Differential microbial assemblages associated with shikonin-producing Borage species in two distinct soil types

Abstract Shikonin and its derivatives are the main components of traditional Chinese medicine, Zicao. The pharmacological potential of shikonin and its derivatives have been extensively studied. Yet, less is known about the microbial assemblages associated with shikonin producing Borage plants. We s...

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Autores principales: Aliya Fazal, Minkai Yang, Zhongling Wen, Farman Ali, Ran Ren, Chenyu Hao, Xingyu Chen, Jiangyan Fu, Xuan Wang, Wencai Jie, Tongming Yin, Guihua Lu, Jinliang Qi, Yonghua Yang
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/d95b26a9f63c46b1823789aac063a989
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Sumario:Abstract Shikonin and its derivatives are the main components of traditional Chinese medicine, Zicao. The pharmacological potential of shikonin and its derivatives have been extensively studied. Yet, less is known about the microbial assemblages associated with shikonin producing Borage plants. We studied microbial profiles of two Borage species, Echium plantagineum (EP) and Lithospermum erythrorhizon (LE), to identify the dynamics of microbial colonization pattern within three rhizo-compatments and two distinct soil types. Results of α and β-diversity via PacBio sequencing revealed significantly higher microbial richness and diversity in the natural soil along with a decreasing microbial gradient across rhizosphere to endosphere. Our results displayed genotype and soil type–dependent fine-tuning of microbial profiles. The host plant was found to exert effects on the physical and chemical properties of soil, resulting in reproducibly different micro-biota. Analysis of differentially abundant microbial OTUs displayed Planctomycetes and Bacteroidetes to be specifically enriched in EP and LE rhizosphere while endosphere was mostly prevailed by Cyanobacteria. Network analysis to unfold co-existing microbial species displayed different types of positive and negative interactions within different communities. The data provided here will help to identify microbes associated with different rhizo-compartments of potential host plants. In the future, this might be helpful for manipulating the keystone microbes for ecosystem functioning.