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BugSigDB捕获了在广泛的宿主相关微生物特征中差异性丰度的模式

Ludwig Geistlinger¹, Chloe Mirzayi^2,3, Fatima Zohra^2,3

¹Center for Computational Biomedicine, Harvard Medical School, Boston, MA, USA.

Nature biotechnology

|September 11, 2023

概括

BugSigDB是一个新的,社区可编辑的数据库,标准化了来自宿主相关微生物组研究的微生物签名. 它促进了跨研究的比较,揭示了诸如口腔病原生物在疾病中的肠内侵袭等模式.

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:

与宿主相关的微生物组研究正在迅速扩大.
在不同研究中对不同丰度微生物群签名进行系统的比较是具有挑战性的.

研究的目的:

介绍BugSigDB,一个手动策划的,社区可编辑的微生物签名数据库,来自差异丰度研究.
为了实现微生物组特征的高通量分析,并促进跨研究的比较.

主要方法:

从600多项已发表的研究中手动处理微生物特征.
包括关于研究地理,宿主体位,健康结果和方法的元数据.
开发用于标准化数据输入的受控词汇.

主要成果:

最初的发布包含了来自三个宿主物种的2500个策划签名.
BugSigDB允许分析签名相似性,分类种丰富性,共发生性和共识签名.
整个数据库的分析发现了与疾病相关的特征中的一致的实验条件和共同点,包括口腔病原生物肠道内侵袭.

结论:

BugSigDB为分析和比较主机相关微生物组数据提供了宝贵的资源.
该数据库有助于评估微生物组在各种条件和环境中的差异性丰度.
这些发现突出了实验一致性和疾病状态中共享的微生物模式.

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