated by (29)Si CP/MAS NMR spectroscopy. Order and mobility of the alkyl chains are investigated with high-speed (1)H MAS and (13)C CP/MAS NMR spectroscopy. Differences in coverage are monitored by (1)H line widths,( 13)C chemical shifts, (13)C cross-polarization constants, and (1)H relaxation times in the rotating frame. It is shown that C(18) phases prepared by the surface polymerization technique exhibit a more regular surface coverage than sorbents prepared by conventional polymeric synthesis. The findings from solid-state NMR investigations are discussed in the context of liquid chromatography (LC) separations of linear and bulky polycyclic aromatic hydrocarbon (PAH) solutes.