Combined metabolomics and transcriptomics reveal the secondary metabolite networks in different growth stages of Bletilla striata (Thunb.) Reichb.f

Abstract

Background: Bletilla striata (Thunb.) Reichb.f. (B. striata) is a traditional Chinese medicinal herb. B. striata polysaccharides (BSP), stilbenes and 2-isobutyl malic acid glucosoxy-benzyl ester compounds are the main active ingredients in B. striata. However, there is limited report on the changes of medicinal components and their biosynthesis regulation mechanisms in the tubers of B. striata at different stages.

Method: The tubers of B. striata were collected during the flowering period, fruiting period, and harvest period to determine the total polysaccharide content using the phenol sulfuric acid method. The changes in secondary metabolites in the tubers at these stages were analyzed by ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS), and transcriptomics was conducted for further exploration of their biosynthetic pathways.

Result: The BSP content gradually increases from the flowering period to the fruiting period as the tubers develop, reaching its peak, but subsequently decreases at harvest time, which may be associated with the germination of B. striata buds in later stage. A total of 294 compounds were identified in this study. Among them, a majority of the compounds, such as 2-isobutyl malate gluconoxy-benzyl ester, exhibited high content during the fruit stage, while stilbenes like coelonin, 3'-O-methylbatatasin III, and blestriarene A accumulated during the harvesting period. The transcriptome data also revealed a substantial number of differentially expressed genes at various stages, providing a partial explanation for the complex changes in metabolites. We observed a correspondence between the expression pattern of GDP-Man biosynthesis-related enzyme genes and cumulative changes in BSP. And identified a positive correlation between 9 transcription factors and genes associated with polysaccharide biosynthesis, while 5 transcription factors were positively correlated with accumulation of 2-isobutyl malate gluconoxy-benzyl ester compounds and 5 transcription factors exhibited negative correlated with stilbene accumulation.

Conclusion: It is imperative to determine the appropriate harvesting period based on the specific requirements of different active ingredients and the accumulation patterns of their metabolites. Considering the involvement of multiple transcription factors in the biosynthesis and accumulation of its active ingredients, a comprehensive investigation into the specific regulatory mechanisms that facilitate high-quality cultivation of B. striata is imperative.

Fig 1

Changes in BSP content during different developmental stages of B. striata tubers (n = 3), **, P ≤ 0.01 (A); The morphology of tubers and buds during the flowering (HQ), fruiting (GQ) and harvesting periods (CSQ) of B. striata (B).

Fig 2. Analysis of metabolites of B. striata tuber in different developmental periods.

Intra-group and inter-group correlations of 9 samples at different developmental stages (A); Classification and composition of secondary metabolites (B); PCA Analysis (PC1 = 41.05%, PC2 = 14.23%) (C); Histogram of the number of differential metabolites between three different comparison groups (D); Venn diagram of differential metabolites between different comparison groups (E); KEGG pathway analysis of all differential metabolites (F).

Fig 3. Heat maps of different metabolites of B. striata tuber at different developmental periods.

Fig 4. Transcriptome analysis of B. striata tuber at different growth and development stages.

E-value distribution of unigenes in Nr database (A); Species similarity distribution of unigenes in Nr database (B); GQ vs HQ differential gene KEGG enrichment bubble map (C); CSQ vs HQ differential gene KEGG enrichment bubble map (D); CSQ vs GQ differential gene KEGG enrichment bubble map (E).

Fig 5. BSP biosynthetic pathway with related enzyme expression pattern and correlation.

The temporal expression patterns of genes encoding enzymes involved in regulating BSP biosynthesis (A); Correlation between genes encoding enzymes involved in regulating BSP biosynthesis and BSP content (B). The first three colors are HQ samples, followed by GQ, and finally CSQ. Beta-fructofuranosidase (sacA), fyn-related kinase (FRK), hexokinase (HK), mannose-6-phosphate isomerase (MPI), phosphomannomutase (PMM), mannose-1-phosphate guanylyltransferase (GMPP), glucose-6-phosphate isomerase (GPI), phosphoglucomutase (pgm), UTP—glucose-1-phosphate uridylyltransferase (UGP2), sucrose synthase (SUS).

Fig 6. Correlation analysis of metabolite content with TFs expression and BSP biosynthesis genes.

The changes of 2-isobutyl malate gluconoxy-benzyl esters and stilbenes in differential metabolites in different periods of tubers of B. striata (A); TFs expression in differential metabolites in different periods of tubers of B. striata (B); Correlation analysis network between metabolite content and transcription factor expression (C). The red line segment represents a positive correlation, while the blue line segment signifies a negative correlation).