Origins of human-specific infectious diseases.

<p>Arrows indicate suggested direction of the transmission.</p

Antibiotic Resistome Associated with Small-Scale Poultry Production in Rural Ecuador

Small-scale poultry farming is common in rural communities across the developing world. To examine the extent to which small-scale poultry farming serves as a reservoir for resistance determinants, the resistome of fecal samples was compared between production chickens that received antibiotics and free-ranging household chickens that received no antibiotics from a rural village in northern Ecuador. A qPCR array was used to quantify antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) using 248 primer pairs; and the microbiome structure was analyzed via 16S rRNA gene sequencing. A large number of ARGs (148) and MGEs (29) were detected. The ARG richness in production chickens was significantly higher than that of household chickens with an average of 15 more genes detected (<i>p</i> < 0.01). Moreover, ARGs and MGEs were much more abundant in production chickens than in household chickens (up to a 157-fold difference). Production chicken samples had significantly lower taxonomic diversity and were more abundant in Gammaproteobacteria, Betaproteobacteria, and Flavobacteria. The high abundance and diversity of ARGs and MGEs found in small-scale poultry farming was comparable to the levels previously found in large scale animal production, suggesting that these chickens could act as a local reservoir for spreading ARGs into rural communities

Antibiotic Resistome Associated with Small-Scale Poultry Production in Rural Ecuador

Small-scale poultry farming is common in rural communities across the developing world. To examine the extent to which small-scale poultry farming serves as a reservoir for resistance determinants, the resistome of fecal samples was compared between production chickens that received antibiotics and free-ranging household chickens that received no antibiotics from a rural village in northern Ecuador. A qPCR array was used to quantify antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) using 248 primer pairs; and the microbiome structure was analyzed via 16S rRNA gene sequencing. A large number of ARGs (148) and MGEs (29) were detected. The ARG richness in production chickens was significantly higher than that of household chickens with an average of 15 more genes detected (<i>p</i> < 0.01). Moreover, ARGs and MGEs were much more abundant in production chickens than in household chickens (up to a 157-fold difference). Production chicken samples had significantly lower taxonomic diversity and were more abundant in Gammaproteobacteria, Betaproteobacteria, and Flavobacteria. The high abundance and diversity of ARGs and MGEs found in small-scale poultry farming was comparable to the levels previously found in large scale animal production, suggesting that these chickens could act as a local reservoir for spreading ARGs into rural communities

Characteristics of study households in semirural Quito, Ecuador at each cycle of data collection between July 2018 and September 2021.

Characteristics of study households in semirural Quito, Ecuador at each cycle of data collection between July 2018 and September 2021.</p

Bar plot of distribution of 3GCR-EC and ESBL-EC carriage stratified by exposures to HH food animals and CFOs.

Number of observations includes fecal samples that were negative for 3GCR-EC (light gray bars for 3GCR-EC), isolates from fecal samples that were 3GCR-EC (orange bars), or ESBL-EC (purple bars) based on phenotypic susceptibility testing, and isolates plus fecal samples negative for both 3GCR-EC and ESBL-EC (light gray bars for ESBL-EC). Percent of observations positive for each outcome are listed above each bar. 3GCR-EC, third-generation cephalosporin-resistant E. coli; CFO, commercial food animal operation; ESBL-EC, extended-spectrum beta-lactamase E. coli; HH, household.</p

Characteristics and behaviors of children in study households at each cycle of data collection between July 2018 and September 2021.

Characteristics and behaviors of children in study households at each cycle of data collection between July 2018 and September 2021.</p

Map of active commercial food animal production operations (<i>n</i> = 130) and their drainage flow paths in the study area, east of Quito, Ecuador.

The inset is an aerial photograph of commercial poultry production facilities in the study area (image credit: Jay P. Graham). Map created in QGIS; contains information from OpenStreetMap and OpenStreetMap Foundation, which is made available under the Open Database License.</p

Additional risk factors for 3GCR-EC and ESBL-EC carriage among children in semirural parishes of Quito, Ecuador.

Points are adjusted RR and error bars are 95% CIs; asterisks (*) indicate significance given alpha = 0.05 (corresponding data including sample sizes and P-values in Tables K and J in S1 Files). RR are adjusted for repeated measures and controlled for the following covariates: caregiver education, asset score, child age and sex, and child antibiotic use in the last 3 months. 3GCR-EC, third-generation cephalosporin-resistant E. coli; CI, confidence interval; ESBL-EC, extended-spectrum beta-lactamase E. coli; RR, relative risk.</p

Supplementary files.

Checklist: Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist of items that should be included in reports of cohort studies. Sample Size and Power Calculations. Table A. Prevalence of third-generation cephalosporin-resistant, extended-spectrum beta-lactamase, multidrug-resistant, and extensively drug-resistant E. coli among children. Table B. Proportion of third-generation cephalosporin-resistant E. coli (3GCR-EC) isolates resistant to individual antibiotics in phenotypic susceptibility testing by data collection cycle. Table C. Antibiotic resistance of 3GCR-EC isolates from animal fecal samples (1 colony isolated per fecal sample) collected at the same households as child fecal samples, stratified by animal species. Table D. Prevalence of clinically important sequence types (ST) among sequenced 3GCR-EC isolates (N = 571) from child fecal samples. Table E. Proportion of 3GCR-EC isolates with beta-lactamase genes (among 15 most prevalent) detected in whole-genome sequences, stratified by phenotypic ESBL production. Table F. Prevalence of beta-lactamase resistance genes among sequenced 3GCR-EC isolates from children, stratified by parishes and intensity of commercial food animal production. Table G. Average number of total antibiotic resistance genes (ARGs) per third-generation cephalosporin-resistant E. coli isolate from children, stratified by parish. Table H. Prevalence of CTX-M-type genes among sequenced 3GCR-EC isolates from children, stratified by parish and intensity of commercial food animal production. Table I. Sensitivity analysis results for main analysis associations between combined food animal exposures and 3GCR-EC and ESBL-EC including only 1 isolate per child fecal sample. Table J. Associations between secondary risk factors and 3GCR-EC carriage among children. Table K. Associations between secondary risk factors and ESBL-EC carriage among children. Table L. Secular trends in caregiver-reported child illness and antibiotic use stratified by household food animal ownership. Table M. Access to water and sanitation at households included in the main analysis (N = 594). Fig A. Directed acyclic graph of causal relationship between exposures to commercial and household food animal production and ESBL-E. coli carriage in children. SES: socioeconomic status. ESBL: extended-spectrum beta-lactamase E. coli. Fig B. Flow chart of enrollment and follow-up by data collection cycle. Households were included in the final analysis if they had the necessary exposure, outcome, and covariate data. Fig C. Prevalence of beta-lactamase genes (top 15 most prevalent) among sequenced third-generation cephalosporin-resistant E. coli isolates from children, stratified by phenotypic extended-spectrum beta-lactamase (ESBL) production. Fig D. Prevalence of beta-lactamase genes by type among third-generation cephalosporin-resistant E. coli (3GCR-EC) isolated from children, stratified by parish. (DOCX)</p

Adjusted RRs of ESBL-EC carriage among children given combined exposures to commercial food animal production and household food animals, including both interaction effects (effects of individual and combined exposures vs. no exposures) and stratum-specific effects (effects of commercial food animal exposures within strata of household food animal ownership vs. no exposures).

Adjusted RRs of ESBL-EC carriage among children given combined exposures to commercial food animal production and household food animals, including both interaction effects (effects of individual and combined exposures vs. no exposures) and stratum-specific effects (effects of commercial food animal exposures within strata of household food animal ownership vs. no exposures).</p