The first therapeutic use of antimicrobial agents initiated their endless arms race with antimicrobial resistance (AMR). Although the genes encoding antimicrobial resistance are ancient and ubiquitous in various environmental compartments, including aquatic environments, over eight decades of exposure to selective pressure has changed the way antimicrobial resistance genes (ARGs) emerge and transmit among the three One Health sectors (that is, the intersected sectors of humans, animals and the environment). The dissemination of ARGs has been facilitated by the widespread use of antimicrobials, along with direct and secondary pollution pathways. Current global consensus dictates that AMR should be addressed under a One Health framework. AMR National Action Plans have frequently been formulated. However, the capacity for implementation is not ready in most countries, especially in low- and middle-income regions. This is in part due to the substantial challenges in documenting and controlling cross-sector AMR connectivity. Here we describe the past and current status of AMR, emphasizing the contribution of connectivity to global AMR burden. We discuss connectivity at ecological, microbial and genetic levels; propose an approach based on genomics and metagenomics to assess connectivity; and finally advocate for cross-sector studies to better understand AMR connectivity and mitigate dissemination. We believe that such harmonized connectivity studies will facilitate coordinated actions and investments across sectors and regions to scale up AMR management globally.

Surveillance of antibiotic resistance genes (ARGs) has been increasingly conducted in environmental sectors to complement the surveys in human and animal sectors under the "One-Health"framework. However, there are substantial challenges in comparing and synthesizing the results of multiple studies that employ different test methods and approaches in bioinformatic analysis. In this article, we consider the commonly used quantification units (ARG copy per cell, ARG copy per genome, ARG density, ARG copy per 16S rRNA gene, RPKM, coverage, PPM, etc.) for profiling ARGs and suggest a universal unit (ARG copy per cell) for reporting such biological measurements of samples and improving the comparability of different surveillance efforts.