Feedstock-dependent antibiotic resistance gene patterns and expression profiles in industrial scale biogas plants revealed by meta-omics technology

• Distinct resistome profiles found by machine-learning guided multi-omics in biogas plants • Anaerobic bacteria exhibit diverse resistance mechanisms • Slight correlation between abundance and expression of ARGs • Most ARGs are located on chromosome while plasmid-encoded ARGs are highly expressed • Anaerobic digesters inhibit potentially pathogenic ARB This study investigated antimicrobial resistance in the anaerobic digesters of two industrial-scale biogas plants processing agricultural biomass and municipal wastewater sludge. A combination of deep sequencing and genome-centric workflow was implemented for metagenomic and metatranscriptomics data analysis to comprehensively examine potential antimicrobial resistance in microbial communities. Anaerobic microbes were found to harbour numerous antibiotic resistance genes (ARGs), with 58.85% of the metagenome-assembled genomes (MAGs) harbouring antibiotic resistance. A moderately positive correlation was observed between the abundance and expression of ARGs. ARGs were located primarily on bacterial chromosomes. A higher expression of resistance genes was observed on plasmids than on chromosomes. Risk index assessment suggests that most ARGs identified posed a significant risk to human health. However, potentially pathogenic bacteria showed lower ARG expression than non-pathogenic ones, indicating that anaerobic treatment is effective against pathogenic microbes. Resistomes at the gene category level were associated with various antibiotic resistance categories, including multidrug resistance, beta-lactams, glycopeptides, peptides, and macrolide-lincosamide-streptogramin (MLS). Differential expression analysis revealed specific genes associated with potential pathogenicity, emphasizing the importance of active gene expression in assessing the risks associated with ARGs.