Pilar Domingo‐Calap

This study isolates and characterizes four broad-range Staphylococcus epidermidis phages, identifies host resistance mechanisms, and highlights their potential for phage therapy.

This study shows that phenotypic heterogeneity in Klebsiella pneumoniae affects phage resistance and cocktail efficacy, with acapsular variants being more susceptible to phages and sustaining cocktail effectiveness under selective pressure.

This study identifies lipid metabolic pathways as key determinants of phage infectivity in Mycobacterium abscessus by analyzing phage-resistant mutants and their genetic and transcriptional changes.

This study evaluates the synergy between phage vB_Kpn_2-P4 and meropenem against OXA-48-producing K. pneumoniae isolates, showing prevention of resistant mutant emergence.

The paper analyzes a mathematical model of phage-bacteria interactions to show coexistence and clearance dynamics governed by quasineutral equilibria and bifurcations.

This study shows that coevolution with a phage cocktail reduces reversible phenotypic resistance in K. pneumoniae by forcing mutation-based resistance.

This paper models phage depolymerase capsular tropism using graph neural networks and sequence clustering, showing predictive ability and transferability to lytic phages.

The paper shows that Klebsiella pneumoniae can resist phage infection through reversible downregulation of capsule biosynthesis without genetic mutations.

The paper identifies novel phage resistance systems encoded in mobile integrons and shows they can be combined for multi-phage and antibiotic resistance with variable fitness costs.

This study evolves a 12-phage cocktail in a diverse Klebsiella environment, revealing strategies for host range modulation through receptor binding proteins and ecological dynamics.

The paper isolates and characterizes phages targeting Klebsiella pneumoniae clinical isolates, showing that specific phage hunting is more effective than broad-spectrum approaches for infection control.

DepoScope uses large language models to accurately annotate phage depolymerases and their domains, improving detection through sequence and amino-acid level predictions.