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The NMR-Based Metabolomics
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The NMR-Based Metabolomics

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Analytical Chemistry".

Deadline for manuscript submissions: closed (31 May 2021) | Viewed by 19450

Special Issue Editor

Dr. Alan Wong

E-Mail Website1 Website2
Guest Editor
NIMBE, CEA, CNRS, Université Paris-Saclay, CEA Saclay, 91191 Gif-sur-Yvette, France
Interests: NMR spectroscopy; NMR developments; metabolomics

Special Issue Information

Dear Colleagues,

Metabolomics is one of the significant -omics fields which investigates the chemical profiles of low-molecular weight metabolites (<1 kDa) and responses to the metabolism of interest. It plays a vital role in untangling many biocomplexities in life. In this, nuclear magnetic resonance (NMR) spectroscopy is one of the driving forces, owing to its simplicity and versatility of acquiring unbiased and rich metabolic information from a broad spectrum of studies (ex vivo, in vitro, in vivo, and intact) with diverse specimens (biofluids, biotissues, etc.). For these reasons, NMR has been an important analytical component in many different research fields of metabolomics. This indeed is the consequence of the vast advancement in technologies, methodologies, and applications of NMR spectroscopy towards metabolomic analyses.

This Special Issue is to showcase the developments—in technologies, methodologies, and applications—of NMR spectroscopy as a frontline analytical strategy to metabolomics. Much like the diversity present in the field of NMR, the issue is designed to cover a wide range of research topics, but with the intent of highlighting the significance of NMR to metabolomics. Submissions of both original research and review articles are welcomed.

Dr. Alan Wong
Guest Editor

Manuscript Submission Information

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Keywords

  • NMR metabolomics
  • NMR technology
  • NMR methodology
  • NMR application

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Published Papers (5 papers)

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Research

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15 pages, 2301 KiB  
Article
1H HR-MAS NMR Based Metabolic Profiling of Lung Cancer Cells with Induced and De-Induced Cisplatin Resistance to Reveal Metabolic Resistance Adaptations
by Martina Vermathen, Hendrik von Tengg-Kobligk, Martin Nils Hungerbühler, Peter Vermathen and Nico Ruprecht
Molecules 2021, 26(22), 6766; https://doi.org/10.3390/molecules26226766 - 9 Nov 2021
Cited by 7 | Viewed by 2003
Abstract
Cisplatin (cisPt) is an important drug that is used against various cancers, including advanced lung cancer. However, drug resistance is still a major ongoing problem and its investigation is of paramount interest. Here, a high-resolution magic angle spinning (HR-MAS) NMR study is presented [...] Read more.
Cisplatin (cisPt) is an important drug that is used against various cancers, including advanced lung cancer. However, drug resistance is still a major ongoing problem and its investigation is of paramount interest. Here, a high-resolution magic angle spinning (HR-MAS) NMR study is presented deciphering the metabolic profile of non-small cell lung cancer (NSCLC) cells and metabolic adaptations at different levels of induced cisPt-resistance, as well as in their de-induced counterparts (cells cultivated in absence of cisPt). In total, fifty-three metabolites were identified and quantified in the 1H-HR-MAS NMR cell spectra. Metabolic adaptations to cisPt-resistance were detected, which correlated with the degree of resistance. Importantly, de-induced cell lines demonstrated similar metabolic adaptations as the corresponding cisPt-resistant cell lines. Metabolites predominantly changed in cisPt resistant cells and their de-induced counterparts include glutathione and taurine. Characteristic metabolic patterns for cisPt resistance may become relevant as biomarkers in cancer medicine. Full article
(This article belongs to the Special Issue The NMR-Based Metabolomics)
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16 pages, 3106 KiB  
Article
1H-NMR-Based Metabolomics: An Integrated Approach for the Detection of the Adulteration in Chicken, Chevon, Beef and Donkey Meat
by Muhammad Tayyab Akhtar, Muneeba Samar, Anam Amin Shami, Muhammad Waseem Mumtaz, Hamid Mukhtar, Amna Tahir, Syed Shahzad-ul-Hussan, Safee Ullah Chaudhary and Ubedullah Kaka
Molecules 2021, 26(15), 4643; https://doi.org/10.3390/molecules26154643 - 30 Jul 2021
Cited by 17 | Viewed by 4252
Abstract
Meat is a rich source of energy that provides high-value animal protein, fats, vitamins, minerals and trace amounts of carbohydrates. Globally, different types of meats are consumed to fulfill nutritional requirements. However, the increasing burden on the livestock industry has triggered the mixing [...] Read more.
Meat is a rich source of energy that provides high-value animal protein, fats, vitamins, minerals and trace amounts of carbohydrates. Globally, different types of meats are consumed to fulfill nutritional requirements. However, the increasing burden on the livestock industry has triggered the mixing of high-price meat species with low-quality/-price meat. This work aimed to differentiate different meat samples on the basis of metabolites. The metabolic difference between various meat samples was investigated through Nuclear Magnetic Resonance spectroscopy coupled with multivariate data analysis approaches like principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA). In total, 37 metabolites were identified in the gluteal muscle tissues of cow, goat, donkey and chicken using 1H-NMR spectroscopy. PCA was found unable to completely differentiate between meat types, whereas OPLS-DA showed an apparent separation and successfully differentiated samples from all four types of meat. Lactate, creatine, choline, acetate, leucine, isoleucine, valine, formate, carnitine, glutamate, 3-hydroxybutyrate and α-mannose were found as the major discriminating metabolites between white (chicken) and red meat (chevon, beef and donkey). However, inosine, lactate, uracil, carnosine, format, pyruvate, carnitine, creatine and acetate were found responsible for differentiating chevon, beef and donkey meat. The relative quantification of differentiating metabolites was performed using one-way ANOVA and Tukey test. Our results showed that NMR-based metabolomics is a powerful tool for the identification of novel signatures (potential biomarkers) to characterize meats from different sources and could potentially be used for quality control purposes in order to differentiate different meat types. Full article
(This article belongs to the Special Issue The NMR-Based Metabolomics)
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13 pages, 2001 KiB  
Article
The Authentication of Java Turmeric (Curcuma xanthorrhiza) Using Thin Layer Chromatography and 1H-NMR Based-Metabolite Fingerprinting Coupled with Multivariate Analysis
by Abdul Rohman, Theresia Wijayanti, Anjar Windarsih and Sugeng Riyanto
Molecules 2020, 25(17), 3928; https://doi.org/10.3390/molecules25173928 - 27 Aug 2020
Cited by 25 | Viewed by 4356
Abstract
The identification of adulteration practices of medicinal plants used as herbal medicine is very important to ensure the quality, safety, and efficacy. In this study, thin layer chromatography (TLC) and proton nuclear magnetic resonance (1H-NMR)-based metabolite fingerprinting coupled with multivariate analysis [...] Read more.
The identification of adulteration practices of medicinal plants used as herbal medicine is very important to ensure the quality, safety, and efficacy. In this study, thin layer chromatography (TLC) and proton nuclear magnetic resonance (1H-NMR)-based metabolite fingerprinting coupled with multivariate analysis were used for authentication of Curcuma xanthorrhiza extract from Curcuma aeruginosa. Curcumin contents obtained from C. xanthorrhiza extract from various regions were in the range of 0.74%–1.23%. Meanwhile, curcumin contents obtained from C. xanthorrhiza extract adulterated with 0%, 10%, 25%, 40%, 50%, and 75% of C. aeruginosa were 1.02%, 0.96%, 0.86%, 0.69%, 0.43%, and 0.27%, respectively. The decreasing of curcumin contents in adulterant concentrations of 40% and more in C. xanthorrhiza rhizome could indicate the adulteration with other rhizomes. Multivariate analysis of PCA (principal component analysis) using data set obtained from 1H-NMR spectra clearly discriminated pure and adulterated C. xanthorrhiza with C. aeruginosa. OPLS-DA (orthogonal projections to latent structures-discriminant analysis) successfully classified pure and adulterated C. xanthorrhiza with higher R2X (0.965), R2Y (0.958), and Q2(cum) (0.93). It can be concluded that 1H-NMR-based metabolite fingerprinting coupled with PCA and OPLS-DA offers an adequate method to assess adulteration practice and to evaluate the authentication of C. xanthorrhiza extracts. Full article
(This article belongs to the Special Issue The NMR-Based Metabolomics)
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Review

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18 pages, 2599 KiB  
Review
HR-MAS NMR Applications in Plant Metabolomics
by Dieuwertje Augustijn, Huub J. M. de Groot and A. Alia
Molecules 2021, 26(4), 931; https://doi.org/10.3390/molecules26040931 - 10 Feb 2021
Cited by 15 | Viewed by 4835
Abstract
Metabolomics is used to reduce the complexity of plants and to understand the underlying pathways of the plant phenotype. The metabolic profile of plants can be obtained by mass spectrometry or liquid-state NMR. The extraction of metabolites from the sample is necessary for [...] Read more.
Metabolomics is used to reduce the complexity of plants and to understand the underlying pathways of the plant phenotype. The metabolic profile of plants can be obtained by mass spectrometry or liquid-state NMR. The extraction of metabolites from the sample is necessary for both techniques to obtain the metabolic profile. This extraction step can be eliminated by making use of high-resolution magic angle spinning (HR-MAS) NMR. In this review, an HR-MAS NMR-based workflow is described in more detail, including used pulse sequences in metabolomics. The pre-processing steps of one-dimensional HR-MAS NMR spectra are presented, including spectral alignment, baseline correction, bucketing, normalisation and scaling procedures. We also highlight some of the models which can be used to perform multivariate analysis on the HR-MAS NMR spectra. Finally, applications of HR-MAS NMR in plant metabolomics are described and show that HR-MAS NMR is a powerful tool for plant metabolomics studies. Full article
(This article belongs to the Special Issue The NMR-Based Metabolomics)
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Other

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11 pages, 3021 KiB  
Technical Note
A Comparative Study on Processed Panax ginseng Products Using HR-MAS NMR-Based Metabolomics
by Dahye Yoon, Woo Cheol Shin, Young-Seob Lee, Suhkmann Kim, Nam-In Baek and Dae Young Lee
Molecules 2020, 25(6), 1390; https://doi.org/10.3390/molecules25061390 - 18 Mar 2020
Cited by 18 | Viewed by 3199
Abstract
Panax ginseng is processed to diversify efficacy. Four processed ginsengs containing white ginseng (WG), tae-geuk ginseng (TG), red ginseng (RG), and black ginseng (BG) were analyzed using nuclear magnetic resonance (NMR) spectroscopy for screening overall primary metabolites. There were significant differences in the [...] Read more.
Panax ginseng is processed to diversify efficacy. Four processed ginsengs containing white ginseng (WG), tae-geuk ginseng (TG), red ginseng (RG), and black ginseng (BG) were analyzed using nuclear magnetic resonance (NMR) spectroscopy for screening overall primary metabolites. There were significant differences in the sugar content among these four processed ginseng products. WG had a high sucrose content, TG had a high maltose content, and BG had high fructose and glucose content. In the multivariate analyses of NMR spectra, the PCA score plot showed significant discrimination between the four processed ginsengs. For effective clustering, orthogonal partial least squares discriminant analyses (OPLS-DA) with a 1:1 comparison were conducted and all OPLS models were validated using the permutation test, the root mean square error of estimation (RMSEE), and the root mean square error of prediction (RMSEP). All OPLS-DA score plots showed clear separations of processed ginseng products, and sugars such as sucrose and fructose mainly contributed to these separations. Full article
(This article belongs to the Special Issue The NMR-Based Metabolomics)
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