The WEIZMASS spectral library for high-confidence metabolite identification

Nir Shahaf, Ilana Rogachev, Uwe Heinig, Sagit Meir, Sergey Malitsky, Maor Battat, Hilary Wyner, Shuning Zheng, Ron Wehrens, Asaph Aharoni

Research output: Contribution to journalArticlepeer-review

Abstract

Annotation of metabolites is an essential, yet problematic, aspect of mass spectrometry (MS)-based metabolomics assays. The current repertoire of definitive annotations of metabolite spectra in public MS databases is limited and suffers from lack of chemical and taxonomic diversity. Furthermore, the heterogeneity of the data prevents the development of universally applicable metabolite annotation tools. Here we present a combined experimental and computational platform to advance this key issue in metabolomics. WEIZMASS is a unique reference metabolite spectral library developed from high-resolution MS data acquired from a structurally diverse set of 3,540 plant metabolites. We also present MatchWeiz, a multi-module strategy using a probabilistic approach to match library and experimental data. This strategy allows efficient and high-confidence identification of dozens of metabolites in model and exotic plants, including metabolites not previously reported in plants or found in few plant species to date.

Original languageEnglish
Article number12423
Number of pages13
JournalNature Communications
Volume7
DOIs
StatePublished - 30 Aug 2016

All Science Journal Classification (ASJC) codes

  • General Chemistry
  • General Biochemistry,Genetics and Molecular Biology
  • General Physics and Astronomy

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