Nutritional Metabolomics

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Nutrition and Metabolism".

Deadline for manuscript submissions: closed (15 October 2020) | Viewed by 21673

Special Issue Editors


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Chief Guest Editor
1. Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
2. Biomic_AUTh, Center for Interdisciplinary Research and Innovation (CIRI-AUTH), Balkan Center, 10th km Thessaloniki-Thermi Rd, 57001 Thessaloniki, Greece
Interests: metabonomic/metabolomic analysis for biomarker discovery; bioanalysis and biological mass spectrometry (LC-MS, GC-MS); exploitation of molecular recognition mechanisms in analytical separations (immunoaffinity chromatography, molecular imprinting); novel sample pretreatment techniques (solid phase extraction-microextraction, chromatographic techniques in bioanalysis, pharmaceutical-toxicological analysis)
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Co-Guest Editor
1. Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
2. Biomic_AUTh, Center for Interdisciplinary Research and Innovation (CIRI-AUTH), Balkan Center, 10th km Thessaloniki-Thermi Rd, 57001 Thessaloniki, Greece
Interests: metabolomics based method development; LC-HRMS; GC-MS; targeted metabolomics LC-MS/MS; foodomics; bioanalysis
Special Issues, Collections and Topics in MDPI journals
1. School of Medicine, Aristotle University of Thessaloniki, University Campus, 54124 Thessaloniki, Greece
2. Greece & Biomic_AUTh, Center for Interdisciplinary Research and Innovation (CIRI-AUTH), Balkan Center, 10th km Thessaloniki-Thermi Rd, 57001 Thessaloniki, Greece
Interests: LC-MS/MS; GC-MS and NMR metabolic profiling; biochemical interpretation of metabolomics data; designing and carrying out procedures on rodents
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Nutritional metabolomics, a rapidly emerging field, aims to promote the mechanistic understanding of the impact of diet on the human metabolome. Metabolomics-based studies in nutrition investigate metabolome perturbations induced by specific diets, foods, nutrients, microorganisms, and bioactive compounds using modern, advanced analytical techniques. Nutritional metabolomics could promote the transition from population-based nutritional sciences to personalized nutrition and facilitate the development of knowledge-based intervention approaches.

Regarding to your noticeable contribution to the area, I would like to invite you to submit either a new research or review paper related to nutritional metabolomics on health and disease based on volunteers/patients or animal models for a Special Issue of Metabolites entitled “Nutritional Metabolomics“.

Thank you for your time, considering this invitation.

Prof. Georgios Theodoridis
Dr. Christina Virgiliou
Dr. Olga Deda
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind 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 monthly 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 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • nutritional metabolomics
  • nutrients
  • diet
  • dietary compounds
  • food
  • metabolic profiling
  • nutritional intervention study
  • foodomics

Published Papers (6 papers)

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Research

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22 pages, 1081 KiB  
Article
Identification and Reproducibility of Urinary Metabolomic Biomarkers of Habitual Food Intake in a Cross-Sectional Analysis of the Cancer Prevention Study-3 Diet Assessment Sub-Study
by Ying Wang, Rebecca A. Hodge, Victoria L. Stevens, Terryl J. Hartman and Marjorie L. McCullough
Metabolites 2021, 11(4), 248; https://doi.org/10.3390/metabo11040248 - 17 Apr 2021
Cited by 9 | Viewed by 2075
Abstract
Previous cross-sectional metabolomics studies have identified many potential dietary biomarkers, mostly in blood. Few studies examined urine samples although urine is preferred for dietary biomarker discovery. Furthermore, little is known regarding the reproducibility of urinary metabolomic biomarkers over time. We aimed to identify [...] Read more.
Previous cross-sectional metabolomics studies have identified many potential dietary biomarkers, mostly in blood. Few studies examined urine samples although urine is preferred for dietary biomarker discovery. Furthermore, little is known regarding the reproducibility of urinary metabolomic biomarkers over time. We aimed to identify urinary metabolomic biomarkers of diet and assess their reproducibility over time. We conducted a metabolomics analysis among 648 racially/ethnically diverse men and women in the Diet Assessment Sub-study of the Cancer Prevention Study-3 cohort to examine the correlation between >100 food groups/items [101 by a food frequency questionnaire (FFQ), and 105 by repeated 24 h diet recalls (24HRs)] and 1391 metabolites measured in 24 h urine sample replicates, six months apart. Diet–metabolite associations were examined by Pearson’s partial correlation analysis. Biomarkers were evaluated for prediction accuracy assessed using area under the curve (AUC) calculated from the receiver operating characteristic curve and for reproducibility assessed using intraclass correlation coefficients (ICCs). A total of 1708 diet–metabolite associations were identified after Bonferroni correction for multiple comparisons and restricting correlation coefficients to >0.2 or <−0.2 (1570 associations using the FFQ and 933 using 24HRs), 513 unique metabolites correlated with 79 food groups/items. The median ICCs of the 513 putative biomarkers was 0.53 (interquartile range 0.42–0.62). In this study, with comprehensive dietary data and repeated 24 h urinary metabolic profiles, we identified a large number of diet–metabolite correlations and replicated many found in previous studies. Our findings revealed the promise of urine samples for dietary biomarker discovery in a large cohort study and provide important information on biomarker reproducibility, which could facilitate their utilization in future clinical and epidemiological studies. Full article
(This article belongs to the Special Issue Nutritional Metabolomics)
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15 pages, 1410 KiB  
Article
Discovery of Urinary Biomarkers of Seaweed Intake Using Untargeted LC–MS Metabolomics in a Three-Way Cross-Over Human Study
by Muyao Xi, Lars Ove Dragsted, Mikkel Tullin, Madeleine Ernst, Nazikussabah Zaharudin and Giorgia La Barbera
Metabolites 2021, 11(1), 11; https://doi.org/10.3390/metabo11010011 - 28 Dec 2020
Cited by 4 | Viewed by 3440
Abstract
Seaweeds are a marine source rich in potentially bioactive components, and therefore have attracted attention since the middle of the twentieth century. Accurate and objective assessment of the intake of seaweeds to study their health effects is hampered by a lack of validated [...] Read more.
Seaweeds are a marine source rich in potentially bioactive components, and therefore have attracted attention since the middle of the twentieth century. Accurate and objective assessment of the intake of seaweeds to study their health effects is hampered by a lack of validated intake biomarkers. In this three-armed, randomized, cross-over study, an untargeted metabolomics approach was applied for discovering novel intake biomarkers. Twenty healthy participants (9 men and 11 women) were provided each of three test meals in a randomized order: 5 g of Laminaria digitate (LD), 5 g of Undaria pinnatifida (UP), or a control meal with energy-adjusted pea protein. Four urine samples and a 24 h pooled urine were collected along with blood samples at seven time-points. All samples were profiled by LC-ESI-QTOF-MS and the data were analyzed by univariate analysis and excretion kinetics to select putative intake biomarkers. In total, four intake biomarkers were selected from urine samples. They were identified as hydroxyl-dihydrocoumarin at Level III, loliolid glucuronide at level I, and isololiolid glucuronide at level II, while the last one remains unknown. Further identification and validation of these biomarkers by a cross-sectional study is essential to assess their specificity and robustness. Full article
(This article belongs to the Special Issue Nutritional Metabolomics)
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29 pages, 4128 KiB  
Article
Comparative Analysis of Milk Triglycerides Profile between Jaffarabadi Buffalo and Holstein Friesian Cow
by Aparna Verma, Ningombam Sanjib Meitei, Prakash U. Gajbhiye, Mark J. Raftery and Kiran Ambatipudi
Metabolites 2020, 10(12), 507; https://doi.org/10.3390/metabo10120507 - 11 Dec 2020
Cited by 6 | Viewed by 2691
Abstract
Milk lipids are known for a variety of biological functions, however; little is known about compositional variation across breeds, especially for Jaffarabadi buffalo, an indigenous Indian breed. Systematic profiling of extracted milk lipids was performed by mass spectrometry across summer and winter in [...] Read more.
Milk lipids are known for a variety of biological functions, however; little is known about compositional variation across breeds, especially for Jaffarabadi buffalo, an indigenous Indian breed. Systematic profiling of extracted milk lipids was performed by mass spectrometry across summer and winter in Holstein Friesian cow and Jaffarabadi buffalo. Extensive MS/MS spectral analysis for the identification (ID) of probable lipid species using software followed by manual verification and grading of each assigned lipid species enabled ID based on (a) parent ion, (b) head group, and (c) partial/full acyl characteristic ions for comparative profiling of triacylglycerols between the breeds. Additionally, new triacylglycerol species with short-chain fatty acids were reported by manual interpretation of MS/MS spectra and comparison with curated repositories. Collectively, 1093 triacylglycerol species belonging to 141 unique sum compositions between the replicates of both the animal groups were identified. Relative quantitation at sum composition level followed by statistical analyses revealed changes in relative abundances of triacylglycerol species due to breed, season, and interaction effect of the two. Significant changes in triacylglycerols were observed between breeds (81%) and seasons (59%). When the interaction effect is statistically significant, a higher number of triacylglycerols species in Jaffarabadi has lesser seasonal variation than Holstein Friesian. Full article
(This article belongs to the Special Issue Nutritional Metabolomics)
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17 pages, 770 KiB  
Article
Blood Metabolomic Profiling Confirms and Identifies Biomarkers of Food Intake
by Julia Langenau, Kolade Oluwagbemigun, Christian Brachem, Wolfgang Lieb, Romina di Giuseppe, Anna Artati, Gabi Kastenmüller, Leonie Weinhold, Matthias Schmid and Ute Nöthlings
Metabolites 2020, 10(11), 468; https://doi.org/10.3390/metabo10110468 - 17 Nov 2020
Cited by 12 | Viewed by 2921
Abstract
Metabolomics can be a tool to identify dietary biomarkers. However, reported food-metabolite associations have been inconsistent, and there is a need to explore further associations. Our aims were to confirm previously reported food-metabolite associations and to identify novel food-metabolite associations. We conducted a [...] Read more.
Metabolomics can be a tool to identify dietary biomarkers. However, reported food-metabolite associations have been inconsistent, and there is a need to explore further associations. Our aims were to confirm previously reported food-metabolite associations and to identify novel food-metabolite associations. We conducted a cross-sectional analysis of data from 849 participants (57% men) of the PopGen cohort. Dietary intake was obtained using FFQ and serum metabolites were profiled by an untargeted metabolomics approach. We conducted a systematic literature search to identify previously reported food-metabolite associations and analyzed these associations using linear regression. To identify potential novel food-metabolite associations, datasets were split into training and test datasets and linear regression models were fitted to the training datasets. Significant food-metabolite associations were evaluated in the test datasets. Models were adjusted for covariates. In the literature, we identified 82 food-metabolite associations. Of these, 44 associations were testable in our data and confirmed associations of coffee with 12 metabolites, of fish with five, of chocolate with two, of alcohol with four, and of butter, poultry and wine with one metabolite each. We did not identify novel food-metabolite associations; however, some associations were sex-specific. Potential use of some metabolites as biomarkers should consider sex differences in metabolism. Full article
(This article belongs to the Special Issue Nutritional Metabolomics)
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20 pages, 694 KiB  
Article
Identification and Reproducibility of Plasma Metabolomic Biomarkers of Habitual Food Intake in a US Diet Validation Study
by Ying Wang, Rebecca A. Hodge, Victoria L. Stevens, Terryl J. Hartman and Marjorie L. McCullough
Metabolites 2020, 10(10), 382; https://doi.org/10.3390/metabo10100382 - 26 Sep 2020
Cited by 17 | Viewed by 3088
Abstract
Previous metabolomic studies have identified putative blood biomarkers of dietary intake. These biomarkers need to be replicated in other populations and tested for reproducibility over time for the potential use in future epidemiological studies. We conducted a metabolomics analysis among 671 racially/ethnically diverse [...] Read more.
Previous metabolomic studies have identified putative blood biomarkers of dietary intake. These biomarkers need to be replicated in other populations and tested for reproducibility over time for the potential use in future epidemiological studies. We conducted a metabolomics analysis among 671 racially/ethnically diverse men and women included in a diet validation study to examine the correlation between >100 food groups/items (101 by a food frequency questionnaire (FFQ), 105 by 24-h diet recalls (24HRs)) with 1141 metabolites measured in fasting plasma sample replicates, six months apart. Diet–metabolite associations were examined by Pearson’s partial correlation analysis. Biomarker reproducibility was assessed using intraclass correlation coefficients (ICCs). A total of 677 diet–metabolite associations were identified after Bonferroni adjustment for multiple comparisons and restricting absolute correlation coefficients to greater than 0.2 (601 associations using the FFQ and 395 using 24HRs). The median ICCs of the 238 putative biomarkers was 0.56 (interquartile range 0.46–0.68). In this study, with repeated FFQs, 24HRs and plasma metabolic profiles, we identified several potentially novel food biomarkers and replicated others found in our previous study. Our findings contribute to the growing literature on food-based biomarkers and provide important information on biomarker reproducibility which could facilitate their utilization in future nutritional epidemiological studies. Full article
(This article belongs to the Special Issue Nutritional Metabolomics)
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Review

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25 pages, 1099 KiB  
Review
FoodOmicsGR_RI: A Consortium for Comprehensive Molecular Characterisation of Food Products
by Georgios Theodoridis, Alexandros Pechlivanis, Nikolaos S. Thomaidis, Apostolos Spyros, Constantinos A. Georgiou, Triantafyllos Albanis, Ioannis Skoufos, Stavros Kalogiannis, George Th. Tsangaris, Athanasios S. Stasinakis, Ioannis Konstantinou, Alexander Triantafyllidis, Konstantinos Gkagkavouzis, Anastasia S. Kritikou, Marilena E. Dasenaki, Helen Gika, Christina Virgiliou, Dritan Kodra, Nikolaos Nenadis, Ioannis Sampsonidis, Georgios Arsenos, Maria Halabalaki, Emmanuel Mikros and on behalf of the FoodOmicsGR_RI Consortiumadd Show full author list remove Hide full author list
Metabolites 2021, 11(2), 74; https://doi.org/10.3390/metabo11020074 - 27 Jan 2021
Cited by 15 | Viewed by 6621
Abstract
The national infrastructure FoodOmicsGR_RI coordinates research efforts from eight Greek Universities and Research Centers in a network aiming to support research and development (R&D) in the agri-food sector. The goals of FoodOmicsGR_RI are the comprehensive in-depth characterization of foods using cutting-edge omics technologies [...] Read more.
The national infrastructure FoodOmicsGR_RI coordinates research efforts from eight Greek Universities and Research Centers in a network aiming to support research and development (R&D) in the agri-food sector. The goals of FoodOmicsGR_RI are the comprehensive in-depth characterization of foods using cutting-edge omics technologies and the support of dietary/nutrition studies. The network combines strong omics expertise with expert field/application scientists (food/nutrition sciences, plant protection/plant growth, animal husbandry, apiculture and 10 other fields). Human resources involve more than 60 staff scientists and more than 30 recruits. State-of-the-art technologies and instrumentation is available for the comprehensive mapping of the food composition and available genetic resources, the assessment of the distinct value of foods, and the effect of nutritional intervention on the metabolic profile of biological samples of consumers and animal models. The consortium has the know-how and expertise that covers the breadth of the Greek agri-food sector. Metabolomics teams have developed and implemented a variety of methods for profiling and quantitative analysis. The implementation plan includes the following research axes: development of a detailed database of Greek food constituents; exploitation of “omics” technologies to assess domestic agricultural biodiversity aiding authenticity-traceability control/certification of geographical/genetic origin; highlighting unique characteristics of Greek products with an emphasis on quality, sustainability and food safety; assessment of diet’s effect on health and well-being; creating added value from agri-food waste. FoodOmicsGR_RI develops new tools to evaluate the nutritional value of Greek foods, study the role of traditional foods and Greek functional foods in the prevention of chronic diseases and support health claims of Greek traditional products. FoodOmicsGR_RI provides access to state-of-the-art facilities, unique, well-characterised sample sets, obtained from precision/experimental farming/breeding (milk, honey, meat, olive oil and so forth) along with more than 20 complementary scientific disciplines. FoodOmicsGR_RI is open for collaboration with national and international stakeholders. Full article
(This article belongs to the Special Issue Nutritional Metabolomics)
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