Floros Dimitrios J, Jensen Paul R, Dorrestein Pieter C, Koyama Nobuhiro
Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, USA.
Skaggs School of Pharmacy and Pharmaceutical Sciences, Collaborative Mass Spectrometry Innovation Center, University of California, San Diego, La Jolla, CA, USA.
Metabolomics. 2016 Sep;12(9). doi: 10.1007/s11306-016-1087-5. Epub 2016 Aug 9.
Natural products from culture collections have enormous impact in advancing discovery programs for metabolites of biotechnological importance. These discovery efforts rely on the metabolomic characterization of strain collections.
Many emerging approaches compare metabolomic profiles of such collections, but few enable the analysis and prioritization of thousands of samples from diverse organisms while delivering chemistry specific read outs.
In this work we utilize untargeted LC-MS/MS based metabolomics together with molecular networking to.
This approach annotated 76 molecular families (a spectral match rate of 28 %), including clinically and biotechnologically important molecules such as valinomycin, actinomycin D, and desferrioxamine E. Targeting a molecular family produced primarily by one microorganism led to the isolation and structure elucidation of two new molecules designated maridric acids A and B.
Molecular networking guided exploration of large culture collections allows for rapid dereplication of know molecules and can highlight producers of uniques metabolites. These methods, together with large culture collections and growing databases, allow for data driven strain prioritization with a focus on novel chemistries.
来自菌种保藏中心的天然产物对推进具有生物技术重要性的代谢物发现计划具有巨大影响。这些发现工作依赖于菌株库的代谢组学表征。
许多新兴方法比较此类库的代谢组学图谱，但很少有方法能够在提供化学特异性读数的同时，对来自不同生物体的数千个样本进行分析和排序。
在这项工作中，我们利用基于非靶向液相色谱-串联质谱的代谢组学结合分子网络技术。
该方法注释了76个分子家族（光谱匹配率为28%），包括临床上和生物技术上重要的分子，如缬氨霉素、放线菌素D和去铁胺E。针对主要由一种微生物产生的一个分子家族，导致分离并阐明了两种新分子，命名为马里德里酸A和B。
分子网络引导的大型菌株库探索允许对已知分子进行快速去重复，并可突出独特代谢物的生产者。这些方法，连同大型菌株库和不断增长的数据库，可以实现以新化学物质为重点的数据驱动菌株排序。
