Chemical Fingerprint Analysis for Discovering Markers and Identifying Saussurea involucrata by HPLC Coupled with OPLS-DA

Abstract

The quality control of Saussurea involucrata has been greatly improved by macroscopic and microscopic identification and chemical profiling described in Chinese Pharmacopoeia since 2005. However, these methods have their own limitations, e.g., their dependence on personal experience and expertise, and it is a huge challenge to identify closely related species that share similar or identical morphological characteristics and chemical profiles. A novel and generally accepted identification strategy is urgently needed as a complement to regulations for protecting the public health interests. In this work, a comprehensive chromatographic fingerprint method was developed and tested on 43 samples from four haplotypes of S. involucrata according to DNA barcoding. Three common patterns consisting of 20, 14, and 7 common peaks were generated by frequency filters of median, upper quartile, and 100%, respectively. Based on two formerly screened patterns, S. involucrata can be effectively identified from its five easily confused snow lotus species, including the most closely related plant (S. orgaadayi) in the orthogonal partial least-squares discriminant analysis (OPLS-DA) models. The model is supported by good R and Q coefficients. In addition, different haplotypes of S. involucrata can be discriminated in the OPLS-DA model using the 20 common peaks. Among them, peaks 9, 11, 16 (zaluzanin C), and 18 (dehydrocostus lactone) have been identified as fingerprint markers of S. involucrata via S-plots and VIP values (>1). Additionally, peaks 19 and 20 were identified as linolenic acid and linoleic acid with anti-inflammatory activity, and they were isolated from the herb for the first time. Collectively, the chromatographic fingerprint of S. involucrata can be an effective and integrated method for the identification of authentic herbs from adulterant species or related plants, and discrimination of its different haplotypes provides an objective and reliable tool for quality control.

An Evaluation of Traits, Nutritional, and Medicinal Component Quality of Polygonatum cyrtonema Hua and P. sibiricum Red.

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“…HPLC was developed to explore and demonstrate the differences in bioactive chemicals between various plant sources ( Ma et al, 2020 ). HPLC is helpful for the green synthesis of NPs particularly because of the involvement of plants as it quantifies the types of compounds present in the sample material.…”

Rapid Detection Method for Pathogenic Candida Captured by Magnetic Nanoparticles and Identified Using SERS via AgNPs+

“…Generally, a 10-fold cross-validation is required, and the accuracy of the algorithm is then estimated via the average accuracy (or error rate). 22 …”

“…Generally, a 10-fold crossvalidation is required, and the accuracy of the algorithm is then estimated via the average accuracy (or error rate). 22 Figure 1A shows the production process of Fe 3 O 4 @PEI. We improved the method of Liu et al 19,21 and synthesized Fe 3 O 4 microspheres sized 300-500 nm.…”