Wang Meng, Lei Ming, He Hailun
School of Life Science, Central South University, Changsha 410000, China.
Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.
Eng Microbiol. 2023 Apr 14;3(3):100087. doi: 10.1016/j.engmic.2023.100087. eCollection 2023 Sep.
China has a rich history of cultivating medicinal plants, whose root microbial communities closely interact with the medicinal plants, thereby influencing their growth, health, and medicinal properties. Currently, researchers widely use 16S rRNA gene amplicon sequencing to study these root microbial communities. However, publicly available sequence datasets often lack essential sample information or contain errors, impeding the reuse of the datasets in the future. In this study, we aimed to create a united, reliable, and readily usable source of 16S rRNA gene sequences for medicinal plant root microbiomes. We compiled a catalog of 1392 microbiome samples for 58 medicinal plants from 58 studies, and manually provided essential sample information based on the experimental setup described in the associated papers. We then processed the sequences using a custom pipeline, generating a united catalog of operational taxonomic units (OTUs) and conducting taxonomic classification. We also predicted the ecological functions of the communities for each sample. Finally, we used this dataset, to compare the rhizosphere bacterial communities of from Fujian and Guizhou Provinces, revealing significant differences in the community composition of the same plant from different geographic locations. By providing a comprehensive and united catalog of amplicon sequences and OTUs for medicinal plant root bacterial communities, this study offers an invaluable resource for future comparative studies and data mining.
中国在药用植物栽培方面有着悠久的历史，药用植物的根系微生物群落与药用植物密切相互作用，从而影响其生长、健康和药用特性。目前，研究人员广泛使用16S rRNA基因扩增子测序来研究这些根系微生物群落。然而，公开可用的序列数据集往往缺乏必要的样本信息或包含错误，阻碍了这些数据集在未来的再利用。在本研究中，我们旨在为药用植物根微生物组创建一个统一、可靠且易于使用的16S rRNA基因序列来源。我们从58项研究中整理了58种药用植物的1392个微生物组样本的目录，并根据相关论文中描述的实验设置手动提供了必要的样本信息。然后，我们使用自定义流程处理这些序列，生成一个统一的操作分类单元（OTU）目录并进行分类学分类。我们还预测了每个样本群落的生态功能。最后，我们使用这个数据集比较了来自福建和贵州的根际细菌群落，揭示了同一植物在不同地理位置的群落组成存在显著差异。通过为药用植物根细菌群落提供一个全面统一的扩增子序列和OTU目录，本研究为未来的比较研究和数据挖掘提供了宝贵的资源。
