MSACL 2018 EU Abstract

Self-Classified Topic Area(s): Microbiology

Deciphering MALDI-TOF Identification of Bacteria Using a Proteogenomic Approach

Frédéric Jauffrit (1,2), Corinne Beaulieu (1), Pierre-Jean Cotte-Pattat (3), Victoria Girard (3), Martin Welker (1), Céline Brochier-Armanet (2), Jean-Pierre Flandrois (2), Jean-Philippe Charrier (1)
(1) Microbiology Research Department, Marcy l’Etoile, bioMérieux S.A., France (2) Université de Lyon, Université Lyon 1, CNRS, Laboratoire de Biométrie et Biologie Evolutive UMR 5558, F-69622 Villeurbanne, France (3) R&D Microbiology, bioMérieux S.A., La Balme Les Grottes, France

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Frédéric Jauffrit (Presenter)
Université de Lyon

Presenter Bio: Computer scientist by training, my thirst for challenging data science applications lead me to join the bioinformatics field.
I am currently at the tail end of my PhD program, where I combined phylogenomics and proteogenomics to unlock insight into bacterial identification by MALDI-TOF. This PhD is a colaboration between the LBBE and bioMérieux.
I developed the RiboDB database, a public resource for ribosomal proteins designed to help phylogeneticists resolve the evolutionary history of bacterial and archaeal species, from subspecies to phylum level.
Further, my work focused on adding knowledge to MALDI-TOF spectra as a means to better understand why MALDI-TOF enable bacterial identification. The finality of my work is to establish a link between proteomics and genomics for bacterial identification.

Relevant Financial Disclosures (within past 24 months)

Salary EZUS Lyon, university of Lyon

Discussing Products? YES, presenter will present educational content related to products/services of one or more ineligible company(ies) listed above.

Conflict mitigation IN PROCESS.

Abstract

Ribosomal and non-ribosomal proteins producing to peaks in WC-MALDI-TOF MS spectra were identified using proteogenomics and, as a case study, the VITEK® MS calibrant strain, Escherichia coli ATCC8739.
Protein expression was evidenced using LC-MS/MS data and a 6 frame translation of the entire genome. ORFs were inferred and MALDI-TOF peaks were assigned to possible protein m/z according to gene sequences, PTMs and charge states.
This method, applied on 832 E. coli spectra, allowed the identification of all major MALDI-TOF peaks (56 peaks above 3% relative intensity) and more deeply of 424 proteins corresponding to 649 peaks.