Imperial College London
Alternate

DrGeraldLarrouy-Maumus

Faculty of Natural Sciences, Department of Life Sciences

Reader in Molecular Microbiology
 
 
 
//

Contact

 

+44 (0)20 7594 7463g.larrouy-maumus

 
 
//

Location

 

3.42Flowers buildingSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@article{Pizzato:2022:10.1002/mbo3.1313,
author = {Pizzato, J and Tang, W and Bernabeu, S and Bonnin, RA and Bille, E and Farfour, E and Guillard, T and Barraud, O and Cattoir, V and Plouzeau, C and Corvec, S and Shahrezaei, V and Dortet, L and Larrouy-Maumus, G},
doi = {10.1002/mbo3.1313},
journal = {MicrobiologyOpen},
pages = {1--14},
title = {Discrimination of Escherichia coli, Shigella flexneri, and Shigella sonnei using lipid profiling by MALDI-TOF mass spectrometry paired with machine learning},
url = {http://dx.doi.org/10.1002/mbo3.1313},
volume = {11},
year = {2022}
}
Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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.
AU  - Pizzato,J
AU  - Tang,W
AU  - Bernabeu,S
AU  - Bonnin,RA
AU  - Bille,E
AU  - Farfour,E
AU  - Guillard,T
AU  - Barraud,O
AU  - Cattoir,V
AU  - Plouzeau,C
AU  - Corvec,S
AU  - Shahrezaei,V
AU  - Dortet,L
AU  - Larrouy-Maumus,G
DO  - 10.1002/mbo3.1313
EP  - 14
PY  - 2022///
SN  - 2045-8827
SP  - 1
TI  - Discrimination of Escherichia coli, Shigella flexneri, and Shigella sonnei using lipid profiling by MALDI-TOF mass spectrometry paired with machine learning
T2  - MicrobiologyOpen
UR  - http://dx.doi.org/10.1002/mbo3.1313
UR  - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000844013100001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://onlinelibrary.wiley.com/doi/10.1002/mbo3.1313
UR  - http://hdl.handle.net/10044/1/100902
VL  - 11
ER  -
Download