Metagenomic and metatranscriptomic analyses reveal activity and hosts of antibiotic resistance genes in activated sludge

Abstract

Wastewater treatment plants (WWTPs) are a source and reservoir for subsequent spread of various antibiotic resistance genes (ARGs). However, little is known about the activity and hosts of ARGs in WWTPs. Here, we utilized both metagenomic and metatranscriptomic approaches to comprehensively reveal the diversity, abundance, expression and hosts of ARGs in activated sludge (AS) from three conventional WWTPs in Taiwan. Based on deep sequencing data and a custom-made ARG database, a total of 360 ARGs associated with 24 classes of antibiotics were identified from the three AS metagenomes, with an abundance range of 7.06 × 10−1–1.20 × 10−4 copies of ARG/copy of 16S rRNA gene. Differential coverage binning analysis revealed that >22 bacterial phyla were the putative hosts of the identified ARGs. Surprisingly, genus Mycobacterium and family Burkholderiaceae were observed as multi-drug resistant harboring 14 and 50 ARGs. Metatranscriptome analysis showed 65.8% of the identified ARGs were being expressed, highlighting that ARGs were not only present, but also transcriptionally active in AS. Remarkably, 110 identified ARGs were annotated as plasmid-associated and displayed a close to two-fold increased likelihood of being transcriptionally expressed compared to those ARGs found exclusively within bacterial chromosomes. Further analysis showed the transcript abundance of aminoglycoside, sulfonamide, and tetracycline resistance genes was mainly contributed by plasmid-borne ARGs. Our approach allowed us to specifically link ARGs to their transcripts and genetic context, providing a comprehensive insight into the prevalence, expression and hosts of ARGs in AS. Overall, results of this study enhance our understanding of the distribution and dissemination of ARGs in WWTPs, which benefits environmental risk assessment and management of ARB and ARGs. Keywords: Antibiotic resistance genes, WWTP, Activated sludge, Metagenomics, Metatranscriptomics, Differential coverage binning