Madueño Laura, Starevich Viviana Ayelen, Agnello Ana Carolina, Coppotelli Bibiana Marina, Laprida Cecilia, Vidal Nuria Carolina, Di Marco Pablo, Oneto Maria Elena, Del Panno Maria Teresa, Morelli Irma Susana
CINDEFI, UNLP-CONICET, La Plata, Argentina.
Instituto de Estudios Andinos, CONICET/UBA, Ciudad Autónoma de Buenos Aires, Argentina.
Front Microbiol. 2021 Mar 5;12:601705. doi: 10.3389/fmicb.2021.601705. eCollection 2021.
Monitored natural recovery (MNR) is an 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.
监测自然恢复(MNR)是一种用于处理受污染沉积物的传统修复技术,它依靠自然过程来降低污染物的生物有效性或毒性。为了评估对监测自然恢复的生物学贡献,将推断功能预测的元条形码和生物信息学方法应用于拉普拉塔河河口一条支流排水渠道的底部沉积物中。水样和表层沉积物中的碳氢化合物浓度低于检测限。表层沉积物的特征是有效磷含量高、碱性pH值,以及厌氧绳菌纲、浮霉菌纲和δ-变形菌纲细菌。表层沉积物中的功能预测显示代谢活动、碳固定、甲烷生成增加,以及古菌、互营杆菌目和脱硫杆菌目之间的协同关系。非表层沉积物中的预测表明其对不同种类环境压力(氧化、渗透、热、酸性pH值和重金属)的响应能力,主要在乳杆菌目中预测到,以及α-变形菌纲、β-变形菌纲、γ-变形菌纲和放线菌纲降解外源化合物的能力。典范对应分析(CCA)表明,深度、磷酸盐含量、氧化还原电位和pH值是构建细菌群落的变量,而非碳氢化合物。通过元条形码和功能预测方法对沉积物进行表征,有助于评估微生物活动如何促进该场地的恢复。