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Dernière mise à jour : Mai 2018

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SpecOMS: software for exploring the protein universe

Analyse structurale fine par MS/MS et par mobilité ionique
© INRA
Deciphering and unravelling modifications carried by proteins is a major scientific challenge for progress in healthcare and biology.

Tandem MS/MS-mode spectrometry is the go-to technique most widely used for protein characterization, but the quality of the results depends on the sample preparation protocol, on the analytical mass spectrometry expertise mobilized, and on the ability of the software to handle and interpret the tens of thousands of spectra generated. The SpecOMS software developed in collaboration between the BIA unit and the LS2N laboratory demonstrates that the fragment ion accuracy reachable with the latest generations of mass spectrometers paves the way to a new generation of spectra algorithms. By exploiting a reorganization of the spectral data at the all-sample level in an appropriately-geared data structure and with efficient data access modes, SpecOMS can handle pairwise comparisons of the tens of thousands of experimental spectra from tandem mass analysis against hundreds of thousands of spectra, such as the spectra corresponding to the human proteome. SpecOMS is currently the world’s fastest mass spectral analysis software and the least-memory intensive, taking just minutes on a standard desktop PC, which makes it easy to use on any and all mass spectrometry platforms. The method provides a profile of the modifications brought by the proteins in a sample, and can even reveal modifications that are simply impossible to get with other approaches available.

Participants

  • Laboratory of Digital Sciences— Nantes (LS2N) under the Griote program, financed by the Pays de la Loire region.
  • Thesis by Matthieu David, under thesis supervisor Guillaume Fertin

Publications

David, M., Fertin, G., Rogniaux, H., and Tessier, D. (2017) SpecOMS: A Full Open Modification Search Method Performing All-to-All Spectra Comparisons within Minutes, J Proteome Res 16, 3030-3038, DOI: 10.1021/acs.jproteome.7b00308

David, M., Fertin, G., and Tessier, D. (2016) SpecTrees: an efficient without a priori data structure for MS/MS spectra identification, In 16th Workshop on Algorithms in Bioinformatics (WABI 2016), Springer-Verlag, Aarhus, Denmark.