Metagenomic Characterization of Resistance Genes in Deception Island and Their Association with Mobile Genetic Elements.
Andrés SantosFelipe BurgosJaime Martínez-UrtazaLeticia Barrientos DíazPublished in: Microorganisms (2022)
Antibiotic resistance genes (ARGs) are undergoing a remarkably rapid geographic expansion in various ecosystems, including pristine environments such as Antarctica. The study of ARGs and environmental resistance genes (ERGs) mechanisms could provide a better understanding of their origin, evolution, and dissemination in these pristine environments. Here, we describe the diversity of ARGs and ERGs and the importance of mobile genetic elements as a possible mechanism for the dissemination of resistance genes in Antarctica. We analyzed five soil metagenomes from Deception Island in Antarctica. Results showed that detected ARGs are associated with mechanisms such as antibiotic efflux, antibiotic inactivation, and target alteration. On the other hand, resistance to metals, surfactants, and aromatic hydrocarbons were the dominant ERGs. The taxonomy of ARGs showed that Pseudomonas , Psychrobacter , and Staphylococcus could be key taxa for studying antibiotic resistance and environmental resistance to stress in Deception Island. In addition, results showed that ARGs are mainly associated with phage-type mobile elements suggesting a potential role in their dissemination and prevalence. Finally, these results provide valuable information regarding the ARGs and ERGs in Deception Island including the potential contribution of mobile genetic elements to the spread of ARGs and ERGs in one of the least studied Antarctic ecosystems to date.
Keyphrases
- antibiotic resistance genes
- microbial community
- wastewater treatment
- genome wide
- anaerobic digestion
- human health
- climate change
- staphylococcus aureus
- risk factors
- dna methylation
- gene expression
- copy number
- pseudomonas aeruginosa
- escherichia coli
- risk assessment
- cystic fibrosis
- biofilm formation
- genome wide identification
- bioinformatics analysis
- transcription factor
- solid state
- genome wide analysis
- sensitive detection
- health risk