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Monitored natural recovery (MNR) is an in situ technique of conventional remediation for the treatment of contaminated sediments that relies on natural processes to reduce the bioavailability or toxicity of contaminants. Metabarcoding and bioinformatics approaches to infer functional prediction were applied in bottom sediments of a tributary drainage channel of Río de La Plata estuary, in order to assess the biological contribution to MNR. Hydrocarbon concentration in water samples and surface sediments was below the detection limit. Surface sediments were represented with high available phosphorous, alkaline pH, and the bacterial classes Anaerolineae, Planctomycetia, and Deltaproteobacteria. The functional prediction in surface sediments showed an increase of metabolic activity, carbon fixation, methanogenesis, and synergistic relationships between Archaeas, Syntrophobacterales, and Desulfobacterales. The prediction in non-surface sediments suggested the capacity to respond to different kinds of environmental stresses (oxidative, osmotic, heat, acid pH, and heavy metals), predicted mostly in Lactobacillales order, and the capacity of Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, and Actinomyces classes to degrade xenobiotic compounds. Canonical correspondence analysis (CCA) suggests that depth, phosphate content, redox potential, and pH were the variables that structured the bacterial community and not the hydrocarbons. The characterization of sediments by metabarcoding and functional prediction approaches, allowed to assess how the microbial activity would contribute to the recovery of the site. |
