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Ma X, Li C, Zhang J, Xin J, Mosongo I, Yang J, Hu K. Monosaccharide composition analysis by 2D quantitative gsHSQC i. Carbohydr Res 2024; 541:109168. [PMID: 38833821 DOI: 10.1016/j.carres.2024.109168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2024] [Revised: 05/13/2024] [Accepted: 05/27/2024] [Indexed: 06/06/2024]
Abstract
The physicochemical properties and biological activities of polysaccharides depend on their structures. Monosaccharide composition analysis is indispensable for the structural characterization of polysaccharides and is helpful in the quality control of polysaccharide preparation. Here, using a model mixture and tamarind seed polysaccharide as examples, we demonstrated that a quantitative 2D NMR method, gsHSQCi (three gradient-selective Heteronuclear Single Quantum Coherence spectra acquired with incremented repetition times, i = 1, 2, 3) can directly quantify a variety of monosaccharides in solution with adequate precision and accuracy, requiring no derivatization, postprocessing steps and column separation. Both anomeric and non-anomeric signals of monosaccharides can be utilized for content determination. More accurate quantification of fructose in a mixture containing nine monosaccharides is obtained, which is difficult to achieve by quantitative 1D 1HNMR and the common PMP-HPLC method (high-performance liquid chromatography through pre-column derivatization with 1-phenyl-3-methyl-5-pyrazolone) due to the peak overlapping and the poor derivatization efficiency, respectively. The results also revealed that Na[Fe(EDTA)] can serve as a proper relaxation-enhancing agent for saccharide samples to save experimental time. We expect that this approach can be applied as an alternative to analyzing the monosaccharide composition and be helpful in interpreting the structure of polysaccharides.
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Affiliation(s)
- Xiaofang Ma
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 611137, China; Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 611137, China.
| | - Caihong Li
- School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 611137, China
| | - Junyin Zhang
- School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 611137, China
| | - Jiang Xin
- School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 611137, China
| | - Isidore Mosongo
- School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 611137, China
| | - Jiahui Yang
- School of Basic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 611137, China.
| | - Kaifeng Hu
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 611137, China; Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 611137, China.
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2
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Foster H, Nilsson M, Adams RW, Morris GA. Universally Quantitative Band-Selective Pure Shift NMR Spectroscopy. Anal Chem 2024; 96:9601-9609. [PMID: 38812212 PMCID: PMC11170551 DOI: 10.1021/acs.analchem.4c01199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 05/07/2024] [Accepted: 05/17/2024] [Indexed: 05/31/2024]
Abstract
NMR spectroscopy is often described as a quantitative analytical technique. Strictly, only the simple pulse-acquire experiment is universally quantitative, but the poor signal resolution of the 1H NMR pulse-acquie experiment frequently complicates quantitative analysis. Pure shift NMR techniques provide higher resolution, by reducing signal overlap, but they are susceptible to a variety of sources of site-dependent signal loss. Here, we introduce a new method that corrects for signal loss from such sources in band-selective pure shift NMR experiments, by performing different numbers of iterations of the same pulse sequence elements before acquisition to allow extrapolation back to the loss-free signal. We apply this method to both interferogram and semi-realtime acquisition modes, obtaining integrals within 1% of those acquired from a pulse-acquire experiment for a three-component mixture.
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Affiliation(s)
- Howard
M. Foster
- Department of Chemistry, The University of Manchester, Oxford Road, Manchester M13 9PL, U.K.
| | - Mathias Nilsson
- Department of Chemistry, The University of Manchester, Oxford Road, Manchester M13 9PL, U.K.
| | - Ralph W. Adams
- Department of Chemistry, The University of Manchester, Oxford Road, Manchester M13 9PL, U.K.
| | - Gareth A. Morris
- Department of Chemistry, The University of Manchester, Oxford Road, Manchester M13 9PL, U.K.
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3
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Chen X, Bertho G, Caradeuc C, Giraud N, Lucas-Torres C. Present and future of pure shift NMR in metabolomics. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2023; 61:654-673. [PMID: 37157858 DOI: 10.1002/mrc.5356] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 04/30/2023] [Accepted: 05/04/2023] [Indexed: 05/10/2023]
Abstract
NMR is one of the most powerful techniques for the analysis of biological samples in the field of metabolomics. However, the high complexity of fluids, tissues, or other biological materials taken from living organisms is still a challenge for state-of-the-art pulse sequences, thereby limiting the detection, the identification, and the quantification of metabolites. In this context, the resolution enhancement provided by broadband homonuclear decoupling methods, which allows for simplifying 1 H multiplet patterns into singlets, has placed this so-called pure shift technique as a promising approach to perform metabolic profiling with unparalleled level of detail. In recent years, the many advances achieved in the design of pure shift experiments has paved the way to the analysis of a wide range of biological samples with ultra-high resolution. This review leads the reader from the early days of the main pure shift methods that have been successfully developed over the last decades to address complex samples, to the most recent and promising applications of pure shift NMR to the field of NMR-based metabolomics.
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Affiliation(s)
- Xi Chen
- Université Paris Cité, CNRS, Laboratoire de Chimie et de Biochimie Pharmacologiques et Toxicologiques, Paris, France
| | - Gildas Bertho
- Université Paris Cité, CNRS, Laboratoire de Chimie et de Biochimie Pharmacologiques et Toxicologiques, Paris, France
| | - Cédric Caradeuc
- Université Paris Cité, CNRS, Laboratoire de Chimie et de Biochimie Pharmacologiques et Toxicologiques, Paris, France
| | - Nicolas Giraud
- Université Paris Cité, CNRS, Laboratoire de Chimie et de Biochimie Pharmacologiques et Toxicologiques, Paris, France
| | - Covadonga Lucas-Torres
- Université Paris Cité, CNRS, Laboratoire de Chimie et de Biochimie Pharmacologiques et Toxicologiques, Paris, France
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4
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Zhang C, Xu L, Huang Q, Wang Y, Tang H. Detecting Submicromolar Analytes in Mixtures with a 5 min Acquisition on 600 MHz NMR Spectrometers. J Am Chem Soc 2023; 145:25513-25517. [PMID: 37955622 DOI: 10.1021/jacs.3c07861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2023]
Abstract
Amino compounds are widely present in complex mixtures in chemistry, biology, medicine, food, and environmental sciences involving drug impurities and metabolisms of proteins, biogenic amines, neurotransmitters, and pyrimidine in biological systems. Nuclear magnetic resonance (NMR) spectroscopy is an excellent tool for simultaneously identifying and quantifying these in-mixture compounds but has a limit-of-detection (LOD) over several micromolarities (>5 μM). To break such a sensitivity barrier, we developed a sensitive and rapid method by combining the probe-induced sensitivity enhancement and nonuniform-sampling-based 1H-13C HSQC 2D-NMR (PRISE-NUS-HSQC). We introduced two 13CH3 tags for each analyte to respectively increase the 1H and 13C abundances for up to 6 and 200 fold. This enabled high-resolution detection of 0.4-0.8 μM analytes in mixtures in 5 mm tubes with a 5 min acquisition on 600 MHz spectrometers. The method is much more sensitive and faster than traditional 1H-13C HSQC methods (∼50 μM, >10 h). Using sulfanilic acid as a single reference, furthermore, we established a database covering chemical shifts and relative-response factors for >100 compounds, enabling reliable identification and quantification. The method showed good quantitation linearity, accuracy, precision, and applicability in multiple biological matrices, offering a rapid and sensitive approach for quantitative analysis of large cohorts of chemical, medicinal, metabolomic, food, and other mixtures.
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Affiliation(s)
- Congcong Zhang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai 200438, China
| | - Li Xu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai 200438, China
| | - Qingxia Huang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai 200438, China
| | - Yulan Wang
- Singapore Phenome Centre, Lee Kong Chian School of Medicine, Nanyang Technological University, 639798 Singapore
| | - Huiru Tang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai 200438, China
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5
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Praud C, Ribay V, Dey A, Charrier B, Mandral J, Farjon J, Dumez JN, Giraudeau P. Optimization of heteronuclear ultrafast 2D NMR for the study of complex mixtures hyperpolarized by dynamic nuclear polarization. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2023; 15:6209-6219. [PMID: 37942549 DOI: 10.1039/d3ay01681a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
Hyperpolarized 13C NMR at natural abundance, based on dissolution dynamic nuclear polarization (d-DNP), provides rich, sensitive and repeatable 13C NMR fingerprints of complex mixtures. However, the sensitivity enhancement is associated with challenges such as peak overlap and the difficulty to assign hyperpolarized 13C signals. Ultrafast (UF) 2D NMR spectroscopy makes it possible to record heteronuclear 2D maps of d-DNP hyperpolarized samples. Heteronuclear UF 2D NMR can provide correlation peaks that link quaternary carbons and protons through long-range scalar couplings. Here, we report the analytical assessment of an optimized UF long-range HETCOR pulse sequence, applied to the detection of metabolic mixtures at natural abundance and hyperpolarized by d-DNP, based on repeatability and sensitivity considerations. We show that metabolite-dependent limits of quantification in the range of 1-50 mM (in the sample before dissolution) can be achieved, with a repeatability close to 10% and a very good linearity. We provide a detailed comparison of such analytical performance in two different dissolution solvents, D2O and MeOD. The reported pulse sequence appears as an useful analytical tool to facilitate the assignment and integration of metabolite signals in hyperpolarized complex mixtures.
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Affiliation(s)
- Clément Praud
- Nantes Université, CNRS, CEISAM, UMR 6230, F-44000 Nantes, France.
| | - Victor Ribay
- Nantes Université, CNRS, CEISAM, UMR 6230, F-44000 Nantes, France.
| | - Arnab Dey
- Nantes Université, CNRS, CEISAM, UMR 6230, F-44000 Nantes, France.
| | - Benoît Charrier
- Nantes Université, CNRS, CEISAM, UMR 6230, F-44000 Nantes, France.
| | - Joris Mandral
- Nantes Université, CNRS, CEISAM, UMR 6230, F-44000 Nantes, France.
| | - Jonathan Farjon
- Nantes Université, CNRS, CEISAM, UMR 6230, F-44000 Nantes, France.
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6
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Metabolomics and modelling approaches for systems metabolic engineering. Metab Eng Commun 2022; 15:e00209. [PMID: 36281261 PMCID: PMC9587336 DOI: 10.1016/j.mec.2022.e00209] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 10/13/2022] [Accepted: 10/14/2022] [Indexed: 11/21/2022] Open
Abstract
Metabolic engineering involves the manipulation of microbes to produce desirable compounds through genetic engineering or synthetic biology approaches. Metabolomics involves the quantitation of intracellular and extracellular metabolites, where mass spectrometry and nuclear magnetic resonance based analytical instrumentation are often used. Here, the experimental designs, sample preparations, metabolite quenching and extraction are essential to the quantitative metabolomics workflow. The resultant metabolomics data can then be used with computational modelling approaches, such as kinetic and constraint-based modelling, to better understand underlying mechanisms and bottlenecks in the synthesis of desired compounds, thereby accelerating research through systems metabolic engineering. Constraint-based models, such as genome scale models, have been used successfully to enhance the yield of desired compounds from engineered microbes, however, unlike kinetic or dynamic models, constraint-based models do not incorporate regulatory effects. Nevertheless, the lack of time-series metabolomic data generation has hindered the usefulness of dynamic models till today. In this review, we show that improvements in automation, dynamic real-time analysis and high throughput workflows can drive the generation of more quality data for dynamic models through time-series metabolomics data generation. Spatial metabolomics also has the potential to be used as a complementary approach to conventional metabolomics, as it provides information on the localization of metabolites. However, more effort must be undertaken to identify metabolites from spatial metabolomics data derived through imaging mass spectrometry, where machine learning approaches could prove useful. On the other hand, single-cell metabolomics has also seen rapid growth, where understanding cell-cell heterogeneity can provide more insights into efficient metabolic engineering of microbes. Moving forward, with potential improvements in automation, dynamic real-time analysis, high throughput workflows, and spatial metabolomics, more data can be produced and studied using machine learning algorithms, in conjunction with dynamic models, to generate qualitative and quantitative predictions to advance metabolic engineering efforts.
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7
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Wishart DS, Cheng LL, Copié V, Edison AS, Eghbalnia HR, Hoch JC, Gouveia GJ, Pathmasiri W, Powers R, Schock TB, Sumner LW, Uchimiya M. NMR and Metabolomics-A Roadmap for the Future. Metabolites 2022; 12:678. [PMID: 35893244 PMCID: PMC9394421 DOI: 10.3390/metabo12080678] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 07/21/2022] [Accepted: 07/21/2022] [Indexed: 12/03/2022] Open
Abstract
Metabolomics investigates global metabolic alterations associated with chemical, biological, physiological, or pathological processes. These metabolic changes are measured with various analytical platforms including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance spectroscopy (NMR). While LC-MS methods are becoming increasingly popular in the field of metabolomics (accounting for more than 70% of published metabolomics studies to date), there are considerable benefits and advantages to NMR-based methods for metabolomic studies. In fact, according to PubMed, more than 926 papers on NMR-based metabolomics were published in 2021-the most ever published in a given year. This suggests that NMR-based metabolomics continues to grow and has plenty to offer to the scientific community. This perspective outlines the growing applications of NMR in metabolomics, highlights several recent advances in NMR technologies for metabolomics, and provides a roadmap for future advancements.
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Affiliation(s)
- David S. Wishart
- Departments of Biological Sciences and Computing Science, University of Alberta, Edmonton, AB T6G 2E9, Canada
| | - Leo L. Cheng
- Department of Pathology, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA;
| | - Valérie Copié
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT 59715, USA;
| | - Arthur S. Edison
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA; (A.S.E.); (G.J.G.); (M.U.)
- Department of Biochemistry & Molecular Biology, University of Georgia, Athens, GA 30602-0001, USA
| | - Hamid R. Eghbalnia
- Department of Molecular Biology and Biophysics, UConn Health, Farmington, CT 06030-3305, USA; (H.R.E.); (J.C.H.)
| | - Jeffrey C. Hoch
- Department of Molecular Biology and Biophysics, UConn Health, Farmington, CT 06030-3305, USA; (H.R.E.); (J.C.H.)
| | - Goncalo J. Gouveia
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA; (A.S.E.); (G.J.G.); (M.U.)
- Department of Biochemistry & Molecular Biology, University of Georgia, Athens, GA 30602-0001, USA
| | - Wimal Pathmasiri
- Nutrition Research Institute, Department of Nutrition, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA;
| | - Robert Powers
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA
- Nebraska Center for Integrated Biomolecular Communication, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA
| | - Tracey B. Schock
- National Institute of Standards and Technology (NIST), Chemical Sciences Division, Charleston, SC 29412, USA;
| | - Lloyd W. Sumner
- Interdisciplinary Plant Group, MU Metabolomics Center, Bond Life Sciences Center, Department of Biochemistry, University of Missouri, Columbia, MO 65211, USA
| | - Mario Uchimiya
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA; (A.S.E.); (G.J.G.); (M.U.)
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Automated metabolic assignment: Semi-supervised learning in metabolic analysis employing two dimensional Nuclear Magnetic Resonance (NMR). Comput Struct Biotechnol J 2021; 19:5047-5058. [PMID: 34589182 PMCID: PMC8455648 DOI: 10.1016/j.csbj.2021.08.048] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 08/29/2021] [Accepted: 08/30/2021] [Indexed: 12/20/2022] Open
Abstract
Automatic assignment of metabolites of 2D-TOCSY NMR spectra. Semi-supervised learning for metabolic profiling. Deconvolution and metabolic profiling of 2D NMR spectra using Machine Learning. Accurate Automatic multicomponent assignment of 2D NMR spectrum.
Metabolomics is an expanding field of medical diagnostics since many diseases cause metabolic reprogramming alteration. Additionally, the metabolic point of view offers an insight into the molecular mechanisms of diseases. Due to the complexity of metabolic assignment dependent on the 1D NMR spectral analysis, 2D NMR techniques are preferred because of spectral resolution issues. Thus, in this work, we introduce an automated metabolite identification and assignment from 1H-1H TOCSY (total correlation spectroscopy) using real breast cancer tissue. The new approach is based on customized and extended semi-supervised classifiers: KNFST, SVM, third (PC3) and fourth (PC4) degree polynomial. In our approach, metabolic assignment is based only on the vertical and horizontal frequencies of the metabolites in the 1H–1H TOCSY. KNFST and SVM show high performance (high accuracy and low mislabeling rate) in relatively low size of initially labeled training data. PC3 and PC4 classifiers showed lower accuracy and high mislabeling rates, and both classifiers fail to provide an acceptable accuracy at extremely low size (≤9% of the entire dataset) of initial training data. Additionally, semi-supervised classifiers were implemented to obtain a fully automatic procedure for signal assignment and deconvolution of TOCSY, which is a big step forward in NMR metabolic profiling. A set of 27 metabolites were deduced from the TOCSY, and their assignments agreed with the metabolites deduced from a 1D NMR spectrum of the same sample analyzed by conventional human-based methodology.
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9
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Kaup KK, Toom L, Truu L, Miller S, Puurand M, Tepp K, Käämbre T, Reile I. A line-broadening free real-time 31P pure shift NMR method for phosphometabolomic analysis. Analyst 2021; 146:5502-5507. [PMID: 34515713 DOI: 10.1039/d1an01198g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Phosphometabolomics by 31P NMR can be challenging, since overlapping multiplets of homonuclear coupled phosphorus nuclei complicate spectral analysis. Pure shift NMR allows to simplify such spectra by collapsing multiplets into singlets, but most pure shift methods require substantially elongated measurement times or cause disturbing spectral line broadening. Herein, we combine established pure shift NMR and artefact suppression techniques to record 31P pure shift NMR spectra without penalties in measurement time or line width. Examples are demonstrated in resolution of a mixture of nucleotide triphosphates and a biological sample of 18O labelled ATP isotopomers.
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Affiliation(s)
- Karl Kristjan Kaup
- National Institute of Chemical Physics and Biophysics, Akadeemia tee 23, Tallinn 12618, Estonia. .,Institute of Chemistry, University of Tartu, Ravila 14A, 50411 Tartu, Estonia
| | - Lauri Toom
- Institute of Chemistry, University of Tartu, Ravila 14A, 50411 Tartu, Estonia
| | - Laura Truu
- National Institute of Chemical Physics and Biophysics, Akadeemia tee 23, Tallinn 12618, Estonia.
| | - Sten Miller
- National Institute of Chemical Physics and Biophysics, Akadeemia tee 23, Tallinn 12618, Estonia.
| | - Marju Puurand
- National Institute of Chemical Physics and Biophysics, Akadeemia tee 23, Tallinn 12618, Estonia.
| | - Kersti Tepp
- National Institute of Chemical Physics and Biophysics, Akadeemia tee 23, Tallinn 12618, Estonia.
| | - Tuuli Käämbre
- National Institute of Chemical Physics and Biophysics, Akadeemia tee 23, Tallinn 12618, Estonia.
| | - Indrek Reile
- National Institute of Chemical Physics and Biophysics, Akadeemia tee 23, Tallinn 12618, Estonia.
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10
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Robust Metabolite Quantification from J-Compensated 2D 1H- 13C-HSQC Experiments. Metabolites 2020; 10:metabo10110449. [PMID: 33171777 PMCID: PMC7695005 DOI: 10.3390/metabo10110449] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 11/03/2020] [Accepted: 11/05/2020] [Indexed: 02/05/2023] Open
Abstract
The spectral resolution of 2D 1H-13C heteronuclear single quantum coherence (1H-13C-HSQC) nuclear magnetic resonance (NMR) spectra facilitates both metabolite identification and quantification in nuclear magnetic resonance-based metabolomics. However, quantification is complicated by variations in magnetization transfer, which among others originate mainly from scalar coupling differences. Methods that compensate for variation in scalar coupling include the generation of calibration factors for individual signals or the use of additional pulse sequence schemes such as quantitative HSQC (Q-HSQC) that suppress the JCH-dependence by modulating the polarization transfer delays of HSQC or, additionally, employ a pure-shift homodecoupling approach in the 1H dimension, such as Quantitative, Perfected and Pure Shifted HSQC (QUIPU-HSQC). To test the quantitative accuracy of these three methods, employing a 600 MHz NMR spectrometer equipped with a helium cooled cryoprobe, a Latin-square design that covered the physiological concentration ranges of 10 metabolites was used. The results show the suitability of all three methods for the quantification of highly abundant metabolites. However, the substantially increased residual water signal observed in QUIPU-HSQC spectra impeded the quantification of low abundant metabolites located near the residual water signal, thus limiting its utility in high-throughput metabolite fingerprinting studies.
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11
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Martineau E, Dumez JN, Giraudeau P. Fast quantitative 2D NMR for metabolomics and lipidomics: A tutorial. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2020; 58:390-403. [PMID: 32239573 DOI: 10.1002/mrc.4899] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 05/17/2019] [Accepted: 05/28/2019] [Indexed: 06/11/2023]
Abstract
Nuclear magnetic resonance (NMR) is a well-known analytical technique for the analysis of complex mixtures. Its quantitative capability makes it ideally suited to metabolomics or lipidomics studies involving large sample collections of complex biological samples. To overcome the ubiquitous limitation of spectral overcrowding when recording 1D NMR spectra on such samples, the acquisition of 2D NMR spectra allows a better separation between overlapped resonances while yielding accurate quantitative data when appropriate analytical protocols are implemented. Moreover, the experiment duration can be considerably reduced by applying fast acquisition methods. Here, we describe the general workflow to acquire fast quantitative 2D NMR spectra in the "omics" context. It is illustrated on three representative and complementary experiments: UF COSY, ZF-TOCSY with nonuniform sampling, and HSQC with nonuniform sampling. After giving some details and recommendations on how to apply this protocol, its implementation in the case of targeted and untargeted metabolomics/lipidomics studies is described.
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Affiliation(s)
- Estelle Martineau
- CEISAM, CNRS UMR 6230, Université de Nantes, Nantes, France
- SpectroMaitrise, CAPACITES SAS, Nantes, France
| | | | - Patrick Giraudeau
- CEISAM, CNRS UMR 6230, Université de Nantes, Nantes, France
- Institut Universitaire de France, Paris Cedex 5, France
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12
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Wang T, Liu Q, Wang M, Zhou J, Yang M, Chen G, Tang F, Hatzakis E, Zhang L. Quantitative Measurement of a Chiral Drug in a Complex Matrix: A J-Compensated Quantitative HSQC NMR Method. Anal Chem 2020; 92:3636-3642. [DOI: 10.1021/acs.analchem.9b04591] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Affiliation(s)
- Tongtong Wang
- Institute of Quality Standard and Testing Technology for Agri-products, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, P.R. China
- Key Laboratory of Agro-food Safety and Quality, Ministry of Agricultures, Beijing 100081, P.R. China
| | - Quanhui Liu
- Institute of Quality Standard and Testing Technology for Agri-products, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, P.R. China
- Key Laboratory of Agro-food Safety and Quality, Ministry of Agricultures, Beijing 100081, P.R. China
| | - Min Wang
- Institute of Quality Standard and Testing Technology for Agri-products, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, P.R. China
- Key Laboratory of Agro-food Safety and Quality, Ministry of Agricultures, Beijing 100081, P.R. China
| | - Jian Zhou
- Institute of Quality Standard and Testing Technology for Agri-products, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, P.R. China
- Key Laboratory of Agro-food Safety and Quality, Ministry of Agricultures, Beijing 100081, P.R. China
| | - Mengrui Yang
- Institute of Quality Standard and Testing Technology for Agri-products, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, P.R. China
- Key Laboratory of Agro-food Safety and Quality, Ministry of Agricultures, Beijing 100081, P.R. China
| | - Gui Chen
- CAS Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Centre for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences (CAS), Wuhan National Research Center for Optoelectronics, Wuhan 430071, P.R. China
| | - Fenfen Tang
- Department of Food Science and Technology, The Ohio State University, Columbus, Ohio 43210, United States
| | - Emmanuel Hatzakis
- Department of Food Science and Technology, The Ohio State University, Columbus, Ohio 43210, United States
| | - Limin Zhang
- CAS Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Centre for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences (CAS), Wuhan National Research Center for Optoelectronics, Wuhan 430071, P.R. China
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13
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Barbosa TM, Castañar L, Moutzouri P, Nilsson M, Morris GA, Rittner R, Tormena CF. Improving the Sensitivity of FESTA Methods for the Analysis of Fluorinated Mixtures. Anal Chem 2020; 92:2224-2228. [PMID: 31846318 DOI: 10.1021/acs.analchem.9b04924] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The analysis of complex mixtures is an important but often intractable problem. When species contain sparse fluorine atoms, NMR spectra of fluorine-containing spin systems can be efficiently extracted from an intact mixture using the recently proposed FESTA (Fluorine-Edited Selective TOCSY Acquisition) methodology. Here an alternative approach to the existing selective reverse INEPT FESTA (SRI-FESTA) experiment is described, based on the use of a modulated spin echo for the initial excitation. MODO-FESTA (modulated echo FESTA) is simpler and has a significant sensitivity advantage over SRI-FESTA. Comparisons are presented of the relative sensitivity and spectral purity of the two types of methods.
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Affiliation(s)
- Thaís M Barbosa
- Chemistry Institute , University of Campinas - UNICAMP , P.O. Box. 6154, 13083-970 Campinas , SP , Brazil
| | - Laura Castañar
- School of Chemistry , University of Manchester , Oxford Road , Manchester M13 9PL , United Kingdom
| | - Pinelopi Moutzouri
- School of Chemistry , University of Manchester , Oxford Road , Manchester M13 9PL , United Kingdom
| | - Mathias Nilsson
- School of Chemistry , University of Manchester , Oxford Road , Manchester M13 9PL , United Kingdom
| | - Gareth A Morris
- School of Chemistry , University of Manchester , Oxford Road , Manchester M13 9PL , United Kingdom
| | - Roberto Rittner
- Chemistry Institute , University of Campinas - UNICAMP , P.O. Box. 6154, 13083-970 Campinas , SP , Brazil
| | - Claudio F Tormena
- Chemistry Institute , University of Campinas - UNICAMP , P.O. Box. 6154, 13083-970 Campinas , SP , Brazil
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14
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Giraudeau P. NMR-based metabolomics and fluxomics: developments and future prospects. Analyst 2020; 145:2457-2472. [DOI: 10.1039/d0an00142b] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Recent NMR developments are acting as game changers for metabolomics and fluxomics – a critical and perspective review.
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15
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Wishart DS. NMR metabolomics: A look ahead. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2019; 306:155-161. [PMID: 31377153 DOI: 10.1016/j.jmr.2019.07.013] [Citation(s) in RCA: 108] [Impact Index Per Article: 21.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Revised: 04/13/2019] [Accepted: 07/08/2019] [Indexed: 05/24/2023]
Abstract
NMR has been used to perform metabolic studies, metabolic profiling and metabolomics in biofluids and tissues for more than 40 years. This close connection between metabolic measurements and NMR has flourished because of NMR's many unique strengths for characterizing the chemical composition of complex mixtures. However, a number of other technologies, including mass spectrometry, have appeared in the past few years that are encroaching on NMR's dominance in metabolomics and metabolic studies. In this brief review, some of the current strengths and existing limitations of NMR-based metabolomics are highlighted. Additionally, a number of recent advances in NMR hardware, methodology and software are also described and these advancements are used to speculate about where NMR-based metabolomics is going, what needs to be done to make it more popular and how it will evolve in the next 5-10 years.
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Affiliation(s)
- David S Wishart
- Department of Computing Science, University of Alberta, Edmonton, AB T6G 2E8, Canada; Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E8, Canada.
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16
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Ultra-Clean Pure Shift 1H-NMR applied to metabolomics profiling. Sci Rep 2019; 9:6900. [PMID: 31053763 PMCID: PMC6499883 DOI: 10.1038/s41598-019-43374-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Accepted: 04/23/2019] [Indexed: 12/19/2022] Open
Abstract
Even though Pure Shift NMR methods have conveniently been used in the assessment of crowded spectra, they are not commonly applied to the analysis of metabolomics data. This paper exploits the recently published SAPPHIRE-PSYCHE methodology in the context of plant metabolome. We compare single pulse, PSYCHE, and SAPPHIRE-PSYCHE spectra obtained from aqueous extracts of Physalis peruviana fruits. STOCSY analysis with simplified SAPPHIRE-PSYCHE spectra of six types of Cape gooseberry was carried out and the results attained compared with classical STOCSY data. PLS coefficients analysis combined with 1D-STOCSY was performed in an effort to simplify biomarker identification. Several of the most compromised proton NMR signals associated with critical constituents of the plant mixture, such as amino acids, organic acids, and sugars, were more cleanly depicted and their inter and intra correlation better reveled by the Pure Shift methods. The simplified data allowed the identification of glutamic acid, a metabolite not observed in previous studies of Cape gooseberry due to heavy overlap of its NMR signals. Overall, the results attained indicated that Ultra-Clean Pure Shift spectra increase the performance of metabolomics data analysis such as STOCSY and multivariate coefficients analysis, and therefore represent a feasible and convenient additional tool available to metabolomics.
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17
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Timári I, Wang C, Hansen AL, Costa dos Santos G, Ok Yoon S, Bruschweiler-Li L, Brüschweiler R. Real-Time Pure Shift HSQC NMR for Untargeted Metabolomics. Anal Chem 2019; 91:2304-2311. [PMID: 30608652 PMCID: PMC6386528 DOI: 10.1021/acs.analchem.8b04928] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Sensitivity and resolution are key considerations for NMR applications in general and for metabolomics in particular, where complex mixtures containing hundreds of metabolites over a large range of concentrations are commonly encountered. There is a strong demand for advanced methods that can provide maximal information in the shortest possible time frame. Here, we present the optimization and application of the recently introduced 2D real-time BIRD 1H-13C HSQC experiment for NMR-based metabolomics of aqueous samples at 13C natural abundance. For mouse urine samples, it is demonstrated how this real-time pure shift sensitivity-improved heteronuclear single quantum correlation method provides broadband homonuclear decoupling along the proton detection dimension and thereby significantly improves spectral resolution in regions that are affected by spectral overlap. Moreover, the collapse of the scalar multiplet structure of cross-peaks leads to a sensitivity gain of about 40-50% over a traditional 2D HSQC-SI experiment. The experiment works well over a range of magnetic field strengths and is particularly useful when resonance overlap in crowded regions of the HSQC spectra hampers accurate metabolite identification and quantitation.
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Affiliation(s)
- István Timári
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| | - Cheng Wang
- Campus Chemical Instrument Center, The Ohio State University, Columbus, Ohio 43210, United States
| | - Alexandar L. Hansen
- Campus Chemical Instrument Center, The Ohio State University, Columbus, Ohio 43210, United States
| | - Gilson Costa dos Santos
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| | - Sung Ok Yoon
- Department of Biological Chemistry and Pharmacology, The Ohio State University, Columbus, Ohio 43210, United States
| | - Lei Bruschweiler-Li
- Campus Chemical Instrument Center, The Ohio State University, Columbus, Ohio 43210, United States
| | - Rafael Brüschweiler
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
- Campus Chemical Instrument Center, The Ohio State University, Columbus, Ohio 43210, United States
- Department of Biological Chemistry and Pharmacology, The Ohio State University, Columbus, Ohio 43210, United States
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18
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Le PM, Milande C, Martineau E, Giraudeau P, Farjon J. Quantification of natural products in herbal supplements: A combined NMR approach applied on goldenseal. J Pharm Biomed Anal 2019; 165:155-161. [DOI: 10.1016/j.jpba.2018.11.062] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Revised: 11/27/2018] [Accepted: 11/29/2018] [Indexed: 01/23/2023]
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19
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Lane D, Skinner TE, Gershenzon NI, Bermel W, Soong R, Dutta Majumdar R, Liaghati Mobarhan Y, Schmidt S, Heumann H, Monette M, Simpson MJ, Simpson AJ. Assessing the potential of quantitative 2D HSQC NMR in 13C enriched living organisms. JOURNAL OF BIOMOLECULAR NMR 2019; 73:31-42. [PMID: 30600417 DOI: 10.1007/s10858-018-0221-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Accepted: 12/17/2018] [Indexed: 05/22/2023]
Abstract
In vivo Nuclear Magnetic Resonance (NMR) spectroscopy has great potential to interpret the biochemical response of organisms to their environment, thus making it an essential tool in understanding toxic mechanisms. However, magnetic susceptibility distortions lead to 1D NMR spectra of living organisms with lines that are too broad to identify and quantify metabolites, necessitating the use of 2D 1H-13C Heteronuclear Single Quantum Coherence (HSQC) as a primary tool. While quantitative 2D HSQC is well established, to our knowledge it has yet to be applied in vivo. This study represents a simple pilot study that compares two of the most popular quantitative 2D HSQC approaches to determine if quantitative results can be directly obtained in vivo in isotopically enriched Daphnia magna (water flea). The results show the perfect-HSQC experiment performs very well in vivo, but the decoupling scheme used is critical for accurate quantitation. An improved decoupling approach derived using optimal control theory is presented here that improves the accuracy of metabolite concentrations that can be extracted in vivo down to micromolar concentrations. When combined with 2D Electronic Reference To access In vivo Concentrations (ERETIC) protocols, the protocol allows for the direct extraction of in vivo metabolite concentrations without the use of internal standards that can be detrimental to living organisms. Extracting absolute metabolic concentrations in vivo is an important first step and should, for example, be important for the parameterization as well as the validation of metabolic flux models in the future.
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Affiliation(s)
- Daniel Lane
- Environmental NMR Centre, University of Toronto Scarborough, 1265 Military Trail, Toronto, ON, M1C 1A4, Canada
| | - Thomas E Skinner
- Department of Physics, Wright State University, Dayton, OH, 45735, USA
| | - Naum I Gershenzon
- Department of Physics, Wright State University, Dayton, OH, 45735, USA
| | - Wolfgang Bermel
- Bruker BioSpin GmbH, Silberstreifen 4, Rheinstetten, Germany
| | - Ronald Soong
- Environmental NMR Centre, University of Toronto Scarborough, 1265 Military Trail, Toronto, ON, M1C 1A4, Canada
| | - Rudraksha Dutta Majumdar
- Environmental NMR Centre, University of Toronto Scarborough, 1265 Military Trail, Toronto, ON, M1C 1A4, Canada
- Bruker Ltd., 2800 Highpoint Drive, Milton, ON, L9T 6P4, Canada
| | - Yalda Liaghati Mobarhan
- Environmental NMR Centre, University of Toronto Scarborough, 1265 Military Trail, Toronto, ON, M1C 1A4, Canada
| | | | | | - Martine Monette
- Bruker Ltd., 2800 Highpoint Drive, Milton, ON, L9T 6P4, Canada
| | - Myrna J Simpson
- Environmental NMR Centre, University of Toronto Scarborough, 1265 Military Trail, Toronto, ON, M1C 1A4, Canada
| | - André J Simpson
- Environmental NMR Centre, University of Toronto Scarborough, 1265 Military Trail, Toronto, ON, M1C 1A4, Canada.
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20
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Parella T. Towards perfect NMR: Spin-echo versus perfect-echo building blocks. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2019; 57:13-29. [PMID: 29927497 DOI: 10.1002/mrc.4776] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Revised: 06/10/2018] [Accepted: 06/12/2018] [Indexed: 06/08/2023]
Abstract
The development of new tools to improve the quality of nuclear magnetic resonance (NMR) spectra is a challenging task. The concept of "perfect NMR" includes the design of robust pulse sequences that allow an investigator to obtain undistorted pure in-phase signals, with pure absorption lineshapes that are free of phase anomalies derived from undesired J modulations. Here, alternative NMR building blocks to the spin-echo that are based on a general double SE module, known as a perfect-echo, are reviewed. Several implementations to minimize/remove unwanted dispersive contributions in homonuclear and heteronuclear NMR experiments are described and illustrated with some examples of broad interest for small molecules.
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Affiliation(s)
- Teodor Parella
- Servei de Ressonància Magnètica Nuclear, Universitat Autònoma de Barcelona, Barcelona, Catalonia, Spain
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21
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Abstract
Nuclear magnetic resonance (NMR) spectroscopy exhibits a great potential for the quantitative analysis of complex biological samples such as those encountered in metabolomics. To overcome the ubiquitous problem of overlapping peaks in 1D NMR spectra of complex mixtures, acquisition of 2D NMR spectra allows a better separation between overlapped resonances while yielding accurate quantitative data when appropriate analytical protocols are implemented. The experiment duration can be made compatible with high-throughput studies on large sample collections by relying on fast acquisition methods. Here, we describe the general metabolomics workflow to acquire fast quantitative 2D NMR data with a focus on targeted or untargeted analyses.
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22
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Puig-Castellví F, Pérez Y, Piña B, Tauler R, Alfonso I. Comparative analysis of 1H NMR and 1H- 13C HSQC NMR metabolomics to understand the effects of medium composition in yeast growth. Anal Chem 2018; 90:12422-12430. [PMID: 30350620 DOI: 10.1021/acs.analchem.8b01196] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
In nuclear magnetic resonance (NMR) metabolomics, most of the studies have been focused on the analysis of one-dimensional proton (1D 1H) NMR, whereas the analysis of other nuclei, such as 13C, or other NMR experiments are still underrepresented. The preference of 1D 1H NMR metabolomics lies on the fact that it has good sensitivity and a short acquisition time, but it lacks spectral resolution because it presents a high degree of overlap. In this study, the growth metabolism of yeast ( Saccharomyces cerevisiae) was analyzed by 1D 1H NMR and by two-dimensional (2D) 1H-13C heteronuclear single quantum coherence (HSQC) NMR spectroscopy, leading to the detection of more than 50 metabolites with both analytical approaches. These two analyses allow for a better understanding of the strengths and intrinsic limitations of the two types of NMR approaches. The two data sets (1D and 2D NMR) were investigated with PCA, ASCA, and PLS DA chemometric methods, and similar results were obtained regardless of the data type used. However, data-analysis time for the 2D NMR data set was substantially reduced when compared with the data analysis of the corresponding 1H NMR data set because, for the 2D NMR data, signal overlap was not a major problem and deconvolution was not required. The comparative study described in this work can be useful for the future design of metabolomics workflows, to assist in the selection of the most convenient NMR platform and to guide the posterior data analysis of biomarker selection.
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Affiliation(s)
- Francesc Puig-Castellví
- Department of Environmental Chemistry , Institute of Environmental Assessment and Water Research (IDAEA-CSIC) , Jordi Girona 18-26 , 08034 Barcelona , Spain
| | - Yolanda Pérez
- NMR Facility , Institute of Advanced Chemistry of Catalonia (IQAC-CSIC) , Jordi Girona 18-26 , 08034 Barcelona , Spain
| | - Benjamín Piña
- Department of Environmental Chemistry , Institute of Environmental Assessment and Water Research (IDAEA-CSIC) , Jordi Girona 18-26 , 08034 Barcelona , Spain
| | - Romà Tauler
- Department of Environmental Chemistry , Institute of Environmental Assessment and Water Research (IDAEA-CSIC) , Jordi Girona 18-26 , 08034 Barcelona , Spain
| | - Ignacio Alfonso
- Department of Biological Chemistry , Institute of Advanced Chemistry of Catalonia (IQAC-CSIC) , Jordi Girona 18-26 , 08034 Barcelona , Spain
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23
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Farjon J, Milande C, Martineau E, Akoka S, Giraudeau P. The FAQUIRE Approach: FAst, QUantitative, hIghly Resolved and sEnsitivity Enhanced 1H, 13C Data. Anal Chem 2018; 90:1845-1851. [PMID: 29303255 DOI: 10.1021/acs.analchem.7b03874] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
The targeted analysis of metabolites in complex mixtures is a challenging issue. NMR is one of the major tools in this field, but there is a strong need for more sensitive, better-resolved, and faster quantitative methods. In this framework, we introduce the concept of FAst, QUantitative, hIghly Resolved and sEnsitivity enhanced (FAQUIRE) NMR to push forward the limits of metabolite NMR analysis. 2D 1H, 13C 2D quantitative maps are promising alternatives for enhancing the spectral resolution but are highly time-consuming because of (i) the intrinsic nature of 2D, (ii) the longer recycling times required for quantitative conditions, and (iii) the higher number of scans needed to reduce the level of detection/quantification to access low concentrated metabolites. To reach this aim, speeding up the recently developed QUantItative Perfected and pUre shifted HSQC (QUIPU HSQC) is an interesting attempt to develop the FAQUIRE concept. Thanks to the combination of spectral aliasing, nonuniform sampling, and variable repetition time, the acquisition time of 2D quantitative maps is reduced by a factor 6 to 9, while conserving a high spectral resolution thanks to a pure shift approach. The analytical potential of the new Quick QUIPU HSQC (Q QUIPU HSQC) is evaluated on a model metabolite sample, and its potential is shown on breast-cell extracts embedding metabolites at millimolar to submillimolar concentrations.
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Affiliation(s)
- Jonathan Farjon
- Faculté des Sciences et Techniques de Nantes, UMR CNRS 6230- CEISAM, Equipe EBSI, LUNAM Université , 44322 Nantes, France
| | - Clément Milande
- Faculté des Sciences et Techniques de Nantes, UMR CNRS 6230- CEISAM, Equipe EBSI, LUNAM Université , 44322 Nantes, France
| | - Estelle Martineau
- Faculté des Sciences et Techniques de Nantes, UMR CNRS 6230- CEISAM, Equipe EBSI, LUNAM Université , 44322 Nantes, France.,SpectroMaitrise, CAPACITÉS SAS, 26 Bd Vincent Gâche, 44200 Nantes, France
| | - Serge Akoka
- Faculté des Sciences et Techniques de Nantes, UMR CNRS 6230- CEISAM, Equipe EBSI, LUNAM Université , 44322 Nantes, France
| | - Patrick Giraudeau
- Faculté des Sciences et Techniques de Nantes, UMR CNRS 6230- CEISAM, Equipe EBSI, LUNAM Université , 44322 Nantes, France.,Institut Universitaire de France , 1 rue Descartes, 75005 Paris CEDEX 05, France
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24
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Verma A, Parihar R, Bhattacharya S, Baishya B. Analyses of Complex Mixtures by F 1 Homo-Decoupled Diagonal Suppressed Total Correlation Spectroscopy. Chemphyschem 2017; 18:3076-3082. [PMID: 28833930 DOI: 10.1002/cphc.201700662] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Revised: 07/31/2017] [Indexed: 11/07/2022]
Abstract
A diagonal suppressed F1 decoupled total correlation spectroscopy(TOCSY) experiment is developed for analyses of complex mixtures. In 2D homonuclear correlation, assignment of the cross peaks is crucial for structure elucidation. However, when cross peaks are close to the diagonal peaks in overcrowded spectral regions, their assignment becomes tedious. In complex mixtures, the presence of multiple spectra along with broad and complex proton multiplets owing to homonuclear scalar couplings degrade the resolution to the extent that assignment of various cross peaks becomes tedious or impossible. Herein, a diagonal suppressed total correlation technique with F1 decoupling is presented to improve the resolution of the cross peaks. The resolution of the cross peaks is improved by both diagonal suppression as well as the collapse of the multiplets to singlets. Application of the method to a few mixtures of organic compounds reveals better identification of the cross peaks relative to other TOCSY variants.
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Affiliation(s)
- Ajay Verma
- Centre of Biomedical Research (Formerly Centre of Biomedical Magnetic Resonance), SGPGIMS Campus, Raebareli Road, Lucknow, 226014, U. P., India.,Department of Chemistry, Institute of Science, Banaras Hindu University, Banaras, 221005, U. P., India
| | - Rashmi Parihar
- Centre of Biomedical Research (Formerly Centre of Biomedical Magnetic Resonance), SGPGIMS Campus, Raebareli Road, Lucknow, 226014, U. P., India.,Department of Bioinformatics, Dr. A. P. J. Abdul Kalam Technical University, Lucknow, 226021, U. P., India
| | - Subrato Bhattacharya
- Department of Chemistry, Institute of Science, Banaras Hindu University, Banaras, 221005, U. P., India
| | - Bikash Baishya
- Centre of Biomedical Research (Formerly Centre of Biomedical Magnetic Resonance), SGPGIMS Campus, Raebareli Road, Lucknow, 226014, U. P., India
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25
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Deborde C, Moing A, Roch L, Jacob D, Rolin D, Giraudeau P. Plant metabolism as studied by NMR spectroscopy. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2017; 102-103:61-97. [PMID: 29157494 DOI: 10.1016/j.pnmrs.2017.05.001] [Citation(s) in RCA: 56] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2017] [Revised: 05/19/2017] [Accepted: 05/22/2017] [Indexed: 05/07/2023]
Abstract
The study of plant metabolism impacts a broad range of domains such as plant cultural practices, plant breeding, human or animal nutrition, phytochemistry and green biotechnologies. Plant metabolites are extremely diverse in terms of structure or compound families as well as concentrations. This review attempts to illustrate how NMR spectroscopy, with its broad variety of experimental approaches, has contributed widely to the study of plant primary or specialized metabolism in very diverse ways. The review presents recent developments of one-dimensional and multi-dimensional NMR methods to study various aspects of plant metabolism. Through recent examples, it highlights how NMR has proved to be an invaluable tool for the global characterization of sample composition within metabolomic studies, and shows some examples of use for targeted phytochemistry, with a special focus on compound identification and quantitation. In such cases, NMR approaches are often used to provide snapshots of the plant sample composition. The review also covers dynamic aspects of metabolism, with a description of NMR techniques to measure metabolic fluxes - in most cases after stable isotope labelling. It is mainly intended for NMR specialists who would be interested to learn more about the potential of their favourite technique in plant sciences and about specific details of NMR approaches in this field. Therefore, as a practical guide, a paragraph on the specific precautions that should be taken for sample preparation is also included. In addition, since the quality of NMR metabolic studies is highly dependent on approaches to data processing and data sharing, a specific part is dedicated to these aspects. The review concludes with perspectives on the emerging methods that could change significantly the role of NMR in the field of plant metabolism by boosting its sensitivity. The review is illustrated throughout with examples of studies selected to represent diverse applications of liquid-state or HR-MAS NMR.
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Affiliation(s)
- Catherine Deborde
- INRA, UMR 1332 Biologie du Fruit et Pathologie, Centre INRA Bordeaux, F-33140 Villenave d'Ornon, France; Plateforme Métabolome Bordeaux - MetaboHUB, Centre de Génomique Fonctionnelle Bordeaux, IBVM, Centre INRA Bordeaux, F-33140 Villenave d'Ornon, France
| | - Annick Moing
- INRA, UMR 1332 Biologie du Fruit et Pathologie, Centre INRA Bordeaux, F-33140 Villenave d'Ornon, France; Plateforme Métabolome Bordeaux - MetaboHUB, Centre de Génomique Fonctionnelle Bordeaux, IBVM, Centre INRA Bordeaux, F-33140 Villenave d'Ornon, France
| | - Léa Roch
- INRA, UMR 1332 Biologie du Fruit et Pathologie, Centre INRA Bordeaux, F-33140 Villenave d'Ornon, France; Plateforme Métabolome Bordeaux - MetaboHUB, Centre de Génomique Fonctionnelle Bordeaux, IBVM, Centre INRA Bordeaux, F-33140 Villenave d'Ornon, France
| | - Daniel Jacob
- INRA, UMR 1332 Biologie du Fruit et Pathologie, Centre INRA Bordeaux, F-33140 Villenave d'Ornon, France; Plateforme Métabolome Bordeaux - MetaboHUB, Centre de Génomique Fonctionnelle Bordeaux, IBVM, Centre INRA Bordeaux, F-33140 Villenave d'Ornon, France
| | - Dominique Rolin
- Plateforme Métabolome Bordeaux - MetaboHUB, Centre de Génomique Fonctionnelle Bordeaux, IBVM, Centre INRA Bordeaux, F-33140 Villenave d'Ornon, France; Univ. Bordeaux, UMR1332, Biologie du Fruit et Pathologie, 71 av Edouard Bourlaux, 33140 Villenave d'Ornon, France
| | - Patrick Giraudeau
- Chimie et Interdisciplinarité: Synthèse, Analyse, Modélisation (CEISAM), UMR 6230, CNRS, Université de Nantes, Faculté des Sciences, BP 92208, 2 rue de la Houssinière, F-44322 Nantes Cedex 03, France; Institut Universitaire de France, 1 rue Descartes, 75005 Paris, France.
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26
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Lu W, Su X, Klein MS, Lewis IA, Fiehn O, Rabinowitz JD. Metabolite Measurement: Pitfalls to Avoid and Practices to Follow. Annu Rev Biochem 2017; 86:277-304. [PMID: 28654323 DOI: 10.1146/annurev-biochem-061516-044952] [Citation(s) in RCA: 261] [Impact Index Per Article: 37.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Metabolites are the small biological molecules involved in energy conversion and biosynthesis. Studying metabolism is inherently challenging due to metabolites' reactivity, structural diversity, and broad concentration range. Herein, we review the common pitfalls encountered in metabolomics and provide concrete guidelines for obtaining accurate metabolite measurements, focusing on water-soluble primary metabolites. We show how seemingly straightforward sample preparation methods can introduce systematic errors (e.g., owing to interconversion among metabolites) and how proper selection of quenching solvent (e.g., acidic acetonitrile:methanol:water) can mitigate such problems. We discuss the specific strengths, pitfalls, and best practices for each common analytical platform: liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS), nuclear magnetic resonance (NMR), and enzyme assays. Together this information provides a pragmatic knowledge base for carrying out biologically informative metabolite measurements.
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Affiliation(s)
- Wenyun Lu
- Lewis Sigler Institute for Integrative Genomics and Department of Chemistry, Princeton University, Princeton, New Jersey 08544;
| | - Xiaoyang Su
- Lewis Sigler Institute for Integrative Genomics and Department of Chemistry, Princeton University, Princeton, New Jersey 08544;
| | - Matthias S Klein
- Department of Biological Science, University of Calgary, Calgary, Alberta T2N 1N4, Canada
| | - Ian A Lewis
- Department of Biological Science, University of Calgary, Calgary, Alberta T2N 1N4, Canada
| | - Oliver Fiehn
- National Institutes of Health West Coast Metabolomics Center, University of California, Davis, California 95616.,Department of Biochemistry, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Joshua D Rabinowitz
- Lewis Sigler Institute for Integrative Genomics and Department of Chemistry, Princeton University, Princeton, New Jersey 08544;
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27
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Sharma R, Gogna N, Singh H, Dorai K. Fast profiling of metabolite mixtures using chemometric analysis of a speeded-up 2D heteronuclear correlation NMR experiment. RSC Adv 2017. [DOI: 10.1039/c7ra04032f] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
One-dimensional (1D) NMR spectra of mixtures of metabolites suffer from severe overlap of spectral resonances and hence recent research in NMR-based metabolomics focuses on using two-dimensional (2D) NMR experiments for metabolite fingerprinting.
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Affiliation(s)
- Rakesh Sharma
- Department of Physical Sciences
- Indian Institute of Science Education & Research (IISER) Mohali
- India
| | - Navdeep Gogna
- Department of Physical Sciences
- Indian Institute of Science Education & Research (IISER) Mohali
- India
| | - Harpreet Singh
- Department of Physical Sciences
- Indian Institute of Science Education & Research (IISER) Mohali
- India
| | - Kavita Dorai
- Department of Physical Sciences
- Indian Institute of Science Education & Research (IISER) Mohali
- India
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Giraudeau P. Challenges and perspectives in quantitative NMR. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2017; 55:61-69. [PMID: 27370178 DOI: 10.1002/mrc.4475] [Citation(s) in RCA: 63] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2016] [Revised: 06/20/2016] [Accepted: 06/23/2016] [Indexed: 06/06/2023]
Abstract
This perspective article summarizes, from the author's point of view at the beginning of 2016, the major challenges and perspectives in the field of quantitative NMR. The key concepts in quantitative NMR are first summarized; then, the most recent evolutions in terms of resolution and sensitivity are discussed, as well as some potential future research directions in this field. A particular focus is made on methodologies capable of boosting the resolution and sensitivity of quantitative NMR, which could open application perspectives in fields where the sample complexity and the analyte concentrations are particularly challenging. These include multi-dimensional quantitative NMR and hyperpolarization techniques such as para-hydrogen-induced polarization or dynamic nuclear polarization. Because quantitative NMR cannot be dissociated from the key concepts of analytical chemistry, i.e. trueness and precision, the methodological developments are systematically described together with their level of analytical performance. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Patrick Giraudeau
- EBSI Team, Chimie et Interdisciplinarité, Synthèse, Analyse, Modélisation (CEISAM), Université de Nantes, CNRS, UMR 6230, LUNAM Université, Nantes, France
- Institut Universitaire de France, Paris Cedex 5, France
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Castañar L. Pure shift 1 H NMR: what is next? MAGNETIC RESONANCE IN CHEMISTRY : MRC 2017; 55:47-53. [PMID: 27761957 DOI: 10.1002/mrc.4545] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2016] [Revised: 10/14/2016] [Accepted: 10/17/2016] [Indexed: 06/06/2023]
Abstract
Currently, pure shift nuclear magnetic resonance (NMR) is an area of high interest. The aim of this contribution is to describe briefly how this technique has evolved, where it is now and what could be the next challenges in the amazing adventure of the development and application of pure shift NMR experiments. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Laura Castañar
- School of Chemistry, University of Manchester, Manchester, UK
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Marchand J, Martineau E, Guitton Y, Dervilly-Pinel G, Giraudeau P. Multidimensional NMR approaches towards highly resolved, sensitive and high-throughput quantitative metabolomics. Curr Opin Biotechnol 2016; 43:49-55. [PMID: 27639136 DOI: 10.1016/j.copbio.2016.08.004] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2016] [Revised: 08/25/2016] [Accepted: 08/30/2016] [Indexed: 11/25/2022]
Abstract
Multi-dimensional NMR is an appealing approach for dealing with the challenging complexity of biological samples in metabolomics. This article describes how spectroscopists have recently challenged their imagination in order to make 2D NMR a powerful tool for quantitative metabolomics, based on innovative pulse sequences combined with meticulous analytical chemistry approaches. Clever time-saving strategies have also been explored to make 2D NMR a high-throughput tool for metabolomics, relying on alternative data acquisition schemes such as ultrafast NMR. Currently, much work is aimed at drastically boosting the NMR sensitivity thanks to hyperpolarisation techniques, which have been used in combination with fast acquisition methods and could greatly expand the application potential of NMR metabolomics.
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Affiliation(s)
- Jérémy Marchand
- CEISAM, UMR6230, Université de Nantes, BP 92208, 2 rue de la Houssinière, 44322 Nantes, France; LUNAM Université, Oniris, Laboratoire d'Etude des Résidus et Contaminants dans les Aliments (LABERCA), 44307 Nantes, France
| | - Estelle Martineau
- CEISAM, UMR6230, Université de Nantes, BP 92208, 2 rue de la Houssinière, 44322 Nantes, France; Spectromaîtrise, CAPACITÉS SAS, 26 Bd Vincent Gâche, 44200 Nantes, France
| | - Yann Guitton
- LUNAM Université, Oniris, Laboratoire d'Etude des Résidus et Contaminants dans les Aliments (LABERCA), 44307 Nantes, France
| | - Gaud Dervilly-Pinel
- LUNAM Université, Oniris, Laboratoire d'Etude des Résidus et Contaminants dans les Aliments (LABERCA), 44307 Nantes, France
| | - Patrick Giraudeau
- CEISAM, UMR6230, Université de Nantes, BP 92208, 2 rue de la Houssinière, 44322 Nantes, France; Institut Universitaire de France, 1 rue Descartes, 75005 Paris Cedex 5, France.
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Markley JL, Brüschweiler R, Edison AS, Eghbalnia HR, Powers R, Raftery D, Wishart DS. The future of NMR-based metabolomics. Curr Opin Biotechnol 2016; 43:34-40. [PMID: 27580257 DOI: 10.1016/j.copbio.2016.08.001] [Citation(s) in RCA: 487] [Impact Index Per Article: 60.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2016] [Revised: 08/05/2016] [Accepted: 08/08/2016] [Indexed: 12/15/2022]
Abstract
The two leading analytical approaches to metabolomics are mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. Although currently overshadowed by MS in terms of numbers of compounds resolved, NMR spectroscopy offers advantages both on its own and coupled with MS. NMR data are highly reproducible and quantitative over a wide dynamic range and are unmatched for determining structures of unknowns. NMR is adept at tracing metabolic pathways and fluxes using isotope labels. Moreover, NMR is non-destructive and can be utilized in vivo. NMR results have a proven track record of translating in vitro findings to in vivo clinical applications.
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Affiliation(s)
- John L Markley
- Biochemistry Department, University of Wisconsin-Madison, 433 Babcock Drive, Madison, WI 53706, USA.
| | - Rafael Brüschweiler
- Department of Chemistry & Biochemistry, The Ohio State University, 151 W. Woodruff Ave., Columbus, OH 43210, USA; Department of Biological Chemistry & Pharmacology, The Ohio State University, 151 W. Woodruff Ave., Columbus, OH 43210, USA
| | - Arthur S Edison
- Department of Genetics and Biochemistry, Institute of Bioinformatics and Complex Carbohydrate Center, University of Georgia, 315 Riverbend Rd, Athens, GA 30602, USA
| | - Hamid R Eghbalnia
- Biochemistry Department, University of Wisconsin-Madison, 433 Babcock Drive, Madison, WI 53706, USA
| | - Robert Powers
- Department of Chemistry, University of Nebraska-Lincoln, 722 Hamilton Hall, Lincoln, NE 68588, USA
| | - Daniel Raftery
- Department of Anesthesiology & Pain Medicine, 850 Republican St, University of Washington, Seattle, WA 98109, USA
| | - David S Wishart
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada T6G 2E8; Department of Computing Science, University of Alberta, Edmonton, AB, Canada T6G 2E8
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Timári I, Kaltschnee L, Raics MH, Roth F, Bell NGA, Adams RW, Nilsson M, Uhrín D, Morris GA, Thiele CM, Kövér KE. Real-time broadband proton-homodecoupled CLIP/CLAP-HSQC for automated measurement of heteronuclear one-bond coupling constants. RSC Adv 2016. [DOI: 10.1039/c6ra14329f] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
A new method is proposed that allows broadband homonuclear decoupled CLIP/CLAP-HSQC NMR spectra to be acquired at virtually no extra cost in measurement time.
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Affiliation(s)
- István Timári
- Department of Inorganic and Analytical Chemistry
- University of Debrecen
- H-4032 Debrecen
- Hungary
| | - Lukas Kaltschnee
- Clemens-Schöpf-Institut für Organische Chemie und Biochemie
- Technische Universität Darmstadt
- D-64287 Darmstadt
- Germany
| | - Mária H. Raics
- Department of Inorganic and Analytical Chemistry
- University of Debrecen
- H-4032 Debrecen
- Hungary
| | - Felix Roth
- Clemens-Schöpf-Institut für Organische Chemie und Biochemie
- Technische Universität Darmstadt
- D-64287 Darmstadt
- Germany
| | | | | | | | - Dušan Uhrín
- EastCHEM School of Chemistry
- University of Edinburgh
- Edinburgh
- UK
| | | | - Christina M. Thiele
- Clemens-Schöpf-Institut für Organische Chemie und Biochemie
- Technische Universität Darmstadt
- D-64287 Darmstadt
- Germany
| | - Katalin E. Kövér
- Department of Inorganic and Analytical Chemistry
- University of Debrecen
- H-4032 Debrecen
- Hungary
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