Applying a polysaccharide lyase from to disrupt alginate exopolysaccharide produced by clinical isolates.

Unlabelled: is considered one of the most challenging, drug-resistant, opportunistic pathogens partly due to its ability to synthesize robust biofilms. Biofilm is a mixture of extracellular polymeric substances (EPS) that encapsulates microbial cells, leading to immune evasion, antibiotic resistance, and thus higher risk of infection. In the cystic fibrosis lung environment, undergoes a mucoid transition, defined by overproduction of the exopolysaccharide alginate.

Niche-specific metabolic phenotypes can be used to identify antimicrobial targets in pathogens.

Bacterial pathogens pose a major risk to human health, leading to tens of millions of deaths annually and significant global economic losses. While bacterial infections are typically treated with antibiotic regimens, there has been a rapid emergence of antimicrobial resistant (AMR) bacterial strains due to antibiotic overuse. Because of this, treatment of infections with traditional antimicrobials has become increasingly difficult, necessitating the development of innovative approaches for deeply understanding pathogen function.

Model-driven characterization of functional diversity of clinical isolates with broadly representative phenotypes.

is a leading cause of infections in immunocompromised individuals and in healthcare settings. This study aims to understand the relationships between phenotypic diversity and the functional metabolic landscape of clinical isolates. To better understand the metabolic repertoire of in infection, we deeply profiled a representative set from a library of 971 clinical isolates with corresponding patient metadata and bacterial phenotypes.

Model-driven characterization of functional diversity of clinical isolates with broadly representative phenotypes.

is a leading cause of infections in immunocompromised individuals and in healthcare settings. This study aims to understand the relationships between phenotypic diversity and the functional metabolic landscape of clinical isolates. To better understand the metabolic repertoire of in infection, we deeply profiled a representative set from a library of 971 clinical isolates with corresponding patient metadata and bacterial phenotypes.