Epidemiology and discrimination of clinically relevant Enterobacter cloacae complex species in Northern Portugal

• Autor(es): Martins, Rita ; Gonçalves, Ana Beatriz ; Marques Silva, Luís ; Castro, Ana Paula ; Read, Maria Antónia ; Alves, Valquíria ; Peixe, Luísa ; Novais, Ângela
• Data: 2024
• Origem: Scientific Letters
• Assunto(s): Poster
• Tipo de Documento: Artigo científico
• Idioma: Inglês

Descrição

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.