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Selection of ESBL-Producing E. coli in a Mouse Intestinal Colonization Model
Frederik Boëtius Hertz1,2, Karen Leth Nielsen2,3, Niels Frimodt-Møller4
1Hvidovre Hospital, Hvidovre, Denmark.
Methods in Molecular Biology (Clifton, N.J.)
|January 12, 2018
Summary
Antimicrobial resistance is a growing global threat. This study presents a mouse model to investigate how antibiotics promote the spread of drug-resistant bacteria like E. coli in the gut.
Area of Science:
- Microbiology
- Pharmacology
- Genetics
Background:
- Rising global rates of asymptomatic carriage of antimicrobial drug-resistant pathogens.
- The critical need to understand the fecal reservoir's role in combating antimicrobial resistance.
- Incomplete understanding of antibiotic-induced damage to intestinal microflora.
Purpose of the Study:
- To present a novel mouse intestinal colonization model.
- To investigate antibiotic selection of ESBL-producing E. coli.
- To study how different antibiotics affect the establishment of multidrug-resistant E. coli.
Main Methods:
- Development and application of a mouse intestinal colonization model.
- Antibiotic administration followed by stool sampling and culturing.
- Identification of bacterial strains using random amplified polymorphic DNA (RAPD) PCR for precise E. coli strain differentiation.
Main Results:
- Successful colonization and tracking of E. coli in mice post-antibiotic treatment.
- Demonstration of antibiotic-specific selection of multidrug-resistant E. coli.
- Validation of RAPD PCR for distinguishing E. coli strains with high genomic similarity (>99.95%).
Conclusions:
- The mouse model effectively simulates antibiotic-induced selection of drug-resistant E. coli.
- This model aids in understanding the impact of antibiotics on gut microbiota and resistance.
- Precise bacterial identification methods are crucial for studying colonization dynamics.
Keywords:
Antibiotic resistanceAntibioticsE. coliExtended-spectrum beta-lactamase (ESBL)Intestinal colonizationMouse modelRAPDSelectionTypingMore Related Videos
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