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      Metabolomics and microbiome reveal potential root microbiota affecting the alkaloidal metabolome in Aconitum vilmorinianum Kom.

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          Abstract

          Background

          The plant microbiome is vital for plant health, fitness, and productivity. Interestingly, plant metabolites and the plant microbiome can influence each other. The combination of metabolomics and microbiome may reveal the critical links between the plant and its microbiome. It is of great significance to agricultural production and human health, especially for Chinese medicine research. Aconitum vilmorinianum Kom. is a herb with alkaloid activities, and its roots are the raw material for some Chinese medicines. Former studies have investigated alkaloidal metabolites and antibacterial activities of endophytes in A. vilmorinianum roots. However, there are limited reports on the root microbiota that can influence the alkaloidal metabolome of A. vilmorinianum.

          Results

          This research used ultra performance liquid chromatography-tandem mass spectrometry technology and high-throughput sequencing to examine the alkaloidal metabolome, bacterial microbiota, and fungal microbiota in A. vilmorinianum roots at two different sites in China. The results revealed that the samples from the two sites were rich in distinct alkaloidal metabolites and recruited significantly different root microbiota. Based on bioinformatics analysis, we found the potential bacterial and fungal microbiota impacting the alkaloidal metabolome in A. vilmorinianum.

          Conclusion

          Our findings reveal the composition of the alkaloidal metabolome, bacterial root microbiota, and fungal root microbiota in A. vilmorinianum roots at two different sites. Potential root microbiota that can influence the alkaloidal metabolome of A. vilmorinianum are indicated. This study provides a strategy for the cultivation and research of A. vilmorinianum and other Chinese herbs.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12866-022-02486-1.

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          Most cited references61

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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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            Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

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              FLASH: fast length adjustment of short reads to improve genome assemblies.

              Next-generation sequencing technologies generate very large numbers of short reads. Even with very deep genome coverage, short read lengths cause problems in de novo assemblies. The use of paired-end libraries with a fragment size shorter than twice the read length provides an opportunity to generate much longer reads by overlapping and merging read pairs before assembling a genome. We present FLASH, a fast computational tool to extend the length of short reads by overlapping paired-end reads from fragment libraries that are sufficiently short. We tested the correctness of the tool on one million simulated read pairs, and we then applied it as a pre-processor for genome assemblies of Illumina reads from the bacterium Staphylococcus aureus and human chromosome 14. FLASH correctly extended and merged reads >99% of the time on simulated reads with an error rate of <1%. With adequately set parameters, FLASH correctly merged reads over 90% of the time even when the reads contained up to 5% errors. When FLASH was used to extend reads prior to assembly, the resulting assemblies had substantially greater N50 lengths for both contigs and scaffolds. The FLASH system is implemented in C and is freely available as open-source code at http://www.cbcb.umd.edu/software/flash. t.magoc@gmail.com.
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                Author and article information

                Contributors
                xupeng@xtbg.ac.cn
                ydq@xtbg.ac.cn
                Journal
                BMC Microbiol
                BMC Microbiol
                BMC Microbiology
                BioMed Central (London )
                1471-2180
                9 March 2022
                9 March 2022
                2022
                : 22
                : 70
                Affiliations
                [1 ]GRID grid.9227.e, ISNI 0000000119573309, CAS Key Laboratory of Tropical Plant Resources and Sustainable Use, Xishuangbanna Tropical Botanical Garden, , Chinese Academy of Sciences, ; Kunming, 650223 China
                [2 ]GRID grid.410726.6, ISNI 0000 0004 1797 8419, College of Life Sciences, , University of Chinese Academy of Sciences, ; Beijing, 100049 China
                [3 ]GRID grid.440773.3, ISNI 0000 0000 9342 2456, State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, , Yunnan University, ; Kunming, 650091 China
                Article
                2486
                10.1186/s12866-022-02486-1
                8905797
                35264111
                ecfd6716-0b4c-4c0f-8026-9947531b6de9
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 1 November 2021
                : 3 March 2022
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Microbiology & Virology
                aconitum vilmorinianum kom.,the alkaloidal metabolome,root microbiota,bacterial microbiota,fungal microbiota

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