Profiling of oligosaccharides and polysaccharides in alcoholic beverage using single quadrupole LC-MS
Posters | 2022 | Shimadzu | AOACInstrumentation
Comprehensive profiling of oligosaccharides and polysaccharides in alcoholic beverages is critical for understanding flavor, quality, and functional properties. Employing metabolomics approaches in food analysis enables detailed evaluation of saccharide composition, supporting quality control, manufacturing optimization, and product differentiation in the brewing industry.
This study aimed to develop a simple and robust method for simultaneous analysis of malto-oligosaccharides and higher polysaccharides (up to DP 40) in beer samples. Using a single quadrupole LC-MS system, the work profiled saccharide distributions in four beers (lager, ale, low-malt, soy-based) and two non-alcoholic beers, followed by principal component analysis to distinguish sample types based on saccharide content.
Samples were diluted 10-fold with water before direct analysis. A mixed standard of malto-oligosaccharides DP1–DP10 (10 mg/L) was used to evaluate calibration performance, linearity, and repeatability. Selected ion monitoring (SIM) targeted monovalent species for DP1–DP10 and polyvalent ions for larger polysaccharides above m/z 1500 to maintain sensitivity and measurable mass range.
The method achieved detection of oligosaccharides up to DP 24 in the standard mixture, with calibration curves showing excellent linearity (r2 > 0.99) and repeatability (RSD < 5%). In beer samples, polysaccharides up to DP 36 (average MW 5855.09) were observed as trivalent ions (m/z 1949.63). PCA of saccharide peak areas separated high-malt beers from low-malt and non-fermented samples, indicating saccharide distribution reflects raw material and fermentation processes. A heat map of relative peak areas revealed that lager and ale beers contained abundant higher oligo- and polysaccharides, whereas a non-alcoholic beer produced by unfermented wort (E) showed minimal saccharide content. Another non-alcoholic product (F) retained high levels of DP1–DP2 due to suppressed fermentation.
Advances may include coupling single-quad methods with high-resolution MS for structural elucidation, expanding analyses to other food and beverage matrices, integrating automated data processing for large-scale metabolomics, and correlating saccharide profiles with sensory and functional attributes.
A streamlined single-quadrupole LC-MS method has been established for comprehensive profiling of oligo- and polysaccharides in beer. The approach demonstrated high sensitivity, good quantitation performance, and effective differentiation of beverage types based on saccharide composition.
LC/MS, LC/SQ
IndustriesFood & Agriculture
ManufacturerShimadzu
Summary
Importance of the Topic
Comprehensive profiling of oligosaccharides and polysaccharides in alcoholic beverages is critical for understanding flavor, quality, and functional properties. Employing metabolomics approaches in food analysis enables detailed evaluation of saccharide composition, supporting quality control, manufacturing optimization, and product differentiation in the brewing industry.
Study Objectives and Overview
This study aimed to develop a simple and robust method for simultaneous analysis of malto-oligosaccharides and higher polysaccharides (up to DP 40) in beer samples. Using a single quadrupole LC-MS system, the work profiled saccharide distributions in four beers (lager, ale, low-malt, soy-based) and two non-alcoholic beers, followed by principal component analysis to distinguish sample types based on saccharide content.
Methodology
Samples were diluted 10-fold with water before direct analysis. A mixed standard of malto-oligosaccharides DP1–DP10 (10 mg/L) was used to evaluate calibration performance, linearity, and repeatability. Selected ion monitoring (SIM) targeted monovalent species for DP1–DP10 and polyvalent ions for larger polysaccharides above m/z 1500 to maintain sensitivity and measurable mass range.
Instrumentation Used
- Nexera XR HPLC system for chromatographic separation
- Shimadzu LCMS-2050 single-quadrupole mass spectrometer operated in positive SIM mode
Main Results and Discussion
The method achieved detection of oligosaccharides up to DP 24 in the standard mixture, with calibration curves showing excellent linearity (r2 > 0.99) and repeatability (RSD < 5%). In beer samples, polysaccharides up to DP 36 (average MW 5855.09) were observed as trivalent ions (m/z 1949.63). PCA of saccharide peak areas separated high-malt beers from low-malt and non-fermented samples, indicating saccharide distribution reflects raw material and fermentation processes. A heat map of relative peak areas revealed that lager and ale beers contained abundant higher oligo- and polysaccharides, whereas a non-alcoholic beer produced by unfermented wort (E) showed minimal saccharide content. Another non-alcoholic product (F) retained high levels of DP1–DP2 due to suppressed fermentation.
Benefits and Practical Applications
- Enhanced sensitivity over RID or ELSD for trace saccharide detection
- Rapid, simultaneous profiling of a broad DP range supports quality control
- Metabolomic fingerprinting aids authentication and product differentiation
- Applicable to process monitoring, storage stability, and formulation optimization
Future Trends and Opportunities
Advances may include coupling single-quad methods with high-resolution MS for structural elucidation, expanding analyses to other food and beverage matrices, integrating automated data processing for large-scale metabolomics, and correlating saccharide profiles with sensory and functional attributes.
Conclusion
A streamlined single-quadrupole LC-MS method has been established for comprehensive profiling of oligo- and polysaccharides in beer. The approach demonstrated high sensitivity, good quantitation performance, and effective differentiation of beverage types based on saccharide composition.
References
- Putri Sastia Prama et al. Application of gas chromatography-mass spectrometry-based metabolomics in food science and technology. J Biosci Bioeng. 133, 425–435 (2022).
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