Quantitative analysis of low-field NMR signals in the time domain

Two novel methods are described for direct quantitative analysis of NMR free induction decay (FID) signals. The methods use adaptations of the generalized rank annihilation method (GRAM) and the direct exponential curve resolution algorithm (DECRA). With FID-GRAM, the Hankel matrix of the sample signal is compared with that of a reference mixture to obtain quantitative data about the components. With FID-DECRA, a single-sample FID matrix is split into two matrices, allowing quantitative recovery of decay constants and the individual signals in the FID. Inaccurate results were obtained with FID-GRAM when there were differences between the frequency or transverse relaxation time of signals for the reference and test samples. This problem does not arise with FID-DECRA, because comparison with a reference signal is unnecessary. Application of FID-DECRA to 19F NMR data, which contained overlapping signals from three components, gave concentrations comparable to those derived from partial least squares (PLS) analysis of the Fourier transformed spectra. However, the main advantage of FID-DECRA was that accurate (<5% error) and precise (2.3% RSD) results were obtained using only one calibration sample, whereas with PLS, a training set of 10 standard mixtures was used to give comparable accuracy and precision.     

Infrared and nuclear magnetic resonance spectroscopic study of secondary amide hydrogen bonding in benzoyl PABA derivatives (retinoids)

Attenuated total reflection (ATR) Fourier transform infrared (FT-IR) and nuclear magnetic resonance (NMR) data are used to characterize the hydrogen bonding of the secondary amide N-H group of several structurally similar benzoyl derivatives of p-aminobenzoic acid esters (retinoids) in chloroform solution. The amide N-H can form intermolecular hydrogen bonds to several proton acceptors in these molecules or it can form an intramolecular hydrogen bond to a fluorine or oxygen atom in some of the molecules. The concentration dependence of the solution N-H infrared absorption bands is used to determine the formation of intramolecular and/or intermolecular H-bonds. Proton NMR spectra were obtained from deuterated chloroform solutions and the sec-amide N-H resonance was assigned for each compound. The downfield shift in the N-H resonance is correlated to intramolecular H-bond formation. Also, the NMR spectra of fluorine-containing compounds provide J(F-H) through-space coupling values. Using infrared and NMR data, the relative intramolecular hydrogen bond strengths (N-H...F or N-H...O) of the compounds are approximately ranked.     

Quantitative 1H NMR with external standards: use in preparation of calibration solutions for algal toxins and other natural products

We examine the use of external standards for quantitative measurement by 1H NMR of solution concentrations of natural products and other low molecular weight, hydrogen-containing compounds and show that precision and accuracy ca. 1% is obtainable with a commercial 11.7 T spectrometer when standards and analytes are contained in separate but identical sealed precision glass NMR tubes. Numerous factors contributing to the intensity of the NMR signals are evaluated. Precise measurements of 360 degrees pulse lengths for each sample provide direct corrections for variations in probe Q-factor that enable samples in different solvents to be compared, provided single-coil excitation and detection is used throughout. Samples need not be prepared in deuterated solvents if the 1H spectra of the solvents are simple enough for peak suppression by presaturation. The approach is particularly suitable for hazardous materials kept in sealed tubes and for the preparation of certified calibration solution reference materials for use with LC-MS and other techniques where deuterated solvents should be avoided.     

Mass spectral metabonomics beyond elemental formula: chemical database querying by matching experimental with computational fragmentation spectra

Despite recent advances in NMR and mass spectrometry, the structural identification of organic compounds in complex biofluids remains a significant analytical challenge. For mass spectroscopy applications, chemical identification is generally limited to determination of elemental formula. Here we test the hypothesis that unknown chemical structures can be determined by matching their experimental collision-induced dissociation (CID) fragmentation spectra with computational fragmentation spectra of compounds retrieved from chemical databases. The monoisotopic molecular weights (MIMW +/- 10 ppm) of 102 "test" compounds were used to download 102 "bins" from the PubChem database. Each bin contained the corresponding test compound and, on average, 272 other candidate compounds, including 158 compounds having the same elemental formula as the test compound. Commercially available software was used to generate fragmentation spectra for all compounds in each of the 102 bins. Experimental CID spectra for each of the 102 test compounds were then compared to the computational spectra in order to rank candidate compounds based on number of fragment MIMW matches. This method returned the test compound as the highest ranking (or tied with the highest ranking) compound for 65 of the 102 bins. The test compound was ranked within the top 20 candidate compounds for 87 bins. In addition, the correct elemental formula was ranked first for 98 of 102 bins. Thus, matching experimental with computational fragmentation spectra is a valid method for rapidly discriminating among compounds having the same elemental formula and provides a novel approach for querying chemical databases for structural information.     

Large scale pesticide multiresidue methods in food combining liquid chromatography--time-of-flight mass spectrometry and tandem mass spectrometry

Liquid chromatography tandem mass spectrometry (LC-MS/MS) and liquid chromatography time-of-flight mass spectrometry (LC-TOFMS) are powerful and complementary techniques that can independently cover the majority of the challenges related with pesticide residue food control. The sequential combination of both systems benefits from their complementary advantages and assists to increase the performance and to simplify routine large scale pesticide multiresidue methods. The proposed approach consists of three stages: (1) automated pesticide screening by LC-TOFMS; (2) identification by LC-TOFMS accurate mass measurements; and (3) confirmation and quantitation by LC-MS/MS. We have developed a fast comprehensive (identification/confirmation + quantitation) automated screening method for 100 target pesticides in crops. In the first stage, a set of data including m/z accurate mass windows (within 20 mDa width) and retention time is obtained (using a standard solution containing all the targeted pesticides) in order to build the automated screening procedure, which is created automatically by assigning retention time and the m/z mass window for each target pesticide. Samples are then analyzed, and the method enables the screening and preliminary identification of the species first by retention time and m/z mass window, followed by subsequent identification (only if positive results) by LC-TOFMS accurate mass measurements. After that, final confirmation of the positive findings using two MRM transitions and accurate quantitation is performed by LC-MS/MS using a hybrid triple quadrupole linear ion trap (QqLIT) mass spectrometer. In addition, the use of this QqLIT instrument also offers additional advantageous scanning modes (enhanced product ion and MS3 modes) for confirmatory purposes in compounds with poor fragmentation. Examples of applications to real samples show the potential of the proposed approach, including the detection of nonselected "a priori" compounds as a typical case of retrospective evaluation of banned or misused substances.     

Automated microflow NMR: routine analysis of five-microliter samples

A microflow CapNMR probe double-tuned for 1H and 13C was installed on a 400-MHz NMR spectrometer and interfaced to an automated liquid handler. Individual samples dissolved in DMSO-d6 are submitted for NMR analysis in vials containing as little as 10 microL of sample. Sets of samples are submitted in a low-volume 384-well plate. Of the 10 microL of sample per well, as with vials, 5 microL is injected into the microflow NMR probe for analysis. For quality control of chemical libraries, 1D NMR spectra are acquired under full automation from 384-well plates on as many as 130 compounds within 24 h using 128 scans per spectrum and a sample-to-sample cycle time of approximately 11 min. Because of the low volume requirements and high mass sensitivity of the microflow NMR system, 30 nmol of a typical small molecule is sufficient to obtain high-quality, well-resolved, 1D proton or 2D COSY NMR spectra in approximately 6 or 20 min of data acquisition time per experiment, respectively. Implementation of pulse programs with automated solvent peak identification and suppression allow for reliable data collection, even for samples submitted in fully protonated DMSO. The automated microflow NMR system is controlled and monitored using web-based software.     

"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.     

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.     

Toward single-calibrant quantification in HPLC. A comparison of three detection strategies: evaporative light scattering, chemiluminescent nitrogen, and proton NMR

There is an urgent need for detection technologies that enable accurate and precise quantification of solutions containing small organic molecules in a manner that is rapid, cheap, non-labor-intensive, readily automated, and without a requirement for specific analyte standards. We provide a theoretical analysis that predicts that the logarithmic nature of the working domain of the evaporative light-scattering detector (ELSD) will normally bias toward underestimation of chromatographically resolved impurities, resulting in an overestimation of analyte purity. This analysis is confirmed by experiments with flow injection analysis (FIA) and gradient reversed-phase high performance liquid chromatography (RP-HPLC). Quantification is further compromised by the dependence of response parameters on the matrix composition and hence on the retention time of the analyte. Attempts were made to ameliorate these problems by using the response surface of a single compound to calibrate throughout the HPLC gradient. A chemiluminescent nitrogen detector (CLND) was also used in a similar manner, and the performance of the two techniques were compared against those of each other and that of a reference standard technique. A protocol for this purpose was developed using proton nuclear magnetic resonance (1H NMR) and the ERETIC method to enable quantification by integrating proton signals. The double-blind comparison exercise confirmed molar nitrogen CLND response to be sufficiently stable and robust across a methanol gradient to be used with a single external nitrogenous calibrant to quantify nitrogen-containing compounds of known molecular formula. The performance of HPLC-CLND was very similar to that of NMR, while that of HPLC-ELSD was seen to be significantly worse, showing it to be unsuitable for the purpose of single-calibrant quantification. We report details and experience of our use of RP-HPLC-CLND-MS to characterize and quantify small amounts of solutions of novel compounds at nominal levels of 10mM in microtiter plate (MTP) format.     

Magic angle spinning NMR and 1H-31P heteronuclear statistical total correlation spectroscopy of intact human gut biopsies

Previously we have demonstrated the use of 1H magic angle spinning (MAS) NMR spectroscopy for the topographical variations in functional metabolic signatures of intact human intestinal biopsy samples. Here we have analyzed a series of MAS 1H NMR spectra (spin-echo, one-dimensional, and diffusion-edited) and 31P-{1H} spectra and focused on analyzing the enhancement of information recovery by use of the statistical total correlation spectroscopy (STOCSY) method. We have applied a heterospectroscopic cross-examination performed on the same samples and between 1H and 31P-{1H} spectra (heteronuclear STOCSY) to recover latent metabolic information. We show that heterospectroscopic correlation can give new information on the molecular compartmentation of metabolites in intact tissues, including the statistical "isolation" of a phospholipid/triglyceride vesicle pool in intact tissue. The application of 31P-1H HET-STOCSY allowed the cross-assignment of major 31P signals to their equivalent 1H NMR spectra, e.g., for phosphorylcholine and phosphorylethanolamine. We also show pathway correlations, e.g., the ascorbate-glutathione pathway, in the STOCSY analysis of intact tissue spectra. These 31P-1H HET-STOCSY spectra also showed different topographical regions, particular for minor signals in different tissue microenvironments. This approach could be extended to allow the detection of altered distributions within metabolic subcompartments as well as conventional metabonomics concentration-based diagnostics.     

Spectrophotometric and chemometric studies on the simultaneous determination of two benzodiazepines in human plasma

A numerical simple, accurate and precise method based on spectrophotometric data coupled with multivariate calibration methods, PLS and MLR, combined with GA was developed for the simultaneous determination of two benzodiazepines, Clobazam and Flurazepam. A data set of absorption spectra obtained from a calibration set of mixtures containing the compounds was used to build GA-PLS and GA-MLR models. The models were tested using a dataset constructed from the compound synthetic solutions. The better model was also applied to plasma samples. The proposed method requires no preliminary separation steps and can be used for these drugs analysis in quality control laboratories.     

Molecular factor analysis applied to collections of NMR spectra

It is often useful to identify and quantify mixture components by analyzing collections of NMR spectra. Such collections arise in metabonomics and many other applications. Many mixtures studied by NMR can contain hundreds of compounds, and it is challenging to analyze the resulting complex spectra. We have approached the problem of separating signals from different molecules in complex mixtures by using self-modeling curve resolution as implemented by the alternating least-squares algorithm. Alternating least squares uses nonnegativity criteria to generate spectra and concentrations from a collection of mixture spectra. Compared to previous applications of alternating least squares, NMR spectra of complex mixtures possess unique features, such as large numbers of components and sample-to-sample variability in peak positions. To deal with these features, we developed a set of data preprocessing methods, and we made modifications to the alternating least-squares algorithm. We use the term "molecular factor analysis" to refer to the preprocessing and modified alternating least-squares methods. Molecular factor analysis was tested using an artificial data set and spectra from a metabonomics study. The results show that the tools can extract valuable information on sample composition from sets of NMR spectra.     

Cryogenic probe 13C NMR spectroscopy of urine for metabonomic studies

Cryogenic probe technology can significantly compensate for the inherently low sensitivity of natural abundance 13C NMR spectroscopy. This now permits its routine use in NMR spectroscopy of biofluids, such as urine or plasma, with acquisition times that enable a high throughput of samples. Metabonomic studies often generate numerous samples in order to characterize fully the time-dependent biochemical response to stimuli, but until now, they have been largely conducted using 1H NMR spectroscopy because of its high sensitivity and hence efficient data acquisition. Here, we demonstrate that information-rich 13C NMR spectra of rat urine can be obtained using appropriately short acquisition times suitable for biochemical samples when using a cryogenic probe. Furthermore, these data were amenable to automated pattern recognition analysis, which produced a profile of the metabolic response to the model hepatotoxin hydrazine that was consistent with earlier studies. Thus, a new source of detailed and complementary information is available to metabonomics using cryogenic probe 13C NMR spectroscopy.     

Streamlined system for purifying and quantifying a diverse library of compounds and the effect of compound concentration measurements on the accurate interpretation of biological assay results

As part of an overall systems approach to generating highly accurate screening data across large numbers of compounds and biological targets, we have developed and implemented streamlined methods for purifying and quantitating compounds at various stages of the screening process, coupled with automated "traditional" storage methods (DMSO, -20 degrees C). Specifically, all of the compounds in our druglike library are purified by LC/MS/UV and are then controlled for identity and concentration in their respective DMSO stock solutions by chemiluminescent nitrogen detection (CLND)/evaporative light scattering detection (ELSD) and MS/UV. In addition, the compound-buffer solutions used in the various biological assays are quantitated by LC/UV/CLND to determine the concentration of compound actually present during screening. Our results show that LC/UV/CLND/ELSD/MS is a widely applicable method that can be used to purify, quantitate, and identify most small organic molecules from compound libraries. The LC/UV/CLND technique is a simple and sensitive method that can be easily and cost-effectively employed to rapidly determine the concentrations of even small amounts of any N-containing compound in aqueous solution. We present data to establish error limits for concentration determination that are well within the overall variability of the screening process. This study demonstrates that there is a significant difference between the predicted amount of soluble compound from stock DMSO solutions following dilution into assay buffer and the actual amount present in assay buffer solutions, even at the low concentrations employed for the assays. We also demonstrate that knowledge of the concentrations of compounds to which the biological target is exposed is critical for accurate potency determinations. Accurate potency values are in turn particularly important for drug discovery, for understanding structure-activity relationships, and for building useful empirical models of protein-ligand interactions. Our new understanding of relative solubility demonstrates that most, if not all, decisions that are made in early discovery are based upon missing or inaccurate information. Finally, we demonstrate that careful control of compound handling and concentration, coupled with accurate assay methods, allows the use of both positive and negative data in analyzing screening data sets for structure-activity relationships that determine potency and selectivity.     

Chemical concentration measurement in blood serum and urine samples using liquid-core optical fiber Raman spectroscopy

We report measurements of chemical concentrations in clinical blood serum and urine samples using liquid-core optical fiber (LCOF) Raman spectroscopy to increase the collected signal strength. Both Raman and absorption spectra were acquired in the near-infrared region using the LCOF geometry. Spectra of 71 blood serum and 61 urine samples were regressed via partial least squares against reference analyzer values. Significant correlation was found between predicted and reference concentrations for 13 chemicals. Using absorption data to normalize the LCOF enhancement made the results more accurate. The experimental geometry is well suited for high-volume and automated chemical analysis of clear biofluids.     

A computer-assisted structure elucidation scheme based upon the pattern of assembly of peaks in carbon-13/ proton NMR spectra

Hashimoto, M.S., Tanaka, Y., Sasabuchi, H. and Hattori, C.F., 1989. A computer-assisted structure elucidation scheme based upon the pattern of assembly of peaks in carbon-13/proton NMR spectra. Chemometrics and Intelligent Laboratory Systems, 6: 143–155.The basic idea reported previously in the qualitative analysis of carbon-13 NMR spectra by a computer-assisted structure elucidation scheme was extended so that it is now applicable to proton NMR spectra.Peaks in proton NMR spectra were grouped into several multiple bands with an evaluation of whether the peaks are close to each other within ± σ ppm, or not. The multiple bands were further patterned to rectangles, of which the widths and lengths correspond to the patterned multiplicities and the intensities of the maximum peaks in the groups.The patterned spectra of unknown compounds were compared with those of reference spectra by evaluating the quantities proportional to the reciprocal of the difference of chemical shifts, that of the multiplicities and that of the intensities of the unknown and the reference spectra.The applicability of this method was examined for steroid compounds and it was shown that the method can be used for structure elucidation problems.     

Robust algorithms for automated chemical shift calibration of 1D 1H NMR spectra of blood serum

In biofluid NMR spectroscopy, the frequency of each resonance is typically calibrated by addition of a reference compound such as 3-(trimethylsilyl)-propionic acid- d 4 (TSP) to the sample. However biofluids such as serum cannot be referenced to TSP, due to shifts resonance caused by binding to macromolecules in solution. In order to overcome this limitation we have developed algorithms, based on analysis of derivative spectra, to locate and calibrate (1)H NMR spectra to the alpha-glucose anomeric doublet. We successfully used these algorithms to calibrate 77 serum (1)H NMR spectra and demonstrate the greater reproducibility of the calculated chemical-shift corrections ( r = 0.97) than those generated by manual alignment ( r = 0.8-0.88). Hence we show that these algorithms provide robust and reproducible methods of calibrating (1)H NMR of serum, plasma, or any biofluid in which glucose is abundant. Precise automated calibration of complex biofluid NMR spectra is an important tool in large-scale metabonomic or metabolomic studies, where hundreds or even thousands of spectra may be analyzed in high-resolution by pattern recognition analysis.     

Measurement of absolute concentrations of individual compounds in metabolite mixtures by gradient-selective time-zero 1H-13C HSQC with two concentration references and fast maximum likelihood reconstruction analysis

Time-zero 2D (13)C HSQC (HSQC(0)) spectroscopy offers advantages over traditional 2D NMR for quantitative analysis of solutions containing a mixture of compounds because the signal intensities are directly proportional to the concentrations of the constituents. The HSQC(0) spectrum is derived from a series of spectra collected with increasing repetition times within the basic HSQC block by extrapolating the repetition time to zero. Here we present an alternative approach to data collection, gradient-selective time-zero (1)H-(13)C HSQC(0) in combination with fast maximum likelihood reconstruction (FMLR) data analysis and the use of two concentration references for absolute concentration determination. Gradient-selective data acquisition results in cleaner spectra, and NMR data can be acquired in both constant-time and non-constant-time mode. Semiautomatic data analysis is supported by the FMLR approach, which is used to deconvolute the spectra and extract peak volumes. The peak volumes obtained from this analysis are converted to absolute concentrations by reference to the peak volumes of two internal reference compounds of known concentration: DSS (4,4-dimethyl-4-silapentane-1-sulfonic acid) at the low concentration limit (which also serves as chemical shift reference) and MES (2-(N-morpholino)ethanesulfonic acid) at the high concentration limit. The linear relationship between peak volumes and concentration is better defined with two references than with one, and the measured absolute concentrations of individual compounds in the mixture are more accurate. We compare results from semiautomated gsHSQC(0) with those obtained by the original manual phase-cycled HSQC(0) approach. The new approach is suitable for automatic metabolite profiling by simultaneous quantification of multiple metabolites in a complex mixture.     

A structural mass spectrometry strategy for the relative quantitation of ligands on mixed monolayer-protected gold nanoparticles

It is becoming increasingly common to use gold nanoparticles (AuNPs) protected by a heterogeneous mixture of thiolate ligands, but many ligand mixtures on AuNPs cannot be properly characterized due to the inherent limitations of commonly used spectroscopic techniques. Using ion mobility-mass spectrometry (IM-MS), we have developed a strategy that allows measurement of the relative quantity of ligands on AuNP surfaces. This strategy is used for the characterization of three samples of mixed-ligand AuNPs: tiopronin:glutathione (av diameter 2.5 nm), octanethiol:decanethiol (av diameter 3.6 nm), and tiopronin:11-mercaptoundecyl(poly ethylene glycol) (av diameter 2.5 nm). For validation purposes, the results obtained for tiopronin:glutathione AuNPs were compared to parallel measurements using nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) without ion mobility separation. Relative quantitation measurements for NMR and IM-MS were in excellent agreement, with an average difference of less than 1% relative abundance. IM-MS and MS without ion mobility separation were not comparable, due to a lack of ion signals for MS. The other two mixed-ligand AuNPs provide examples of measurements that cannot be performed using NMR spectroscopy.     

LC-UV-solid-phase extraction-NMR-MS combined with a cryogenic flow probe and its application to the identification of compounds present in Greek oregano

Structure elucidation of natural products usually relies on a combination of NMR spectroscopy with mass spectrometry whereby NMR trails MS in terms of the minimum sample amount required. In the present study, the usefulness of on-line solid-phase extraction (SPE) in LC-NMR for peak storage after the LC separation prior to NMR analysis is demonstrated. The SPE unit allows the use of normal protonated solvents for the LC separation and fully deuterated solvents for flushing the trapped compounds to the NMR probe. Thus, solvent suppression is no longer necessary. Multiple trapping of the same analyte from repeated LC injections was utilized to solve the problem of low concentration and to obtain 2D heteronuclear NMR spectra. In addition, a combination of the SPE unit with a recently developed cryoflow NMR probe and an MS was evaluated. This on-line LC-UV-SPE-NMR-MS system was used for the automated analysis of a Greek oregano extract. Combining the data provided by the UV, MS, and NMR spectra, the flavonoids taxifolin, aromadendrin, eriodictyol, naringenin, and apigenin, the phenolic acid rosmarinic acid, and the monoterpene carvacrol were identified. This automated technique is very useful for natural product analysis, and the large sensitivity improvement leads to significantly reduced NMR acquisition times.