Back

Phenotype-genotype discordance in antimicrobial resistance profiles of Gram-negative uropathogens recovered from catheter-associated urinary tract infections in Egypt

Eladawy, M.; Heslop, N.; Negus, D.; Thomas, J.; Hoyles, L.

2025-04-22 microbiology
10.1101/2025.04.17.649370 bioRxiv
Show abstract

Catheter-associated urinary tract infections (CAUTIs) are among the most common healthcare-associated infections in low- and middle-income countries (LMICs). In this study, phenotypic (EUCAST AMR profiles) and genomic data were generated for 132 isolates (67 Escherichia coli, 14 Pseudomonas aeruginosa, 11 Klebsiella pneumoniae, 9 Proteus mirabilis, 8 Providencia spp., 5 Enterobacter hormaechei, and 18 rare uropathogens) recovered from CAUTIs in an Egyptian hospital. Among the Escherichia coli isolates, phylogroup B2 was most represented (53.7 %), followed by B1 (19.4 %), A (11.9 %), D (7.4 %), F (5.9 %) and C (1.4 %). Several (22/132, 16.6 %) isolates were multidrug-resistant, while almost half (62/132, 46.9 %) were extensively drug-resistant. Comparison of phenotypic data with genotypic data from three different AMR-profiling tools (ResFinder, CARD, AMRFinder) highlighted phenotype-genotype discordance as an important consideration in resistome studies in Egypt, with a total concordance of 91.1 %, 85.7 %, and 80.3 % for ResFinder, CARD and AMRFinder, respectively. Pseudomonas, at the species level, exhibited the greatest discordance. At the antimicrobial level, meropenem was subject to greatest discordance. In addition to the findings from our comparative analyses, new AMR variants are reported for Egypt for Pseudomonas (OXA-486, OXA-488, OXA-905, IMP-43, PDC-35, PDC-45, PDC-201) and Escherichia coli (TEM-176, TEM-190). In summary, we show that there is phenotype-genotype discordance in AMR profiling among CAUTI isolates, highlighting the need for comprehensive approaches in resistome studies. We also show the genomic diversity of Gram-negative uropathogens contributing to disease burden in a little-studied LMIC setting.

Published in Journal of Antimicrobial Chemotherapy (predicted rank #12) · training set

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.