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应用特定生态系统的参考数据库提高土壤微生物剖析中的分类分辨率。

Application of ecosystem-specific reference databases for increased taxonomic resolution in soil microbial profiling.

作者信息

Overgaard Christina Karmisholt, Tao Ke, Zhang Sha, Christensen Bent Tolstrup, Blahovska Zuzana, Radutoiu Simona, Kelly Simon, Dueholm Morten Kam Dahl

机构信息

Department of Chemistry and Bioscience, Center for Microbial Communities, Aalborg University, Aalborg, Denmark.

Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark.

出版信息

Front Microbiol. 2022 Nov 3;13:942396. doi: 10.3389/fmicb.2022.942396. eCollection 2022.

Abstract

Intensive agriculture systems have paved the way for a growing human population. However, the abundant use of mineral fertilizers and pesticides may negatively impact nutrient cycles and biodiversity. One potential alternative is to harness beneficial relationships between plants and plant-associated rhizobacteria to increase nutrient-use efficiency and provide pathogen resistance. Plant-associated microbiota profiling can be achieved using high-throughput 16S rRNA gene amplicon sequencing. However, interrogation of these data is limited by confident taxonomic classifications at high taxonomic resolution (genus- or species level) with the commonly applied universal reference databases. High-throughput full-length 16S rRNA gene sequencing combined with automated taxonomy assignment (AutoTax) can be used to create amplicon sequence variant resolved ecosystems-specific reference databases that are superior to the traditional universal reference databases. This approach was used here to create a custom reference database for bacteria and archaea based on 987,353 full-length 16S rRNA genes from Askov and Cologne soils. We evaluated the performance of the database using short-read amplicon data and found that it resulted in the increased genus- and species-level classification compared to commonly use universal reference databases. The custom database was utilized to evaluate the ecosystem-specific primer bias and taxonomic resolution of amplicon primers targeting the V5-V7 region of the 16S rRNA gene commonly used within the plant microbiome field. Finally, we demonstrate the benefits of custom ecosystem-specific databases through the analysis of V5-V7 amplicon data to identify new plant-associated microbes for two legumes and two cereal species.

摘要

集约化农业系统为不断增长的人口铺平了道路。然而,大量使用矿物肥料和农药可能会对养分循环和生物多样性产生负面影响。一种潜在的替代方法是利用植物与植物相关根际细菌之间的有益关系,以提高养分利用效率并提供病原体抗性。可以使用高通量16S rRNA基因扩增子测序来分析植物相关微生物群。然而,使用常用的通用参考数据库,在高分类分辨率(属或种水平)下进行可靠的分类学分类会限制对这些数据的分析。高通量全长16S rRNA基因测序与自动分类分配(AutoTax)相结合,可用于创建优于传统通用参考数据库的扩增子序列变体解析的特定生态系统参考数据库。本文采用这种方法,基于来自阿斯克夫和科隆土壤的987,353个全长16S rRNA基因,创建了一个细菌和古菌的定制参考数据库。我们使用短读扩增子数据评估了该数据库的性能,发现与常用的通用参考数据库相比,它在属和种水平上的分类有所增加。该定制数据库用于评估针对植物微生物组领域常用的16S rRNA基因V5-V7区域的扩增子引物的生态系统特异性引物偏差和分类分辨率。最后,我们通过分析V5-V7扩增子数据,展示了定制生态系统特异性数据库在识别两种豆类和两种谷类作物新的植物相关微生物方面的优势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f986/9669317/a022cc1d23a0/fmicb-13-942396-g0001.jpg

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