Epidemiology and discrimination of clinically relevant Enterobacter cloacae complex species in Northern Portugal
DOI:
https://doi.org/10.48797/sl.2024.167Keywords:
PosterAbstract
Background: E. cloacae complex species are increasingly implicated in infections caused by multidrug-resistant bacteria, but their epidemiology is scarce due to the limitations of automated methods in accurate species identification (e.g. VITEK2/ MALDI–TOF MS) [1]. FT-IR is a promising quick, simple and low-cost alternative for bacterial discrimination [2]. Objective: We aim to assess the epidemiology of Enterobacter spp. isolates causing infections in two hospitals from North of Portugal, and the potential of FT-IR to differentiate the main clinically relevant Enterobacterspecies. Methods: We analyzed forty-five Enterobacter isolates from infection (n=43) or colonization (n=2) identified between 2019-2021 by VITEK2. Species identification was confirmed by PCR and sequencing of hsp60, used to build a phylogenetic tree with MEGA7 software. Antibiotic susceptibility testing was performed by standard methods according to EUCAST. Spectra from the most frequent species were acquired in the ATR mode of FT-IR equipment (Spectrum Two, Perkin-Elmer) in standardized conditions (4000-400cm-1; 4cm-1 resolution), processed (SNV, Saviztky-Golay) and used to identify species discriminatory profiles using PLSDA with Clover MS Data Analysis software, as described [3]. Results: Only 73% of the isolates were Enterobacter identified as E. hormaechei (n=19), E. kobei (n=7), E. asburiae (n=3), E. bugandensis (n=2), E. cloacae (n=1) and E. ludwigii (n=1). A few isolates produced VIM-1 (E. hormaechei), KPC (E. cloacae) or ESBL (4 species) The remaining isolates were identified as K. aerogenes (n=7), K. variicola (n=3), E. coli (n=1) and K. michiganensis (n=1). By using a PLSDA model, we were able to discriminate E. kobei and E. hormaechei with 92% average correct predictions. Conclusions: We found that E. hormaechei and E. kobei are the most frequent species causing hospital infections and that FT-IR can accurately differentiate these species, opening the possibility for its expansion to other E. cloacae complex species.
References
1. Vogt S, Löffler K, Dinkelacker AG, Bader B, Autenrieth IB, Peter S, Liese J. Fourier-Transform Infrared (FTIR) Spectroscopy for Typing of Clinical Enterobacter cloacae Complex Isolates. 2019. Front. Microbiol. 10:2582.
2. Novais, Â., Freitas, A. R., Rodrigues, C., Peixe L. Fourier transform infrared spectroscopy: unlocking fundamentals and prospects for bacterial strain typing. Eur J Clin Microbiol Infect Dis, 2019. 38 (3): p. 427-448.
3. Novais, Â., Gonçalves, A. B., Ribeiro, T.G., Freitas, A.R., Méndez, G., Mancera, L., Read, A., Alves, V., López-Cerero, L., Rodríguez-Bano, J., Pascual, A., Peixe L. Development and validation of a quick, automated, and reproducible ATR FT-IR spectroscopy machine-learning model for Klebsiella pneumoniae typing. 2024. J Clin Microbiol, 62(2), e0121123.
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Copyright (c) 2024 Rita Martins, Ana Beatriz Gonçalves, Luís Marques Silva, Ana Paula Castro, Maria Antónia Read, Valquíria Alves, Luísa Peixe, Ângela Novais
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