Literature DB >> 28323065

The impact of fecal sample processing on prevalence estimates for antibiotic-resistant Escherichia coli.

Sylvia Omulo1, Eric T Lofgren1, Maina Mugoh2, Moshe Alando2, Joshua Obiya2, Korir Kipyegon2, Gilbert Kikwai2, Wilson Gumbi2, Samuel Kariuki3, Douglas R Call4.   

Abstract

Investigators often rely on studies of Escherichia coli to characterize the burden of antibiotic resistance in a clinical or community setting. To determine if prevalence estimates for antibiotic resistance are sensitive to sample handling and interpretive criteria, we collected presumptive E. coli isolates (24 or 95 per stool sample) from a community in an urban informal settlement in Kenya. Isolates were tested for susceptibility to nine antibiotics using agar breakpoint assays and results were analyzed using generalized linear mixed models. We observed a <3-fold difference between prevalence estimates based on freshly isolated bacteria when compared to isolates collected from unprocessed fecal samples or fecal slurries that had been stored at 4°C for up to 7days. No time-dependence was evident (P>0.1). Prevalence estimates did not differ for five distinct E. coli colony morphologies on MacConkey agar plates (P>0.2). Successive re-plating of samples for up to five consecutive days had little to no impact on prevalence estimates. Finally, culturing E. coli under different conditions (with 5% CO2 or micro-aerobic) did not affect estimates of prevalence. For the conditions tested in these experiments, minor modifications in sample processing protocols are unlikely to bias estimates of the prevalence of antibiotic-resistance for fecal E. coli.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Antibiotic resistance prevalence; E. coli; Re-plating; Storage

Mesh:

Substances:

Year:  2017        PMID: 28323065     DOI: 10.1016/j.mimet.2017.03.006

Source DB:  PubMed          Journal:  J Microbiol Methods        ISSN: 0167-7012            Impact factor:   2.363


  5 in total

1.  Identification of risk factors associated with carriage of resistant Escherichia coli in three culturally diverse ethnic groups in Tanzania: a biological and socioeconomic analysis.

Authors:  Mark A Caudell; Colette Mair; Murugan Subbiah; Louise Matthews; Robert J Quinlan; Marsha B Quinlan; Ruth Zadoks; Julius Keyyu; Douglas R Call
Journal:  Lancet Planet Health       Date:  2018-11

2.  Carriage of antimicrobial-resistant bacteria in a high-density informal settlement in Kenya is associated with environmental risk-factors.

Authors:  Sylvia Omulo; Eric T Lofgren; Svetlana Lockwood; Samuel M Thumbi; Godfrey Bigogo; Alice Ouma; Jennifer R Verani; Bonventure Juma; M Kariuki Njenga; Samuel Kariuki; Terry F McElwain; Guy H Palmer; Douglas R Call
Journal:  Antimicrob Resist Infect Control       Date:  2021-01-22       Impact factor: 4.887

3.  Estimating the population-level prevalence of antimicrobial-resistant enteric bacteria from latrine samples.

Authors:  Sylvia Omulo; Maina Mugoh; Joshua Obiya; Moshe Alando; Douglas R Call
Journal:  Antimicrob Resist Infect Control       Date:  2022-08-20       Impact factor: 6.454

4.  Antibiotic use and hygiene interact to influence the distribution of antimicrobial-resistant bacteria in low-income communities in Guatemala.

Authors:  Brooke M Ramay; Mark A Caudell; Celia Cordón-Rosales; L Diego Archila; Guy H Palmer; Claudia Jarquin; Purificación Moreno; John P McCracken; Leah Rosenkrantz; Ofer Amram; Sylvia Omulo; Douglas R Call
Journal:  Sci Rep       Date:  2020-08-13       Impact factor: 4.379

5.  Antibiotic residues and antibiotic-resistant bacteria detected in milk marketed for human consumption in Kibera, Nairobi.

Authors:  Kelsey Brown; Maina Mugoh; Douglas R Call; Sylvia Omulo
Journal:  PLoS One       Date:  2020-05-28       Impact factor: 3.240

  5 in total

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