A protocol for high-throughput, untargeted forest community metabolomics using mass spectrometry molecular networks

一种利用质谱分子网络进行高通量、非靶向森林群落代谢组学分析的方案

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作者:Brian E Sedio ,Cristopher A Boya P ,Juan Camilo Rojas Echeverri

Abstract

Premise of the study: We describe a field collection, sample processing, and ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) instrumental and bioinformatics method developed for untargeted metabolomics of plant tissue and suitable for molecular networking applications. Methods and results: A total of 613 leaf samples from 204 tree species was collected in the field and analyzed using UHPLC-MS/MS. Matching of molecular fragmentation spectra generated over 125,000 consensus spectra representing unique molecular structures, 26,410 of which were linked to at least one structurally similar compound. Conclusions: Our workflow is able to generate molecular networks of hundreds of thousands of compounds representing broad classes of plant secondary chemistry and a wide range of molecular masses, from 100 to 2500 daltons, making possible large-scale comparative metabolomics, as well as studies of chemical community ecology and macroevolution in plants. Keywords: chemical ecology; liquid chromatography; molecular networking; tandem mass spectrometry; tropical forest ecology; untargeted metabolomics.

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