Natural selenium stress influences the changes of antibiotic resistome in seleniferous forest soils

Abstract

Abstract Background Metal(loid)s can promote the spread and enrichment of antibiotic resistance genes (ARGs) in the environment through a co-selection effect. However, it remains unclear whether exposure of microorganisms to varying concentrations of selenium (Se), an essential but potentially deleterious metal(loid) to living organisms, can influence the migration and distribution of ARGs in forest soils. Results Precisely 235 ARGs conferring resistance to seven classes of antibiotics were detected along a Se gradient (0.06–20.65 mg kg−1) across 24 forest soils. (flor)/(chlor)/(am)phenicol resistance genes were the most abundant in all samples. The total abundance of ARGs first increased and then decreased with an elevated available Se content threshold of 0.034 mg kg−1 (P = 2E−05). A structural equation model revealed that the dominant mechanism through which Se indirectly influences the vertical migration of ARGs is by regulating the abundance of the bacterial community. In addition, the methylation of Se (mediated by tehB) and the repairing of DNA damages (mediated by ruvB and recG) were the dominant mechanisms involved in Se resistance in the forest soils. The co-occurrence network analysis revealed a significant correlated cluster between Se-resistance genes, MGEs and ARGs, suggesting the co-transfer potential. Lelliottia amnigena YTB01 isolated from the soil was able to tolerate 50 μg mL−1 ampicillin and 1000 mg kg−1 sodium selenite, and harbored both Se resistant genes and ARGs in the genome. Conclusions Our study demonstrated that the spread and enrichment of ARGs are enhanced under moderate Se pressure but inhibited under severe Se pressure in the forest soil (threshold at 0.034 mg kg−1 available Se content). The data generated in this pilot study points to the potential health risk associated with Se contamination and its associated influence on ARGs distribution in soil.

Keywords

• Antibiotic resistance genes
• Selenium
• Soil environment
• Bacterial community
• High-throughput quantitative PCR
• Whole genome analysis