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Lactobacillus delbrueckii subsp. allosunkii and lactis as emerging human uropathogens in elderly patients

François Guérin, Mohamed Sassi, François Gravey, Asma Zouari, Benjamin Quenet, Maxime Lecourt, Pauline Ract, Charlotte Michaux et al.

Journal of Clinical Microbiology, 2025

48 participants · 3 citations

Abstract

ABSTRACT Lactobacillus delbrueckii has been considered a very rare cause of human urinary tract infections (UTIs). However, little is known about its clinical significance and antimicrobial susceptibility, and genomic data from clinical isolates are lacking. This study aimed at analyzing clinical, microbiological, and genomic data of L. delbrueckii urinary isolates. All L. delbrueckii isolates collected from patients hospitalized in a French university hospital from 2014 to 2016 were included. Clinical and biological data were gathered. Species identification was performed by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry, and MICs were determined using the broth microdilution method. Whole genome sequencing (WGS) was conducted (Illumina MiSeq 2 × 300 bp), and genomes were compared using three approaches (multilocus sequence typing [MLST], average nucleotide identity [ANI], and core genome single nucleotide polymorphism [SNP]). From 2014 to 2016, 48 isolates of L. delbrueckii were recovered from the urine of 48 patients (mean age = 84 years; sex ratio M/F = 0.04). Nearly half (44%) of patients were diagnosed with a UTI, and all had significant cultures (≥10 5 CFU/mL) with a positive direct examination in >90% of cases. The majority of isolates were susceptible to most antibiotics (especially β-lactams), whereas they seemed intrinsically resistant to fosfomycin and metronidazole. Subspecies identification was consistent across the…

How strong is the evidence?

Evidence Hub reads this as a case series, done in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health. Reported size: 48 participants or records.

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