Profiling phenolics compounds in shea by 2D LC (RPLC × HILIC) – cyclic ion mobility – quadrupole time-of-flight

Significance of the Topic

Shea kernels and shells contain abundant phenolic compounds with demonstrated antioxidant, anti-inflammatory, and other health-promoting properties. Profiling these metabolites is essential for valorizing shea by-products, improving quality control in food and personal care applications, and reinforcing sustainable supply chain practices.

Aim and Study Overview

This study linked traditional shea quality markers to supply chain parameters and mapped semi-polar secondary metabolites—primarily phenolics—in kernels and nut shells. The goal was to evaluate a four-dimensional analytical platform combining liquid chromatography, ion mobility, and high-resolution mass spectrometry under a data-independent acquisition (DIA) strategy.

Methodology

• Two-dimensional LC: Reversed-phase (Zorbax SB-C18) × HILIC (BEH Amide) separations with optimized flow rates, temperatures, and modulation times.
• Ion Mobility–MS: Single-pass cyclic ion mobility spectrometry (cIMS) in tandem with quadrupole time-of-flight MS, alternating low-energy MS1 and high-energy MS2 scans.
• Data Processing: Custom workflows using ProteoWizard, R (mzR, MALDIquant), and MATLAB to extract fully resolved four-dimensional data (retention time, drift time, m/z).

Used Instrumentation

• LC Columns: Zorbax SB-C18, Eclipse Plus C18, Acquity BEH Amide.
• Mass Spectrometer: ESI-Q-cIMS-qTOF system with cyclic ion mobility cell.
• Software: MassLynx, MSConvert, R packages, custom MATLAB scripts.

Main Results and Discussion

• Four-dimensional separation significantly enhanced chromatographic and spectral resolution, enabling unusually clean DIA spectra.
• Single-pass cIMS resolved near-isobaric and isobaric phenolics beyond conventional software capabilities.
• Collisional cross section (CCS) values matched experimental database entries within 2.9% error, with predicted CCS showing deviations up to 6%.
• Identification of 50 metabolites, including first reports of epitaxifolin, eight proanthocyanidins, isoorientin, and isoquercitrin in shea.

Benefits and Practical Applications

This workflow supports non-targeted screening in QA/QC, enables recovery of valuable bioactives from waste streams, and informs sustainable production strategies for the food and cosmetics industries.

Future Trends and Applications

• Advanced ion mobility techniques for deeper metabolomic coverage.
• Machine learning–driven annotation and CCS prediction to accelerate compound identification.
• Expanding the platform to other agro-industrial matrices for sustainable valorization.

Conclusion

The integrated 2D-LC × cIMS × HRMS with DIA demonstrates a robust approach for resolving complex phenolic profiles in shea, offering high-purity spectra and comprehensive metabolite identification for sustainable valorization.

References

• Giles K. et al. Analytical Chemistry, 2019, 91, 8564.
• Muller K. et al. Journal of Chromatography A, 2018.
• Kronik O.M. et al. Journal of Chromatography A, 2022; 2024.
• Zhang H. et al. Analytical Chemistry, 2023.