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BMC Microbiol
2021 Jan 08;211:18. doi: 10.1186/s12866-020-02081-2.
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Diversity and composition of the Panax ginseng rhizosphere microbiome in various cultivation modesand ages.
Tong AZ
,
Liu W
,
Liu Q
,
Xia GQ
,
Zhu JY
.
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BACKGROUND: Continuous cropping of ginseng (Panax ginseng Meyer) cultivated in farmland for an extended period gives rise to soil-borne disease. The change in soil microbial composition is a major cause of soil-borne diseases and an obstacle to continuous cropping. The impact of cultivation modes and ages on the diversity and composition of the P. ginseng rhizosphere microbial community and technology suitable for cropping P. ginseng in farmland are still being explored.
METHODS: Amplicon sequencing of bacterial 16S rRNA genes and fungal ITS regions were analyzed for microbial community composition and diversity.
RESULTS: The obtained sequencing data were reasonable for estimating soil microbial diversity. We observed significant variations in richness, diversity, and relative abundances of microbial taxa between farmland, deforestation field, and different cultivation years. The bacterial communities of LCK (forest soil where P. ginseng was not grown) had a much higher richness and diversity than those in NCK (farmland soil where P. ginseng was not grown). The increase in cultivation years of P. ginseng in farmland and deforestation field significantly changed the diversity of soil microbial communities. In addition, the accumulation of P. ginseng soil-borne pathogens (Monographella cucumerina, Ilyonectria mors-panacis, I. robusta, Fusarium solani, and Nectria ramulariae) varied with the cropping age of P. ginseng.
CONCLUSION: Soil microbial diversity and function were significantly poorer in farmland than in the deforestation field and were affected by P. ginseng planting years. The abundance of common soil-borne pathogens of P. ginseng increased with the cultivation age and led to an imbalance in the microbial community.
Fig. 1. Rarefaction curves of individual soil samples (a. bacteria, b. fungi).The rarefaction curve was assembled using the Sobs index at the OTU level. Relative to the total number of sequences, sequence similarity was defined at 97% cut-off by Mothur
Fig. 2. Estimate the microbial community by alpha diversity. a, Alpha diversity of bacterial communities between NCK and LCK. b, Alpha diversity of bacterial communities among NCK, N1, N2, N3, N4, and N5. c, Alpha diversity of fungal communities among NCK, N1, N2, N3, N4, and N5. d, Alpha diversity of bacterial communities among LCK, L1, L2, L3, L4, and L5. Estimation of Alpha diversity representing two biological replicates for the NCK samples, and three biological replicates for the other rhizospheric soil samples (*p < 0.05, **p < 0.01, ***p < 0.001)
Fig. 3. Estimation of similarity and distance based on the hierarchical clustering tree of the samples (a, bacteria; c, fungi) and principal coordinate analysis (PCoA) (b, bacteria; d fungus) of the OTUs. The length of the branches in the hierarchical tree represents the distance between samples. The closer the two samples are on the PCoA plot, the more similar the species composition of the two samples
Fig. 4. The composition and structure of the bacterial community. A, Pieplot for bacterial community analysis at the phylum level. B, Relative abundances of the bacterial phyla in different samples
Fig. 5. The composition and structure of the fungal community. A, Pieplot for fungal community analysis at the phylum level. B, Relative abundances of the fungal phylain different samples
Fig. 6. The relative abundance of pathogenic fungal in soil samples. Three biological replicates of each sample. A, Relative abundances of the different fungal in different samples at genus level. B, Relative abundance of pathogenic fungal species in soil samples
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