RESUMO
Recombineering using bacteriophage lambda Red recombinase (λ-Red) uses homologous recombination to manipulate bacterial genomes and is commonly applied to disrupt genes to elucidate their function. This is often followed by the introduction of a wild-type copy of the gene on a plasmid to complement its function. This is often not, however, at a native copy number and the introduction of a chromosomal version of a gene can be a desirable solution to provide wild-type copy expression levels of an allele in trans. Here, we present a simple methodology based on the λ-Red-based 'gene doctoring' technique, where we developed tools used for chromosomal tagging in a conserved locus downstream of glmS and found no impact on a variety of important phenotypes. The tools described provide an easy, quick and inexpensive method of chromosomal modification for the creation of a library of insertion mutants to study gene function.
Assuntos
Cromossomos Bacterianos/genética , Enterobacteriaceae/genética , Técnicas Genéticas , Plasmídeos/genética , Bacteriófago lambda/genética , Genes Reporter/genética , Teste de Complementação Genética , Recombinação Homóloga , Mutagênese Insercional , FenótipoRESUMO
Most bacteria in nature exist in biofilms, which are inherently tolerant to antibiotics. There is currently very limited understanding of how biofilms evolve in response to sub-lethal concentrations of antimicrobials. In this study, we use a biofilm evolution model to study the effects of sub-inhibitory concentrations of three antibiotics on Salmonella Typhimurium biofilms. We show that biofilms rapidly evolve resistance to each antibiotic they are exposed to, demonstrating a strong selective pressure on biofilms from low antibiotic concentrations. While all antibiotics tested select for clinical resistance, there is no common mechanism. Adaptation to antimicrobials, however, has a marked cost for other clinically important phenotypes, including biofilm formation and virulence. Cefotaxime selects mutants with the greatest deficit in biofilm formation followed by azithromycin and then ciprofloxacin. Understanding the impacts of exposure of biofilms to antibiotics will help understand evolutionary trajectories and may help guide how best to use antibiotics in a biofilm context. Experimental evolution in combination with whole-genome sequencing is a powerful tool for the prediction of evolution trajectories associated with antibiotic resistance in biofilms.