Ultra-high performance liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry and database-driven automatic peak annotation for the rapid profiling and characterization of the multicomponents from stephaniae tetrandrae radix (Fang-Ji)

An automatic LC-MS/MS data analysis workflow for herbal compound annotation with AutoAnnotatoR: A case study of ten botanical origins of Fritillaria species

BACKGROUND

Despite the widespread implementation of analytical hardware capable of recording large-scale datasets for botanical natural products, the data processing procedures for compound annotation remain a bothersome obstacle that demand a tremendous amount of time and expert knowledge.

METHODS

Herein, an automatic LC-MS/MS data analysis workflow with AutoAnnotatoR was introduced for the compound annotation of plant derived natural products, which has the merits of great efficiency, high accuracy, saving time and simplified process. This procedure enabled automatic matching of MS2 data with characteristic fragment ions, as well as MS1 data with compound libraries, which improves the accuracy of structural elucidation. Notably, the optimization of collision energy for each target ion was successfully performed for the first time, facilitating the acquisition of comprehensive fragmentation information.

RESULTS

The automatic analysis workflow with AutoAnnotatoR was successfully applied for the annotation of alkaloids from 10 botanical origins of Fritillaria species. Consequently, a total of 2684 chemical constituents were tentatively characterized, with 23 components being unambiguously validated by reference standards and 2434 being probable novel chemicals.

CONCLUSION

The entire data analysis procedure takes only a few hours, vastly improving analysis speed while assuring high accuracy. This method provides a powerful tool for the rapid and precise annotation of complex natural products. The workflow is publicly accessible on Github as an open-source R package called AutoAnnotatoR (https://github.com/anyaling2022/AutoAnnotatoR).

Metabolomics for Clinical Biomarker Discovery and Therapeutic Target Identification

As links between genotype and phenotype, small-molecule metabolites are attractive biomarkers for disease diagnosis, prognosis, classification, drug screening and treatment, insight into understanding disease pathology and identifying potential targets. Metabolomics technology is crucial for discovering targets of small-molecule metabolites involved in disease phenotype. Mass spectrometry-based metabolomics has implemented in applications in various fields including target discovery, explanation of disease mechanisms and compound screening. It is used to analyze the physiological or pathological states of the organism by investigating the changes in endogenous small-molecule metabolites and associated metabolism from complex metabolic pathways in biological samples. The present review provides a critical update of high-throughput functional metabolomics techniques and diverse applications, and recommends the use of mass spectrometry-based metabolomics for discovering small-molecule metabolite signatures that provide valuable insights into metabolic targets. We also recommend using mass spectrometry-based metabolomics as a powerful tool for identifying and understanding metabolic patterns, metabolic targets and for efficacy evaluation of herbal medicine.

A quantitative chemomics strategy for the comprehensive comparison of Murraya paniculata and M. exotica using liquid chromatography coupled with mass spectrometry

Murrayae Folium et Cacumen (MFC) is a traditional Chinese medicine (TCM) derived from two plant species, Murraya exotica L. and Murraya paniculata (L.) Jack, as recorded in the Chinese Pharmacopoeia. However, there is no research available on the comprehensive analysis and comparison of the chemical constituents of these two species. In the present study, an integrated LC-MS-based quantitative metabolome strategy was proposed to conduct a comprehensive and in-depth qualitative and quantitative analysis and comparison of the chemome of M. exotica and M. paniculata. Firstly, the universal chemical information of two plants was obtained by quadrupole-time-of-flight mass spectrometry (Q-TOF-MS) combined with hybrid triple quadrupole-linear ion trap mass spectrometry (Qtrap-MS). Subsequently, a UNIFI in house database, the proposed fragmentation patterns, and a quantitative structure chromatographic retention relationship (QSRR) model were integrated for the rapid, comprehensive, and accurate structural elucidation of the chemical constituents of these two species. Thirdly, a large-scale quantitation method was established using scheduled multiple reaction monitoring mode (sMRM) and 76 primary components were selected as quantitative markers for the method validation. The obtained dataset was then subjected for multivariate statistical analysis to comprehensive comparison of these two plants. As a result, a total of 209 and 212 compounds were identified from M. exotica and M. paniculata, respectively. Among them, 103 common constituents were disclosed in both plants. The multivariate statistical analysis and absolute quantitative analysis revealed noticeable differences in the contents of specific chemical constituents between these two plants. The higher quantity constituents in M. exotica are 7-methoxycoumarins, while polymethoxylated flavonoids are the major constituents in M. paniculata. The common compounds accounted for approximately 80 % of the quantitative components in both plants, which provides a theoretical basis for their common use as the official source of MFC. In sum, the established quantitative chemomics strategy supplies an effective means for comprehensive chemical comparison of multi-source TCMs.

An integrated strategy for characterization of chemical constituents in Stephania tetrandra using LC-QTOF-MS/MS and the target isolation of two new biflavonoids

LC-MS has been a widely used analytical technique for identification of natural compounds. However, sophisticated and laborious data analysis is required to identify chemical components, especially new compounds, from a large LC-MS dataset. The aim of this study is to develop an integrated data-mining strategy that combines molecular networking (MN), in-house polygonal mass defect filtering (MDF), and diagnostic fragment ion filtering (DFIF) to identify phytochemicals in Stephania tetrandra based on LC-MS data. S. tetrandra samples were prepared by matrix solid-phase dispersion extraction methods and then raw MS spectra were acquired using LC-QTOF-MS/MS. MN and in-house polygonal MDF classified the compounds roughly. Modified DFIF were then used in succession to place each spectrum into a specific class. Finally, the exact structures were deduced by fragmentation pathways and related botanical biogenesis, with the help of the narrowed classification from MN and MDF. The total workflow was a combination of data filtering and identification methods for rapid characterization of known compounds (dereplication) and discovery of new compounds. Consequently, 144 compounds were identified or tentatively identified in the aerial parts and roots of S. tetrandra, including 11 potentially new compounds and 63 compounds first identified in this species. Among 144 compounds, 61 were from the aerial parts exclusively, 8 were from the roots exclusively, and 75 were found in both parts. Furthermore, two new biflavonoids were isolated with the guide of LC-MS analysis and structurally elucidated by spectroscopic methods. In conclusion, the proposed data-mining strategy based on LC-MS can be used to profile chemical constituents with high efficiency and guide the isolation of new compounds from medicinal plants. The comparison of the components of the aerial parts and roots of S. tetrandra would be helpful for the rational utilization of the medicinal plant.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

Enhanced profiling and quantification of ginsenosides from mountain-cultivated ginseng and comparison with garden-cultivated ginseng

Panax ginseng can be generally divided into mountain-cultivated ginseng (MCG) and garden-cultivated ginseng (GCG). The market price of MCG is significantly higher than that of GCG. However, the chemical compositions of MCG and the differences from GCG remained unclear. In this study, an integrated strategy combing an offline two-dimensional liquid chromatography separation, LTQ-orbitrap dual mode acquisition, and Q-trap full quantification/quasi-quantification was proposed to explore and compare the chemical compositions of MCG. Consequently, 559 ginsenosides were characterized, among which 437 ginsenosides were in-depth characterized with α-chain and β-chain annotated. Subsequently, enhanced quantification of 213 ginsenosides was conducted in 57 batches of MCG and GCG. Ginsenosides were found more abundant in MCG than GCG. In addition, 25-year-old MCG could be distinctly differentiated from 15/20-year-old MCG. This strategy facilitated the enhanced profiling and comparison of ginsenosides, improved the quality control tactics of MCG and provided a reference approach for other ginseng related products.

Analysis of the absorbed constituents and mechanism of liquidambaris fructus extract on hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) refers to one of the top 10 cancers in terms of morbidity and mortality globally, seriously influencing people’s lives. First recorded in Compendium of Materia Medica, liquidambaris fructus (LF) generates definite anti-liver tumor effect. However, its effective substances and mechanism remain to be elucidated.

Methods: Serum pharmacochemistry and UPLC-QTOF-MS technologies were employed to explore the plasma of rats after intragastric administration of liquidambaris fructus extract (LFE) in order to find the active ingredients. Subsequently, DEN-induced rat liver cancer model was established with the purpose of investigating the anti-tumor activity of LFE from physiological, pathological and biochemical aspects. Finally, non-target metabonomics combined with q-PCR and Western blot methods were adopted for revealing the mechanism.

Results: Totally 11 prototype blood transfused ingredients, including imperatorin and phellopterin were detected. LFE presents excellent impact on enhancing the quality of life, prolonging the life cycle, reducing inflammatory reaction, protecting hepatocytes, improving body immunity and killing liver tumor cells. Altogether 82 endogenous differential metabolites were found in metabonomics, suggesting that LFE can treat HCC by acting on key targets of PTEN/PI3K/Akt pathway and fatty acid metabolism. Further research also verified that LFE can upregulate the relative expression levels of PTEN, PDCD4, Caspase 9, Caspase 3, Bax and Bad as well as lower the relative expression levels of PI3K, AKT, VEGFA and Bcl-2.

Conclusion: This study revealed the pharmacodynamic material basis of LFE in the treatment of HCC, and from the perspective of metabolomics proved that the effects of inhibiting the growth of tumor cells, promoting tumor cell apoptosis, reducing inflammatory reaction, protecting hepatocytes, improving the survival state of tumor rats, and prolonging the life cycle are related to its impact on PTEN/PI3K/Akt, fatty acid metabolism and other key signal pathways.

Integrating Enhanced Profiling and Chemometrics to Unveil the Potential Markers for Differentiating among the Leaves of Panax ginseng, P. quinquefolius, and P. notoginseng by Ultra-High Performance Liquid Chromatography/Ion Mobility-Quadrupole Time-of-Flight Mass Spectrometry

The leaves of Panax species (e.g., Panax ginseng-PGL, P. quinquefolius-PQL, and P. notoginseng-PNL) can serve as a source for healthcare products. Comprehensive characterization and unveiling of the metabolomic difference among PGL, PQL, and PNL are critical to ensure their correct use. For this purpose, enhanced profiling and chemometrics were integrated to probe into the ginsenoside markers for PGL/PQL/PNL by ultra-high performance liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (UHPLC/IM-QTOF-MS). A hybrid scan approach (HDMSE-HDDDA) was established achieving the dimension-enhanced metabolic profiling, with 342 saponins identified or tentatively characterized from PGL/PQL/PNL. Multivariate statistical analysis (33 batches of leaf samples) could unveil 42 marker saponins, and the characteristic ginsenosides diagnostic for differentiating among PGL/PQL/PNL were primarily established. Compared with the single DDA or DIA, the HDMSE-HDDDA hybrid scan approach could balance between the metabolome coverage and spectral reliability, leading to high-definition MS spectra and the additional collision-cross section (CCS) useful to differentiate isomers.

A Strategy for Identification and Structural Characterization of Compounds from Plantago asiatica L. by Liquid Chromatography-Mass Spectrometry Combined with Ion Mobility Spectrometry

Plantago asiatica L. (PAL) as a medicinal and edible plant is rich in chemical compounds, which makes the systematic and comprehensive characterization of its components challenging. In this study, an integrated strategy based on three-dimensional separation including AB-8 macroporous resin column chromatography, ultra-high performance liquid chromatography–quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF MS), and ultra-high performance liquid chromatography-mass spectrometry with ion-mobility spectrometry (UHPLC-IM-MS) was established and used to separate and identify the structures of compounds from PAL. The extracts of PAL were firstly separated into three parts by AB-8 macroporous resin and further separated and identified by UHPLC-Q-TOF MS and UHPLC-IM-MS, respectively. Additionally, UHPLC-IM-MS was used to identify isomers and coeluting compounds, so that the product ions appearing at the same retention time (RT)can clearly distinguish where the parent ion belongs by their different drift times. UNIFI software was used for data processing and structure identification. A total of 86 compounds, including triterpenes, iridoids, phenylethanoid glycosides, guanidine derivatives, organic acids, and fatty acids, were identified by using MS information and fragment ion information provided by UHPLC-Q-TOF MS and UHPLC-IM-MS. In particular, a pair of isoforms of plantagoside from PAL were detected and identified by UHPLC-IM-MS combined with the theoretical calculation method for the first time. In conclusion, the AB-8 macroporous resin column chromatography can separate the main compounds of PAL and enrich the trace compounds. Combining UHPLC-IM-MS and UHPLC-Q-TOF MS can obtain not only more fragments but also their unique drift times and RT, which is more conducive to the identification of complex systems, especially isomers. This proposed strategy can provide an effective method to separate and identify chemical components, and distinguish isomers in the complex system of traditional Chinese medicine (TCM).

Systematical characterization and comparison of saponins in Achyranthes bidentata Blume and its three analogous species

INTRODUCTION

Achyranthes bidentata Blume (AB) has been used for a long time and is recorded in the Chinese Pharmacopoeia 2020 edition. It is commonly confused with Achyranthes aspera Linn (AA), Cyathula officinalis Kuan (CO) and Cyathula capitata (Wall.) Moq. (CC), belonging to the Achyranthes and Cyathula genera of the Amaranthaceae family. It is of great significance to recognize and distinguish chemical components of AB, AA, CO and CC.

OBJECTIVE

The purpose of this study was to develop an analytical method for in-depth characterization and comparison of saponins in AB, AA, CO and CC.

METHODS

The extracts of AB, AA, CO and CC were analyzed by an RP × RP (C18 × Phenyl-Hexyl) 2D LC system, eluted by acidic × ion pair mobile phases and detected by high resolution mass spectrometry. Fragmentation patterns of saponins were elucidated and proposed according to reference compounds or literature reports.

RESULTS

As a result, 839 saponins consisting of 81, 415, 99 and 392 components corresponding to AB, AA, CO and CC, respectively, were characterized, including 594 potentially new saponins. Meanwhile, 29 kinds of aglycones were elucidated, among which 25 were new ones. Besides, 14, 91, 37 and 174 characteristic potential quality markers with MS intensities exceeding 10,000 were found in AB, AA, CO and CC, respectively.

CONCLUSION

This comprehensive study not only expands our knowledge of the types of saponins in Achyranthes and Cyathula, but also reveals the differences among four kinds of analogous herbs (AB, AA, CO and CC), which facilitates the quality control of these herbal medicines in the future.