Identification and quantification of bacterial genomes carrying antibiotic resistance genes and virulence factor...

Aquatic ecosystems have been increasingly threatened by anthropogenic activities, e.g., wastewater discharge and farm operation. Several methods are adopted to evaluate the effects of anthropogenic activities on biological risk in the environment, such as qPCR and amplicon next-generation sequencing. However, these methods fall short of providing genomic information of target species, which is vital for risk assessment from genomic aspect. Here, we developed a novel approach integrating metagenomic analysis and flow cytometry to identify and quantify potential pathogenic antibiotic resistant bacteria (PARB; carrying both antibiotic resistance genes (ARGs) and virulence factor genes (VFGs)) in the environment, which are of particular concern due to their infection ability and antibiotic resistance. Based on the abundance/density of PARB, we evaluated microbiological risk in a river impacted by both municipal drainage and agriculture runoff. We collected samples upstream (mountainous area) as the control. Results showed that 81.8% of dominant PARB (33) recovered using our approach were related to known pathogenic taxa. In addition, intragenomic ARGs-VFGs coexistence patterns in the dominant Pseudomonas genomes (20 out of 71 PARB) showed high similarity with the most closely related Pseudomonas genomes from the NCBI RefSeq database. These results reflect acceptable reliability of the approach for (potential) pathogen identification in environmental samples. According to the PARB density, microbiological risk in samples from the agricultural area was significantly higher than in samples from the urban area. We speculated that this was due to the higher antibiotic usage in agriculture as well as intragenomic ARGs-VFGs co-evolution under antibiotic selective pressure. This study provides an alternative approach for the identification and quantification of PARB in aquatic environments, which can be applied for microbiological risk assessment.