Mangrove sediments are prone to anthropogenic activities that could enrich antibiotics resistance genes (ARGs). The emergence and dissemination of ARGs are of serious concern to public health worldwide. Therefore, a comprehensive resistome analysis of global mangrove sediment is of paramount importance. In this study, we have implemented a deep machine learning approach to analyze the resistome of mangrove sediments from Brazil, China, Saudi Arabia, India, and Malaysia. Geography (RANOSIM = 39.26%; p 0.05). Several genes including multidrug efflux pumps were significantly (p
Saline tolerant mangrove forests partake in vital biogeochemical cycles. However, they are endangered due to deforestation as a result of urbanization. In this study, we have carried out a metagenomic snapshot of the mangrove ecosystem from five countries to assess its taxonomic, functional and antibiotic resistome structure. Chao1 alpha diversity varied significantly (P 90% relative abundance. Comparative analysis of mangrove with terrestrial and marine ecosystems revealed the strongest heterogeneity in the mangrove microbial community. We also observed that the mangrove community shared similarities to both the terrestrial and marine microbiome, forming a link between the two contrasting ecosystems. The antibiotic resistant genes (ARG) resistome was comprised of nineteen level 3 classifications dominated by multidrug resistance efflux pumps (46.7 ± 4.3%) and BlaR1 family regulatory sensor-transducer disambiguation (25.2 ± 4.8%). ARG relative abundance was significantly higher in Asian countries and in human intervention datasets at a global scale. Our study shows that the mangrove microbial community and its antibiotic resistance are affected by geography as well as human intervention and are unique to the mangrove ecosystem. Understanding changes in the mangrove microbiome and its ARG is significant for sustainable development and public health.