Quality evaluation and traceability of Bletilla striata by fluorescence fingerprint coupled with multiway chemometrics analysis

Rapid Raman spectroscopy analysis assisted with machine learning: a case study on Radix Bupleuri

BACKGROUND

Radix Bupleuri has been widely used for its plentiful pharmacological effects. But it is hard to evaluate their safety and efficacy because the concentrations of components are tightly affected by the surrounding environment. Thus, Radix Bupleuri samples from different regions and varieties were collected. Based on the experimental and computational Raman spectrum, machine learning is emphasized for certain obscured characteristics; for example, linear discriminant analysis (LDA), support vector machine (SVM), eXtreme gradient boosting (XGBoost) and light gradient boosting machine (LightGBM).

RESULTS

After dimension reduction by LDA, models of SVM, XGBoost and LightGBM were trained for classification and regression prediction of Bupleurum production regions. Support vector classifiers achieved the best accuracy of 98% and an F1 score above 0.96 on the test set. Support vector regression has a good fitting performance with an R2 score above 0.90 and a relatively low mean square error. However, complex models were prone to overfitting, resulting in poor generalization ability.

CONCLUSION

Among these machine learning models, the typical LDA-SVM models, consistent with the high-performance liquid chromatography results, demonstrate great performance and stability. We envision that this rapid classification and regression technique can be extended to predictions for other herbs. © 2024 Society of Chemical Industry.

Metabolomic and transcriptomic analyses reveal the mechanism of polysaccharide and secondary metabolite biosynthesis in Bletilla striata tubers in response to shading

Polysaccharides and various secondary metabolites are the major bioactive ingredients in Bletilla striata tubers and their biosynthesis and accumulation are influenced by light intensity. However, the mechanisms underlying shading effects remain largely unknown. In the present study, we used a combined analysis of the physiology, metabolome, and transcriptome to investigate the physiological activities and bioactive component accumulation of B. striata under different shading treatments (S0, S50, S70, and S90). The dry weight of shoots and tubers, net photosynthetic rate, and polysaccharide content were highest in S50 and lowest in S90. The content of precursors (sucrose, Glucose-6P, and Mannose-6P) for polysaccharide synthesis significantly increased in S50. However, the expression levels of genes involved in starch biosynthesis decreased in S50. Several structural genes involved in secondary metabolism, including cinnamic acid 4-hydroxylase (C4H), chalcone synthase (CHS), and 1-Deoxy-D-xylulose-5-phosphate synthase (DXS), showed decreased expression in S50. However, the shading effect on the biosynthesis of secondary metabolites (phenylpropanoids, flavonoids, and terpenoids) was inconsistent. Our study provides the molecular mechanisms underlying the effects of shading on the biosynthesis of polysaccharides and secondary metabolites in B. striata and offers a theoretical basis for the artificial cultivation and industrial production of bioactive ingredients.

The rhizosphere microbiome and its influence on the accumulation of metabolites in Bletilla striata (Thunb.) Reichb. f

BACKGROUND

Bletilla striata (Thunb.) Reichb. f. (B. striata) is a perennial herbaceous plant in the Orchidaceae family known for its diverse pharmacological activities, such as promoting wound healing, hemostasis, anti-inflammatory effects, antioxidant properties, and immune regulation. Nevertheless, the microbe-plant-metabolite regulation patterns for B. striata remain largely undetermined, especially in the field of rhizosphere microbes. To elucidate the interrelationships between soil physics and chemistry and rhizosphere microbes and metabolites, a comprehensive approach combining metagenome analysis and targeted metabolomics was employed to investigate the rhizosphere soil and tubers from four provinces and eight production areas in China.

RESULTS

Our study reveals that the core rhizosphere microbiome of B. striata is predominantly comprised of Paraburkholderia, Methylibium, Bradyrhizobium, Chitinophaga, and Mycobacterium. These microbial species are recognized as potentially beneficial for plants health. Comprehensive analysis revealed a significant association between the accumulation of metabolites, such as militarine and polysaccharides in B. striata and the composition of rhizosphere microbes at the genus level. Furthermore, we found that the soil environment indirectly influenced the metabolite profile of B. striata by affecting the composition of rhizosphere microbes. Notably, our research identifies soil organic carbon as a primary driving factor influencing metabolite accumulation in B. striata.

CONCLUSION

Our fndings contribute to an enhanced understanding of the comprehensive regulatory mechanism involving microbe-plant-metabolite interactions. This research provides a theoretical basis for the cultivation of high-quality traditional Chinese medicine B. striata.

Tracing sources of oilfield wastewater based on excitation-emission matrix fluorescence spectroscopy coupled with chemical pattern recognition techniques

In order to prevent the illegal discharge of oilfield wastewater, this work proposed excitation-emission matrix fluorescence (EEMF) spectroscopy coupled with two kinds of chemical pattern recognition methods for tracing the sources of oilfield wastewater. The first pattern recognition method was built from the relative concentrations extracted by alternating trilinear decomposition (ATLD) based on partial least squares-discriminant analysis (PLS-DA) algorithm, and the other one was modeled based on strictly multi-way partial least squares-discriminant analysis (N-PLS-DA). Both methods showed good discrimination abilities for oilfield wastewater samples from three different sources. The total recognition rates of the training and prediction sets are 100%, the values of sensitivity and selectivity are 1. This study showed that EEMF spectroscopy combined with chemical pattern recognition techniques could be used as a potential tool for tracing the sources of oilfield wastewater.

A Review of The Application of Spectroscopy to Flavonoids from Medicine and Food Homology Materials

Medicinal and food homology materials are a group of drugs in herbal medicine that have nutritional value and can be used as functional food, with great potential for development and application. Flavonoids are one of the major groups of components in pharmaceutical and food materials that have been found to possess a variety of biological activities and pharmacological effects. More and more analytical techniques are being used in the study of flavonoid components of medicinal and food homology materials. Compared to traditional analytical methods, spectroscopic analysis has the advantages of being rapid, economical and free of chemical waste. It is therefore widely used for the identification and analysis of herbal components. This paper reviews the application of spectroscopic techniques in the study of flavonoid components in medicinal and food homology materials, including structure determination, content determination, quality identification, interaction studies, and the corresponding chemometrics. This review may provide some reference and assistance for future studies on the flavonoid composition of other medicinal and food homology materials.

Screening of Bletilla striata, Bletilla ochracea, and Oreorchis foliosa differential metabolites based on metabolomics

As a representative medicinal plant in Orchidaceae, Bletilla striata plays a variety of pharmacological roles in the clinic. However, the emergence of counterfeit species affects the basic medicinal materials source identification process, of which Bletilla ochracea and Oreorchis foliosa of Orchidaceae are two representative species. For this study, 13 representative B. striata samples, 3 B. ochracea samples and 3 O. foliosa samples were selected for the systematic determination of polysaccharide yields and monosaccharide composition, and further detection of secondary metabolites by HPLC-MS. The results revealed that there was a significant difference in the yields of polysaccharides between B. striata and B. ochracea (P = 0.006). Although the polysaccharides of both species were composed of glucose and mannose, the molar ratio of the two monosaccharides was different suggested that the structures of the polysaccharide were different. The metabolomics results showed that there were no differences in the types of metabolites between B. striata and B. ochracea; however, there were differences in the content of these metabolites. Although there was no significant difference in the polysaccharide yields of B. striata and O. foliosa (P = 0.074) and the monosaccharide composition was the same (glucose and mannose), many different metabolites were screened out between them: 6 compounds such as C₃₆ H₃₄ O₁₁ existed only in B. striata, while substance C₃₉ H₅₄ O₂₂ was unique to O. foliosa. Therefore, based on the analysis of the polysaccharide content and monosaccharide composition, combined with phase metabolomics research, a preliminary distinction between B. striata, B. ochracea, and O. foliosa was achieved.

Comprehensive evaluation of Bletilla striata and its substitutes by combining phenotypic characteristic, chemical composition, and anti-melanogenic activity

Bletilla striata is a precious traditional Chinese medical herb with a wide range of applications in pharmacological and cosmetic fields. Because of the shortage of resources, Bletilla ochracea and Bletilla formosanare are also used as the substitutes. To distinguish the differences and homologies, the typical morphologic and microscopic characteristics of them were compared, and a UPLC fingerprint analysis coupled with chemometric methods were developed for characterization and quality evaluation of Bletillae Rhizoma. Gastrodin, protocatechuic acid, gymnoside V, blestrianol A, coelonin, gymnosides Ⅸ and batatasin II were identified as the potential chemical markers for comprehensive quality evaluation by ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). The anti-melanogenic activities of the three species were also compared for the first time in vivo using the zebrafish model, the results suggested that B. striata and its two substitutes had obvious anti-melanogenic activities, and they were not-toxic at depigmenting doses. Molecular docking studies revealed batatasin III, blestrianol A, coelonin, and gastrodin were possible multitarget compounds associated with melanogenesis suppression, which are important for their potential future medical application.

A novel fluorescence sensing strategy based on nanoparticles combined with spectral splicing and chemometrics for the recognition of Citrus reticulata 'Chachi' and its storage year

BACKGROUND

The fluorescence sensing method has been increasingly applied in food quality control because it is fast and sensitive. However, its application in quality evaluation is challenging. Using Citri Reticulatae Pericarpium (CRP; dried mandarin orange peel) as an example, we developed a simple and low-cost fluorescence sensing strategy based on nanoparticles combined with spectral splicing and chemometrics for quality evaluation. This method can recognize Citrus reticulata 'Chachi' (CRC) from other CRP cultivars and further identify the storage year.

RESULTS

Nanogold particles and cadmium telluride quantum dots were selected as nanosensors and mixed with aqueous extracts of CRP separately to produce fluorescence quenching spectra. Then, a simple spectral splicing procedure was applied to obtain spliced spectra comprising different combinations of the self-fluorescence and fluorescence quenching spectra of CRP samples. With the aid of partial least-squares discriminant analysis, the new strategy achieved recognition rates of 100% in distinguishing CRC samples from other CRP samples, as well as recognition rates of 100% for the training set and 98.04% for the prediction set in the discrimination of the storage year of CRC. The recognition mechanism is dominated by interactions between the nanoparticles and the fluorescent components in the CRP samples, but other components also have concurrent effects.

CONCLUSIONS

This novel fluorescence sensing strategy not only provides a new tool for the quality evaluation of CRC but also has good prospects for the authentication and traceability of other foods and herbs. Crucially, the developed method is convenient, simple and effective. © 2020 Society of Chemical Industry.

Evaluation of a multiple and global analytical indicator of batch consistency: traditional Chinese medicine injection as a case study

This paper evaluates a multiple and global analytical indicator of batch consistency in traditional Chinese medicine injections (TCMIs) via a chemometrics tool, which is more comprehensive to appraise quality consistency of different batches of injections than the traditional method of fingerprint similarity. A commonly used TCMI, Salviae miltiorrhizae and ligustrazine hydrochloride injection (SLI), was employed as a model. With the aid of a chemometrics tool (principal component analysis, PCA), evaluation of multiple and global analytical indicators of batch consistency, which included saccharides, phenolic acids and inorganic salts (18 indicators in total), was carried out to appraise the quality consistency of 13 batches of injection provided by the Guizhou Baite Pharmaceutical Co., Ltd. (Guizhou, China). Compared with the traditional HPLC-UV fingerprint similarity evaluation, the method proposed in the paper can more comprehensively and correctly reflect the quality consistency of different batches of injections. In this paper, the multi-index evaluation result showed poor batch consistency, which was more consistent with the determination results, while the fingerprint similarity evaluation results still showed good batch consistency. The HPLC-UV fingerprint reflects only substances with UV absorption, but it is not able to reflect substances without UV absorption or weak UV absorption, which leads to inappropriate conclusions. Therefore, quality consistency of injections can be effectively appraised by evaluation of multiple and global analytical indicators, instead of HPLC-UV fingerprint only. For visualizing the batch consistency of the multiple and global analytical indicators, a heat map was used to represent the fluctuation. Furthermore, critical indicator identification was also applied to select several indicators that should be paid more attention during the process of quality control of injection. And the analysis result showed that Na+, fructose (Fru), glucose (Glc), manninotriose (Man), danshensu (DSS) and salvianolic acid B (SAB) are the indicators that should be given more attention when controlling the quality of injections, also called critical quality control indicators. The proposed method provides a reference for the quality control of TCMIs and has broad application potential.

Chemometrics: a complementary tool to guide the isolation of pharmacologically active natural products

Chemometrics offers an important complementary tool to enhance the searching and isolation of bioactive natural products from natural sources.

Determination of adulterated gasoline using fluorescence emission-excitation matrices and multivariate calibration

Methanol gasoline, known as a new energy, has a certain degree of damage to automobile. The aim of this work was to identify and quantify the methanol in methanol gasoline using three-dimensional fluorescence spectroscopy technique combined with second order chemometric methods. Parallel factor analysis (PARAFAC) and self-weighted alternating trilinear decomposition (SWATLD) methods were used to analyse artificial samples. However, the obtained results by PARAFAC were not satisfactory. On the other hand, excellent prediction results were obtained when SWATLD model was applied, with recovery rate between 98.7 and 102.8%, and between 97.4 and 101.9% for two and three factor respectively. In order to verify the accuracy of the method, four real samples were predicted using SWATLD model with RMSEP between 0.1 μg/mL and 0.23 μg/mL.