Discrimination of Escherichia coli, Shigella flexneri , and Shigella sonnei using lipid profiling by MALDI‐TOF mass spectrometry paired with machine learning - Université de Rennes Accéder directement au contenu
Article Dans Une Revue MicrobiologyOpen Année : 2022

Discrimination of Escherichia coli, Shigella flexneri , and Shigella sonnei using lipid profiling by MALDI‐TOF mass spectrometry paired with machine learning

Eric Farfour

Résumé

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.
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Origine : Publication financée par une institution

Dates et versions

inserm-03760632 , version 1 (25-08-2022)

Identifiants

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Jade Pizzato, Wenhao Tang, Sandrine Bernabeu, Rémy Bonnin, Emmanuelle Bille, et al.. Discrimination of Escherichia coli, Shigella flexneri , and Shigella sonnei using lipid profiling by MALDI‐TOF mass spectrometry paired with machine learning. MicrobiologyOpen, 2022, 11 (4), pp.e1313. ⟨10.1002/mbo3.1313⟩. ⟨inserm-03760632⟩
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