Phytochemical Profiling and Quality Control of Terminalia sericea Burch. ex DC. Using HPTLC Metabolomics

Abstract

Terminalia sericea is used throughout Africa for the treatment of a variety of conditions and has been identified as a potential commercial plant. The study was aimed at establishing a high-performance thin layer chromatography (HPTLC) chemical fingerprint for T. sericea root bark as a reference for quality control and exploring chemical variation within the species using HPTLC metabo3lomics. Forty-two root bark samples were collected from ten populations in South Africa and extracted with dichloromethane: methanol (1:1). An HPTLC method was optimized to resolve the major compounds from other sample components. Dichloromethane: ethyl acetate: methanol: formic acid (90:10:30:1) was used as the developing solvent and the plates were visualized using 10% sulfuric acid in methanol as derivatizing agent. The concentrations of three major bioactive compounds, sericic acid, sericoside and resveratrol-3-O-β-rutinoside, in the extracts were determined using a validated ultra-performance liquid chromatography-photodiode array (UPLC-PDA) detection method. The rTLC software (written in the R-programming language) was used to select the most informative retardation factor (Rf) ranges from the images of the analysed sample extracts. Further chemometric models, including principal component analysis (PCA) and hierarchical cluster analysis (HCA), were constructed using the web-based high throughput metabolomic software. The rTLC chemometric models were compared with the models previously obtained from ultra-performance liquid chromatography coupled with mass spectrometry (UPLC-MS). A characteristic fingerprint containing clear bands for the three bioactive compounds was established. All three bioactive compounds were present in all the samples, although their corresponding band intensities varied. The intensities correlated with the UPLC-PDA results, in that samples containing a high concentration of a particular compound, displayed a more intense band. Chemometric analysis using HCA revealed two chemotypes, and the subsequent construction of a loadings plot indicated that sericic acid and sericoside were responsible for the chemotypic variation; with sericoside concentrated in Chemotype 1, while sericic acid was more abundant in Chemotype 2. A characteristic chemical fingerprint with clearly distinguishable features was established for T. sericea root bark that can be used for species authentication, and to select samples with high concentrations of a particular marker compound(s). Different chemotypes, potentially differing in their therapeutic potency towards a particular target, could be distinguished. The models revealed the three analytes as biomarkers, corresponding to results reported for UPLC-MS profiling and thereby indicating that HPTLC is a suitable technique for the quality control of T. sericea root bark.

Quality evaluation methods of chinese medicine based on scientific supervision: recent research progress and prospects

“…Mulaudzi and colleagues used HPTLC chemical fingerprint and metabolomics to analyze its root bark for quality control and intraspecies chemical variation. Although using white light in HPTLC to observe TLC plates has limitations, this shortcoming can be overcome by carefully inspecting images corresponding to the locations of individual samples with known concentrations of labeled compounds [ 30 ].…”

Chemical and cytotoxicity profiles of 11 pink pepper (Schinus spp.) samples via non-targeted hyphenated high-performance thin-layer chromatography

“…The most commonly used profiling tools are nuclear magnetic resonance spectroscopy and various chromatographic techniques, such as LC–MS/MS and GC–MS/MS, followed by in silico analyses. High-performance thin-layer chromatography (HPTLC) has been successfully integrated into metabolomics workflows for quality control and authentication through fingerprinting and subsequent chemometric analysis such as principal component analysis (PCA) or hierarchical cluster analysis (HCA) (Booker et al, 2016 ; Ivanović et al, 2023 ; Mulaudzi et al, 2021 ; Salomé-Abarca et al, 2021 ). Hyphenated HPTLC and metabolomics are both excellent tools for simultaneous non-target bioprofiling of samples, whereby the investigation of the bioactivity is performed on-surface via HPTLC (Schreiner & Morlock, 2021 ; Schreiner et al, 2021 ) versus usually in silico via metabolomics.…”

HPTLC-Based Chemical Profiling: An Approach to Monitor Plant Metabolic Expansion Caused by Fungal Endophytes

“…Recently, high performance thin layer chromatography (HPTLC) has gained ground as an interesting alternative for chemical profiling, alone or as a complementary tool [16,17]. Its multiple advantages include its broad range of chemical profiling options [18] and enhanced detection thanks to the possibility of using numerous post-analytical chemical reagents [19], speed of analysis, and parallel analysis of samples [20].…”