Widely targeted metabolomics of hydrophilic compounds in wine using two LC-MS/MS methods: Comparison of different types and producing regions

Significance of the topic

Metabolomic profiling of hydrophilic compounds in wine offers deep insights into the chemical factors that influence taste, flavor, and quality. As consumer interest in wine diversity and functional attributes grows, robust analytical methods enable objective evaluation of wine characteristics and optimization of production processes.

Objectives and Study Overview

This study aimed to implement widely targeted metabolomics of short chain fatty acids, organic acids, and other hydrophilic metabolites in red wines. Two complementary LC-MS/MS workflows were compared: a derivatization-based method for 23 short chain fatty acids and organic acids, and a non-derivatization method for 97 hydrophilic compounds using a novel IonFocus ionization unit. Wines from six producing regions and grape varieties were analyzed to identify characteristic metabolite patterns linked to origin and grape type.

Methodology

The analyses employed:

• Derivatization of short chain fatty acids and organic acids with 3-nitrophenylhydrazine and carbodiimide, followed by UHPLC on a C18 column (Nexera X3 → LCMS-8060)
• Direct analysis of 97 hydrophilic metabolites by UHPLC on an HS F5 column (Nexera X2 → LCMS-8060NX with IonFocus)
• Sample preparation involving centrifugation, filtration, and appropriate dilution steps for each method.

Used Instrumentation

• UHPLC systems: Shimadzu Nexera X3 and Nexera X2
• Triple quadrupole mass spectrometers: Shimadzu LCMS-8060 and LCMS-8060NX equipped with the IonFocus unit

Main Results and Discussion

Optimization of the focus voltage for the IonFocus unit revealed maximal sensitivity at ±2 kV for most analytes. Principal component analysis (PCA) of short chain fatty acids and organic acids distinguished wines by geographic origin: French samples were enriched in tartaric and succinic acids, U.S. wines in malic and pyruvic acids, while Chilean and Australian wines showed similar profiles. PCA of 97 hydrophilic metabolites clustered wines by grape variety: Cabernet Sauvignon and Merlot exhibited elevated levels of proline and 4-hydroxyproline; Merlot also showed higher phenylalanine, leucine, and lysine; Pinot Noir was marked by increased alanine, correlating with perceived sweetness and umami.

Benefits and Practical Applications of the Method

The integration of the IonFocus unit with LC-MS/MS provides enhanced sensitivity and robustness for complex food matrices, facilitating comprehensive metabolite profiling. This approach supports:

• Objective quality assessment of wines
• Monitoring of fermentation progress and yeast nutrition
• Evaluation of regional and varietal signatures for authenticity control

Future Trends and Opportunities

Emerging directions include expanding the targeted analyte panels, coupling with non-targeted metabolomics for broader coverage, and leveraging machine learning for pattern recognition. Real-time fermentation monitoring, automation of sample preparation, and application to other beverages and complex food matrices can further enhance process control and product innovation.

Conclusion

The study demonstrates that the newly developed IonFocus-assisted LC-MS/MS workflows enable sensitive and reproducible profiling of hydrophilic metabolites in wine. The methods successfully differentiate wines by grape variety and geographic origin, offering valuable tools for quality control and winemaking optimization.