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通过dbBact知识库获得泛微生物组生物学见解

Amnon Amir¹, Eitan Ozel², Yael Haberman³

¹Microbiome center, Sheba Medical Center, Israel.

Nucleic acids research

|June 16, 2023

概括

dbBact是一个新的资源,它结合了1000多项微生物组研究的数据. 它帮助研究人员解释他们的16S rRNA amplicon测序结果,通过将它们与大量的微生物群落和潜在污染物进行比较.

科学领域:

微生物学微生物学
生物信息学是一种生物信息学.
计算生物学计算生物学

背景情况:

16S rRNA amplicon测序是研究微生物群落的一个常见方法.
存在大量的数据,但将研究结果整合到不同研究中是具有挑战性的.
需要一个集中,精心策划的资源来将微生物组研究置于背景中.

研究的目的:

为了介绍dbBact,一个新的泛微生物群资源.
创建一个16S rRNA amplicon序列变体 (ASV) 和相关的本体学术语的协作存储库.
为用户数据集与dbBact数据库进行查询提供计算工具.

主要方法:

从1000多项研究中手动整理数据.
将多个本体学术语分配给ASVs.
开发用于数据库查询的计算工具.
用dbBact.重新分析了16项已发表的微生物组研究,使用dbBact.

主要成果:

dbBact包含来自1000多项研究的数据,将36万个ASV与6500个本体学术语联系起来.
重新分析揭示了新的宿主之间的相似性和潜在的宿主内部细菌来源.
确定了疾病之间的共同点,以及与疾病相关的细菌中较低的宿主特异性.
证明了环境来源,试剂污染物和交叉样本污染的检测.

结论:

通过整合多样化的研究数据,dbBact促进了对微生物群落的更广泛理解.
该资源有助于识别污染和理解宿主微生物相互作用.
结合跨息地和跨研究信息,可以增强生物过程的解释.

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