The rhizome of Atractylodes lancea is extensively used in the practice of Traditional Chinese Medicine because of its broad pharmacological activities. This study was designed to characterize the transcriptome profiling of the rhizome and leaf of Atractylodes lancea in an attempt to uncover the molecular mechanisms regulating rhizome formation and growth. Over 270 million clean reads were assembled into 92,366 unigenes, 58% of which are homologous with sequences in public protein databases (NR, Swiss-Prot, GO, and KEGG). Analysis of expression levels showed that genes involved in photosynthesis, stress response, and translation were the most abundant transcripts in the leaf, while transcripts involved in stress response, transcription regulation, translation, and metabolism were dominant in the rhizome. Tissue-specific gene analysis identified distinct gene families active in the leaf and rhizome. Differential gene expression analysis revealed a clear difference in gene expression pattern, identifying 1,518 up-regulated genes and 3,464 down-regulated genes in the rhizome compared with the leaf,, including a series of genes related to signal transduction, primary and secondary metabolism. Transcription factor (TF) analysis identified 42 TF families, with 67 and 60 TFs up-regulated in the rhizome and leaf, respectively. A total of 104 unigenes were identified as candidates for regulating rhizome formation and development. These data offer an overview of the gene expression pattern of the rhizome and leaf and provide essential information for future studies on the molecular mechanisms of controlling rhizome formation and growth. The extensive transcriptome data generated in this study will be a valuable resource for further functional genomics studies of A. lancea.

Chrysanthemum indicum var. aromaticum (CIA) is an endemic plant that occurs only in the high mountain areas of the Shennongjia Forest District in China. The whole plant, in particular the flowers of CIA, have intense fragrance, making it a novel resource plant for agricultural, medicinal, and industrial applications. However, the volatile metabolite emissions in relation to CIA flower development and the molecular mechanisms underlying the generation of floral scent remain poorly understood. Here, integrative metabolome and transcriptome analyses were performed to investigate floral scent-related volatile compounds and genes in CIA flowers at three different developmental stages. A total of 370 volatile metabolites, mainly terpenoids and esters, were identified, of which 89 key differential metabolites exhibited variable emitting profiles during flower development. Transcriptome analysis further identified 8,945 differentially expressed genes (DEGs) between these samples derived from different flower developmental stages and KEGG enrichment analyses showed that 45, 93, and 101 candidate DEGs associated with the biosynthesis of phenylpropanoids, esters, and terpenes, respectively. Interestingly, significant DEGs involved into the volatile terpenes are only present in the MEP and its downstream pathways, including those genes encoding ISPE, ISPG, FPPS, GPPS, GERD, ND and TPS14 enzymes. Further analysis showed that 20 transcription factors from MYB, bHLH, AP2/EFR, and WRKY families were potentially key regulators affecting the expressions of floral scent-related genes during the CIA flower development. These findings provide insights into the molecular basis of plant floral scent metabolite biosynthesis and serve as an important data resources for molecular breeding and utilization of CIA plants in the future.

As a medicine-food homology (MFH) plant, golden-flowered tea (Camellia nitidissima Chi, CNC) has many different pharmacologic activities and is known as “the queen of the tea family” and “the Panda of the Plant world”. Several studies have revealed the pharmacologic effects of CNC crude extract, including anti-tumor, anti-oxidative and hepatoprotective activity. However, there are few studies on the anti-tumor active fractions and components of CNC, yet the underlying mechanism has not been investigated. Thus, we sought to verify the anti-non-small cell lung cancer (NSCLC) effects of four active fractions of CNC. Firstly, we determined the pharmacodynamic material basis of the four active fractions of CNC (Camellia. leave. saponins, Camellia. leave. polyphenols, Camellia. flower. saponins, Camellia. flower. polyphenols) by UPLC-Q-TOF-MS/MS and confirmed the differences in their specific compound contents. Then, MTT, colony formation assay and EdU incorporation assay confirmed that all fractions of CNC exhibit significant inhibitory on NSCLC, especially the Camellia. leave. saponins (CLS) fraction on EGFR mutated NSCLC cell lines. Moreover, transcriptome analysis revealed that the inhibition of NSCLC cell growth by CLS may be via three pathways, including “Cytokine-cytokine receptor interaction,” “PI3K-Akt signaling pathway” and “MAPK signaling pathway.” Subsequently, quantitative real-time PCR (RT-qPCR) and Western blot (WB) revealed TGFB2, INHBB, PIK3R3, ITGB8, TrkB and CACNA1D as the critical targets for the anti-tumor effects of CLS in vitro. Finally, the xenograft models confirmed that CLS treatment effectively suppressed tumor growth, and the key targets were also verified in vivo. These observations suggest that golden-flowered tea could be developed as a functional tea drink with anti-cancer ability, providing an essential molecular mechanism foundation for MFH medicine treating NSCLC.

In this research paper, a fast, quantitative, analytical model for magnesium oxide (MgO) content in medicinal mineral talcum was explored based on near-infrared (NIR) spectroscopy. MgO content in each sample was determined by ethylenediaminetetraacetic acid (EDTA) titration and taken as reference value of NIR spectroscopy, and then a variety of processing methods of spectra data were compared to establish a good NIR spectroscopy model. To start, 50 batches of talcum samples were categorized into training set and test set using the Kennard–Stone (K-S) algorithm. In a partial least squares regression (PLSR) model, both leave-one-out cross-validation (LOOCV) and training set validation (TSV) were used to screen spectrum preprocessing methods from multiplicative scatter correction (MSC), and finally the standard normal variate transformation (SNV) was chosen as the optimal pretreatment method. The modeling spectrum bands and ranks were optimized using PLSR method, and the characteristic spectrum ranges were determined as 11995–10664, 7991–6661, and 4326–3999 cm ⁻¹ , with four optimal ranks. In the support vector machine (SVM) model, the radical basis function (RBF) kernel function was used. Moreover, the full spectrum data of samples pretreated with SNV, the characteristic spectrum data screened using synergy interval partial least squares (SiPLS), and the scoring data of the first four ranks obtained by a partial least squares (PLS) dimension reduction of characteristic spectrum were taken as input variables of SVM, and the MgO content reference values of various sample were taken as output values. In addition, the SVM model internal parameters were optimized using the grid optimization method (GRID), particle swarm optimization (PSO), and genetic algorithm (GA) so that the optimal C and g-values were determined and the validation model was established. By comprehensively comparing the validation effects of different models, it can be concluded that the scoring data of the first four ranks obtained by PLS dimension reduction of characteristic spectrum were taken as input variables of SVM, and the PLS-SVM regression model established using GRID was the optimal NIR spectroscopy quantitative model of talc. This PLS-SVM regression model (rank = 4) measured that the MgO content of talcum was in the range of 17.42–33.22%, with root mean square error of cross validation (RMSECV) of 2.2127%, root mean square error of calibration (RMSEC) of 0.6057%, and root mean square error of prediction (RMSEP) of 1.2901%. This model showed high accuracy and strong prediction capacity, which can be used for rapid prediction of MgO content in talcum.

Aims This study investigated the antifungal activity and mechanisms of ethyl acetate extract of Artemisia argyi (EAAA) against Verticillium dahliae. Methods and Results Optical and scanning electron microscopy observation showed that 2.0 mg ml^-1 EAAA treatment reduced spore germination rate to 4.56%. Histochemical staining showed that 2.0 mg ml^-1 EAAA treatment increased reactive oxygen species (ROS) by more than two times. Physiological test showed that EAAA treatment decreased the contents of soluble proteins and sugars, and reduced the activities of malate dehydrogenase and succinate dehydrogenase by nearly half. Transcriptome analysis showed that EAAA treatment down-regulated the expression of genes involved in primary metabolic pathways of V. dahliae. Conclusions Our results revealed that EAAA inhibited the growth and development of V. dahliae from multiple levels and multiple targets, including inhibiting the germination and development of V. dahliae spores, destroying the structure of cell membranes, inducing ROS burst, reducing the activities of respiratory-related enzymes, and down-regulating the expression of genes in primary metabolic pathways. Significance and Impact of the Study The mechanism of the multitarget effects of EAAA against V. dahliae may limit the potential of fungus developing resistance and provide the efficient methods to control verticillium wilt disease in the future.

Pinellia ternata (Thunb.) Breit. (P. ternata) is a very important plant that is commonly used in traditional Chinese medicine. Its corms can be used as medicine and function to alleviate cough, headache, and phlegm. The epidermis of P. ternata corms is often light yellow to yellow in color; however, within the range of P. ternata found in JingZhou City in Hubei Province, China, there is a form of P. ternata in which the epidermis of the corm is red. We found that the total flavonoid content of red P. ternata corms is significantly higher than that of yellow P. ternata corms. The objective of this study was to understand the molecular mechanisms behind the difference in epidermal color between the two forms of P. ternata. The results showed that a high content of anthocyanidin was responsible for the red epidermal color in P. ternata, and 15 metabolites, including cyanidin-3-O-rutinoside-5-O-glucoside, cyanidin-3-O-glucoside, and cyanidin-3-O-rutinoside, were screened as potential color markers in P. ternata through metabolomic analysis. Based on an analysis of the transcriptome, seven genes, including PtCHS1, PtCHS2, PtCHI1, PtDFR5, PtANS, PtUPD-GT2, and PtUPD-GT3, were found to have important effects on the biosynthesis of anthocyanins in the P. ternata corm epidermis. Furthermore, two transcription factors (TFs), bHLH1 and bHLH2, may have regulatory functions in the biosynthesis of anthocyanins in red P. ternata corms. Using an integrative analysis of the metabolomic and transcriptomic data, we identified five genes, PtCHI, PtDFR2, PtUPD-GT1, PtUPD-GT2, and PtUPD-GT3, that may play important roles in the presence of the red epidermis color in P. ternata corms.