Successes and Pitfalls in Automated Dereplication Strategy Using Mass Spectrometry Data: a CASMI Experience

Title:Successes and Pitfalls in Automated Dereplication Strategy Using Mass Spectrometry Data: a CASMI Experience

Volume: 5 Issue: 1

Author(s): Samuel Bertrand, Catherine Roullier and Yann Guitton

Affiliation:

Keywords: Annotation, automated method, CASMI contest, dereplication, mass spectrometry, natural products.

Abstract: Background: Automated annotation of MS spectra remains highly challenging. Therefore, the Critical Assessment of Small Molecule Identification (CASMI) Contest (http://casmi-contest.org/) represents a unique opportunity to blindly evaluate an annotation workflow.

Objective: The 2014 CASMI Contest consisted of 42 MS and MS2 spectra (from “molecules detected in mammalian biofluids and tissues”, “natural products of plant, fungal or bacterial origin”, “synthetic or semi-synthetic molecules”), which had to be identified (molecular formulae and structures).

Methods: An R script based on the Rdisop and RMassBank packages was devised for the automated annotation of the provided spectra. Searching within various databases yielded the assignment of structures. Further discrimination between annotations was achieved using phylogenetic information and in silico fragmentation by competitive fragmentation modelling using CFM-ID.

Results: Successes and failures of the proposed script were investigated after release of the CASMI Contest solutions.

Conclusion: The CASMI Contest allowed identifying key points for the successful annotation of MS spectra. As an example, this study pointed out the importance of taking a large number of adducts into consideration (such as [M+H]+, [M+H-H2O]+, [M+Na]+, [M+K]+ and [M]+ in positive ionization) to avoid failed annotations.

Cite this article as:

Bertrand Samuel, Roullier Catherine and Guitton Yann, Successes and Pitfalls in Automated Dereplication Strategy Using Mass Spectrometry Data: a CASMI Experience, Current Metabolomics 2017; 5 (1) . https://dx.doi.org/10.2174/2213235X04666160622074357

DOI https://dx.doi.org/10.2174/2213235X04666160622074357	Print ISSN 2213-235X
Publisher Name Bentham Science Publisher	Online ISSN 2213-2368