Multi-omics surveillance of antimicrobial resistance in the pig gut microbiome

Abstract Background High-throughput sequencing technologies play an increasingly active role in the surveillance of major global health challenges, such as the emergence of antimicrobial resistance. The post-weaning period is of critical importance for the swine industry and antimicrobials are still required when infection occurs during this period. Here, two sequencing approaches, shotgun metagenomics and metatranscriptomics, have been applied to decipher the effect of different treatments used in post-weaning diarrhea on the transcriptome and resistome of pig gut microbiome. With this objective, a metagenome-assembled genome (MAG) catalogue was generated to use as a reference database for transcript mapping obtained from a total of 140 pig fecal samples in a cross-sectional and longitudinal design to study differential gene expression. The different treatments included antimicrobials trimethoprim/sulfamethoxazole, colistin, gentamicin, and amoxicillin, and an oral commercial vaccine, a control with water acidification, and an untreated control. For metatranscriptomics, fecal samples from pigs were selected before weaning, three days and four weeks post-treatment. Results The final non-redundant MAGs collection comprised a total of 1396 genomes obtained from single assemblies and co-assemblies per treatment group and sampling time from the metagenomics data. Analysis of antimicrobial resistance genes (ARGs) at this assembly level considerably reduced the total number of ARGs identified in comparison to those found at the reads level. Besides, from the metatranscriptomics data, half of those ARGs were detected transcriptionally active in all treatment groups. Differential gene expression between sampling times after treatment found major number of differential expressed genes (DEGs) against the group treated continuously with amoxicillin, with DEGs being correlated with antimicrobial resistance. Moreover, at three days post-treatment, a high number of significantly downregulated genes was detected in the group treated with gentamicin. At this sampling time, this group showed an altered expression of ribosomal-related genes, demonstrating the rapid effect of gentamicin to inhibit bacterial protein synthesis. Conclusions Different antimicrobial treatments can impact differently the transcriptome and resistome of microbial communities, highlighting the relevance of novel sequencing approaches to monitor the resistome and contribute to a more efficient antimicrobial stewardship.