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Journal articles on the topic 'Metabolomics, Nuclear Magnetic Resonance'

Author: Grafiati

Published: 10 March 2023

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1

Lombó, Marta, Sara Ruiz-Díaz, Alfonso Gutiérrez-Adán, and María-Jesús Sánchez-Calabuig. "Sperm Metabolomics through Nuclear Magnetic Resonance Spectroscopy." Animals 11, no. 6 (June 3, 2021): 1669. http://dx.doi.org/10.3390/ani11061669.

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This report reviews current knowledge of sperm metabolomics analysis using proton nuclear magnetic resonance spectroscopy (1 H-NMR) with particular emphasis on human and farm animals. First, we present the benefits of NMR over other techniques to identify sperm metabolites and then describe the specific methodology required for NMR sperm analysis, stressing the importance of analyzing metabolites extracted from both the hydrophilic and lipophilic phases. This is followed by a description of advances produced to date in the use of NMR to diagnose infertility in humans and to identify metabolic differences among the sperm of mammalian herbivore, carnivore, and omnivore species. This last application of NMR mainly seeks to explore the possible use of lipids to fuel sperm physiology, contrary to previous theories that glycolysis and oxidative phosphorylation (OXPHOS) are the only sources of sperm energy. This review describes the use of NMR to identify sperm and seminal plasma metabolites as possible indicators of semen quality, and to examine the metabolites needed to maintain sperm motility, induce their capacitation, and consequently, to predict animal fertility.

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Capati, Ana, Omkar B. Ijare, and Tedros Bezabeh. "Diagnostic Applications of Nuclear Magnetic Resonance–Based Urinary Metabolomics." Magnetic Resonance Insights 10 (January 1, 2017): 1178623X1769434. http://dx.doi.org/10.1177/1178623x17694346.

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Metabolomics is a rapidly growing field with potential applications in various disciplines. In particular, metabolomics has received special attention in the discovery of biomarkers and diagnostics. This is largely due to the fact that metabolomics provides critical information related to the downstream products of many cellular and metabolic processes which could provide a snapshot of the health/disease status of a particular tissue or organ. Many of these cellular products eventually find their way to urine; hence, analysis of urine via metabolomics has the potential to yield useful diagnostic and prognostic information. Although there are a number of analytical platforms that can be used for this purpose, this review article will focus on nuclear magnetic resonance–based metabolomics. Furthermore, although there have been many studies addressing different diseases and metabolic disorders, the focus of this review article will be in the following specific applications: urinary tract infection, kidney transplant rejection, diabetes, some types of cancer, and inborn errors of metabolism. A number of methodological considerations that need to be taken into account for the development of a clinically useful optimal test are discussed briefly.

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Mayboroda, Oleg A., and Ekaterina Nevedomskaya. "On nuclear magnetic resonance, metabolomics and "metabolic individuality"." Vestnik Тomskogo gosudarstvennogo universiteta. Khimiya, no. 1 (September 1, 2015): 61–64. http://dx.doi.org/10.17223/24135542/1/9.

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Shin, Min-Ji, Tarmo Veskioja, Tiina Titma, and Ago Samoson. "Kemeny–Snell Distance in Nuclear Magnetic Resonance Metabolomics." Applied Magnetic Resonance 51, no. 12 (October 17, 2020): 1637–45. http://dx.doi.org/10.1007/s00723-020-01282-2.

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Paris, Debora, Mauro Maniscalco, and Andrea Motta. "Nuclear magnetic resonance-based metabolomics in respiratory medicine." European Respiratory Journal 52, no. 4 (August 16, 2018): 1801107. http://dx.doi.org/10.1183/13993003.01107-2018.

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6

Weng, JianXiang, Isabella H. Muti, Anya B. Zhong, Pia Kivisäkk, Bradley T. Hyman, Steven E. Arnold, and Leo L. Cheng. "A Nuclear Magnetic Resonance Spectroscopy Method in Characterization of Blood Metabolomics for Alzheimer’s Disease." Metabolites 12, no. 2 (February 15, 2022): 181. http://dx.doi.org/10.3390/metabo12020181.

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There is currently a crucial need for improved diagnostic techniques and targeted treatment methods for Alzheimer’s disease (AD), a disease which impacts millions of elderly individuals each year. Metabolomic analysis has been proposed as a potential methodology to better investigate and understand the progression of this disease. In this report, we present our AD metabolomics results measured with high resolution magic angle spinning (HRMAS) nuclear magnetic resonance (NMR) on human blood plasma samples obtained from AD and non-AD subjects. Our study centers on developments of AD and non-AD metabolomics differentiating models with procedures of quality assurance (QA) and quality control (QC) through pooled samples. Our findings suggest that analysis of blood plasma samples using HRMAS NMR has the potential to differentiate between diseased and healthy subjects, which has important clinical implications for future improvements in AD diagnosis methodologies.

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Brennan, Lorraine. "Metabolomics in nutrition research–a powerful window into nutritional metabolism." Essays in Biochemistry 60, no. 5 (December 15, 2016): 451–58. http://dx.doi.org/10.1042/ebc20160029.

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Metabolomics is the study of small molecules present in biological samples. In recent years it has become evident that such small molecules, called metabolites, play a key role in the development of disease states. Furthermore, metabolomic applications can reveal information about alterations in certain metabolic pathways under different conditions. Data acquisition in metabolomics is usually performed using nuclear magnetic resonance (NMR)-based approaches or mass spectrometry (MS)-based approaches with a more recent trend including the application of multiple platforms in order to maximise the coverage in terms of metabolites measured. The application of metabolomics is rapidly increasing and the present review will highlight applications in nutrition research.

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Lin, Yanqin, Qing Zeng, Liangjie Lin, and Zhong Chen. "High Resolution Nuclear Magnetic Resonance Spectroscopy on Biological Tissue and Metabolomics." Current Medicinal Chemistry 26, no. 12 (July 1, 2019): 2190–207. http://dx.doi.org/10.2174/0929867326666190312130155.

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High-resolution nuclear magnetic resonance (NMR) spectroscopy is a universal analytical tool. It can provide detailed information on chemical shifts, J coupling constants, multiplet patterns, and relative peak areas. It plays an important role in the fields of chemistry, biology, medicine, and pharmacy. A highly homogeneous magnetic field is a prerequisite for excellent spectral resolution. However, in some cases, such as in vivo and ex vivo biological tissues, the magnetic field inhomogeneity due to magnetic susceptibility variation in samples is unavoidable and hard to eliminate by conventional methods. The techniques based on intermolecular multiple quantum coherences and conventional single quantum coherence can remove the influence of the field inhomogeneity effects and be applied to obtain highresolution NMR spectra of biological tissues, including in vivo animal and human tissues. Broadband 1H homo-decoupled NMR spectroscopy displays J coupled resonances as collapsed singlets, resulting in highly resolved spectra. It can be used to acquire high-resolution spectra of some pharmaceuticals. The J-difference edited spectra can be used to detect J coupled metabolites, such as γ-aminobutyric acid, the detection of which is interfered by intense neighboring peaks. High-resolution 1H NMR spectroscopy has been widely utilized for the identification and characterization of biological fluids, constituting an important tool in drug discovery, drug development, and disease diagnosis.

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Wishart, David S., Leo L. Cheng, Valérie Copié, Arthur S. Edison, Hamid R. Eghbalnia, Jeffrey C. Hoch, Goncalo J. Gouveia, et al. "NMR and Metabolomics—A Roadmap for the Future." Metabolites 12, no. 8 (July 23, 2022): 678. http://dx.doi.org/10.3390/metabo12080678.

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Metabolomics investigates global metabolic alterations associated with chemical, biological, physiological, or pathological processes. These metabolic changes are measured with various analytical platforms including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance spectroscopy (NMR). While LC-MS methods are becoming increasingly popular in the field of metabolomics (accounting for more than 70% of published metabolomics studies to date), there are considerable benefits and advantages to NMR-based methods for metabolomic studies. In fact, according to PubMed, more than 926 papers on NMR-based metabolomics were published in 2021—the most ever published in a given year. This suggests that NMR-based metabolomics continues to grow and has plenty to offer to the scientific community. This perspective outlines the growing applications of NMR in metabolomics, highlights several recent advances in NMR technologies for metabolomics, and provides a roadmap for future advancements.

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Ge, Yanhui, Xiaojia Chen, Dejan Gođevac, Paula C. P. Bueno, Luis F. Salomé Abarca, Young Pyo Jang, Mei Wang, and Young Hae Choi. "Metabolic Profiling of Saponin-Rich Ophiopogon japonicus Roots Based on 1H NMR and HPTLC Platforms." Planta Medica 85, no. 11/12 (June 17, 2019): 917–24. http://dx.doi.org/10.1055/a-0947-5797.

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AbstractIdeally, metabolomics should deal with all the metabolites that are found within cells and biological systems. The most common technologies for metabolomics include mass spectrometry, and in most cases, hyphenated to chromatographic separations (liquid chromatography- or gas chromatography-mass spectrometry) and nuclear magnetic resonance spectroscopy. However, limitations such as low sensitivity and highly congested spectra in nuclear magnetic resonance spectroscopy and relatively low signal reproducibility in mass spectrometry impede the progression of these techniques from being universal metabolomics tools. These disadvantages are more notorious in studies of certain plant secondary metabolites, such as saponins, which are difficult to analyse, but have a great biological importance in organisms. In this study, high-performance thin-layer chromatography was used as a supplementary tool for metabolomics. A method consisting of coupling 1H nuclear magnetic resonance spectroscopy and high-performance thin-layer chromatography was applied to distinguish between Ophiopogon japonicus roots that were collected from two growth locations and were of different ages. The results allowed the root samples from the two growth locations to be clearly distinguished. The difficulties encountered in the identification of the marker compounds by 1H nuclear magnetic resonance spectroscopy was overcome using high-performance thin-layer chromatography to separate and isolate the compounds. The saponins, ophiojaponin C or ophiopogonin D, were found to be marker metabolites in the root samples and proved to be greatly influenced by plant growth location, but barely by age variation. The procedure used in this study is fully described with the purpose of making a valuable contribution to the quality control of saponin-rich herbal drugs using high-performance thin-layer chromatography as a supplementary analytical tool for metabolomics research.

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Furina, R. R., N. N. Mitrakova, V. L. Ryzhkov, and I. K. Safiullin. "Metabolomic research in medicine." Kazan medical journal 95, no. 1 (February 15, 2014): 1–6. http://dx.doi.org/10.17816/kmj1445.

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The paper covers the questions of metabolomic research in medicine. The central idea of metabolomics is to identify the specific biomarkers in biological samples for diagnosis of a number of conditions. The biomarkers include volatile organic compounds - metabolites isolated from various tissues and biological fluids (blood, urine, sputum, exhaled air). Main methods of separation and identification of volatile organic compounds (gas chromatography, mass spectrometry, nuclear magnetic resonance spectroscopy) applied in metabolomics, are reviewed. Mass spectrometry and nuclear magnetic resonance spectroscopy are compared as the main methods of volatile metabolites detection. The method of solid phase microextraction, used for sample preparation, is described. The paper reviews laboratory research results aimed at the detection of cancer, chronic infections and inherited diseases biomarkers. The qualitative characteristics of biological sample metabolome taken from patients with different diseases are discussed. Besides, special attention is paid to the possible use of metabolomics in experimental medicine. The results of volatile metabolome changes in cell culture in vitro depending on the additives to nutrient media, β-carotene volatile decomposition products as suspected carcinogens, volatile organic compounds emitted at vertebrates decay are described. In addition, the method of two-dimensional gas chromatography aimed to increase the sensitivity and specificity of metabolomics tests is portrayed. The presented approach adds to early diagnosis of a number of diseases.

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Vignoli, Alessia, Gaia Meoni, and Leonardo Tenori. "Applications and Challenges for Metabolomics via Nuclear Magnetic Resonance Spectroscopy." Applied Sciences 12, no. 9 (May 6, 2022): 4655. http://dx.doi.org/10.3390/app12094655.

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Even though metabolomics is about 20 years old, the interest in this “-omic” science is still growing, and high expectations remain in the scientific community for new practical applications in biomedicine and in the agricultural field [...]

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Pérez-Trujillo, Miriam, and Toby J. Athersuch. "Special Issue: NMR-Based Metabolomics." Molecules 26, no. 11 (May 29, 2021): 3283. http://dx.doi.org/10.3390/molecules26113283.

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Nuclear magnetic resonance (NMR) spectroscopy remains one of the core analytical platforms for metabolomics, providing complementary chemical information to others, such as mass spectrometry, and offering particular advantages in some areas of research on account of its inherent robustness, reproducibility, and phenomenal dynamic range [...]

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14

Chowdhury, Shamiha, Sultan Mohammed Faheem, Shaik Sarfaraz Nawaz, and Khalid Siddiqui. "The role of metabolomics in personalized medicine for diabetes." Personalized Medicine 18, no. 5 (September 2021): 501–8. http://dx.doi.org/10.2217/pme-2021-0083.

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Metabolomics is rapidly evolving omics technology in personalized medicine, it offers a new avenue for identification of multiple novel metabolic mediators of impaired glucose tolerance and dysglycemia. Liquid chromatography–mass spectrometry, gas chromatography–mass spectrometry and nuclear magnetic resonance spectroscopy are most commonly used analytical methods in the field of metabolomics. Recent evidences showed that metabolomic profiles are link to the incidence of diabetes. In this review, an overview of metabolomics studies in diabetes revealed several diabetes-associated metabolites including 1,5-anhydroglycitol, branch chain amino acids, glucose, α-hydroxybutyric acid, 3-hydroundecanoyl-carnitine and phosphatidylcholine that could be potential biomarkers associated with diabetes. These identified metabolites can be used to develop personalized prognostics and diagnostic, and help in diabetes management.

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Lima, Marta R. M., Sílvia O. Diaz, Inês Lamego, Michael A. Grusak, Marta W. Vasconcelos, and Ana M. Gil. "Nuclear Magnetic Resonance Metabolomics of Iron Deficiency in Soybean Leaves." Journal of Proteome Research 13, no. 6 (May 2014): 3075–87. http://dx.doi.org/10.1021/pr500279f.

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16

Lamichhane, Santosh, Christian C. Yde, Mette S. Schmedes, Henrik Max Jensen, Sebastian Meier, and Hanne Christine Bertram. "Strategy for Nuclear-Magnetic-Resonance-Based Metabolomics of Human Feces." Analytical Chemistry 87, no. 12 (May 28, 2015): 5930–37. http://dx.doi.org/10.1021/acs.analchem.5b00977.

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Yu, Hyo-Yeon, Sangki Myoung, and Sangdoo Ahn. "Recent Applications of Benchtop Nuclear Magnetic Resonance Spectroscopy." Magnetochemistry 7, no. 9 (September 1, 2021): 121. http://dx.doi.org/10.3390/magnetochemistry7090121.

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Benchtop nuclear magnetic resonance (NMR) spectroscopy uses small permanent magnets to generate magnetic fields and therefore offers the advantages of operational simplicity and reasonable cost, presenting a viable alternative to high-field NMR spectroscopy. In particular, the use of benchtop NMR spectroscopy for rapid in-field analysis, e.g., for quality control or forensic science purposes, has attracted considerable attention. As benchtop NMR spectrometers are sufficiently compact to be operated in a fume hood, they can be efficiently used for real-time reaction and process monitoring. This review introduces the recent applications of benchtop NMR spectroscopy in diverse fields, including food science, pharmaceuticals, process and reaction monitoring, metabolomics, and polymer materials.

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Byers, Nathaniel, Amy Fleshman, Rushika Perera, and Claudia Molins. "Metabolomic Insights into Human Arboviral Infections: Dengue, Chikungunya, and Zika Viruses." Viruses 11, no. 3 (March 6, 2019): 225. http://dx.doi.org/10.3390/v11030225.

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The global burden of arboviral diseases and the limited success in controlling them calls for innovative methods to understand arbovirus infections. Metabolomics has been applied to detect alterations in host physiology during infection. This approach relies on mass spectrometry or nuclear magnetic resonance spectroscopy to evaluate how perturbations in biological systems alter metabolic pathways, allowing for differentiation of closely related conditions. Because viruses heavily depend on host resources and pathways, they present unique challenges for characterizing metabolic changes. Here, we review the literature on metabolomics of arboviruses and focus on the interpretation of identified molecular features. Metabolomics has revealed biomarkers that differentiate disease states and outcomes, and has shown similarities in metabolic alterations caused by different viruses (e.g., lipid metabolism). Researchers investigating such metabolomic alterations aim to better understand host–virus dynamics, identify diagnostically useful molecular features, discern perturbed pathways for therapeutics, and guide further biochemical research. This review focuses on lessons derived from metabolomics studies on samples from arbovirus-infected humans.

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Motta, A., D. Paris, D. Melck, G. de Laurentiis, M. Maniscalco, M. Sofia, and P. Montuschi. "Nuclear magnetic resonance-based metabolomics of exhaled breath condensate: methodological aspects." European Respiratory Journal 39, no. 2 (January 31, 2012): 498–500. http://dx.doi.org/10.1183/09031936.00036411.

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20

Laíns, Inês, Daniela Duarte, António S. Barros, Ana Sofia Martins, Tatiana J. Carneiro, João Q. Gil, John B. Miller, et al. "Urine Nuclear Magnetic Resonance (NMR) Metabolomics in Age-Related Macular Degeneration." Journal of Proteome Research 18, no. 3 (January 23, 2019): 1278–88. http://dx.doi.org/10.1021/acs.jproteome.8b00877.

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Soininen, Pasi, Antti J. Kangas, Peter Würtz, Teemu Suna, and Mika Ala-Korpela. "Quantitative Serum Nuclear Magnetic Resonance Metabolomics in Cardiovascular Epidemiology and Genetics." Circulation: Cardiovascular Genetics 8, no. 1 (February 2015): 192–206. http://dx.doi.org/10.1161/circgenetics.114.000216.

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22

Tsai, Cheng-Kun, Chien-Yu Lin, Chung-Jan Kang, Chun-Ta Liao, Wan-Ling Wang, Meng-Han Chiang, Tzu-Chen Yen, and Gigin Lin. "Nuclear Magnetic Resonance Metabolomics Biomarkers for Identifying High Risk Patients with Extranodal Extension in Oral Squamous Cell Carcinoma." Journal of Clinical Medicine 9, no. 4 (March 30, 2020): 951. http://dx.doi.org/10.3390/jcm9040951.

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Extranodal extension (ENE) is an independent adverse prognostic factor in oral squamous cell carcinoma (OSCC), and is difficult to identify preoperatively. We aimed to discover biomarkers for high risk patients with ENE. Tandem tissue, plasma, and urine samples of 110 patients with OSCC were investigated through 600-MHz nuclear magnetic resonance (NMR) metabolomics analysis. We found that the levels of creatine, creatine phosphate, glycine, and tyramine in plasma significantly decreased in stage IV ENE positive OSCC compared with stage IV ENE negative OSCC. To understand the underlying mechanism behind the alteration of plasma metabolites, our tissue analysis revealed that the carnitine level significantly increased in tumors but significantly decreased in the adjacent normal tissue in advanced stage OSCC, in addition to decreased levels of alanine and pyruvate in tumor tissues. The global metabolomics analysis on tumor tissues also showed that stage IV tumors with an ENE positive status demonstrated higher levels of aspartate, butyrate, carnitine, glutamate, glutathione, glycine, glycolate, guanosine, and sucrose but lower levels of alanine, choline, glucose, isoleucine, lactate, leucine, myo-inositol, O-acetylcholine, oxypurinol, phenylalanine, pyruvate, succinate, tyrosine, valine, and xanthine than tumors with an ENE negative status. We concluded that metabolomics alterations in tumor tissues correspond to an increase in the tumor stage and are detectable in plasma samples. Metabolomic alterations of OSCC can serve as potential diagnostic markers and predictors of ENE in patients with stage IV OSCC.

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Monge, María Eugenia, James N. Dodds, Erin S. Baker, Arthur S. Edison, and Facundo M. Fernández. "Challenges in Identifying the Dark Molecules of Life." Annual Review of Analytical Chemistry 12, no. 1 (June 12, 2019): 177–99. http://dx.doi.org/10.1146/annurev-anchem-061318-114959.

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Metabolomics is the study of the metabolome, the collection of small molecules in living organisms, cells, tissues, and biofluids. Technological advances in mass spectrometry, liquid- and gas-phase separations, nuclear magnetic resonance spectroscopy, and big data analytics have now made it possible to study metabolism at an omics or systems level. The significance of this burgeoning scientific field cannot be overstated: It impacts disciplines ranging from biomedicine to plant science. Despite these advances, the central bottleneck in metabolomics remains the identification of key metabolites that play a class-discriminant role. Because metabolites do not follow a molecular alphabet as proteins and nucleic acids do, their identification is much more time consuming, with a high failure rate. In this review, we critically discuss the state-of-the-art in metabolite identification with specific applications in metabolomics and how technologies such as mass spectrometry, ion mobility, chromatography, and nuclear magnetic resonance currently contribute to this challenging task.

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Huang, Katherine, Natalie Thomas, Paul R. Gooley, and Christopher W. Armstrong. "Systematic Review of NMR-Based Metabolomics Practices in Human Disease Research." Metabolites 12, no. 10 (October 12, 2022): 963. http://dx.doi.org/10.3390/metabo12100963.

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Nuclear magnetic resonance (NMR) spectroscopy is one of the principal analytical techniques for metabolomics. It has the advantages of minimal sample preparation and high reproducibility, making it an ideal technique for generating large amounts of metabolomics data for biobanks and large-scale studies. Metabolomics is a popular “omics” technology and has established itself as a comprehensive exploratory biomarker tool; however, it has yet to reach its collaborative potential in data collation due to the lack of standardisation of the metabolomics workflow seen across small-scale studies. This systematic review compiles the different NMR metabolomics methods used for serum, plasma, and urine studies, from sample collection to data analysis, that were most popularly employed over a two-year period in 2019 and 2020. It also outlines how these methods influence the raw data and the downstream interpretations, and the importance of reporting for reproducibility and result validation. This review can act as a valuable summary of NMR metabolomic workflows that are actively used in human biofluid research and will help guide the workflow choice for future research.

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Lankadurai, Brian P., Edward G. Nagato, and Myrna J. Simpson. "Environmental metabolomics: an emerging approach to study organism responses to environmental stressors." Environmental Reviews 21, no. 3 (September 2013): 180–205. http://dx.doi.org/10.1139/er-2013-0011.

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Metabolomics is the analysis of endogenous and exogenous low molecular mass metabolites within a cell, tissue, or biofluid of an organism in response to an external stressor. The sub-discipline of environmental metabolomics is the application of metabolomic techniques to analyze the interactions of organisms with their environment. There has been a rapid growth in environmental metabolomics over the past decade. This growth can be attributed to the comprehensive and rapid nature of nontargeted metabolomics and the ability to generate hypotheses involving complex environmental stressors, especially when the mode of action is unknown. Using a wide variety of model organisms, metabolomic studies have detected stress from abiotic factors such as xenobiotic exposure and temperature shifts as well as biotic stressors such as herbivory and competition. Nuclear magnetic resonance (NMR)-based metabolomics has been the dominant analytical platform used for environmental metabolomics studies, owing to its nonselectivity and ease of sample preparation. However, the number of mass spectrometry (MS)-based metabolomic studies is also increasing rapidly, owing to its high sensitivity for the detection of trace levels of metabolites. In this review, we provide an overview of the general experimental design, extraction methods, analytical instrumentation, and statistical methods used in environmental metabolomics. We then highlight some of the recent studies that have used metabolomics to elucidate hitherto unknown biochemical modes of actions of various environmental stressors to both terrestrial and aquatic organisms, as well as identify potential metabolite shifts as early bioindicators of these stressors. Through this, we emphasize the immense potential and versatility of environmental metabolomics as a routine tool for characterizing the responses of organisms to numerous types of environmental stressors.

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Serkova, Natalie J., Zachary Van Rheen, Meghan Tobias, Joshua E. Pitzer, J. Erby Wilkinson, and Kathleen A. Stringer. "Utility of magnetic resonance imaging and nuclear magnetic resonance-based metabolomics for quantification of inflammatory lung injury." American Journal of Physiology-Lung Cellular and Molecular Physiology 295, no. 1 (July 2008): L152—L161. http://dx.doi.org/10.1152/ajplung.00515.2007.

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Magnetic resonance imaging (MRI) and metabolic nuclear magnetic resonance (NMR) spectroscopy are clinically available but have had little application in the quantification of experimental lung injury. There is a growing and unfulfilled need for predictive animal models that can improve our understanding of disease pathogenesis and therapeutic intervention. Integration of MRI and NMR could extend the application of experimental data into the clinical setting. This study investigated the ability of MRI and metabolic NMR to detect and quantify inflammation-mediated lung injury. Pulmonary inflammation was induced in male B6C3F1 mice by intratracheal administration of IL-1β and TNF-α under isoflurane anesthesia. Mice underwent MRI at 2, 4, 6, and 24 h after dosing. At 6 and 24 h lungs were harvested for metabolic NMR analysis. Data acquired from IL-1β+TNF-α-treated animals were compared with saline-treated control mice. The hyperintense-to-total lung volume (HTLV) ratio derived from MRI was higher in IL-1β+TNF-α-treated mice compared with control at 2, 4, and 6 h but returned to control levels by 24 h. The ability of MRI to detect pulmonary inflammation was confirmed by the association between HTLV ratio and histological and pathological end points. Principal component analysis of NMR-detectable metabolites also showed a temporal pattern for which energy metabolism-based biomarkers were identified. These data demonstrate that both MRI and metabolic NMR have utility in the detection and quantification of inflammation-mediated lung injury. Integration of these clinically available techniques into experimental models of lung injury could improve the translation of basic science knowledge and information to the clinic.

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Emwas, Abdul-Hamid, Raja Roy, Ryan T. McKay, Leonardo Tenori, Edoardo Saccenti, G. A. Nagana Gowda, Daniel Raftery, et al. "NMR Spectroscopy for Metabolomics Research." Metabolites 9, no. 7 (June 27, 2019): 123. http://dx.doi.org/10.3390/metabo9070123.

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Over the past two decades, nuclear magnetic resonance (NMR) has emerged as one of the three principal analytical techniques used in metabolomics (the other two being gas chromatography coupled to mass spectrometry (GC-MS) and liquid chromatography coupled with single-stage mass spectrometry (LC-MS)). The relative ease of sample preparation, the ability to quantify metabolite levels, the high level of experimental reproducibility, and the inherently nondestructive nature of NMR spectroscopy have made it the preferred platform for long-term or large-scale clinical metabolomic studies. These advantages, however, are often outweighed by the fact that most other analytical techniques, including both LC-MS and GC-MS, are inherently more sensitive than NMR, with lower limits of detection typically being 10 to 100 times better. This review is intended to introduce readers to the field of NMR-based metabolomics and to highlight both the advantages and disadvantages of NMR spectroscopy for metabolomic studies. It will also explore some of the unique strengths of NMR-based metabolomics, particularly with regard to isotope selection/detection, mixture deconvolution via 2D spectroscopy, automation, and the ability to noninvasively analyze native tissue specimens. Finally, this review will highlight a number of emerging NMR techniques and technologies that are being used to strengthen its utility and overcome its inherent limitations in metabolomic applications.

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Jingwei Lv, Jingwei Lv, Chunnan Li Chunnan Li, Nanxi Zhang Nanxi Zhang, Kaiyue Z. Kaiyue Z, Xiaochen Gao Xiaochen Gao, Na Li Na Li, Lingwen M. Lingwen M, Yinping Y. Yinping Y, and Hui Zhang and Jiaming Sun Hui Zhang and Jiaming Sun. "Metabolomic Profiling of Different Maca Color Types Using Nuclear Magnetic Resonance Spectroscopy and Multivariate Data Analysis." Journal of the chemical society of pakistan 44, no. 4 (2022): 356. http://dx.doi.org/10.52568/001071/jcsp/44.04.2022.

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This study aimed to explore significant differences in chemical composition among maca (Lepidium meyenii Walp.) types with different colors in Yunnan province, China. 1H-NMR spectroscopy, in combination with principal component analysis and partial least squares discriminant analysis, was used to investigate the compounds responsible for compositional differences. Different maca color types in Yunnan were clearly distinguished by 11 differential metabolites. Furthermore, network pharmacology results showed that 30 active components were related to Alzheimer’s disease. Nine intersecting compounds among the 11 differential metabolites and 30 active components, namely, lysine, isoleucine, phenylalanine, β-hydroxybutyrate, tryptophan, pyroglutamate, proline, glutamine, and fructose, were used as bioactive markers to identify different maca color types. The results showed the bioactive markers among different maca color types holistically, providing a scientific basis for assessing the quality of commercial products derived from different maca color types.

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Ahmed, Sakir, Durgesh Dubey, Abhra Chowdhury, Smriti Chaurasia, Anupam Guleria, Sandeep Kumar, Rajeev Singh, Dinesh Kumar, and Ramnath Misra. "Nuclear magnetic resonance‐based metabolomics reveals similar metabolomics profiles in undifferentiated peripheral spondyloarthritis and reactive arthritis." International Journal of Rheumatic Diseases 22, no. 4 (February 27, 2019): 725–33. http://dx.doi.org/10.1111/1756-185x.13490.

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Di Donato, Samantha, Alessia Vignoli, Chiara Biagioni, Luca Malorni, Elena Mori, Leonardo Tenori, Vanessa Calamai, et al. "A Serum Metabolomics Classifier Derived from Elderly Patients with Metastatic Colorectal Cancer Predicts Relapse in the Adjuvant Setting." Cancers 13, no. 11 (June 2, 2021): 2762. http://dx.doi.org/10.3390/cancers13112762.

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Adjuvant treatment for patients with early stage colorectal cancer (eCRC) is currently based on suboptimal risk stratification, especially for elderly patients. Metabolomics may improve the identification of patients with residual micrometastases after surgery. In this retrospective study, we hypothesized that metabolomic fingerprinting could improve risk stratification in patients with eCRC. Serum samples obtained after surgery from 94 elderly patients with eCRC (65 relapse free and 29 relapsed, after 5-years median follow up), and from 75 elderly patients with metastatic colorectal cancer (mCRC) obtained before a new line of chemotherapy, were retrospectively analyzed via proton nuclear magnetic resonance spectroscopy. The prognostic role of metabolomics in patients with eCRC was assessed using Kaplan–Meier curves. PCA-CA-kNN could discriminate the metabolomic fingerprint of patients with relapse-free eCRC and mCRC (70.0% accuracy using NOESY spectra). This model was used to classify the samples of patients with relapsed eCRC: 69% of eCRC patients with relapse were predicted as metastatic. The metabolomic classification was strongly associated with prognosis (p-value 0.0005, HR 3.64), independently of tumor stage. In conclusion, metabolomics could be an innovative tool to refine risk stratification in elderly patients with eCRC. Based on these results, a prospective trial aimed at improving risk stratification by metabolomic fingerprinting (LIBIMET) is ongoing.

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Sethi, Nikunj, Rohit Mahar, Sanjeev K. Shukla, Akhilesh Kumar, and Neeraj Sinha. "Correction: A novel approach for testing the teratogenic potential of chemicals on the platform of metabolomics: studies employing HR-MAS nuclear magnetic resonance spectroscopy." RSC Advances 5, no. 66 (2015): 53341. http://dx.doi.org/10.1039/c5ra90058a.

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Correction for ‘A novel approach for testing the teratogenic potential of chemicals on the platform of metabolomics: studies employing HR-MAS nuclear magnetic resonance spectroscopy’ by Nikunj Sethi et al., RSC Adv., 2015, 5, 26027–26039.

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Abooshahab, Raziyeh, Hamidreza Ardalani, Maryam Zarkesh, Koroush Hooshmand, Ali Bakhshi, Crispin R. Dass, and Mehdi Hedayati. "Metabolomics—A Tool to Find Metabolism of Endocrine Cancer." Metabolites 12, no. 11 (November 21, 2022): 1154. http://dx.doi.org/10.3390/metabo12111154.

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Clinical endocrinology entails an understanding of the mechanisms involved in the regulation of tumors that occur in the endocrine system. The exact cause of endocrine cancers remains an enigma, especially when discriminating malignant lesions from benign ones and early diagnosis. In the past few years, the concepts of personalized medicine and metabolomics have gained great popularity in cancer research. In this systematic review, we discussed the clinical metabolomics studies in the diagnosis of endocrine cancers within the last 12 years. Cancer metabolomic studies were largely conducted using nuclear magnetic resonance (NMR) and mass spectrometry (MS) combined with separation techniques such as gas chromatography (GC) and liquid chromatography (LC). Our findings revealed that the majority of the metabolomics studies were conducted on tissue, serum/plasma, and urine samples. Studies most frequently emphasized thyroid cancer, adrenal cancer, and pituitary cancer. Altogether, analytical hyphenated techniques and chemometrics are promising tools in unveiling biomarkers in endocrine cancer and its metabolism disorders.

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Darshi, Manjula, Benjamin Van Espen, and Kumar Sharma. "Metabolomics in Diabetic Kidney Disease: Unraveling the Biochemistry of a Silent Killer." American Journal of Nephrology 44, no. 2 (2016): 92–103. http://dx.doi.org/10.1159/000447954.

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The development of new therapies for chronic diseases, such as diabetic kidney disease (DKD), will continue to be hampered by lack of sufficient biomarkers that will provide insights and will be responsive to treatment interventions. The recent application of metabolomic technologies, such as nuclear magnetic resonance and mass spectroscopy, has allowed large-scale analysis of small molecules to be interrogated in a targeted or untargeted manner. Recent advances from both human and animal studies that have arisen from metabolomic analysis have recognized that mitochondrial function and fatty acid oxidation play key roles in the development and progression of DKD. Although many challenges in the technology for clinical chronic kidney disease (CKD) are yet to be validated, there will very likely be ongoing major contributions of metabolomics to develop new biochemical understanding for diabetic and CKD. The clinical application of metabolomics and accompanying bioinformatic tools will likely be a cornerstone of personalized medicine triumphs for CKD.

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Bliziotis, Nikolaos G., Leo A. J. Kluijtmans, Gerjen H. Tinnevelt, Parminder Reel, Smarti Reel, Katharina Langton, Mercedes Robledo, et al. "Preanalytical Pitfalls in Untargeted Plasma Nuclear Magnetic Resonance Metabolomics of Endocrine Hypertension." Metabolites 12, no. 8 (July 24, 2022): 679. http://dx.doi.org/10.3390/metabo12080679.

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Despite considerable morbidity and mortality, numerous cases of endocrine hypertension (EHT) forms, including primary aldosteronism (PA), pheochromocytoma and functional paraganglioma (PPGL), and Cushing’s syndrome (CS), remain undetected. We aimed to establish signatures for the different forms of EHT, investigate potentially confounding effects and establish unbiased disease biomarkers. Plasma samples were obtained from 13 biobanks across seven countries and analyzed using untargeted NMR metabolomics. We compared unstratified samples of 106 PHT patients to 231 EHT patients, including 104 PA, 94 PPGL and 33 CS patients. Spectra were subjected to a multivariate statistical comparison of PHT to EHT forms and the associated signatures were obtained. Three approaches were applied to investigate and correct confounding effects. Though we found signatures that could separate PHT from EHT forms, there were also key similarities with the signatures of sample center of origin and sample age. The study design restricted the applicability of the corrections employed. With the samples that were available, no biomarkers for PHT vs. EHT could be identified. The complexity of the confounding effects, evidenced by their robustness to correction approaches, highlighted the need for a consensus on how to deal with variabilities probably attributed to preanalytical factors in retrospective, multicenter metabolomics studies.

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Yong, Helena Y., Gerald Larrouy-Maumus, Mire Zloh, Rosemary Smyth, Rayan Ataya, Christopher M. Benton, and Michael R. Munday. "Early detection of metabolic changes in drug-induced steatosis using metabolomics approaches." RSC Advances 10, no. 67 (2020): 41047–57. http://dx.doi.org/10.1039/d0ra06577c.

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Urinary metabolic profiling of tetracycline induced hepatic steatotic rats were investigated using ¹H nuclear magnetic resonance, 2D ¹H–¹H total correlation spectroscopy and electrospray liquid chromatography-mass spectrometry based metabolomics.

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Jagannathan, NaranamangalamR, and RRavikanth Reddy. "Potential of nuclear magnetic resonance metabolomics in the study of prostate cancer." Indian Journal of Urology 38, no. 2 (2022): 99. http://dx.doi.org/10.4103/iju.iju_416_21.

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Montuschi, Paolo, Debora Paris, Silvia Montella, Dominique Melck, Virginia Mirra, Giuseppe Santini, Nadia Mores, et al. "Nuclear Magnetic Resonance–based Metabolomics Discriminates Primary Ciliary Dyskinesia from Cystic Fibrosis." American Journal of Respiratory and Critical Care Medicine 190, no. 2 (July 15, 2014): 229–33. http://dx.doi.org/10.1164/rccm.201402-0249le.

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GU, Hai-Wei, Yun-Peng QI, Ning XU, Jian-Hua DING, Yan-Bo AN, and Huan-Wen CHEN. "Nuclear Magnetic Resonance Spectroscopy and Mass Spectrometry-based Metabolomics for Cancer Diagnosis." CHINESE JOURNAL OF ANALYTICAL CHEMISTRY (CHINESE VERSION) 40, no. 12 (July 30, 2013): 1933–37. http://dx.doi.org/10.3724/sp.j.1096.2012.10542.

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Marshall, Darrell D., and Robert Powers. "Beyond the paradigm: Combining mass spectrometry and nuclear magnetic resonance for metabolomics." Progress in Nuclear Magnetic Resonance Spectroscopy 100 (May 2017): 1–16. http://dx.doi.org/10.1016/j.pnmrs.2017.01.001.

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GU, Hai-Wei, Yun-Peng QI, Ning XU, Jian-Hua DING, Yan-Bo AN, and Huan-Wen CHEN. "Nuclear Magnetic Resonance Spectroscopy and Mass Spectrometry-Based Metabolomics for Cancer Diagnosis." Chinese Journal of Analytical Chemistry 40, no. 12 (December 2012): 1933–37. http://dx.doi.org/10.1016/s1872-2040(11)60594-x.

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Leenders, Justine, Michel Frédérich, and Pascal de Tullio. "Nuclear magnetic resonance: a key metabolomics platform in the drug discovery process." Drug Discovery Today: Technologies 13 (June 2015): 39–46. http://dx.doi.org/10.1016/j.ddtec.2015.06.005.

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Sharma, Raj Kumar, Kumudesh Mishra, Alvina Farooqui, Anu Behari, Vinay Kumar Kapoor, and Neeraj Sinha. "1H nuclear magnetic resonance (NMR)-based serum metabolomics of human gallbladder inflammation." Inflammation Research 66, no. 1 (October 21, 2016): 97–105. http://dx.doi.org/10.1007/s00011-016-0998-y.

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Maniscalco, Mauro, Adele Cutignano, Debora Paris, Dominique J. Melck, Antonio Molino, Salvatore Fuschillo, and Andrea Motta. "Metabolomics of Exhaled Breath Condensate by Nuclear Magnetic Resonance Spectroscopy and Mass Spectrometry: A Methodological Approach." Current Medicinal Chemistry 27, no. 14 (April 29, 2020): 2381–99. http://dx.doi.org/10.2174/0929867325666181008122749.

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: Respiratory diseases present a very high prevalence in the general population, with an increase in morbidity, mortality and health-care expenses worldwide. They are complex and heterogeneous pathologies that may present different pathological facets in different subjects, often with personal evolution. Therefore, there is a need to identify patients with similar characteristics, prognosis or treatment, defining the so-called phenotype, but also to mark specific differences within each phenotype, defining the endotypes. : Biomarkers are very useful to study respiratory phenotypes and endotypes. Metabolomics, one of the recently introduced “omics”, is becoming a leading technique for biomarker discovery. For the airways, metabolomics appears to be well suited as the respiratory tract offers a natural matrix, the Exhaled Breath Condensate (EBC), in which several biomarkers can be measured. In this review, we will discuss the main methodological issues related to the application of Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) to EBC metabolomics for investigating respiratory diseases.

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Chasapi, Styliani A., Evdokia Karagkouni, Dimitra Kalavrizioti, Sotirios Vamvakas, Aikaterini Zompra, Panteleimon G. Takis, Dimitrios S. Goumenos, and Georgios A. Spyroulias. "NMR-Based Metabolomics in Differential Diagnosis of Chronic Kidney Disease (CKD) Subtypes." Metabolites 12, no. 6 (May 28, 2022): 490. http://dx.doi.org/10.3390/metabo12060490.

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Chronic Kidney Disease (CKD) is considered as a major public health problem as it can lead to end-stage kidney failure, which requires replacement therapy. A prompt and accurate diagnosis, along with the appropriate treatment, can delay CKD’s progression, significantly. Herein, we sought to determine whether CKD etiology can be reflected in urine metabolomics during its early stage. This is achieved through the analysis of the urine metabolic fingerprint from 108 CKD patients by means of Nuclear Magnetic Resonance (NMR) spectroscopy metabolomic analysis. We report the first NMR—metabolomics data regarding the three most common etiologies of CKD: Chronic Glomerulonephritis (IgA and Membranous Nephropathy), Diabetic Nephropathy (DN) and Hypertensive Nephrosclerosis (HN). Analysis aided a moderate glomerulonephritis clustering, providing characterization of the metabolic fluctuations between the CKD subtypes and control disease. The urine metabolome of IgA Nephropathy reveals a specific metabolism, reflecting its different etiology or origin and is useful for determining the origin of the disease. In contrast, urine metabolomes from DN and HN patients did not reveal any indicative metabolic pattern, which is consistent with their fused clinical phenotype. These findings may contribute to improving diagnostics and prognostic approaches for CKD, as well as improving our understanding of its pathology.

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Anand, Anupama, Anshu Sharma, Harpreet Kaur Saini, Somesh Sharma, Ruchi Sharma, Chahat Thakur, Priyanka, Maria Atanassova, Gianluca Caruso, and Ardalan Pasdaran. "Profiling of Plant Derived Natural Constituents by Using Magnetic Resonance Techniques." Concepts in Magnetic Resonance Part A 2022 (August 8, 2022): 1–17. http://dx.doi.org/10.1155/2022/5705637.

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Plants are reservoirs of naturally occurring chemical constituents with a wide range of structural diversity. These biological compounds can be derived from different parts of plants such as leaves, barks, seeds, seed coats, flowers, and roots. A broad array of secondary metabolic compounds is present in the plants such as antibiotics, alkaloids, antimicrobials, food-grade pigments, and phenolics which have been reported to possess numerous health-related benefits, including antioxidant, anti-inflammatory, anticancer, and antiobesity activities. Therefore, the identification and detection of these compounds are of utmost importance in order to utilise their benefits into various fields. Wherein, magnetic resonance techniques, such as NMR (nuclear magnetic resonance), MRI (magnetic resonance imaging), and EPR (electron paramagnetic resonance), being far more reproducible, nondestructive, than other analytical techniques such as liquid chromatography, mass spectroscopy, and high-performance liquid chromatography cover a much wider dynamic range of metabolites with easy sample preparation techniques with high speed and fidelity. Hence, these magnetic resonance techniques have been proven to be extremely useful in plant metabolite profiling and disease metabolomics, along with structural elucidation of bioactive compounds from plant sources. Therefore, the present review focuses on the effectiveness of magnetic resonance for the detection of plant-derived metabolites that may lead to new areas of research in various fields such as drug discovery and development, metabolomics, combinatorial chemistry, and assessing overall food safety and quality.

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Date, Yasuhiro, Chiaki Ishikawa, Makoto Umeda, Yusuke Tarumoto, Megumi Okubo, Yasuaki Tamura, and Hiroshi Ono. "Sugarcane Metabolome Compositional Stability in Pretreatment Processes for NMR Measurements." Metabolites 12, no. 9 (September 14, 2022): 862. http://dx.doi.org/10.3390/metabo12090862.

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Sugarcane is essential for global sugar production and its compressed juice is a key raw material for industrial products. Sugarcane juice includes various metabolites with abundances and compositional balances influencing product qualities and functionalities. Therefore, understanding the characteristic features of the sugarcane metabolome is important. However, sugarcane compositional variability and stability, even in pretreatment processes for nuclear magnetic resonance (NMR)-based metabolomic studies, remains elusive. The objective of this study is to evaluate sugarcane juice metabolomic variability affected by centrifugation, filtration, and thermal pretreatments, as well as the time-course changes for determining optimal conditions for NMR-based metabolomic approach. The pretreatment processes left the metabolomic compositions unchanged, indicating that these pretreatments are compatible with one another and the studied metabolomes are comparable. The thermal processing provided stability to the metabolome for more than 32 h at room temperature. Based on the determined analytical conditions, we conducted an NMR-based metabolomic study to discriminate the differences in the harvest period and allowed for successfully identifying the characteristic metabolome. Our findings denote that NMR-based sugarcane metabolomics enable us to provide an opportunity to collect a massive amount of data upon collaboration between multiple researchers, resulting in the rapid construction of useful databases for both research purposes and industrial use.

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He, Weiwei, and Hanne Christine Bertram. "NMR-Based Metabolomics to Decipher the Molecular Mechanisms in the Action of Gut-Modulating Foods." Foods 11, no. 17 (September 5, 2022): 2707. http://dx.doi.org/10.3390/foods11172707.

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Metabolomics deals with uncovering and characterizing metabolites present in a biological system, and is a leading omics discipline as it provides the nearest link to the biological phenotype. Within food and nutrition, metabolomics applied to fecal samples and bio-fluids has become an important tool to obtain insight into how food and food components may exert gut-modulating effects. This review aims to highlight how nuclear magnetic resonance (NMR)-based metabolomics in food and nutrition science may help us get beyond where we are today in understanding foods’ inherent, or added, biofunctionalities in relation to gut health.

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Behrends, Volker, Benedikt Geier, Huw D. Williams, and Jacob G. Bundy. "Direct Assessment of Metabolite Utilization by Pseudomonas aeruginosa during Growth on Artificial Sputum Medium." Applied and Environmental Microbiology 79, no. 7 (January 25, 2013): 2467–70. http://dx.doi.org/10.1128/aem.03609-12.

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ABSTRACTWe grewPseudomonas aeruginosain LB and artificial sputum medium (ASM) (filtered and unfiltered) and quantified metabolite utilization and excretion by nuclear magnetic resonance (NMR) spectroscopy (metabolic footprinting or extracellular metabolomics). Utilization rates were similar between media, but there were differences in excretion—e.g., acetate was produced only in unfiltered ASM.

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Li, Zhongfeng, Xinfeng Liu, Juan Wang, Jian Gao, Shuzhen Guo, Kuo Gao, Hongxue Man, Yingfeng Wang, Jianxin Chen, and Wei Wang. "Analysis of urinary metabolomic profiling for unstable angina pectoris disease based on nuclear magnetic resonance spectroscopy." Molecular BioSystems 11, no. 12 (2015): 3387–96. http://dx.doi.org/10.1039/c5mb00489f.

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Merz, Andrea L., and Natalie J. Serkova. "Use of nuclear magnetic resonance-based metabolomics in detecting drug resistance in cancer." Biomarkers in Medicine 3, no. 3 (June 2009): 289–306. http://dx.doi.org/10.2217/bmm.09.15.

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