Greenhouse gas emission potential of tropical coastal sediments in densely urbanized area inferred from metabarcoding microbial community data.

Although benthic microbial community offers crucial insights into ecosystem services, they are underestimated for coastal sediment monitoring. Sepetiba Bay (SB) in Rio de Janeiro, Brazil, holds long-term metal pollution. Currently, SB pollution is majorly driven by domestic effluents discharge. Here, functional prediction analysis inferred from 16S rRNA gene metabarcoding data reveals the energy metabolism profiles of benthic microbial assemblages along the metal pollution gradient. Methanogenesis, denitrification, and N2 fixation emerge as dominant pathways in the eutrophic/polluted internal sector (Spearman; p < 0.05). These metabolisms act in the natural attenuation of sedimentary pollutants. The methane (CH4) emission (mcr genes) potential was found more abundant in the internal sector, while the external sector exhibited higher CH4 consumption (pmo + mmo genes) potential. Methanofastidiosales and Exiguobacterium, possibly involved in CH4 emission and associated with CH4 consumers respectively, are the main taxa detected in SB. Furthermore, SB exhibits higher nitrous oxide (N2O) emission potential since the norB/C gene proportions surpass nosZ up to 4 times. Blastopirellula was identified as the main responsible for N2O emissions. This study reveals fundamental contributions of the prokaryotic community to functions involved in greenhouse gas emissions, unveiling their possible use as sentinels for ecosystem monitoring.

Microbial indicators along a metallic contamination gradient in tropical coastal sediments.

The structure and diversity of microbial community inhabiting coastal sediments reflect the exposition to contaminants. Aiming to assess the changes in the microbiota from Sepetiba Bay (SB, Brazil) sediments, correlations between the 16S rRNA gene data (V4-V5 region), metal contamination factors (CF), and the ecological risk classification provided by the Quality Ratio (QR) index were considered. The results show that microbial diversity differs significantly between the less (SB external sector) and the most (SB internal sector) polluted sectors. Also, differences in the microbial community structure regarding the ecological risk classifications validated the QR index as a reliable tool to report the SB chronic contamination. Microbial indicator genera resistant to metals (Desulfatiglans, SEEP-SRB1, Spirochaeta 2, among others) presented mainly anaerobic metabolisms. These genera are related to the sulfate reducing and methanogenic metabolisms probably participating in the natural attenuation processes but also associated with greenhouse gas emissions. In contrast, microbial indicator genera sensitive to metals (Rubripirellula, Blastopirellula, Aquibacter, among others) presented mainly aerobic metabolisms. It is suggested that future works should investigate the metabolic functions to evaluate the influence of metallic contaminants on microbial community inhabiting SB sediment.

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

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.

Applying enzymatic biomarkers of the in situ microbial community to assess the sediment risk from Sepetiba Bay (Brazil).

The Quality Ratio (QR) index was applied in Sepetiba Bay to integrate geochemical and microbiological parameters of the in situ microbial community in order to classify the ecological risk of sediments. Total concentrations (C) of Hg, Cd, As, Pb, Cr, Cu and Zn (indicators of the mixture of contaminants) were determined at 26 stations and at a background area (C0) to calculate the contamination factor (CF = C/C0) and the degree of contamination (ΣCF). Enzymatic biomarkers of energy production into cell (dehydrogenase - DHA) and hydrolase of organic matter outside the cell (esterases - EST) were determined. The QR, a function of the microbial term (DHA/EST) and the geochemical term (TOC × ΣCF/fine-grained content), was able to segregate stations into the internal sector (east of the bay with the largest continental contributions) and the external sector (west of the bay), proving its accessibility (low-cost and fast) and efficiency for assessing ecological risk.