Single-cell transcriptome of Nepeta tenuifolia leaves reveal differentiation trajectories in glandular trichomes

Applications of some advanced sequencing, analytical, and computational approaches in medicinal plant research: a review

The potential active chemicals found in medicinal plants, which have long been employed as natural medicines, are abundant. Exploring the genes responsible for producing these compounds has given new insights into medicinal plant research. Previously, the authentication of medicinal plants was done via DNA marker sequencing. With the advancement of sequencing technology, several new techniques like next-generation sequencing, single molecule sequencing, and fourth-generation sequencing have emerged. These techniques enshrined the role of molecular approaches for medicinal plants because all the genes involved in the biosynthesis of medicinal compound(s) could be identified through RNA-seq analysis. In several research insights, transcriptome data have also been used for the identification of biosynthesis pathways. miRNAs in several medicinal plants and their role in the biosynthesis pathway as well as regulation of the disease-causing genes were also identified. In several research articles, an in silico study was also found to be effective in identifying the inhibitory effect of medicinal plant-based compounds against virus' gene(s). The use of advanced analytical methods like spectroscopy and chromatography in metabolite proofing of secondary metabolites has also been reported in several recent research findings. Furthermore, advancement in molecular and analytic methods will give new insight into studying the traditionally important medicinal plants that are still unexplored.

Mass spectrometry imaging and single-cell transcriptional profiling reveal the tissue-specific regulation of bioactive ingredient biosynthesis in Taxus leaves

Taxus leaves provide the raw industrial materials for taxol, a natural antineoplastic drug widely used in the treatment of various cancers. However, the precise distribution, biosynthesis, and transcriptional regulation of taxoids and other active components in Taxus leaves remain unknown. Matrix-assisted laser desorption/ionization-mass spectrometry imaging analysis was used to visualize various secondary metabolites in leaf sections of Taxus mairei, confirming the tissue-specific accumulation of different active metabolites. Single-cell sequencing was used to produce expression profiles of 8846 cells, with a median of 2352 genes per cell. Based on a series of cluster-specific markers, cells were grouped into 15 clusters, suggesting a high degree of cell heterogeneity in T. mairei leaves. Our data were used to create the first Taxus leaf metabolic single-cell atlas and to reveal spatial and temporal expression patterns of several secondary metabolic pathways. According to the cell-type annotation, most taxol biosynthesis genes are expressed mainly in leaf mesophyll cells; phenolic acid and flavonoid biosynthesis genes are highly expressed in leaf epidermal cells (including the stomatal complex and guard cells); and terpenoid and steroid biosynthesis genes are expressed specifically in leaf mesophyll cells. A number of novel and cell-specific transcription factors involved in secondary metabolite biosynthesis were identified, including MYB17, WRKY12, WRKY31, ERF13, GT_2, and bHLH46. Our research establishes the transcriptional landscape of major cell types in T. mairei leaves at a single-cell resolution and provides valuable resources for studying the basic principles of cell-type-specific regulation of secondary metabolism.

Applying quantitative spatial phenotypes analysis to the investigation of peltate glandular trichomes development pattern in Perilla frutescens

BACKGROUND

Glandular trichomes, often referred to as "phytochemical factories", plays a crucial role in plant growth and metabolism. As the site for secretion and storage, the development of glandular trichomes is related to the dynamic biosynthesis of specialised metabolites. The study aims to explore the relationship between spatial phenotype and dynamic metabolism of glandular trichomes, and establish a novel approach for the exploration and study of the regulatory mechanism governing the development of glandular trichomes.

RESULTS

In this study, we proposed a technical route based on the relative deviation value to distinguish the peltate glandular trichomes (PGTs) from the background tissues and extract their spatial phenotype. By defining glandular trichome developmental stages based on the leaf vein growth axis, we found that young PGTs were densely distributed near the proximal end of growth axis of the leaf veins, where perillaketone, a primary metabolite of PGTs, is predominantly accumulated. Conversely, mature PGTs are typically found near the distal end of the mid-vein growth axis and the lateral end of the secondary vein growth axis, where the accumulation rate of isoegomaketone and egomaketone exceeds that of perillaketone in PGTs. We further identified spatial phenotypic parameters, Lsum and d, as independent variables to construct a linear regression model that illustrates the relationship between the spatial phenotypes and metabolite content of PGTs, including perillaketone (R2 = 0.698), egomaketone (R2 = 0.593), isoegomaketone (R2 = 0.662) and the sum of the amount (R2 = 0.773).

CONCLUSIONS

This model proved that the development of PGTs was correlated with the growth of the entire leaf, and the development stage of PGTs can be identifined by spatial phenotypes based on the leaf veins. In conclusion, the findings of this study enhance our understanding of correlation between spatial phenotype and development of glandular trichomes and offer a new approach to explore and study the regulatory mechanism of glandular trichome development.