ESCMID 2026 Highlights from Day 3

Early Antimicrobial Resistance Prediction Using Urinary Proteomics and Machine Learning

Presenter: Emelie Lemann

This study evaluated the use of urinary proteomics combined with machine learning (ML) to predict antimicrobial resistance (AMR) in E. coli urinary tract infections using clinical samples. Proteomic data from urine samples were analysed alongside resistance phenotypes, and random forest ML models were trained to predict resistance to 10 antibiotics. Single-label models (one antibiotic at a time) and an exploratory multi-label model (multiple antibiotics simultaneously) were developed. Single-label models showed high predictive accuracy, with the best performance for cefadroxil (99.5%) and cefotaxime (99.3%), as well as meropenem (98.9%) and mecillinam (98.4%). Other antibiotics were predicted with accuracies ranging from 77.2% to 98.2%.

The multi-label model achieved 59.3% average accuracy, with a macro-F1 score of 68.6% and a weighted F1 score of 91.4%, indicating strong performance for common resistance patterns.

Overall, urinary proteomic signatures enabled accurate prediction of AMR, supporting their potential use in early, sample-specific resistance assessment.

A Next-Generation Platform for Culture-Free AMR Gene Identification in Human Infections

Presenter: Tanshi Mehrotra

This multicentric genomics study characterized the antimicrobial resistance (AMR) landscape in India and explored its relevance for developing rapid diagnostic tools for sepsis, urinary tract infections (UTIs), and respiratory infections. A total of 2,720 genomes were analysed, including 203 clinical isolates from 13 Gram-negative bacterial species collected between 2016 and 2022. Phenotypic susceptibility data for 17 antibiotics supported genomic identification of AMR alleles. Phylogeographic analysis, multilocus sequence typing (MLST), and pan-genome reconstruction demonstrated substantial genetic diversity, lineage expansion, and evolution of resistant pathogens. Extracellular pathogens showed extensive drug resistance, with over 70% of isolates exhibiting extensively drug-resistant profiles, largely driven by horizontally acquired AMR genes. A wide range of AMR determinants was identified, associated with 38 plasmid types, indicating high transmission potential. Regionally enriched high-risk international clones were also observed.

The study further evaluated key AMR gene sets in Klebsiella pneumoniae, Acinetobacter baumannii, Escherichia coli, and Pseudomonas aeruginosa across antibiotic contexts.

In conclusion, the validated AMR gene panels provide a foundation for developing region-specific rapid diagnostics targeting major resistance determinants.

Epidemiology of Penicillin-Binding Protein 3 Variants in Carbapenem-Resistant Escherichia coli Isolates from France

Presenter: Imene Mehidi

This genomic study analysed 1,837 Escherichia coli isolates (July 2023–October 2024) to investigate penicillin-binding protein 3 (PBP3) alterations and their association with carbapenem resistance. PBP3 modifications were identified in 64.9% (1,189/1,837) of isolates, with 56 polymorphisms detected. The most common changes were two amino acid substitutions (56.7%; n=674) and four–amino acid insertions (33.8%; n=402) at positions 331–334, resulting in YRIN, YRIK, or YTIP duplications. The predominant carbapenemases were OXA-244 (27.8%) and NDM-5 (26.3%). High-risk sequence types included ST38 (22.3%), ST410 (10.3%), and ST167 (6.9%). Common resistance genes included CTX-M-15 (66.5%) and CMY-2 (8.5%).

Isolates with PBP3 insertions showed reduced susceptibility to last-line antibiotics: 98.9% had cefiderocol MICs >2 µg/mL, and 22.36% had aztreonam/avibactam MICs ≥4 µg/mL.

Overall, PBP3 insertions, often linked with NDM enzymes and high-risk clones, contribute to increasing resistance and reduced efficacy of key antibiotics.

Molecular Antimicrobial Resistance Gene Profiles in Community-Acquired, Healthcare-Associated, and Hospital-Onset E. Coli and K. Pneumoniae Bacteraemia

Presenter: Leyla Genç

This prospective study evaluated resistance determinants in Escherichia coli and Klebsiella pneumoniae bloodstream infections across community-acquired (CAB), healthcare-associated (HCAB), and hospital-onset bacteremia (HOB) between June and November 2025. A total of 142 isolates were collected, of which 77 resistant isolates underwent molecular analysis. In E. coli, ESBLs—mainly blaCTX-M—and AmpC were widespread across groups, while carbapenemases (blaNDM, blaOXA-48) and plasmid-mediated quinolone resistance (qnrS1) were detected only in HCAB and HOB. Aminoglycoside resistance determinants were also concentrated in HCAB.

K. pneumoniae showed a higher and broader multidrug-resistant profile, including widespread ESBLs, PMQR genes, multiple aminoglycoside resistance determinants, and double carbapenemase production (NDM + OXA-48).

Overall, resistance burden followed a gradient (HOB > HCAB > CAB), with K. pneumoniae demonstrating the highest resistance across all categories.

PathCrisp: A Next-Generation CRISPR Diagnostic Platform for Rapid Detection of Antimicrobial Resistance

Presenter: Mandar Prakash Naik

This study evaluated PathCrisp, a CRISPR-based diagnostic platform designed for rapid detection of pathogens and antimicrobial resistance (AMR) markers. The system integrates PCR-based amplification with Cas12-mediated detection and supports fluorescence, visual, and lateral flow readouts for both laboratory and point-of-care use. The PathCrisp-TyphoidDetect panel was developed to identify Salmonella species (S. Typhi, S. Paratyphi) and key AMR genes (NDM, CTX-M, SHV). Analytical validation using positive blood culture bottles showed 100% concordance with comparator PCR and standard culture methods. The limit of detection ranged from 1–10 cells/µL. The assay generated results within ~2 hours after blood culture positivity, significantly faster than conventional diagnostics (18–24 hours). Lyophilized reagents maintained performance, supporting use in resource-limited settings.

Additional panels under development include detection of carbapenemases (NDM, OXA, VIM, KPC, IMP), ESBL genes, and other pathogens.

Overall, PathCrisp demonstrated rapid, accurate, and field-adaptable detection of pathogens and AMR markers.

MIC Creep in the Shadows: An Interactive Dashboard for Forecasting MIC Trends in Newer antimicrobials against MDR pathogens across WHO regions

Presenter: Neha Nityadarshini

This study evaluated temporal trends and forecasts of minimum inhibitory concentrations (MICs) for newer antibiotics against carbapenem-resistant pathogens using 49,758 isolates from global datasets (Pfizer-ATLAS, SIDERO-WT, IST-Entesis). Eight drug–pathogen combinations were analysed, including Klebsiella pneumoniae, Escherichia coli, Pseudomonas aeruginosa, and Acinetobacter baumannii. Resistance metrics included % resistance, log2MIC, MIC50, and MIC90, with forecasts generated for five years.

In 2023, E. coli–ceftazidime-avibactam (CZA) and E. coli–meropenem-vaborbactam (MPV) showed the highest global resistance. The Southeast Asia region had the highest burden for multiple combinations, including KP-MPV and PA-ceftolozane-tazobactam.

E. coli–CZA showed the fastest increase in log2MIC globally and in the Americas. Forecasts indicated that E. coli–MPV and K. pneumoniae–CZA may exceed clinical breakpoints within five years. In contrast, A. baumannii–sulbactam-durlobactam and –cefiderocol remained within safe MIC ranges. Wider uncertainty was noted for MPV combinations due to limited data.

The study highlights emerging MIC increases in key drug–pathogen pairs and regional variation in resistance trends.

ESCMID 2026, 17-21 April, Munich, Germany.