Comprehensive feature-based molecular networking and metabolomics approaches to reveal the differences components in Cinnamomum cassia and Cinnamomum verum

In-depth characterization of cycloartane triterpenoids and discovery of species-specific markers from three Cimicifuga species guided by a strategy that integrates in-source fragment elimination, diagnostic ion recognition, and feature-based molecular networking

Characterization studies of the plant metabolome are crucial for revealing plant physiology, developing functional foods, and controlling quality. Mass spectrometry-based metabolite profiling allows unprecedented qualitative coverage of complex biological extract composition. However, the electrospray ionization used in metabolite profiling generates multiple artifactual signals for a single analyte, which makes it challenging to filter out redundant signals and organize the signals corresponding to abundant constituents. This study proposed a strategy integrating in-source fragments elimination, diagnostic ions recognition, and feature-based molecular networking (ISFE-DIR-FBMN) to simultaneously characterize cycloartane triterpenoids (CTs) from three medicinal Cimicifuga species. The results showed that 63.1 % of the measured ions were redundant. A total of 184 CTs were annotated, with 27.1 % being reported for the first time. It presents a promising approach to assess the composition of natural extracts, thus facilitating new ingredient registrations or natural-extracts-based drug discovery campaigns. Besides, chemometrics analysis of the three Cimicifuga species identified 32 species-specific markers, highlighting significant differences among them. The valuable information can enhance the sustainable utilization and further development of Cimicifuga resources. The codes involved in ISFE-DIR-FBMN are freely available on GitHub (https://github.com/LHJ-Group/ISFE-DIR-FBMN.git).

Feature-Based Molecular Network-Assisted Cannabinoid and Flavonoid Profiling of Cannabis sativa Leaves and Their Antioxidant Properties

Cannabis sativa (C. sativa) leaves are rich in cannabinoids and flavonoids, which play important antioxidant roles. Since the environmental factors may influence the accumulation of antioxidants in herbal medicines, which affects their activity, this study aimed to investigate the correlation between the chemical composition of C. sativa leaves and their geographical origin and antioxidant activity. Firstly, a high-resolution mass spectrometry method assisted by semi-quantitative feature-based molecular networking (SQFBMN) was established for the characterization and quantitative analysis of C. sativa leaves from various regions. Subsequently, antioxidant activity analysis was conducted on 73 batches of C. sativa leaves, and a partial least squares regression (PLS) model was employed to assess the correlation between the content of cannabinoids and flavonoids in the leaves and their antioxidant activity. A total of 16 cannabinoids and 57 flavonoids were annotated from C. sativa, showing a significant regular geographical distribution. The content of flavonoid-C glycosides in Sichuan leaves is relatively high, and their antioxidant activity is also correspondingly high. However, the leaves in Shaanxi and Xinjiang were primarily composed of flavonoid-O glycosides, and exhibited slightly lower antioxidant activity. A significant positive correlation (p < 0.001) was found between the total flavonoids and cannabinoids and the antioxidant activity of the leaves, and two flavonoids and one cannabinoid were identified as significant contributors.

Metabolites rapid-annotation in mice by comprehensive method of virtual polygons and Kendric mass loss filtering: A case study of Dendrobium nobile Lindl

With significant advancements in high-resolution mass spectrometry, there has been a substantial increase in the amount of chemical component data acquired from natural products. Therefore, the rapid and efficient extraction of valuable mass spectral information from large volumes of high-resolution mass spectrometry data holds crucial significance. This study illustrates a targeted annotation of the metabolic products of alkaloid and sesquiterpene components from Dendrobium nobile (D. nobile) aqueous extract in mice serum through the integration of an in-houses database, R programming, a virtual metabolic product library, polygonal mass defect filtering, and Kendrick mass defect strategies. The research process involved initially establishing a library of alkaloids and sesquiterpenes components and simulating 71 potential metabolic reactions within the organism using R programming, thus creating a virtual metabolic product database. Subsequently, employing the virtual metabolic product library allowed for polygonal mass defect filtering, rapidly screening 1705 potential metabolites of alkaloids and 3044 potential metabolites of sesquiterpenes in the serum. Furthermore, based on the chemical composition database of D. nobile and online mass spectrometry databases, 95 compounds, including alkaloids, sesquiterpenes, and endogenous components, were characterized. Finally, utilizing Kendrick mass defect analysis in conjunction with known alkaloids and sesquiterpenes targeted screening of 209 demethylation, methylation, and oxidation products in phase I metabolism, and 146 glucuronidation and glutathione conjugation products in phase II metabolism. This study provides valuable insights for the rapid and accurate annotation of chemical components and their metabolites in vivo within natural products.

Chemical characterization and comparative analysis of different parts of Cocculus orbiculatus through UHPLC-Q-TOF-MS

Cocculus orbiculatus (L.) DC. (C. orbiculatus) is a medicinal herb valued for its dried roots with anti-inflammatory, analgesic, diuretic, and other therapeutic properties. Despite its traditional applications, chemical investigations into C. orbiculatus remain limited, focusing predominantly on alkaloids and flavonoids. Furthermore, the therapeutic use of C. orbiculatus predominantly focuses on the roots, leaving the stems, a significant portion of the plant, underutilized. This study employed ultra-high performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS/MS) with in-house and online databases for comprehensive identification of components in various plant parts. Subsequently, untargeted metabolomics was employed to analyze differences in components across different harvest periods and plant sections of C. orbiculatus, aiming to screen for distinct components in different parts of the plant. Finally, metabolomic analysis of the roots and stems, which contribute significantly to the plant's weight, was conducted using chemometrics, including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), orthogonal partial least squares discriminant analysis (OPLS-DA), and heatmaps. A total of 113 components, including alkaloids, flavonoids, and organic acids, were annotated across the root, stem, leaf, flower, and fruit, along with numerous previously unreported compounds. Metabolomic analyses revealed substantial differences in components between the root and stem compared to the leaf, flower, and fruit during the same harvest period. PLS-DA and OPLS-DA annotated 10 differentiating components (VIP > 1.5, P < 0.05, FC > 2 or FC < 0.67), with 5 unique to the root and stem, exhibiting lower mass spectrometric responses. This study provided the first characterization of 113 chemical constituents in different parts of C. orbiculatus, laying the groundwork for pharmacological research and advocating for the enhanced utilization of its stem.

Development and application of mass spectrometric molecular networking for analyzing the ingredients of areca nut

Areca nut (Areca catechu L.) is commonly consumed as a chewing food in the Asian region. However, the investigations into the components of areca nut are limited. In this study, we have developed an approach that combines mass spectrometry with feature-based molecular network to explore the chemical characteristics of the areca nut. In comparison to the conventional method, this technique demonstrates a superior capability in annotating unknown compounds present in areca nut. We annotated a total of 52 compounds, including one potential previously unreported alkaloid, one carbohydrate, and one phenol and confirmed the presence of 7 of them by comparing with commercial standards. The validated method was used to evaluate chemical features of areca nut at different growth stages, annotating 25 compounds as potential biomarkers for distinguishing areca nut growth stages. Therefore, this approach offers a rapid and accurate method for the component analysis of areca nut.

An improved strategy for identification and annotation of easily in-sourced dissociation diterpene lactones from plant natural products: Taking Andrographis paniculata (Burm. f.) as an example

RATIONALE

Diterpene lactones (DL) in Andrographis paniculata (AP) are known as "natural antibiotics" for their excellent antibacterial activity. During mass spectrometry (MS) analysis, the hydroxyl groups in the AP DL skeleton are prone to neutral loss of H₂ O, producing high in-source fragment peaks and affecting the characterization of these components.

METHODS

Mass tags were applied during the MS data acquisition step, and special adduct ion form was used to guide the data processing and characterization steps. Besides, the total number of characterized AP DLs significantly increased when combining the number of neutrally lost H₂ O from AP DLs, incorporating information on the diagnostic ions, and adopting molecular networks generated with the Global Natural Products Social Molecular Networking database.

RESULTS

Ninety-nine DLs, comprising 6 monohydroxyl groups, 20 dihydroxyl groups, 27 trihydroxy groups, and 46 DLs with more than 3 hydroxyl groups, were characterized from AP. In addition, based on the characteristic fragments in the product ions (C₃ H₄ , Δm/z = 40.03 Da), it could be assumed that 90 DLs had the C19-OH structure among the identified DLs. The current study provides a new approach for collecting, processing, and characterizing MS analysis of natural DLs prone to in-source fragmentation.

CONCLUSIONS

MS characterization of AP DLs was significantly improved, and many potential new compounds were identified in AP. This characterization provides new methods for the purification and identification of AP DLs.

The chemistry and activity-orientedcharacterization of isoflavones difference between roots of Pueraria lobata and P. thomsonii guided by feature-based molecular networking

Isoflavones are important chemical components in Pueraria species with various biological activities. This study proposed an integrated strategy combining feature-based molecular networking (FBMN), chemometrics and activity evaluation for isoflavone analysis in the roots of P. lobate (PLR) and P. thomsonii (PTR). Based on the strategy, a total of 68 isoflavones were annotated in the two Pueraria species, and 11 significant difference isoflavones between PLR and PTR were identified by chemometric methods. Additionally, the correlation coefficient between the characteristic isoflavones and hypoglycemic activity were calculated, and 7 isoflavones were further confirmed as bioactive marker compounds. This approach provided guidance for the discovery of active markers among different products.

Study of the Chemical Profile and Anti-Fungal Activity against Candida auris of Cinnamomum cassia Essential Oil and of Its Nano-Formulations Based on Polycaprolactone

BACKGROUND

Candida auris represents an emerging pathogen that results in nosocomial infections and is considered a serious global health problem. The aim of this work was to evaluate the in vitro antifungal efficacy of Cinnamomum cassia essential oil (CC-EO) pure or formulated in polycaprolactone (PCL) nanoparticles against ten clinical strains of C. auris.

METHODS

nanoparticles of PCL were produced using CC-EO (nano-CC-EO) and cinnamaldehyde (CIN) through the nanoprecipitation method. The chemical profile of both CC-EO and nano-CC-EO was evaluated using SPME sampling followed by GC-MS analysis. Micro-broth dilution tests were performed to evaluate both fungistatic and fungicidal effectiveness of CC-EO and CIN, pure and nano-formulated. Furthermore, checkerboard tests to evaluate the synergistic action of CC-EO or nano-CC-EO with micafungin or fluconazole were conducted. Finally, the biofilm disrupting activity of both formulations was evaluated.

RESULTS

GC-MS analysis shows a different composition between CC-EO and nano-CC-EO. Moreover, the microbiological analyses do not show any variation in antifungal effectiveness either towards the planktonic form (MIC_CC-EO = 0.01 ± 0.01 and MIC_nano-CC-EO = 0.02 ± 0.01) or the biofilm form. No synergistic activity with the antifungal drugs tested was found.

CONCLUSIONS

both CC-EO and nano-CC-EO show the same antimicrobial effectiveness and are potential assets in the fight against C. auris.