Special Issue "Challenging Biochemical Complexities by NMR"

A special issue of Metabolites (ISSN 2218-1989).

Deadline for manuscript submissions: closed (31 August 2016).

Special Issue Editor

Guest Editor
Dr. Jun Kikuchi

Environmental Metabolic Analysis Research Team, RIKEN Center for Sustainable Resource Science, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 235-0045, Japan
Website | E-Mail
Interests: Biology and Biochemistry; Microbiology; Environment and Ecology; Geosciences

Special Issue Information

Dear Colleagues,

Nuclear Magnetic Resonance (NMR) has strong advantages for the structure determination of metabolites, therefore, it has been used significantly in chemical analysis, namely with purified natural products. However, NMR has also great potential to analyze un-purified, biochemical mixtures, including in situ/in vivo sample systems. With this feature, NMR has also been contributed to metabolomics/metabonomics studies, also applied for macromolecular mixtures, including foods and biomass. Recent technical advances for signal separation of crowded regions, using high-field magnets, allow more accurate analysis of biochemical mixtures. Furthermore, the hardware development of low-field magnets also has potential to open a new avenue for on-site analysis of agricultural/industrial products, as well as human samples, without performing laboratory sample preparation.

This Special Issue of Metabolites will be focused on cutting-edge technologies for sampling, measurements, and analysis, both from a fundamental, as well as an applied point of view. The topics that shall be covered by this Special Issue include recent developments of hardware or related apparatus including benchtop NMR. The sample preparation method is also a key feature to be covered, as well as efficient extraction, concentration of dilute sample system, stable isotope labeling, and in situ/in vivo measurements. Therefore, sample systems can also be widely covered, not only laboratory-made biochemical extracts, but also in agriculture, forestry, and fishery products, such as foods, woods, and their process monitoring, environmental complexity, such as plants, animals, unculturable microbiota, as well as geochemical samples, human related samples, biochemically degradable system such as historical heritage. The inter-convertibility of NMR data among different institutions is also a distinct advantage for the NMR-based approach, therefore, database construction of obtained large amounts of biological data and its computation, as well as chemoinformatics, are also important issues. Manuscripts dealing with other challenging issues in the field of biochemical mixture analysis are also highly welcome.

Dr. Jun Kikuchi
Guest Editor

Relevant Special Issue can be found here: https://www.mdpi.com/journal/metabolites/special_issues/NMR.

Manuscript Submission Information

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Keywords

  • agriculture, forestry and fishery
  • large amounts of biological data and its computation
  • chemoinformatics
  • diffusion and mobility-based separation
  • environmental complexity
  • geochemistry
  • historical heritage
  • human health
  • industrial process
  • inorganic mixtures
  • instrumentation
  • isotope labeling
  • macromolecular mixtures
  • metabolite mixtures
  • sampling technique
  • signal deconvolution

Published Papers (6 papers)

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Research

Open AccessArticle
NMR-Based Metabolic Profiling of Field-Grown Leaves from Sugar Beet Plants Harbouring Different Levels of Resistance to Cercospora Leaf Spot Disease
Metabolites 2017, 7(1), 4; https://doi.org/10.3390/metabo7010004
Received: 31 August 2016 / Revised: 17 January 2017 / Accepted: 23 January 2017 / Published: 26 January 2017
Cited by 7 | PDF Full-text (2235 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Cercospora leaf spot (CLS) is one of the most serious leaf diseases for sugar beet (Beta vulgaris L.) worldwide. The breeding of sugar beet cultivars with both high CLS resistance and high yield is a major challenge for breeders. In this study, [...] Read more.
Cercospora leaf spot (CLS) is one of the most serious leaf diseases for sugar beet (Beta vulgaris L.) worldwide. The breeding of sugar beet cultivars with both high CLS resistance and high yield is a major challenge for breeders. In this study, we report the nuclear magnetic resonance (NMR)-based metabolic profiling of field-grown leaves for a subset of sugar beet genotypes harbouring different levels of CLS resistance. Leaves were collected from 12 sugar beet genotypes at four time points: seedling, early growth, root enlargement, and disease development stages. 1H-NMR spectra of foliar metabolites soluble in a deuterium-oxide (D2O)-based buffer were acquired and subjected to multivariate analyses. A principal component analysis (PCA) of the NMR data from the sugar beet leaves shows clear differences among the growth stages. At the later time points, the sugar and glycine betaine contents were increased, whereas the choline content was decreased. The relationship between the foliar metabolite profiles and resistance level to CLS was examined by combining partial least squares projection to latent structure (PLS) or orthogonal PLS (OPLS) analysis and univariate analyses. It was difficult to build a robust model for predicting precisely the disease severity indices (DSIs) of each genotype; however, GABA and Gln differentiated susceptible genotypes (genotypes with weak resistance) from resistant genotypes (genotypes with resistance greater than a moderate level) before inoculation tests. The results suggested that breeders might exclude susceptible genotypes from breeding programs based on foliar metabolites profiled without inoculation tests, which require an enormous amount of time and effort. Full article
(This article belongs to the Special Issue Challenging Biochemical Complexities by NMR)
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Open AccessArticle
FoodPro: A Web-Based Tool for Evaluating Covariance and Correlation NMR Spectra Associated with Food Processes
Metabolites 2016, 6(4), 36; https://doi.org/10.3390/metabo6040036
Received: 25 August 2016 / Revised: 7 October 2016 / Accepted: 17 October 2016 / Published: 19 October 2016
Cited by 3 | PDF Full-text (1850 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Foods from agriculture and fishery products are processed using various technologies. Molecular mixture analysis during food processing has the potential to help us understand the molecular mechanisms involved, thus enabling better cooking of the analyzed foods. To date, there has been no web-based [...] Read more.
Foods from agriculture and fishery products are processed using various technologies. Molecular mixture analysis during food processing has the potential to help us understand the molecular mechanisms involved, thus enabling better cooking of the analyzed foods. To date, there has been no web-based tool focusing on accumulating Nuclear Magnetic Resonance (NMR) spectra from various types of food processing. Therefore, we have developed a novel web-based tool, FoodPro, that includes a food NMR spectrum database and computes covariance and correlation spectra to tasting and hardness. As a result, FoodPro has accumulated 236 aqueous (extracted in D2O) and 131 hydrophobic (extracted in CDCl3) experimental bench-top 60-MHz NMR spectra, 1753 tastings scored by volunteers, and 139 hardness measurements recorded by a penetrometer, all placed into a core database. The database content was roughly classified into fish and vegetable groups from the viewpoint of different spectrum patterns. FoodPro can query a user food NMR spectrum, search similar NMR spectra with a specified similarity threshold, and then compute estimated tasting and hardness, covariance, and correlation spectra to tasting and hardness. Querying fish spectra exemplified specific covariance spectra to tasting and hardness, giving positive covariance for tasting at 1.31 ppm for lactate and 3.47 ppm for glucose and a positive covariance for hardness at 3.26 ppm for trimethylamine N-oxide. Full article
(This article belongs to the Special Issue Challenging Biochemical Complexities by NMR)
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Open AccessArticle
Untargeted NMR Spectroscopic Analysis of the Metabolic Variety of New Apple Cultivars
Metabolites 2016, 6(3), 29; https://doi.org/10.3390/metabo6030029
Received: 31 May 2016 / Revised: 9 September 2016 / Accepted: 13 September 2016 / Published: 19 September 2016
Cited by 8 | PDF Full-text (2802 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Metabolome analyses by NMR spectroscopy can be used in quality control by generating unique fingerprints of different species. Hundreds of components and their variation between different samples can be analyzed in a few minutes/hours with high accuracy and low cost of sample preparation. [...] Read more.
Metabolome analyses by NMR spectroscopy can be used in quality control by generating unique fingerprints of different species. Hundreds of components and their variation between different samples can be analyzed in a few minutes/hours with high accuracy and low cost of sample preparation. Here, apple peel and pulp extracts of a variety of apple cultivars were studied to assess their suitability to discriminate between the different varieties. The cultivars comprised mainly newly bred varieties or ones that were brought onto the market in recent years. Multivariate analyses of peel and pulp extracts were able to unambiguously identify all cultivars, with peel extracts showing a higher discriminative power. The latter was increased if the highly concentrated sugar metabolites were omitted from the analysis. Whereas sugar concentrations lay within a narrow range, polyphenols, discussed as potential health promoting substances, and acids varied remarkably between the cultivars. Full article
(This article belongs to the Special Issue Challenging Biochemical Complexities by NMR)
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Open AccessArticle
NMR Chemical Shift Ranges of Urine Metabolites in Various Organic Solvents
Metabolites 2016, 6(3), 27; https://doi.org/10.3390/metabo6030027
Received: 10 June 2016 / Revised: 28 July 2016 / Accepted: 27 August 2016 / Published: 2 September 2016
PDF Full-text (1606 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Signal stability is essential for reliable multivariate data analysis. Urine samples show strong variance in signal positions due to inter patient differences. Here we study the exchange of the solvent of a defined urine matrix and how it affects signal and integral stability [...] Read more.
Signal stability is essential for reliable multivariate data analysis. Urine samples show strong variance in signal positions due to inter patient differences. Here we study the exchange of the solvent of a defined urine matrix and how it affects signal and integral stability of the urinary metabolites by NMR spectroscopy. The exchange solvents were methanol, acetonitrile, dimethyl sulfoxide, chloroform, acetone, dichloromethane, and dimethyl formamide. Some of these solvents showed promising results with a single batch of urine. To evaluate further differences between urine samples, various acid, base, and salt solutions were added in a defined way mimicking to some extent inter human differences. Corresponding chemical shift changes were monitored. Full article
(This article belongs to the Special Issue Challenging Biochemical Complexities by NMR)
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Open AccessArticle
Deciphering the Duality of Clock and Growth Metabolism in a Cell Autonomous System Using NMR Profiling of the Secretome
Metabolites 2016, 6(3), 23; https://doi.org/10.3390/metabo6030023
Received: 28 June 2016 / Revised: 18 July 2016 / Accepted: 19 July 2016 / Published: 27 July 2016
Cited by 5 | PDF Full-text (1794 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Oscillations in circadian metabolism are crucial to the well being of organism. Our understanding of metabolic rhythms has been greatly enhanced by recent advances in high-throughput systems biology experimental techniques and data analysis. In an in vitro setting, metabolite rhythms can be measured [...] Read more.
Oscillations in circadian metabolism are crucial to the well being of organism. Our understanding of metabolic rhythms has been greatly enhanced by recent advances in high-throughput systems biology experimental techniques and data analysis. In an in vitro setting, metabolite rhythms can be measured by time-dependent sampling over an experimental period spanning one or more days at sufficent resolution to elucidate rhythms. We hypothesized that cellular metabolic effects over such a time course would be influenced by both oscillatory and circadian-independent cell metabolic effects. Here we use nuclear magnetic resonance (NMR) spectroscopy-based metabolic profiling of mammalian cell culture media of synchronized U2 OS cells containing an intact transcriptional clock. The experiment was conducted over 48 h, typical for circadian biology studies, and samples collected at 2 h resolution to unravel such non-oscillatory effects. Our data suggest specific metabolic activities exist that change continuously over time in this settting and we demonstrate that the non-oscillatory effects are generally monotonic and possible to model with multivariate regression. Deconvolution of such non-circadian persistent changes are of paramount importance to consider while studying circadian metabolic oscillations. Full article
(This article belongs to the Special Issue Challenging Biochemical Complexities by NMR)
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Graphical abstract

Open AccessArticle
Complex Mixture Analysis of Organic Compounds in Yogurt by NMR Spectroscopy
Metabolites 2016, 6(2), 19; https://doi.org/10.3390/metabo6020019
Received: 26 April 2016 / Revised: 8 June 2016 / Accepted: 13 June 2016 / Published: 16 June 2016
Cited by 5 | PDF Full-text (1562 KB) | HTML Full-text | XML Full-text
Abstract
NMR measurements do not require separation and chemical modification of samples and therefore rapidly and directly provide non-targeted information on chemical components in complex mixtures. In this study, one-dimensional (1H, 13C, and 31P) and two-dimensional (1H-13 [...] Read more.
NMR measurements do not require separation and chemical modification of samples and therefore rapidly and directly provide non-targeted information on chemical components in complex mixtures. In this study, one-dimensional (1H, 13C, and 31P) and two-dimensional (1H-13C and 1H-31P) NMR spectroscopy were conducted to analyze yogurt without any pretreatment. 1H, 13C, and 31P NMR signals were assigned to 10 types of compounds. The signals of α/β-lactose and α/β-galactose were separately observed in the 1H NMR spectra. In addition, the signals from the acyl chains of milk fats were also successfully identified but overlapped with many other signals. Quantitative difference spectra were obtained by subtracting the diffusion ordered spectroscopy (DOSY) spectra from the quantitative 1H NMR spectra. This method allowed us to eliminate interference on the overlaps; therefore, the correct intensities of signals overlapped with those from the acyl chains of milk fat could be determined directly without separation. Moreover, the 1H-31P HMBC spectra revealed for the first time that N-acetyl-d-glucosamine-1-phosphate is contained in yogurt. Full article
(This article belongs to the Special Issue Challenging Biochemical Complexities by NMR)
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