Discrimination of Escherichia coli, Shigella flexneri, and Shigella sonnei using lipid profiling by MALDI-TOF mass spectrometry paired with machine learning.
Jade Pizzato, Wenhao Tang, Sandrine Bernabeu, Rémy A Bonnin, Emmanuelle Bille, Eric Farfour, Thomas Guillard, Olivier Barraud, Vincent Cattoir, Chloe Plouzeau, Stéphane Corvec, Vahid Shahrezaei, Laurent Dortet, Gerald Larrouy-Maumus
Author Information
Jade Pizzato: Faculty of Natural Sciences, Department of Life Sciences, MRC Centre for Molecular Bacteriology & Infection, Imperial College London, England.
Wenhao Tang: Faculty of Natural Sciences, Department of Mathematics, Imperial College London, England.
Sandrine Bernabeu: CHU de Bicêtre, Laboratoire de Bactériologie-Hygiène, Assistance Publique des Hôpitaux de Paris, Le Kremlin-Bicêtre, France.
Rémy A Bonnin: INSERM UMR 1184, Team RESIST, Faculté de Médecine, Université Paris-Saclay, Le Kremlin-Bicêtre, France.
Emmanuelle Bille: Service de Microbiologie, Assistance Publique-Hôpitaux de Paris, Hôpital Necker Enfants-Malades, AP-HP Centre-Université de Paris, Paris, France.
Eric Farfour: Service de Biologie Clinique, Hôpital Foch, Suresnes, France.
Thomas Guillard: Université de Reims-Champagne-Ardenne, Inserm UMR-S 1250 P3Cell, SFR CAP-Santé, Laboratoire de Bactériologie-Virologie-Hygiène, Hospitalière-Parasitologie-Mycologie, Hôpital Robert Debré, CHU Reims, Reims, France.
Olivier Barraud: CHU Limoges, Service de Bactériologie-Virologie-Hygiène, CIC1435, INSERM 1092, Université de Limoges, UMR, Limoges, France.
Vincent Cattoir: Service de Bactériologie-Hygiène, CHU de Rennes, Rennes, France.
Chloe Plouzeau: Service de Bactériologie et d'Hygiène hospitalière, Unité de microbiologie moléculaire et séquençage, CHU de Poitiers, Poitiers, France.
Stéphane Corvec: Université de Nantes, CHU Nantes, Service de Bactériologie et des Contrôles Microbiologiques, INSERM, INCIT UMR 1302 F- 44000 Nantes, France.
Vahid Shahrezaei: Faculty of Natural Sciences, Department of Mathematics, Imperial College London, England.
Laurent Dortet: CHU de Bicêtre, Laboratoire de Bactériologie-Hygiène, Assistance Publique des Hôpitaux de Paris, Le Kremlin-Bicêtre, France.
Gerald Larrouy-Maumus: Faculty of Natural Sciences, Department of Life Sciences, MRC Centre for Molecular Bacteriology & Infection, Imperial College London, England. ORCID
Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) has become a staple in clinical microbiology laboratories. Protein-profiling of bacteria using this technique has accelerated the identification of pathogens in diagnostic workflows. Recently, lipid profiling has emerged as a way to complement bacterial identification where protein-based methods fail to provide accurate results. This study aimed to address the challenge of rapid discrimination between Escherichia coli and Shigella spp. using MALDI-TOF MS in the negative ion mode for lipid profiling coupled with machine learning. Both E. coli and Shigella species are closely related; they share high sequence homology, reported for 16S rRNA gene sequence similarities between E. coli and Shigella spp. exceeding 99%, and a similar protein expression pattern but are epidemiologically distinct. A bacterial collection of 45 E. coli, 48 Shigella flexneri, and 62 Shigella sonnei clinical isolates were submitted to lipid profiling in negative ion mode using the MALDI Biotyper Sirius® system after treatment with mild-acid hydrolysis (acetic acid 1% v/v for 15 min at 98°C). Spectra were then analyzed using our in-house machine learning algorithm and top-ranked features used for the discrimination of the bacterial species. Here, as a proof-of-concept, we showed that lipid profiling might have the potential to differentiate E. coli from Shigella species using the analysis of the top five ranked features obtained by MALDI-TOF MS in the negative ion mode of the MALDI Biotyper Sirius® system. Based on this new approach, MALDI-TOF MS analysis of lipids might help pave the way toward these goals.
