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Integrated HPLC–UV validation and LC–MS/MS optimization with molecular networking and chemometrics for advanced characterization of chlorogenic acids in Ilex guayusa

Abstract:

Chlorogenic acids (caffeoylquinic acid isomers, CQAs) are major phenolic constituents of Ilex guayusa, but their comprehensive profiling in complex plant matrices is hindered by co-elution, overlapping UV spectra, and isomeric similarity in MS/MS. Rather than aiming to fully resolve isomer-specific quantification by MS, here we present an integrated workflow that couples validated HPLC–UV quantification of the major CQA (5-CQA) with an optimized UPLC–MS/MS strategy designed to improve MS1 peak integrity and expand MS/MS coverage for higher-confidence structural annotation. The HPLC–UV method showed excellent performance for targeted quantification of 5-CQA, including strong linearity (r² = 0.998), selectivity, sensitivity (LOQ = 0.25 mg/L), precision, and recovery. For LC–MS/MS, FastDDA acquisition (top-5 vs. top-15 precursors) revealed the expected trade-off between fragmentation depth and MS1 peak quality; however, post-acquisition raw-data merging restored MS1 fidelity and increased the number of detected features by 43%, enabling high-confidence annotation rather than quantitative discrimination of 16 metabolites and the propagation of oxidized CQA-related derivatives using feature-based molecular networking. Multivariate analyses (PCA, volcano plots, HCA) indicated that geographic location exerted the strongest influence on the metabolite composition, followed by sunlight exposure and plant age. Overall, the proposed workflow provides a practical framework that integrates robust chromatographic quantification with MS acquisition and data-processing optimization, thereby enhancing structural characterization and biological interpretation, rather than complete isomer-resolved quantification, of chlorogenic-acid-related chemistry across complex plant-derived and natural product matrices