Bioprofiling for the quality control of Egyptian propolis using an integrated NIR-HPTLC-image analysis strategy

Abstract

Quality control of propolis being a complex mixture of compounds that are very difficult to analyze and standardize is certainly challenging. Shown on the example of 35 Egyptian propolis samples, a strategy for an improved quality control was demonstrated in which efficacy-directed fingerprint analysis of high-performance thin-layer chromatography (HPTLC) fingerprints were evaluated in combination with Near Infra-Red spectrometry (NIRS) to realize precise discrimination and high quality assessment of chemical and effective consistency of propolis samples that are collected from various geographical locations in Egypt. The fingerprints obtained after derivatization and fluorescence detection (FLD) at λ 366 nm were analyzed by using multivariate data analysis and data were used to identify nine marker ingredients of the different propolis samples. These markers were then quantified by a new validated HPTLC method and an attempt to classify the samples by using a targeted approach was implemented. All investigated propolis samples were initially divided into two types in the untargeted and targeted HPTLC image multivariate analysis. The antimicrobial activities of propolis samples were then evaluated and the results showed that there was significant variation in the biological activities of the different samples. The quantitative data of marker compounds as well as the samples bioactivity results were then subjected to partial least squares regression (PLS-R) analysis which revealed that chrysin, galangin‑5‑O‑methylether, pinostrobin, and islapinin were the main bioactive markers. Based on the efficacy-associated marker ingredients, pretreated spectral patterns of NIRS were selected as a complementary evaluation technique directed to the comprehensive efficacy-directed discrimination of the different Egyptian propolis samples which could successfully classify the propolis samples tested into three different types. Hierarchical cluster analysis and orthogonal projection to latent structures discriminant analysis (OPLS-DA) were applied to the quantitative results from the efficacy-associated markers only. From this systematic method, the 35 samples were subsequently divided into three types; orange, green and blue, displaying a more intricate division than OPLS-DA which is based only on the untargeted HPTLC analysis or the full NIR spectral data. This study initiated the research on the Egyptian propolis and confirmed the existence of three different types of Egyptian propolis, the blue, green and orange types. The study also emphasizes how it is critical to implement the fingerprint- efficacy relationship analysis in finding out the main health-relevant biomarkers for the quality assessment especially for samples displaying delicate differences in their chemical composition and bioactivity.