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Schlippenbach TV, Oefner PJ, Gronwald W. Systematic Evaluation of Non-Uniform Sampling Parameters in the Targeted Analysis of Urine Metabolites by 1H, 1H 2D NMR Spectroscopy. Sci Rep 2018; 8:4249. [PMID: 29523811 PMCID: PMC5844889 DOI: 10.1038/s41598-018-22541-0] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2017] [Accepted: 02/23/2018] [Indexed: 11/15/2022] Open
Abstract
Non-uniform sampling (NUS) allows the accelerated acquisition of multidimensional NMR spectra. The aim of this contribution was the systematic evaluation of the impact of various quantitative NUS parameters on the accuracy and precision of 2D NMR measurements of urinary metabolites. Urine aliquots spiked with varying concentrations (15.6-500.0 µM) of tryptophan, tyrosine, glutamine, glutamic acid, lactic acid, and threonine, which can only be resolved fully by 2D NMR, were used to assess the influence of the sampling scheme, reconstruction algorithm, amount of omitted data points, and seed value on the quantitative performance of NUS in 1H,1H-TOCSY and 1H,1H-COSY45 NMR spectroscopy. Sinusoidal Poisson-gap sampling and a compressed sensing approach employing the iterative re-weighted least squares method for spectral reconstruction allowed a 50% reduction in measurement time while maintaining sufficient quantitative accuracy and precision for both types of homonuclear 2D NMR spectroscopy. Together with other advances in instrument design, such as state-of-the-art cryogenic probes, use of 2D NMR spectroscopy in large biomedical cohort studies seems feasible.
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Affiliation(s)
- Trixi von Schlippenbach
- Institute of Functional Genomics, University of Regensburg, Am BioPark 9, 93053, Regensburg, Germany
| | - Peter J Oefner
- Institute of Functional Genomics, University of Regensburg, Am BioPark 9, 93053, Regensburg, Germany
| | - Wolfram Gronwald
- Institute of Functional Genomics, University of Regensburg, Am BioPark 9, 93053, Regensburg, Germany.
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102
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Beirnaert C, Meysman P, Vu TN, Hermans N, Apers S, Pieters L, Covaci A, Laukens K. speaq 2.0: A complete workflow for high-throughput 1D NMR spectra processing and quantification. PLoS Comput Biol 2018; 14:e1006018. [PMID: 29494588 PMCID: PMC5849334 DOI: 10.1371/journal.pcbi.1006018] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2017] [Revised: 03/13/2018] [Accepted: 02/04/2018] [Indexed: 01/18/2023] Open
Abstract
Nuclear Magnetic Resonance (NMR) spectroscopy is, together with liquid chromatography-mass spectrometry (LC-MS), the most established platform to perform metabolomics. In contrast to LC-MS however, NMR data is predominantly being processed with commercial software. Meanwhile its data processing remains tedious and dependent on user interventions. As a follow-up to speaq, a previously released workflow for NMR spectral alignment and quantitation, we present speaq 2.0. This completely revised framework to automatically analyze 1D NMR spectra uses wavelets to efficiently summarize the raw spectra with minimal information loss or user interaction. The tool offers a fast and easy workflow that starts with the common approach of peak-picking, followed by grouping, thus avoiding the binning step. This yields a matrix consisting of features, samples and peak values that can be conveniently processed either by using included multivariate statistical functions or by using many other recently developed methods for NMR data analysis. speaq 2.0 facilitates robust and high-throughput metabolomics based on 1D NMR but is also compatible with other NMR frameworks or complementary LC-MS workflows. The methods are benchmarked using a simulated dataset and two publicly available datasets. speaq 2.0 is distributed through the existing speaq R package to provide a complete solution for NMR data processing. The package and the code for the presented case studies are freely available on CRAN (https://cran.r-project.org/package=speaq) and GitHub (https://github.com/beirnaert/speaq).
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Affiliation(s)
- Charlie Beirnaert
- Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium
- Biomedical Informatics Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
- * E-mail: (CB); (KL)
| | - Pieter Meysman
- Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium
- Biomedical Informatics Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Trung Nghia Vu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Nina Hermans
- Natural Products & Food Research and Analysis (NatuRA), Department of Pharmaceutical Sciences, University of Antwerp, Wilrijk, Belgium
| | - Sandra Apers
- Natural Products & Food Research and Analysis (NatuRA), Department of Pharmaceutical Sciences, University of Antwerp, Wilrijk, Belgium
| | - Luc Pieters
- Natural Products & Food Research and Analysis (NatuRA), Department of Pharmaceutical Sciences, University of Antwerp, Wilrijk, Belgium
| | - Adrian Covaci
- Toxicological Center, Department of Pharmaceutical Sciences, University of Antwerp, Wilrijk, Belgium
| | - Kris Laukens
- Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium
- Biomedical Informatics Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
- * E-mail: (CB); (KL)
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103
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Barbier Saint Hilaire P, Hohenester UM, Colsch B, Tabet JC, Junot C, Fenaille F. Evaluation of the High-Field Orbitrap Fusion for Compound Annotation in Metabolomics. Anal Chem 2018; 90:3030-3035. [PMID: 29425452 DOI: 10.1021/acs.analchem.7b05372] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Annotation of signals of interest represents a key point in mass spectrometry-based metabolomics studies. The first level of investigation is the elemental composition, which can be deduced from accurately measured masses and isotope patterns. However, accuracy of these two parameters remains to be evaluated on last generation mass spectrometers to determine the level of confidence that can be used during the annotation process. In this context, we evaluated the performance of the Orbitrap Fusion mass spectrometer for the first time and demonstrated huge potential for metabolite annotation via elemental composition determination. This work was performed using a set of 50 standard compounds analyzed under LC/MS conditions in solvent and biological media. Accurate control of the number of trapped ions proved mandatory to avoid space charge effects, ensure sub-ppm mass accuracy (using external calibration), and reliable measurement of isotopic patterns at 500,000 resolution. On the basis of the results, we propose standard optimized experimental conditions for performing robust and accurate untargeted metabolomics on the Orbitrap Fusion at high mass measurement and mass spectral accuracy.
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Affiliation(s)
- Pierre Barbier Saint Hilaire
- Service de Pharmacologie et d'Immunoanalyse (SPI), Laboratoire d'Etude du Métabolisme des Médicaments, CEA, INRA , Université Paris Saclay, MetaboHUB , F-91191 Gif-sur-Yvette , France
| | - Ulli M Hohenester
- Service de Pharmacologie et d'Immunoanalyse (SPI), Laboratoire d'Etude du Métabolisme des Médicaments, CEA, INRA , Université Paris Saclay, MetaboHUB , F-91191 Gif-sur-Yvette , France
| | - Benoit Colsch
- Service de Pharmacologie et d'Immunoanalyse (SPI), Laboratoire d'Etude du Métabolisme des Médicaments, CEA, INRA , Université Paris Saclay, MetaboHUB , F-91191 Gif-sur-Yvette , France
| | - Jean-Claude Tabet
- Service de Pharmacologie et d'Immunoanalyse (SPI), Laboratoire d'Etude du Métabolisme des Médicaments, CEA, INRA , Université Paris Saclay, MetaboHUB , F-91191 Gif-sur-Yvette , France.,Sorbonne Universités , Campus Pierre et Marie Curie, IPCM, 4 place Jussieu , 75252 Paris Cedex 05, France
| | - Christophe Junot
- Service de Pharmacologie et d'Immunoanalyse (SPI), Laboratoire d'Etude du Métabolisme des Médicaments, CEA, INRA , Université Paris Saclay, MetaboHUB , F-91191 Gif-sur-Yvette , France
| | - François Fenaille
- Service de Pharmacologie et d'Immunoanalyse (SPI), Laboratoire d'Etude du Métabolisme des Médicaments, CEA, INRA , Université Paris Saclay, MetaboHUB , F-91191 Gif-sur-Yvette , France
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104
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Gogiashvili M, Horsch S, Marchan R, Gianmoena K, Cadenas C, Tanner B, Naumann S, Ersova D, Lippek F, Rahnenführer J, Andersson JT, Hergenröder R, Lambert J, Hengstler JG, Edlund K. Impact of intratumoral heterogeneity of breast cancer tissue on quantitative metabolomics using high-resolution magic angle spinning 1 H NMR spectroscopy. NMR IN BIOMEDICINE 2018; 31:e3862. [PMID: 29206323 DOI: 10.1002/nbm.3862] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2016] [Revised: 10/15/2017] [Accepted: 10/16/2017] [Indexed: 06/07/2023]
Abstract
High-resolution magic angle spinning (HR MAS) nuclear magnetic resonance (NMR) spectroscopy is increasingly being used to study metabolite levels in human breast cancer tissue, assessing, for instance, correlations with prognostic factors, survival outcome or therapeutic response. However, the impact of intratumoral heterogeneity on metabolite levels in breast tumor tissue has not been studied comprehensively. More specifically, when biopsy material is analyzed, it remains questionable whether one biopsy is representative of the entire tumor. Therefore, multi-core sampling (n = 6) of tumor tissue from three patients with breast cancer, followed by lipid (0.9- and 1.3-ppm signals) and metabolite quantification using HR MAS 1 H NMR, was performed, resulting in the quantification of 32 metabolites. The mean relative standard deviation across all metabolites for the six tumor cores sampled from each of the three tumors ranged from 0.48 to 0.74. This was considerably higher when compared with a morphologically more homogeneous tissue type, here represented by murine liver (0.16-0.20). Despite the seemingly high variability observed within the tumor tissue, a random forest classifier trained on the original sample set (training set) was, with one exception, able to correctly predict the tumor identity of an independent series of cores (test set) that were additionally sampled from the same three tumors and analyzed blindly. Moreover, significant differences between the tumors were identified using one-way analysis of variance (ANOVA), indicating that the intertumoral differences for many metabolites were larger than the intratumoral differences for these three tumors. That intertumoral differences, on average, were larger than intratumoral differences was further supported by the analysis of duplicate tissue cores from 15 additional breast tumors. In summary, despite the observed intratumoral variability, the results of the present study suggest that the analysis of one, or a few, replicates per tumor may be acceptable, and supports the feasibility of performing reliable analyses of patient tissue.
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Affiliation(s)
- Mikheil Gogiashvili
- Leibniz Institut für Analytische Wissenschaften - ISAS e.V, Dortmund, Germany
| | - Salome Horsch
- Department of Statistics, TU Dortmund University, Dortmund, Germany
| | - Rosemarie Marchan
- Leibniz Research Center for Working Environment and Human Factors (IfADo), Dortmund, Germany
| | - Kathrin Gianmoena
- Leibniz Research Center for Working Environment and Human Factors (IfADo), Dortmund, Germany
| | - Cristina Cadenas
- Leibniz Research Center for Working Environment and Human Factors (IfADo), Dortmund, Germany
| | - Berno Tanner
- Department of Obstetrics and Gynecology, Oranienburg Clinic, Oranienburg, Germany
| | - Sabrina Naumann
- Department of Obstetrics and Gynecology, Oranienburg Clinic, Oranienburg, Germany
| | - Diana Ersova
- Department of Obstetrics and Gynecology, Oranienburg Clinic, Oranienburg, Germany
| | - Frank Lippek
- Institute of Pathology, MVZ OGD, Neuruppin, Germany
| | | | - Jan T Andersson
- Institute of Inorganic and Analytical Chemistry, University of Münster, Münster, Germany
| | - Roland Hergenröder
- Leibniz Institut für Analytische Wissenschaften - ISAS e.V, Dortmund, Germany
| | - Jörg Lambert
- Leibniz Institut für Analytische Wissenschaften - ISAS e.V, Dortmund, Germany
| | - Jan G Hengstler
- Leibniz Research Center for Working Environment and Human Factors (IfADo), Dortmund, Germany
| | - Karolina Edlund
- Leibniz Research Center for Working Environment and Human Factors (IfADo), Dortmund, Germany
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Zurfluh S, Baumgartner T, Meier MA, Ottiger M, Voegeli A, Bernasconi L, Neyer P, Mueller B, Schuetz P. The role of metabolomic markers for patients with infectious diseases: implications for risk stratification and therapeutic modulation. Expert Rev Anti Infect Ther 2018; 16:133-142. [PMID: 29316826 DOI: 10.1080/14787210.2018.1426460] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
INTRODUCTION Metabolomics is a rapidly growing area of research. Metabolomic markers can provide information about the interaction of different organ systems, and thereby improve the understanding of physio-pathological processes, disease risk, prognosis and therapy responsiveness in a variety of diseases. Areas covered: In this narrative review of recent clinical studies investigating metabolomic markers in adult patients presenting with acute infectious disease, we mainly focused on patients with sepsis and lower respiratory tract infections. Currently, there is a growing body of literature showing that single metabolites from distinct metabolic pathways, as well as more complex metabolomic signatures are associated with disease severity and outcome in patients with systemic infections. These pathways include, among others, metabolomic markers of oxidative stress, steroid hormone and amino acid pathways, and nutritional markers. Expert commentary: Metabolic profiling has great potential to optimize patient management, to provide new targets for individual therapy and thereby improve survival of patients. At this stage, research mainly focused on the identification of new predictive signatures and less on metabolic determinants to predict treatment response. The transition from observational studies to implementation of novel markers into clinical practice is the next crucial step to prove the usefulness of metabolomic markers in patient care.
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Affiliation(s)
- Seline Zurfluh
- a University Department of Medicine, Kantonsspital Aarau and Faculty of Medicine , University of Basel , Aarau , Switzerland
| | - Thomas Baumgartner
- a University Department of Medicine, Kantonsspital Aarau and Faculty of Medicine , University of Basel , Aarau , Switzerland
| | - Marc A Meier
- a University Department of Medicine, Kantonsspital Aarau and Faculty of Medicine , University of Basel , Aarau , Switzerland
| | - Manuel Ottiger
- a University Department of Medicine, Kantonsspital Aarau and Faculty of Medicine , University of Basel , Aarau , Switzerland
| | - Alaadin Voegeli
- a University Department of Medicine, Kantonsspital Aarau and Faculty of Medicine , University of Basel , Aarau , Switzerland
| | - Luca Bernasconi
- b Department of Laboratory Medicine, University Department of Medicine , Kantonsspital Aarau , Aarau , Switzerland
| | - Peter Neyer
- b Department of Laboratory Medicine, University Department of Medicine , Kantonsspital Aarau , Aarau , Switzerland
| | - Beat Mueller
- a University Department of Medicine, Kantonsspital Aarau and Faculty of Medicine , University of Basel , Aarau , Switzerland
| | - Philipp Schuetz
- a University Department of Medicine, Kantonsspital Aarau and Faculty of Medicine , University of Basel , Aarau , Switzerland
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106
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Zhang LN, Wang L, Shi ZQ, Li P, Li HJ. A metabolomic strategy based on integrating headspace gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry to differentiate the five cultivars of Chrysanthemum flower. RSC Adv 2018; 8:9074-9082. [PMID: 35541849 PMCID: PMC9078625 DOI: 10.1039/c7ra13503c] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2017] [Accepted: 02/18/2018] [Indexed: 11/21/2022] Open
Abstract
The extreme complexity of the chemical composition of plant extracts requires an unbiased and comprehensive detection methodology to improve the potential of metabolomic study. The present work, taking five closely related cultivars of Chrysanthemum flowers as a typical case, attempts to develop a metabolomic strategy to find more markers of metabolites for precise differentiation based on headspace gas chromatography-mass spectrometry (HSGC-MS) and ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF/MS). In detail, 53 batches of Chrysanthemum flower samples were collected and analyzed. The fusion of datasets from HSGC-MS and UHPLC-QTOF/MS was done in two different ways. After comparison, the fusion of the total peak area normalized metabolomic data was performed for multivariate statistical analysis. A total of 21 marker compounds (including 14 volatile and 7 nonvolatile metabolites) were identified, and a heatmap was employed for clarifying the distribution of the identified metabolites among the five cultivars. The results indicated that the integrated platform benefited the metabolomic study of medicinal and edible herbs by providing complementary information through fully monitoring functional constituents. A metabolomic strategy based on HSGC-MS and UPLC-QTOF/MS provided complementary information through fully monitoring functional constituents.![]()
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Affiliation(s)
- Lin-Ning Zhang
- State Key Laboratory of Natural Medicines
- China Pharmaceutical University
- Nanjing
- China
| | - Long Wang
- State Key Laboratory of Natural Medicines
- China Pharmaceutical University
- Nanjing
- China
| | - Zi-Qi Shi
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine
- Nanjing University of Chinese Medicine
- Nanjing
- China
- Jiangsu Province Academy of Traditional Chinese Medicine
| | - Ping Li
- State Key Laboratory of Natural Medicines
- China Pharmaceutical University
- Nanjing
- China
| | - Hui-Jun Li
- State Key Laboratory of Natural Medicines
- China Pharmaceutical University
- Nanjing
- China
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107
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Struja T, Eckart A, Kutz A, Huber A, Neyer P, Kraenzlin M, Mueller B, Meier C, Bernasconi L, Schuetz P. Metabolomics for Prediction of Relapse in Graves' Disease: Observational Pilot Study. Front Endocrinol (Lausanne) 2018; 9:623. [PMID: 30386302 PMCID: PMC6199355 DOI: 10.3389/fendo.2018.00623] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2018] [Accepted: 10/01/2018] [Indexed: 12/12/2022] Open
Abstract
Background: There is a lack of biochemical markers for early prediction of relapse in patients with Graves' disease [GD], which may help to direct treatment decisions. We assessed the prognostic ability of a high-throughput proton NMR metabolomic profile to predict relapse in a well characterized cohort of GD patients. Methods: Observational study investigating patients presenting with GD at a Swiss hospital endocrine referral center and an associated endocrine outpatient clinic. We measured 227 metabolic markers in the blood of patients before treatment initiation. Main outcome was relapse of hyperthyroidism within 18 months of stopping anti-thyroid drugs. We used ROC analysis with AUC to assess discrimination. Results: Of 69 included patients 18 (26%) patients had a relapse of disease. The clinical GREAT score had an AUC of 0.68 (95% CI 0.63-0.70) to predict relapse. When looking at the metabolomic markers, univariate analysis revealed pyruvate and triglycerides in medium VLDL as predictors with AUCs of 0.73 (95% CI 0.58-0.84) and 0.67 (95% CI 0.53-0.80), respectively. All other metabolomic markers had lower AUCs. Conclusion: Overall, metabolomic markers in our pilot study had low to moderate prognostic potential for prediction of relapse of GD, with pyruvate and triglycerides being candidates with acceptable discriminatory abilities. Our data need validation in future larger trials.
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Affiliation(s)
- Tristan Struja
- Division of Endocrinology, Diabetes and Metabolism, Medical University Department, Kantonsspital Aarau, Aarau, Switzerland
- *Correspondence: Tristan Struja
| | - Andreas Eckart
- Division of Endocrinology, Diabetes and Metabolism, Medical University Department, Kantonsspital Aarau, Aarau, Switzerland
| | - Alexander Kutz
- Division of Endocrinology, Diabetes and Metabolism, Medical University Department, Kantonsspital Aarau, Aarau, Switzerland
| | - Andreas Huber
- Department of Laboratory Medicine, Kantonsspital Aarau, Aarau, Switzerland
| | - Peter Neyer
- Department of Laboratory Medicine, Kantonsspital Aarau, Aarau, Switzerland
| | | | - Beat Mueller
- Division of Endocrinology, Diabetes and Metabolism, Medical University Department, Kantonsspital Aarau, Aarau, Switzerland
- Medical Faculty, University of Basel, Basel, Switzerland
| | - Christian Meier
- Endonet, Basel, Switzerland
- Medical Faculty, University of Basel, Basel, Switzerland
| | - Luca Bernasconi
- Department of Laboratory Medicine, Kantonsspital Aarau, Aarau, Switzerland
| | - Philipp Schuetz
- Division of Endocrinology, Diabetes and Metabolism, Medical University Department, Kantonsspital Aarau, Aarau, Switzerland
- Medical Faculty, University of Basel, Basel, Switzerland
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108
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Gomes NG, Pereira DM, Valentão P, Andrade PB. Hybrid MS/NMR methods on the prioritization of natural products: Applications in drug discovery. J Pharm Biomed Anal 2018; 147:234-249. [DOI: 10.1016/j.jpba.2017.07.035] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2017] [Revised: 07/27/2017] [Accepted: 07/28/2017] [Indexed: 12/17/2022]
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109
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Tiwari R, Ahire D, Kumar H, Sinha S, Chauthe SK, Subramanian M, Iyer R, Sarabu R, Bajpai L. Use of Hybrid Capillary Tube Apparatus on 400 MHz NMR for Quantitation of Crucial Low-Quantity Metabolites Using aSICCO Signal. Drug Metab Dispos 2017; 45:1215-1224. [PMID: 28935657 DOI: 10.1124/dmd.117.077073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2017] [Accepted: 09/13/2017] [Indexed: 11/22/2022] Open
Abstract
Metabolites of new chemical entities can influence safety and efficacy of a molecule and often times need to be quantified in preclinical studies. However, synthetic standards of metabolites are very rarely available in early discovery. Alternate approaches such as biosynthesis need to be explored to generate these metabolites. Assessing the quantity and purity of these small amounts of metabolites with a nondestructive analytical procedure becomes crucial. Quantitative NMR becomes the method of choice for these samples. Recent advances in high-field NMR (>500 MHz) with the use of cryoprobe technology have helped to improve sensitivity for analysis of small microgram quantity of such samples. However, this type of NMR instrumentation is not routinely available in all laboratories. To analyze microgram quantities of metabolites on a routine basis with lower-resolution 400 MHz NMR instrument fitted with a broad band fluorine observe room temperature probe, a novel hybrid capillary tube setup was developed. To quantitate the metabolite in the sample, an artificial signal insertion for calculation of concentration observed (aSICCO) method that introduces an internally calibrated mathematical signal was used after acquiring the NMR spectrum. The linearity of aSICCO signal was established using ibuprofen as a model analyte. The limit of quantification of this procedure was 0.8 mM with 10 K scans that could be improved further with the increase in the number of scans. This procedure was used to quantify three metabolites-phenytoin from fosphenytoin, dextrophan from dextromethorphan, and 4-OH-diclofenac from diclofenac-and is suitable for minibiosynthesis of metabolites from in vitro systems.
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Affiliation(s)
- Ranjeet Tiwari
- Discovery Analytical Sciences (R.T., H.K., S.K.C., R.S., L.B.) and Pharmaceutical Candidate Optimization (D.A., S.S., M.S.), Bristol-Myers Squibb-Biocon Research Center, Bangalore, India; and Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (R.I.)
| | - Deepak Ahire
- Discovery Analytical Sciences (R.T., H.K., S.K.C., R.S., L.B.) and Pharmaceutical Candidate Optimization (D.A., S.S., M.S.), Bristol-Myers Squibb-Biocon Research Center, Bangalore, India; and Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (R.I.)
| | - Hemantha Kumar
- Discovery Analytical Sciences (R.T., H.K., S.K.C., R.S., L.B.) and Pharmaceutical Candidate Optimization (D.A., S.S., M.S.), Bristol-Myers Squibb-Biocon Research Center, Bangalore, India; and Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (R.I.)
| | - Sarmistha Sinha
- Discovery Analytical Sciences (R.T., H.K., S.K.C., R.S., L.B.) and Pharmaceutical Candidate Optimization (D.A., S.S., M.S.), Bristol-Myers Squibb-Biocon Research Center, Bangalore, India; and Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (R.I.)
| | - Siddheshwar Kisan Chauthe
- Discovery Analytical Sciences (R.T., H.K., S.K.C., R.S., L.B.) and Pharmaceutical Candidate Optimization (D.A., S.S., M.S.), Bristol-Myers Squibb-Biocon Research Center, Bangalore, India; and Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (R.I.)
| | - Murali Subramanian
- Discovery Analytical Sciences (R.T., H.K., S.K.C., R.S., L.B.) and Pharmaceutical Candidate Optimization (D.A., S.S., M.S.), Bristol-Myers Squibb-Biocon Research Center, Bangalore, India; and Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (R.I.)
| | - Ramaswamy Iyer
- Discovery Analytical Sciences (R.T., H.K., S.K.C., R.S., L.B.) and Pharmaceutical Candidate Optimization (D.A., S.S., M.S.), Bristol-Myers Squibb-Biocon Research Center, Bangalore, India; and Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (R.I.)
| | - Ramakanth Sarabu
- Discovery Analytical Sciences (R.T., H.K., S.K.C., R.S., L.B.) and Pharmaceutical Candidate Optimization (D.A., S.S., M.S.), Bristol-Myers Squibb-Biocon Research Center, Bangalore, India; and Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (R.I.)
| | - Lakshmikant Bajpai
- Discovery Analytical Sciences (R.T., H.K., S.K.C., R.S., L.B.) and Pharmaceutical Candidate Optimization (D.A., S.S., M.S.), Bristol-Myers Squibb-Biocon Research Center, Bangalore, India; and Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (R.I.)
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110
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Monakhova YB, Diehl BWK. Facilitating the performance of qNMR analysis using automated quantification and results verification. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2017; 55:813-820. [PMID: 28295588 DOI: 10.1002/mrc.4591] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2016] [Revised: 03/03/2017] [Accepted: 03/06/2017] [Indexed: 06/06/2023]
Abstract
Quantitative nuclear magnetic resonance (qNMR) is considered as a powerful tool for measuring the absolute amount of small molecules in complex mixtures. However, verification of the accuracy of such quantification is not a trivial task. In particular, preprocessing and integration steps are challenging and potentially erroneous. A script was developed in Matlab environment to automate qNMR analysis. Verification of the results is based on two evolving integration profiles. The analysis of binary mixtures of internal standards as well as pharmaceutical products has shown that all common artifacts (phase and baseline distortion, impurities) can be easily recognized in routine qNMR experiments. In the absence of distortion, deviation between automatically (mean value of several integrals) and manually calculated values was generally below 0.1%. The routine is independent of multiplet pattern, solvent, spectrometer, nuclei type and pulse sequence used. In general, the usage of the developed script can facilitate and verify results of routine qNMR analysis in an automatic manner. Copyright © 2017 John Wiley & Sons, Ltd.
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Affiliation(s)
- Yulia B Monakhova
- Spectral Service AG, Emil-Hoffmann-Straße 33, 50996, Cologne, Germany
- Institute of Chemistry, Saratov State University, Astrakhanskaya Street 83, 410012, Saratov, Russia
| | - Bernd W K Diehl
- Spectral Service AG, Emil-Hoffmann-Straße 33, 50996, Cologne, Germany
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111
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Zhou J, Lu C, Zhang D, Ma C, Su X. NMR-based metabolomics reveals the metabolite profiles of Vibrio parahaemolyticus under ferric iron stimulation. J Microbiol 2017; 55:628-634. [PMID: 28752295 DOI: 10.1007/s12275-017-6551-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Revised: 04/11/2017] [Accepted: 05/10/2017] [Indexed: 01/15/2023]
Abstract
Vibrio parahaemolyticus is a halophilic bacterium endemic to coastal areas, and its pathogenicity has caused widespread seafood poisoning. In our previous research, the protein expression of V. parahaemolyticus in Fe3+ medium was determined using isobaric tags for relative and absolute quantitation (iTRAQ). Here, nuclear magnetic resonance (NMR) was used to detect changes in the V. parahaemolyticus metabolome. NMR spectra were obtained using methanol-water extracts of intracellular metabolites from V. parahaemolyticus under various culture conditions, and 62 metabolites were identified, including serine, arginine, alanine, ornithine, tryptophan, glutamine, malate, NAD+, NADP+, oxypurinol, xanthosine, dCTP, uracil, thymine, hypoxanthine, and betaine. Among these, 21 metabolites were up-regulated after the stimulation of the cells by ferric iron, and 9 metabolites were down-regulated. These metabolites are involved in amino acid and protein synthesis, energy metabolism, DNA and RNA synthesis and osmolality. Based on these results, we conclude that Fe3+ influences the metabolite profiles of V. parahaemolyticus.
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Affiliation(s)
- Jun Zhou
- School of Marine Science, Ningbo University, Zhejiang, 315211, P. R. China
| | - Chenyang Lu
- School of Marine Science, Ningbo University, Zhejiang, 315211, P. R. China.
| | - Dijun Zhang
- School of Marine Science, Ningbo University, Zhejiang, 315211, P. R. China
| | - Chennv Ma
- School of Marine Science, Ningbo University, Zhejiang, 315211, P. R. China
| | - Xiurong Su
- School of Marine Science, Ningbo University, Zhejiang, 315211, P. R. China.
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Stryeck S, Birner-Gruenberger R, Madl T. Integrative metabolomics as emerging tool to study autophagy regulation. MICROBIAL CELL (GRAZ, AUSTRIA) 2017; 4:240-258. [PMID: 28845422 PMCID: PMC5568430 DOI: 10.15698/mic2017.08.584] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Accepted: 07/01/2017] [Indexed: 12/15/2022]
Abstract
Recent technological developments in metabolomics research have enabled in-depth characterization of complex metabolite mixtures in a wide range of biological, biomedical, environmental, agricultural, and nutritional research fields. Nuclear magnetic resonance spectroscopy and mass spectrometry are the two main platforms for performing metabolomics studies. Given their broad applicability and the systemic insight into metabolism that can be obtained it is not surprising that metabolomics becomes increasingly popular in basic biological research. In this review, we provide an overview on key metabolites, recent studies, and future opportunities for metabolomics in studying autophagy regulation. Metabolites play a pivotal role in autophagy regulation and are therefore key targets for autophagy research. Given the recent success of metabolomics, it can be expected that metabolomics approaches will contribute significantly to deciphering the complex regulatory mechanisms involved in autophagy in the near future and promote understanding of autophagy and autophagy-related diseases in living cells and organisms.
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Affiliation(s)
- Sarah Stryeck
- Institute of Molecular Biology and Biochemistry, Center of Molecular Medicine, Medical University of Graz, 8010 Graz, Austria
| | - Ruth Birner-Gruenberger
- Research Unit for Functional Proteomics and Metabolic Pathways, Institute of Pathology, Medical University of Graz, 8010 Graz, Austria
| | - Tobias Madl
- Institute of Molecular Biology and Biochemistry, Center of Molecular Medicine, Medical University of Graz, 8010 Graz, Austria
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113
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Li DW, Wang C, Brüschweiler R. Maximal clique method for the automated analysis of NMR TOCSY spectra of complex mixtures. JOURNAL OF BIOMOLECULAR NMR 2017; 68:195-202. [PMID: 28573376 PMCID: PMC7032946 DOI: 10.1007/s10858-017-0119-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2017] [Accepted: 05/24/2017] [Indexed: 05/16/2023]
Abstract
Characterization of the chemical components of complex mixtures in solution is important in many areas of biochemistry and chemical biology, including metabolomics. The use of 2D NMR total correlation spectroscopy (TOCSY) experiments has proven very useful for the identification of known metabolites as well as for the characterization of metabolites that are unknown by taking advantage of the good resolution and high sensitivity of this homonuclear experiment. Due to the complexity of the resulting spectra, automation is critical to facilitate and speed-up their analysis and enable high-throughput applications. To better meet these emerging needs, an automated spin-system identification algorithm of TOCSY spectra is introduced that represents the cross-peaks and their connectivities as a mathematical graph, for which all subgraphs are determined that are maximal cliques. Each maximal clique can be assigned to an individual spin system thereby providing a robust deconvolution of the original spectrum for the easy extraction of critical spin system information. The approach is demonstrated for a complex metabolite mixture consisting of 20 compounds and for E. coli cell lysate.
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Affiliation(s)
- Da-Wei Li
- Campus Chemical Instrument Center, The Ohio State University, Columbus, OH, 43210, USA.
| | - Cheng Wang
- Department of Chemistry and Biochemistry, The Ohio State University, CBEC Building, Columbus, OH, 43210, USA
| | - Rafael Brüschweiler
- Campus Chemical Instrument Center, The Ohio State University, Columbus, OH, 43210, USA.
- Department of Chemistry and Biochemistry, The Ohio State University, CBEC Building, Columbus, OH, 43210, USA.
- Department of Biological Chemistry and Pharmacology, The Ohio State University, Columbus, OH, 43210, USA.
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114
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Marshall DD, Powers R. Beyond the paradigm: Combining mass spectrometry and nuclear magnetic resonance for metabolomics. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2017; 100:1-16. [PMID: 28552170 PMCID: PMC5448308 DOI: 10.1016/j.pnmrs.2017.01.001] [Citation(s) in RCA: 133] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2016] [Revised: 01/04/2017] [Accepted: 01/08/2017] [Indexed: 05/02/2023]
Abstract
Metabolomics is undergoing tremendous growth and is being employed to solve a diversity of biological problems from environmental issues to the identification of biomarkers for human diseases. Nuclear magnetic resonance (NMR) and mass spectrometry (MS) are the analytical tools that are routinely, but separately, used to obtain metabolomics data sets due to their versatility, accessibility, and unique strengths. NMR requires minimal sample handling without the need for chromatography, is easily quantitative, and provides multiple means of metabolite identification, but is limited to detecting the most abundant metabolites (⩾1μM). Conversely, mass spectrometry has the ability to measure metabolites at very low concentrations (femtomolar to attomolar) and has a higher resolution (∼103-104) and dynamic range (∼103-104), but quantitation is a challenge and sample complexity may limit metabolite detection because of ion suppression. Consequently, liquid chromatography (LC) or gas chromatography (GC) is commonly employed in conjunction with MS, but this may lead to other sources of error. As a result, NMR and mass spectrometry are highly complementary, and combining the two techniques is likely to improve the overall quality of a study and enhance the coverage of the metabolome. While the majority of metabolomic studies use a single analytical source, there is a growing appreciation of the inherent value of combining NMR and MS for metabolomics. An overview of the current state of utilizing both NMR and MS for metabolomics will be presented.
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Affiliation(s)
- Darrell D Marshall
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, United States
| | - Robert Powers
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, United States.
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Karouia F, Peyvan K, Pohorille A. Toward biotechnology in space: High-throughput instruments for in situ biological research beyond Earth. Biotechnol Adv 2017; 35:905-932. [PMID: 28433608 DOI: 10.1016/j.biotechadv.2017.04.003] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2016] [Revised: 03/27/2017] [Accepted: 04/12/2017] [Indexed: 12/18/2022]
Abstract
Space biotechnology is a nascent field aimed at applying tools of modern biology to advance our goals in space exploration. These advances rely on our ability to exploit in situ high throughput techniques for amplification and sequencing DNA, and measuring levels of RNA transcripts, proteins and metabolites in a cell. These techniques, collectively known as "omics" techniques have already revolutionized terrestrial biology. A number of on-going efforts are aimed at developing instruments to carry out "omics" research in space, in particular on board the International Space Station and small satellites. For space applications these instruments require substantial and creative reengineering that includes automation, miniaturization and ensuring that the device is resistant to conditions in space and works independently of the direction of the gravity vector. Different paths taken to meet these requirements for different "omics" instruments are the subjects of this review. The advantages and disadvantages of these instruments and technological solutions and their level of readiness for deployment in space are discussed. Considering that effects of space environments on terrestrial organisms appear to be global, it is argued that high throughput instruments are essential to advance (1) biomedical and physiological studies to control and reduce space-related stressors on living systems, (2) application of biology to life support and in situ resource utilization, (3) planetary protection, and (4) basic research about the limits on life in space. It is also argued that carrying out measurements in situ provides considerable advantages over the traditional space biology paradigm that relies on post-flight data analysis.
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Affiliation(s)
- Fathi Karouia
- University of California San Francisco, Department of Pharmaceutical Chemistry, San Francisco, CA 94158, USA; NASA Ames Research Center, Exobiology Branch, MS239-4, Moffett Field, CA 94035, USA; NASA Ames Research Center, Flight Systems Implementation Branch, Moffett Field, CA 94035, USA.
| | | | - Andrew Pohorille
- University of California San Francisco, Department of Pharmaceutical Chemistry, San Francisco, CA 94158, USA; NASA Ames Research Center, Exobiology Branch, MS239-4, Moffett Field, CA 94035, USA.
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116
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Gowda GAN, Raftery D. Whole Blood Metabolomics by 1H NMR Spectroscopy Provides a New Opportunity To Evaluate Coenzymes and Antioxidants. Anal Chem 2017; 89:4620-4627. [PMID: 28318242 PMCID: PMC6245939 DOI: 10.1021/acs.analchem.7b00171] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Conventional human blood metabolomics employs serum or plasma and provides a wealth of metabolic information therein. However, this approach lacks the ability to measure and evaluate important metabolites such as coenzymes and antioxidants that are present at high concentrations in red blood cells. As an important alternative to serum/plasma metabolomics, we show here that a simple 1H NMR experiment can simultaneously measure coenzymes and antioxidants in extracts of whole human blood, in addition to the nearly 70 metabolites that were shown to be quantitated in serum/plasma recently [ Anal. Chem. 2015 , 87 , 706 - 715 ]. Coenzymes of redox reactions: oxidized/reduced nicotinamide adenine dinucleotide (NAD+ and NADH) and nicotinamide adenine dinucleotide phosphate (NADP+ and NADPH); coenzymes of energy including adenosine triphosphate (ATP), adenosine diphosphate (ADP), and adenosine monophosphate (AMP); and antioxidants, the sum of oxidized and reduced glutathione (GSSG and GSH) can be measured with essentially no additional effort. A new method was developed for detecting many of these unstable species without affecting other blood/blood plasma metabolites. The identities of coenzymes and antioxidants in blood NMR spectra were established combining 1D/2D NMR techniques, chemical shift databases, pH measurements and, finally, spiking with authentic compounds. This is the first study to report identification of major coenzymes and antioxidants and quantify them, simultaneously, with the large pool of other metabolites in human blood using NMR spectroscopy. Considering that the levels of coenzymes and antioxidants represent a sensitive measure of cellular functions in health and numerous diseases, the NMR method presented here potentially opens a new chapter in the metabolomics of blood.
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Affiliation(s)
- G. A. Nagana Gowda
- Northwest Metabolomics Research Center, University of Washington, Seattle, Washington 98109, United States
- Mitochondria and Metabolism Center, Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, Washington 98109, United States
| | - Daniel Raftery
- Northwest Metabolomics Research Center, University of Washington, Seattle, Washington 98109, United States
- Mitochondria and Metabolism Center, Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, Washington 98109, United States
- Department of Chemistry, University of Washington, Seattle, Washington 98109, United States
- Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, United States
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117
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Hoffmann F, Li DW, Sebastiani D, Brüschweiler R. Improved Quantum Chemical NMR Chemical Shift Prediction of Metabolites in Aqueous Solution toward the Validation of Unknowns. J Phys Chem A 2017; 121:3071-3078. [PMID: 28388058 DOI: 10.1021/acs.jpca.7b01954] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
A quantum-chemistry based protocol, termed MOSS-DFT, is presented for the prediction of 13C and 1H NMR chemical shifts of a wide range of organic molecules in aqueous solution, including metabolites. Molecular motif-specific linear scaling parameters are reported for five different density functional theory (DFT) methods (B97-2/pcS-1, B97-2/pcS-2, B97-2/pcS-3, B3LYP/pcS-2, and BLYP/pcS-2), which were applied to a large set of 176 metabolite molecules. The chemical shift root-mean-square deviations (RMSD) for the best method, B97-2/pcS-3, are 1.93 and 0.154 ppm for 13C and 1H chemical shifts, respectively. Excellent results have been obtained for chemical shifts of methyl and aromatic 13C and 1H that are not directly bonded to a heteroatom (O, N, S, or P) with RMSD values of 1.15/0.079 and 1.31/0.118 ppm, respectively. This study not only demonstrates how NMR chemical shift in aqueous environment can be improved over the commonly used global linear scaling approach, but also allows for motif-specific error estimates, which are useful for an improved chemical shift-based verification of metabolite candidates of metabolomics samples containing unknown components.
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Affiliation(s)
- Felix Hoffmann
- Institute of Chemistry, Martin-Luther-University Halle-Wittenberg , von-Danckelmann-Platz 4, 06120 Halle, Germany
| | - Da-Wei Li
- Campus Chemical Instrument Center, The Ohio State University , Columbus, Ohio 43210, United States
| | - Daniel Sebastiani
- Institute of Chemistry, Martin-Luther-University Halle-Wittenberg , von-Danckelmann-Platz 4, 06120 Halle, Germany
| | - Rafael Brüschweiler
- Campus Chemical Instrument Center, The Ohio State University , Columbus, Ohio 43210, United States.,Department of Chemistry and Biochemistry, 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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118
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Affiliation(s)
- G. A. Nagana Gowda
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine and
| | - Daniel Raftery
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine and
- Department of Chemistry, University of Washington, Seattle, Washington 98109, United States
- Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, United States
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119
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Wist J. Complex mixtures by NMR and complex NMR for mixtures: experimental and publication challenges. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2017; 55:22-28. [PMID: 27668407 DOI: 10.1002/mrc.4533] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2016] [Revised: 09/14/2016] [Accepted: 09/22/2016] [Indexed: 06/06/2023]
Abstract
Untargeted strategies have changed the rules of the game in complex mixture analysis, introducing an amazing potential for medical and biological applications that is just starting to be tapped. But with great power come great challenges; although untargeted mixture analysis opens the road for many exciting possibilities, the road is still full of perils. On the one hand, this article highlights some of the difficulties that need to be sorted for mixture analysis by NMR to fulfill its potential, along with insight on how they may be managed. Highlighted key points include the need for 'computer friendly' solutions for sharing data, experimental design and algorithm to facilitate the steady growth of knowledge and modeling ability in the field, and the need for large-scale studies to improve confidence in newly identified biomarkers. On the other hand, the second part of this article presents some breakthroughs in NMR experiments that, when combined, may modify the landscape of mixture analysis. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Julien Wist
- Chemistry Department, Universidad del Valle, Cali, Colombia
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120
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Bekri S. The role of metabolomics in precision medicine. EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT 2016. [DOI: 10.1080/23808993.2016.1273067] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Affiliation(s)
- Soumeya Bekri
- Department of Metabolic Biochemistry, Rouen University Hospital, Rouen 76000, France
- Normandie Univ, UNIROUEN, INSERM, CHU Rouen, IRIB, INSERM U1245, Rouen 76000, France
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121
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Contreras AV, Cocom-Chan B, Hernandez-Montes G, Portillo-Bobadilla T, Resendis-Antonio O. Host-Microbiome Interaction and Cancer: Potential Application in Precision Medicine. Front Physiol 2016; 7:606. [PMID: 28018236 PMCID: PMC5145879 DOI: 10.3389/fphys.2016.00606] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Accepted: 11/21/2016] [Indexed: 12/19/2022] Open
Abstract
It has been experimentally shown that host-microbial interaction plays a major role in shaping the wellness or disease of the human body. Microorganisms coexisting in human tissues provide a variety of benefits that contribute to proper functional activity in the host through the modulation of fundamental processes such as signal transduction, immunity and metabolism. The unbalance of this microbial profile, or dysbiosis, has been correlated with the genesis and evolution of complex diseases such as cancer. Although this latter disease has been thoroughly studied using different high-throughput (HT) technologies, its heterogeneous nature makes its understanding and proper treatment in patients a remaining challenge in clinical settings. Notably, given the outstanding role of host-microbiome interactions, the ecological interactions with microorganisms have become a new significant aspect in the systems that can contribute to the diagnosis and potential treatment of solid cancers. As a part of expanding precision medicine in the area of cancer research, efforts aimed at effective treatments for various kinds of cancer based on the knowledge of genetics, biology of the disease and host-microbiome interactions might improve the prediction of disease risk and implement potential microbiota-directed therapeutics. In this review, we present the state of the art of sequencing and metabolome technologies, computational methods and schemes in systems biology that have addressed recent breakthroughs of uncovering relationships or associations between microorganisms and cancer. Together, microbiome studies extend the horizon of new personalized treatments against cancer from the perspective of precision medicine through a synergistic strategy integrating clinical knowledge, HT data, bioinformatics, and systems biology.
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Affiliation(s)
| | - Benjamin Cocom-Chan
- Instituto Nacional de Medicina GenómicaMexico City, Mexico; Human Systems Biology Laboratory, Instituto Nacional de Medicina GenómicaMexico City, Mexico
| | - Georgina Hernandez-Montes
- Coordinación de la Investigación Científica, Red de Apoyo a la Investigación-National Autonomous University of Mexico (UNAM) Mexico City, Mexico
| | - Tobias Portillo-Bobadilla
- Coordinación de la Investigación Científica, Red de Apoyo a la Investigación-National Autonomous University of Mexico (UNAM) Mexico City, Mexico
| | - Osbaldo Resendis-Antonio
- Instituto Nacional de Medicina GenómicaMexico City, Mexico; Human Systems Biology Laboratory, Instituto Nacional de Medicina GenómicaMexico City, Mexico; Coordinación de la Investigación Científica, Red de Apoyo a la Investigación-National Autonomous University of Mexico (UNAM)Mexico City, Mexico
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Gogiashvili M, Edlund K, Gianmoena K, Marchan R, Brik A, Andersson JT, Lambert J, Madjar K, Hellwig B, Rahnenführer J, Hengstler JG, Hergenröder R, Cadenas C. Metabolic profiling of ob/ob mouse fatty liver using HR-MAS 1H-NMR combined with gene expression analysis reveals alterations in betaine metabolism and the transsulfuration pathway. Anal Bioanal Chem 2016; 409:1591-1606. [PMID: 27896396 DOI: 10.1007/s00216-016-0100-1] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2016] [Revised: 10/21/2016] [Accepted: 11/14/2016] [Indexed: 02/07/2023]
Abstract
Metabolic perturbations resulting from excessive hepatic fat accumulation are poorly understood. Thus, in this study, leptin-deficient ob/ob mice, a mouse model of fatty liver disease, were used to investigate metabolic alterations in more detail. Metabolites were quantified in intact liver tissues of ob/ob (n = 8) and control (n = 8) mice using high-resolution magic angle spinning (HR-MAS) 1H-NMR. In addition, after demonstrating that HR-MAS 1H-NMR does not affect RNA integrity, transcriptional changes were measured by quantitative real-time PCR on RNA extracted from the same specimens after HR-MAS 1H-NMR measurements. Importantly, the gene expression changes obtained agreed with those observed by Affymetrix microarray analysis performed on RNA isolated directly from fresh-frozen tissue. In total, 40 metabolites could be assigned in the spectra and subsequently quantified. Quantification of lactate was also possible after applying a lactate-editing pulse sequence that suppresses the lipid signal, which superimposes the lactate methyl resonance at 1.3 ppm. Significant differences were detected for creatinine, glutamate, glycine, glycolate, trimethylamine-N-oxide, dimethylglycine, ADP, AMP, betaine, phenylalanine, and uridine. Furthermore, alterations in one-carbon metabolism, supported by both metabolic and transcriptional changes, were observed. These included reduced demethylation of betaine to dimethylglycine and the reduced expression of genes coding for transsulfuration pathway enzymes, which appears to preserve methionine levels, but may limit glutathione synthesis. Overall, the combined approach is advantageous as it identifies changes not only at the single gene or metabolite level but also deregulated pathways, thus providing critical insight into changes accompanying fatty liver disease. Graphical abstract A Evaluation of RNA integrity before and after HR-MAS 1H-NMR of intact mouse liver tissue. B Metabolite concentrations and gene expression levels assessed in ob/ob (steatotic) and ob/+ (control) mice using HR-MAS 1H-NMR and qRT-PCR, respectively.
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Affiliation(s)
- Mikheil Gogiashvili
- Leibniz Institut für Analytische Wissenschaften - ISAS e.V., Bunsen-Kirchhoff-Strasse 11, 44139, Dortmund, Germany.
| | - Karolina Edlund
- Leibniz Research Centre for Working Environment and Human Factors (IfADo), Ardeystrasse 67, 44139, Dortmund, Germany
| | - Kathrin Gianmoena
- Leibniz Research Centre for Working Environment and Human Factors (IfADo), Ardeystrasse 67, 44139, Dortmund, Germany
| | - Rosemarie Marchan
- Leibniz Research Centre for Working Environment and Human Factors (IfADo), Ardeystrasse 67, 44139, Dortmund, Germany
| | - Alexander Brik
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance (IPA), Institute of the Ruhr-Universität Bochum, Bürkle-de-la-Camp-Platz 1, 44789, Bochum, Germany
| | - Jan T Andersson
- Institute of Inorganic and Analytical Chemistry, University of Münster, Corrensstrasse 30, 48149, Münster, Germany
| | - Jörg Lambert
- Leibniz Institut für Analytische Wissenschaften - ISAS e.V., Bunsen-Kirchhoff-Strasse 11, 44139, Dortmund, Germany
| | - Katrin Madjar
- Faculty of Statistics, TU Dortmund University, Mathematics Building, 44221, Dortmund, Germany
| | - Birte Hellwig
- Faculty of Statistics, TU Dortmund University, Mathematics Building, 44221, Dortmund, Germany
| | - Jörg Rahnenführer
- Faculty of Statistics, TU Dortmund University, Mathematics Building, 44221, Dortmund, Germany
| | - Jan G Hengstler
- Leibniz Research Centre for Working Environment and Human Factors (IfADo), Ardeystrasse 67, 44139, Dortmund, Germany
| | - Roland Hergenröder
- Leibniz Institut für Analytische Wissenschaften - ISAS e.V., Bunsen-Kirchhoff-Strasse 11, 44139, Dortmund, Germany
| | - Cristina Cadenas
- Leibniz Research Centre for Working Environment and Human Factors (IfADo), Ardeystrasse 67, 44139, Dortmund, Germany
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Metabolomics, a Powerful Tool for Agricultural Research. Int J Mol Sci 2016; 17:ijms17111871. [PMID: 27869667 PMCID: PMC5133871 DOI: 10.3390/ijms17111871] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2016] [Revised: 11/02/2016] [Accepted: 11/03/2016] [Indexed: 11/17/2022] Open
Abstract
Metabolomics, which is based mainly on nuclear magnetic resonance (NMR), gas-chromatography (GC) or liquid-chromatography (LC) coupled to mass spectrometry (MS) analytical technologies to systematically acquire the qualitative and quantitative information of low-molecular-mass endogenous metabolites, provides a direct snapshot of the physiological condition in biological samples. As complements to transcriptomics and proteomics, it has played pivotal roles in agricultural and food science research. In this review, we discuss the capacities of NMR, GC/LC-MS in the acquisition of plant metabolome, and address the potential promise and diverse applications of metabolomics, particularly lipidomics, to investigate the responses of Arabidopsis thaliana, a primary plant model for agricultural research, to environmental stressors including heat, freezing, drought, and salinity.
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MacKinnon N, While PT, Korvink JG. Novel selective TOCSY method enables NMR spectral elucidation of metabolomic mixtures. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2016; 272:147-157. [PMID: 27701031 DOI: 10.1016/j.jmr.2016.09.011] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2016] [Revised: 09/15/2016] [Accepted: 09/15/2016] [Indexed: 06/06/2023]
Abstract
Complex mixture analysis is routinely encountered in NMR-based investigations. With the aim of component identification, spectral complexity may be addressed chromatographically or spectroscopically, the latter being favored to reduce sample handling requirements. An attractive experiment is selective total correlation spectroscopy (sel-TOCSY), which is capable of providing tremendous spectral simplification and thereby enhancing assignment capability. Unfortunately, isolating a well resolved resonance is increasingly difficult as the complexity of the mixture increases and the assumption of single spin system excitation is no longer robust. We present TOCSY optimized mixture elucidation (TOOMIXED), a technique capable of performing spectral assignment particularly in the case where the assumption of single spin system excitation is relaxed. Key to the technique is the collection of a series of 1D sel-TOCSY experiments as a function of the isotropic mixing time (τm), resulting in a series of resonance intensities indicative of the underlying molecular structure. By comparing these τm-dependent intensity patterns with a library of pre-determined component spectra, one is able to regain assignment capability. After consideration of the technique's robustness, we tested TOOMIXED firstly on a model mixture. As a benchmark we were able to assign a molecule with high confidence in the case of selectively exciting an isolated resonance. Assignment confidence was not compromised when performing TOOMIXED on a resonance known to contain multiple overlapping signals, and in the worst case the method suggested a follow-up sel-TOCSY experiment to confirm an ambiguous assignment. TOOMIXED was then demonstrated on two realistic samples (whisky and urine), where under our conditions an approximate limit of detection of 0.6mM was determined. Taking into account literature reports for the sel-TOCSY limit of detection, the technique should reach on the order of 10μM sensitivity. We anticipate this technique will be highly attractive to various analytical fields facing mixture analysis, including metabolomics, foodstuff analysis, pharmaceutical analysis, and forensics.
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Affiliation(s)
- Neil MacKinnon
- Institute for Microstructure Technology - IMT, Karlsruhe Institute of Technology, Karlsruhe, Germany.
| | - Peter T While
- Department of Radiology and Nuclear Medicine, St. Olav's University Hospital, Trondheim, Norway
| | - Jan G Korvink
- Institute for Microstructure Technology - IMT, Karlsruhe Institute of Technology, Karlsruhe, Germany
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125
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Carrabba MG, Tavel L, Oliveira G, Forcina A, Quilici G, Nardelli F, Tresoldi C, Ambrosi A, Ciceri F, Bernardi M, Vago L, Musco G. Integrating a prospective pilot trial and patient-derived xenografts to trace metabolic changes associated with acute myeloid leukemia. J Hematol Oncol 2016; 9:115. [PMID: 27793157 PMCID: PMC5086061 DOI: 10.1186/s13045-016-0346-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2016] [Accepted: 10/18/2016] [Indexed: 11/30/2022] Open
Abstract
Despite the considerable progress in understanding the molecular bases of acute myeloid leukemia (AML), new tools to link disease biology to the unpredictable patient clinical course are still needed. Herein, high-throughput metabolomics, combined with the other “-omics” disciplines, holds promise in identifying disease-specific and clinically relevant features. In this study, we took advantage of nuclear magnetic resonance (NMR) to trace AML-associated metabolic trajectory employing two complementary strategies. On the one hand, we performed a prospective observational clinical trial to identify metabolic changes associated with blast clearance during the first two cycles of intensive chemotherapy in nine adult patients. On the other hand, to reduce the intrinsic variability associated with human samples and AML genetic heterogeneity, we analyzed the metabolic changes in the plasma of immunocompromised mice upon engraftment of primary human AML blasts. Combining the two longitudinal approaches, we narrowed our screen to seven common metabolites, for which we observed a mirror-like trajectory in mice and humans, tracing AML progression and remission, respectively. We interpreted this set of metabolites as a dynamic fingerprint of AML evolution. Overall, these NMR-based metabolomic data, to be consolidated in larger cohorts and integrated in more comprehensive system biology approaches, hold promise for providing valuable and non-redundant information on the systemic effects of leukemia.
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Affiliation(s)
- Matteo G Carrabba
- Unit of Hematology and Bone Marrow Transplantation, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy
| | - Laurette Tavel
- Biomolecular Nuclear Magnetic Resonance Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Giacomo Oliveira
- Unit of Immunogenetics, Leukemia Genomics and Immunobiology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Alessandra Forcina
- Unit of Hematology and Bone Marrow Transplantation, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy
| | - Giacomo Quilici
- Biomolecular Nuclear Magnetic Resonance Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Francesca Nardelli
- Biomolecular Nuclear Magnetic Resonance Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Cristina Tresoldi
- Molecular Hematology Laboratory, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Alessandro Ambrosi
- Center for Statistics in Biomedical Sciences, University Vita-Salute San Raffaele, Milan, Italy
| | - Fabio Ciceri
- Unit of Hematology and Bone Marrow Transplantation, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy. .,University Vita-Salute San Raffaele, Milan, Italy.
| | - Massimo Bernardi
- Unit of Hematology and Bone Marrow Transplantation, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy
| | - Luca Vago
- Unit of Hematology and Bone Marrow Transplantation, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132, Milan, Italy.,Unit of Immunogenetics, Leukemia Genomics and Immunobiology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Giovanna Musco
- Biomolecular Nuclear Magnetic Resonance Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
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126
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Di Gialleonardo V, Tee SS, Aldeborgh HN, Miloushev VZ, Cunha LS, Sukenick GD, Keshari KR. High-Throughput Indirect Quantitation of 13C Enriched Metabolites Using 1H NMR. Anal Chem 2016; 88:11147-11153. [PMID: 27749041 DOI: 10.1021/acs.analchem.6b03307] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Nuclear magnetic resonance (NMR) spectroscopy is widely used in metabolomics to perform quantitative profiling of low-molecular weight compounds from biological specimens. The measurement of endogenous metabolites using NMR has proven to be a powerful tool to identify new metabolic biomarkers in physiological and pathological conditions, and to study and evaluate treatment efficiency. In this study we present a rapid approach to indirectly quantify 13C enriched molecules using one-dimensional (1D) 1H NMR. We demonstrate this approach using isotopically labeled [1,6-13C]glucose and in four different cell lines. We confirm the applicability of this approach for treatment follow-up, utilizing a renal cancer cell line with rapamycin as a tool compound to study changes in metabolic profiles. Finally, we validate the applicability of this method to study metabolic biomarkers from ex vivo tumor extracts, after infusion, using isotopically enriched glucose. Given the high throughput and increased sensitivity of direct-detect 1H NMR, this analytical approach provides an avenue for simple and rapid metabolic analysis of biological samples including blood, urine, and biopsies.
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Affiliation(s)
- Valentina Di Gialleonardo
- Radiology and Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center , New York, New York 10065, United Sates
| | - Sui Seng Tee
- Radiology and Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center , New York, New York 10065, United Sates
| | - Hannah N Aldeborgh
- Radiology and Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center , New York, New York 10065, United Sates
| | - Vesselin Z Miloushev
- Radiology and Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center , New York, New York 10065, United Sates
| | - Lidia S Cunha
- Radiology and Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center , New York, New York 10065, United Sates
| | - George D Sukenick
- Radiology and Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center , New York, New York 10065, United Sates
| | - Kayvan R Keshari
- Radiology and Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center , New York, New York 10065, United Sates.,Weill Cornell Medical College, New York, New York 10065, United States
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127
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Vicente-Muñoz S, Morcillo I, Puchades-Carrasco L, Payá V, Pellicer A, Pineda-Lucena A. Pathophysiologic processes have an impact on the plasma metabolomic signature of endometriosis patients. Fertil Steril 2016; 106:1733-1741.e1. [PMID: 27793377 DOI: 10.1016/j.fertnstert.2016.09.014] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2016] [Revised: 08/31/2016] [Accepted: 09/07/2016] [Indexed: 02/01/2023]
Abstract
OBJECTIVE To evaluate potential variations in the plasma metabolomic profile of endometriosis patients as a consequence of pathophysiologic alterations associated with this disorder. DESIGN Prospective study. For each subject, a plasma sample was collected after overnight fasting and before surgery. SETTING University medical center. PATIENT(S) The clinical cohort included 50 endometriosis patients, diagnosed at early (n = 6) and advanced (n = 44) stages of the disease, and 23 healthy women. All volunteers underwent diagnostic laparoscopy to visually confirm the presence or absence of endometriotic lesions. INTERVENTION(S) Metabolomic profiling of plasma samples based on 1H-nuclear magnetic resonance (NMR) spectroscopy in combination with statistical approaches. MAIN OUTCOME MEASURE(S) Comparative identification of metabolites present in plasma from endometriosis patients and healthy women. RESULT(S) The plasma metabolomic profile of endometriosis patients was characterized by increased concentration of valine, fucose, choline-containing metabolites, lysine/arginine, and lipoproteins and decreased concentration of creatinine compared with healthy women. Metabolic alterations identified in the plasma metabolomic profile of endometriosis patients correlate with pathophysiologic events previously described in the progression of this disease. CONCLUSION(S) The results highlight the potential of 1H-NMR-based metabolomics to characterize metabolic alterations associated with endometriosis in plasma samples. This information could be useful to get a better understanding of the molecular mechanisms involved in the pathogenesis of endometriosis, thus facilitating the noninvasive diagnosis of this pathology at early stages.
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Affiliation(s)
- Sara Vicente-Muñoz
- Structural Biochemistry Laboratory, Centro de Investigación Príncipe Felipe, Valencia, Spain; Department of Obstetrics and Gynecology, Hospital Universitario La Fe, Valencia, Spain
| | - Inmaculada Morcillo
- Department of Obstetrics and Gynecology, Hospital Universitario La Fe, Valencia, Spain
| | | | - Vicente Payá
- Department of Obstetrics and Gynecology, Hospital Universitario La Fe, Valencia, Spain
| | - Antonio Pellicer
- Department of Obstetrics and Gynecology, Hospital Universitario La Fe, Valencia, Spain; Instituto Valenciano de Infertilidad, Valencia, Spain
| | - Antonio Pineda-Lucena
- Structural Biochemistry Laboratory, Centro de Investigación Príncipe Felipe, Valencia, Spain; Instituto de Investigación Sanitaria La Fe, Valencia, Spain.
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128
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Rhoades SD, Sengupta A, Weljie AM. Time is ripe: maturation of metabolomics in chronobiology. Curr Opin Biotechnol 2016; 43:70-76. [PMID: 27701007 DOI: 10.1016/j.copbio.2016.09.007] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2016] [Revised: 09/15/2016] [Accepted: 09/18/2016] [Indexed: 12/14/2022]
Abstract
Sleep and circadian rhythms studies have recently benefited from metabolomics analyses, uncovering new connections between chronobiology and metabolism. From untargeted mass spectrometry to quantitative nuclear magnetic resonance spectroscopy, a diversity of analytical approaches has been applied for biomarker discovery in the field. In this review we consider advances in the application of metabolomics technologies which have uncovered significant effects of sleep and circadian cycles on several metabolites, namely phosphatidylcholine species, medium-chain carnitines, and aromatic amino acids. Study design and data processing measures essential for detecting rhythmicity in metabolomics data are also discussed. Future developments in these technologies are anticipated vis-à-vis validating early findings, given metabolomics has only recently entered the ring with other systems biology assessments in chronometabolism studies.
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Affiliation(s)
- Seth D Rhoades
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States; Institute of Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Arjun Sengupta
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States; Institute of Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Aalim M Weljie
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States; Institute of Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States.
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129
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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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130
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Bingol K, Brüschweiler R. Knowns and unknowns in metabolomics identified by multidimensional NMR and hybrid MS/NMR methods. Curr Opin Biotechnol 2016; 43:17-24. [PMID: 27552705 DOI: 10.1016/j.copbio.2016.07.006] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2016] [Revised: 07/26/2016] [Accepted: 07/28/2016] [Indexed: 01/10/2023]
Abstract
Metabolomics continues to make rapid progress through the development of new and better methods and their applications to gain insight into the metabolism of a wide range of different biological systems from a systems biology perspective. Customization of NMR databases and search tools allows the faster and more accurate identification of known metabolites, whereas the identification of unknowns, without a need for extensive purification, requires new strategies to integrate NMR with mass spectrometry, cheminformatics, and computational methods. For some applications, the use of covalent and non-covalent attachments in the form of labeled tags or nanoparticles can significantly reduce the complexity of these tasks.
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Affiliation(s)
- Kerem Bingol
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Rafael Brüschweiler
- Campus Chemical Instrument Center, The Ohio State University, Columbus, OH 43210, United States; Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH 43210, United States; Department of Biological Chemistry and Pharmacology, The Ohio State University, Columbus, OH 43210, United States.
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131
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Sweeney SR, Kavanaugh A, Lodi A, Wang B, Boyle D, Tiziani S, Guma M. Metabolomic profiling predicts outcome of rituximab therapy in rheumatoid arthritis. RMD Open 2016; 2:e000289. [PMID: 27651926 PMCID: PMC5013418 DOI: 10.1136/rmdopen-2016-000289] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2016] [Revised: 06/27/2016] [Accepted: 07/21/2016] [Indexed: 01/13/2023] Open
Abstract
OBJECTIVE To determine whether characterisation of patients' metabolic profiles, utilising nuclear magnetic resonance (NMR) and mass spectrometry (MS), could predict response to rituximab therapy. 23 patients with active, seropositive rheumatoid arthritis (RA) on concomitant methotrexate were treated with rituximab. Patients were grouped into responders and non-responders according to the American College of Rheumatology improvement criteria, at a 20% level at 6 months. A Bruker Avance 700 MHz spectrometer and a Thermo Scientific Q Exactive Hybrid Quadrupole-Orbitrap mass spectrometer were used to acquire (1)H-NMR and ultra high pressure liquid chromatography (UPLC)-MS/MS spectra, respectively, of serum samples before and after rituximab therapy. Data processing and statistical analysis were performed in MATLAB. 14 patients were characterised as responders, and 9 patients were considered non-responders. 7 polar metabolites (phenylalanine, 2-hydroxyvalerate, succinate, choline, glycine, acetoacetate and tyrosine) and 15 lipid species were different between responders and non-responders at baseline. Phosphatidylethanolamines, phosphatidyserines and phosphatidylglycerols were downregulated in responders. An opposite trend was observed in phosphatidylinositols. At 6 months, 5 polar metabolites (succinate, taurine, lactate, pyruvate and aspartate) and 37 lipids were different between groups. The relationship between serum metabolic profiles and clinical response to rituximab suggests that (1)H-NMR and UPLC-MS/MS may be promising tools for predicting response to rituximab.
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Affiliation(s)
- Shannon R Sweeney
- Department of Nutritional Sciences, Dell Pediatric Research Institute, University of Texas at Austin, Austin, Texas, USA
| | - Arthur Kavanaugh
- Division of Rheumatology, Allergy and Immunology, UC San Diego School of Medicine, La Jolla, California, USA
| | - Alessia Lodi
- Department of Nutritional Sciences, Dell Pediatric Research Institute, University of Texas at Austin, Austin, Texas, USA
| | - Bo Wang
- Department of Nutritional Sciences, Dell Pediatric Research Institute, University of Texas at Austin, Austin, Texas, USA
| | - David Boyle
- Division of Rheumatology, Allergy and Immunology, UC San Diego School of Medicine, La Jolla, California, USA
| | - Stefano Tiziani
- Department of Nutritional Sciences, Dell Pediatric Research Institute, University of Texas at Austin, Austin, Texas, USA
| | - Monica Guma
- Division of Rheumatology, Allergy and Immunology, UC San Diego School of Medicine, La Jolla, California, USA
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132
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Chatzimitakos TG, Stalikas CD. Qualitative Alterations of Bacterial Metabolome after Exposure to Metal Nanoparticles with Bactericidal Properties: A Comprehensive Workflow Based on (1)H NMR, UHPLC-HRMS, and Metabolic Databases. J Proteome Res 2016; 15:3322-30. [PMID: 27432757 DOI: 10.1021/acs.jproteome.6b00489] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Metal nanoparticles (NPs) have proven to be more toxic than bulk analogues of the same chemical composition due to their unique physical properties. The NPs, lately, have drawn the attention of researchers because of their antibacterial and biocidal properties. In an effort to shed light on the mechanism through which the bacteria elimination is achieved and the metabolic changes they undergo, an untargeted metabolomic fingerprint study was carried out on Gram-positive (Staphylococcus aureus) and Gram-negative (Escherichia coli) bacteria species. The (1)H NMR spectroscopy, in conjunction with high resolution mass-spectrometry (HRMS) and an unsophisticated data processing workflow were implemented. The combined NMR/HRMS data, supported by an open-access metabolomic database, proved to be efficacious in the process of assigning a putative annotation to a wide range of metabolite signals and is a useful tool to appraise the metabolome alterations, as a consequence of bacterial response to NPs. Interestingly, not all the NPs diminished the intracellular metabolites; bacteria treated with iron NPs produced metabolites not present in the nonexposed bacteria sample, implying the activation of previously inactive metabolic pathways. In contrast, copper and iron-copper NPs reduced the annotated metabolites, alluding to the conclusion that the metabolic pathways (mainly alanine, aspartate, and glutamate metabolism, beta-alanine metabolism, glutathione metabolism, and arginine and proline metabolism) were hindered by the interactions of NPs with the intracellular metabolites.
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Affiliation(s)
- Theodoros G Chatzimitakos
- Laboratory of Analytical Chemistry, Department of Chemistry, University of Ioannina , 45110 Ioannina, Greece
| | - Constantine D Stalikas
- Laboratory of Analytical Chemistry, Department of Chemistry, University of Ioannina , 45110 Ioannina, Greece
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133
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Deng L, Gu H, Zhu J, Nagana Gowda GA, Djukovic D, Chiorean EG, Raftery D. Combining NMR and LC/MS Using Backward Variable Elimination: Metabolomics Analysis of Colorectal Cancer, Polyps, and Healthy Controls. Anal Chem 2016; 88:7975-83. [PMID: 27437783 DOI: 10.1021/acs.analchem.6b00885] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Both nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) play important roles in metabolomics. The complementary features of NMR and MS make their combination very attractive; however, currently the vast majority of metabolomics studies use either NMR or MS separately, and variable selection that combines NMR and MS for biomarker identification and statistical modeling is still not well developed. In this study focused on methodology, we developed a backward variable elimination partial least-squares discriminant analysis algorithm embedded with Monte Carlo cross validation (MCCV-BVE-PLSDA), to combine NMR and targeted liquid chromatography (LC)/MS data. Using the metabolomics analysis of serum for the detection of colorectal cancer (CRC) and polyps as an example, we demonstrate that variable selection is vitally important in combining NMR and MS data. The combined approach was better than using NMR or LC/MS data alone in providing significantly improved predictive accuracy in all the pairwise comparisons among CRC, polyps, and healthy controls. Using this approach, we selected a subset of metabolites responsible for the improved separation for each pairwise comparison, and we achieved a comprehensive profile of altered metabolite levels, including those in glycolysis, the TCA cycle, amino acid metabolism, and other pathways that were related to CRC and polyps. MCCV-BVE-PLSDA is straightforward, easy to implement, and highly useful for studying the contribution of each individual variable to multivariate statistical models. On the basis of these results, we recommend using an appropriate variable selection step, such as MCCV-BVE-PLSDA, when analyzing data from multiple analytical platforms to obtain improved statistical performance and a more accurate biological interpretation, especially for biomarker discovery. Importantly, the approach described here is relatively universal and can be easily expanded for combination with other analytical technologies.
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Affiliation(s)
- Lingli Deng
- Department of Information Engineering, East China University of Technology , 418 Guanglan Avenue, Nanchang, Jiangxi Province 330013, China.,Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington , 850 Republican Street, Seattle, Washington 98109, United States
| | - Haiwei Gu
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington , 850 Republican Street, Seattle, Washington 98109, United States.,Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology , 418 Guanglan Avenue, Nanchang, Jiangxi Province 330013, China
| | - Jiangjiang Zhu
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington , 850 Republican Street, Seattle, Washington 98109, United States
| | - G A Nagana Gowda
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington , 850 Republican Street, Seattle, Washington 98109, United States
| | - Danijel Djukovic
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington , 850 Republican Street, Seattle, Washington 98109, United States
| | - E Gabriela Chiorean
- Department of Medicine, University of Washington , 825 Eastlake Avenue East, Seattle, Washington 98109, United States.,Indiana University Melvin and Bren Simon Cancer Center , 535 Barnhill Drive, Indianapolis, Indiana 46202, United States
| | - Daniel Raftery
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington , 850 Republican Street, Seattle, Washington 98109, United States.,Department of Chemistry, Purdue University , 560 Oval Drive, West Lafayette, Indiana 47907, United States.,Public Health Sciences Division, Fred Hutchinson Cancer Research Center , 1100 Fairview Avenue North, Seattle, Washington 98109, United States
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134
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van Duynhoven JPM, Jacobs DM. Assessment of dietary exposure and effect in humans: The role of NMR. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2016; 96:58-72. [PMID: 27573181 DOI: 10.1016/j.pnmrs.2016.03.001] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2015] [Revised: 03/19/2016] [Accepted: 03/19/2016] [Indexed: 06/06/2023]
Abstract
In human nutritional science progress has always depended strongly on analytical measurements for establishing relationships between diet and health. This field has undergone significant changes as a result of the development of NMR and mass spectrometry methods for large scale detection, identification and quantification of metabolites in body fluids. This has allowed systematic studies of the metabolic fingerprints that biological processes leave behind, and has become the research field of metabolomics. As a metabolic profiling technique, NMR is at its best when its unbiased nature, linearity and reproducibility are exploited in well-controlled nutritional intervention and cross-sectional population screening studies. Although its sensitivity is less good than that of mass spectrometry, NMR has maintained a strong position in metabolomics through implementation of standardisation protocols, hyphenation with mass spectrometry and chromatographic techniques, accurate quantification and spectral deconvolution approaches, and high-throughput automation. Thus, NMR-based metabolomics has contributed uniquely to new insights into dietary exposure, in particular by unravelling the metabolic fates of phytochemicals and the discovery of dietary intake markers. NMR profiling has also contributed to the understanding of the subtle effects of diet on central metabolism and lipoprotein metabolism. In order to hold its ground in nutritional metabolomics, NMR will need to step up its performance in sensitivity and resolution; the most promising routes forward are the analytical use of dynamic nuclear polarisation and developments in microcoil construction and automated fractionation.
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Affiliation(s)
- John P M van Duynhoven
- Unilever R&D Vlaardingen, Olivier van Noortlaan 120, 3130AC Vlaardingen, The Netherlands; Laboratory of Biophysics and Wageningen NMR Centre, Wageningen University, Dreijenlaan 3, 6703HA Wageningen, The Netherlands.
| | - Doris M Jacobs
- Unilever R&D Vlaardingen, Olivier van Noortlaan 120, 3130AC Vlaardingen, The Netherlands
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135
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Metabolomics: Bridging the Gap between Pharmaceutical Development and Population Health. Metabolites 2016; 6:metabo6030020. [PMID: 27399792 PMCID: PMC5041119 DOI: 10.3390/metabo6030020] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2016] [Revised: 06/06/2016] [Accepted: 07/01/2016] [Indexed: 12/28/2022] Open
Abstract
Metabolomics has emerged as an essential tool for studying metabolic processes, stratification of patients, as well as illuminating the fundamental metabolic alterations in disease onset, progression, or response to therapeutic intervention. Metabolomics materialized within the pharmaceutical industry as a standalone assay in toxicology and disease pathology and eventually evolved towards aiding in drug discovery and pre-clinical studies via supporting pharmacokinetic and pharmacodynamic characterization of a drug or a candidate. Recent progress in the field is illustrated by coining of the new term—Pharmacometabolomics. Integration of data from metabolomics with large-scale omics along with clinical, molecular, environmental and behavioral analysis has demonstrated the enhanced utility of deconstructing the complexity of health, disease, and pharmaceutical intervention(s), which further highlight it as an essential component of systems medicine. This review presents the current state and trend of metabolomics applications in pharmaceutical development, and highlights the importance and potential of clinical metabolomics as an essential part of multi-omics protocols that are directed towards shaping precision medicine and population health.
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136
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Lu Y, Hu F, Miyakawa T, Tanokura M. Complex Mixture Analysis of Organic Compounds in Yogurt by NMR Spectroscopy. Metabolites 2016; 6:metabo6020019. [PMID: 27322339 PMCID: PMC4931550 DOI: 10.3390/metabo6020019] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2016] [Revised: 06/08/2016] [Accepted: 06/13/2016] [Indexed: 11/16/2022] Open
Abstract
NMR measurements do not require separation and chemical modification of samples and therefore rapidly and directly provide non-targeted information on chemical components in complex mixtures. In this study, one-dimensional (¹H, (13)C, and (31)P) and two-dimensional (¹H-(13)C and ¹H-(31)P) NMR spectroscopy were conducted to analyze yogurt without any pretreatment. ¹H, (13)C, and (31)P NMR signals were assigned to 10 types of compounds. The signals of α/β-lactose and α/β-galactose were separately observed in the ¹H NMR spectra. In addition, the signals from the acyl chains of milk fats were also successfully identified but overlapped with many other signals. Quantitative difference spectra were obtained by subtracting the diffusion ordered spectroscopy (DOSY) spectra from the quantitative ¹H NMR spectra. This method allowed us to eliminate interference on the overlaps; therefore, the correct intensities of signals overlapped with those from the acyl chains of milk fat could be determined directly without separation. Moreover, the ¹H-(31)P HMBC spectra revealed for the first time that N-acetyl-d-glucosamine-1-phosphate is contained in yogurt.
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Affiliation(s)
- Yi Lu
- Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan.
| | - Fangyu Hu
- Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan.
| | - Takuya Miyakawa
- Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan.
| | - Masaru Tanokura
- Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan.
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137
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Bornet A, Maucourt M, Deborde C, Jacob D, Milani J, Vuichoud B, Ji X, Dumez JN, Moing A, Bodenhausen G, Jannin S, Giraudeau P. Highly Repeatable Dissolution Dynamic Nuclear Polarization for Heteronuclear NMR Metabolomics. Anal Chem 2016; 88:6179-83. [PMID: 27253320 DOI: 10.1021/acs.analchem.6b01094] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
At natural (13)C abundance, metabolomics based on heteronuclear NMR is limited by sensitivity. We have recently demonstrated how hyperpolarization by dissolution dynamic nuclear polarization (D-DNP) assisted by cross-polarization (CP) provides a reliable way of enhancing the sensitivity of heteronuclear NMR in dilute mixtures of metabolites. In this Technical Note, we evaluate the precision of this experimental approach, a critical point for applications to metabolomics. The higher the repeatability, the greater the likelihood that one can detect small biologically relevant differences between samples. The average repeatability of our state-of-the-art D-DNP NMR equipment for samples of metabolomic relevance (20 mg dry weight tomato extracts) is 3.6% for signals above the limit of quantification (LOQ) and 6.4% when all the signals above the limit of detection (LOD) are taken into account. This first report on the repeatability of D-DNP highlights the compatibility of the technique with the requirements of metabolomics and confirms its potential as an analytical tool for such applications.
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Affiliation(s)
- Aurélien Bornet
- Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL) , 1015 Lausanne, Switzerland
| | - Mickaël Maucourt
- Plateforme Métabolome Bordeaux-MetaboHUB, Centre de Génomique Fonctionnelle Bordeaux, IBVM, Centre INRA Bordeaux, 33140 Villenave d'Ornon, France.,Université de Bordeaux , UMR 1332 Biologie du Fruit et Pathologie, Centre INRA Bordeaux, 33140 Villenave d'Ornon, France
| | - Catherine Deborde
- Plateforme Métabolome Bordeaux-MetaboHUB, Centre de Génomique Fonctionnelle Bordeaux, IBVM, Centre INRA Bordeaux, 33140 Villenave d'Ornon, France.,INRA, UMR 1332 Biologie du Fruit et Pathologie, Centre INRA Bordeaux, 33140 Villenave d'Ornon, France
| | - Daniel Jacob
- Plateforme Métabolome Bordeaux-MetaboHUB, Centre de Génomique Fonctionnelle Bordeaux, IBVM, Centre INRA Bordeaux, 33140 Villenave d'Ornon, France.,INRA, UMR 1332 Biologie du Fruit et Pathologie, Centre INRA Bordeaux, 33140 Villenave d'Ornon, France
| | - Jonas Milani
- Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL) , 1015 Lausanne, Switzerland
| | - Basile Vuichoud
- Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL) , 1015 Lausanne, Switzerland
| | - Xiao Ji
- Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL) , 1015 Lausanne, Switzerland
| | - Jean-Nicolas Dumez
- Institut de Chimie des Substances Naturelles, CNRS UPR 2301, Univ. Paris-Sud, Université Paris-Saclay , 91190 Gif-sur-Yvette, France
| | - Annick Moing
- Plateforme Métabolome Bordeaux-MetaboHUB, Centre de Génomique Fonctionnelle Bordeaux, IBVM, Centre INRA Bordeaux, 33140 Villenave d'Ornon, France.,INRA, UMR 1332 Biologie du Fruit et Pathologie, Centre INRA Bordeaux, 33140 Villenave d'Ornon, France
| | - Geoffrey Bodenhausen
- Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL) , 1015 Lausanne, Switzerland.,Département de Chimie, Ecole Normale Supérieure (ENS)-Paris Sciences Lettres (PSL) Research University , 75005 Paris, France.,Laboratoire de Biomolécules (LBM), Université Pierre et Marie Curie (UPMC) - Paris 06, Sorbonne Universités , 75005 Paris, France.,Laboratoire de Biomolécules (LBM), Unité Mixte de Recherche (UMR) 7203 Centre National de la Recherche Scientifique (CNRS), 75005 Paris, France
| | - Sami Jannin
- Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL) , 1015 Lausanne, Switzerland
| | - Patrick Giraudeau
- Université de Nantes , CNRS, CEISAM UMR 6230, 44322 Nantes Cedex 03, France.,Institut Universitaire de France , 75005 Paris, France
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138
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Nagana Gowda GA, Abell L, Lee CF, Tian R, Raftery D. Simultaneous Analysis of Major Coenzymes of Cellular Redox Reactions and Energy Using ex Vivo (1)H NMR Spectroscopy. Anal Chem 2016; 88:4817-24. [PMID: 27043450 PMCID: PMC4857157 DOI: 10.1021/acs.analchem.6b00442] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2016] [Accepted: 04/04/2016] [Indexed: 01/08/2023]
Abstract
Coenzymes of cellular redox reactions and cellular energy mediate biochemical reactions fundamental to the functioning of all living cells. Despite their immense interest, no simple method exists to gain insights into their cellular concentrations in a single step. We show that a simple (1)H NMR experiment can simultaneously measure oxidized and reduced forms of nicotinamide adenine dinucleotide (NAD(+) and NADH), oxidized and reduced forms of nicotinamide adenine dinucleotide phosphate (NADP(+) and NADPH), and adenosine triphosphate (ATP) and its precursors, adenosine diphosphate (ADP) and adenosine monophosphate (AMP), using mouse heart, kidney, brain, liver, and skeletal muscle tissue extracts as examples. Combining 1D/2D NMR experiments, chemical shift libraries, and authentic compound data, reliable peak identities for these coenzymes have been established. To assess this methodology, cardiac NADH and NAD(+) ratios/pool sizes were measured using mouse models with a cardiac-specific knockout of the mitochondrial Complex I Ndufs4 gene (cKO) and cardiac-specific overexpression of nicotinamide phosphoribosyltransferase (cNAMPT) as examples. Sensitivity of NAD(+) and NADH to cKO or cNAMPT was observed, as anticipated. Time-dependent investigations showed that the levels of NADH and NADPH diminish by up to ∼50% within 24 h; concomitantly, NAD(+) and NADP(+) increase proportionately; however, degassing the sample and flushing the sample tubes with helium gas halted such changes. The analysis protocol along with the annotated characteristic fingerprints for each coenzyme is provided for easy identification and absolute quantification using a single internal reference for routine use. The ability to visualize the ubiquitous coenzymes fundamental to cellular functions, simultaneously and reliably, offers a new avenue to interrogate the mechanistic details of cellular function in health and disease.
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Affiliation(s)
- G. A. Nagana Gowda
- Northwest Metabolomics Research Center, Mitochondria and Metabolism Center,
Anesthesiology and Pain Medicine, and Department of Chemistry, University of Washington, Seattle, Washington 98109, United States
| | - Lauren Abell
- Northwest Metabolomics Research Center, Mitochondria and Metabolism Center,
Anesthesiology and Pain Medicine, and Department of Chemistry, University of Washington, Seattle, Washington 98109, United States
| | - Chi Fung Lee
- Northwest Metabolomics Research Center, Mitochondria and Metabolism Center,
Anesthesiology and Pain Medicine, and Department of Chemistry, University of Washington, Seattle, Washington 98109, United States
| | - Rong Tian
- Northwest Metabolomics Research Center, Mitochondria and Metabolism Center,
Anesthesiology and Pain Medicine, and Department of Chemistry, University of Washington, Seattle, Washington 98109, United States
| | - Daniel Raftery
- Northwest Metabolomics Research Center, Mitochondria and Metabolism Center,
Anesthesiology and Pain Medicine, and Department of Chemistry, University of Washington, Seattle, Washington 98109, United States
- Fred
Hutchinson Cancer Research Center, Seattle, Washington 98109, United States
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139
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Mahamad Maifiah MH, Cheah SE, Johnson MD, Han ML, Boyce JD, Thamlikitkul V, Forrest A, Kaye KS, Hertzog P, Purcell AW, Song J, Velkov T, Creek DJ, Li J. Global metabolic analyses identify key differences in metabolite levels between polymyxin-susceptible and polymyxin-resistant Acinetobacter baumannii. Sci Rep 2016; 6:22287. [PMID: 26924392 PMCID: PMC4770286 DOI: 10.1038/srep22287] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2015] [Accepted: 02/11/2016] [Indexed: 02/07/2023] Open
Abstract
Multidrug-resistant Acinetobacter baumannii presents a global medical crisis and polymyxins are used as the last-line therapy. This study aimed to identify metabolic differences between polymyxin-susceptible and polymyxin-resistant A. baumannii using untargeted metabolomics. The metabolome of each A. baumannii strain was measured using liquid chromatography-mass spectrometry. Multivariate and univariate statistics and pathway analyses were employed to elucidate metabolic differences between the polymyxin-susceptible and -resistant A. baumannii strains. Significant differences were identified between the metabolic profiles of the polymyxin-susceptible and -resistant A. baumannii strains. The lipopolysaccharide (LPS) deficient, polymyxin-resistant 19606R showed perturbation in specific amino acid and carbohydrate metabolites, particularly pentose phosphate pathway (PPP) and tricarboxylic acid (TCA) cycle intermediates. Levels of nucleotides were lower in the LPS-deficient 19606R. Furthermore, 19606R exhibited a shift in its glycerophospholipid profile towards increased abundance of short-chain lipids compared to the parent polymyxin-susceptible ATCC 19606. In contrast, in a pair of clinical isolates 03-149.1 (polymyxin-susceptible) and 03-149.2 (polymyxin-resistant, due to modification of lipid A), minor metabolic differences were identified. Notably, peptidoglycan biosynthesis metabolites were significantly depleted in both of the aforementioned polymyxin-resistant strains. This is the first comparative untargeted metabolomics study to show substantial differences in the metabolic profiles of the polymyxin-susceptible and -resistant A. baumannii.
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Affiliation(s)
- Mohd Hafidz Mahamad Maifiah
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC, 3052, Australia
| | - Soon-Ee Cheah
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC, 3052, Australia
| | - Matthew D. Johnson
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC, 3052, Australia
| | - Mei-Ling Han
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC, 3052, Australia
| | - John D. Boyce
- Department of Microbiology, Faculty of Medicine, Nursing & Health Sciences, Monash University, Clayton, VIC, 3800, Australia
| | - Visanu Thamlikitkul
- Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, 10700, Thailand
| | - Alan Forrest
- UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599-7569, USA
| | - Keith S. Kaye
- Detroit Medical Centre and Wayne State University, University Health Centre, Detroit, MI, 48201, USA
| | - Paul Hertzog
- Hudson Institute of Medical Research, Clayton, VIC, 3168, Australia
- Faculty of Medicine, Nursing & Health Sciences, Monash University, Clayton, VIC, 3800, Australia
| | - Anthony W. Purcell
- Department of Biochemistry and Molecular Biology, Faculty of Medicine, Nursing & Health Sciences, Monash University, Clayton, VIC, 3800, Australia
| | - Jiangning Song
- Department of Biochemistry and Molecular Biology, Faculty of Medicine, Nursing & Health Sciences, Monash University, Clayton, VIC, 3800, Australia
| | - Tony Velkov
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC, 3052, Australia
| | - Darren J. Creek
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC, 3052, Australia
| | - Jian Li
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC, 3052, Australia
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140
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Abstract
This review discusses strategies for the identification of metabolites in complex biological mixtures, as encountered in metabolomics, which have emerged in the recent past. These include NMR database-assisted approaches for the identification of commonly known metabolites as well as novel combinations of NMR and MS analysis methods for the identification of unknown metabolites. The use of certain chemical additives to the NMR tube can permit identification of metabolites with specific physical chemical properties.
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