@article{mbs:/content/journal/acmi/10.1099/acmi.mim2019.po0001, author = "Trampari, Eleftheria and Holden, Emma and Wickham, Gregory and Ravi, Anuradha and Prischi, Filippo and Martins, Leonardo de Oliveira and Savva, George and Bavro, Vassiliy and Webber, Mark", title = "Experimental evolution selects clinically relevant antibiotic resistance in biofilms but with collateral tradeoffs", journal= "Access Microbiology", year = "2020", volume = "2", number = "1", pages = "", doi = "https://doi.org/10.1099/acmi.mim2019.po0001", url = "https://www.microbiologyresearch.org/content/journal/acmi/10.1099/acmi.mim2019.po0001", publisher = "Microbiology Society", issn = "2516-8290", type = "Journal Article", eid = "8", abstract = "The widespread usage of antimicrobials in modern clinical, veterinary and industrial practices has selected for the emergence of antibiotic-resistant bacteria, which are increasingly hard to treat with currently available antibiotics. Most bacteria in nature exist in aggregated communities known as biofilms, which are inherently highly tolerant to antibiotics. There is currently a limited understanding of how biofilms evolve in response to antimicrobial pressure. Here we used a biofilm evolution model as a tool to study the effects of antimicrobial exposure on biofilms compared to planktonic cultures. We showed that biofilms of the model foodborne pathogen, Salmonella Typhimurium rapidly evolve in response to exposure to three clinically important antibiotics. Adaptation to antibiotic stress imposed a marked cost in biofilm formation, particularly evident for populations exposed to cefotaxime and azithromycin. By pairing the evolution model with whole-genome sequencing, we were able to identify and characterise two distinct mechanisms of resistance to cefotaxime and azithromycin. Among others, we identified novel substitutions within the multidrug efflux transporter, AcrB (R717L and Q176K) and validated their impact in drug export as well as changes in regulators of this efflux system. We showed that the model biofilm system selects clinically-important mechanisms of resistance and can be used to help predict how biofilms evolve under antimicrobial pressure.", }