Ecological and evolutionary mechanisms driving within-patient emergence of antimicrobial resistance.

The ecological and evolutionary mechanisms of antimicrobial resistance (AMR) emergence within patients and how these vary across bacterial infections are poorly understood. Increasingly widespread use of pathogen genome sequencing in the clinic enables a deeper understanding of these processes. In this Review, we explore the clinical evidence to support four major mechanisms of within-patient AMR emergence in bacteria: spontaneous resistance mutations; in situ horizontal gene transfer of resistance genes; selection of pre-existing resistance; and immigration of resistant lineages.

Combining SNAPs with antibiotics shows enhanced synergistic efficacy against S. aureus and P. aeruginosa biofilms.

Biofilm infections are associated with a high mortality risk for patients. Antibiotics perform poorly against biofilm communities, so high doses and prolonged treatments are often used in clinical settings. We investigated the pairwise interactions of two synthetic nano-engineered antimicrobial polymers (SNAPs).

Transcriptome Analysis of Pseudomonas aeruginosa Biofilm Infection in an Pig Model of the Cystic Fibrosis Lung.

Pseudomonas aeruginosa is the predominant cause of chronic biofilm infections that form in the lungs of people with cystic fibrosis (CF). These infections are highly resistant to antibiotics and persist for years in the respiratory tract. One of the main research challenges is that current laboratory models do not accurately replicate key aspects of a P.

Antibiotic Efficacy Testing in an Ex vivo Model of Pseudomonas aeruginosa and Staphylococcus aureus Biofilms in the Cystic Fibrosis Lung.

The effective prescription of antibiotics for the bacterial biofilms present within the lungs of individuals with cystic fibrosis (CF) is limited by a poor correlation between antibiotic susceptibility testing (AST) results using standard diagnostic methods (e.g., broth microdilution, disk diffusion, or Etest) and clinical outcomes after antibiotic treatment.

Building a better biofilm - Formation of -like biofilm structures by in a porcine model of cystic fibrosis lung infection.

biofilm infections in the cystic fibrosis (CF) lung are highly resistant to current antimicrobial treatments and are associated with increased mortality rates. The existing models for such infections are not able to reliably mimic the clinical biofilms observed. We aimed to further optimise an pig lung (EVPL) model for CF lung infection that can be used to increase understanding of chronic CF biofilm infection.

An cystic fibrosis model recapitulates key clinical aspects of chronic infection.

is the most prevalent organism isolated from the airways of people with cystic fibrosis (CF), predominantly early in life. Yet its role in the pathology of lung disease is poorly understood. In mice, and many experiments using cell lines, the bacterium invades cells or interstitium, and forms abscesses.

Predicting Antibiotic-Associated Virulence of Using an Lung Biofilm Model.

Background: Bacterial biofilms are known to have high antibiotic tolerance which directly affects clearance of bacterial infections in people with cystic fibrosis (CF). Current antibiotic susceptibility testing methods are either based on planktonic cells or do not reflect the complexity of biofilms . Consequently, inaccurate diagnostics affect treatment choice, preventing bacterial clearance and potentially selecting for antibiotic resistance.