Volume 73 (2023) Issue: 2023 No#2

Resistance to antibiotics by enteric bacteria associated with the swine industry: in silico exploration of the distribution of resistance genes

Author(s): Javier Rubén Miranda-Valdés, Yagul Pedraza-Pérez, Lidia Esmeralda García-Díaz, Ricardo Carreño-López, Luis Ernesto Fuentes-Ramírez, Rosa Del Carmen Rocha-Gracia, Lucero Montserrat Cuautle-García, Vianey Marín-Cevada

Keywords:bioinformatic analysis, enteric bacteria, pig farming, antimicrobial resistance genes, mobile genetic elements

Multidrug-resistant (MDR) bacteria are a significant contributor to the global antibiotic resistance crisis, which is predicted to kill more people than cancer by 2050. Livestock production is a contributing factor as it has been one of the fastest-growing industries in the previous century but has the most harmful effects on the environment and human health. The pig is the most widely raised and consumed food-producing animal globally, with an upward trend. The derived residues and the meat products constitute an important reservoir of antibiotic resistance genes (ARGs) that can be transmitted to humans through consumption, direct contact, the environment, or poor handling, leading to relevant zoonotic diseases, especially enteric ones. It is essential to know the diversity, abundance, and distribution of ARGs to have better control and monitoring of their dispersion. In the present study, the ARGs and Mobile Genetic Elements (MGEs) of five enteric and pathogenic species commonly present in the microbiota of both pigs and humans were examined by bioinformatic analysis. This analysis showed that 157 ARGs were distributed across 1869 genomes of five bacterial species, ranked from highest to lowest diversity of ARGs: Klebsiella pneumoniae, Escherichia coli, Enterococcus faecium, Salmonella enterica, and Enterococcus faecalis. This study contributes to better management of antibiotics, which directly impact the health of both humans and animals.

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ISSN: 0567-8315

eISSN: 1820-7448

Journal Impact Factor 2022: 0.6

5-Year Impact Factor: 0.9

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