Antimicrobial-specific response from resistance gene carriers studied in a natural, highly diverse microbiome

Background Antimicrobial resistance (AMR) is a major threat to public health. It is suggested to be partially emerging from microbial communities found in natural habitats; however, this hypothesis remained mostly elusive so far. To understand AMR development in native microbiomes, we exposed lichen thalli of Peltigera polydactylon, which present defined, highly diverse miniature ecosystems, to clinical (colistin, tetracycline), and non-clinical (glyphosate, alkylpyrazine) antimicrobials and studied them by combined analyses of DNA- and RNA-based amplicon and metagenomic libraries. Results The native Peltigera microbiome harboured high bacterial abundances of 107 to 108 16S rRNA gene copies ng-1 DNA and was dominated by Alphaproteobacteria and Bacteroidetes. Its natural resistome encompassed 728 AMR genes spanning 30 antimicrobial classes. After a 10-day exposure in four different concentrations (full therapeutic dosage and a gradient of sub-therapeutic dosages) we identified statistically significant, antimicrobial-specific shifts in structure and function but not in abundances of the microbiota. We observed a relatively lower effect after exposure to non-clinical compared to the clinical antimicrobial compounds. Further, we observed specific bacterial responders, e.g. Pseudomonas and Burkholderia towards clinical antimicrobial substances. Interestingly, the main positive responders naturally occur in rather low proportions in the lichen holobiont. Metagenomic recovery of the responders' genomes suggested that all are naturally equipped with specific genetic repertoires that allow them to thrive and bloom under antimicrobial exposure; Sphingomonas, Pseudomonas and Methylobacterium showed the highest potential. Conclusions Antimicrobial exposure resulted in microbial dysbiosis due to a bloom of naturally low abundant taxa (positive responders) with specific AMR features. Overall, this study provides mechanistic insights into community-level responses of a native microbiota to antimicrobials and opens novel strategies for AMR prediction and management.