Qualitative and quantitative analysis of Teucrium polium essential oil components by GC-MS coupled with MCR and PARAFAC methods

Tensor methods in data analysis of chromatography/mass spectroscopy-based plant metabolomics

Plant metabolomics is an important research area in plant science. Chemometrics is a useful tool for plant metabolomic data analysis and processing. Among them, high-order chemometrics represented by tensor modeling provides a new and promising technical method for the analysis of complex multi-way plant metabolomics data. This paper systematically reviews different tensor methods widely applied to the analysis of complex plant metabolomic data. The advantages and disadvantages as well as the latest methodological advances of tensor models are reviewed and summarized. At the same time, application of different tensor methods in solving plant science problems are also reviewed and discussed. The reviewed applications of tensor methods in plant metabolomics cover a wide range of important plant science topics including plant gene mutation and phenotype, plant disease and resistance, plant pharmacology and nutrition analysis, and plant products ingredient characterization and quality evaluation. It is evident from the review that tensor methods significantly promote the automated and intelligent process of plant metabolomics analysis and profoundly affect the paradigm of plant science research. To the best of our knowledge, this is the first review to systematically summarize the tensor analysis methods in plant metabolomic data analysis.

Towards a better understanding of commonly used medicinal plants from Turkiye: Detailed phytochemical screening and biological activity studies of two Teucrium L. species with in vitro and in silico approach

ETHNOPHARMACOLOGICAL RELEVANCE

Since ancient times, Teucrium L. species have been among the most commonly used traditional medicinal plants mainly in the Mediterranean region. From tackling gastrointestinal problems to maintaining the healthy functioning of endocrine glands, and from treating malaria to severe dermatological disorders, Teucrium species are known to have extensive therapeutic applications. Teucrium polium L. and Teucrium parviflorum Schreb. are the two members of the genus that have been used in Turkish folk medicine for various medicinal purposes.

AIM OF THE STUDY

To determine the phytochemical compositions of the essential oils and ethanol extracts of Teucrium polium and Teucrium parviflorum collected from different locations in Turkiye along with the investigation of in vitro antioxidant, anticancer, antimicrobial activities, and both in vitro and in silico enzyme inhibitory activities of the extracts.

MATERIALS AND METHODS

Ethanol extracts of Teucrium polium aerial parts and roots, and aerial parts of Teucrium parviflorum were prepared. Volatile profiling of the essential oils by GC-MS, phytochemical profiling of the ethanol extracts by LC-HRMS, antioxidant activity by DPPH radical scavenging, ABTS cation radical scavenging, CUPRAC, and metal chelating activity assays, anticholinesterase, antityrosinase, antiurease, activities by different enzyme inhibitory activity assays, anticancer activity by SRB cell viability assay, and antimicrobial activity against a standard panel of bacteria and fungi by the microbroth dilution technique. Molecular docking studies were performed by Autodock Vina (Ver. 1.1.2).

RESULTS

The studied extracts were found to be quite rich in various biologically important volatile and phenolic compounds. (-)-Epigallocatechin gallate, which is a molecule renowned for having great therapeutic potential, was the major compound of all extracts. Teucrium polium aerial parts extract was revealed as a great source for naringenin with 16327 ± 685.23 μg/g extract. All extracts exerted significant antioxidant activity by different methods. All extracts demonstrated antibutrylcholinesterase, antityrosinase, and antiurease activities by in vitro and in silico assays. Teucrium polium roots extract stood out with remarkable tyrosinase and urease inhibitory and cytotoxic activities.

CONCLUSION

The obtained results from this multi-disciplinary study proves that the traditional use of these two Teucrium species is justified, and the mechanisms behind are enlightened.

Saffron essential oil ameliorates CUMS-induced depression-like behavior in mice via the MAPK-CREB1-BDNF signaling pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Saffron, the dried stigma of Crocus sativus L., has a long history of use in the treatment of depression in traditional Chinese medicine and Islamic medicine. The unique aroma of saffron, primarily derived from its volatile oil, has been widely used by folk to mitigate anxiety and depression via sniffing because the aroma of saffron has a pleasant and invigorating effect.

AIM OF THE STUDY

This study aimed to investigate the antidepressant effect and the underlying mechanism of saffron essential oil (SEO) in mice exposed to chronic unpredictable mild stress (CUMS).

MATERIALS AND METHODS

In this study, compounds of SEO were identified using gas chromatography-mass spectrometry analysis, while network pharmacology was used to predict potential active compounds, antidepressant targets, and related signaling pathways of SEO. The CUMS depression model was further used to explore the therapeutic effect and possible mechanism of SEO. During the modeling period, mice were regularly administered fluoxetine (3.6 mg/kg, i.g.) or diluted SEO (2%, 4%, and 6% SEO, inhalation). The antidepressant and neuroprotective effects of SEO were evaluated by behavior tests (the open field test, the sucrose preference test, the tail suspension test, and the forced swimming test), hematoxylin-eosin staining, and Nissl staining. The enzyme-linked immunosorbent assay kits were used to measure dopamine (DA), 5-serotonin (5-HT), brain-derived neurotrophic factor (BDNF), and γ-aminobutyric acid (GABA) levels in serum. The relative abundance of Raf1, MEK1, P-ERK1/2/ERK1/2, P-CREB1/CREB1, BDNF, and P-Trk B/Trk B in the hippocampus was determined using western blot (WB).

RESULTS

According to the network pharmacology analysis, seven active SEO compounds mediated 113 targets related to depression treatment, most of which were enriched in the 5-HT synapse, calcium signaling pathway, and cAMP signaling pathway. In vivo experiments indicated that fluoxetine and SEO improved depression-like behaviors in depressed mice. The levels of 5-HT, DA, BDNF, and GABA in serum increased significantly. Histopathological examinations revealed that fluoxetine and SEO ameliorated neuronal damage in the hippocampus. WB analysis showed that the relative expressions of Raf1, MEK1, P-ERK1/2/ERK1/2, P-CREB1/CREB1, BDNF, and P-Trk B/Trk B were significantly higher in the fluoxetine and SEO groups than in the CUMS group.

CONCLUSION

Overall, these findings suggest that SEO significantly alleviates the depressive symptoms in CUMS exposed mice and partially restores hippocampal neuronal damage. Meanwhile, the best efficacy was observed in 4% SEO. Furthermore, the antidepressant mechanism of SEO is primarily dependent on the regulation of the MAPK-CREB1-BDNF signaling pathway.

Vasorelaxant Mechanism of Herbal Extracts from Mentha suaveolens, Conyza canadensis, Teucrium polium and Salvia verbenaca in the Aorta of Wistar Rats

Mentha suaveolens (MS), Conyza canadensis (CC), Teucrium polium (TP) and Salvia verbenaca (SV) are used in Morocco to treat hypertension. Our aim was to characterize the composition and vasoreactivity of extracts of MS, CC, TP and SV. The chemical compositions of aqueous extracts of MS, SV and TP, and of a hydromethanolic extract of CC, were identified by HPLC-DAD. The vasoreactive effect was tested in rings of the thoracic aorta of female Wistar rats (8-14 weeks-old) pre-contracted with 10 µM noradrenaline, in the absence or presence of L-NAME 100 µM, indomethacin 10 µM or atropine 6 µM, to inhibit nitric oxide synthase, cyclooxygenase or muscarinic receptors, respectively. L-NAME and atropine decreased the vasorelaxant effect caused by low concentrations of MS. Atropine and indomethacin decreased the vasorelaxant effect of low concentrations of SV. High concentrations of MS or SV and the effect of SV and TP were not altered by any antagonist. The activation of muscarinic receptors and NO or the cyclooxygenase pathway underlie the vasorelaxant effect of MS and SV, respectively. Neither of those mechanisms underlines the vasorelaxant effect of CC and TP. These vasorelaxant effect might support the use of herbal teas from these plants as anti-hypertensives in folk medicine.

A Review of the Phytochemistry, Traditional Uses and Biological Activities of the Essential Oils of Genus Teucrium

The genus Teucrium is a large and polymorphic genus of the Lamiaceae family distributed in mild climate zones, particularly in the Mediterranean basin and Central Asia. Studies of nonvolatile constituents of Teucrium species showed that they are a rich source of neo-clerodane diterpenoids, considered as chemotaxonomic markers of the genus. In addition to the nonvolatile metabolites, there has been a large interest in the essential oils of this genus. In this review, a complete survey of the chemical composition and biological properties of the essential oils isolated from Teucrium taxa is provided. In traditional medicine, since ancient times, species of this genus have been widely implemented for their biological properties, including antimicrobial, anti-inflammatory, antispasmodic, insecticidal, anti-malaria, etc. Therefore, a complete review of all of the traditional uses of Teucrium taxa are also reported.

Chemical Composition, Antioxidant, Antimicrobial, and Phytotoxic Potential of Eucalyptus grandis × E. urophylla Leaves Essential Oils

Eucalyptus grandis × E. urophylla was a unique hybridization in China. However, the chemical and pharmacological properties were rarely reported. Therefore, in this work, we used a steam distillation method to obtain essential oils from leaves of E. grandis × E. urophylla, and further evaluated the antioxidant, antimicrobial, and phytotoxic potential of the essential oil. Gas chromatography mass spectrometry (GC-MS) was applied to investigate the chemical composition of E. grandis × E. urophylla essential oil (EEO) and the results showed that the main components of EEO were monoterpenes followed by sesquiterpenes. Among them, α-pinene accounted about 17.02%. EEO could also well scavenge 1,1-diphenyl-2-picrylhydrazyl (DPPH) and 2, 2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) free radicals showing a good free radical clearance ability. In addition, EEO efficiently inhibited the growth of six kinds of bacteria as well as seven kinds of plant pathogens, especially Salmonella typhimurium and Colletotrichum gloeosporioides. Moreover, the seedling germination of Raphanus sativus, Lactuca sativa, Lolium perenne, and Bidens pilosa was significantly suppressed by EEO, thus, indicating essential oils from eucalyptus possessed an excellent phytotoxic activity. This study may give a better understanding on EEO and provide a pharmacological activities analysis contributing to the further research of EEO as a functional drug in agronomic and cosmetic industries.

Data handling and data analysis in metabolomic studies of essential oils using GC-MS

Gas chromatography electron impact ionization mass spectrometry (GC-EI-MS) has been, and remains, the most widely applied analytical technique for metabolomic studies of essential oils. GC-EI-MS analysis of complex samples, such as essential oils, creates a large volume of data. Creating predictive models for such samples and observing patterns within complex data sets presents a significant challenge and requires application of robust data handling and data analysis methods. Accordingly, a wide variety of software and algorithms has been investigated and developed for this purpose over the years. This review provides an overview and summary of that research effort, and attempts to classify and compare different data handling and data analysis procedures that have been reported to-date in the metabolomic study of essential oils using GC-EI-MS.

Teucrium Polium Plant Extract Provokes Substantial Cytotoxicity at the Early Stage of Embryonic Development

The aim of this study is to explore the outcome of Teucrium polium (TP) medicinal plant consumption on the early stage of fetal development. We used the chicken embryo at 3 days of incubation as a model to evaluate the effect of TP plant extract during embryogenesis. In addition, quantitative polymerase chain reaction (qPCR) was applied to explore the expression of six genes related to cell proliferation, apoptosis, sur-vival, angiogenesis, and migration. Our data revealed that TP exposure inhibits angiogenesis of the chicken embryo and its chorioallantoic membrane. In addition, we found that TP extract significantly harms the normal development of the embryos since around 95% of TP-exposed embryos died after 1-3 days of treatment. Macroscopic examination did not show any anomalies in these embryos. However, qPCR analysis of activation transcription factor-3, B-cell lymphoma-2, caspase 8, inhibin subunit beta A, vascular endothelial growth factor-C, and Cadherin-6 type-2 genes revealed that these genes are considerably deregulated in heart and brain tissues from TP-exposed embryos in comparison with their matched tissues from unexposed ones. Our study implies that TP plant can have very toxic effects on the early stage of the embryo. Therefore, it is important to alert expectant women to avoid the use of this medicinal plant during pregnancy.

Automated supervised learning pipeline for non-targeted GC-MS data analysis

Non-targeted analysis is nowadays applied in many different domains of analytical chemistry such as metabolomics, environmental and food analysis. Conventional processing strategies for GC-MS data include baseline correction, feature detection, and retention time alignment before multivariate modeling. These techniques can be prone to errors and therefore time-consuming manual corrections are generally necessary. We introduce here a novel fully automated approach to non-targeted GC-MS data processing. This new approach avoids feature extraction and retention time alignment. Supervised machine learning on decomposed tensors of segmented chromatographic raw data signal is used to rank regions in the chromatograms contributing to differentiation between sample classes. The performance of this novel data analysis approach is demonstrated on three published datasets.