Hernandez Antonio, Krull Nyssa K, Murphy Brian T
Department of Pharmaceutical Sciences, College of Pharmacy, University of Illinois at Chicago, Chicago, IL 60607, United States.
Center for Biomolecular Sciences, College of Pharmacy, University of Illinois at Chicago, Chicago, IL 60607, United States.
ISME Commun. 2025 Mar 13;5(1):ycaf046. doi: 10.1093/ismeco/ycaf046. eCollection 2025 Jan.
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.
细菌天然产物对全球药物研发工作做出了巨大贡献。此外,将研究较少的细菌类群纳入研发流程仍是一种很有前景的方法,可为这项工作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点。在此,我们提出一种方法,该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,从环境样本中对研究较少的细菌进行靶向分离。用代表目标研究较少属的50个已鉴定菌株的光谱作为种子,构建了479个未知细菌分离株的MS蛋白质谱树状图。该方法在识别目标类群的代表方面非常有效,当在树状图中实施估计的属水平截断值时,成功率达到86.3%。总体而言,这项研究表明了MALDI-MS/IDBac在高通量挖掘环境细菌分离株集合中目标类群的潜力,特别是在没有专有软件的情况下。它还为形态学和基因测序分析提供了一种经济高效的替代方法,这些分析通常用于指导从大型细菌分离株集合中进行鉴定和优先级排序策略。