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. 2023 Dec 15:14:1292896.
doi: 10.3389/fmicb.2023.1292896. eCollection 2023.

Role of plant metabolites in the formation of bacterial communities in the rhizosphere of Tetrastigma hemsleyanum

Yuqing Huang  1 , Hongliang Hu  2 , Erkui Yue  1 , Wu Ying  1 , Tianxin Niu  1 , Jianli Yan  1 , Qiujun Lu  3 , Songlin Ruan  1
Affiliations

Role of plant metabolites in the formation of bacterial communities in the rhizosphere of Tetrastigma hemsleyanum

Yuqing Huang et al. Front Microbiol. .

Abstract

Tetrastigma hemsleyanum Diels et Gilg, commonly known as Sanyeqing (SYQ), is an important traditional Chinese medicine. The content of bioactive constituents varies in different cultivars of SYQ. In the plant growth related researches, rhizosphere microbiome has gained significant attention. However, the role of bacterial communities in the accumulation of metabolites in plants have not been investigated. Herein, the composition of bacterial communities in the rhizosphere soils and the metabolites profile of different SYQ cultivars' roots were analyzed. It was found that the composition of microbial communities varied in the rhizosphere soils of different SYQ cultivars. The high abundance of Actinomadura, Streptomyces and other bacteria was found to be associated with the metabolites profile of SYQ roots. The findings suggest that the upregulation of rutin and hesperetin may contribute to the high bioactive constituent in SYQ roots. These results provide better understanding of the metabolite accumulation pattern in SYQ, and also provide a solution for enhancing the quality of SYQ by application of suitable microbial consortia.

Keywords: Sanyeqing; Tetrastigma hemsleyanum; bioactive constituents; metabolite profiling; metagenome; microbial community structure; rhizosphere microbiome.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
FC, TPC, and ESEC in the roots of four cultivars. FC, flavonoid content; TPC, total phenolic content; ESEC, ethanol-soluble extractive content.
Figure 2
Figure 2
Metagenomics analysis of different soil samples. (A) The number of non-redundant genes in different cultivars. (B) PCA of bacterial composition in four soil samples.
Figure 3
Figure 3
Bacterial structure analysis of different soil samples. (A) Bacterial structure at phylum level in four soil samples. (B) Bacterial structure at genus level in four cultivars.
Figure 4
Figure 4
LEfSe analysis showing the different taxon among different SYQ cultivar rhizospheres bacterial communities. Different colored regions represent different culitvars (red for SYQ1, green for SYQ2, blue for SYQ3 and purple for SYQ4) and the diameter of each circle is proportional to the relative abundance of the taxon. The inner to outer circle represents the level of the phylum to the genus.
Figure 5
Figure 5
Clustering heatmap of bacterial communities at genus level. G1, SYQ1; G2, SYQ2; G3, SYQ3; G4, SYQ4. The bacterial genus framed in red box had a higher abundance in SYQ2 and SYQ4.
Figure 6
Figure 6
KEGG analysis of the genes identified by metagenomics analysis. (A) Venn diagram of shared level 3 KEGG pathways among the rhizosphere soils of four cultivars. (B) The dominant KEGG pathways of different cultivars. G1, SYQ1; G2, SYQ2; G3, SYQ3; G4, SYQ4.
Figure 7
Figure 7
Metabolites profiles of different roots samples. (A) Venn diagram of shared metabolites in four cultivars. (B) PCA of metabolites in four cultivars, and (C) Clustering heatmap of metabolites in four cultivars.
Figure 8
Figure 8
KEGG pathway enrichment analysis of differentially accumulated metabolites in four cultivars: (A) analysis between SYQ1 and SYQ2, (B) analysis between SYQ1 and SYQ4, (C) analysis between SYQ3 and SYQ2, and (D) analysis between SYQ3 and SYQ4.
Figure 9
Figure 9
Pearson correlation test of the highly abundant communities and upregulated DAMs.
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