Accumulation mechanism of metabolite markers identified by machine learning between Qingyuan and Xiushui counties in Polygonatum cyrtonema Hua.

Polygonatum cyrtonema Hua is a traditional Chinese medicinal plant acclaimed for its therapeutic potential in diabetes and various chronic diseases. Its rhizomes are the main functional parts rich in secondary metabolites, such as flavonoids and saponins. But their quality varies by region, posing challenges for industrial and medicinal application of P. cyrtonema. In this study, 482 metabolites were identified in P. cyrtonema rhizome from Qingyuan and Xiushui counties. Cluster analysis showed that samples between these two regions had distinct secondary metabolite profiles. Machine learning methods, specifically support vector machine-recursive feature elimination and random forest, were utilized to further identify metabolite markers including flavonoids, phenolic acids, and lignans. Comparative transcriptomics and weighted gene co-expression analysis were performed to uncover potential candidate genes including CHI, UGT1, and PcOMT10/11/12/13 associated with these compounds. Functional assays using tobacco transient expression system revealed that PcOMT10/11/12/13 indeed impacted metabolic fluxes of the phenylpropanoid pathway and phenylpropanoid-related metabolites such as chrysoeriol-6,8-di-C-glucoside, syringaresinol-4'-O-glucopyranosid, and 1-O-Sinapoyl-D-glucose. These findings identified metabolite markers between these two regions and provided valuable genetic insights for engineering the biosynthesis of these compounds.

Synthesis, Aggregation Induced Emission and Mechanochromic Luminescence of New ß-Diketone Derivatives Bearing Tetraphenylene Moieties.

A series of ß-diketone derivatives bearing tetraphenylene (TPE) moieties were synthesized and characterized. Their photophysical properties were investigated systematically via spectroscopic and theoretical methods. All compounds exhibit broad absorption bands between 300 and 450 nm, which are assigned to the 1π-π* transition of the conjugated system mixed intramolecular charge-transfer (ICT) transitions. Meanwhile, the emission of these compounds in solution at room temperature (λ em = 458 ~ 509 nm) can be attributed to the 1π,π*/1ICT state. Introduction of freely rotatable TPE to conventional ß-diketone luminophors quenches their light emissions in the solutions, but endows these molecules with aggregation-induced emission (AIE) characteristics in the condensed phase due to the restriction of intramolecular rotation. The spectroscopic studies and theoretical calculations indicate that the photophysical properties of these ß-diketone derivatives can be tuned by the appended substituents, which would be useful for rational design of AIE compounds with high solid state luminescence performance. Furthermore, these AIE-active compounds exhibited distinct piezofluorochromic properties and switched reversibly upon grinding-fuming. Their photophysical properties have been investigated with the aim to provide a basis for elucidating the structure-property correlations and developing new multi-stimuli responsive luminescent materials.

Co-expressed network analysis based on 289 transcriptome samples reveals methyl jasmonate-mediated gene regulatory mechanism of flavonoid compounds in Dendrobium catenatum.

Flavonoids are momentous bioactive ingredients in orchid plant Dendrobium catenatum (D. catenatum), which are bioactive compounds with great medical and commercial potential. However, the accurate dissection of flavonoids profiling and their accumulation mechanism are largely unknown. In this study, methyl jasmonate (MeJA) treatment was used to investigate the change of flavonoids content and transcripts in two D. catenatum clones (A6 and B1). We identified 40 flavonoids using liquid chromatograph mass spectrometer (LC-MS). By weighted gene co-expressed network analysis (WGCNA) of flavonoids content and transcript expression of MeJA-treated samples, 37 hub genes were identified. Among them, DcCHIL, DcFLS, and DcDFR were highly correlation with two key transcription factors DcWRKY3/4 by correlation analysis of large-scale transcriptome data and above hub genes expression. Furthermore, transient overexpression of DcWRKY3/4 in tobacco leaves significantly increased the content of flavonoids. This study identified flavonoid profiling and built a new approach to mine regulatory mechanism of flavonoids in D. catenatum. These valuable flavonoids and gene resources will be key for understanding and harnessing natural flavonoids products in pharmaceuticals and foods industry of D. catenatum.

Machine learning uncovers accumulation mechanism of flavonoid compounds in Polygonatum cyrtonema Hua.

The compositions and yield of flavonoid compounds of Polygonatum cyrtonema Hua (PC) are important indices of the quality of medicinal materials. However, the flavonoids compositions and accumulation mechanism are still unclear in PC. Here, we identified 22 flavonoids using widely-targeted metabolome analysis in 15 genotypes of PC. Then weighted gene co-expression network analysis based on 45 transcriptome samples was performed to construct 12 co-expressed modules, in which blue module highly correlated with flavonoids was identified. Furthermore, 4 feature genes including PcCHS1, PcCHI, PcCHS2 and PcCHR5 were identified from 94 hub genes in blue module via machine learning methods support vector machine-recursive feature elimination (SVM-RFE) and random forest (RF), and their functions on metabolic flux of flavonoids pathway were confirmed by tobacco transient expression system. Our findings identified representative flavonoids and key enzymes in PC that provided new insight for elite breeding rich in flavonoids, and thus will be beneficial for rapid development of great potential economic and medicinal value of PC.