Metabolomics was very fast recognized as a powerful tool in analytical chemistry and biology for its ability to generate new hypotheses. The opportunity to work under a holistic and unsupervised approach, with simple sample preparation and short wet-lab times, attracted many researchers. On the other hand, building up an unbiased untargeted method is a tricky and delicate issue, which requires multidisciplinary knowledge and experience, while the time needed for data analysis is multiplied in respect to the targeted methods. Probably the biggest actual problem in Metabolomics is the lack of standardization and guidelines; which causes many different invalidated workflows and methods -often inadequate-, prolonged data analysis periods, and many expensive unpublished metabolomics experiments because of the poor and insufficient data quality. To overcome these problems is essential a systematic control of every step during the workflow, and a good knowledge of the sample nature and the instrumentations capabilities. In this wine metabolomics project we present a complete, 3 years, workflow which include the follow steps: 1. Experimental design 2. LC-MS method optimization/adaptation 3. Sample preparation optimization 4. LC-MS analysis (including daily controls of system stability and data quality) 5. Different QC strategies evaluation 6. Quality control of the final data 7. Marker discovery 8. Dealing with false positive and false negative 9. Markers annotation 10. New compounds identification 11. Markers validation 12. Hypotheses generation From this experience it was clear that in metabolomics, and in contrast to targeted methods, the wet-lab represents a very small part of the total project time (5-10%), but since this is “heart” and the most delicate component of the work maximum attention is necessary to avoid long data analysis and problematic data quality. Between the results of this project, were new hypotheses and knowledge about the red wine quality decrease during domestic storage

Arapitsas, P.; Perenzoni, D.; Angeli, A.; Mattivi, F. (2014). Wine metabolomics: a complete workflow. In: Metabolomics Series-GR Workshop III (MET-GR III): metabolic and protein network analysis in system biology, 18-20 September 2014, Patras Greece. handle: http://hdl.handle.net/10449/24118

Wine metabolomics: a complete workflow

Arapitsas, Panagiotis;Perenzoni, Daniele;Angeli, Andrea;Mattivi, Fulvio
2014-01-01

Abstract

Metabolomics was very fast recognized as a powerful tool in analytical chemistry and biology for its ability to generate new hypotheses. The opportunity to work under a holistic and unsupervised approach, with simple sample preparation and short wet-lab times, attracted many researchers. On the other hand, building up an unbiased untargeted method is a tricky and delicate issue, which requires multidisciplinary knowledge and experience, while the time needed for data analysis is multiplied in respect to the targeted methods. Probably the biggest actual problem in Metabolomics is the lack of standardization and guidelines; which causes many different invalidated workflows and methods -often inadequate-, prolonged data analysis periods, and many expensive unpublished metabolomics experiments because of the poor and insufficient data quality. To overcome these problems is essential a systematic control of every step during the workflow, and a good knowledge of the sample nature and the instrumentations capabilities. In this wine metabolomics project we present a complete, 3 years, workflow which include the follow steps: 1. Experimental design 2. LC-MS method optimization/adaptation 3. Sample preparation optimization 4. LC-MS analysis (including daily controls of system stability and data quality) 5. Different QC strategies evaluation 6. Quality control of the final data 7. Marker discovery 8. Dealing with false positive and false negative 9. Markers annotation 10. New compounds identification 11. Markers validation 12. Hypotheses generation From this experience it was clear that in metabolomics, and in contrast to targeted methods, the wet-lab represents a very small part of the total project time (5-10%), but since this is “heart” and the most delicate component of the work maximum attention is necessary to avoid long data analysis and problematic data quality. Between the results of this project, were new hypotheses and knowledge about the red wine quality decrease during domestic storage
Metabolomics
Food
Wine
Quality control
Biomarker
Metaboloma
Vino
workflow
2014
Arapitsas, P.; Perenzoni, D.; Angeli, A.; Mattivi, F. (2014). Wine metabolomics: a complete workflow. In: Metabolomics Series-GR Workshop III (MET-GR III): metabolic and protein network analysis in system biology, 18-20 September 2014, Patras Greece. handle: http://hdl.handle.net/10449/24118
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