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Refractory wastewater shapes bacterial assembly and key taxa during long-term acclimatization.
Gao, Linjun; Wang, Xiaoxiao; Wang, Yujie; Xu, Xu; Miao, Yu; Shi, Peng; Jia, Shuyu.
Afiliación
  • Gao L; College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China.
  • Wang X; College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China.
  • Wang Y; State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China.
  • Xu X; College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China.
  • Miao Y; Department of Civil and Environmental Engineering, Northeastern University, Boston 02115, United States; Department of Marine and Environmental Sciences, Northeastern University, Boston 02115, United States.
  • Shi P; State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China.
  • Jia S; College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China. Electronic address: jiasy@njau.edu.cn.
Water Res ; 265: 122246, 2024 Nov 01.
Article en En | MEDLINE | ID: mdl-39163712
ABSTRACT
Bacterial assembly and key taxa during long-term acclimatization in refractory wastewater treatment systems is of paramount importance for optimizing system performance and improving management strategies. Therefore, this study employed high-throughput sequencing, coupled with machine learning models and statistical analysis approaches, to comprehensively elucidate key features of bacterial communities and assembly processes in pesticide wastewater treatment systems. A nine-month monitoring showed substantial variation in diversity and composition of bacterial community between two interconnected biological treatment units (designated as BA and PA). Dynamics of bacterial communities in both units were similar. Moreover, water quality played crucial roles in regulating the bacterial community structure of activated sludge, which were primarily driven by deterministic patterns. Homogeneous selection contributed to 62.85 % and 64.43 % of the variations in BA and PA samples, respectively. Additionally, network analysis revealed significant modularity in bacterial compositions in both groups. Linear regression analysis identified major bacterial modules associated with metabolism and degradation functions. Notably, Module 2 in PA samples has significant positive correlations with functions related to metabolism of nucleotide, amino acid, and xenobiotics, as well as benzoate degradation. Furthermore, key taxa in ecological modules identified by Random Forest model, such as Pseudomonas, Sphingobium, and PHOS-HE28, were dominant populations with metabolism and degradation functions. Particularly, Sphingobium, appeared to be a potential multifunctional degrading bacterium, related to amino acid and xenobiotics metabolism, as well as fatty acid, valine, leucine, isoleucine, fluorobenzoate, and aminobenzoate degradation. These findings are important for developing operating strategies to maintain stable system performance during refractory wastewater treatment.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Bacterias / Aguas Residuales Idioma: En Revista: Water Res Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Bacterias / Aguas Residuales Idioma: En Revista: Water Res Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido