Microbial community metabolic alterations and resistance to metals and antibiotics driven by chronic exposition to multiple pollutants in a highly impacted tropical coastal bay

Abstract

Microbial communities from Sepetiba Bay (SB, Rio de Janeiro, Brazil), characterized by 16S rRNA gene (V4–V5 region) sequencing analysis, were found to be correlated with the metallic contamination factor and the Quality Ratio (QR) index. Consistently, the predicted function of microbial communities, obtained with Tax4Fun2, showed that the functional patterns in SB internal sector under the highest anthropogenic pressure were different from that observed in the external sector with the lowest contamination level. Signal transduction, cellular community, membrane transport, and energy metabolism were among the KEGG pathways favored by metallic contamination in the SB internal sector, while lipid metabolism, transcription, and translation were among the pathways favored in the SB external sector. Noteworthy, the relative proportions of KEGG pathways and genes associated with metallic homeostasis showed significant differences according to the SB sectors, consistently with the ecological risk classification (QR index) of sediments. The functional prediction approach is an economically viable alternative and presents an overview of the main pathways/genes favored in the SB microbiota exposed to long-term pollution. In contrast, the microgAMBI, ecological status index based on bacterial community composition, was not consistent with the metallic contamination of SB, suggesting that this index requires improvements to be applied in tropical areas. Our study also revealed a strong correlation between metal resistance genes (MRG) and antibiotic resistance genes (ARG), indicating that MRG and ARG are co-selected by the metallic contamination prevailing in SB.