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. 2021 Apr 20:12:651461.
doi: 10.3389/fmicb.2021.651461. eCollection 2021.

Exploring the Antibiotic Resistance Burden in Livestock, Livestock Handlers and Their Non-Livestock Handling Contacts: A One Health Perspective

Rachel A Hickman  1 , Thongpan Leangapichart  2 , Kamonwan Lunha  3 , Jatesada Jiwakanon  4 , Sunpetch Angkititrakul  4 , Ulf Magnusson  3 , Marianne Sunde  2 , Josef D Järhult  5
Affiliations

Exploring the Antibiotic Resistance Burden in Livestock, Livestock Handlers and Their Non-Livestock Handling Contacts: A One Health Perspective

Rachel A Hickman et al. Front Microbiol. .

Abstract

Antibiotics are freqeuently used in the livestock sector in low- and middle-income countries for treatment, prophylaxis, and growth promotion. However, there is limited information into the zoonotic prevalence and dissemination patterns of antimicrobial resistance (AMR) within these environments. In this study we used pig farming in Thailand as a model to explore AMR; 156 pig farms were included, comprising of small-sized (<50 sows) and medium-sized (≥100 sows) farms, where bacterial isolates were selectively cultured from animal rectal and human fecal samples. Bacterial isolates were subjected to antimicrobial susceptibility testing (AST), and whole-genome sequencing. Our results indicate extensive zoonotic sharing of antibiotic resistance genes (ARGs) by horizontal gene transfer. Resistance to multiple antibiotics was observed with higher prevalence in medium-scale farms. Zoonotic transmission of colistin resistance in small-scale farms had a dissemination gradient from pigs to handlers to non-livestock contacts. We highly recommend reducing the antimicrobial use in animals' feeds and medications, especially the last resort drug colistin.

Keywords: E. coli; antibiotic resistance; livestock; meat-production; one-health approach; pigs; zoonotic transmission.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Overview of experimental and computational set-up of the study. (A) Experimental workflow of the study. (B) Computational analysis work-flow of the study.
FIGURE 2
FIGURE 2
Average Minimal inhibitory concentration (MIC) for drug investigation group to each drug reagent with their respective standard deviation and clinical breakpoints for each drug are displayed across the y-axis.
FIGURE 3
FIGURE 3
Venn diagrams displaying number of antibiotic resistance genes (ARGs) shared between different investigation groups. (A) Comparison of total antibiotic resistance genes in small-scale farms. (B) Comparison of total antibiotic resistance genes in medium-scale farms.
FIGURE 4
FIGURE 4
Overview of total ARGs and chromosomal mutations. (A) Display of % of total ARGs according to antibiotic drug class for each investigation group of this study. (B) Display of % of antibiotic resistant associated chromosomal for each investigation group of this study.
FIGURE 5
FIGURE 5
Venn diagram of Multi Locus Sequence Types shared between different investigation groups. (A) Comparison of STs in small-scale farms. (B) Comparison of total STs genes in medium-scale farms.
See this image and copyright information in PMC

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