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.     

NMR detection with multiple solenoidal microcoils for continuous-flow capillary electrophoresis

Nuclear magnetic resonance (NMR) spectroscopy represents a promising on-line detector for capillary electrophoresis (CE). The inherent poor sensitivity of NMR mandates the use of NMR probes with the highest mass sensitivity, such as those containing solenoidal microcoils, for CE/NMR hyphenation. However, electrophoretic current degrades the resolution of NMR spectra obtained from solenoidal coils. A new method to avoid microcoil NMR spectral degradation during continuous-flow CE is demonstrated using a unique multiple solenoidal coil NMR probe. The electrophoretic flow from a single separation capillary is split into multiple outlets, each possessing its own NMR detection coil. While the CE electrophoretic flow is directed through one outlet, stopped-flow, high-resolution NMR spectra are obtained from the coil at the other outlet. The electrophoretic flow and NMR measurements are cycled between the outlets to allow a continuous CE separation with "stopped-flow" detection. As a new approach for improving multiple coil probe performance, the magnetic field homogeneity is automatically adjusted (via the shim coils of the magnet) for the active coil. The multiple microcoil CE/NMR coupling has been used to analyze a <3 nmole mixture of amines while obtaining between 1 and 2 Hz line width, demonstrating the ability to avoid electrophoretic current-induced line broadening.     

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.     

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.     

High-resolution capillary tube NMR. A miniaturized 5-microL high-sensitivity TXI probe for mass-limited samples,off-line LC NMR,and HT NMR

A new triple-resonance (TXI) (1H, 13C, 15N) high-resolution nuclear magnetic resonance (NMR) capillary probe with 2.5-microL NMR-active sample volume (V(obs)) was built and tested for applications with mass- and volume-limited samples and for coupling of microbore liquid chromatography to NMR. This is the first microliter probe with optimized coil geometry for use with individual capillary tubes with an outer diameter of 1 mm. The 90 degree pulse lengths of the 1-mm microliter probe were below 2 micros for proton, below 8 micros for carbon, and below 20 micros for nitrogen, and a spectral line width at signal half-height below 1 Hz was obtained. Compared to a conventional 5-mm probe, the new 600-MHz 1-mm TXI microliter probe with z-gradient shows an increase in mass sensitivity by a factor of 5, corresponding to a 25-fold reduction in measuring time. The consumption of costly deuterated solvent is reduced by at least 2 orders of magnitude. The 1-mm TXI microliter probe with z-gradient allows the measurement of one-dimensional 1H NMR and two-dimensional heteronuclear NMR spectra with a few nanomoles (micrograms) of compound with high sensitivity, speed, and quality. This is a breakthrough for discrete sample NMR spectroscopy with paramount importance for structure elucidation in natural compound chemistry and metabolic research. It offers also advantages for linking chromatographic methods to NMR in a nindustrial environment. Capillary tube NMR may find new applications in areas where high sample throughput is essential, e.g., in the quality control of large sample arrays from parallel chemistry, screening, and compound depositories. It has the potential to increase the sample throughput by 1 order of magnitude or more if new hardware for fast sample handling and exchange becomes available.     

Variable reference alignment: an improved peak alignment protocol for NMR spectral data with large intersample variation

In an effort to address the variable correspondence problem across large sample cohorts common in metabolomic/metabonomic studies, we have developed a prealignment protocol that aims to generate spectral segments sharing a common target spectrum. Under the assumption that a single reference spectrum will not correctly represent all spectra of a data set, the goal of this approach is to perform local alignment corrections on spectral regions which share a common "most similar" spectrum. A natural beneficial outcome of this procedure is the automatic definition of spectral segments, a feature that is not common to all alignment methods. This protocol is shown to specifically improve the quality of alignment in (1)H NMR data sets exhibiting large intersample compositional variation (e.g., pH, ionic strength). As a proof-of-principle demonstration, we have utilized two recently developed alignment algorithms specific to NMR data, recursive segment-wise peak alignment and interval correlated shifting, and applied them to two data sets composed of 15 aqueous cell line extract and 20 human urine (1)H NMR profiles. Application of this protocol represents a fundamental shift from current alignment methodologies that seek to correct misalignments utilizing a single representative spectrum, with the added benefit that it can be appended to any alignment algorithm.     

Micromixer-based time-resolved NMR: applications to ubiquitin protein conformation

Time-resolved NMR spectroscopy is used to studychanges in protein conformation based on the elapsed time after a change in the solvent composition of a protein solution. The use of a micromixer and a continuous-flow method is described where the contents of two capillary flows are mixed rapidly, and then the NMR spectra of the combined flow are recorded at precise time points. The distance after mixing the two fluids and flow rates define the solvent-protein interaction time; this method allows the measurement of NMR spectra at precise mixing time points independent of spectral acquisition time. Integration of a micromixer and a microcoil NMR probe enables low-microliter volumes to be used without losing significant sensitivity in the NMR measurement. Ubiquitin, the model compound, changes its conformation from native to A-state at low pH and in 40% or higher methanol/water solvents. Proton NMR resonances of the His-68 and the Tyr-59 of ubiquitin are used to probe the conformational changes. Mixing ubiquitin and methanol solutions under low pH at microliter per minute flow rates yields both native and A-states. As the flow rate decreases, yielding longer reaction times, the population of the A-state increases. The micromixer-NMR system can probe reaction kinetics on a time scale of seconds.     

Comprehensive extraction method integrated with NMR metabolomics: a new bioactivity screening method for plants, adenosine A1 receptor binding compounds in Orthosiphon stamineus Benth

A large number of plant metabolites has provided as an incomparable chemical source for drug development. However, the wide range of the polarity of metabolites has been a big obstacle for full use of the chemical diversity. The initial step conventional extraction method by a single solvent does not make use of all the metabolites contained in plants. Also, it takes a long time to confirm the target activity of a single compound because of tedious separation steps. To solve the problem, a new extraction method coupled to NMR-based metabolomics is applied to identify bioactive natural products. A comprehensive extraction method consisting of a continuous flow of solvent mixtures through plant material was developed to provide extracts with a wider chemical variety than those yielded with a single solvent extraction. As the model experiment, (1)H NMR spectra of the extracts obtained from the comprehensive extraction of Orthosiphon stamineus were subjected to multivariate data analysis to find its adenosine A1 binding activity. On the basis of the results, two flavonoids from a large number of chemicals were clearly verified to show the adenosine A1 binding activity without any further purification steps. This method could provide a solution to the major drawbacks of natural products in drug development.     

1, 5-Bis (2-hydroxyacetophenone)thiocarbohydrazone: A novel colorimetric and fluorescent dual-mode chemosensor for the recognition of fluoride

1,5-Bis (2-hydroxyacetophenone)thiocarbohydrazone (H₄L) has been synthesized and characterized by means of spectroscopic and single crystal X-ray diffraction methods. Interactions of the H₄L with a variety of anions were investigated using a combination of UV–visible and fluorescence spectroscopic methods in a biological competing solvent DMSO. The H₄L has a high degree of selectivity for fluoride over other anions. ¹H NMR titration experiments indicate that a deprotonation process is involved in the chemo sensing process.     

Binder distribution in Si3N4 ceramic green bodies studied by stray-field NMR imaging

Nuclear magnetic resonance (NMR) imaging is an emerging technology which provides a unique material-diagnostic technique by in situ internal mapping. It can provide information not only on material distribution, but also on the chemical and physical characteristics of materials. However, due to the nuclear dipole dipole interaction in solid state materials, NMR spectroscopic signals are normally very broad. NMR imaging based on these unresolved broad lines is extremely difficult, and resolution is poor. The binder distribution was studied in ceramic green bodies with a stray-field NMR imaging facility at a proton frequency of 163 MHz near the edge of a 9.394 T superconducting magnet. The ¹H nuclear spin echo signal from silicon nitride green bodies containing 10 wt% of either polyethylene glycol or polyvinyl alcohol as a binder was detected at 163 MHz. NMR images show a good homogeneity of the binder distribution in the cross-sections of the samples. Overall results show that the distribution of polyethylene glycol in Si₃N₄ green bodies is more homogeneous than that of polyvinyl alcohol under similar processing parameters. NMR spectroscopic results also indicate a higher moisture content in the green bodies containing a polyvinyl alcohol binder.     

核磁共振研究聚氨酯结构

利用超导核磁共振（ＮＭＲ）测定了各种类型的聚氨酯的＾１Ｈ和＾１３Ｃ谱，得到了一系列聚氨酯的ＮＭＲ化学位移数据，可用于未知结构的聚氨酯结构鉴定，同时对鉴定工作中遇到的问题作了一系列阐述。     

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.     

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.     

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.     

NMR metabolomics of planktonic and biofilm modes of growth in Pseudomonas aeruginosa

Bacteria often reside in communities where the cells have secreted sticky, polymeric compounds that allow them to attach to surfaces. This sessile lifestyle, referred to as a biofilm, affords the cells within these communities a tolerance of antibiotics and antimicrobial treatments. Biofilms of the bacterium Pseudomonas aeruginosa have been implicated in cystic fibrosis and are capable of colonizing medical implant devices, such as heart valves and catheters, where treatment of the infection often requires the removal of the infected device. This mode of growth is in stark contrast to planktonic, free floating cells, which are more easily eradicated with antibiotics. The mechanisms contributing to a biofilm's tenacity and a planktonic cell's susceptibility are just beginning to be explored. In this study, we have used a metabolomic approach employing nuclear magnetic resonance (NMR) techniques to study the metabolic distinctions between these two modes of growth in P. aeruginosa. One-dimensional 1H NMR spectra of fresh growth medium were compared with spent medium supernatants from batch and chemostat planktonic and biofilms generated in continual flow system culture. In addition, 1H high-resolution magic angle spinning NMR techniques were employed to collect 1H NMR spectra of the corresponding cells. Principal component analysis and spectral comparisons revealed that the overall metabolism of planktonic and biofilm modes of growth appeared similar for the spent media, while the planktonic and biofilm cells displayed marked differences. To determine the robustness of this technique, we prepared cell samples under slightly different preparation methods. Both techniques showed similar results. These feasibility studies show that there exist chemical differences between planktonic and biofilm cells; however, in order to identify these metabolomic differences, more extensive studies would have to be performed, including 1H-1H total correlated spectroscopy.     

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.     

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.     

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.