Mass spectral molecular networking of living microbial colonies
Mass spectral molecular networking of living microbial colonies
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DOI：
10.1073/pnas.1203689109
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发表时间：
2012-06-26
影响因子：
11.1
通讯作者：
Dorrestein, Pieter C.
中科院分区：
文献类型：
--
作者：
Watrous, Jeramie;Roach, Patrick;Dorrestein, Pieter C.
将掌管化学与微生物菌落的基因组学和表型相结合一直是微生物学中的“圣杯”。这项工作描述了一种高度敏感的，广泛的和具有成本效益的方法，可以直接从培养皿中直接从培养皿中对活微生物菌落进行代谢分析，而无需任何样品制备。纳米喷雾解吸电喷雾电离质谱法（MS），结合MS数据和分子网络的比对，可以监测来自不同细菌属的活微生物菌落的代谢产物，包括枯草芽孢杆菌，枯草链球菌，coelecolces coelicolor，mycobocterium，mycobocterium，smegmatium smegmatis和perseosan和psseodon。这项工作表明，通过使用这些工具可视化细菌相互作用中的小分子变化，由于改善了MS/MS数据的组织，可以将见解获得细菌发育过程。为了验证这个实验平台，在假单胞菌SP上进行了代谢分析。 SH-C52，可保护甜菜植物免受特定土壤传播真菌的感染[R. Mendes等。 （2011）科学332：1097-1100]。菌株SHC52的抗真菌作用归因于tanamycin，tanamycin是一种由非核糖体肽合成酶基因簇编码的预测脂肽。我们的技术与我们最近开发的肽基因组学策略结合使用，实现了毛霉素的检测和部分表征，并表明它是属于抗真菌药物的溶菌菌素家族的单氯化脂蛋白。总之，此处介绍的平台为我们了解现场微生物菌落和社区中代谢物生产的时空动态的能力提供了重大进步。
Integrating the governing chemistry with the genomics and phenotypes of microbial colonies has been a "holy grail" in microbiology. This work describes a highly sensitive, broadly applicable, and cost-effective approach that allows metabolic profiling of live microbial colonies directly from a Petri dish without any sample preparation. Nanospray desorption electrospray ionization mass spectrometry (MS), combined with alignment of MS data and molecular networking, enabled monitoring of metabolite production from live microbial colonies from diverse bacterial genera, including Bacillus subtilis, Streptomyces coelicolor, Mycobacterium smegmatis, and Pseudomonas aeruginosa. This work demonstrates that, by using these tools to visualize small molecular changes within bacterial interactions, insights can be gained into bacterial developmental processes as a result of the improved organization of MS/MS data. To validate this experimental platform, metabolic profiling was performed on Pseudomonas sp. SH-C52, which protects sugar beet plants from infections by specific soil-borne fungi [R. Mendes et al. (2011) Science 332: 1097-1100]. The antifungal effect of strain SHC52 was attributed to thanamycin, a predicted lipopeptide encoded by a nonribosomal peptide synthetase gene cluster. Our technology, in combination with our recently developed peptidogenomics strategy, enabled the detection and partial characterization of thanamycin and showed that it is a monochlorinated lipopeptide that belongs to the syringomycin family of antifungal agents. In conclusion, the platform presented here provides a significant advancement in our ability to understand the spatiotemporal dynamics of metabolite production in live microbial colonies and communities.