利用 MALDI-TOF 质谱仪和 IDBac 从环境中挖掘未被充分研究的细菌属。

IF 5.1 Q1 ECOLOGY
ISME communications Pub Date : 2025-03-13 eCollection Date: 2025-01-01 DOI:10.1093/ismeco/ycaf046
Antonio Hernandez, Nyssa K Krull, Brian T Murphy
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引用次数: 0

摘要

细菌天然产物对全球药物发现工作做出了巨大贡献。此外,将未充分研究的细菌分类群纳入发现管道仍然是一种有希望的方法,可以为这一努力提供急需的化学多样性。不幸的是,研究人员缺乏快速有效的技术来实现这一目标。在这里,我们提出了一种方法,利用基质辅助激光解吸/电离飞行时间质谱(MALDI-TOF MS)和生物信息学平台IDBac从环境样品中进行靶向分离。从479个未知细菌分离株中提取的MS蛋白谱树状图与50个表征菌株的谱相结合,这些菌株代表了未被研究的目标属。该方法在识别目标分类群的代表时非常有效,当在树形图中实现估计的属水平截断时,成功率为86.3%。总的来说,本研究显示了MALDI-MS/IDBac在高通量挖掘目标分类群的环境细菌分离物收集方面的潜力,特别是在没有专有软件的情况下。它还提供了一种具有成本效益的形态学和基因测序分析替代方案,这些分析通常用于指导大型细菌分离物收集的鉴定和优先排序策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Use of MALDI-TOF mass spectrometry and IDBac to mine for understudied bacterial genera from the environment.

Bacterial natural products have greatly contributed to the global drug discovery effort. Further, the incorporation of understudied bacterial taxa into discovery pipelines remains a promising approach to supply much needed chemical diversity to this effort. Unfortunately, researchers lack rapid and efficient techniques to accomplish this. Here we present an approach that employs matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) and the bioinformatics platform IDBac to perform targeted isolation of understudied bacteria from environmental samples. A dendrogram of MS protein spectra from 479 unknown bacterial isolates was seeded with spectra from 50 characterized strains that represented target understudied genera. This method was highly effective at identifying representatives from target taxa, demonstrating an 86.3% success rate when an estimated genus level cutoff was implemented in the dendrogram. Overall, this study shows the potential of MALDI-MS/IDBac to mine environmental bacterial isolate collections for target taxa in high-throughput, particularly in the absence of proprietary software. It also provides a cost-effective alternative to morphology and gene-sequencing analyses that are typically used to guide identification and prioritization strategies from large bacterial isolate collections.

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