TY - JOUR
T1 - New molecular evidence of wine yeast-bacteria interaction unraveled by non-targeted exometabolomic profiling
AU - Liu, Youzhong
AU - Forcisi, Sara
AU - Harir, Mourad
AU - Deleris-Bou, Magali
AU - Krieger-Weber, Sibylle
AU - Lucio, Marianna
AU - Longin, Cédric
AU - Degueurce, Claudine
AU - Gougeon, Régis D.
AU - Schmitt-Kopplin, Philippe
AU - Alexandre, Hervé
N1 - Publisher Copyright:
© 2016, Springer Science+Business Media New York.
PY - 2016/4/1
Y1 - 2016/4/1
N2 - Introduction: Bacterial malolactic fermentation (MLF) has a considerable impact on wine quality. The yeast strain used for primary fermentation can systematically stimulate (MLF+ phenotype) or inhibit (MLF−) bacteria and the MLF process as a function of numerous winemaking practices, but the underlying molecular evidence still remains a mystery. Objectives: The goal of the study was to elucidate such evidence by the direct comparison of extracellular metabolic profiles of MLF+ and MLF− phenotypes. Methods: We have applied a non-targeted metabolomic approach combining ultrahigh-resolution FT-ICR-MS analysis, powerful statistical tools and a comprehensive wine metabolite database. Results: We discovered around 2500 unknown masses and 800 putative biomarkers involved in phenotypic distinction. For the putative biomarkers, we also developed a biomarker identification workflow and elucidated the exact structure (by UPLC-Q-ToF–MS2) and/or exact physiological impact (by in vitro tests) of several novel biomarkers, such as D-gluconic acid, citric acid, trehalose and tripeptide Pro-Phe-Val. In addition to valid biomarkers, molecular evidence was reflected by unprecedented chemical diversity (around 3000 discriminant masses) that characterized both the yeast phenotypes. While distinct chemical families such as phenolic compounds, carbohydrates, amino acids and peptides characterize the extracellular metabolic profiles of the MLF+ phenotype, the MLF− phenotype is associated with sulphur-containing peptides. Conclusion: The non-targeted approach used in this study played an important role in finding new and unexpected molecular evidence.
AB - Introduction: Bacterial malolactic fermentation (MLF) has a considerable impact on wine quality. The yeast strain used for primary fermentation can systematically stimulate (MLF+ phenotype) or inhibit (MLF−) bacteria and the MLF process as a function of numerous winemaking practices, but the underlying molecular evidence still remains a mystery. Objectives: The goal of the study was to elucidate such evidence by the direct comparison of extracellular metabolic profiles of MLF+ and MLF− phenotypes. Methods: We have applied a non-targeted metabolomic approach combining ultrahigh-resolution FT-ICR-MS analysis, powerful statistical tools and a comprehensive wine metabolite database. Results: We discovered around 2500 unknown masses and 800 putative biomarkers involved in phenotypic distinction. For the putative biomarkers, we also developed a biomarker identification workflow and elucidated the exact structure (by UPLC-Q-ToF–MS2) and/or exact physiological impact (by in vitro tests) of several novel biomarkers, such as D-gluconic acid, citric acid, trehalose and tripeptide Pro-Phe-Val. In addition to valid biomarkers, molecular evidence was reflected by unprecedented chemical diversity (around 3000 discriminant masses) that characterized both the yeast phenotypes. While distinct chemical families such as phenolic compounds, carbohydrates, amino acids and peptides characterize the extracellular metabolic profiles of the MLF+ phenotype, the MLF− phenotype is associated with sulphur-containing peptides. Conclusion: The non-targeted approach used in this study played an important role in finding new and unexpected molecular evidence.
KW - Biomarkers
KW - FT-ICR-MS
KW - Machine learning
KW - Non-targeted metabolomics
KW - UPLC-Q-ToF-MS
KW - Wine
UR - http://www.scopus.com/inward/record.url?scp=84960384901&partnerID=8YFLogxK
U2 - 10.1007/s11306-016-1001-1
DO - 10.1007/s11306-016-1001-1
M3 - Article
AN - SCOPUS:84960384901
SN - 1573-3882
VL - 12
JO - Metabolomics
JF - Metabolomics
IS - 4
M1 - 69
ER -