Identification of Hypermutator Enterohemorrhagic Escherishia coli (EHEC) Using a High Throughput Screening Method to Inform Food Safety Investigations

McCarthy, Alexa

doi:10.22215/etd/2020-14245

Cited by 2 publications

(4 citation statements)

References 195 publications

(263 reference statements)

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“…1 ). The genetic backgrounds sampled were the laboratory strain MG1655 and 11 clinical isolates, including enterohemorrhagic (EHEC) and extraintestinal pathogenic (ExPEC) E. coli , that vary in serotype, antibiotic resistance profile, and plasmid presence ( Basra et al 2018 ; McCarthy 2020 ). For generalizability, we selected mutations that confer resistance to multiple antibiotic classes (fluoroquinolone, rifampicin, and aminoglycoside) by modifying drug binding sites or by upregulating antibiotic efflux ( Nakamura et al 1989 ; Vila et al 1994 ; Alekshun and Levy 1999 ; Morgan-Linnell et al 2009 ).…”

Section: Resultsmentioning

confidence: 99%

“…The E. coli isolates sampled for AMR mutagenesis include the K-12 reference strain (MG1655) ( Blattner et al 1997 ), six extraintestinal isolates collected from patients during the 2007 to 2011 CANWARD survey of antibiotic-resistant pathogens in Canada ( Zhanel et al 2013 ; Basra et al 2018 ) and three enterohemorrhagic strains from the Ottawa Laboratory Carling culture collection ( McCarthy 2020 ). Additional E. coli strains used for molecular cloning procedures include DH5α λpir and WM3064 ( Saltikov and Newman 2003 ).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Unpredictability of the Fitness Effects of Antimicrobial Resistance Mutations Across Environments in Escherichia coli

Hinz,

Amado,

Kassen

et al. 2024

Molecular Biology and Evolution

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The evolution of antimicrobial resistance (AMR) in bacteria is a major public health concern, and antibiotic restriction is often implemented to reduce the spread of resistance. These measures rely on the existence of deleterious fitness effects (i.e., costs) imposed by AMR mutations during growth in the absence of antibiotics. According to this assumption, resistant strains will be outcompeted by susceptible strains that do not pay the cost during the period of restriction. The fitness effects of AMR mutations are generally studied in laboratory reference strains grown in standard growth environments; however, the genetic and environmental context can influence the magnitude and direction of a mutation’s fitness effects. In this study, we measure how three sources of variation impact the fitness effects of Escherichia coli AMR mutations: the type of resistance mutation, the genetic background of the host, and the growth environment. We demonstrate that while AMR mutations are generally costly in antibiotic-free environments, their fitness effects vary widely and depend on complex interactions between the mutation, genetic background, and environment. We test the ability of the Rough Mount Fuji fitness landscape model to reproduce the empirical data in simulation. We identify model parameters that reasonably capture the variation in fitness effects due to genetic variation. However, the model fails to accommodate the observed variation when considering multiple growth environments. Overall, this study reveals a wealth of variation in the fitness effects of resistance mutations owing to genetic background and environmental conditions, that will ultimately impact their persistence in natural populations.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Unpredictability of the Fitness Effects of Antimicrobial Resistance Mutations Across Environments in Escherichia coli

Hinz,

Amado,

Kassen

et al. 2024

Molecular Biology and Evolution

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“…The E. coli isolates sampled for AMR mutagenesis include the K-12 reference strain (MG1655) [67], six extra-intestinal isolates collected from patients during the 2007-11 CANWARD survey of antibiotic-resistant pathogens in Canada [38,68], and three enterohemorrhagic strains from the Ottawa Laboratory Carling culture collection [39]. Additional E. coli strains used for molecular cloning procedures include DH5α λpir and WM3064 [69].…”

Section: Methodsmentioning

confidence: 99%

“…The total number of mutant constructs was 67, after accounting for failed constructions and isolates that already harbored the mutation (Fig 1). The genetic backgrounds sampled were the laboratory strain MG1655 and 11 clinical isolates, including enterohemorrhagic (EHEC) and extraintestinal pathogenic (ExPEC) E. coli, that vary in serotype, antibiotic resistance profile, and plasmid presence [38,39]. The AMR mutations confer fluoroquinolone, rifampicin, or aminoglycoside resistance by modifying drug binding sites or by upregulating antibiotic efflux [13,[40][41][42] and cause clinical resistance for pathogens such as E. coli, Pseudomonas aeruginosa, and Mycobacterium tuberculosis [12,26,[43][44][45][46][47].…”

Section: Library Of E Coli Clinical Isolates With Introduced Resistan...mentioning

confidence: 99%

Unpredictability of the fitness effects of antimicrobial resistance mutations across environments inEscherichia coli

Hinz,

Amado,

Kassen

et al. 2023

Preprint

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The evolution of antimicrobial resistance (AMR) in bacteria is a major public health concern. When resistant bacteria are highly prevalent in microbial populations, antibiotic restriction protocols are often implemented to reduce their spread. These measures rely on the existence of deleterious fitness effects (i.e., costs) imposed by AMR mutations during growth in the absence of antibiotics. According to this assumption, resistant strains will be outcompeted by susceptible strains that do not pay the cost during the period of restriction. Hence, the success of a given intervention depends on the magnitude and direction of fitness effects of mutations, which can vary depending on the genetic and environmental context. However, the fitness effects of AMR mutations are generally studied in laboratory reference strains and estimated in a limited number of environments, usually a standard laboratory growth medium. In this study, we systematically measure how three sources of variation impact the fitness effects of AMR mutations: the type of resistance mutation, the genetic background of the host, and the growth environment. We demonstrate that while AMR mutations are generally costly in antibiotic-free environments, their fitness effects vary widely and depend on complex interactions between the AMR mutation, genetic background, and environment. We test the ability of the Rough Mount Fuji genotype-fitness model to reproduce the empirical data in simulation. We identify model parameters that reasonably capture the variation in fitness effects due to genetic variation. However, the model fails to accommodate variation when considering multiple growth environments. Overall, this study reveals a wealth of variation in the fitness effects of resistance mutations owing to genetic background and environmental conditions, that will ultimately impact their persistence in natural populations.

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Identification of Hypermutator Enterohemorrhagic Escherishia coli (EHEC) Using a High Throughput Screening Method to Inform Food Safety Investigations

Cited by 2 publications

References 195 publications

Unpredictability of the Fitness Effects of Antimicrobial Resistance Mutations Across Environments in Escherichia coli

Unpredictability of the Fitness Effects of Antimicrobial Resistance Mutations Across Environments in Escherichia coli

Unpredictability of the fitness effects of antimicrobial resistance mutations across environments inEscherichia coli

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