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1.
J Hazard Mater ; 472: 134521, 2024 Jul 05.
Article in English | MEDLINE | ID: mdl-38718513

ABSTRACT

Norfloxacin (NOR) is widely used in medicine and animal husbandry, but its accumulation in the environment poses a substantial threat to ecological and human health. Traditional physical, chemical, and rudimentary biological methods often fall short in mitigating NOR contamination, necessitating innovative biological approaches. This study proposes an engineered bacterial consortium found in marine sediment as a strategy to enhance NOR degradation through inter-strain co-metabolism of diverse substrates. Strategically supplementing the engineered bacterial consortium with exogenous carbon sources and metal ions boosted the activity of key degradation enzymes like laccase, manganese peroxidase, and dehydrogenase. Iron and amino acids demonstrated synergistic effects, resulting in a remarkable 70.8% reduction in NOR levels. The innovative application of molecular docking elucidated enzyme interactions with NOR, uncovering potential biodegradation mechanisms. Quantitative assessment reinforced the efficiency of NOR degradation within the engineered bacterial consortium. Four metabolic routes are herein proposed: acetylation, defluorination, ring scission, and hydroxylation. Notably, this study discloses distinctive, co-operative metabolic pathways for NOR degradation within the specific microbial community. These findings provide new ways of understanding and investigating the bioremediation potential of NOR contaminants, which may lead to the development of more sustainable and effective environmental management strategies.


Subject(s)
Biodegradation, Environmental , Molecular Docking Simulation , Norfloxacin , Norfloxacin/metabolism , Anti-Bacterial Agents/metabolism , Anti-Bacterial Agents/chemistry , Metabolic Networks and Pathways , Bacteria/metabolism , Geologic Sediments/microbiology , Geologic Sediments/chemistry , Microbial Consortia , Water Pollutants, Chemical/metabolism , Water Pollutants, Chemical/chemistry
2.
J Hazard Mater ; 466: 133655, 2024 Mar 15.
Article in English | MEDLINE | ID: mdl-38310843

ABSTRACT

The extensive use of plastics has given rise to microplastics, a novel environmental contaminant that has sparked considerable ecological and environmental concerns. Biodegradation offers a more environmentally friendly approach to eliminating microplastics, but their degradation by marine microbial communities has received little attention. In this study, we used iron-enhanced marine sediment to augment the natural bacterial community and facilitate the decomposition of polyethylene (PE) microplastics. The introduction of iron-enhanced sediment engendered an augmented bacterial biofilm formation on the surface of polyethylene (PE), thereby leading to a more pronounced degradation effect. This novel observation has been ascribed to the oxidative stress-induced generation of a variety of oxygenated functional groups, including hydroxyl (-OH), carbonyl (-CO), and ether (-C-O) moieties, within the microplastic substrate. The analysis of succession in the community structure of sediment bacteria during the degradation phase disclosed that Acinetobacter and Pseudomonas emerged as the principal bacterial players in PE degradation. These taxa were directly implicated in oxidative metabolic pathways facilitated by diverse oxidase enzymes under iron-facilitated conditions. The present study highlights bacterial community succession as a new pivotal factor influencing the complex biodegradation dynamics of polyethylene (PE) microplastics. This investigation also reveals, for the first time, a unique degradation pathway for PE microplastics orchestrated by the multifaceted marine sediment microbiota. These novel insights shed light on the unique functional capabilities and internal biochemical mechanisms employed by the marine sediment microbiota in effectively degrading polyethylene microplastics.


Subject(s)
Microbiota , Water Pollutants, Chemical , Microplastics/pharmacology , Plastics/analysis , Polyethylene/pharmacology , Iron/analysis , Water Pollutants, Chemical/analysis , Bacteria , Geologic Sediments/microbiology , Metabolic Networks and Pathways
3.
Sci Total Environ ; 858(Pt 2): 159876, 2023 Feb 01.
Article in English | MEDLINE | ID: mdl-36334662

ABSTRACT

Bisphenol A (BPA), a typical endocrine disruptor and a contaminant of emerging concern (CECs), has detrimental impacts not only on the environment and ecosystems, but also on human health. Therefore, it is essential to investigate the degrading processes of BPA in order to diminish its persistent effects on ecological environmental safety. With this objective, the present study reports on the effectiveness of biotic/abiotic factors in optimizing BPA removal and evaluates the kinetic models of the biodegradation processes. The results showed that BPA affected chlorophyll a, superoxide dismutase (SOD) and peroxidase (POD) activities, malondialdehyde (MDA) content, and photosystem intrinsic PSII efficiency (Fv/Fm) in the microalga Chlorella pyrenoidosa, which degraded 43.0 % of BPA (8.0 mg L-1) under general experimental conditions. The bacteria consortium AEF21 could remove 55.4 % of BPA (20 mg L-1) under orthogonal test optimization (temperature was 32 °C, pH was 8.0, inoculum was 6.0 %) and the prediction of artificial neural network (ANN) of machine learning (R2 equal to 0.99 in training, test, and validation phase). The microalgae-bacteria consortia have a high removal rate of 57.5 % of BPA (20.0 mg L-1). The kinetic study revealed that the removal processes of BPA by microalgae, bacteria, and microalgae-bacteria consortia all followed the Monod's kinetic model. This work provided a new perspective to apply artificial intelligence to predict the degradation of BPA and to understand the kinetic processes of BPA biodegradation by integrated biological approaches, as well as a novel research strategy to achieve environmental CECs elimination for long-term ecosystem health.


Subject(s)
Chlorella , Microalgae , Humans , Microalgae/metabolism , Ecosystem , Chlorella/metabolism , Chlorophyll A/metabolism , Artificial Intelligence , Benzhydryl Compounds/metabolism , Biodegradation, Environmental , Bacteria/metabolism , Machine Learning
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