Tracking Antibiotic Resistance from the Environment to Human Health

Antimicrobial resistance (AMR) is one of the threats to our world according to the World Health Organization (WHO). Resistance is an evolutionary dynamic process where host-associated microbes have to adapt to their stressful environments. AMR could be classified according to the mechanism of resistance or the biome where resistance takes place. Antibiotics are one of the stresses that lead to resistance through antibiotic resistance genes (ARGs). The resistome could be defined as the collection of all ARGs in an organism's genome or metagenome. Currently, there is a growing body of evidence supporting that the environment is the largest source of ARGs, but to what extent the environment does contribute to the antimicrobial resistance evolution is a matter of investigation. Monitoring the ARGs transfer route from the environment to humans and vice versa is a nature-to-nature feedback loop where you cannot set an accurate starting point of the evolutionary event. Thus, tracking resistome evolution and transfer to and from different biomes is crucial for the surveillance and prediction of the next resistance outbreak.Herein, we review the overlap between clinical and environmental resistomes and the available databases and computational analysis tools for resistome analysis through ARGs detection and characterization in bacterial genomes and metagenomes. Till this moment, there is no tool that can predict the resistance evolution and dynamics in a distinct biome. But, hopefully, by understanding the complicated relationship between the environmental and clinical resistome, we could develop tools that track the feedback loop from nature to nature in terms of evolution, mobilization, and transfer of ARGs.