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IntroductionAntimicrobial resistance (AMR) poses a significant threat to global public health. The One Health approach, which integrates human, animal, and environmental health, highlights the roles of agricultural and hospital settings in the propagation of AMR. This study aimed to analyze the resistome and gut microbiome composition of individuals from a high-intensity animal husbandry area in the western region of Santa Catarina, Southern Brazil, who were subsequently admitted to the University Hospital in the city of Florianopolis, located in the eastern part of the same state.MethodsRectal swab samples were collected upon admission and discharge. Metagenomic sequencing and resistome analysis were employed to identify antimicrobial resistance genes (ARGs) and their associated bacterial taxa. Additionally, the impact of the hospital environment on the resistome and microbiome profiles of these patients was assessed.ResultsA total of 247 genetic elements related to AMR were identified, with 66.4% of these elements present in both admission and discharge samples. Aminoglycoside resistance genes were the most prevalent, followed by resistance genes for tetracyclines and lincosamides. Notably, unique resistance genes, including dfrF and mutations in gyrB, were identified at discharge. ARGs were associated with 55 bacterial species, with Lactobacillus fermentum, harboring the ermB gene. (MLSB), detected in both admission and discharge samples. The most prevalent bacterial families included Mycobacteriaceae, Enterobacteriaceae, and Bacteroidaceae. Among these, Mycobacteriaceae was the most abundant, with ARGs primarily associated with mutations in the 16S rRNA gene, RNA polymerase subunits, and gyrases.DiscussionThe study revealed a high prevalence of genes related to aminoglycoside and tetracycline resistance, with a notable increase in certain resistance determinants at discharge, likely influenced by extended antimicrobial use. The presence of mcr genes, associated with colistin resistance, in both admission and discharge samples from a single patient highlights a concerning trend in AMR, particularly in relation to animal husbandry. These findings underscore the substantial impact of antimicrobial use on resistance development and the complex dynamics of the resistome in hospital settings. They also emphasize the influence of local factors, such as intensive animal production, on resistance patterns and advocate for ongoing surveillance and policy development to manage multidrug-resistant bacteria eVectively.

Antimicrobial resistance is a major threat to public health. Antimicrobial use in animal husbandry is a major concern since it can favor an increase in antimicrobial resistance among farms. Herein, we aim to better understand and characterize the main resistome profiles in microbial communities found in pig farms. Sampling of swine manure was performed in two different timepoints (October 2019 and January 2020) in each of the 14 different swine farms, located in the mesoregion of Western Santa Catarina state in Brazil, a pole of swine product production of worldwide importance. Samples were divided into three groups: farms with the opened regimen and no usage of antimicrobials (F1; n = 10), farms with the closed regimen and usage of antimicrobials (F2; n = 16), and farms with the closed regimen and no usage of antimicrobials (F3; n = 2). The metagenomic evaluation was performed to obtain and identify genetic elements related to antimicrobial resistance using nanopore sequencing. We used ResistoXplorer software to perform composition, alpha and beta diversity, and clustering analysis. In addition, PCR reactions were performed to confirm the presence or absence of seven different beta-lactamase family genes and five phosphoethanolamine transferase gene variants clinically relevant. Our findings based on the identification of resistance genes at the mechanism level showed a prevalence of alteration of the drug target (72.3%) profile, followed by drug inactivation (17.5%) and drug efflux (10.1%). We identified predominantly aminoglycosides (45.3%), tetracyclines (15.9%), and multiclass (11,2%) resistance genes. PCoA analysis indicates differences between F1 and F2 profiles. F2 samples showed increased diversity when compared to the F1 group. In addition, herein we first report the identification of mcr-4 in a slurry sample (C1F1.1) in Santa Catarina State. In general, our findings reinforce that many factors on the practices of animal husbandry are involved in the resistome profile at the mechanism and class levels. Further studies to better understand microbiome and mobilome aspects of these elements are necessary to elucidate transmission pathways between different bacteria and environments.