Gender discrimination of Populus tomentosa barks by HPLC fingerprint combined with multivariate statistics

Multicomponent Analysis of Liuwei Dihuang Pills by a Single Marker Quantification Method and Chemometric Discrimination of Fingerprints

An effective and comprehensive quality evaluation method for Liuwei Dihuang pills (LDP) was established by the simultaneous determination of 8 active components in LDP by the quantitative analysis of multicomponents by single marker (QAMS) method and high-performance liquid chromatography (HPLC) fingerprint combined with chemometrics. These 8 active components were determined by QAMS and the external standard method (ESM), and the quantitative results of the two methods were compared to validate the accuracy and feasibility of the QAMS method. 8 active components showed good linear relationships within their ranges, whose average recoveries were 99.7∼102.3%. No significant difference was found (P > 0.05) in the quantitative results determined by QAMS and ESM. Furthermore, the fingerprint of LDP was also established, with 11 common peaks identified, and the similarity of the fingerprints of 21 batches of LDP was greater than 0.95. The 21 batches of LDP were basically divided into 3 groups by hierarchical cluster analysis (HCA) and principal component analysis (PCA), and 3 differential markers were screened out by orthogonal partial least squares discriminant analysis (OPLS-DA). The established QAMS method is accurate, economical, fast, and convenient and can simultaneously determine the content of 8 active components in LDP. HPLC fingerprint combined with chemometric analysis more comprehensively evaluated the quality consistency of different batches of LDP and analyzed the markers that cause quality differences between batches. It can provide a scientific basis and reference of quality consistency evaluation for the manufacturers and drug regulatory departments of the preparation.

Comprehensive Quality Evaluation of Qizhi Xiangfu Pills Based on Quantitative Analysis of Multi-Components by a Single Marker Combined with GC Fingerprints and Chemometrics

BACKGROUND

Qizhi Xiangfu Pills (QXPs) are a traditional Chinese medicine (TCM) used clinically for qi stagnation and blood stasis. The current quality control of QXPs in the ministry standards and the reported literature is minimal, and requires improvement.

OBJECTIVE

This study aimed to analyze and determine the active ingredients in QXPs for its overall evaluation.

METHODS

In this study, a quantitative analysis of multi-components by a single marker (QAMS) method was established to simultaneously determine caryophyllene oxide, cyperotundone, ligustilide, and α-cyperone in QXPs by GC. Moreover, the GC fingerprints of 22 batches of samples were also established, and the common peaks were initially identified by GC-MS, then classified in various dimensions using chemometric methods, and the main markers causing the discrepancies between groups were analyzed by orthogonal partial least-squares discrimination analysis (OPLS-DA).

RESULTS

Compared with an internal standard method (ISM), the determination results obtained by QAMS had no significant difference. Twenty-two common peaks were distinguished in the fingerprint of 22 batches of QXPs, 17 of which were identified, and the similarity of the fingerprints was greater than 0.898. The 22 batches of QXPs were roughly divided into 3 categories, and 12 main markers causing the discrepancies were discovered.

CONCLUSION

The established QAMS method combined with the GC fingerprint and chemometrics is convenient and feasible, which helps to improve the quality evaluation of QXPs and provides a demonstration for the related study of compound preparations and single herbs.

HIGHLIGHTS

QAMS combined with a GC fingerprint and chemometrics method was established to evaluate the quality of QXPs for the first time.

Combined analysis of transcriptomics and metabolomics on the cumulative effect of nano-titanium dioxide on mulberry seedlings

Introduction

Titanium dioxide nanoparticles (TiO₂ NPs) are among the most widely used inorganic nanomaterials in industry, medicine and food additives. There are increasing concerns regarding their potential risks to plants and the environment. Mulberry trees are widely grown in China due to their high survival rate and ability to aid ecological recovery.

Methods

Herein, the effects of TiO₂ NPs with different concentrations (100, 200, 400 and 800 mg/L) on the growth and physiology of the mulberry tree were systematically evaluated in aspects of physiology, transcriptomics and metabolomics.

Results

Results showed that TiO₂ NPs could be absorbed by the mulberry sapling root system and be transferred to the plant shoot. This results in the destruction of mulberry sapling root and leaf tissue. Furthermore, the number of chloroplasts and their pigment contents were reduced and the homeostasis of metal ions was disrupted. The toxic effects of TiO₂ NPs attenuated the mulberry sapling's stress resistance, the contents of malondialdehyde in 100 mg/L, 200 mg/L 400 mg/L and 800 mg/L treatment groups increased by 87.70%, 91.36%, 96.57% and 192.19% respectively compared with the control group. The transcriptomic data showed that TiO₂ NPs treatment mainly affected the expression of genes related to energy synthesis and transport, protein metabolism, and response to stress. Meanwhile, the results of metabolomics showed that 42 metabolites produced significant differences in mulberry, of which 26 differential metabolites were up-regulated in expression and 16 differential metabolites were down-regulated, mainly including metabolic pathways such as secondary metabolite biosynthesis, citric acid cycle, and tricarboxylic acid cycle, and was not conducive to the seed germination and or growth of the mulberry sapling.

Discussion

This study enriches the understanding of the effects of TiO₂ NPs on plants and provides a reference for the comprehensive scientific assessment of the potential risks of nanomaterials on plants.

Gender Discrimination of Flower Buds of Mature Populus tomentosa by HPLC Fingerprint Combined with Chemometrics

A high performance liquid chromatography-diode array detector (HPLC-DAD) was used to establish the HPLC fingerprint. Chemometrics methods were used to discriminate against the gender of flower buds of Populus tomentosa based on areas of common peaks calibrated with the HPLC fingerprint. The score plot of principal component analysis (PCA) showed a clear grouping trend (R²X, 0.753; Q², 0.564) between female and male samples. Two groups were also well discriminated with orthogonal partial least squares-discriminant analysis (OPLS-DA) (R²X, 0.741; R²Y, 0.980; Q², 0.970). As the hierarchical clustering analysis (HCA) heatmap showed, all samples were separated into two groups. Four compounds were screened out by S-plot and variable importance in projection (VIP > 1.0). Two of them were identified as siebolside B and tremulacin. This study demonstrated that HPLC fingerprints combined with chemometrics can be applied to discriminate against dioecious plants and screen differences, providing a reference for identifying the gender of dioecious plants.

Untargeted Metabolomics Coupled with Chemometrics for Leaves and Stem Barks of Dioecious Morus alba L

The differences in metabolites in male and female individuals of dioecious Morus alba L. (Moraceae) are usually ignored and lack study. In the present study, 58 leaves and 61 stem barks from male and female individuals were analyzed by untargeted metabolomics via headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) coupled with chemometrics, including principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA). A total of 66 and 44 metabolites were identified from leaves and stem barks, respectively. Four and eight differential metabolites among candidate metabolites in leaves and stem barks from male and female individuals were identified. Moreover, females possessed stronger antioxidant activity than males. This is the first report where untargeted metabolomics coupled with chemometrics was used to analyze the different metabolites and to discriminate the gender of leaves and stem barks of dioecious M. alba. It provided the basis for further study of M. alba and reference value for researching dioecious plants.

Multivariate Statistical Analysis Uncovers Spectrum–Effect Relationship between HPLC Fingerprints and Antioxidant Activity of Saffron

Crocus sativus L. is commonly used as functional food and medicinal herb in traditional Chinese medicine. In this study, the spectrum–effect relationship was established between HPLC fingerprints and in vitro antioxidant activity of saffron to improve the quality evaluation method of saffron. The fingerprints of 21 batches of saffron collected from different regions were assessed, and the data were further analyzed by chemometric methods, including similarity analysis, hierarchical clustering analysis, principal component analysis, and orthogonal partial least squares discriminant analysis. The spectrum–effect relationship between fingerprints and antioxidant effect of saffron was analyzed by grey relational analysis and partial least square methods to figure out the antioxidant component of saffron. Thirteen common peaks of 21 batches of saffron were included in the analysis, and peak 3 (picrocrocin), peak 7 (crocin I), and peak 10 (crocin II) were identified as the main active components responsible for antioxidant efficacy. Besides, a multi-index quality control method was developed for simultaneous determination of these three antioxidant components in saffron. Taken together, this study provided new strategies for the quality control and the development of new bioactive products of saffron in the future.

1H NMR Combined with Multivariate Statistics for Discrimination of Female and Male Flower Buds of Populus tomentosa

¹H Nuclear Magnetic Resonance (¹H NMR) combined with multivariate statistics was adopted to discriminate female and male flower buds of Populus tomentosa in the study. Samples of 11 female and 16 male flower buds of P. tomentosa were collected in Beijing, China. ¹H NMR spectra were acquired on a 400 MHz spectrometer. In total, 30 chemical compounds were identified with standards and literature according to chemical shifts, peak areas, and multiplicity. Principal component analysis (PCA), hierarchical clustering analysis (HCA), and supervised orthogonal partial least squares-discriminant analysis (OPLS-DA) were applied to discriminate female and male flower buds. An apparent grouping trend (R²X, 0.809; Q², 0.903) between female and male groups was exhibited with PCA and HCA. The two groups were also well discriminated with OPLS-DA (R²X, 0.808; R²Y, 0.976; Q², 0.960). Combined with variable importance in projection (VIP) > 1.0 and p < 0.05 of OPLS-DA, it was found that the content of daucosterol, β-sitosterol, ursolic acid, and betulonic acid in male group was higher than that in female, which should be the key differences of chemical constituents in female and male flower buds of P. tomentosa. The study demonstrated that ¹H NMR combined with multivariate statistics could be used to discriminate female and male plants and clarify differences, which provided a novel method to identify the gender of dioecious plants.