1
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Dey A, Charrier B, Ribay V, Dumez JN, Giraudeau P. Hyperpolarized 1H and 13C NMR Spectroscopy in a Single Experiment for Metabolomics. Anal Chem 2023; 95:16861-16867. [PMID: 37947414 DOI: 10.1021/acs.analchem.3c02614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2023]
Abstract
The application of NMR spectroscopy to complex mixture analysis and, in particular, to metabolomics is limited by the low sensitivity of NMR. We recently showed that dissolution dynamic nuclear polarization (d-DNP) could enhance the sensitivity of 13C NMR for complex metabolite mixtures, leading to the detection of highly sensitive 13C NMR fingerprints of complex samples such as plant extracts or urine. While such experiments provide heteronuclear spectra, which are complementary to conventional NMR, hyperpolarized 1H NMR spectra would also be highly useful, with improved limits of detection and compatibility with the existing metabolomics workflow and databases. In this technical note, we introduce an approach capable of recording both 1H and 13C hyperpolarized spectra of metabolite mixtures in a single experiment and on the same hyperpolarized sample. We investigate the analytical performance of this method in terms of sensitivity and repeatability, and then we show that it can be efficiently applied to a plant extract. Significant sensitivity enhancements in 1H NMR are reported with a repeatability suitable for metabolomics studies without compromising on the performance of hyperpolarized 13C NMR. This approach provides a way to perform both 1H and 13C hyperpolarized NMR metabolomics with unprecedented sensitivity and throughput.
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Affiliation(s)
- Arnab Dey
- Nantes Université, CEISAM UMR 6230, 44000 Nantes, France
| | | | - Victor Ribay
- Nantes Université, CEISAM UMR 6230, 44000 Nantes, France
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2
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Watermann S, Bode MC, Hackl T. Identification of metabolites from complex mixtures by 3D correlation of 1H NMR, MS and LC data using the SCORE-metabolite-ID approach. Sci Rep 2023; 13:15834. [PMID: 37740032 PMCID: PMC10516956 DOI: 10.1038/s41598-023-43056-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 09/19/2023] [Indexed: 09/24/2023] Open
Abstract
Not only in metabolomics studies, but also in natural product chemistry, reliable identification of metabolites usually requires laborious steps of isolation and purification and remains a bottleneck in many studies. Direct metabolite identification from a complex mixture without individual isolation is therefore a preferred approach, but due to the large number of metabolites present in natural products, this approach is often hampered by signal overlap in the respective 1H NMR spectra. This paper presents a method for the three-dimensional mathematical correlation of NMR with MS data over the third dimension of the time course of a chromatographic fractionation. The MATLAB application SCORE-metabolite-ID (Semi-automatic COrrelation analysis for REliable metabolite IDentification) provides semi-automatic detection of correlated NMR and MS data, allowing NMR signals to be related to associated mass-to-charge ratios from ESI mass spectra. This approach enables fast and reliable dereplication of known metabolites and facilitates the dynamic analysis for the identification of unknown compounds in any complex mixture. The strategy was validated using an artificial mixture and further tested on a polar extract of a pine nut sample. Straightforward identification of 40 metabolites could be shown, including the identification of β-D-glucopyranosyl-1-N-indole-3-acetyl-N-L-aspartic acid (1) and Nα-(2-hydroxy-2-carboxymethylsuccinyl)-L-arginine (2), the latter being identified in a food sample for the first time.
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Affiliation(s)
- Stephanie Watermann
- Institute of Organic Chemistry, University of Hamburg, Martin-Luther-King-Platz 6, 20146, Hamburg, Germany
| | - Marie-Christin Bode
- Institute of Organic Chemistry, University of Hamburg, Martin-Luther-King-Platz 6, 20146, Hamburg, Germany
| | - Thomas Hackl
- Institute of Organic Chemistry, University of Hamburg, Martin-Luther-King-Platz 6, 20146, Hamburg, Germany.
- Hamburg School of Food Science - Institute of Food Chemistry, University of Hamburg, Grindelallee 117, 20146, Hamburg, Germany.
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3
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Bridoux MC, Gaiffe G, Pacholski P, Cangemi S, Vinci G, Spaccini R, Schramm S. Concealed by darkness: Combination of NMR and HRMS reveal the molecular nature of dissolved organic matter in fractured-rock groundwater and connected surface waters. WATER RESEARCH 2023; 243:120392. [PMID: 37542781 DOI: 10.1016/j.watres.2023.120392] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 07/18/2023] [Accepted: 07/19/2023] [Indexed: 08/07/2023]
Abstract
Detailed molecular composition of solid phase extracted dissolved organic matter (SPEDOM) collected from fractured-rock groundwater was compared to connected surface river water at two different watersheds in the unconfined chalk aquifer of Champagne in France using full scan ultrahigh resolution electrospray and photoionization Fourier transform ion cyclotron mass spectrometry (FT-ICR MS), Orbitrap tandem MS (MS/MS) and 1H magnetic resonance spectroscopy (NMR). 1H NMR spectroscopy indicated that groundwater SPEDOM carried a higher contribution of aliphatic compounds while surface river waters SPEDOM were enriched in carboxyl-rich alicyclic molecules (CRAM), acetate derivatives and oxygenated units. Furthermore, we show here that use of photoionization (APPI(+)) in aquifer studies is key, ionizing about eight times more compounds than ESI in surface river water samples, specifically targeting the dissolved organic nitrogen pool, accounting for more than 50% of the total molecular space, as well as a non-polar, more aromatic fraction; with little overlap with compounds detected by ESI(-) FT-ICR MS. On the other hand, groundwater SPEDOM samples did not show similar selectivity as less molecular diversity was observed in APPI compared to ESI. Mass-difference transformation networks (MDiNs) applied to ESI(-) and APPI(+) FT-ICR MS datasets provided an overview of the biogeochemical relationships within the aquifer, revealing chemical diversity and microbial/abiotic reactions. Finally, the combination of ESI(-) FT-ICR MS and detailed Orbitrap MS/MS analysis revealed a pool of polar, anthropogenic sulfur-containing surfactants in the groundwaters, likely originating from agricultural runoff. Overall, our study shows that in this aquifer, groundwater SPEDOM contains a significantly reduced pool of organic compounds compared to surface river waters, possibly related to a combination of lack of sunlight and adsorption of high O/C formulas to mineral surfaces.
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Affiliation(s)
| | - G Gaiffe
- CEA, DAM, DIF, F-91297 Arpajon, France
| | - P Pacholski
- CEA, DAM, DIF, F-91297 Arpajon, France; Laboratoire de Chimie et de Physique-Approches Multi-échelles des Milieux Complexes (LCP-A2MC), Université de Lorraine, Metz, France
| | - S Cangemi
- Centro Interdipartimentale di Ricerca sulla Risonanza Magnetica Nucleare per l'Ambiente, l'Agroalimentare e Nuovi Materiali (CERMANU), Università di Napoli Federico II, Via Università, 100, Portici (NA), 80055, Italy
| | - G Vinci
- Centro Interdipartimentale di Ricerca sulla Risonanza Magnetica Nucleare per l'Ambiente, l'Agroalimentare e Nuovi Materiali (CERMANU), Università di Napoli Federico II, Via Università, 100, Portici (NA), 80055, Italy
| | - R Spaccini
- Centro Interdipartimentale di Ricerca sulla Risonanza Magnetica Nucleare per l'Ambiente, l'Agroalimentare e Nuovi Materiali (CERMANU), Università di Napoli Federico II, Via Università, 100, Portici (NA), 80055, Italy
| | - S Schramm
- Laboratoire de Chimie et de Physique-Approches Multi-échelles des Milieux Complexes (LCP-A2MC), Université de Lorraine, Metz, France
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4
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Gupta P, Verma A, Rai N, Singh AK, Singh SK, Kumar B, Kumar R, Gautam V. Mass Spectrometry-Based Technology and Workflows for Studying the Chemistry of Fungal Endophyte Derived Bioactive Compounds. ACS Chem Biol 2021; 16:2068-2086. [PMID: 34724607 DOI: 10.1021/acschembio.1c00581] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Bioactive compounds have gained substantial attention in research and have conferred great advancements in the industrial and pharmacological fields. Highly diverse fungi and their metabolome serve as a big platform to be explored for their diverse bioactive compounds. Omics tools coupled with bioinformatics, statistical, and well-developed algorithm tools have elucidated immense knowledge about fungal endophyte derived bioactive compounds. Further, these compounds are subjected to chromatography-gas chromatography and liquid chromatography (LC), spectroscopy-nuclear magnetic resonance (NMR), and "soft ionization" technique-matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) based analytical techniques for structural characterization. The mass spectrometry (MS)-based approach, being highly sensitive, reproducible, and reliable, produces quick and high-profile identification. Coupling these techniques with MS has resulted in a descriptive account of the identification and quantification of fungal endophyte derived bioactive compounds. This paper emphasizes the workflows of the above-mentioned techniques, their advancement, and future directions to study the unraveled area of chemistry of fungal endophyte-derived bioactive compounds.
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Affiliation(s)
- Priyamvada Gupta
- Centre of Experimental Medicine and Surgery, Institute of Medical Sciences, Banaras Hindu University, Varanasi-221005, India
| | - Ashish Verma
- Centre of Experimental Medicine and Surgery, Institute of Medical Sciences, Banaras Hindu University, Varanasi-221005, India
| | - Nilesh Rai
- Centre of Experimental Medicine and Surgery, Institute of Medical Sciences, Banaras Hindu University, Varanasi-221005, India
| | - Anurag Kumar Singh
- Centre of Experimental Medicine and Surgery, Institute of Medical Sciences, Banaras Hindu University, Varanasi-221005, India
| | - Santosh Kumar Singh
- Centre of Experimental Medicine and Surgery, Institute of Medical Sciences, Banaras Hindu University, Varanasi-221005, India
| | - Brijesh Kumar
- Department of Pharmacology, Institute of Medical Sciences, Banaras Hindu University, Varanasi-221005, India
| | - Rajiv Kumar
- Centre of Experimental Medicine and Surgery, Institute of Medical Sciences, Banaras Hindu University, Varanasi-221005, India
| | - Vibhav Gautam
- Centre of Experimental Medicine and Surgery, Institute of Medical Sciences, Banaras Hindu University, Varanasi-221005, India
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5
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Letertre MPM, Giraudeau P, de Tullio P. Nuclear Magnetic Resonance Spectroscopy in Clinical Metabolomics and Personalized Medicine: Current Challenges and Perspectives. Front Mol Biosci 2021; 8:698337. [PMID: 34616770 PMCID: PMC8488110 DOI: 10.3389/fmolb.2021.698337] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 08/30/2021] [Indexed: 12/12/2022] Open
Abstract
Personalized medicine is probably the most promising area being developed in modern medicine. This approach attempts to optimize the therapies and the patient care based on the individual patient characteristics. Its success highly depends on the way the characterization of the disease and its evolution, the patient’s classification, its follow-up and the treatment could be optimized. Thus, personalized medicine must combine innovative tools to measure, integrate and model data. Towards this goal, clinical metabolomics appears as ideally suited to obtain relevant information. Indeed, the metabolomics signature brings crucial insight to stratify patients according to their responses to a pathology and/or a treatment, to provide prognostic and diagnostic biomarkers, and to improve therapeutic outcomes. However, the translation of metabolomics from laboratory studies to clinical practice remains a subsequent challenge. Nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the two key platforms for the measurement of the metabolome. NMR has several advantages and features that are essential in clinical metabolomics. Indeed, NMR spectroscopy is inherently very robust, reproducible, unbiased, quantitative, informative at the structural molecular level, requires little sample preparation and reduced data processing. NMR is also well adapted to the measurement of large cohorts, to multi-sites and to longitudinal studies. This review focus on the potential of NMR in the context of clinical metabolomics and personalized medicine. Starting with the current status of NMR-based metabolomics at the clinical level and highlighting its strengths, weaknesses and challenges, this article also explores how, far from the initial “opposition” or “competition”, NMR and MS have been integrated and have demonstrated a great complementarity, in terms of sample classification and biomarker identification. Finally, a perspective discussion provides insight into the current methodological developments that could significantly raise NMR as a more resolutive, sensitive and accessible tool for clinical applications and point-of-care diagnosis. Thanks to these advances, NMR has a strong potential to join the other analytical tools currently used in clinical settings.
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Affiliation(s)
| | | | - Pascal de Tullio
- Metabolomics Group, Center for Interdisciplinary Research of Medicine (CIRM), Department of Pharmacy, Université de Liège, Liège, Belgique
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6
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Ortiz CN, Torres-Reverón A, Appleyard CB. Metabolomics in endometriosis: challenges and perspectives for future studies. REPRODUCTION AND FERTILITY 2021; 2:R35-R50. [PMID: 35128453 PMCID: PMC8812441 DOI: 10.1530/raf-20-0047] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Accepted: 04/01/2021] [Indexed: 12/15/2022] Open
Abstract
Endometriosis is a complex disease characterized by inflammation and the growth of endometrial- like glands and stroma outside the uterine cavity. The pathophysiology of endometriosis is not entirely understood, however, with a prevalence of ~10% of women in their reproductive years, the disease symptoms significantly affect the quality of life of millions of women globally. Metabolomic studies have previously identified specific metabolites that could be a signature of endometriosis. This approach could potentially be used as a non-invasive tool for early diagnosis and provide a better understanding of endometriosis pathophysiology. This review aims to provide insight as to how endometriosis affects the metabolome by reviewing different studies that have used this approach to design follow-up studies. The search query included the term 'endometriosis' in combination with 'metabolomics', 'lipidomics', or 'sphingolipidomics' published between 2012 and 2020. We included studies in humans and animal models. Most studies reported differences in the metabolome of subjects with endometriosis in comparison to healthy controls and used samples taken from serum, endometrial tissue, follicular fluid, urine, peritoneal fluid, or endometrial fluid. Statistically significant metabolites contributed to group separation between patients and healthy controls. Reported metabolites included amino acids, lipids, organic acids, and other organic compounds. Differences in methods, analytical techniques, and the presence of confounding factors can interfere with results and interpretation of data. Metabolomics seems to be a promising tool for identifying significant metabolites in patients with endometriosis. Nonetheless, more investigation is needed in order to understand the significance of the study results.
Lay summary
Endometriosis is a chronic disease affecting the quality of life in one out of every ten women during their reproductive years, causing pain and infertility. It is characterized by inflammation and growth of tissue like the endometrium (uterus lining) outside the uterine cavity. Studies have searched for a predictor of endometriosis-associated changes by observing small molecules necessary for metabolism on a large scale (metabolomics). Metabolomics could serve to resolve one of the biggest challenges that patients with endometriosis face: a delay in diagnosis. In this review, the authors summarize identified potential biomarkers from various bodily fluids and tissues that are characteristic of metabolic processes observed in endometriosis. Biomarkers include cell growth, cell survival, high energy demand, oxidative stress, and fatty acid levels. A metabolomics approach offers promise as a non-invasive tool to identify significant metabolite changes in patients with endometriosis, potentially leading to earlier diagnoses and new opportunities for back-translational strategies.
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Affiliation(s)
- Camila N Ortiz
- Department of Basic Sciences, Ponce Health Sciences University, Ponce Research Institute, Ponce, Puerto Rico, USA
| | | | - Caroline B Appleyard
- Department of Basic Sciences, Ponce Health Sciences University, Ponce Research Institute, Ponce, Puerto Rico, USA
- Department of Internal Medicine, Ponce Health Sciences University, Ponce, Puerto Rico, USA
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7
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Cox N, Millard P, Charlier C, Lippens G. Improved NMR Detection of Phospho-Metabolites in a Complex Mixture. Anal Chem 2021; 93:4818-4824. [PMID: 33711235 DOI: 10.1021/acs.analchem.0c04056] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Phosphorylated metabolites are omnipresent in cells, but their analytical characterization faces several technical hurdles. Here, we detail an improved NMR workflow aimed at assigning the high-resolution subspectrum of the phospho-metabolites in a complex mixture. Combining a pure absorption J-resolved spectrum (Pell, A. J.; J. Magn. Reson. 2007, 189 (2), 293-299) with alternate on- and off-switching of the 31P coupling interaction during the t1 evolution with a pure in-phase (PIP) HSQMBC experiment (Castañar, L.; Angew. Chem., Int. Ed. 2014, 53 (32), 8379-8382) without or with total correlation spectroscopy (TOCSY) transfer during the insensitive nuclei enhancement by polarization transfer (INEPT) gives access to selective identification of the individual subspectra of the phosphorylated metabolites. Returning to the initial J-res spectra, we can extract with optimal resolution the full trace for the individual phospho-metabolites, which can then be transposed on the high-resolution quantitative one dimensional spectrum.
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Affiliation(s)
- Neil Cox
- TBI, Université de Toulouse, CNRS, INRAE, INSA, 31077 Toulouse, France
| | - Pierre Millard
- TBI, Université de Toulouse, CNRS, INRAE, INSA, 31077 Toulouse, France
| | - Cyril Charlier
- TBI, Université de Toulouse, CNRS, INRAE, INSA, 31077 Toulouse, France
| | - Guy Lippens
- TBI, Université de Toulouse, CNRS, INRAE, INSA, 31077 Toulouse, France
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8
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Jimenez-Carvelo AM, Cuadros-Rodríguez L. Data mining/machine learning methods in foodomics. Curr Opin Food Sci 2021. [DOI: 10.1016/j.cofs.2020.09.008] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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9
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Dey A, Charrier B, Martineau E, Deborde C, Gandriau E, Moing A, Jacob D, Eshchenko D, Schnell M, Melzi R, Kurzbach D, Ceillier M, Chappuis Q, Cousin SF, Kempf JG, Jannin S, Dumez JN, Giraudeau P. Hyperpolarized NMR Metabolomics at Natural 13C Abundance. Anal Chem 2020; 92:14867-14871. [PMID: 33136383 PMCID: PMC7705890 DOI: 10.1021/acs.analchem.0c03510] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 10/15/2020] [Indexed: 12/14/2022]
Abstract
Metabolomics plays a pivotal role in systems biology, and NMR is a central tool with high precision and exceptional resolution of chemical information. Most NMR metabolomic studies are based on 1H 1D spectroscopy, severely limited by peak overlap. 13C NMR benefits from a larger signal dispersion but is barely used in metabolomics due to ca. 6000-fold lower sensitivity. We introduce a new approach, based on hyperpolarized 13C NMR at natural abundance, that circumvents this limitation. A new untargeted NMR-based metabolomic workflow based on dissolution dynamic nuclear polarization (d-DNP) for the first time enabled hyperpolarized natural abundance 13C metabolomics. Statistical analysis of resulting hyperpolarized 13C data distinguishes two groups of plant (tomato) extracts and highlights biomarkers, in full agreement with previous results on the same biological model. We also optimize parameters of the semiautomated d-DNP system suitable for high-throughput studies.
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Affiliation(s)
- Arnab Dey
- Université
de Nantes, CNRS, CEISAM UMR
6230, F-44000 Nantes, France
| | - Benoît Charrier
- Université
de Nantes, CNRS, CEISAM UMR
6230, F-44000 Nantes, France
| | - Estelle Martineau
- Université
de Nantes, CNRS, CEISAM UMR
6230, F-44000 Nantes, France
- SpectroMaitrise,
CAPACITES SAS, F-44000 Nantes, France
| | - Catherine Deborde
- INRAE,
Univ. Bordeaux, UMR Biologie du Fruit et Pathologie, Centre INRAE de Nouvelle Aquitaine-Bordeaux, F-33140 Villenave
d’Ornon, France
- Bordeaux
Metabolome, MetaboHUB, Centre INRAE de Nouvelle
Aquitaine-Bordeaux, F-33140 Villenave d’Ornon, France
| | - Elodie Gandriau
- Université
de Nantes, CNRS, CEISAM UMR
6230, F-44000 Nantes, France
| | - Annick Moing
- INRAE,
Univ. Bordeaux, UMR Biologie du Fruit et Pathologie, Centre INRAE de Nouvelle Aquitaine-Bordeaux, F-33140 Villenave
d’Ornon, France
- Bordeaux
Metabolome, MetaboHUB, Centre INRAE de Nouvelle
Aquitaine-Bordeaux, F-33140 Villenave d’Ornon, France
| | - Daniel Jacob
- INRAE,
Univ. Bordeaux, UMR Biologie du Fruit et Pathologie, Centre INRAE de Nouvelle Aquitaine-Bordeaux, F-33140 Villenave
d’Ornon, France
- Bordeaux
Metabolome, MetaboHUB, Centre INRAE de Nouvelle
Aquitaine-Bordeaux, F-33140 Villenave d’Ornon, France
| | - Dmitry Eshchenko
- Bruker
Biospin, Industriestrasse
26, 8117 Fällanden, Switzerland
| | - Marc Schnell
- Bruker
Biospin, Industriestrasse
26, 8117 Fällanden, Switzerland
| | | | - Dennis Kurzbach
- University
of Vienna, Faculty of Chemistry, Institute of Biological Chemistry, Währinger Str. 38, 1090 Vienna, Austria
| | - Morgan Ceillier
- Université
de Lyon, CNRS, Université Claude
Bernard Lyon 1, ENS de Lyon, Centre de RMN à Très Hauts Champs (CRMN),
FRE 2034, F-69100 Villeurbanne, France
| | - Quentin Chappuis
- Université
de Lyon, CNRS, Université Claude
Bernard Lyon 1, ENS de Lyon, Centre de RMN à Très Hauts Champs (CRMN),
FRE 2034, F-69100 Villeurbanne, France
| | - Samuel F. Cousin
- Université
de Lyon, CNRS, Université Claude
Bernard Lyon 1, ENS de Lyon, Centre de RMN à Très Hauts Champs (CRMN),
FRE 2034, F-69100 Villeurbanne, France
| | - James G. Kempf
- Bruker
Biospin, 15 Fortune Dr., Billerica, Massachusetts 01821, United States
| | - Sami Jannin
- Université
de Lyon, CNRS, Université Claude
Bernard Lyon 1, ENS de Lyon, Centre de RMN à Très Hauts Champs (CRMN),
FRE 2034, F-69100 Villeurbanne, France
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Asampille G, Cheredath A, Joseph D, Adiga SK, Atreya HS. The utility of nuclear magnetic resonance spectroscopy in assisted reproduction. Open Biol 2020; 10:200092. [PMID: 33142083 PMCID: PMC7729034 DOI: 10.1098/rsob.200092] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Accepted: 10/13/2020] [Indexed: 12/21/2022] Open
Abstract
Infertility affects approximately 15-20% of individuals of reproductive age worldwide. Over the last 40 years, assisted reproductive technology (ART) has helped millions of childless couples. However, ART is limited by a low success rate and risk of multiple gestations. Devising methods for selecting the best gamete or embryo that increases the ART success rate and prevention of multiple gestation has become one of the key goals in ART today. Special emphasis has been placed on the development of non-invasive approaches, which do not require perturbing the embryonic cells, as the current morphology-based embryo selection approach has shortcomings in predicting the implantation potential of embryos. An observed association between embryo metabolism and viability has prompted researchers to develop metabolomics-based biomarkers. Nuclear magnetic resonance (NMR) spectroscopy provides a non-invasive approach for the metabolic profiling of tissues, gametes and embryos, with the key advantage of having a minimal sample preparation procedure. Using NMR spectroscopy, biologically important molecules can be identified and quantified in intact cells, extracts or secretomes. This, in turn, helps to map out the active metabolic pathways in a system. The present review covers the contribution of NMR spectroscopy in assisted reproduction at various stages of the process.
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Affiliation(s)
- Gitanjali Asampille
- Department of Clinical Embryology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal 576104, India
| | - Aswathi Cheredath
- Department of Clinical Embryology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal 576104, India
| | - David Joseph
- NMR Research Centre, Indian Institute of Science, Bangalore 560012, India
- Solid State and Structural Chemistry Unit, Indian Institute of Science, Bangalore 560012, India
| | - Satish K. Adiga
- Department of Clinical Embryology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal 576104, India
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11
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Sharma U, Jagannathan NR. Metabolism of prostate cancer by magnetic resonance spectroscopy (MRS). Biophys Rev 2020; 12:1163-1173. [PMID: 32918707 DOI: 10.1007/s12551-020-00758-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Accepted: 09/04/2020] [Indexed: 12/11/2022] Open
Abstract
Understanding the metabolism of prostate cancer (PCa) is important for developing better diagnostic approaches and also for exploring new therapeutic targets. Magnetic resonance spectroscopy (MRS) techniques have been shown to be useful in the detection and quantification of metabolites. PCa illustrates metabolic phenotype, showing lower levels of citrate (Cit), a key metabolite of oxidative phosphorylation and alteration in several metabolic pathways to sustain tumor growth. Recently, dynamic nuclear polarization (DNP) studies have documented high rates of glycolysis (Warburg phenomenon) in PCa. High-throughput metabolic profiling strategies using MRS on variety of samples including intact tissues, biofluids like prostatic fluid, seminal fluid, blood plasma/sera, and urine have also played a vital role in understanding the abnormal metabolic activity of PCa patients. The enhanced analytical potential of these techniques in the detection and quantification of a large number of metabolites provides an in-depth understanding of metabolic rewiring associated with the tumorigenesis. Metabolomics analysis offers dual advantages of identification of diagnostic and predictive biomarkers as well as in understanding the altered metabolic pathways which can be targeted for inhibiting the cancer progression. This review briefly describes the potential applications of in vivo 1H MRS, high-resolution magic angle spinning spectroscopy (HRMAS) and in vitro MRS methods in understanding the metabolic changes of PCa and its usefulness in the management of PCa patients.
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Affiliation(s)
- Uma Sharma
- Department of NMR & MRI Facility, All India Institute of Medical Sciences, New Delhi, 110029, India.
| | - Naranamangalam R Jagannathan
- Department of Radiology, Chettinad Hospital & Research Institute, Chettinad Academy of Research & Education, Kelambakkam, TN, 603103, India.
- Department of Radiology, Sri Ramachandra Institute of Higher Education and Research, Chennai, 600116, India.
- Department of Electrical Engineering, Indian Institute Technology Madras, Chennai, 600 036, India.
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12
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Yu Y, Pauli GF, Huang L, Gan LS, van Breemen RB, Li D, McAlpine JB, Lankin DC, Chen SN. Classification of Flavonoid Metabolomes via Data Mining and Quantification of Hydroxyl NMR Signals. Anal Chem 2020; 92:4954-4962. [PMID: 32108467 PMCID: PMC7442116 DOI: 10.1021/acs.analchem.9b05084] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Utilizing the distinct HMBC cross-peak patterns of lower-field range (LFR; 11.80-14.20 ppm) hydroxyl singlets, presented NMR methodology characterizes flavonoid metabolomes both qualitatively and quantitatively. It enables simultaneous classification of the structural types of 5-OH flavonoids and biogenetically related 2'-OH chalcones, as well as quantification of individual metabolites from 1H NMR spectra, even in complex mixtures. Initially, metabolite-specific LFR 1D 1H and 2D HMBC patterns were established via literature mining and experimental data interpretation, demonstrating that LFR HMBC patterns encode the different structural types of 5-OH flavonoids/2'-OH chalcones. Taking advantage of the simplistic multiplicity of the H,H-uncoupled LFR 5-/2'-OH singlets, individual metabolites could subsequently be quantified by peak fitting quantitative 1H NMR (PF-qHNMR). Metabolomic analysis of enriched fractions from three medicinal licorice (Glycyrrhiza) species established proof-of-concept for distinguishing three major structural types and eight subtypes in biomedical applications. The method identified 15 G. uralensis (GU) phenols from the six possible subtypes of 5,7-diOH (iso)flav(an)ones with 6-, 8-, and nonprenyl substitution, including the new 6-prenyl-licoisoflavanone (1) and two previously unknown compounds (4 and 7). Relative (100%) qNMR established quantitative metabolome patterns suitable for species discrimination and plant metabolite studies. Absolute qNMR with combined external and internal (solvent) calibration (ECIC) identified and quantified 158 GU metabolites. HMBC-supported qHNMR analysis of flavonoid metabolomes ("flavonomics") empowers the exploration of structure-abundance-activity relationships of designated bioactivity. Its ability to identify and quantify numerous metabolites simultaneously and without identical reference materials opens new avenues for natural product discovery and botanical quality control and can be adopted to other flavonoid- and chalcone-containing taxa.
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Affiliation(s)
| | | | | | - Li-She Gan
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | | | - Dianpeng Li
- Guangxi Key Laboratory of Functional Phytochemicals Research and Utilization, Guangxi Institute of Botany, Chinese Academy of Sciences, Guilin 541006, China
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13
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Marzullo BP, Morgan TE, Wootton CA, Li M, Perry SJ, Saeed M, Barrow MP, O'Connor PB. Comparison of Fragmentation Techniques for the Structural Characterization of Singly Charged Agrochemicals. Anal Chem 2020; 92:3143-3151. [PMID: 31909982 DOI: 10.1021/acs.analchem.9b04820] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Investigating the structure of active ingredients, such as agrochemicals and their associated metabolites, is a crucial requisite in the discovery and development of these molecules. In this study, structural characterization by electron-induced dissociation (EID) was compared to collisionally activated dissociation (CAD) on a series of agrochemicals. EID fragmentation produced a greater variety of fragment ions and complementary ion pairs leading to more complete functional group characterization compared to CAD. The results obtained displayed many more cross-ring fragmentation of the pyrimidine ring compared to the pyridine ring. Compounds that consisted of one aromatic heterocyclic moiety (azoxystrobin, fluazifop acid, fluazifop-p-butyl, and pirimiphos-methyl) displayed cross-ring fragmentation while compounds with only aromatic hydrocarbon rings (fenpropidin and S-metolachlor) displayed no cross-ring fragmentation. The advantages of high-resolution accurate mass spectrometry (HRAM MS) are shown with the majority of assignments at ppb range error values and the ability to differentiate ions with the same nominal mass but different elemental composition. This highlights the potential for HRAM MS and EID to be used as a tool for structural characterization of small molecules with a wide variety of functional groups and structural motifs.
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Affiliation(s)
- Bryan P Marzullo
- Department of Chemistry , University of Warwick , Coventry CV4 7AL , United Kingdom
| | - Tomos E Morgan
- Department of Chemistry , University of Warwick , Coventry CV4 7AL , United Kingdom
| | | | - Meng Li
- Department of Chemistry , University of Warwick , Coventry CV4 7AL , United Kingdom
| | - Simon J Perry
- Syngenta, Jealott's Hill International Research Centre , Product Metabolism & Analytical Sciences , RG42 6EY Berkshire , United Kingdom
| | - Mansoor Saeed
- Syngenta, Jealott's Hill International Research Centre , Product Metabolism & Analytical Sciences , RG42 6EY Berkshire , United Kingdom
| | - Mark P Barrow
- Department of Chemistry , University of Warwick , Coventry CV4 7AL , United Kingdom
| | - Peter B O'Connor
- Department of Chemistry , University of Warwick , Coventry CV4 7AL , United Kingdom
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14
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Salem MA, Perez de Souza L, Serag A, Fernie AR, Farag MA, Ezzat SM, Alseekh S. Metabolomics in the Context of Plant Natural Products Research: From Sample Preparation to Metabolite Analysis. Metabolites 2020; 10:E37. [PMID: 31952212 PMCID: PMC7023240 DOI: 10.3390/metabo10010037] [Citation(s) in RCA: 113] [Impact Index Per Article: 28.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Revised: 12/25/2019] [Accepted: 01/11/2020] [Indexed: 12/22/2022] Open
Abstract
Plant-derived natural products have long been considered a valuable source of lead compounds for drug development. Natural extracts are usually composed of hundreds to thousands of metabolites, whereby the bioactivity of natural extracts can be represented by synergism between several metabolites. However, isolating every single compound from a natural extract is not always possible due to the complex chemistry and presence of most secondary metabolites at very low levels. Metabolomics has emerged in recent years as an indispensable tool for the analysis of thousands of metabolites from crude natural extracts, leading to a paradigm shift in natural products drug research. Analytical methods such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) are used to comprehensively annotate the constituents of plant natural products for screening, drug discovery as well as for quality control purposes such as those required for phytomedicine. In this review, the current advancements in plant sample preparation, sample measurements, and data analysis are presented alongside a few case studies of the successful applications of these processes in plant natural product drug discovery.
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Affiliation(s)
- Mohamed A. Salem
- Department of Pharmacognosy, Faculty of Pharmacy, Menoufia University, Gamal Abd El Nasr st., Shibin Elkom, Menoufia 32511, Egypt
| | - Leonardo Perez de Souza
- Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany; (L.P.d.S.); (A.R.F.)
| | - Ahmed Serag
- Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Al-Azhar University, Cairo 11751, Egypt;
| | - Alisdair R. Fernie
- Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany; (L.P.d.S.); (A.R.F.)
- Center of Plant Systems Biology and Biotechnology (CPSBB), Plovdiv 4000, Bulgaria
| | - Mohamed A. Farag
- Pharmacognosy Department, Faculty of Pharmacy, Cairo University, Cairo 11562, Egypt; (M.A.F.); (S.M.E.)
- Chemistry Department, School of Sciences & Engineering, The American University in Cairo, New Cairo 11835, Egypt
| | - Shahira M. Ezzat
- Pharmacognosy Department, Faculty of Pharmacy, Cairo University, Cairo 11562, Egypt; (M.A.F.); (S.M.E.)
- Department of Pharmacognosy, Faculty of Pharmacy, October University for Modern Sciences and Arts (MSA), Giza 11787, Egypt
| | - Saleh Alseekh
- Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany; (L.P.d.S.); (A.R.F.)
- Center of Plant Systems Biology and Biotechnology (CPSBB), Plovdiv 4000, Bulgaria
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15
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Kong SW, Hernandez-Ferrer C. Assessment of coverage for endogenous metabolites and exogenous chemical compounds using an untargeted metabolomics platform. PACIFIC SYMPOSIUM ON BIOCOMPUTING. PACIFIC SYMPOSIUM ON BIOCOMPUTING 2020; 25:587-598. [PMID: 31797630 PMCID: PMC6910716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
Physiological status and pathological changes in an individual can be captured by metabolic state that reflects the influence of both genetic variants and environmental factors such as diet, lifestyle and gut microbiome. The totality of environmental exposure throughout lifetime - i.e., exposome - is difficult to measure with current technologies. However, targeted measurement of exogenous chemicals and untargeted profiling of endogenous metabolites have been widely used to discover biomarkers of pathophysiologic changes and to understand functional impacts of genetic variants. To investigate the coverage of chemical space and interindividual variation related to demographic and pathological conditions, we profiled 169 plasma samples using an untargeted metabolomics platform. On average, 1,009 metabolites were quantified in each individual (range 906 - 1,038) out of 1,244 total chemical compounds detected in our cohort. Of note, age was positively correlated with the total number of detected metabolites in both males and females. Using the robust Qn estimator, we found metabolite outliers in each sample (mean 22, range from 7 to 86). A total of 50 metabolites were outliers in a patient with phenylketonuria including the ones known for phenylalanine pathway suggesting multiple metabolic pathways perturbed in this patient. The largest number of outliers (N=86) was found in a 5-year-old boy with alpha-1-antitrypsin deficiency who were waiting for liver transplantation due to cirrhosis. Xenobiotics including drugs, diets and environmental chemicals were significantly correlated with diverse endogenous metabolites and the use of antibiotics significantly changed gut microbial products detected in host circulation. Several challenges such as annotation of features, reference range and variance for each feature per age group and gender, and population scale reference datasets need to be addressed; however, untargeted metabolomics could be immediately deployed as a biomarker discovery platform and to evaluate the impact of genomic variants and exposures on metabolic pathways for some diseases.
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Affiliation(s)
- Sek Won Kong
- Computational Health Informatics Program, Boston Children’s Hospital, 300 Longwood Avenue Boston, MA 02115, USA,Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA,To whom correspondence should be addressed.
| | - Carles Hernandez-Ferrer
- Computational Health Informatics Program, Boston Children’s Hospital, 300 Longwood Avenue Boston, MA 02115, USA,Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
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16
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Gupta A, Nath K, Bansal N, Kumar M. Role of metabolomics-derived biomarkers to identify renal cell carcinoma: a comprehensive perspective of the past ten years and advancements. Expert Rev Mol Diagn 2019; 20:5-18. [DOI: 10.1080/14737159.2020.1704259] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
- Ashish Gupta
- Centre of Biomedical Research, SGPGIMS Campus, Lucknow, India
| | - Kavindra Nath
- Department of Radiology, University of Pennsylvania, Pheladelphia, PA, USA
| | - Navneeta Bansal
- Department of Urology, King George’s Medical University, Lucknow, India
| | - Manoj Kumar
- Department of Urology, King George’s Medical University, Lucknow, India
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17
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Ose J, Gigic B, Lin T, Liesenfeld DB, Böhm J, Nattenmüller J, Scherer D, Zielske L, Schrotz-King P, Habermann N, Ochs-Balcom HM, Peoples AR, Hardikar S, Li CI, Shibata D, Figueiredo J, Toriola AT, Siegel EM, Schmit S, Schneider M, Ulrich A, Kauczor HU, Ulrich CM. Multiplatform Urinary Metabolomics Profiling to Discriminate Cachectic from Non-Cachectic Colorectal Cancer Patients: Pilot Results from the ColoCare Study. Metabolites 2019; 9:E178. [PMID: 31500101 PMCID: PMC6780796 DOI: 10.3390/metabo9090178] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Revised: 08/26/2019] [Accepted: 09/04/2019] [Indexed: 12/18/2022] Open
Abstract
Cachexia is a multifactorial syndrome that is characterized by loss of skeletal muscle mass in cancer patients. The biological pathways involved remain poorly characterized. Here, we compare urinary metabolic profiles in newly diagnosed colorectal cancer patients (stage I-IV) from the ColoCare Study in Heidelberg, Germany. Patients were classified as cachectic (n = 16), pre-cachectic (n = 13), or non-cachectic (n = 23) based on standard criteria on weight loss over time at two time points. Urine samples were collected pre-surgery, and 6 and 12 months thereafter. Fat and muscle mass area were assessed utilizing computed tomography scans at the time of surgery. N = 152 compounds were detected using untargeted metabolomics with gas chromatography-mass spectrometry and n = 154 features with proton nuclear magnetic resonance spectroscopy. Thirty-four metabolites were overlapping across platforms. We calculated differences across groups and performed discriminant and overrepresentation enrichment analysis. We observed a trend for 32 compounds that were nominally significantly different across groups, although not statistically significant after adjustment for multiple testing. Nineteen compounds could be identified, including acetone, hydroquinone, and glycine. Comparing cachectic to non-cachectic patients, higher levels of metabolites such as acetone (Fold change (FC) = 3.17; p = 0.02) and arginine (FC = 0.33; p = 0.04) were observed. The two top pathways identified were glycerol phosphate shuttle metabolism and glycine and serine metabolism pathways. Larger subsequent studies are needed to replicate and validate these results.
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Affiliation(s)
- Jennifer Ose
- Huntsman Cancer Institute, Salt Lake City, UT 84112, USA.
- Department of Population Health Sciences, University of Utah, Salt Lake City, UT 84112, USA.
| | - Biljana Gigic
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, 69117 Heidelberg, Germany.
| | - Tengda Lin
- Huntsman Cancer Institute, Salt Lake City, UT 84112, USA.
| | - David B Liesenfeld
- Division of Preventive Oncology, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), 69117 Heidelberg, Germany.
| | - Jürgen Böhm
- Huntsman Cancer Institute, Salt Lake City, UT 84112, USA.
| | - Johanna Nattenmüller
- Diagnostic and Interventional Radiology, University of Heidelberg, 69117 Heidelberg, Germany.
| | - Dominique Scherer
- Institute of Medical Biometry and Informatics, University of Heidelberg, 69117 Heidelberg, Germany.
| | - Lin Zielske
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, 69117 Heidelberg, Germany.
| | - Petra Schrotz-King
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, 69117 Heidelberg, Germany.
| | - Nina Habermann
- European Molecular Biology Laboratory (EMBL), Genome Biology, 69117 Heidelberg, Germany.
| | - Heather M Ochs-Balcom
- Huntsman Cancer Institute, Salt Lake City, UT 84112, USA.
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY 14260, USA.
| | - Anita R Peoples
- Huntsman Cancer Institute, Salt Lake City, UT 84112, USA.
- Department of Population Health Sciences, University of Utah, Salt Lake City, UT 84112, USA.
| | - Sheetal Hardikar
- Huntsman Cancer Institute, Salt Lake City, UT 84112, USA.
- Department of Population Health Sciences, University of Utah, Salt Lake City, UT 84112, USA.
| | - Christopher I Li
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109-1024, USA.
| | - David Shibata
- Department of Surgery, University of Tennessee Health Science Center, Memphis, TN 38163, USA.
| | - Jane Figueiredo
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
| | - Adetunji T Toriola
- Department of Surgery, Washington University School of Medicine and Siteman Cancer Center, St. Louis, MO 63110, USA.
| | - Erin M Siegel
- Cancer Epidemiology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
| | - Stephanie Schmit
- Cancer Epidemiology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
| | - Martin Schneider
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, 69117 Heidelberg, Germany.
| | - Alexis Ulrich
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, 69117 Heidelberg, Germany.
| | - Hans-Ulrich Kauczor
- Diagnostic and Interventional Radiology, University of Heidelberg, 69117 Heidelberg, Germany.
| | - Cornelia M Ulrich
- Huntsman Cancer Institute, Salt Lake City, UT 84112, USA.
- Department of Population Health Sciences, University of Utah, Salt Lake City, UT 84112, USA.
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18
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Gómez-Cebrián N, Rojas-Benedicto A, Albors-Vaquer A, López-Guerrero JA, Pineda-Lucena A, Puchades-Carrasco L. Metabolomics Contributions to the Discovery of Prostate Cancer Biomarkers. Metabolites 2019; 9:metabo9030048. [PMID: 30857149 PMCID: PMC6468766 DOI: 10.3390/metabo9030048] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 03/01/2019] [Accepted: 03/04/2019] [Indexed: 02/06/2023] Open
Abstract
Prostate cancer (PCa) is one of the most frequently diagnosed cancers and a leading cause of death among men worldwide. Despite extensive efforts in biomarker discovery during the last years, currently used clinical biomarkers are still lacking enough specificity and sensitivity for PCa early detection, patient prognosis, and monitoring. Therefore, more precise biomarkers are required to improve the clinical management of PCa patients. In this context, metabolomics has shown to be a promising and powerful tool to identify novel PCa biomarkers in biofluids. Thus, changes in polyamines, tricarboxylic acid (TCA) cycle, amino acids, and fatty acids metabolism have been reported in different studies analyzing PCa patients' biofluids. The review provides an up-to-date summary of the main metabolic alterations that have been described in biofluid-based studies of PCa patients, as well as a discussion regarding their potential to improve clinical PCa diagnosis and prognosis. Furthermore, a summary of the most significant findings reported in these studies and the connections and interactions between the different metabolic changes described has also been included, aiming to better describe the specific metabolic signature associated to PCa.
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Affiliation(s)
- Nuria Gómez-Cebrián
- Drug Discovery Unit, Instituto de Investigación Sanitaria La Fe, Valencia 46026, Spain.
- Joint Research Unit in Clinical Metabolomics, Centro de Investigación Príncipe Felipe/Instituto de Investigación Sanitaria La Fe, Valencia 46012, Spain.
- Laboratory of Molecular Biology, Fundación Instituto Valenciano de Oncología, Valencia 46009, Spain.
| | - Ayelén Rojas-Benedicto
- Drug Discovery Unit, Instituto de Investigación Sanitaria La Fe, Valencia 46026, Spain.
- Joint Research Unit in Clinical Metabolomics, Centro de Investigación Príncipe Felipe/Instituto de Investigación Sanitaria La Fe, Valencia 46012, Spain.
| | - Arturo Albors-Vaquer
- Drug Discovery Unit, Instituto de Investigación Sanitaria La Fe, Valencia 46026, Spain.
- Joint Research Unit in Clinical Metabolomics, Centro de Investigación Príncipe Felipe/Instituto de Investigación Sanitaria La Fe, Valencia 46012, Spain.
| | | | - Antonio Pineda-Lucena
- Drug Discovery Unit, Instituto de Investigación Sanitaria La Fe, Valencia 46026, Spain.
- Joint Research Unit in Clinical Metabolomics, Centro de Investigación Príncipe Felipe/Instituto de Investigación Sanitaria La Fe, Valencia 46012, Spain.
| | - Leonor Puchades-Carrasco
- Joint Research Unit in Clinical Metabolomics, Centro de Investigación Príncipe Felipe/Instituto de Investigación Sanitaria La Fe, Valencia 46012, Spain.
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19
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Luan H, Wang X, Cai Z. Mass spectrometry-based metabolomics: Targeting the crosstalk between gut microbiota and brain in neurodegenerative disorders. MASS SPECTROMETRY REVIEWS 2019; 38:22-33. [PMID: 29130504 DOI: 10.1002/mas.21553] [Citation(s) in RCA: 115] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Accepted: 10/12/2017] [Indexed: 05/10/2023]
Abstract
Metabolomics seeks to take a "snapshot" in a time of the levels, activities, regulation and interactions of all small molecule metabolites in response to a biological system with genetic or environmental changes. The emerging development in mass spectrometry technologies has shown promise in the discovery and quantitation of neuroactive small molecule metabolites associated with gut microbiota and brain. Significant progress has been made recently in the characterization of intermediate role of small molecule metabolites linked to neural development and neurodegenerative disorder, showing its potential in understanding the crosstalk between gut microbiota and the host brain. More evidence reveals that small molecule metabolites may play a critical role in mediating microbial effects on neurotransmission and disease development. Mass spectrometry-based metabolomics is uniquely suitable for obtaining the metabolic signals in bidirectional communication between gut microbiota and brain. In this review, we summarized major mass spectrometry technologies including liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and imaging mass spectrometry for metabolomics studies of neurodegenerative disorders. We also reviewed the recent advances in the identification of new metabolites by mass spectrometry and metabolic pathways involved in the connection of intestinal microbiota and brain. These metabolic pathways allowed the microbiota to impact the regular function of the brain, which can in turn affect the composition of microbiota via the neurotransmitter substances. The dysfunctional interaction of this crosstalk connects neurodegenerative diseases, including Parkinson's disease, Alzheimer's disease and Huntington's disease. The mass spectrometry-based metabolomics analysis provides information for targeting dysfunctional pathways of small molecule metabolites in the development of the neurodegenerative diseases, which may be valuable for the investigation of underlying mechanism of therapeutic strategies.
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Affiliation(s)
- Hemi Luan
- Department of Chemistry, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR, China
| | - Xian Wang
- Key Laboratory of Analytical Chemistry of State Ethnic Affairs Commission, College of Chemistry and Materials Science, South-Central University for Nationalities, Wuhan, Hubei, China
| | - Zongwei Cai
- Department of Chemistry, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR, China
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20
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Leggett A, Wang C, Li DW, Somogyi A, Bruschweiler-Li L, Brüschweiler R. Identification of Unknown Metabolomics Mixture Compounds by Combining NMR, MS, and Cheminformatics. Methods Enzymol 2019; 615:407-422. [PMID: 30638535 PMCID: PMC6953983 DOI: 10.1016/bs.mie.2018.09.003] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Metabolomics aims at the comprehensive identification of metabolites in complex mixtures to characterize the state of a biological system and elucidate their roles in biochemical pathways. For many biological samples, a large number of spectral features observed by NMR spectroscopy and mass spectrometry (MS) belong to unknowns, i.e., these features do not belong to metabolites that have been previously identified, and their spectral information is not available in databases. By combining NMR, MS, and combinatorial cheminformatics, the analysis of unknowns can be pursued in complex mixtures requiring minimal purification. This chapter describes the SUMMIT MS/NMR approach covering sample preparation, NMR and MS data collection and processing, and the identification of likely unknowns with the use of cheminformatics tools and the prediction of NMR spectral properties.
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Affiliation(s)
- Abigail Leggett
- Ohio State Biochemistry Program, The Ohio State University, Columbus, Ohio 43210, U.S.A
| | - Cheng Wang
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, U.S.A
| | - Da-Wei Li
- Campus Chemical Instrument Center (CCIC), The Ohio State University, Columbus, Ohio 43210, U.S.A
| | - Arpad Somogyi
- Campus Chemical Instrument Center (CCIC), The Ohio State University, Columbus, Ohio 43210, U.S.A
| | - Lei Bruschweiler-Li
- Campus Chemical Instrument Center (CCIC), The Ohio State University, Columbus, Ohio 43210, U.S.A
| | - Rafael Brüschweiler
- Ohio State Biochemistry Program, The Ohio State University, Columbus, Ohio 43210, U.S.A.,Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, U.S.A.,Campus Chemical Instrument Center (CCIC), The Ohio State University, Columbus, Ohio 43210, U.S.A.,Department of Biological Chemistry and Pharmacology, The Ohio State University, Columbus, Ohio 43210, U.S.A.,To whom correspondence should be addressed: Rafael Brüschweiler, Ph.D.,
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21
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Grape and Wine Metabolomics to Develop New Insights Using Untargeted and Targeted Approaches. FERMENTATION-BASEL 2018. [DOI: 10.3390/fermentation4040092] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Chemical analysis of grape juice and wine has been performed for over 50 years in a targeted manner to determine a limited number of compounds using Gas Chromatography, Mass-Spectrometry (GC-MS) and High Pressure Liquid Chromatography (HPLC). Therefore, it only allowed the determination of metabolites that are present in high concentration, including major sugars, amino acids and some important carboxylic acids. Thus, the roles of many significant but less concentrated metabolites during wine making process are still not known. This is where metabolomics shows its enormous potential, mainly because of its capability in analyzing over 1000 metabolites in a single run due to the recent advancements of high resolution and sensitive analytical instruments. Metabolomics has predominantly been adopted by many wine scientists as a hypothesis-generating tool in an unbiased and non-targeted way to address various issues, including characterization of geographical origin (terroir) and wine yeast metabolic traits, determination of biomarkers for aroma compounds, and the monitoring of growth developments of grape vines and grapes. The aim of this review is to explore the published literature that made use of both targeted and untargeted metabolomics to study grapes and wines and also the fermentation process. In addition, insights are also provided into many other possible avenues where metabolomics shows tremendous potential as a question-driven approach in grape and wine research.
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22
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Taherkhani A, Kalantari S, Oskouie AA, Nafar M, Taghizadeh M, Tabar K. Network analysis of membranous glomerulonephritis based on metabolomics data. Mol Med Rep 2018; 18:4197-4212. [PMID: 30221719 PMCID: PMC6172390 DOI: 10.3892/mmr.2018.9477] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Accepted: 06/29/2018] [Indexed: 12/14/2022] Open
Abstract
Membranous glomerulonephritis (MGN) is one of the most frequent causes of nephrotic syndrome in adults. It is characterized by the thickening of the glomerular basement membrane in the renal tissue. The current diagnosis of MGN is based on renal biopsy and the detection of antibodies to the few podocyte antigens. Due to the limitations of the current diagnostic methods, including invasiveness and the lack of sensitivity of the current biomarkers, there is a requirement to identify more applicable biomarkers. The present study aimed to identify diagnostic metabolites that are involved in the development of the disease using topological features in the component‑reaction‑enzyme‑gene (CREG) network for MGN. Significant differential metabolites in MGN compared with healthy controls were identified using proton nuclear magnetic resonance and gas chromatography‑mass spectrometry techniques, and multivariate analysis. The CREG network for MGN was constructed, and metabolites with a high centrality and a striking fold‑change in patients, compared with healthy controls, were introduced as putative diagnostic biomarkers. In addition, a protein‑protein interaction (PPI) network, which was based on proteins associated with MGN, was built and analyzed using PPI analysis methods, including molecular complex detection and ClueGene Ontology. A total of 26 metabolites were identified as hub nodes in the CREG network, 13 of which had salient centrality and fold‑changes: Dopamine, carnosine, fumarate, nicotinamide D‑ribonucleotide, adenosine monophosphate, pyridoxal, deoxyguanosine triphosphate, L‑citrulline, nicotinamide, phenylalanine, deoxyuridine, tryptamine and succinate. A total of 13 subnetworks were identified using PPI analysis. In total, two of the clusters contained seed proteins (phenylalanine‑4‑hydroxlylase and cystathionine γ‑lyase) that were associated with MGN based on the CREG network. The following biological processes associated with MGN were identified using gene ontology analysis: 'Pyrimidine‑containing compound biosynthetic process', 'purine ribonucleoside metabolic process', 'nucleoside catabolic process', 'ribonucleoside metabolic process' and 'aromatic amino acid family metabolic process'. The results of the present study may be helpful in the diagnostic and therapeutic procedures of MGN. However, validation is required in the future.
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Affiliation(s)
- Amir Taherkhani
- Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran 1971653313, Iran
| | - Shiva Kalantari
- Chronic Kidney Disease Research Center, Shahid Labbafinejad Hospital, Shahid Beheshti University of Medical Sciences, Tehran 1666663111, Iran
| | - Afsaneh Arefi Oskouie
- Department of Basic Science, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran 1971653313, Iran
| | - Mohsen Nafar
- Urology Nephrology Research Center, Shahid Labbafinejad Hospital, Shahid Beheshti University of Medical Sciences, Tehran 1666663111, Iran
| | - Mohammad Taghizadeh
- Bioinformatics Department, Institute of Biochemistry and Biophysics, Tehran University, Tehran 1417614411, Iran
| | - Koorosh Tabar
- Chemistry and Chemical Engineering Research Center of Iran, Tehran 1496813151, Iran
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Bhinderwala F, Wase N, DiRusso C, Powers R. Combining Mass Spectrometry and NMR Improves Metabolite Detection and Annotation. J Proteome Res 2018; 17:4017-4022. [PMID: 30303385 DOI: 10.1021/acs.jproteome.8b00567] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Despite inherent complementarity, nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are routinely separately employed to characterize metabolomics samples. More troubling is the erroneous view that metabolomics is better served by exclusively utilizing MS. Instead, we demonstrate the importance of combining NMR and MS for metabolomics by using small chemical compound treatments of Chlamydomonas reinhardtii as an illustrative example. A total of 102 metabolites were detected (82 by gas chromatography-MS, 20 by NMR, and 22 by both techniques). Out of these, 47 metabolites of interest were identified: 14 metabolites were uniquely identified by NMR, and 16 metabolites were uniquely identified by GC-MS. A total of 17 metabolites were identified by both NMR and GC-MS. In general, metabolites identified by both techniques exhibited similar changes upon compound treatment. In effect, NMR identified key metabolites that were missed by MS and enhanced the overall coverage of the oxidative pentose phosphate pathway, Calvin cycle, tricarboxylic acid cycle, and amino acid biosynthetic pathways that informed on pathway activity in central carbon metabolism, leading to fatty-acid and complex-lipid synthesis. Our study emphasizes a prime advantage of combining multiple analytical techniques: the improved detection and annotation of metabolites.
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Affiliation(s)
- Fatema Bhinderwala
- Department of Chemistry , University of Nebraska , Lincoln , Nebraska 68588-0304 , United States.,Nebraska Center for Integrated Biomolecular Communication , Lincoln , Nebraska 68588-0304 , United States
| | - Nishikant Wase
- Department of Biochemistry , University of Nebraska , Lincoln , Nebraska 68588-0664 , United States
| | - Concetta DiRusso
- Department of Biochemistry , University of Nebraska , Lincoln , Nebraska 68588-0664 , United States.,Nebraska Center for Integrated Biomolecular Communication , Lincoln , Nebraska 68588-0304 , United States
| | - Robert Powers
- Department of Chemistry , University of Nebraska , Lincoln , Nebraska 68588-0304 , United States.,Nebraska Center for Integrated Biomolecular Communication , Lincoln , Nebraska 68588-0304 , United States
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24
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Mathé E, Hays JL, Stover DG, Chen JL. The Omics Revolution Continues: The Maturation of High-Throughput Biological Data Sources. Yearb Med Inform 2018; 27:211-222. [PMID: 30157526 PMCID: PMC6115204 DOI: 10.1055/s-0038-1667085] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
OBJECTIVE The aim is to provide a comprehensive review of state-of-the art omics approaches, including proteomics, metabolomics, cell-free DNA, and patient cohort matching algorithms in precision oncology. METHODS In the past several years, the cancer informatics revolution has been the beneficiary of a data explosion. Different complementary omics technologies have begun coming into their own to provide a more nuanced view of the patient-tumor interaction beyond that of DNA alterations. A combined approach is beneficial to the patient as nearly all new cancer therapeutics are designed with an omics biomarker in mind. Proteomics and metabolomics provide us with a means of assaying in real-time the response of the tumor to treatment. Circulating cell-free DNA may allow us to better understand tumor heterogeneity and interactions with the host genome. RESULTS Integration of increasingly available omics data increases our ability to segment patients into smaller and smaller cohorts, thereby prompting a shift in our thinking about how to use these omics data. With large repositories of patient omics-outcomes data being generated, patient cohort matching algorithms have become a dominant player. CONCLUSIONS The continued promise of precision oncology is to select patients who are most likely to benefit from treatment and to avoid toxicity for those who will not. The increased public availability of omics and outcomes data in patients, along with improved computational methods and resources, are making precision oncology a reality.
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Affiliation(s)
- Ewy Mathé
- Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA
| | - John L. Hays
- Department of Internal Medicine, The Ohio State University, Columbus, OH, USA
- Department of Obstetrics and Gynecology, The Ohio State University, Columbus, OH, USA
| | - Daniel G. Stover
- Department of Internal Medicine, The Ohio State University, Columbus, OH, USA
| | - James L. Chen
- Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA
- Department of Internal Medicine, The Ohio State University, Columbus, OH, USA
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25
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Abstract
PURPOSE OF THE REVIEW This review presents the analytical techniques, processing and analytical steps used in metabolomics phenotyping studies, as well as the main results from epidemiological studies on the associations between metabolites and high blood pressure. RECENT FINDINGS A variety of metabolomic approaches have been applied to a range of epidemiological studies to uncover the pathophysiology of high blood pressure. Several pathways have been suggested in relation to blood pressure including the possible role of the gut microflora, inflammatory, oxidative stress, and lipid pathways. Metabolic changes have also been identified associated with blood pressure lowering effects of diets high in fruits and vegetables and low in meat intake. However, the current body of literature on metabolic profiling and blood pressure is still in its infancy, not fully consistent and requires careful interpretation. Metabolic phenotyping is a promising approach to uncover metabolic pathways associated with high blood pressure and throw light into the complex pathophysiology of hypertension.
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Affiliation(s)
- Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece.
| | - Aikaterini Iliou
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Athens, Athens, Greece
| | - Emmanuel Mikros
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Athens, Athens, Greece
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Health Data Research UK (HDR-UK), London, UK
- Dementia Research Institute at Imperial College London, London, UK
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26
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A Survey of Orbitrap All Ion Fragmentation Analysis Assessed by an R MetaboList Package to Study Small-Molecule Metabolites. Chromatographia 2018. [DOI: 10.1007/s10337-018-3536-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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27
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Bingol K. Recent Advances in Targeted and Untargeted Metabolomics by NMR and MS/NMR Methods. High Throughput 2018; 7:E9. [PMID: 29670016 PMCID: PMC6023270 DOI: 10.3390/ht7020009] [Citation(s) in RCA: 91] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Revised: 04/09/2018] [Accepted: 04/13/2018] [Indexed: 12/23/2022] Open
Abstract
Metabolomics has made significant progress in multiple fronts in the last 18 months. This minireview aimed to give an overview of these advancements in the light of their contribution to targeted and untargeted metabolomics. New computational approaches have emerged to overcome the manual absolute quantitation step of metabolites in one-dimensional (1D) ¹H nuclear magnetic resonance (NMR) spectra. This provides more consistency between inter-laboratory comparisons. Integration of two-dimensional (2D) NMR metabolomics databases under a unified web server allowed for very accurate identification of the metabolites that have been catalogued in these databases. For the remaining uncatalogued and unknown metabolites, new cheminformatics approaches have been developed by combining NMR and mass spectrometry (MS). These hybrid MS/NMR approaches accelerated the identification of unknowns in untargeted studies, and now they are allowing for profiling ever larger number of metabolites in application studies.
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Affiliation(s)
- Kerem Bingol
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354, USA.
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28
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Pînzariu O, Georgescu B, Georgescu CE. Metabolomics-A Promising Approach to Pituitary Adenomas. Front Endocrinol (Lausanne) 2018; 9:814. [PMID: 30705668 PMCID: PMC6345099 DOI: 10.3389/fendo.2018.00814] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Accepted: 12/27/2018] [Indexed: 12/28/2022] Open
Abstract
Background: Metabolomics-the novel science that evaluates the multitude of low-molecular-weight metabolites in a biological system, provides new data on pathogenic mechanisms of diseases, including endocrine tumors. Although development of metabolomic profiling in pituitary disorders is at an early stage, it seems to be a promising approach in the near future in identifying specific disease biomarkers and understanding cellular signaling networks. Objectives: To review the metabolomic profile and the contributions of metabolomics in pituitary adenomas (PA). Methods: A systematic review was conducted via PubMed, Web of Science Core Collection and Scopus databases, summarizing studies that have described metabolomic aspects of PA. Results: Liquid chromatography tandem mass spectrometry (LC-MS/MS) and nuclear magnetic resonance (NMR) spectrometry, which are traditional techniques employed in metabolomics, suggest amino acids metabolism appears to be primarily altered in PA. N-acetyl aspartate, choline-containing compounds and creatine appear as highly effective in differentiating PA from healthy tissue. Deoxycholic and 4-pyridoxic acids, 3-methyladipate, short chain fatty acids and glucose-6-phosphate unveil metabolite biomarkers in patients with Cushing's disease. Phosphoethanolamine, N-acetyl aspartate and myo-inositol are down regulated in prolactinoma, whereas aspartate, glutamate and glutamine are up regulated. Phosphoethanolamine, taurine, alanine, choline-containing compounds, homocysteine, and methionine were up regulated in unclassified PA across studies. Intraoperative use of ultra high mass resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), which allows localization and delineation between functional PA and healthy pituitary tissue, may contribute to achievement of complete tumor resection in addition to preservation of pituitary cell lines and vasopressin secretory cells, thus avoiding postoperative diabetes insipidus. Conclusion: Implementation of ultra high performance metabolomics analysis techniques in the study of PA will significantly improve diagnosis and, potentially, the therapeutic approach, by identifying highly specific disease biomarkers in addition to novel molecular pathogenic mechanisms. Ultra high mass resolution MALDI-MSI emerges as a helpful clinical tool in the neurosurgical treatment of pituitary tumors. Therefore, metabolomics appears to be a science with a promising prospect in the sphere of PA, and a starting point in pituitary care.
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Affiliation(s)
- Oana Pînzariu
- 6 Department of Medical Sciences, Department of Endocrinology, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Bogdan Georgescu
- Department of Ecology, Environmental Protection and Zoology, University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, Cluj-Napoca, Romania
| | - Carmen E. Georgescu
- 6 Department of Medical Sciences, Department of Endocrinology, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania
- Endocrinology Clinic, Cluj County Emergency Clinical Hospital, Cluj-Napoca, Romania
- *Correspondence: Carmen E. Georgescu
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29
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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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30
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Costa Pereira J, Jarak I, Carvalho RA. Resolving NMR signals of short-chain fatty acid mixtures using unsupervised component analysis. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2017; 55:936-943. [PMID: 28480544 DOI: 10.1002/mrc.4606] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Revised: 04/28/2017] [Accepted: 05/03/2017] [Indexed: 06/07/2023]
Abstract
Nuclear magnetic resonance (NMR) is a very powerful instrumental technique suited to identify and characterize organic compounds. NMR has been successfully used in the analysis of complex biological and environmental samples; however, these applications are still rather limited. In this work, we describe unsupervised component analysis as a multivariate unsupervised method suited to identify the number of relevant NMR signal contributions and to deconvolve mixed signals into signal individual sources and respective contributions. Using this approach, we were able to advance further in the field of quantification of NMR spectra, and this methodology will help in the characterization of complex biological samples. Copyright © 2017 John Wiley & Sons, Ltd.
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Affiliation(s)
- Jorge Costa Pereira
- CQC, Department of Chemistry, University of Coimbra, P-3004 535, Coimbra, Portugal
| | - Ivana Jarak
- CICS-UBI, University of Beira Interior, 6201-506, Covilha, Portugal
- Centre for Functional Ecology, Faculty of Sciences and Technology, University of Coimbra, P-3000 456, Coimbra, Portugal
| | - Rui Albuquerque Carvalho
- Centre for Functional Ecology, Faculty of Sciences and Technology, University of Coimbra, P-3000 456, Coimbra, Portugal
- Department of Life Sciences, Faculty of Sciences and Technology, University of Coimbra, P-3000 456, Coimbra, Portugal
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31
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Richard V, Conotte R, Mayne D, Colet JM. Does the 1H-NMR plasma metabolome reflect the host-tumor interactions in human breast cancer? Oncotarget 2017; 8:49915-49930. [PMID: 28611296 PMCID: PMC5564817 DOI: 10.18632/oncotarget.18307] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2016] [Accepted: 04/01/2017] [Indexed: 12/13/2022] Open
Abstract
Breast cancer (BC) is the most common diagnosed cancer and the leading cause of cancer death in women worldwide. There is an obvious need for a better understanding of BC biology. Alterations in the serum metabolome of BC patients have been identified but their clinical significance remains elusive. We evaluated by 1H-Nuclear Magnetic Resonance (1H-NMR) spectroscopy, filtered plasma metabolome of 50 early (EBC) and 15 metastatic BC (MBC) patients. Using Principal Component Analysis, Partial Least-Squares Discriminant Analysis and Hierarchical Clustering we show that plasma levels of glucose, lactate, pyruvate, alanine, leucine, isoleucine, glutamate, glutamine, valine, lysine, glycine, threonine, tyrosine, phenylalanine, acetate, acetoacetate, β-hydroxy-butyrate, urea, creatine and creatinine are modulated across patients clusters. In particular lactate levels are inversely correlated with the tumor size in the EBC cohort (Pearson correlation r = -0.309; p = 0.044). We suggest that, in BC patients, tumor cells could induce modulation of the whole patient's metabolism even at early stages. If confirmed in a lager study these observations could be of clinical importance.
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Affiliation(s)
- Vincent Richard
- Department of Medical Oncology, CHU Ambroise Paré, B-7000 Mons, Belgium
- Laboratory of Human Biology and Toxicology, Faculty of Medicine and Pharmacy, University of Mons, B-7000 Mons, Belgium
- UMHAP, Bioprofiling Unit, B-7000 Mons, Belgium
| | - Raphaël Conotte
- Laboratory of Human Biology and Toxicology, Faculty of Medicine and Pharmacy, University of Mons, B-7000 Mons, Belgium
- UMHAP, Bioprofiling Unit, B-7000 Mons, Belgium
| | - David Mayne
- Unité de Recherche Clinique, CHU Ambroise Paré, B-7000 Mons, Belgium
| | - Jean-Marie Colet
- Laboratory of Human Biology and Toxicology, Faculty of Medicine and Pharmacy, University of Mons, B-7000 Mons, Belgium
- UMHAP, Bioprofiling Unit, B-7000 Mons, Belgium
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32
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Abstract
Metabolomics is the newest addition to the "omics" disciplines and has shown rapid growth in its application to human health research because of fundamental advancements in measurement and analysis techniques. Metabolomics has unique and proven advantages in systems biology and biomarker discovery. The next generation of analysis techniques promises even richer and more complete analysis capabilities that will enable earlier clinical diagnosis, drug refinement, and personalized medicine. A review of current advancements in methodologies and statistical analysis that are enhancing and improving the performance of metabolomics is presented along with highlights of some recent successful applications.
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Affiliation(s)
- Eli Riekeberg
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Robert Powers
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE, USA
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33
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Pandey R, Caflisch L, Lodi A, Brenner AJ, Tiziani S. Metabolomic signature of brain cancer. Mol Carcinog 2017; 56:2355-2371. [PMID: 28618012 DOI: 10.1002/mc.22694] [Citation(s) in RCA: 74] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2017] [Revised: 06/01/2017] [Accepted: 06/13/2017] [Indexed: 12/17/2022]
Abstract
Despite advances in surgery and adjuvant therapy, brain tumors represent one of the leading causes of cancer-related mortality and morbidity in both adults and children. Gliomas constitute about 60% of all cerebral tumors, showing varying degrees of malignancy. They are difficult to treat due to dismal prognosis and limited therapeutics. Metabolomics is the untargeted and targeted analyses of endogenous and exogenous small molecules, which charact erizes the phenotype of an individual. This emerging "omics" science provides functional readouts of cellular activity that contribute greatly to the understanding of cancer biology including brain tumor biology. Metabolites are highly informative as a direct signature of biochemical activity; therefore, metabolite profiling has become a promising approach for clinical diagnostics and prognostics. The metabolic alterations are well-recognized as one of the key hallmarks in monitoring disease progression, therapy, and revealing new molecular targets for effective therapeutic intervention. Taking advantage of the latest high-throughput analytical technologies, that is, nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), metabolomics is now a promising field for precision medicine and drug discovery. In the present report, we review the application of metabolomics and in vivo metabolic profiling in the context of adult gliomas and paediatric brain tumors. Analytical platforms such as high-resolution (HR) NMR, in vivo magnetic resonance spectroscopic imaging and high- and low-resolution MS are discussed. Moreover, the relevance of metabolic studies in the development of new therapeutic strategies for treatment of gliomas are reviewed.
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Affiliation(s)
- Renu Pandey
- Department of Nutritional Sciences, The University of Texas at Austin, Austin, Texas
| | - Laura Caflisch
- Department of Hematology and Medical oncology, University of Texas Health Science Center at San Antonio, San Antonio, Texas
| | - Alessia Lodi
- Department of Nutritional Sciences, The University of Texas at Austin, Austin, Texas
| | - Andrew J Brenner
- Department of Hematology and Medical oncology, University of Texas Health Science Center at San Antonio, San Antonio, Texas.,Department of Cancer Therapy and Research Center, University of Texas Health Science Center at San Antonio, San Antonio, Texas
| | - Stefano Tiziani
- Department of Nutritional Sciences, The University of Texas at Austin, Austin, Texas.,Dell Pediatric Research Institute, The University of Texas at Austin, Austin, Texas
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34
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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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35
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Metabolic Investigations of the Molecular Mechanisms Associated with Parkinson's Disease. Metabolites 2017; 7:metabo7020022. [PMID: 28538683 PMCID: PMC5487993 DOI: 10.3390/metabo7020022] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Revised: 05/16/2017] [Accepted: 05/16/2017] [Indexed: 12/20/2022] Open
Abstract
Parkinson’s disease (PD) is a neurodegenerative disorder characterized by fibrillar cytoplasmic aggregates of α-synuclein (i.e., Lewy bodies) and the associated loss of dopaminergic cells in the substantia nigra. Mutations in genes such as α-synuclein (SNCA) account for only 10% of PD occurrences. Exposure to environmental toxicants including pesticides and metals (e.g., paraquat (PQ) and manganese (Mn)) is also recognized as an important PD risk factor. Thus, aging, genetic alterations, and environmental factors all contribute to the etiology of PD. In fact, both genetic and environmental factors are thought to interact in the promotion of idiopathic PD, but the mechanisms involved are still unclear. In this study, we summarize our findings to date regarding the toxic synergistic effect between α-synuclein and paraquat treatment. We identified an essential role for central carbon (glucose) metabolism in dopaminergic cell death induced by paraquat treatment that is enhanced by the overexpression of α-synuclein. PQ “hijacks” the pentose phosphate pathway (PPP) to increase NADPH reducing equivalents and stimulate paraquat redox cycling, oxidative stress, and cell death. PQ also stimulated an increase in glucose uptake, the translocation of glucose transporters to the plasma membrane, and AMP-activated protein kinase (AMPK) activation. The overexpression of α-synuclein further stimulated an increase in glucose uptake and AMPK activity, but impaired glucose metabolism, likely directing additional carbon to the PPP to supply paraquat redox cycling.
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36
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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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37
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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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38
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Bingol K, Li DW, Zhang B, Brüschweiler R. Comprehensive Metabolite Identification Strategy Using Multiple Two-Dimensional NMR Spectra of a Complex Mixture Implemented in the COLMARm Web Server. Anal Chem 2016; 88:12411-12418. [PMID: 28193069 DOI: 10.1021/acs.analchem.6b03724] [Citation(s) in RCA: 72] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Identification of metabolites in complex mixtures represents a key step in metabolomics. A new strategy is introduced, which is implemented in a new public web server, COLMARm, that permits the coanalysis of up to three two-dimensional (2D) NMR spectra, namely, 13C-1H HSQC (heteronuclear single quantum coherence spectroscopy), 1H-1H TOCSY (total correlation spectroscopy), and 13C-1H HSQC-TOCSY, for the comprehensive, accurate, and efficient performance of this task. The highly versatile and interactive nature of COLMARm permits its application to a wide range of metabolomics samples independent of the magnetic field. Database query is performed using the HSQC spectrum, and the top metabolite hits are then validated against the TOCSY-type experiment(s) by superimposing the expected cross-peaks on the mixture spectrum. In this way the user can directly accept or reject candidate metabolites by taking advantage of the complementary spectral information offered by these experiments and their different sensitivities. The power of COLMARm is demonstrated for a human serum sample uncovering the existence of 14 metabolites that hitherto were not identified by NMR.
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Affiliation(s)
- Kerem Bingol
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory , Richland, Washington 99354, United States
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39
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Walker LR, Hoyt DW, Walker SM, Ward JK, Nicora CD, Bingol K. Unambiguous metabolite identification in high-throughput metabolomics by hybrid 1D 1 H NMR/ESI MS 1 approach. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2016; 54:998-1003. [PMID: 27539910 DOI: 10.1002/mrc.4503] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2016] [Revised: 07/08/2016] [Accepted: 08/15/2016] [Indexed: 06/06/2023]
Affiliation(s)
- Lawrence R Walker
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, 99354, USA
| | - David W Hoyt
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, 99354, USA
| | - S Michael Walker
- Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, KS, 66045, USA
| | - Joy K Ward
- Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, KS, 66045, USA
| | - Carrie D Nicora
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, 99354, USA
| | - Kerem Bingol
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, 99354, USA
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40
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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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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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42
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The metabolomic signature of hematologic malignancies. Leuk Res 2016; 49:22-35. [PMID: 27526405 DOI: 10.1016/j.leukres.2016.08.002] [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: 06/26/2016] [Revised: 08/04/2016] [Accepted: 08/08/2016] [Indexed: 12/17/2022]
Abstract
The ongoing accumulation of knowledge raises hopes that understanding tumor metabolism will provide new ways for predicting, diagnosing, and even treating cancers. Some metabolic biomarkers are at present routinely utilized to diagnose cancer and metabolic alterations of tumors are being confirmed as therapeutic targets. The growing utilization of metabolomics in clinical research may rapidly turn it into one of the most potent instruments used to detect and fight tumor. In fact, while the current state and trends of high throughput metabolomics profiling focus on the purpose of discovering biomarkers and hunting for metabolic mechanism, a prospective direction, namely reprogramming metabolomics, highlights the way to use metabolomics approach for the aim of treatment of disease by way of reconstruction of disturbed metabolic pathways. In this review, we present an ample summary of the current clinical appliances of metabolomics in hematological malignancies.
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Frédérich M, Pirotte B, Fillet M, de Tullio P. Metabolomics as a Challenging Approach for Medicinal Chemistry and Personalized Medicine. J Med Chem 2016; 59:8649-8666. [PMID: 27295417 DOI: 10.1021/acs.jmedchem.5b01335] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
"Omics" sciences have been developed to provide a holistic point of view of biology and to better understand the complexity of an organism as a whole. These systems biology approaches can be examined at different levels, starting from the most fundamental, i.e., the genome, and finishing with the most functional, i.e., the metabolome. Similar to how genomics is applied to the exploration of DNA, metabolomics is the qualitative and quantitative study of metabolites. This emerging field is clearly linked to genomics, transcriptomics, and proteomics. In addition, metabolomics provides a unique and direct vision of the functional outcome of an organism's activities that are required for it to survive, grow, and respond to internal and external stimuli or stress, e.g., pathologies and drugs. The links between metabolic changes, patient phenotype, physiological and/or pathological status, and treatment are now well established and have opened a new area for the application of metabolomics in the drug discovery process and in personalized medicine.
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Affiliation(s)
- Michel Frédérich
- Laboratory of Pharmacognosy, Center for Interdisciplinary Research on Medicines (CIRM), University of Liege , Quartier Hôpital, Avenue Hippocrate 15, B-4000 Liege, Belgium
| | - Bernard Pirotte
- Laboratory of Medicinal Chemistry, Center for Interdisciplinary Research on Medicines (CIRM), University of Liege , Quartier Hôpital, Avenue Hippocrate 15, B-4000 Liege, Belgium
| | - Marianne Fillet
- Laboratory for the Analysis of Medicines, Center for Interdisciplinary Research on Medicines (CIRM), University of Liege , Quartier Hôpital, Avenue Hippocrate 15, B-4000 Liege, Belgium
| | - Pascal de Tullio
- Laboratory of Medicinal Chemistry, Center for Interdisciplinary Research on Medicines (CIRM), University of Liege , Quartier Hôpital, Avenue Hippocrate 15, B-4000 Liege, Belgium
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Kilgore MB, Kutchan TM. The Amaryllidaceae alkaloids: biosynthesis and methods for enzyme discovery. PHYTOCHEMISTRY REVIEWS : PROCEEDINGS OF THE PHYTOCHEMICAL SOCIETY OF EUROPE 2016; 15:317-337. [PMID: 27340382 PMCID: PMC4914137 DOI: 10.1007/s11101-015-9451-z] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2015] [Accepted: 12/08/2015] [Indexed: 05/21/2023]
Abstract
Amaryllidaceae alkaloids are an example of the vast diversity of secondary metabolites with great therapeutic promise. The identification of novel compounds in this group with over 300 known structures continues to be an area of active study. The recent identification of norbelladine 4'-O-methyltransferase (N4OMT), an Amaryllidaceae alkaloid biosynthetic enzyme, and the assembly of transcriptomes for Narcissus sp. aff. pseudonarcissus and Lycoris aurea highlight the potential for discovery of Amaryllidaceae alkaloid biosynthetic genes with new technologies. Recent technical advances of interest include those in enzymology, next generation sequencing, genetic modification, nuclear magnetic resonance spectroscopy (NMR), and mass spectrometry (MS).
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Affiliation(s)
- Matthew B. Kilgore
- Donald Danforth Plant Science Center, 63132 St. Louis, Missouri, 975 N. Warson Rd., St. Louis, MO
| | - Toni M. Kutchan
- Donald Danforth Plant Science Center, 63132 St. Louis, Missouri, 975 N. Warson Rd., St. Louis, MO
- To whom correspondence should be addressed: Toni M. Kutchan, , Tel.: (314) 587-1473, Fax: (314) 587-1573
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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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