Crüsemann Max, O'Neill Ellis C, Larson Charles B, Melnik Alexey V, Floros Dimitrios J, da Silva Ricardo R, Jensen Paul R, Dorrestein Pieter C, Moore Bradley S
Research Support Center in Natural and Synthetic Products, Department of Physics and Chemistry, Faculty of Pharmaceutical Sciences, University of São Paulo , Ribeirão Preto, 14040-903, Brazil.
J Nat Prod. 2017 Mar 24;80(3):588-597. doi: 10.1021/acs.jnatprod.6b00722. Epub 2016 Nov 11.
In order to expedite the rapid and efficient discovery and isolation of novel specialized metabolites, while minimizing the waste of resources on rediscovery of known compounds, it is crucial to develop efficient approaches for strain prioritization, rapid dereplication, and the assessment of favored cultivation and extraction conditions. Herein we interrogated bacterial strains by systematically evaluating cultivation and extraction parameters with LC-MS/MS analysis and subsequent dereplication through the Global Natural Product Social Molecular Networking (GNPS) platform. The developed method is fast, requiring minimal time and sample material, and is compatible with high-throughput extract analysis, thereby streamlining strain prioritization and evaluation of culturing parameters. With this approach, we analyzed 146 marine Salinispora and Streptomyces strains that were grown and extracted using multiple different protocols. In total, 603 samples were analyzed, generating approximately 1.8 million mass spectra. We constructed a comprehensive molecular network and identified 15 molecular families of diverse natural products and their analogues. The size and breadth of this network shows statistically supported trends in molecular diversity when comparing growth and extraction conditions. The network provides an extensive survey of the biosynthetic capacity of the strain collection and a method to compare strains based on the variety and novelty of their metabolites. This approach allows us to quickly identify patterns in metabolite production that can be linked to taxonomy, culture conditions, and extraction methods, as well as informing the most valuable growth and extraction conditions.
为了加快新型特殊代谢产物的快速高效发现与分离,同时尽量减少在已知化合物重新发现上的资源浪费,开发高效的菌株优先级排序、快速去重复以及有利培养和提取条件评估方法至关重要。在此,我们通过使用液相色谱 - 串联质谱分析系统评估培养和提取参数,并随后通过全球天然产物社会分子网络(GNPS)平台进行去重复,对细菌菌株进行了研究。所开发的方法速度快,所需时间和样品材料最少,并且与高通量提取物分析兼容,从而简化了菌株优先级排序和培养参数评估。通过这种方法,我们分析了146株海洋盐孢菌属和链霉菌属菌株,这些菌株采用多种不同方案进行培养和提取。总共分析了603个样品,产生了约180万个质谱图。我们构建了一个综合分子网络,鉴定出15个不同天然产物及其类似物的分子家族。当比较生长和提取条件时,该网络的大小和广度显示出分子多样性方面具有统计学支持的趋势。该网络提供了对菌株集合生物合成能力的广泛调查,以及一种基于代谢产物的多样性和新颖性来比较菌株的方法。这种方法使我们能够快速识别代谢产物产生中的模式,这些模式可以与分类学、培养条件和提取方法相关联,同时也能为最有价值的生长和提取条件提供信息。