Special Issue "NMR-based Metabolomics and Its Application"
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A special issue of Metabolites (ISSN 2218-1989).
Deadline for manuscript submissions: closed (31 January 2013)
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Special Issue Information
Submission
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed Open Access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 300 CHF (Swiss Francs).
English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.
Published Papers (5 papers)
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Received: 13 November 2012; in revised form: 18 December 2012 / Accepted: 21 January 2013 / Published: 30 January 2013
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Abstract: In the present study, proton NMR-based metabonomics was applied on femoral arterial plasma samples collected from young male subjects (milk protein n = 12 in a crossover design; non-caloric control n = 8) at different time intervals (70, 220, 370 min) after heavy resistance training and intake of either a whey or calcium caseinate protein drink in order to elucidate the impact of the protein source on post-exercise metabolism, which is important for muscle hypertrophy. Dynamic changes in the post-exercise plasma metabolite profile consisted of fluctuations in alanine, beta-hydroxybutyrate, branched amino acids, creatine, glucose, glutamine, glutamate, histidine, lipids and tyrosine. In comparison with the intake of a non-caloric drink, the same pattern of changes in low-molecular weight plasma metabolites was found for both whey and caseinate intake. However, the study indicated that whey and caseinate protein intake had a different impact on low-density and very-low-density lipoproteins present in the blood, which may be ascribed to different effects of the two protein sources on the mobilization of lipid resources during energy deficiency. In conclusion, no difference in the effects on low-molecular weight metabolites as measured by proton NMR-based metabonomics was found between the two protein sources.
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Received: 1 February 2013; in revised form: 22 March 2013 / Accepted: 25 March 2013 / Published: 2 April 2013
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Abstract: Milk is a key component in infant nutrition worldwide and, in the Western parts of the world, also in adult nutrition. Milk of bovine origin is both consumed fresh and processed into a variety of dairy products including cheese, fermented milk products, and infant formula. The nutritional quality and processing capabilities of bovine milk is closely associated to milk composition. Metabolomics is ideal in the study of the low-molecular-weight compounds in milk, and this review focuses on the recent nuclear magnetic resonance (NMR)-based metabolomics trends in milk research, including applications linking the milk metabolite profiling with nutritional aspects, and applications which aim to link the milk metabolite profile to various technological qualities of milk. The metabolite profiling studies encompass the identification of novel metabolites, which potentially can be used as biomarkers or as bioactive compounds. Furthermore, metabolomics applications elucidating how the differential regulated genes affects milk composition are also reported. This review will highlight the recent advances in NMR-based metabolomics on milk, as well as give a brief summary of when NMR spectroscopy can be useful for gaining a better understanding of how milk composition is linked to nutritional or quality traits.
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Received: 19 February 2013; in revised form: 28 March 2013 / Accepted: 1 April 2013 / Published: 9 April 2013
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Abstract: It is consensus in the metabolomics community that standardized protocols should be followed for sample handling, storage and analysis, as it is of utmost importance to maintain constant measurement conditions to identify subtle biological differences. The aim of this work, therefore, was to systematically investigate the influence of freezing procedures and storage temperatures and their effect on NMR spectra as a potentially disturbing aspect for NMR-based metabolomics studies. Urine samples were collected from two healthy volunteers, centrifuged and divided into aliquots. Urine aliquots were frozen either at −20 °C, on dry ice, at −80 °C or in liquid nitrogen and then stored at −20 °C, −80 °C or in liquid nitrogen vapor phase for 1–5 weeks before NMR analysis. Results show spectral changes depending on the freezing procedure, with samples frozen on dry ice showing the largest deviations. The effect was found to be based on pH differences, which were caused by variations in CO2 concentrations introduced by the freezing procedure. Thus, we recommend that urine samples should be frozen at −20 °C and transferred to lower storage temperatures within one week and that freezing procedures should be part of the publication protocol.
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Received: 1 February 2013; in revised form: 29 March 2013 / Accepted: 2 April 2013 / Published: 15 April 2013
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Abstract: One of the most significant challenges in the comparative analysis of Nuclear Magnetic Resonance (NMR) metabolome profiles is the occurrence of shifts between peaks across different spectra, for example caused by fluctuations in pH, temperature, instrument factors and ion content. Proper alignment of spectral peaks is therefore often a crucial preprocessing step prior to downstream quantitative analysis. Various alignment methods have been developed specifically for this purpose. Other methods were originally developed to align other data types (GC, LC, SELDI-MS, etc.), but can also be applied to NMR data. This review discusses the available methods, as well as related problems such as reference determination or the evaluation of alignment quality. We present a generic alignment framework that allows for comparison and classification of different alignment approaches according to their algorithmic principles, and we discuss their performance.
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Received: 8 February 2013; in revised form: 7 May 2013 / Accepted: 10 May 2013 / Published: 17 May 2013
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Abstract: There has been a recent shift in how cancers are defined, where tumors are no longer simply classified by their tissue origin, but also by their molecular characteristics. Furthermore, personalized medicine has become a popular term and it could start to play an important role in future medical care. However, today, a “one size fits all” approach is still the most common form of cancer treatment. In this mini-review paper, we report on the role of nuclear magnetic resonance (NMR) metabolomics in drug development and in personalized medicine. NMR spectroscopy has successfully been used to evaluate current and potential therapies, both single-agents and combination therapies, to analyze toxicology, optimal dose, resistance, sensitivity, and biological mechanisms. It can also provide biological insight on tumor subtypes and their different responses to drugs, and indicate which patients are most likely to experience off-target effects and predict characteristics for treatment efficacy. Identifying pre-treatment metabolic profiles that correlate to these events could significantly improve how we view and treat tumors. We also briefly discuss several targeted cancer drugs that have been studied by metabolomics. We conclude that NMR technology provides a key platform in metabolomics that is well-positioned to play a crucial role in realizing the ultimate goal of better tailored cancer medicine.
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Last update: 12 October 2012
