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Zwierzchowski G, Haxhiaj K, Wójcik R, Wishart DS, Ametaj BN. Identifying Predictive Biomarkers of Subclinical Mastitis in Dairy Cows through Urinary Metabotyping. Metabolites 2024; 14:205. [PMID: 38668333 PMCID: PMC11051925 DOI: 10.3390/metabo14040205] [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] [Received: 02/26/2024] [Revised: 03/22/2024] [Accepted: 03/30/2024] [Indexed: 04/28/2024] Open
Abstract
Mastitis is a significant infectious disease in dairy cows, resulting in milk yield loss and culling. Early detection of mastitis-prone cows is crucial for implementing effective preventive measures before disease onset. Current diagnosis of subclinical mastitis (SCM) relies on somatic cell count assessment post-calving, lacking predictive capabilities. This study aimed to identify metabolic changes in pre-SCM cows through targeted metabolomic analysis of urine samples collected 8 wks and 4 wks before calving, using mass spectrometry. A nested case-control design was employed, involving a total of 145 multiparous dairy cows, with disease occurrence monitored pre- and postpartum. Among them, 15 disease-free cows served as healthy controls (CON), while 10 cows exclusively had SCM, excluding those with additional diseases. Urinary metabolite profiling revealed multiple alterations in acylcarnitines, amino acids, and organic acids in pre-SCM cows. Metabotyping identified 27 metabolites that distinguished pre-SCM cows from healthy CON cows at both 8 and 4 wks before parturition. However, only four metabolites per week showed significant alterations (p < 0.005). Notably, a panel of four serum metabolites (asymmetric dimethylarginine, proline, leucine, and homovanillate) at 8 wks prepartum, and another panel (asymmetric dimethylarginine, methylmalonate, citrate, and spermidine) at 4 wks prepartum, demonstrated predictive ability as urinary biomarkers for SCM risk (AUC = 0.88; p = 0.02 and AUC = 0.88; p = 0.03, respectively). In conclusion, our findings indicate that metabolite testing can identify cows at risk of SCM as early as 8 and 4 wks before parturition. Validation of the two identified metabolite panels is warranted to implement these predictive biomarkers, facilitate early intervention strategies, and improve dairy cow management to mitigate the impact of SCM. Further research is needed to confirm the efficacy and applicability of these biomarkers in practical farm settings.
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Affiliation(s)
- Grzegorz Zwierzchowski
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada; (G.Z.); (K.H.)
- Faculty of Biology and Biotechnology, University of Warmia and Mazury, 1a Oczapowskiego Str., 10-719 Olsztyn, Poland
| | - Klevis Haxhiaj
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada; (G.Z.); (K.H.)
| | - Roman Wójcik
- Faculty of Veterinary Medicine, University of Warmia and Mazury, 1a Oczapowskiego Str., 10-719 Olsztyn, Poland;
| | - David S. Wishart
- Department of Biological and Computer Sciences, University of Alberta, Edmonton, AB T6G 2P5, Canada;
| | - Burim N. Ametaj
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada; (G.Z.); (K.H.)
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Kamrath C, Friedrich C, Hartmann MF, Wudy SA. Metabotypes of Congenital Adrenal Hyperplasia in Infants determined by Gas Chromatography-Mass Spectrometry in Spot Urine. J Steroid Biochem Mol Biol 2023; 231:106304. [PMID: 36990162 DOI: 10.1016/j.jsbmb.2023.106304] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 03/14/2023] [Accepted: 03/26/2023] [Indexed: 03/30/2023]
Abstract
Biochemical monitoring of treatment in infants with classic congenital adrenal hyperplasia (CAH) is not yet well defined. The aim of this study was to perform a cluster analysis of the urinary steroid metabolome for treatment monitoring of infants with classic salt-wasting CAH. We analysed spot urine samples obtained from 60 young children ≤ 4 years of age (29 females) with classic CAH due to 21-hydroxylase deficiency treated with hydrocortisone and fludrocortisone by targeted gas chromatography-mass spectrometry (GC-MS). Patients were classified into different groups according to their metabolic patterns (metabotypes) using unsupervised k-means clustering algorithms. Three metabotypes could be discovered. Metabotype #1 (N=15 (25%)) showed high concentrations of androgen and 17-hydroxyprogesterone (17OHP) precursor steroids, metabotype #2 (N=28 (47%)) revealed balanced metabolic control, and metabotype #3 (N=17; 28%) demonstrated severe adrenal suppression with low concentrations of androgen and 17OHP precursor steroids. Daily hydrocortisone doses and urinary concentrations of cortisol and cortisone metabolites did not differ between all three metabotypes. Metabotype #2 had highest daily dose of fludrocortisone (p=0.006). Receiver operating characteristic curve analysis showed that 11-ketopregnanetriol (area under the curve [AUC] 0.967) and pregnanetriol (AUC 0.936) were most suitable of separating metabotype #1 from #2. For separation between metabotypes #2 vs. #3, the 11-oxygenated androgen metabolite 11-hydroxyandrosterone (AUC 0.983) and the ratio of 11-hydroxyandrosterone to tetrahydrocortisone (AUC 0.970) were most suitable. In conclusion, GC-MS-based urinary steroid metabotyping is a new method to help monitor the treatment of infants with CAH. This method allows classification of under-, over- and adequately treated young children.
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Affiliation(s)
- Clemens Kamrath
- Division of Pediatric Endocrinology & Diabetology, Center of Child and Adolescent Medicine, Justus Liebig University, Giessen, Germany
| | - Clemens Friedrich
- Division of Pediatric Endocrinology & Diabetology, Center of Child and Adolescent Medicine, Justus Liebig University, Giessen, Germany
| | - Michaela F Hartmann
- Division of Pediatric Endocrinology & Diabetology, Center of Child and Adolescent Medicine, Justus Liebig University, Giessen, Germany
| | - Stefan A Wudy
- Division of Pediatric Endocrinology & Diabetology, Center of Child and Adolescent Medicine, Justus Liebig University, Giessen, Germany.
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Trouwborst I, Gijbels A, Jardon KM, Siebelink E, Hul GB, Wanders L, Erdos B, Péter S, Singh-Povel CM, de Vogel-van den Bosch J, Adriaens ME, Arts ICW, Thijssen DHJ, Feskens EJM, Goossens GH, Afman LA, Blaak EE. Cardiometabolic health improvements upon dietary intervention are driven by tissue-specific insulin resistance phenotype: A precision nutrition trial. Cell Metab 2023; 35:71-83.e5. [PMID: 36599304 DOI: 10.1016/j.cmet.2022.12.002] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 10/12/2022] [Accepted: 11/13/2022] [Indexed: 01/05/2023]
Abstract
Precision nutrition based on metabolic phenotype may increase the effectiveness of interventions. In this proof-of-concept study, we investigated the effect of modulating dietary macronutrient composition according to muscle insulin-resistant (MIR) or liver insulin-resistant (LIR) phenotypes on cardiometabolic health. Women and men with MIR or LIR (n = 242, body mass index [BMI] 25-40 kg/m2, 40-75 years) were randomized to phenotype diet (PhenoDiet) group A or B and followed a 12-week high-monounsaturated fatty acid (HMUFA) diet or low-fat, high-protein, and high-fiber diet (LFHP) (PhenoDiet group A, MIR/HMUFA and LIR/LFHP; PhenoDiet group B, MIR/LFHP and LIR/HMUFA). PhenoDiet group B showed no significant improvements in the primary outcome disposition index, but greater improvements in insulin sensitivity, glucose homeostasis, serum triacylglycerol, and C-reactive protein compared with PhenoDiet group A were observed. We demonstrate that modulating macronutrient composition within the dietary guidelines based on tissue-specific insulin resistance (IR) phenotype enhances cardiometabolic health improvements. Clinicaltrials.gov registration: NCT03708419, CCMO registration NL63768.068.17.
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Affiliation(s)
- Inez Trouwborst
- Department of Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Center, Maastricht, the Netherlands; TI Food and Nutrition (TIFN), Wageningen, the Netherlands
| | - Anouk Gijbels
- TI Food and Nutrition (TIFN), Wageningen, the Netherlands; Division of Human Nutrition and Health, Wageningen University, Wageningen, the Netherlands
| | - Kelly M Jardon
- Department of Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Center, Maastricht, the Netherlands; TI Food and Nutrition (TIFN), Wageningen, the Netherlands
| | - Els Siebelink
- Division of Human Nutrition and Health, Wageningen University, Wageningen, the Netherlands
| | - Gabby B Hul
- Department of Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Center, Maastricht, the Netherlands; TI Food and Nutrition (TIFN), Wageningen, the Netherlands
| | - Lisa Wanders
- TI Food and Nutrition (TIFN), Wageningen, the Netherlands; Radboud Institute for Health Sciences, Department of Physiology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Balázs Erdos
- TI Food and Nutrition (TIFN), Wageningen, the Netherlands; Maastricht Centre for Systems Biology, Maastricht University, Maastricht, the Netherlands
| | | | | | | | - Michiel E Adriaens
- TI Food and Nutrition (TIFN), Wageningen, the Netherlands; Maastricht Centre for Systems Biology, Maastricht University, Maastricht, the Netherlands
| | - Ilja C W Arts
- TI Food and Nutrition (TIFN), Wageningen, the Netherlands; Maastricht Centre for Systems Biology, Maastricht University, Maastricht, the Netherlands
| | - Dick H J Thijssen
- Radboud Institute for Health Sciences, Department of Physiology, Radboud University Medical Center, Nijmegen, the Netherlands; Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK
| | - Edith J M Feskens
- Division of Human Nutrition and Health, Wageningen University, Wageningen, the Netherlands
| | - Gijs H Goossens
- Department of Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Lydia A Afman
- TI Food and Nutrition (TIFN), Wageningen, the Netherlands; Division of Human Nutrition and Health, Wageningen University, Wageningen, the Netherlands
| | - Ellen E Blaak
- Department of Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Center, Maastricht, the Netherlands; TI Food and Nutrition (TIFN), Wageningen, the Netherlands.
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Costa CP, Bezerra AR, Almeida A, Rocha SM. Candida Species (Volatile) Metabotyping through Advanced Comprehensive Two-Dimensional Gas Chromatography. Microorganisms 2020; 8:E1911. [PMID: 33266330 PMCID: PMC7760324 DOI: 10.3390/microorganisms8121911] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [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: 11/05/2020] [Revised: 11/28/2020] [Accepted: 11/29/2020] [Indexed: 01/04/2023] Open
Abstract
Microbial metabolomics is a challenge strategy that allows a comprehensive analysis of metabolites within a microorganism and may support a new approach in microbial research, including the microbial diagnosis. Thus, the aim of this research was to in-depth explore a metabolomics strategy based on the use of an advanced multidimensional gas chromatography for the comprehensive mapping of cellular metabolites of C. albicans and non-C. albicans (C. glabrata and C. tropicalis) and therefore contributing for the development of a comprehensive platform for fungal detection management and for species distinction in early growth times (6 h). The volatile fraction comprises 126 putatively identified metabolites distributed over several chemical families: acids, alcohols, aldehydes, hydrocarbons, esters, ketones, monoterpenic and sesquiterpenic compounds, norisoprenoids, phenols and sulphur compounds. These metabolites may be related with different metabolic pathways, such as amino acid metabolism and biosynthesis, fatty acids metabolism, aromatic compounds degradation, mono and sesquiterpenoid synthesis and carotenoid cleavage. These results represent an enlargement of ca. 70% of metabolites not previously reported for C. albicans, 91% for C. glabrata and 90% for C. tropicalis. This study represents the most detailed study about Candida species exometabolome, allowing a metabolomic signature of each species, which signifies an improvement towards the construction of a Candida metabolomics platform whose application in clinical diagnostics can be crucial to guide therapeutic interventions.
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Affiliation(s)
- Carina Pedrosa Costa
- Department of Chemistry & LAQV-REQUIMTE, University of Aveiro, Campus Universitário Santiago, 3810-193 Aveiro, Portugal;
| | - Ana Rita Bezerra
- Health Sciences Department, Institute for Biomedicine—iBiMED, University of Aveiro, Campus Universitário Santiago, 3810-193 Aveiro, Portugal;
| | - Adelaide Almeida
- Department of Biology & CESAM, University of Aveiro, Campus Universitário Santiago, 3810-193 Aveiro, Portugal
| | - Sílvia M. Rocha
- Department of Chemistry & LAQV-REQUIMTE, University of Aveiro, Campus Universitário Santiago, 3810-193 Aveiro, Portugal;
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Palmnäs M, Brunius C, Shi L, Rostgaard-Hansen A, Torres NE, González-Domínguez R, Zamora-Ros R, Ye YL, Halkjær J, Tjønneland A, Riccardi G, Giacco R, Costabile G, Vetrani C, Nielsen J, Andres-Lacueva C, Landberg R. Perspective: Metabotyping-A Potential Personalized Nutrition Strategy for Precision Prevention of Cardiometabolic Disease. Adv Nutr 2020; 11:524-532. [PMID: 31782487 PMCID: PMC7231594 DOI: 10.1093/advances/nmz121] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2019] [Revised: 09/26/2019] [Accepted: 10/14/2019] [Indexed: 12/22/2022] Open
Abstract
Diet is an important, modifiable lifestyle factor of cardiometabolic disease risk, and an improved diet can delay or even prevent the onset of disease. Recent evidence suggests that individuals could benefit from diets adapted to their genotype and phenotype: that is, personalized nutrition. A novel strategy is to tailor diets for groups of individuals according to their metabolic phenotypes (metabotypes). Randomized controlled trials evaluating metabotype-specific responses and nonresponses are urgently needed to bridge the current gap of knowledge with regard to the efficacy of personalized strategies in nutrition. In this Perspective, we discuss the concept of metabotyping, review the current literature on metabotyping in the context of cardiometabolic disease prevention, and suggest potential strategies for metabotype-based nutritional advice for future work. We also discuss potential determinants of metabotypes, including gut microbiota, and highlight the use of metabolomics to define effective markers for cardiometabolic disease-related metabotypes. Moreover, we hypothesize that people at high risk for cardiometabolic diseases have distinct metabotypes and that individuals grouped into specific metabotypes may respond differently to the same diet, which is being tested in a project of the Joint Programming Initiative: A Healthy Diet for a Healthy Life.
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Affiliation(s)
- Marie Palmnäs
- Department of Biology and Biological Engineering, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
| | - Carl Brunius
- Department of Biology and Biological Engineering, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
| | - Lin Shi
- Department of Biology and Biological Engineering, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
- School of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an, China
| | - Agneta Rostgaard-Hansen
- Department of Biology and Biological Engineering, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
- Diet, Genes, and Environment, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Núria Estanyol Torres
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences, and Gastronomy, Institute for Research on Nutrition and Food Safety, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain
- Centro de Investigacion Biomedica en Red (CIBER) of Frailty and Healthy Aging (CIBERFES), Instituto de Salud Carlos III, Barcelona, Spain
| | - Raúl González-Domínguez
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences, and Gastronomy, Institute for Research on Nutrition and Food Safety, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain
- Centro de Investigacion Biomedica en Red (CIBER) of Frailty and Healthy Aging (CIBERFES), Instituto de Salud Carlos III, Barcelona, Spain
| | - Raul Zamora-Ros
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences, and Gastronomy, Institute for Research on Nutrition and Food Safety, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Prgramme, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de LLobregat, Barcelona, Spain
| | - Ye Lingqun Ye
- Department of Biology and Biological Engineering, Division of Systems and Synthetic Biology, Chalmers University of Technology, Gothenburg, Sweden
| | - Jytte Halkjær
- Diet, Genes, and Environment, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Anne Tjønneland
- Diet, Genes, and Environment, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Gabriele Riccardi
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Rosalba Giacco
- Institute of Food Science, Italian National Research Council, Avellino, Italy
| | - Giuseppina Costabile
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Claudia Vetrani
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Jens Nielsen
- Department of Biology and Biological Engineering, Division of Systems and Synthetic Biology, Chalmers University of Technology, Gothenburg, Sweden
| | - Cristina Andres-Lacueva
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences, and Gastronomy, Institute for Research on Nutrition and Food Safety, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain
- Centro de Investigacion Biomedica en Red (CIBER) of Frailty and Healthy Aging (CIBERFES), Instituto de Salud Carlos III, Barcelona, Spain
| | - Rikard Landberg
- Department of Biology and Biological Engineering, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
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Billet K, Houillé B, Dugé de Bernonville T, Besseau S, Oudin A, Courdavault V, Delanoue G, Guérin L, Clastre M, Giglioli-Guivarc'h N, Lanoue A. Field-Based Metabolomics of Vitis vinifera L. Stems Provides New Insights for Genotype Discrimination and Polyphenol Metabolism Structuring. Front Plant Sci 2018; 9:798. [PMID: 29977248 PMCID: PMC6021511 DOI: 10.3389/fpls.2018.00798] [Citation(s) in RCA: 29] [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] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Accepted: 05/24/2018] [Indexed: 05/21/2023]
Abstract
Grape accumulates numerous polyphenols with abundant health benefit and organoleptic properties that in planta act as key components of the plant defense system against diseases. Considerable advances have been made in the chemical characterization of wine metabolites particularly volatile and polyphenolic compounds. However, the metabotyping (metabolite-phenotype characterization) of grape varieties, from polyphenolic-rich vineyard by-product is unprecedented. As this composition might result from the complex interaction between genotype, environment and viticultural practices, a field experiment was setting up with uniform pedo-climatic factors and viticultural practices of growing vines to favor the genetic determinism of polyphenol expression. As a result, UPLC-MS-based targeted metabolomic analyses of grape stems from 8 Vitis vinifera L. cultivars allowed the determination of 42 polyphenols related to phenolic acids, flavonoids, procyanidins, and stilbenoids as resveratrol oligomers (degree of oligomerization 1-4). Using a partial least-square discriminant analysis approach, grape stem chemical profiles were discriminated according to their genotypic origin showing that polyphenol profile express a varietal signature. Furthermore, hierarchical clustering highlights various degree of polyphenol similarity between grape varieties that were in agreement with the genetic distance using clustering analyses of 22 microsatellite DNA markers. Metabolite correlation network suggested that several polyphenol subclasses were differently controlled. The present polyphenol metabotyping approach coupled to multivariate statistical analyses might assist grape selection programs to improve metabolites with both health-benefit potential and plant defense traits.
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Affiliation(s)
- Kévin Billet
- EA 2106 Biomolécules et Biotechnologie Végétales, Université de Tours, Faculté des Sciences Pharmaceutiques, Tours, France
| | - Benjamin Houillé
- EA 2106 Biomolécules et Biotechnologie Végétales, Université de Tours, Faculté des Sciences Pharmaceutiques, Tours, France
| | - Thomas Dugé de Bernonville
- EA 2106 Biomolécules et Biotechnologie Végétales, Université de Tours, Faculté des Sciences Pharmaceutiques, Tours, France
| | - Sébastien Besseau
- EA 2106 Biomolécules et Biotechnologie Végétales, Université de Tours, Faculté des Sciences Pharmaceutiques, Tours, France
| | - Audrey Oudin
- EA 2106 Biomolécules et Biotechnologie Végétales, Université de Tours, Faculté des Sciences Pharmaceutiques, Tours, France
| | - Vincent Courdavault
- EA 2106 Biomolécules et Biotechnologie Végétales, Université de Tours, Faculté des Sciences Pharmaceutiques, Tours, France
| | | | | | - Marc Clastre
- EA 2106 Biomolécules et Biotechnologie Végétales, Université de Tours, Faculté des Sciences Pharmaceutiques, Tours, France
| | - Nathalie Giglioli-Guivarc'h
- EA 2106 Biomolécules et Biotechnologie Végétales, Université de Tours, Faculté des Sciences Pharmaceutiques, Tours, France
| | - Arnaud Lanoue
- EA 2106 Biomolécules et Biotechnologie Végétales, Université de Tours, Faculté des Sciences Pharmaceutiques, Tours, France
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Corol DI, Harflett C, Beale MH, Ward JL. An efficient high throughput metabotyping platform for screening of biomass willows. Metabolites 2014; 4:946-76. [PMID: 25353313 PMCID: PMC4279154 DOI: 10.3390/metabo4040946] [Citation(s) in RCA: 10] [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: 09/04/2014] [Revised: 10/15/2014] [Accepted: 10/22/2014] [Indexed: 11/16/2022] Open
Abstract
Future improvement of woody biomass crops such as willow and poplar relies on our ability to select for metabolic traits that sequester more atmospheric carbon into biomass, or into useful products to replace petrochemical streams. We describe the development of metabotyping screens for willow, using combined 1D 1H-NMR-MS. A protocol was developed to overcome 1D 1H-NMR spectral alignment problems caused by variable pH and peak broadening arising from high organic acid levels and metal cations. The outcome was a robust method to allow direct statistical comparison of profiles arising from source (leaf) and sink (stem) tissues allowing data to be normalised to a constant weight of the soluble metabolome. We also describe the analysis of two willow biomass varieties, demonstrating how fingerprints from 1D 1H-NMR-MS vary from the top to the bottom of the plant. Automated extraction of quantitative data of 56 primary and secondary metabolites from 1D 1H-NMR spectra was realised by the construction and application of a Salix metabolite spectral library using the Chenomx software suite. The optimised metabotyping screen in conjunction with automated quantitation will enable high-throughput screening of genetic collections. It also provides genotype and tissue specific data for future modelling of carbon flow in metabolic networks.
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Affiliation(s)
- Delia I Corol
- Department of Plant Biology and Crop Sciences, Rothamsted Research, West Common, Harpenden, Herts AL5 2JQ, UK.
| | - Claudia Harflett
- Department of Plant Biology and Crop Sciences, Rothamsted Research, West Common, Harpenden, Herts AL5 2JQ, UK.
| | - Michael H Beale
- Department of Plant Biology and Crop Sciences, Rothamsted Research, West Common, Harpenden, Herts AL5 2JQ, UK.
| | - Jane L Ward
- Department of Plant Biology and Crop Sciences, Rothamsted Research, West Common, Harpenden, Herts AL5 2JQ, UK.
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