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.
ABSTRACT: 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.
Project description:Quantitative one-dimensional (1D) (1)H NMR spectroscopy is a useful tool for determining metabolite concentrations because of the direct proportionality of signal intensity to the quantity of analyte. However, severe signal overlap in 1D (1)H NMR spectra of complex metabolite mixtures hinders accurate quantification. Extension of 1D (1)H to 2D (1)H-(13)C HSQC leads to the dispersion of peaks along the (13)C dimension and greatly alleviates peak overlapping. Although peaks are better resolved in 2D (1)H-(13)C HSQC than in 1D (1)H NMR spectra, the simple proportionality of cross peaks to the quantity of individual metabolites is lost by resonance-specific signal attenuation during the coherence transfer periods. As a result, peaks for individual metabolites usually are quantified by reference to calibration data collected from samples of known concentration. We show here that data from a series of HSQC spectra acquired with incremented repetition times (the time between the end of the first (1)H excitation pulse to the beginning of data acquisition) can be extrapolated back to zero time to yield a time-zero 2D (1)H-(13)C HSQC spectrum (HSQC(0)) in which signal intensities are proportional to concentrations of individual metabolites. Relative concentrations determined from cross peak intensities can be converted to absolute concentrations by reference to an internal standard of known concentration. Clustering of the HSQC(0) cross peaks by their normalized intensities identifies those corresponding to metabolites present at a given concentration, and this information can assist in assigning these peaks to specific compounds. The concentration measurement for an individual metabolite can be improved by averaging the intensities of multiple, nonoverlapping cross peaks assigned to that metabolite.
Project description:BACKGROUND: One-dimensional (1D) 1H nuclear magnetic resonance (NMR) spectroscopy is widely used in metabolomic studies involving biofluids and tissue extracts. There are several software packages that support compound identification and quantification via 1D 1H NMR by spectral fitting techniques. Because 1D 1H NMR spectra are characterized by extensive peak overlap or spectral congestion, two-dimensional (2D) NMR, with its increased spectral resolution, could potentially improve and even automate compound identification or quantification. However, the lack of dedicated software for this purpose significantly restricts the application of 2D NMR methods to most metabolomic studies. RESULTS: We describe a standalone graphics software tool, called MetaboMiner, which can be used to automatically or semi-automatically identify metabolites in complex biofluids from 2D NMR spectra. MetaboMiner is able to handle both 1H-1H total correlation spectroscopy (TOCSY) and 1H-13C heteronuclear single quantum correlation (HSQC) data. It identifies compounds by comparing 2D spectral patterns in the NMR spectrum of the biofluid mixture with specially constructed libraries containing reference spectra of approximately 500 pure compounds. Tests using a variety of synthetic and real spectra of compound mixtures showed that MetaboMiner is able to identify >80% of detectable metabolites from good quality NMR spectra. CONCLUSION: MetaboMiner is a freely available, easy-to-use, NMR-based metabolomics tool that facilitates automatic peak processing, rapid compound identification, and facile spectrum annotation from either 2D TOCSY or HSQC spectra. Using comprehensive reference libraries coupled with robust algorithms for peak matching and compound identification, the program greatly simplifies the process of metabolite identification in complex 2D NMR spectra.
Project description:A new metabolomics database and query algorithm for the analysis of (13)C-(1)H HSQC spectra is introduced, which unifies NMR spectroscopic information on 555 metabolites from both the Biological Magnetic Resonance Data Bank (BMRB) and Human Metabolome Database (HMDB). The new database, termed Complex Mixture Analysis by NMR (COLMAR) (13)C-(1)H HSQC database, can be queried via an interactive, easy to use web interface at http://spin.ccic.ohio-state.edu/index.php/hsqc/index . Our new HSQC database separately treats slowly exchanging isomers that belong to the same metabolite, which permits improved query in cases where lowly populated isomers are below the HSQC detection limit. The performance of our new database and query web server compares favorably with the one of existing web servers, especially for spectra of samples of high complexity, including metabolite mixtures from the model organisms Drosophila melanogaster and Escherichia coli. For such samples, our web server has on average a 37% higher accuracy (true positive rate) and a 82% lower false positive rate, which makes it a useful tool for the rapid and accurate identification of metabolites from (13)C-(1)H HSQC spectra at natural abundance. This information can be combined and validated with NMR data from 2D TOCSY-type spectra that provide connectivity information not present in HSQC spectra.
Project description:Identification and quantification of analytes in complex solution-state mixtures are critical procedures in many areas of chemistry, biology, and molecular medicine. Nuclear magnetic resonance (NMR) is a unique tool for this purpose providing a wealth of atomic-detail information without requiring extensive fractionation of the samples. We present three new multidimensional-NMR based approaches that are geared toward the analysis of mixtures with high complexity at natural (13)C abundance, including approaches that are encountered in metabolomics. Common to all three approaches is the concept of the extraction of one-dimensional (1D) consensus spectral traces or 2D consensus planes followed by clustering, which significantly improves the capability to identify mixture components that are affected by strong spectral overlap. The methods are demonstrated for covariance (1)H-(1)H TOCSY and (13)C-(1)H HSQC-TOCSY spectra and triple-rank correlation spectra constructed from pairs of (13)C-(1)H HSQC and (13)C-(1)H HSQC-TOCSY spectra. All methods are first demonstrated for an eight-compound metabolite model mixture before being applied to an extract from E. coli cell lysate.
Project description:2D NMR (1)H-X (X=(15)N or (13)C) HSQC spectra contain cross-peaks for all XHn moieties. Multiplicity-edited(1)H-(13)C HSQC pulse sequences generate opposite signs between peaks of CH(2) and CH/CH(3) at a cost of lower signal-to-noise due to the (13)C T(2) relaxation during an additional 1/(1)JCH period. Such CHn-editing experiments are useful in assignment of chemical shifts and have been successfully applied to small molecules and small proteins (e.g. ubiquitin) dissolved in deuterated solvents where, generally, peak overlap is minimal. By contrast, for larger biomolecules, peak overlap in 2D HSQC spectra is unavoidable and peaks with opposite phases cancel each other out in the edited spectra. However, there is an increasing need for using NMR to profile biomolecules at natural abundance dissolved in water (e.g., protein therapeutics) where NMR experiments beyond 2D are impractical. Therefore, the existing 2D multiplicity-edited HSQC methods must be improved to acquire data on nuclei other than (13)C (i.e.(15)N), to resolve more peaks, to reduce T(2) losses and to accommodate water suppression approaches. To meet these needs, a multiplicity-separated(1)H-X HSQC (MS-HSQC) experiment was developed and tested on 500 and 700 MHz NMR spectrometers equipped with room temperature probes using RNase A (14 kDa) and retroviral capsid (26 kDa) proteins dissolved in 95% H(2)O/5% D(2)O. In this pulse sequence, the 1/(1)JXH editing-period is incorporated in to the semi-constant time (semi-CT) X resonance chemical shift evolution period, which increases sensitivity, and importantly, the sum and the difference of the interleaved (1)J(XH)-active and the (1)J(XH)-inactive HSQC experiments yield two separate spectra for XH(2) and XH/XH(3). Furthermore we demonstrate improved water suppression using triple xyz-gradients instead of the more widely used z-gradient only water-suppression approach.
Project description:HSQC spectra are routinely acquired for chemical structure analysis based on hydrogen and carbon chemical environments. Two fast HSQC peak matching algorithms have been developed; a nearest neighbour approach and a probabilistic method based on an existing discrete genetic algorithm. Both of these techniques are intended to find HSQC spectra matches that supplement information generated by established molecular fingerprint methods. Our results are compared to those calculated using a specific implementation of molecular fingerprints. The nearest neighbour and genetic algorithm-based methods ranked highly particular structures missed by molecular fingerprints. Our analysis shows that by complementing molecular fingerprint matches with our findings, a comprehensive list of matches can be identified. The refined list of compounds could be used to improve the quality of compounds used in screening libraries in the pharmaceutical industry.
Project description:Four precise, accurate, selective, and sensitive UV-spectrophotometric methods were developed and validated for the simultaneous determination of a binary mixture of Oxytetracycline HCl (OXY) and Flunixin Meglumine (FLU). The first method, dual wavelength (DW), depends on measuring the difference in absorbance (ΔA 273.4-327 nm) for the determination of OXY where FLU is zero while FLU is determined at ΔA 251.7-275.7 nm. The second method, first-derivative spectrophotometric method (1D), depends on measuring the peak amplitude of the first derivative selectively at 377 and 266.7 nm for the determination of OXY and FLU, respectively. The third method, ratio difference method, depends on the difference in amplitudes of the ratio spectra at ΔP 286.5-324.8 nm and ΔP 249.6-286.3 nm for the determination of OXY and FLU, respectively. The fourth method, first derivative of ratio spectra method (1DD), depends on measuring the amplitude peak to peak of the first derivative of ratio spectra at 296.7 to 369 nm and 259.1 to 304.7 nm for the determination of OXY and FLU, respectively. Different factors affecting the applied spectrophotometric methods were studied. The proposed methods were validated according to ICH guidelines. Satisfactory results were obtained for determination of both drugs in laboratory prepared mixture and pharmaceutical dosage form. The developed methods are compared favourably with the official ones.
Project description:Analogous to the recently introduced ARTSY method for measurement of one-bond (1)H-(15)N residual dipolar couplings (RDCs) in large perdeuterated proteins, we introduce methods for measurement of base (13)C-(1)H and (15)N-(1)H RDCs in protonated nucleic acids. Measurements are based on quantitative analysis of intensities in (1)H-(15)N and (13)C-(1)H TROSY-HSQC spectra, and are illustrated for a 71-nucleotide adenine riboswitch. Results compare favorably with those of conventional frequency-based measurements in terms of completeness and convenience of use. The ARTSY method derives the size of the coupling from the ratio of intensities observed in two TROSY-HSQC spectra recorded with different dephasing delays, thereby minimizing potential resonance overlap problems. Precision of the RDC measurements is limited by the signal-to-noise ratio, S/N, achievable in the 2D TROSY-HSQC reference spectrum, and is approximately given by 30/(S/N) Hz for (15)N-(1)H and 65/(S/N) Hz for (13)C-(1)H. The signal-to-noise ratio of both (1)H-(15)N and (1)H-(13)C spectra greatly benefits when water magnetization during the experiments is not perturbed, such that rapid magnetization transfer from bulk water to the nucleic acid, mediated by rapid amino and hydroxyl hydrogen exchange coupled with (1)H-(1)H NOE transfer, allows for fast repetition of the experiment. RDCs in the mutated helix 1 of the riboswitch are compatible with nucleotide-specifically modeled, idealized A-form geometry and a static orientation relative to the helix 2/3 pair, which differs by ca 6° relative to the X-ray structure of the native riboswitch.
Project description:We present a simple method, ARTSY, for extracting ¹J(NH) couplings and ¹H-¹?N RDCs from an interleaved set of two-dimensional ¹H-¹?N TROSY-HSQC spectra, based on the principle of quantitative J correlation. The primary advantage of the ARTSY method over other methods is the ability to measure couplings without scaling peak positions or altering the narrow line widths characteristic of TROSY spectra. Accuracy of the method is demonstrated for the model system GB3. Application to the catalytic core domain of HIV integrase, a 36 kDa homodimer with unfavorable spectral characteristics, demonstrates its practical utility. Precision of the RDC measurement is limited by the signal-to-noise ratio, S/N, achievable in the 2D TROSY-HSQC spectrum, and is approximately given by 30/(S/N) Hz.
Project description:Higher-rank correlation spectroscopy is introduced as an alternative to 3D Fourier-transform (FT) NMR spectroscopy for resonance assignment and molecular structure determination. The method combines standard 2D FT spectra that share a common frequency dimension, such as a 2D (13)C-(1)H HSQC and a 2D (1)H-(1)H TOCSY spectrum, and constructs higher-rank correlation spectra with ultra-high spectral resolution. Spectral overlap along a common dimension, in particular the (1)H dimension, is addressed by a spectral filtering method, which identifies mismatches between the 1(st) and 2(nd) moments of cross-peak profiles. The method, which provides a substantial speed-up over traditional 3D FT spectroscopy while effectively suppressing false peaks, is demonstrated for the triple-rank (13)C-(1)H HSQC-TOCSY spectrum of a cyclic decapeptide with different mixing times. Higher-rank correlation spectroscopy is usefully applicable to the analysis of a wide range of NMR spectra of synthetic and natural products.