Utilizing co-abundances of antimicrobial resistance genes to identify potential co-selection in the resistome

• Published in: bioRxiv
• Main Authors: Hannah-Marie Martiny, Munk, Patrick, Brinch, Christian, Aarestrup, Frank M, Calle, Mluz, Petersen, Thomas N
• Format: Paper
• Language: English
• Published: Cold Spring Harbor Cold Spring Harbor Laboratory Press 08.11.2023
• Subjects: Antimicrobial agents; Antimicrobial resistance; Drug resistance; Metagenomics; Public health
• DOI: 10.1101/2022.12.19.519133

The rapid spread of antimicrobial resistance (AMR) is a threat to global health, and the nature of co-occurring antimicrobial resistance genes (ARGs) may cause collateral AMR effects once antimicrobial agents are used. Therefore, it is essential to identify which pairs of ARGs co-occur. Given the wealth of NGS data available in public repositories, we have investigated the correlation between ARG abundances in a collection of 214,095 metagenomic datasets. Using more than 6.76·108 read fragments aligned to ARGs to infer pairwise correlation coefficients, we found that more ARGs correlated with each other in human and animal sampling origins than in soil and water environments. Furthermore, we showed that the correlations serve as risk profiles of resistance co-occurring to critically important antimicrobials. Using these profiles, we found several key ARGs indirectly but strongly selecting for ARGs of critical importance, such as tetracycline ARGs correlating with most forms of resistances. In conclusion, this study highlights the important ARG players indirectly involved in shaping the resistomes of various environments that can serve as monitoring targets in AMR surveillance programs.Competing Interest StatementThe authors have declared no competing interest.Footnotes* Updated text and figures* https://zenodo.org/record/6919377* https://github.com/hmmartiny/global_resistome_correlations