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Pigsborg K, Stentoft-Larsen V, Demharter S, Aldubayan MA, Trimigno A, Khakimov B, Engelsen SB, Astrup A, Hjorth MF, Dragsted LO, Magkos F. Predicting weight loss success on a new Nordic diet: an untargeted multi-platform metabolomics and machine learning approach. Front Nutr 2023; 10:1191944. [PMID: 37599689 PMCID: PMC10434509 DOI: 10.3389/fnut.2023.1191944] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 07/12/2023] [Indexed: 08/22/2023] Open
Abstract
Background and aim Results from randomized controlled trials indicate that no single diet performs better than other for all people living with obesity. Regardless of the diet plan, there is always large inter-individual variability in weight changes, with some individuals losing weight and some not losing or even gaining weight. This raises the possibility that, for different individuals, the optimal diet for successful weight loss may differ. The current study utilized machine learning to build a predictive model for successful weight loss in subjects with overweight or obesity on a New Nordic Diet (NND). Methods Ninety-one subjects consumed an NND ad libitum for 26 weeks. Based on their weight loss, individuals were classified as responders (weight loss ≥5%, n = 46) or non-responders (weight loss <2%, n = 24). We used clinical baseline data combined with baseline urine and plasma untargeted metabolomics data from two different analytical platforms, resulting in a data set including 2,766 features, and employed symbolic regression (QLattice) to develop a predictive model for weight loss success. Results There were no differences in clinical parameters at baseline between responders and non-responders, except age (47 ± 13 vs. 39 ± 11 years, respectively, p = 0.009). The final predictive model for weight loss contained adipic acid and argininic acid from urine (both metabolites were found at lower levels in responders) and generalized from the training (AUC 0.88) to the test set (AUC 0.81). Responders were also able to maintain a weight loss of 4.3% in a 12 month follow-up period. Conclusion We identified a model containing two metabolites that were able to predict the likelihood of achieving a clinically significant weight loss on an ad libitum NND. This work demonstrates that models based on an untargeted multi-platform metabolomics approach can be used to optimize precision dietary treatment for obesity.
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Affiliation(s)
- Kristina Pigsborg
- Department of Nutrition, Exercise and Sports, University of Copenhagen, Frederiksberg, Denmark
| | | | | | - Mona Adnan Aldubayan
- Department of Nutrition, Exercise and Sports, University of Copenhagen, Frederiksberg, Denmark
- King Saud bin Abdulaziz University for Health Sciences, College of Applied Medical Sciences, Riyadh, Saudi Arabia
| | - Alessia Trimigno
- Department of Food Science, University of Copenhagen, Frederiksberg, Denmark
| | - Bekzod Khakimov
- Department of Food Science, University of Copenhagen, Frederiksberg, Denmark
| | | | - Arne Astrup
- Obesity and Nutritional Sciences, Novo Nordisk Foundation, Hellerup, Denmark
| | - Mads Fiil Hjorth
- Obesity and Nutritional Sciences, Novo Nordisk Foundation, Hellerup, Denmark
| | - Lars Ove Dragsted
- Department of Nutrition, Exercise and Sports, University of Copenhagen, Frederiksberg, Denmark
| | - Faidon Magkos
- Department of Nutrition, Exercise and Sports, University of Copenhagen, Frederiksberg, Denmark
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Trimigno A, Khakimov B, Rasmussen MA, Dragsted LO, Larsen TM, Astrup A, Engelsen SB. Human blood plasma biomarkers of diet and weight loss among centrally obese subjects in a New Nordic Diet intervention. Front Nutr 2023; 10:1198531. [PMID: 37396134 PMCID: PMC10308042 DOI: 10.3389/fnut.2023.1198531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Accepted: 05/15/2023] [Indexed: 07/04/2023] Open
Abstract
Scope The New Nordic Diet (NND) has been shown to promote weight loss and lower blood pressure amongst obese people. This study investigates blood plasma metabolite and lipoprotein biomarkers differentiating subjects who followed Average Danish Diet (ADD) or NND. The study also evaluates how the individual response to the diet is reflected in the metabolic differences between NND subjects who lost or maintained their pre-intervention weight. Methods Centrally obese Danes (BMI >25) followed NND (90 subjects) or ADD (56 subjects) for 6 months. Fasting blood plasma samples, collected at three time-points during the intervention, were screened for metabolites and lipoproteins (LPs) using proton nuclear magnetic resonance spectroscopy. In total, 154 metabolites and 65 lipoproteins were analysed. Results The NND showed a relatively small but significant effect on the plasma metabolome and lipoprotein profiles, with explained variations ranging from 0.6% for lipoproteins to 4.8% for metabolites. A total of 38 metabolites and 11 lipoproteins were found to be affected by the NND. The primary biomarkers differentiating the two diets were found to be HDL-1 cholesterol, apolipoprotein A1, phospholipids, and ketone bodies (3-hydroxybutyric acid, acetone, and acetoacetic acid). The increased levels of ketone bodies detected in the NND group inversely associated with the decrease in diastolic blood pressure of the NND subjects. The study also showed that body weight loss among the NND subjects was weakly associated with plasma levels of citrate. Conclusion The main plasma metabolites associated with NND were acetate, methanol and 3-hydroxybutyrate. The metabolic changes associated with the NND-driven weight loss are mostly pronounced in energy and lipid metabolism.
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Affiliation(s)
- Alessia Trimigno
- Department of Food Science, Faculty of Science, University of Copenhagen, Frederiksberg, Denmark
| | - Bekzod Khakimov
- Department of Food Science, Faculty of Science, University of Copenhagen, Frederiksberg, Denmark
| | - Morten Arendt Rasmussen
- Department of Food Science, Faculty of Science, University of Copenhagen, Frederiksberg, Denmark
- COPSAC (Copenhagen Prospective Studies on Asthma in Childhood), Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Lars Ove Dragsted
- Department of Nutrition Exercise and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark
| | - Thomas Meinert Larsen
- Department of Nutrition Exercise and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark
| | - Arne Astrup
- Department of Nutrition Exercise and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark
| | - Søren Balling Engelsen
- Department of Food Science, Faculty of Science, University of Copenhagen, Frederiksberg, Denmark
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Trimigno A, Khakimov B, Lauge Quaade M, Honoré OL, Clausen T, Blaabjerg K, Balling Engelsen S, Vedsted Hammer AS. Urinary and plasma metabolome of farm mink ( Neovison vison) after an intervention with raw or cooked poultry offal: a 1H NMR investigation. Arch Anim Nutr 2022; 76:74-91. [PMID: 35289194 DOI: 10.1080/1745039x.2021.2003682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
The introduction of high amounts of cooked poultry offal in mink feed has been associated with health problems in growing mink. Cooking mink feed is a convenient way of reducing microbiological activity, but it may have a negative effect on raw material quality and animal welfare. This study investigates growth and health of mink fed raw or cooked poultry offal and describes urinary and blood plasma metabolic changes related to the feeding. A total of 65 male mink were divided in three feeding groups, two fed cooked offal and one group fed raw offal, and the plasma and urine samples were collected at 3 time points during the growth. Both bio-fluids and feed samples were measured by 1H NMR spectroscopy and resulted metabolomics data were analysed using univariate and multivariate statistical methods that revealed dominating effect of the mink growth stages and to a less extent the feeding regime. Metabolome differences in relation to low body mass index (BMI) and kidney lesions were observed in plasma. Disease and decrease in BMI was associated with high creatinine and dimethylglycine content in plasma. These molecules were also particularly indicative of the cooked feeds. Moreover, low urinary taurine levels were also associated with disease and low BMI. Individual mink appeared to show negative effects of the cooked feed diet, including impaired growth and gross pathological lesions involving the kidneys. This may be related to the absorption of essential metabolites such as amino acids and fats, necessary for mink growth, that are negatively impacted by the cooking process.
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Affiliation(s)
- Alessia Trimigno
- Department of Food Science, University of Copenhagen, Frederiksberg, Denmark
| | - Bekzod Khakimov
- Department of Food Science, University of Copenhagen, Frederiksberg, Denmark
| | - Michelle Lauge Quaade
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Oliver Legarth Honoré
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tove Clausen
- Danish Fur Breeders Research Centre, Holstebro, Denmark
| | | | | | - Anne Sofie Vedsted Hammer
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Cui M, Trimigno A, Castro-Mejía JL, Reitelseder S, Bülow J, Bechshøft RL, Nielsen DS, Holm L, Engelsen SB, Khakimov B. Human Fecal Metabolome Reflects Differences in Body Mass Index, Physical Fitness, and Blood Lipoproteins in Healthy Older Adults. Metabolites 2021; 11:717. [PMID: 34822375 PMCID: PMC8620003 DOI: 10.3390/metabo11110717] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 10/12/2021] [Accepted: 10/15/2021] [Indexed: 12/12/2022] Open
Abstract
This study investigated how body mass index (BMI), physical fitness, and blood plasma lipoprotein levels are related to the fecal metabolome in older adults. The fecal metabolome data were acquired using proton nuclear magnetic resonance spectroscopy and gas chromatography-mass spectrometry on 163 healthy older adults (65-80 years old, 80 females and 83 males). Overweight and obese subjects (BMI ≥ 27) showed higher levels of fecal amino acids (AAs) (valine, alanine, and phenylalanine) compared to normal-weight subjects (BMI ≤ 23.5). Adults classified in the high-fitness group displayed slightly lower concentrations of fecal short-chain fatty acids, propionic acid, and AAs (methionine, leucine, glutamic acid, and threonine) compared to the low-fitness group. Subjects with lower levels of cholesterol in low-density lipoprotein particles (LDLchol, ≤2.6 mmol/L) displayed higher fecal levels of valine, glutamic acid, phenylalanine, and lactic acid, while subjects with a higher level of cholesterol in high-density lipoprotein particles (HDLchol, ≥2.1 mmol/L) showed lower fecal concentration of isovaleric acid. The results from this study suggest that the human fecal metabolome, which primarily represents undigested food waste and metabolites produced by the gut microbiome, carries important information about human health and should be closely integrated to other omics data for a better understanding of the role of the gut microbiome and diet on human health and metabolism.
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Affiliation(s)
- Mengni Cui
- Chemometrics and Analytical Technology Section, Department of Food Science University of Copenhagen Rolighedsvej 26, 1958 Frederiksberg C, Denmark; (M.C.); (A.T.)
| | - Alessia Trimigno
- Chemometrics and Analytical Technology Section, Department of Food Science University of Copenhagen Rolighedsvej 26, 1958 Frederiksberg C, Denmark; (M.C.); (A.T.)
| | - Josue L. Castro-Mejía
- Food Microbiology & Fermentation Section, Department of Food Science University of Copenhagen Rolighedsvej 26, 1958 Frederiksberg C, Denmark; (J.L.C.-M.); (D.S.N.)
| | - Søren Reitelseder
- Institute of Sports Medicine, Department of Orthopedic Surgery, Bispebjerg and Frederiksberg Hospital, Nielsine Nielsens Vej 11, 2400 Copenhagen, Denmark; (S.R.); (J.B.); (R.L.B.); (L.H.)
| | - Jacob Bülow
- Institute of Sports Medicine, Department of Orthopedic Surgery, Bispebjerg and Frederiksberg Hospital, Nielsine Nielsens Vej 11, 2400 Copenhagen, Denmark; (S.R.); (J.B.); (R.L.B.); (L.H.)
| | - Rasmus Leidesdorff Bechshøft
- Institute of Sports Medicine, Department of Orthopedic Surgery, Bispebjerg and Frederiksberg Hospital, Nielsine Nielsens Vej 11, 2400 Copenhagen, Denmark; (S.R.); (J.B.); (R.L.B.); (L.H.)
| | - Dennis Sandris Nielsen
- Food Microbiology & Fermentation Section, Department of Food Science University of Copenhagen Rolighedsvej 26, 1958 Frederiksberg C, Denmark; (J.L.C.-M.); (D.S.N.)
| | - Lars Holm
- Institute of Sports Medicine, Department of Orthopedic Surgery, Bispebjerg and Frederiksberg Hospital, Nielsine Nielsens Vej 11, 2400 Copenhagen, Denmark; (S.R.); (J.B.); (R.L.B.); (L.H.)
- School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Søren Balling Engelsen
- Chemometrics and Analytical Technology Section, Department of Food Science University of Copenhagen Rolighedsvej 26, 1958 Frederiksberg C, Denmark; (M.C.); (A.T.)
| | - Bekzod Khakimov
- Chemometrics and Analytical Technology Section, Department of Food Science University of Copenhagen Rolighedsvej 26, 1958 Frederiksberg C, Denmark; (M.C.); (A.T.)
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Cui M, Trimigno A, Aru V, Rasmussen MA, Khakimov B, Engelsen SB. Influence of Age, Sex, and Diet on the Human Fecal Metabolome Investigated by 1H NMR Spectroscopy. J Proteome Res 2021; 20:3642-3653. [PMID: 34048241 DOI: 10.1021/acs.jproteome.1c00220] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
The human fecal metabolome is increasingly studied to explore the impact of diet and lifestyle on health and the gut microbiome. However, systematic differences and confounding factors related to age, sex, and diet remain largely unknown. In this study, absolute concentrations of fecal metabolites from 205 healthy Danes (105 males and 100 females, 49 ± 31 years old) were quantified using 1H NMR spectroscopy and the newly developed SigMa software. The largest systemic variation was found to be highly related to age. Fecal concentrations of short-chain fatty acids (SCFA) were higher in the 18 years old group, while amino acids (AA) were higher in the elderly. Sex-related metabolic differences were weak but significant and mainly related to changes in SCFA. The concentrations of butyric, valeric, propionic, and isovaleric acids were found to be higher in males compared to females. Sex differences were associated with a stronger, possibly masking, effect from differential intake of macronutrients. Dietary fat intake decreased levels of SCFA and AA of both sexes, while carbohydrate intake showed weak correlations with valeric and isovaleric acids in females. This study highlights some possible demographic confounders linked to diet, disease, lifestyle, and microbiota that have to be taken into account when analyzing fecal metabolome data.
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Affiliation(s)
- Mengni Cui
- Chemometrics and Analytical Technology Section Department of Food Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark
| | - Alessia Trimigno
- Chemometrics and Analytical Technology Section Department of Food Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark
| | - Violetta Aru
- Chemometrics and Analytical Technology Section Department of Food Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark
| | - Morten A Rasmussen
- Chemometrics and Analytical Technology Section Department of Food Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark.,COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen 2820, Denmark
| | - Bekzod Khakimov
- Chemometrics and Analytical Technology Section Department of Food Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark
| | - Søren Balling Engelsen
- Chemometrics and Analytical Technology Section Department of Food Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark
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Trimigno A, Bøge Lyndgaard C, Atladóttir GA, Aru V, Balling Engelsen S, Harder Clemmensen LK. An NMR Metabolomics Approach to Investigate Factors Affecting the Yoghurt Fermentation Process and Quality. Metabolites 2020; 10:metabo10070293. [PMID: 32709034 PMCID: PMC7408429 DOI: 10.3390/metabo10070293] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 07/15/2020] [Accepted: 07/16/2020] [Indexed: 11/19/2022] Open
Abstract
A great number of factors can influence milk fermentation for yoghurt production such as fermentation conditions, starter cultures and milk characteristics. It is important for dairy companies to know the best combinations of these parameters for a controlled fermentation and for the desired qualities of yoghurt. This study investigates the use of a 1H-NMR metabolomics approach to monitor the changes in milk during fermentation from time 0 to 24 h, taking samples every hour in the first 8 h and then at the end-point at 24 h. Three different starter cultures (L. delbrueckii ssp. bulgaricus, S. thermophilus and their combination) were used and two different heat treatments (99 or 105 °C) were applied to milk. The results clearly show the breakdown of proteins and lactose as well as the concomitant increase in acetate, lactate and citrate during fermentation. Formate is found at different initial concentrations depending on the heat treatment of the milk and its different time trajectory depends on the starter cultures: Lactobacillus cannot produce formate, but needs it for growth, whilst Streptococcus is able to produce formate from pyruvate, therefore promoting the symbiotic relationship between the two strains. On the other hand, Lactobacillus can hydrolyze milk proteins into amino acids, enriching the quality of the final product. In this way, better insight into the protocooperation of lactic acid bacteria strains and information on the impact of a greater heat treatment in the initial matrix were obtained. The global chemical view on the fermentations provided using NMR is key information for yoghurt producers and companies producing starter cultures.
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Affiliation(s)
- Alessia Trimigno
- Chemometrics and Analytical Technology Section, Department of Food Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark; (A.T.); (V.A.); (S.B.E.)
| | - Christian Bøge Lyndgaard
- DTU COMPUTE, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Richard Petersens Plads, 2800 Kgs. Lyngby, Denmark; (C.B.L.); (G.A.A.)
| | - Guðrún Anna Atladóttir
- DTU COMPUTE, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Richard Petersens Plads, 2800 Kgs. Lyngby, Denmark; (C.B.L.); (G.A.A.)
| | - Violetta Aru
- Chemometrics and Analytical Technology Section, Department of Food Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark; (A.T.); (V.A.); (S.B.E.)
| | - Søren Balling Engelsen
- Chemometrics and Analytical Technology Section, Department of Food Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark; (A.T.); (V.A.); (S.B.E.)
| | - Line Katrine Harder Clemmensen
- DTU COMPUTE, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Richard Petersens Plads, 2800 Kgs. Lyngby, Denmark; (C.B.L.); (G.A.A.)
- Correspondence:
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7
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Cui M, Trimigno A, Aru V, Khakimov B, Engelsen SB. Human Faecal 1H NMR Metabolomics: Evaluation of Solvent and Sample Processing on Coverage and Reproducibility of Signature Metabolites. Anal Chem 2020; 92:9546-9555. [DOI: 10.1021/acs.analchem.0c00606] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Mengni Cui
- Chemometrics and Analytical Technology, Department of Food Science, Faculty of Science, University of Copenhagen Rolighedsvej 26, Frederiksberg 1958, Denmark
| | - Alessia Trimigno
- Chemometrics and Analytical Technology, Department of Food Science, Faculty of Science, University of Copenhagen Rolighedsvej 26, Frederiksberg 1958, Denmark
| | - Violetta Aru
- Chemometrics and Analytical Technology, Department of Food Science, Faculty of Science, University of Copenhagen Rolighedsvej 26, Frederiksberg 1958, Denmark
| | - Bekzod Khakimov
- Chemometrics and Analytical Technology, Department of Food Science, Faculty of Science, University of Copenhagen Rolighedsvej 26, Frederiksberg 1958, Denmark
| | - Søren Balling Engelsen
- Chemometrics and Analytical Technology, Department of Food Science, Faculty of Science, University of Copenhagen Rolighedsvej 26, Frederiksberg 1958, Denmark
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Ciampa A, Dell'Abate MT, Florio A, Tarricone L, Di Gennaro D, Picone G, Trimigno A, Capozzi F, Benedetti A. Combined magnetic resonance imaging and high resolution spectroscopy approaches to study the fertilization effects on metabolome, morphology and yeast community of wine grape berries, cultivar Nero di Troia. Food Chem 2019; 274:831-839. [DOI: 10.1016/j.foodchem.2018.09.056] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Revised: 09/07/2018] [Accepted: 09/10/2018] [Indexed: 01/10/2023]
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Picone G, De Noni I, Ferranti P, Nicolai MA, Alamprese C, Trimigno A, Brodkorb A, Portmann R, Pihlanto A, El SN, Capozzi F. Monitoring molecular composition and digestibility of ripened bresaola through a combined foodomics approach. Food Res Int 2019; 115:360-368. [DOI: 10.1016/j.foodres.2018.11.021] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Revised: 11/08/2018] [Accepted: 11/12/2018] [Indexed: 11/16/2022]
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Ulaszewska MM, Weinert CH, Trimigno A, Portmann R, Andres Lacueva C, Badertscher R, Brennan L, Brunius C, Bub A, Capozzi F, Cialiè Rosso M, Cordero CE, Daniel H, Durand S, Egert B, Ferrario PG, Feskens EJM, Franceschi P, Garcia-Aloy M, Giacomoni F, Giesbertz P, González-Domínguez R, Hanhineva K, Hemeryck LY, Kopka J, Kulling SE, Llorach R, Manach C, Mattivi F, Migné C, Münger LH, Ott B, Picone G, Pimentel G, Pujos-Guillot E, Riccadonna S, Rist MJ, Rombouts C, Rubert J, Skurk T, Sri Harsha PSC, Van Meulebroek L, Vanhaecke L, Vázquez-Fresno R, Wishart D, Vergères G. Nutrimetabolomics: An Integrative Action for Metabolomic Analyses in Human Nutritional Studies. Mol Nutr Food Res 2018; 63:e1800384. [PMID: 30176196 DOI: 10.1002/mnfr.201800384] [Citation(s) in RCA: 141] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Revised: 07/10/2018] [Indexed: 12/13/2022]
Abstract
The life sciences are currently being transformed by an unprecedented wave of developments in molecular analysis, which include important advances in instrumental analysis as well as biocomputing. In light of the central role played by metabolism in nutrition, metabolomics is rapidly being established as a key analytical tool in human nutritional studies. Consequently, an increasing number of nutritionists integrate metabolomics into their study designs. Within this dynamic landscape, the potential of nutritional metabolomics (nutrimetabolomics) to be translated into a science, which can impact on health policies, still needs to be realized. A key element to reach this goal is the ability of the research community to join, to collectively make the best use of the potential offered by nutritional metabolomics. This article, therefore, provides a methodological description of nutritional metabolomics that reflects on the state-of-the-art techniques used in the laboratories of the Food Biomarker Alliance (funded by the European Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL)) as well as points of reflections to harmonize this field. It is not intended to be exhaustive but rather to present a pragmatic guidance on metabolomic methodologies, providing readers with useful "tips and tricks" along the analytical workflow.
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Affiliation(s)
- Marynka M Ulaszewska
- Department of Food Quality and Nutrition, Fondazione Edmund Mach, Research and Innovation Centre, San Michele all'Adige, Italy
| | - Christoph H Weinert
- Department of Safety and Quality of Fruit and Vegetables, Max Rubner-Institut, Karlsruhe, Germany
| | - Alessia Trimigno
- Department of Agricultural and Food Science, University of Bologna, Italy
| | - Reto Portmann
- Method Development and Analytics Research Division, Agroscope, Federal Office for Agriculture, Berne, Switzerland
| | - Cristina Andres Lacueva
- Biomarkers & Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA, Faculty of Pharmacy and Food Sciences, Campus Torribera, University of Barcelona, Barcelona, Spain. CIBER de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Barcelona, Spain
| | - René Badertscher
- Method Development and Analytics Research Division, Agroscope, Federal Office for Agriculture, Berne, Switzerland
| | - Lorraine Brennan
- School of Agriculture and Food Science, Institute of Food and Health, University College Dublin, Dublin, Ireland
| | - Carl Brunius
- Department of Biology and Biological Engineering, Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
| | - Achim Bub
- Department of Physiology and Biochemistry of Nutrition, Max Rubner-Institut, Karlsruhe, Germany
| | - Francesco Capozzi
- Department of Agricultural and Food Science, University of Bologna, Italy
| | - Marta Cialiè Rosso
- Dipartimento di Scienza e Tecnologia del Farmaco Università degli Studi di Torino, Turin, Italy
| | - Chiara E Cordero
- Dipartimento di Scienza e Tecnologia del Farmaco Università degli Studi di Torino, Turin, Italy
| | - Hannelore Daniel
- Nutritional Physiology, Technische Universität München, Freising, Germany
| | - Stéphanie Durand
- Plateforme d'Exploration du Métabolisme, MetaboHUB-Clermont, INRA, Human Nutrition Unit, Université Clermont Auvergne, Clermont-Ferrand, France
| | - Bjoern Egert
- Department of Safety and Quality of Fruit and Vegetables, Max Rubner-Institut, Karlsruhe, Germany
| | - Paola G Ferrario
- Department of Physiology and Biochemistry of Nutrition, Max Rubner-Institut, Karlsruhe, Germany
| | - Edith J M Feskens
- Division of Human Nutrition, Wageningen University, Wageningen, The Netherlands
| | - Pietro Franceschi
- Computational Biology Unit, Fondazione Edmund Mach, Research and Innovation Centre, San Michele all'Adige, Italy
| | - Mar Garcia-Aloy
- Biomarkers & Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA, Faculty of Pharmacy and Food Sciences, Campus Torribera, University of Barcelona, Barcelona, Spain. CIBER de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Barcelona, Spain
| | - Franck Giacomoni
- Plateforme d'Exploration du Métabolisme, MetaboHUB-Clermont, INRA, Human Nutrition Unit, Université Clermont Auvergne, Clermont-Ferrand, France
| | - Pieter Giesbertz
- Molecular Nutrition Unit, Technische Universität München, Freising, Germany
| | - Raúl González-Domínguez
- Biomarkers & Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA, Faculty of Pharmacy and Food Sciences, Campus Torribera, University of Barcelona, Barcelona, Spain. CIBER de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Barcelona, Spain
| | - Kati Hanhineva
- Institute of Public Health and Clinical Nutrition, Department of Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Lieselot Y Hemeryck
- Laboratory of Chemical Analysis, Department of Veterinary Public Health and Food Safety, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Joachim Kopka
- Department of Molecular Physiology, Applied Metabolome Analysis, Max-Planck-Institute of Molecular Plant Physiology, Potsdam-Golm, Germany
| | - Sabine E Kulling
- Department of Safety and Quality of Fruit and Vegetables, Max Rubner-Institut, Karlsruhe, Germany
| | - Rafael Llorach
- Biomarkers & Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA, Faculty of Pharmacy and Food Sciences, Campus Torribera, University of Barcelona, Barcelona, Spain. CIBER de Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Barcelona, Spain
| | - Claudine Manach
- INRA, UMR 1019, Human Nutrition Unit, Université Clermont Auvergne, Clermont-Ferrand, France
| | - Fulvio Mattivi
- Department of Food Quality and Nutrition, Fondazione Edmund Mach, Research and Innovation Centre, San Michele all'Adige, Italy.,Center Agriculture Food Environment, University of Trento, San Michele all'Adige, Italy
| | - Carole Migné
- Plateforme d'Exploration du Métabolisme, MetaboHUB-Clermont, INRA, Human Nutrition Unit, Université Clermont Auvergne, Clermont-Ferrand, France
| | - Linda H Münger
- Food Microbial Systems Research Division, Agroscope, Federal Office for Agriculture, Berne, Switzerland
| | - Beate Ott
- Else Kröner Fresenius Center for Nutritional Medicine, Technical University of Munich, Munich, Germany.,ZIEL Institute for Food and Health, Core Facility Human Studies, Technical University of Munich, Freising, Germany
| | - Gianfranco Picone
- Department of Agricultural and Food Science, University of Bologna, Italy
| | - Grégory Pimentel
- Food Microbial Systems Research Division, Agroscope, Federal Office for Agriculture, Berne, Switzerland
| | - Estelle Pujos-Guillot
- Plateforme d'Exploration du Métabolisme, MetaboHUB-Clermont, INRA, Human Nutrition Unit, Université Clermont Auvergne, Clermont-Ferrand, France
| | - Samantha Riccadonna
- Computational Biology Unit, Fondazione Edmund Mach, Research and Innovation Centre, San Michele all'Adige, Italy
| | - Manuela J Rist
- Department of Physiology and Biochemistry of Nutrition, Max Rubner-Institut, Karlsruhe, Germany
| | - Caroline Rombouts
- Laboratory of Chemical Analysis, Department of Veterinary Public Health and Food Safety, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Josep Rubert
- Department of Food Quality and Nutrition, Fondazione Edmund Mach, Research and Innovation Centre, San Michele all'Adige, Italy
| | - Thomas Skurk
- Else Kröner Fresenius Center for Nutritional Medicine, Technical University of Munich, Munich, Germany.,ZIEL Institute for Food and Health, Core Facility Human Studies, Technical University of Munich, Freising, Germany
| | - Pedapati S C Sri Harsha
- School of Agriculture and Food Science, Institute of Food and Health, University College Dublin, Dublin, Ireland
| | - Lieven Van Meulebroek
- Laboratory of Chemical Analysis, Department of Veterinary Public Health and Food Safety, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Lynn Vanhaecke
- Laboratory of Chemical Analysis, Department of Veterinary Public Health and Food Safety, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Rosa Vázquez-Fresno
- Departments of Biological Sciences and Computing Science, University of Alberta, Edmonton, Canada
| | - David Wishart
- Departments of Biological Sciences and Computing Science, University of Alberta, Edmonton, Canada
| | - Guy Vergères
- Food Microbial Systems Research Division, Agroscope, Federal Office for Agriculture, Berne, Switzerland
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11
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Trimigno A, Khakimov B, Savorani F, Tenori L, Hendrixson V, Čivilis A, Glibetic M, Gurinovic M, Pentikäinen S, Sallinen J, Garduno Diaz S, Pasqui F, Khokhar S, Luchinat C, Bordoni A, Capozzi F, Balling Engelsen S. Investigation of Variations in the Human Urine Metabolome amongst European Populations: An Exploratory Search for Biomarkers of People at Risk-of-Poverty. Mol Nutr Food Res 2018; 63:e1800216. [PMID: 29757492 DOI: 10.1002/mnfr.201800216] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Revised: 04/26/2018] [Indexed: 12/23/2022]
Abstract
SCOPE According to Eurostat 2016, approximately 119 million European citizens live at-risk-of-poverty (ROP). This subpopulation is highly diverse by ethnicity, age, and culture in the different EU states, but they all have in common a low income that could represent an increased risk of nutrient deficiencies due to poor nutritional habits. This study aims to investigate the human urine metabolome in the search of common biomarkers representing dietary deficiencies amongst European populations at ROP. METHODS AND RESULTS 2732 urine samples were collected from 1391 subjects across five different European countries, including the United Kingdom, Finland, Italy, Lithuania, and Serbia, and analyzed using 1 H-NMR spectroscopy. The resulting urine metabolome data were explored according to study design factors including economic status, country, and gender. CONCLUSION Partitioning of the effects derived from the study design factors using ANOVA-simultaneous component analysis (ASCA) revealed that country and gender effects were responsible for most of the systematic variation. The effect of economic status was, as expected, much weaker than country and gender, but more pronounced in Lithuania than in other countries. Citrate and hippurate were among the most powerful ROP biomarkers. The possible relationship between these markers and nutritional deficiencies amongst the ROP population is discussed.
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Affiliation(s)
- Alessia Trimigno
- Chemometrics and Analytical Technology Section, Department of Food Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark
| | - Bekzod Khakimov
- Chemometrics and Analytical Technology Section, Department of Food Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark
| | - Francesco Savorani
- Department of Applied Science and Technology (DISAT), Polytechnic University of Turin, 10129 Torino, Italy
| | - Leonardo Tenori
- Department of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, 50134, Florence, Italy
| | - Vaiva Hendrixson
- Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, LT-03101 Vilnius, Lithuania
| | - Alminas Čivilis
- Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, LT-03101 Vilnius, Lithuania
| | - Marija Glibetic
- Centre of Research Excellence in Nutrition and Metabolism Research, Institute for Medical Research, University of Belgrade, Tadeusa Koscuska 1, P.O. Box 102, 11000 Belgrade, Serbia
| | - Mirjana Gurinovic
- Centre of Research Excellence in Nutrition and Metabolism Research, Institute for Medical Research, University of Belgrade, Tadeusa Koscuska 1, P.O. Box 102, 11000 Belgrade, Serbia
| | - Saara Pentikäinen
- VTT Technical Research Centre of Finland Ltd, P.O. Box 1000, FI-02044 VTT, Finland
| | - Janne Sallinen
- VTT Technical Research Centre of Finland Ltd, P.O. Box 1000, FI-02044 VTT, Finland
| | - Sara Garduno Diaz
- School of Food Science and Nutrition, University of Leeds, Leeds, LS2 9JT, UK
| | - Francesca Pasqui
- Department of Medical and Surgical Sciences, University of Bologna, 40138 Bologna, Italy
| | | | - Claudio Luchinat
- CERM, Center of Magnetic Resonance, University of Florence, Via Luigi Sacconi 6, 50019, Sesto Fiorentino, Florence, Italy
| | - Alessandra Bordoni
- Department of Agricultural and Food Sciences, Alma Mater Studiorum University of Bologna Piazza G. Goidanich, 60 - 47521, Cesena, Italy
| | - Francesco Capozzi
- Department of Agricultural and Food Sciences, Alma Mater Studiorum University of Bologna Piazza G. Goidanich, 60 - 47521, Cesena, Italy
| | - Søren Balling Engelsen
- Chemometrics and Analytical Technology Section, Department of Food Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark
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12
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Vitali F, Lombardo R, Rivero D, Mattivi F, Franceschi P, Bordoni A, Trimigno A, Capozzi F, Felici G, Taglino F, Miglietta F, De Cock N, Lachat C, De Baets B, De Tré G, Pinart M, Nimptsch K, Pischon T, Bouwman J, Cavalieri D. ONS: an ontology for a standardized description of interventions and observational studies in nutrition. Genes Nutr 2018; 13:12. [PMID: 29736190 PMCID: PMC5928560 DOI: 10.1186/s12263-018-0601-y] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Accepted: 04/03/2018] [Indexed: 12/12/2022]
Abstract
Background The multidisciplinary nature of nutrition research is one of its main strengths. At the same time, however, it presents a major obstacle to integrate data analysis, especially for the terminological and semantic interpretations that specific research fields or communities are used to. To date, a proper ontology to structure and formalize the concepts used for the description of nutritional studies is still lacking. Results We have developed the Ontology for Nutritional Studies (ONS) by harmonizing selected pre-existing de facto ontologies with novel health and nutritional terminology classifications. The ONS is the result of a scholarly consensus of 51 research centers in nine European countries. The ontology classes and relations are commonly encountered while conducting, storing, harmonizing, integrating, describing, and searching nutritional studies. The ONS facilitates the description and specification of complex nutritional studies as demonstrated with two application scenarios. Conclusions The ONS is the first systematic effort to provide a solid and extensible formal ontology framework for nutritional studies. Integration of new information can be easily achieved by the addition of extra modules (i.e., nutrigenomics, metabolomics, nutrikinetics, and quality appraisal). The ONS provides a unified and standardized terminology for nutritional studies as a resource for nutrition researchers who might not necessarily be familiar with ontologies and standardization concepts. Electronic supplementary material The online version of this article (10.1186/s12263-018-0601-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Francesco Vitali
- 1Institute of Biometeorology (IBIMET), National Research Council (CNR), Via Giovanni Caproni, 8, 50145 Florence, FI Italy.,4Department of Biology, University of Florence, Via Madonna del Piano, 6, 50019 Sesto F, FI Italy
| | - Rosario Lombardo
- 2The Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI), Piazza Manifattura, 1, I-38068 Rovereto, TN Italy
| | - Damariz Rivero
- 4Department of Biology, University of Florence, Via Madonna del Piano, 6, 50019 Sesto F, FI Italy
| | - Fulvio Mattivi
- 5Food Quality and Nutrition Department, Research and Innovation Centre, Edmund Mach Foundation, Via Edmund Mach, 1, 38010 San Michele all'Adige, TN Italy.,12Center Agriculture Food Environment, University of Trento, San Michele all'Adige, Italy
| | - Pietro Franceschi
- 5Food Quality and Nutrition Department, Research and Innovation Centre, Edmund Mach Foundation, Via Edmund Mach, 1, 38010 San Michele all'Adige, TN Italy
| | - Alessandra Bordoni
- 6Department of Agri-Food Sciences and Technologies, University of Bologna, Piazza Goidanich 60, Cesena, FC Italy
| | - Alessia Trimigno
- 6Department of Agri-Food Sciences and Technologies, University of Bologna, Piazza Goidanich 60, Cesena, FC Italy
| | - Francesco Capozzi
- 6Department of Agri-Food Sciences and Technologies, University of Bologna, Piazza Goidanich 60, Cesena, FC Italy
| | - Giovanni Felici
- 7Institute for Systems Analysis and Computer Science (IASI), National Research Council (CNR), Via dei Taurini, 19, 00185 Rome, RM Italy
| | - Francesco Taglino
- 7Institute for Systems Analysis and Computer Science (IASI), National Research Council (CNR), Via dei Taurini, 19, 00185 Rome, RM Italy
| | - Franco Miglietta
- 1Institute of Biometeorology (IBIMET), National Research Council (CNR), Via Giovanni Caproni, 8, 50145 Florence, FI Italy
| | - Nathalie De Cock
- 3Department of Food Technology, Safety and Health, Ghent University, Coupure links 653, 9000 Ghent, Belgium
| | - Carl Lachat
- 3Department of Food Technology, Safety and Health, Ghent University, Coupure links 653, 9000 Ghent, Belgium
| | - Bernard De Baets
- 8KERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, Coupure links 653, 9000 Ghent, Belgium
| | - Guy De Tré
- 9Department of Telecommunications and Information Processing, Ghent University, Coupure links 653, 9000 Ghent, Belgium
| | - Mariona Pinart
- 10Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Katharina Nimptsch
- 10Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Tobias Pischon
- 10Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Jildau Bouwman
- 11Microbiology and Systems Biology, TNO, Utrechtseweg 48, 3704HE Zeist, The Netherlands
| | - Duccio Cavalieri
- 1Institute of Biometeorology (IBIMET), National Research Council (CNR), Via Giovanni Caproni, 8, 50145 Florence, FI Italy.,4Department of Biology, University of Florence, Via Madonna del Piano, 6, 50019 Sesto F, FI Italy
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13
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Trimigno A, Münger L, Picone G, Freiburghaus C, Pimentel G, Vionnet N, Pralong F, Capozzi F, Badertscher R, Vergères G. GC-MS Based Metabolomics and NMR Spectroscopy Investigation of Food Intake Biomarkers for Milk and Cheese in Serum of Healthy Humans. Metabolites 2018; 8:E26. [PMID: 29570652 PMCID: PMC6027507 DOI: 10.3390/metabo8020026] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Revised: 03/14/2018] [Accepted: 03/20/2018] [Indexed: 02/08/2023] Open
Abstract
The identification and validation of food intake biomarkers (FIBs) in human biofluids is a key objective for the evaluation of dietary intake. We report here the analysis of the GC-MS and 1H-NMR metabolomes of serum samples from a randomized cross-over study in 11 healthy volunteers having consumed isocaloric amounts of milk, cheese, and a soy drink as non-dairy alternative. Serum was collected at baseline, postprandially up to 6 h, and 24 h after consumption. A multivariate analysis of the untargeted serum metabolomes, combined with a targeted analysis of candidate FIBs previously reported in urine samples from the same study, identified galactitol, galactonate, and galactono-1,5-lactone (milk), 3-phenyllactic acid (cheese), and pinitol (soy drink) as candidate FIBs for these products. Serum metabolites not previously identified in the urine samples, e.g., 3-hydroxyisobutyrate after cheese intake, were detected. Finally, an analysis of the postprandial behavior of candidate FIBs, in particular the dairy fatty acids pentadecanoic acid and heptadecanoic acid, revealed specific kinetic patterns of relevance to their detection in future validation studies. Taken together, promising candidate FIBs for dairy intake appear to be lactose and metabolites thereof, for lactose-containing products, and microbial metabolites derived from amino acids, for fermented dairy products such as cheese.
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Affiliation(s)
- Alessia Trimigno
- Department of Agricultural and Food Sciences (DISTAL), University of Bologna, 47521 Cesena, Italy.
| | | | - Gianfranco Picone
- Department of Agricultural and Food Sciences (DISTAL), University of Bologna, 47521 Cesena, Italy.
| | | | | | - Nathalie Vionnet
- Service of Endocrinology, Diabetes and Metabolism, Lausanne University Hospital, 1011 Lausanne 1005, Switzerland.
| | - François Pralong
- Service of Endocrinology, Diabetes and Metabolism, Lausanne University Hospital, 1011 Lausanne 1005, Switzerland.
| | - Francesco Capozzi
- Department of Agricultural and Food Sciences (DISTAL), University of Bologna, 47521 Cesena, Italy.
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14
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Picone G, Zappaterra M, Luise D, Trimigno A, Capozzi F, Motta V, Davoli R, Nanni Costa L, Bosi P, Trevisi P. Metabolomics characterization of colostrum in three sow breeds and its influences on piglets' survival and litter growth rates. J Anim Sci Biotechnol 2018. [PMID: 29527304 PMCID: PMC5840723 DOI: 10.1186/s40104-018-0237-1] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Background Colostrum is the first secretion produced by mammary glands during the hours immediately preceding and succeeding parturition. This secretion differs from milk and represents an essential vehicle of passive immunity, prebiotic compounds and growth factors involved in intestinal development. Most of the literature concerning colostrum composition refers mainly to human and cow; and little is known about pig colostrum metabolome and how it varies between pig breeds and different farrowing parity. Thus, the aim of the present research is to provide new information about pig colostrum composition and the associations between metabolites, the sows’ breed and the survival and growth rates of their litters. Results Colostrum samples were gathered from 58 parturitions of sows belonging to three different breeds chosen for their importance in Italian heavy pig production: 31 Large White, 15 Landrace and 12 Duroc respectively. The defatted and ultrafiltered colostrum samples were analysed using 1H–NMR spectroscopy. Principal Components Analysis (PCA) was assessed on the obtained spectra. In addition, using a Stepwise Regression and a Linear Regression analyses the metabolites named after the signals assignment were tested for their associations with piglets’ performances. Twenty-five metabolites were identified, comprehending monosaccharides, disaccharides (such as lactose), organic acids (lactate, citrate, acetate and formate), nitrogenous organic acids (such as creatine) and other compounds, including nucleotides. PCA results evidence a clustering due to breed and season effects. Lactose was the main compound determining the assignment of the samples into different clusters according to the sow breed. Furthermore, some metabolites showed to be associated with piglets’ performance and survival traits: acetate and taurine were positively related to litter weight gain and piglets’ survival rate, respectively, while dimethylamine and cis-aconitate were linked to new-borns’ impaired ability to survive. Conclusions The results obtained suggest that colostrum composition is affected by breed, which, together with environmental conditions, may cause changes in colostrum metabolites content with possible consequences on piglets’ performances. Among the identified metabolites, acetate, taurine, dimethylamine and cis-aconitate showed consistent associations with piglets’ survival rate and litter weight gain, implying that these compounds may affect new-borns’ ability to survive. Electronic supplementary material The online version of this article (10.1186/s40104-018-0237-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Gianfranco Picone
- Department of Agricultural and Food Sciences (DISTAL), Alma Mater Studiorum - University of Bologna, Viale Fanin 46, 40127 Bologna, Italy
| | - Martina Zappaterra
- Department of Agricultural and Food Sciences (DISTAL), Alma Mater Studiorum - University of Bologna, Viale Fanin 46, 40127 Bologna, Italy
| | - Diana Luise
- Department of Agricultural and Food Sciences (DISTAL), Alma Mater Studiorum - University of Bologna, Viale Fanin 46, 40127 Bologna, Italy
| | - Alessia Trimigno
- Department of Agricultural and Food Sciences (DISTAL), Alma Mater Studiorum - University of Bologna, Viale Fanin 46, 40127 Bologna, Italy
| | - Francesco Capozzi
- Department of Agricultural and Food Sciences (DISTAL), Alma Mater Studiorum - University of Bologna, Viale Fanin 46, 40127 Bologna, Italy
| | - Vincenzo Motta
- Department of Agricultural and Food Sciences (DISTAL), Alma Mater Studiorum - University of Bologna, Viale Fanin 46, 40127 Bologna, Italy
| | - Roberta Davoli
- Department of Agricultural and Food Sciences (DISTAL), Alma Mater Studiorum - University of Bologna, Viale Fanin 46, 40127 Bologna, Italy
| | - Leonardo Nanni Costa
- Department of Agricultural and Food Sciences (DISTAL), Alma Mater Studiorum - University of Bologna, Viale Fanin 46, 40127 Bologna, Italy
| | - Paolo Bosi
- Department of Agricultural and Food Sciences (DISTAL), Alma Mater Studiorum - University of Bologna, Viale Fanin 46, 40127 Bologna, Italy
| | - Paolo Trevisi
- Department of Agricultural and Food Sciences (DISTAL), Alma Mater Studiorum - University of Bologna, Viale Fanin 46, 40127 Bologna, Italy
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15
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Jiang P, Trimigno A, Stanstrup J, Khakimov B, Viereck N, Engelsen SB, Sangild PT, Dragsted LO. Antibiotic Treatment Preventing Necrotising Enterocolitis Alters Urinary and Plasma Metabolomes in Preterm Pigs. J Proteome Res 2017; 16:3547-3557. [PMID: 28871782 DOI: 10.1021/acs.jproteome.7b00263] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Necrotising enterocolitis (NEC) is a serious gut inflammatory condition in premature neonates, onset and development of which depend on the gut microbiome. Attenuation of the gut microbiome by antibiotics can reduce NEC incidence and severity. However, how the antibiotics-suppressed gut microbiome affects the whole-body metabolism in NEC-sensitive premature neonates is unknown. In formula-fed preterm pigs, used as a model for preterm infants, plasma and urinary metabolomes were investigated by LC-MS and 1H NMR, with and without antibiotic treatment immediately after birth. While it reduced the gut microbiome density and NEC lesions as previously reported, the antibiotic treatment employed in the current study affected the abundance of 44 metabolites in different metabolic pathways. In antibiotics-treated pigs, tryptophan metabolism favored the kynurenine pathway, relative to the serotonin pathway, as shown by specific metabolites. Metabolites associated with the gut microbiome, including 3-phenyllactic acid, 4-hydroxyphenylacetic acid, and phenylacetylglycine, all from phenylalanine, and three bile acids showed lower levels in the antibiotics-treated pigs where the gut microbiome was extensively attenuated. Findings in the current study warrant further investigation of metabolic and developmental consequences of antibiotic treatment in preterm neonates.
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Affiliation(s)
| | - Alessia Trimigno
- Department of Agricultural and Food Sciences, University of Bologna , Campus di Scienze degli Alimenti, Cesena, Italy
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16
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Münger LH, Trimigno A, Picone G, Freiburghaus C, Pimentel G, Burton KJ, Pralong FP, Vionnet N, Capozzi F, Badertscher R, Vergères G. Identification of Urinary Food Intake Biomarkers for Milk, Cheese, and Soy-Based Drink by Untargeted GC-MS and NMR in Healthy Humans. J Proteome Res 2017; 16:3321-3335. [PMID: 28753012 DOI: 10.1021/acs.jproteome.7b00319] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
The measurement of food intake biomarkers (FIBs) in biofluids represents an objective tool for dietary assessment. FIBs of milk and cheese still need more investigation due to the absence of candidate markers. Thus, an acute intervention study has been performed to sensitively and specifically identify candidate FIBs. Eleven healthy male and female volunteers participated in the randomized, controlled crossover study that tested a single intake of milk and cheese as test products, and soy-based drink as a control. Urine samples were collected at baseline and up to 24 h at distinct time intervals (0-1, 1-2, 2-4, 4-6, 6-12, and 12-24 h) and were analyzed using an untargeted multiplatform approach (GC-MS and 1H NMR). Lactose, galactose, and galactonate were identified exclusively after milk intake while for other metabolites (allantoin, hippurate, galactitol, and galactono-1,5-lactone) a significant increase has been observed. Urinary 3-phenyllactic acid was the only compound specifically reflecting cheese intake although alanine, proline, and pyroglutamic acid were found at significantly higher levels after cheese consumption. In addition, several novel candidate markers for soy drink were identified, such as pinitol and trigonelline. Together, these candidate FIBs of dairy intake could serve as a basis for future validation studies under free-living conditions.
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Affiliation(s)
- Linda H Münger
- Federal Department of Economic Affairs, Education and Research EAER, Agroscope , Berne, Switzerland
| | - Alessia Trimigno
- Department of Agricultural and Food Sciences (DISTAL), University of Bologna , Cesena, Italy
| | - Gianfranco Picone
- Department of Agricultural and Food Sciences (DISTAL), University of Bologna , Cesena, Italy
| | - Carola Freiburghaus
- Federal Department of Economic Affairs, Education and Research EAER, Agroscope , Berne, Switzerland
| | - Grégory Pimentel
- Federal Department of Economic Affairs, Education and Research EAER, Agroscope , Berne, Switzerland.,Service of Endocrinology, Diabetes and Metabolism, Lausanne University Hospital , 1011 Lausanne, Switzerland
| | - Kathryn J Burton
- Service of Endocrinology, Diabetes and Metabolism, Lausanne University Hospital , 1011 Lausanne, Switzerland
| | - François P Pralong
- Service of Endocrinology, Diabetes and Metabolism, Lausanne University Hospital , 1011 Lausanne, Switzerland
| | - Nathalie Vionnet
- Service of Endocrinology, Diabetes and Metabolism, Lausanne University Hospital , 1011 Lausanne, Switzerland
| | - Francesco Capozzi
- Department of Agricultural and Food Sciences (DISTAL), University of Bologna , Cesena, Italy
| | - René Badertscher
- Federal Department of Economic Affairs, Education and Research EAER, Agroscope , Berne, Switzerland
| | - Guy Vergères
- Federal Department of Economic Affairs, Education and Research EAER, Agroscope , Berne, Switzerland
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17
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Trimigno A, Khakimov B, Mejia JLC, Mikkelsen MS, Kristensen M, Jespersen BM, Engelsen SB. Identification of weak and gender specific effects in a short 3 weeks intervention study using barley and oat mixed linkage β-glucan dietary supplements: a human fecal metabolome study by GC-MS. Metabolomics 2017; 13:108. [PMID: 28867988 PMCID: PMC5562775 DOI: 10.1007/s11306-017-1247-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Accepted: 08/05/2017] [Indexed: 01/17/2023]
Abstract
INTRODUCTION Mixed-linkage (1→3),(1→4)-β-d-glucans (BG) reduce cholesterol level and insulin response in humans. Despite this, their role in human metabolism and a mode of action remains largely unknown. OBJECTIVES To investigate the effects of three structurally different BG on human fecal metabolome in a full cross-over intervention using GC-MS metabolomics. METHODS Over three weeks of intervention, young healthy adults received food supplemented with BG from oat, two different BG from barley or a non-fiber control in a full cross-over design. Untargeted metabolomics and short chain fatty acid analysis was performed on day three fecal samples. ANOVA-simultaneous component analysis was applied to partition the data variation according to the study design, and PLS-DA was used to select most discriminative metabolite markers. RESULTS Univariate and multivariate data analysis revealed a dominating effect of inter-individual variances followed by a gender effect. Weak effects of BG intake were identified including an increased level of gamma-amino-butyrate and palmitoleic acid in males and a decreased level of enterolactone in females. Barley and oat derived BG were found to influence the human fecal metabolome differently. Barley BG increased the relative level of formate in males and isobutyrate, isovalerate, 2-methylbutyrate in females. In total 15, 3 and 11 human fecal metabolites were significantly different between control vs. BG, control vs. oat BG, and barley BG vs. oat BG, respectively. CONCLUSIONS The study show that human fecal metabolome largely reflects individual (∼28% variation) and gender (∼15% variation) differences, whereas the treatment effect of the BG (∼8% variation) only manifests in a few key metabolites (primarily by the metabolites: d-2-aminobutyric acid, palmitoleic acid, linoleic acid and 11-eicosenoic acid).
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Affiliation(s)
- Alessia Trimigno
- 0000 0001 0674 042Xgrid.5254.6Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark
- 0000 0004 1757 1758grid.6292.fDepartment of Agricultural and Food Sciences, Alma Mater Studiorum - University of Bologna, Piazza Goidanich 60, 47521 Cesena (FC), Italy
| | - Bekzod Khakimov
- 0000 0001 0674 042Xgrid.5254.6Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark
| | - Josue Leonardo Castro Mejia
- 0000 0001 0674 042Xgrid.5254.6Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark
| | - Mette Skau Mikkelsen
- 0000 0001 0674 042Xgrid.5254.6Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark
| | - Mette Kristensen
- 0000 0001 0674 042Xgrid.5254.6Department of Nutrition, Exercise, and Sports, Faculty of Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark
| | - Birthe Møller Jespersen
- 0000 0001 0674 042Xgrid.5254.6Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark
| | - Søren Balling Engelsen
- 0000 0001 0674 042Xgrid.5254.6Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Denmark
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Picone G, Trimigno A, Tessarin P, Donnini S, Rombolà AD, Capozzi F. 1 H NMR foodomics reveals that the biodynamic and the organic cultivation managements produce different grape berries ( Vitis vinifera L. cv. Sangiovese). Food Chem 2016; 213:187-195. [DOI: 10.1016/j.foodchem.2016.06.077] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2016] [Revised: 06/05/2016] [Accepted: 06/22/2016] [Indexed: 10/21/2022]
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