Activity, structure and functionality of benthic microbial community in response to multiple contaminants exposure: assessment of environmental quality in Sepetiba Bay (Rio de Janeiro State, SE - Brazil)

• Ano de defesa: 2022
• Autor(a) principal: Vanessa de Almeida Moreira
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Palavras-chave em Português: Metal pollution; Quality Ratio index; MicrogAMBI index; Metal homeostasis genes; Antibiotic resistance genes; Poluição do mar; Poluição metálica; Índice Quality Ratio; Índice MicrogAMBI; Genes de homeostase metálica; Genes de resistência a antibióticos
• Link de acesso: http://app.uff.br/riuff/handle/1/26185

Coastal ecosystems are impacted by persistent and bioaccumulative contaminants, such as metals, affecting the metabolism, structure, diversity, and functional dynamics of benthic microbial communities. Sepetiba Bay (SB), located in Rio de Janeiro state (SE-Brazil), suffers mainly from chronic metallic contamination. The Quality Ratio (QR) index was applied through the integration of physical (fine-grain content – silt + clay) and geochemical (TOC and degree of metal contamination – CF) and microbiological parameters (Esterase – EST - and Dehydrogenase – DHA – enzyme activities) of the in situ microbial community to classify the ecological risk of sediments. Thus, SB was segregated into the internal (higher continental contributions and anthropogenic pressure), with greater eutrophication and CF, and the external sectors evidencing the accessibility (low-cost and fast) and efficiency of QR for assessing ecological risks. Microbial community data were obtained through fragments of the 16S rRNA gene sequencing, showing significant differences among SB sectors and QR classes. Significant higher microbial Amplicon Sequence Variant (ASV) richness and Shannon's diversity index were found in the external sector compared to the internal sector. Proteobacteria (53.5%) was the most abundant phylum at SB, with a predominance of the Gammaproteobacteria (29%) and Deltaproteobacteria (21%) that play important roles in biogeochemical cycles and presented the highest relative abundances in the internal sector. The prokaryotic classes with higher abundances in the internal sector (i. e., Thermococci, Thermoplasmata, and Thermodesulfovibrionia) follow the reducing nature of the area, presenting methanogenic and sulfate-reduction metabolisms. Conversely, the external sector presents higher abundances of taxa sensitive to contaminants (e.g., Nitrososphaeria), confirmed by the negative correlation with CFs and the relevance on low/moderate ecological risks stations. Some bacterial taxa classified as sensitive/indifferent to pollutants (ecological group - EG I) in the microgAMBI original taxa list changed to tolerant/opportunistic classification (EG III) when considering their positive correlation with metals. The microgAMBI index, after calibration, assigned mainly a poor ecological status to SB – in both internal and the external sectors stations - reflecting the history of multiple contaminations, eutrophication, and the dispersion of the contaminants and organic load due to the clockwise hydrodynamic circulation of the bay. Signal transduction, cellular community, membrane transport, and cell motility are the most important metabolic pathways in the SB internal sector, reinforcing the idea that these functions are typical of eutrophic/anoxic/highly polluted environments as reported in the literature. The SB prokaryotic community is adapted, capable of maintaining normal growth and metabolic functions despite the chronic exposition to contaminants, suggesting that resistance has been reached. This fact is proven by the presence of genes associated with metal homeostasis, in which the higher proportions are found in internal sector stations. Twelve genes that code for multidrug/antibiotic resistance showed a positive correlation with CFs and genes that code for metal homeostasis, indicating the co-selection of antibiotic resistance genes, supporting the metallic pollutants as good indicators of the multiple contaminations. The structure and diversity of the microbial community proved to be very good bioindicators, corroborating and validating the results from the QR index application in SB.