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Study of the Glycosylated Secondary Metabolites in Tea (Camellia Sinensis L.) Using UHPLC/Q-TOF/MS

Applications | 2017 | Agilent TechnologiesInstrumentation
LC/TOF, LC/HRMS, LC/MS, LC/MS/MS
Industries
Metabolomics
Manufacturer
Agilent Technologies

Summary

Significance of Glycosylation Analysis in Tea Metabolomics


Glycosylation profoundly influences the chemical stability, solubility, and bioactivity of plant secondary metabolites. In tea (Camellia sinensis L.), glycosylated compounds contribute to flavor, antioxidant properties, and health benefits. However, comprehensive mapping of these modifications has been hindered by analytical challenges. This study presents a nontargeted, modification-specific metabolomics approach to systematically profile glycosylated metabolites in green tea, advancing our understanding of tea chemistry and quality control.

Objectives and Study Overview


The main goals were:
  • Develop a workflow to selectively extract and identify glycosylated metabolites in tea.
  • Apply the method to pooled and individual green tea samples from 14 cultivars.
  • Discover novel glycosylated compounds and characterize varietal glycosylation patterns linked to tea processing suitability.

Methodology and Workflow


The strategy combines ultra-high-performance liquid chromatography (UHPLC) with high-resolution quadrupole time-of-flight mass spectrometry (Q-TOF/MS) operated in all-ions in-source collision-induced dissociation (ISCID) mode. Key steps:
  • Extract pooled or individual green tea infusions with 60% methanol.
  • Acquire TOF/MS scans over 0–45 eV collision energies to induce sugar neutral losses.
  • Perform molecular feature extraction and peak alignment using MassHunter Qualitative Analysis and Mass Profiler Professional.
  • Apply a customized neutral-loss matching algorithm to detect pairs of coeluting precursor and fragment ions with mass deltas of 162.0528, 146.0579, 308.1107, and 294.0951 Da, corresponding to common glycosylation types.
  • Identify candidates by database searches (tea PCDL, METLIN, HMDB) for both glycosylated metabolites and their substrates, followed by MS/MS confirmation or standard comparison.

Instrumental Setup


Used instrumentation:
  • Agilent 1290 Infinity II UHPLC system with ZORBAX Eclipse Plus C18 column.
  • Agilent 6540 Q-TOF LC/MS with dual Jet Stream electrospray source.
  • All-ions in-source CID for simultaneous neutral-loss profiling at multiple collision energies.

Main Results and Discussion


The workflow detected 202 glycosylated metabolites across four modification types (glucosylation/galactosylation, rhamnosylation, rutinosylation, primeverosylation).
  • 144 compounds yielded characteristic neutral-loss features; 68 were matched to known standards or database entries.
  • 44 novel glycosylated metabolites were tentatively elucidated based on MS/MS fragmentation, including a newly discovered theanine glucoside confirmed by synthesized standard.
  • PCA of 14 tea cultivars based on glycosylated metabolite profiles revealed clear clustering correlated with traditional processing suitability: varieties rich in galactosides favored green and semi-fermented tea, whereas those higher in rutinosides and glucosides aligned with black tea production.

Benefits and Practical Applications


This approach enables:
  • Comprehensive and selective mapping of glycosylation modifications in complex plant matrices.
  • Discovery of previously unreported glycosylated metabolites.
  • Quality control and cultivar selection by linking glycosylation patterns to tea processing characteristics.

Future Trends and Possibilities


Extensions of this methodology may include:
  • Application to other crop or medicinal plants to profile diverse modification types (acylation, sulfation).
  • Integration with bioactivity assays to correlate specific glycosides with health benefits.
  • Development of targeted quantification assays for key glycosylated biomarkers in tea breeding and authentication.

Conclusion


A nontargeted modification-specific UHPLC/Q-TOF/MS workflow was established to profile glycosylated secondary metabolites in tea. This strategy improved coverage of known and novel glycosides, provided insights into varietal differences, and offers a versatile platform for plant metabolomics and tea quality research.

References


  1. Dai W., Tan J., et al. J. Agric. Food Chem. 64:6783–6790 (2016).
  2. Croci D.O., et al. Cell 156:744–758 (2014).
  3. Cheng J., et al. Plant Physiol. 166:1044–1058 (2014).
  4. Cui L., et al. J. Exp. Bot. 67:2285–2297 (2016).
  5. Huan T., et al. Anal. Chem. 87:10619–10626 (2015).
  6. Li L., et al. Anal. Chem. 85:3401–3408 (2013).
  7. Arbona V., et al. Int. J. Mol. Sci. 14:4885–4911 (2013).
  8. Tan J., et al. Food Res. Int. 79:106–113 (2016).

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