Boas C L van der Putten1,2, Daniel Remondini3, Giovanni Pasquini3, Victoria A Janes2, Sébastien Matamoros2, Constance Schultsz1,2. 1. Amsterdam UMC, University of Amsterdam, Department of Global Health, Amsterdam Institute for Global Health and Development, Meibergdreef 9, Amsterdam, Netherlands. 2. Amsterdam UMC, University of Amsterdam, Department of Medical Microbiology, Meibergdreef 9, Amsterdam, Netherlands. 3. Department of Physics and Astronomy (DIFA), University of Bologna, Viale Berti Pichat 6/2, Bologna, Bologna, Italy.
Abstract
Background: Reviews assessing the genetic basis of ciprofloxacin resistance in Escherichia coli have mostly been qualitative. However, to predict resistance phenotypes based on genotypic characteristics, it is essential to quantify the contribution of genotypic determinants to resistance. Objectives: We performed a systematic review to assess the relative contribution of known genomic resistance determinants to the MIC of ciprofloxacin in E. coli. Methods: PubMed and Web of Science were searched for English language studies that assessed ciprofloxacin MIC and presence or introduction of genetic determinants of ciprofloxacin resistance in E. coli. We included experimental and observational studies without time restrictions. Medians and ranges of MIC fold changes were calculated for individual resistance determinants and combinations thereof. Results: We included 66 studies, describing 604 E. coli isolates that carried at least one genetic ciprofloxacin resistance determinant. Mutations in gyrA and parC, genes encoding targets of ciprofloxacin, contribute to the largest fold changes in ciprofloxacin resistance in E. coli compared with the WT. Efflux and physical blocking or enzymatic modifications confer smaller increases in ciprofloxacin MIC than mutations in gyrA and parC. However, the presence of these other resistance mechanisms in addition to target alteration mutations further increases ciprofloxacin MIC, thus resulting in ciprofloxacin MIC increases ranging from 250- to 4000-fold. Conclusions: This quantitative review of genomic determinants of ciprofloxacin resistance in E. coli demonstrates the complexity of resistance phenotype prediction from genomic data and serves as a reference point for studies aiming to predict ciprofloxacin MIC from E. coli genomes.
Background: Reviews assessing the genetic basis of ciprofloxacin resistance in Escherichia coli have mostly been qualitative. However, to predict resistance phenotypes based on genotypic characteristics, it is essential to quantify the contribution of genotypic determinants to resistance. Objectives: We performed a systematic review to assess the relative contribution of known genomic resistance determinants to the MIC of ciprofloxacin in E. coli. Methods: PubMed and Web of Science were searched for English language studies that assessed ciprofloxacin MIC and presence or introduction of genetic determinants of ciprofloxacin resistance in E. coli. We included experimental and observational studies without time restrictions. Medians and ranges of MIC fold changes were calculated for individual resistance determinants and combinations thereof. Results: We included 66 studies, describing 604 E. coli isolates that carried at least one genetic ciprofloxacin resistance determinant. Mutations in gyrA and parC, genes encoding targets of ciprofloxacin, contribute to the largest fold changes in ciprofloxacin resistance in E. coli compared with the WT. Efflux and physical blocking or enzymatic modifications confer smaller increases in ciprofloxacin MIC than mutations in gyrA and parC. However, the presence of these other resistance mechanisms in addition to target alteration mutations further increases ciprofloxacin MIC, thus resulting in ciprofloxacin MIC increases ranging from 250- to 4000-fold. Conclusions: This quantitative review of genomic determinants of ciprofloxacin resistance in E. coli demonstrates the complexity of resistance phenotype prediction from genomic data and serves as a reference point for studies aiming to predict ciprofloxacin MIC from E. coli genomes.
Authors: Victoria J Chalker; Martin G Sharratt; Christopher L Rees; Oliver H Bell; Edward Portal; Kirsty Sands; Matthew S Payne; Lucy C Jones; Owen B Spiller Journal: Antimicrob Agents Chemother Date: 2021-03-18 Impact factor: 5.191
Authors: Marcos H de Moraes; FoSheng Hsu; Dean Huang; Dustin E Bosch; Jun Zeng; Matthew C Radey; Noah Simon; Hannah E Ledvina; Jacob P Frick; Paul A Wiggins; S Brook Peterson; Joseph D Mougous Journal: Elife Date: 2021-01-15 Impact factor: 8.713
Authors: Dimard E Foudraine; Nikolaos Strepis; Christoph Stingl; Marian T Ten Kate; Annelies Verbon; Corné H W Klaassen; Wil H F Goessens; Theo M Luider; Lennard J M Dekker Journal: Sci Rep Date: 2021-06-14 Impact factor: 4.379
Authors: Bálint Ármin Pataki; Sébastien Matamoros; Boas C L van der Putten; Daniel Remondini; Enrico Giampieri; Derya Aytan-Aktug; Rene S Hendriksen; Ole Lund; István Csabai; Constance Schultsz Journal: Sci Rep Date: 2020-09-14 Impact factor: 4.379
Authors: Ian Boostrom; Yohan Bala; Jelena Minic Vasic; Jelena Gluvakov; Emmanuel Chanard; Andrew H Barratt; Kirsty Sands; Edward Portal; Laurence Devigne; Lucy C Jones; Owen B Spiller Journal: J Antimicrob Chemother Date: 2021-11-12 Impact factor: 5.790
Authors: Carly Ching; Ebiowei S F Orubu; Indorica Sutradhar; Veronika J Wirtz; Helen W Boucher; Muhammad H Zaman Journal: JAC Antimicrob Resist Date: 2020-09-30