The rise of antibiotic resistance (AR) in clinical settings is one of the biggest modern global public health concerns, therefore, the understanding of its mechanisms, evolution and global distribution is a priority due to its impact on the treatment course and patient survivability. Besides all efforts in the elucidation of AR mechanisms in clinical strains, little is known about its prevalence and evolution in environmental uncultivable microorganisms. In this study, 293 metagenomic and 10 metatranscriptomic samples from the TARA oceans project were used to detect and quantify environmental Antibiotic Resistance Genes (ARGs) using modern machine learning tools. We show here their global distribution, abundance, taxonomy and phylogeny, their potential to be horizontally transferred by plasmids or viruses and their correlation with environmental and geographical parameters. The abundance of ARGs in 293 samples showed different patterns of distribution, being some classes significantly more abundant in Coastal Biomes. ARGs conferring resistance to some of the most relevant clinical antibiotics were also identified, revealing the presence of 15 ARGs from the recently discovered MCR-1 family with high abundance on Polar Biomes. A total of 5 MCR-1 ORFs are present in the genus Psychrobacter, an opportunistic bacteria that can cause fatal infections in humans. The present dataset is a full MySQL dump of the processed data showing main discoveries described above.

This dataset is the second version of the data descibed in the paper "Global oceanic resistome revealed: exploring Antibiotic Resistance Genes (ARGs) abundance and distribution on TARA ocean samples through machine learning tools" submitted to the biorXiv the 11th of September 2019. This dataset is not definitive and therefore needs to be used with caution, as it does not contain the manual curation that the next versions of it do.