Related Experiment Video
Updated: Aug 31, 2025

Quantitative Polymerase Chain Reaction-based Analyses of Murine Intestinal Microbiota After Oral Antibiotic Treatment
Published on: November 17, 2018
Estimating the population-level prevalence of antimicrobial-resistant enteric bacteria from latrine samples
Sylvia Omulo1,2,3, Maina Mugoh4, Joshua Obiya5
1Paul G. Allen School for Global Health, Washington State University, Pullman, WA, USA. sylvia.omulo@wsu.edu.
Background:
Logistical and economic barriers hamper community-level surveillance for antimicrobial-resistant bacteria in low-income countries. Latrines are commonly used in these settings and offer a low-cost source of surveillance samples. It is unclear, however, whether antimicrobial resistance prevalence estimates from latrine samples reflect estimates generated from randomly sampled people.
Methods:
We compared the prevalence of antimicrobial-resistant enteric bacteria from stool samples of people residing in randomly selected households within Kibera-an informal urban settlement in Kenya-to estimates from latrine samples within the same community. Fecal samples were collected between November 2015 and Jan 2016. Presumptive Escherichia coli isolates were collected from each household stool sample (n = 24) and each latrine sample (n = 48), resulting in 8935 and 8210 isolates, respectively. Isolates were tested for resistance to nine antibiotics using the replica-plating technique. Correlation- and Kolmogorov-Smirnov (K-S) tests were used to compare results.
Results:
Overall, the prevalence values obtained from latrine samples closely reflected those from stool samples, particularly for low-prevalence (< 15%) resistance phenotypes. Similarly, the distribution of resistance phenotypes was similar between latrine and household samples (r > 0.6; K-S p-values > 0.05).
Conclusions:
Although latrine samples did not perfectly estimate household antimicrobial resistance prevalence, they were highly correlated and thus could be employed as low-cost samples to monitor trends in antimicrobial resistance, detect the emergence of new resistance phenotypes and assess the impact of community interventions.
More Related Videos
08:58Isolation and Identification of Waterborne Antibiotic-Resistant Bacteria and Molecular Characterization of their Antibiotic Resistance Genes
Published on: March 3, 2023
04:56Detection of Helicobacter pylori Infection and Antibiotic Resistance via Stool Quantitative Polymerase Chain Reaction Analysis
Published on: May 16, 2025