Xiangsong Meng

Isatis indigotica Fort.—a well-known medicinal cruciferous species—is the source plant of Isatidis Radix and Folium Isatidis, and is widely cultivated for medicinal raw material. The silique serves as the propagative organ for seed production of I. indigotica, and its developmental performance directly determines the plant’s seed quality and seed multiplication efficiency. To decipher the physiological and molecular mechanisms by which exogenous salicylic acid (SA) and indole-3-acetic acid (IAA) modulate silique development, we performed a field experiment using the cultivar ‘Songming No. 1’. Plants were foliar-sprayed with 2 mmol·L⁻¹ SA at the full-bloom stage and 0.571 mmol·L⁻¹ IAA at the flower-bud stage, with distilled water treatment serving as the control (CK). Silique samples were collected at five key developmental stages: formation, growth, expansion, browning maturation, and full maturation. We measured nutrient contents, carbohydrate-metabolizing enzyme activities, and endogenous phytohormone levels, and performed integrated transcriptomic and untargeted metabolomic analyses. Exogenous SA and IAA substantially reshaped the accumulation patterns of sucrose, starch, soluble proteins, and other nutrients. The activities of invertase, pyruvate kinase (PK), glucose-6-phosphate dehydrogenase (G6PDH), and soluble starch synthase (SSS) were significantly altered by hormone treatments; SA accelerated metabolic processes in early-stage siliques. Transcriptomic screening identified nine SA-responsive genes and one IAA-responsive candidate gene. SA mainly perturbed carbohydrate and amino acid metabolic pathways, whereas IAA modulated terpenoid and polyketide biosynthetic pathways. A total of 7028 metabolites were annotated, showing that SA exerted stronger effects on carbohydrate metabolism than IAA. Nine-quadrant correlation analysis identified multiple gene–metabolite modules associated with silique development. Collectively, this study characterizes the physiological and multi-omics responses of I. indigotica siliques to exogenous SA and IAA. The physiological and molecular alterations observed here are consistent with the phenotypic outcomes reported under identical experimental treatments. This work provides valuable resources for exploring hormone-mediated high-quality seed propagation and candidate gene mining in I. indigotica.

Background/Objectives: Vitex negundo L. is a multi-part medicinal and aromatic plant, but organ-resolved chemical information for its aerial organs remains incomplete. This study generated an exploratory paired untargeted liquid chromatography–tandem mass spectrometry (LC-MS/MS) dataset for flowers, stems, and leaves and prioritized organ-associated putative metabolite families for subsequent validation. Methods: To reduce inter-individual background variation, flower, stem, and leaf tissues were harvested from the same three V. negundo individuals to form n = 3 paired plant blocks. LC-MS/MS feature data were filtered using pooled quality-control relative standard deviation (QC RSD ≤ 30%), median-normalized and log2-transformed. Principal component analysis (PCA) provided an unsupervised overview, and paired feature-level comparisons were performed using paired t-tests with Benjamini−Hochberg false discovery rate (FDR) correction. Results: A total of 42,125 QC-filtered LC-MS features were retained. PCA showed organ-associated separation among flowers, stems, and leaves. Using FDR < 0.05 and |mean paired log2 difference| ≥ 1, paired screening yielded 13,043, 22,836, and 13,393 FDR-supported LC-MS features for flower vs. stem, flower vs. leaf, and stem vs. leaf comparisons, respectively. Higher-scoring putative annotations suggested organ-associated putative family-level patterns, including flavonoid-related, hydroxycinnamic-acid derivative, phenolamide-related, triterpenoid-related, iridoid-related, and lignan-related signals. Conclusions: This organ-resolved dataset provides a chemical-feature framework for V. negundo aerial organs and putative family-level patterns for future structural confirmation, targeted quantification, bioactivity evaluation, and quality-marker development. Feature counts are not equivalent to unique metabolite counts, and compound labels require validation before being interpreted as confirmed structures.