Rafael Cantón

The paper develops a rules-based classifier to predict ciprofloxacin resistance in Klebsiella pneumoniae from genotype data and demonstrates its global distribution association with quinolone consumption.

This study shows that loss of type I restriction-modification methyltransferases in Pseudomonas aeruginosa increases fluoroquinolone persistence through enhanced SOS response and slower growth.

The paper characterizes microbial communities in hospital sinks, showing they are stable, multi-kingdom reservoirs harboring MDROs and shaped by environmental factors.

The paper characterizes a collection of 50 multidrug-resistant clinical isolates of Escherichia coli and Klebsiella spp., providing genomic insights into antimicrobial resistance and mobile genetic elements.

This study identifies 34 phage tail-like bacteriocins (PTLBs) in Pseudomonas aeruginosa genomes, with some showing strong antimicrobial activity against bacterial infections.

This study shows that S. aureus enters a viable but non-culturable state when competing with P. aeruginosa, altering its metabolism and survival strategies in response to antibiotics.

This study investigates how oxygen levels affect antimicrobial resistance gene performance in Enterobacterales, showing significant variations in resistance under aerobic and anaerobic conditions.

This study uses nanomotion technology to rapidly test Salmonella enterica's susceptibility to azithromycin, showing correlation with traditional susceptibility measures.

The paper identifies 12 new Pf-like phages in P. aeruginosa clinical isolates and links their presence to resistance against phage infection through novel anti-phage defence systems.

This study shows plasmid-encoded insertion sequences (IS1) enhance bacterial adaptation by increasing gene inactivation rates in clinical enterobacteria.

This paper uses layered phylogenomics and polymorphism fingerprinting to reconstruct the evolutionary history of Escherichia coli, identifying three root lineages and a new phylogroup, while highlighting adaptive strategies in different lineages.

The paper uses a membrane computing model to simulate and analyze the multi-level dynamics of antimicrobial resistance across genes, clones, species, hosts, and environments.