Statistical heterospectroscopy, an approach to the integrated analysis of NMR and UPLC-MS data sets: application in metabonomic toxicology studies

Statistical heterospectroscopy (SHY) is a new statistical paradigm for the coanalysis of multispectroscopic data sets acquired on multiple samples. This method operates through the analysis of the intrinsic covariance between signal intensities in the same and related molecules measured by different techniques across cohorts of samples. The potential of SHY is illustrated using both 600-MHz 1H NMR and UPLC-TOFMS data obtained from control rat urine samples (n = 54) and from a corresponding hydrazine-treated group (n = 58). We show that direct cross-correlation of spectral parameters, viz. chemical shifts from NMR and m/z data from MS, is readily achievable for a variety of metabolites, which leads to improved efficiency of molecular biomarker identification. In addition to structure, higher level biological information can be obtained on metabolic pathway activity and connectivities by examination of different levels of the NMR to MS correlation and anticorrelation matrixes. The SHY approach is of general applicability to complex mixture analysis, if two or more independent spectroscopic data sets are available for any sample cohort. Biological applications of SHY as demonstrated here show promise as a new systems biology tool for biomarker recovery.     

Quantitative 1H NMR spectroscopy of blood plasma metabolites

The absolute quantification of blood plasma metabolites by proton NMR spectroscopy is complicated by the presence of a baseline and broad resonances originating from serum macromolecules and lipoproteins. A method for spectral simplification of proton NMR spectra of blood plasma is presented. Serum macromolecules and metabolites are completely separated by utilizing the large difference in translational diffusion coefficients in combination with diffusion-sensitized proton NMR spectroscopy. The concentration of blood plasma metabolites can be quantified by using formate as an internal concentration reference. The results are compared with those obtained with ultrafiltration, a traditional method for separating macromolecules and metabolites, and demonstrate an excellent correlation between the two methods. The general nature of diffusion-sensitized NMR spectroscopy allows application on a wide range of biological fluids.     

Identification of endohedral water in single-walled carbon nanotubes by (1)H NMR

Water confinement within single-walled carbon nanotubes (SWCNTs) has been a topic of current interest, due in part to their potential nanofiltration applications. Experiments have recently validated molecular dynamics predictions of flow enhancement within these channels, although few studies have probed the detailed structure and dynamics of water in these systems. Proton nuclear magnetic resonance ( (1)H NMR) is a technique capable of providing some of these details, although care must be exercised in separating the confined water of interest from exterior water. By using controlled experiments with both sealed and opened SWCNTs and by providing a quantitative measure of water content through desorption experiments, a signature for confined water in SWCNTs has been positively identified. This endohedral or interior water is characterized by a relatively broad feature located at 0.0 ppm, shifted upfield relative to bulk water. With the identification of a signature for water inside SWCNTs, further studies aimed at probing water dynamics will be enabled.     

Quantification of high-resolution (1)H NMR spectra from rat brain extracts

Extracting quantitative information about absolute concentrations from high-resolution (1)H NMR spectra of complex mixtures such as brain extracts remains challenging. Partial overlap of resonances complicates integration, whereas simple line fitting algorithms cannot accommodate the spectral complexity of coupled spin systems. Here, it is shown that high-resolution (1)H NMR spectra of rat brain extracts from 11 distinct brain regions can be reproducibly quantified using a basis set of 29 compounds. The basis set is simulated with the density matrix formalism using complete prior knowledge of chemical shifts and scalar couplings. A crucial aspect to obtain reproducible results was the inclusion of a line shape distortion common among all 73 resonances of the 29 compounds. All metabolites could be quantified with <10% and <3% inter- and intrasubject variation, respectively.     

Assessment of analytical reproducibility of 1H NMR spectroscopy based metabonomics for large-scale epidemiological research: the INTERMAP Study

Large-scale population phenotyping for molecular epidemiological studies is subject to all the usual criteria of analytical chemistry. As part of a major phenotyping investigation we have used high-resolution 1H NMR spectroscopy to characterize 24-h urine specimens obtained from population samples in Aito Town, Japan (n = 259), Chicago, IL (n = 315), and Guangxi, China (n = 278). We have investigated analytical reproducibility, urine specimen storage procedures, interinstrument variability, and split specimen detection. Our data show that the multivariate analytical reproducibility of the NMR screening platform was >98% and that most classification errors were due to urine specimen handling inhomogeneity. Differences in metabolite profiles were then assessed for Aito Town, Chicago, and Guangxi population samples; novel combinations of biomarkers were detected that separated the population samples. These cross-population differences in urinary metabolites could be related to genetic, dietary, and gut microbial factors.     

Measurement of SDS Micelle-Peptide Association Using (1)H NMR Chemical Shift Analysis and Pulsed-Field Gradient NMR Spectroscopy

The binding of two simple tripeptides, glycyl-histidyl-glycine (GHG) and phenylalanyl-histidyl-phenylalanine (FHF) with SDS micelles was examined using (1)H NMR chemical shift analysis and self-diffusion coefficients measured with pulsed-field gradient NMR spectroscopy. The presence of GHG or FHF did not appear to significantly affect the critical micelle concentration (cmc) or the average size of the SDS micelles formed. The chemical shifts of several of the GHG resonances change as a function of SDS concentration, indicating an interaction between the peptide and the micelles. In addition, the concentration-dependent decrease observed for the GHG diffusion coefficients suggests association of the peptide with SDS micelles. The free and micelle-associated GHG are in fast exchange on both the (1)H chemical shift and diffusion time scales. The equilibrium constant for the binding of GHG to SDS micelles was determined from the analysis of the concentration dependence of the histidine C2 and C4 resonances to be 17 ± 5 and 24 ± 6 M(-)(1), respectively. The precision of the equilibrium constants obtained by analysis of the chemical shift data is limited by the small chemical shift changes observed. Analysis of the concentration dependence of the diffusion coefficients produced an equilibrium constant of 17 ± 1 M(-)(1). The more hydrophobic peptide, FHF is strongly associated with the SDS micelles. Because the fraction of free FHF is small in these solutions, it was not possible to determine a formation constant for the interaction of FHF with the SDS micelles by analysis of either the (1)H chemical shift or diffusion coefficient data. The cmc of SDS in 0.10 M Na(2)C(2)O(4) buffer was determined to be 5.4 ± 0.1 mM by analysis of the SDS diffusion coefficients in the absence of the peptides. The SDS cmc could also be extracted from the GHG and FHF diffusion coefficients measured as a function of the SDS concentration. The cmc determined from the GHG diffusion data, 5.7 ± 0.2 mM, is in good agreement with the value determined from analysis of the SDS diffusion coefficients in the 5.0 mM GHG solution, 5.2 ± 0.1 mM. The smaller cmc determined from the FHF diffusion data, 4.1 ± 0.1 mM, may reflect some association of the SDS with the peptide prior to micelle formation in bulk solution.     

Experimental and analytical variation in human urine in 1H NMR spectroscopy-based metabolic phenotyping studies

1H NMR spectroscopy potentially provides a robust approach for high-throughput metabolic screening of biofluids such as urine and plasma, but sample handling and preparation need careful optimization to ensure that spectra accurately report biological status or disease state. We have investigated the effects of storage temperature and time on the 1H NMR spectral profiles of human urine from two participants, collected three times a day on four different days. These were analyzed using modern chemometric methods. Analytical and preparation variation (tested between -40 degrees C and room temperature) and time of storage (to 24 h) were found to be much less influential than biological variation in sample classification. Statistical total correlation spectroscopy and discriminant function methods were used to identify the specific metabolites that were hypervariable due to preparation and biology. Significant intraindividual variation in metabolite profiles were observed even for urine collected on the same day and after at least 6 h fasting. The effect of long-term storage at different temperatures was also investigated, showing urine is stable if frozen for at least 3 months and that storage at room temperature for long periods (1-3 months) results in a metabolic profile explained by bacterial activity. Presampling (e.g., previous day) intake of food and medicine can also strongly influence the urinary metabolic profiles indicating that collective detailed participant historical meta data are important for interpretation of metabolic phenotypes and for avoiding false biomarker discovery.     

A Quantitative Method for Determination of Lactide Composition in Poly(lactide) Using (1)H NMR

A method has been developed to quantitatively determine the composition of d-lactide and meso-lactide stereoisomer impurities in poly(lactide) containing predominantly l-lactide. In this method, the stereosequence information obtained from a few well-resolved resonances in the (1)H NMR spectrum representing RR and R stereogenic defects is used. The d-lactide and meso-lactide as minor components lead to RR and R stereogenic defects, respectively, which influence the isotactic chain length distribution and hence affect the polymer properties. Analytical equations relating the stereosequence probability to the lactide feed composition are not available due the complicated kinetics involved for the melt polymerization; viz. the preference for syndiotactic lactide addition decreases with reducing residual lactide concentration in the batch process. Hence, empirical correlations were determined by least-squares fit to the predictions for the specific stereosequence probabilities provided by Monte Carlo calculations of a number of lactide stereocopolymerizations. The Monte Carlo calculations simulate the kinetics observed for melt polymerization at 180 °C catalyzed by Sn(II) bis(2-ethylhexanoate) (Sn(II) octoate) in a 1:10 000 catalyst/lactide ratio.     

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.     

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.     

Determination of residue-specific acid dissociation constants for peptides by band-selective homonuclear-decoupled (1)H NMR

Acid dissociation constants of side-chain acidic groups of amino acid residues in peptides can be determined by 1H NMR, provided resonances can be resolved for carbon-bonded reporter protons located near the acidic group. We report here that the increased resolution of the band-selective homonuclear-decoupled (BASHD) TOCSY experiment greatly extends the range of application of the NMR method for determination of residue-specific, side-chain acid dissociation constants of peptides that contain multiple residues of the same amino acid. Chemical shift-pH titration curves are obtained from cross-peaks for reporter protons in BASHD-TOCSY spectra measured as a function of pH. The method is based on using sequence-dependent differences in the chemical shifts of resonances for the backbone CalphaH protons and the increased resolution in BASHD-TOCSY spectra from collapse of CalphaH multiplets to singlets in the F1 dimension to resolve resonances for the side-chain reporter protons. Application of the method is demonstrated by determination of residue-specific pKA values for each of the side-chain ammonium groups of the six lysine residues in the hexadecapeptide Ac-SRGKAKVKAKVKDQTK-NH2. Chemical shift-pH titration curves were obtained for the lysine side-chain CepsilonH2 reporter protons from their resolved CalphaH-CepsilonH2 TOCSY cross-peaks in BASHD-TOCSY spectra. Relative acidities of the six ammonium groups were also determined from the residue specific chemical shift-pH titration data by a pH-independent method, and calculation of fractional concentrations of protonation microspecies using the residue-specific pKAs is also described.     

Determination of the composition of acetylglycerol mixtures by (1)H NMR followed by GC investigation

Commercially available partly acetylated glycerols (mono- and diacetins) are a mixture of glycerol, 1- and 2-acetylglycerol, 1,2- and 1,3-diacetylglycerol, and triacetin. No exact analysis method is available. Comparisons of (1)H NMR measurements obtained using deuterated dimethyl sulfoxide (DMSO-d6) and DMSO-d6/15% D2O are sufficient to identify and determine quickly all the components. Advantages compared with the commonly used NMR solvent CDCl3 for fatty acid glycerides include the solubility of all the components and a highly informative OH signal pattern in a region between 4.36 and 5.26 ppm almost free of other signals. 2-Acetylglycerol (2-acetin) is shown to disproportionate even at 50 degrees C into a mixture of glycerol and acetylglycerol thereby making it difficult to quantify by liquid chromatography (LC) and gas chromatography (GC) methods. Complete (1)H chemical shift data for all five components allow for the identification of the components in the mixture and thus the determination of the composition. The NMR method with DMSO-d6 as solvent was used for acetins, propionins, and butyrins. Semipreparative high-performance liquid chromatography (HPLC) on an RP18 column led to moderately pure 1-monoacetin and a mixture of diacylated species. Electron impact mass spectra show for all the components very characteristic fragmentation patterns with loss of AcOCH2 radicals, in contrast to the well-known pattern of longer-chained fatty acid derivatives that show preferred first-step loss of acyl-O radicals.     

Curve-fitting method for direct quantitation of compounds in complex biological mixtures using 1H NMR: application in metabonomic toxicology studies

A new software tool has been developed that provides automated measurement of signal intensities in NMR spectra of complex mixtures without using data reduction procedures. The algorithm finds best-fit transformations between signals in reference compound spectra and the corresponding signals in analyte spectra. Unlike other algorithms, it is insensitive to variation in chemical shift and can even be used for relative quantitation of compounds whose identities have not yet been established. Additionally, the parameters of the transformation provide information and error metrics that may assist in the streamlining of quality control. The approach presented is general in scope but has been tested by application to peak quantitation in NMR spectra of biofluids. Replicate NMR measurements of solutions of biologically important compounds at various concentrations were made. Further NMR data were collected on urine samples from human, rat, and mouse, which were "spiked" with reference compound solutions at known concentrations. Finally, existing data from an independent toxicology project involving several hundred samples were analyzed, and the consistency of the measurements for metabolites that give multiple NMR signals was assessed. The results of all these tests give confidence that the technique can be used in automated quantitation of compounds in large NMR data sets with minimal operator intervention.     

Targeted profiling: quantitative analysis of 1H NMR metabolomics data

Extracting meaningful information from complex spectroscopic data of metabolite mixtures is an area of active research in the emerging field of "metabolomics", which combines metabolism, spectroscopy, and multivariate statistical analysis (pattern recognition) methods. Chemometric analysis and comparison of 1H NMR1 spectra is commonly hampered by intersample peak position and line width variation due to matrix effects (pH, ionic strength, etc.). Here a novel method for mixture analysis is presented, defined as "targeted profiling". Individual NMR resonances of interest are mathematically modeled from pure compound spectra. This database is then interrogated to identify and quantify metabolites in complex spectra of mixtures, such as biofluids. The technique is validated against a traditional "spectral binning" analysis on the basis of sensitivity to water suppression (presaturation, NOESY-presaturation, WET, and CPMG), relaxation effects, and NMR spectral acquisition times (3, 4, 5, and 6 s/scan) using PCA pattern recognition analysis. In addition, a quantitative validation is performed against various metabolites at physiological concentrations (9 microM-8 mM). "Targeted profiling" is highly stable in PCA-based pattern recognition, insensitive to water suppression, relaxation times (within the ranges examined), and scaling factors; hence, direct comparison of data acquired under varying conditions is made possible. In particular, analysis of metabolites at low concentration and overlapping regions are well suited to this analysis. We discuss how targeted profiling can be applied for mixture analysis and examine the effect of various acquisition parameters on the accuracy of quantification.     

Experimental studies of hydrogen on boron nitride: II. NMR studies of orientational ordering of H2

We report the results of NMR studies of thin films of hydrogen adsorbed on hexagonal boron nitride. Orientational ordering is observed below 1 K but the ordering is not complete, and a clear two-component ordering is observed. Molecules are either (i) almost completely ordered with local order parameters = 1 – 3/2Jz ² clustered close to a maximum value of a 0.94 (comparable to the values for long range ordering in bulk samples at high ortho concentrations), and (ii) a large fraction of the molecules that remain nearly disordered with 0.25. The degree of Orientational ordering depends on the number of hydrogen layers and on the ortho-hydrogen concentration, and these studies indicate that ordering occurs principally in the first four layers closest to the substrate, with weaker Orientational ordering in the outer layers near the free surface even at temperatures as low as 210 mK.     

Hyphenation of capillary HPLC to microcoil (1)H NMR spectroscopy for the determination of tocopherol homologues

Highly selective reversed phases (C(30) phases) are self-packed in 250 microm inner diameter fused-silica capillaries and employed for capillary HPLC separation of shape-constrained natural compounds (tocopherol homologues, vitamin E). Miniaturized hyphenated systems such as capillary HPLC-ESI-MS (positive ionization mode) and, with special emphasis, continuous-flow capillary HPLC- NMR are used for structural determination of the separated compounds. Despite the small amount of sample available (1.33 microg of each tocopherol), the authors have been able to monitor the capillary HPLC separation under continuous-flow (1)H NMR conditions, thus allowing an immediate peak identification. Further structural assignment was carried out in the stopped-flow NMR mode as shown, for example, by a 2D (1)H,(1)H COSY NMR spectrum of alpha-tocopherol. We demonstrate in this paper the considerable potential of hyphenated capillary separations coupled to MS and NMR for the investigation of restricted amounts of sample.     

Mesoporous nickel (or cobolt)-doped silica-pillared clay: Synthesis and characterization studies

The metals-doped silica-pillared clay (SPC) materials with ordered pore structure in the gallery were obtained by a surfactant-directed assembly of silica species in the interlayer space of natural montmorillonite (MMT). The novel method afforded SPC derivatives with basal spacings of 4.4-4.5 nm, BET specific surface areas of 382.4-472.6 m²/g, pore volumes of 0.64-0.71 cm³ g⁻¹ and uniform pores (3.6 nm) between the layers. The main nickel and cobalt species was tetrahedrally coordinated Ni²⁺ or Co²⁺ in the gallery silica framework. Our results indicate that surfactant plays a decisive role in pore formation, because in acts as a micelle-like template during the hydrolysis of TEOS. In particular, the formation of metal-ammonia complex and rapid adsorption by surfactant in galleries controls metal species outflow from interlayers and contributes to the formation of metal species containing firm silica-pillars.     

Surface-modified superparamagnetic nanoparticles for drug delivery: preparation, characterization, and cytotoxicity studies

Superparamagnetic iron oxide nanoparticles have been used for many years as magnetic resonance imaging (MRI) contrast agents or in drug delivery applications. In this study, a novel approach to prepare magnetic polymeric nanoparticles with magnetic core and polymeric shell using inverse microemulsion polymerization process is reported. Poly(ethyleneglycol) (PEG)-modified superparamagnetic iron oxide nanoparticles with specific shape and size have been prepared inside the aqueous cores of AOT/n-Hexane reverse micelles and characterized by various physicochemical means such as transmission electron microscopy (TEM), infrared spectroscopy, atomic force microscopy (AFM), vibrating sample magnetometry (VSM), and ultraviolet/visible spectroscopy. The inverse microemulsion polymerization of a polymerizable derivative of PEG and a cross-linking agent resulted in a stable hydrophilic polymeric shell of the nanoparticles. The results taken together from TEM and AFM studies showed that the particles are spherical in shape with core-shell structure. The average size of the PEG-modified nanoparticles was found to be around 40-50 nm with narrow size distribution. The magnetic measurement studies revealed the superparamagnetic behavior of the nanoparticles with saturation magnetization values between 45-50 electromagnetic units per gram. The cytotoxicity profile of the nanoparticles on human dermal fibroblasts as measured by standard 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay showed that the particles are nontoxic and may be useful for various in vivo and in vitro biomedical applications.