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. 2023 Sep 23;12(19):3363.
doi: 10.3390/plants12193363.

Enhancing Centelloside Production in Centella asiatica Hairy Root Lines through Metabolic Engineering of Triterpene Biosynthetic Pathway Early Genes

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Enhancing Centelloside Production in Centella asiatica Hairy Root Lines through Metabolic Engineering of Triterpene Biosynthetic Pathway Early Genes

Miguel Angel Alcalde et al. Plants (Basel). .

Abstract

Centella asiatica is a medicinal plant with a rich tradition of use for its therapeutic properties. Among its bioactive compounds are centellosides, a group of triterpenoid secondary metabolites whose potent pharmacological activities have attracted significant attention. Metabolic engineering has emerged as a powerful biotechnological tool to enhance the production of target compounds. In this study, we explored the effects of overexpressing the squalene synthase (SQS) gene and transcription factor TSAR2 on various aspects of C. asiatica hairy root lines: the expression level of centelloside biosynthetic genes, morphological traits, as well as squalene, phytosterol, and centelloside content. Three distinct categories of transformed lines were obtained: LS, harboring At-SQS; LT, overexpressing TSAR2; and LST, simultaneously carrying both transgenes. These lines displayed noticeable alterations in morphological traits, including changes in branching rate and biomass production. Furthermore, we observed that the expression of T-DNA genes, particularly aux2 and rolC genes, significantly modulated the expression of pivotal genes involved in centelloside biosynthesis. Notably, the LS lines boasted an elevated centelloside content but concurrently displayed reduced phytosterol content, a finding that underscores the intriguing antagonistic relationship between phytosterol and triterpene pathways. Additionally, the inverse correlation between the centelloside content and morphological growth values observed in LS lines was countered by the action of TSAR2 in the LST and LT lines. This difference could be attributed to the simultaneous increase in the phytosterol content in the TSAR2-expressing lines, as these compounds are closely linked to root development. Overall, these discoveries offer valuable information for the biotechnological application of C. asiatica hairy roots and their potential to increase centelloside production.

Keywords: centelloside; machine learning; metabolic engineering; plant biotechnology; synthetic biology; triterpene.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Overview of the centelloside biosynthetic pathway and gene expression profile. L1 denotes the control line, while LST, LS, and LT represent the transformed lines. The reddish heatmap indicates the upregulation (UP) or downregulation (DOWN) of gene expression for HMGR (encoding the 3-hydroxy-3-methylglutaryl coenzyme A reductase), SQS (encoding squalene synthase), β-AS (encoding beta amyrin synthase), CYP83 (cytochrome CYP716A83), CYP19 (cytochrome CYP714E19), CYP11 (cytochrome CYP716C11), and UGT (UGT73AD1). The bluish heatmap reflects the fold change in gene expression of At-SQS (squalene synthase from Arabidopsis thaliana).
Figure 2
Figure 2
Comprehensive heatmap illustrating the impact of rol and aux genes on the endogenous gene expression profile in Centella asiatica hairy roots.
Figure 3
Figure 3
Comparative plot of various types of hairy root lines. The density plot illustrates the profiles of sterols, squalene, and centellosides, while the bar plots display the gene expression profiles of HMGR, SQS, and At-SQS in terms of fold change values. The stacked column highlighted in purple represents the contribution of At-SQS. See Table S1 for more details.
Figure 4
Figure 4
Average morphology of different hairy root lines of Centella asiatica at day 28 of growth: (a) control, (b) LST, (c) LS, (d) LT. The initial inoculum was a small section of 10 mg of fresh weight.
Figure 5
Figure 5
Pearson’s correlation analysis of morphological traits and metabolite content. (a) Correlation plot for the control line; (b) correlation plot for the LS lines; (c) correlation plot for the lines overexpressing the transcription factor. Values indicate the Pearson correlation coefficient (r).

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