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      Taxonomic Structure of Rhizosphere Bacterial Communities and Its Association With the Accumulation of Alkaloidal Metabolites in Sophora flavescens

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          Abstract

          Plant secondary metabolites (SMs) play a crucial role in plant defense against pathogens and adaptation to environmental stresses, some of which are produced from medicinal plants and are the material basis of clinical efficacy and vital indicators for quality evaluation of corresponding medicinal materials. The influence of plant microbiota on plant nutrient uptake, production, and stress tolerance has been revealed, but the associations between plant microbiota and the accumulation of SMs in medicinal plants remain largely unknown. Plant SMs can vary among individuals, which could be partly ascribed to the shift in microbial community associated with the plant host. In the present study, we sampled fine roots and rhizosphere soils of Sophora flavescens grown in four well-separated cities/counties in China and determined the taxonomic composition of rhizosphere bacterial communities using Illumina 16S amplicon sequencing. In addition, the association of the rhizosphere bacterial microbiota with the accumulation of alkaloids in the roots of S. flavescens was analyzed. The results showed that S. flavescens hosted distinct bacterial communities in the rhizosphere across geographic locations and plant ages, also indicating that geographic location was a larger source of variation than plant age. Moreover, redundancy analysis revealed that spatial, climatic (mean annual temperature and precipitation), and edaphic factors (pH and available N and P) were the key drivers that shape the rhizosphere bacterial communities. Furthermore, the results of the Mantel test demonstrated that the rhizosphere bacterial microbiota was remarkably correlated with the contents of oxymatrine, sophoridine, and matrine + oxymatrine in roots. Specific taxa belonging to Actinobacteria and Chloroflexi were identified as potential beneficial bacteria associated with the total accumulation of matrine and oxymatrine by a random forest machine learning algorithm. Finally, the structural equation modeling indicated that the Actinobacteria phylum had a direct effect on the total accumulation of matrine and oxymatrine. The present study addresses the association between the rhizosphere bacterial communities and the accumulation of alkaloids in the medicinal plant S. flavescens. Our findings may provide a basis for the quality improvement and sustainable utilization of this medicinal plant thorough rhizosphere microbiota manipulation.

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          The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

          SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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            QIIME allows analysis of high-throughput community sequencing data.

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              Search and clustering orders of magnitude faster than BLAST.

              Biological sequence data is accumulating rapidly, motivating the development of improved high-throughput methods for sequence classification. UBLAST and USEARCH are new algorithms enabling sensitive local and global search of large sequence databases at exceptionally high speeds. They are often orders of magnitude faster than BLAST in practical applications, though sensitivity to distant protein relationships is lower. UCLUST is a new clustering method that exploits USEARCH to assign sequences to clusters. UCLUST offers several advantages over the widely used program CD-HIT, including higher speed, lower memory use, improved sensitivity, clustering at lower identities and classification of much larger datasets. Binaries are available at no charge for non-commercial use at http://www.drive5.com/usearch.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                14 December 2021
                2021
                : 12
                : 781316
                Affiliations
                School of Pharmaceutical Science, Shanxi Medical University , Taiyuan, China
                Author notes

                Edited by: Bin Ma, Zhejiang University, China

                Reviewed by: Shuo Jiao, Northwest A & F University, China; Anandham Rangasamy, Tamil Nadu Agricultural University, India

                *Correspondence: Guan’e Yang, yangguane@ 123456aliyun.com

                These authors have contributed equally to this work

                This article was submitted to Terrestrial Microbiology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2021.781316
                8712762
                de208561-4f6a-4b96-8b15-d403145be85a
                Copyright © 2021 Chen, Li, Chang, Ren, Zhou and Yang.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 22 September 2021
                : 15 November 2021
                Page count
                Figures: 6, Tables: 0, Equations: 0, References: 61, Pages: 11, Words: 7919
                Funding
                Funded by: Shanxi Province Science and Technology Research
                Award ID: 201901D211341
                Funded by: Shanxi Higher Education Innovation Project
                Award ID: 2019L0417
                Funded by: Central Government Guides Local Scientific and Technological Development Fund Projects
                Award ID: YDZX 20201400001443
                Funded by: Shanxi International Science and Technology Cooperation Project
                Award ID: 201803D421065
                Funded by: Science Research Start-up Fund for Doctor of Shanxi Province
                Award ID: SD1815
                Funded by: Taiyuan City Science and Technology Project Special Talents Star Project
                Award ID: 120247-08
                Funded by: Science Research Start-up Fund for Doctor of Shanxi Medical University
                Award ID: XD1816
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                medicinal plants,secondary metabolites,alkaloids,plant bacterial community,rhizosphere

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