Quantitative assessment, molecular docking and novel metabolic pathways reveal the interaction mechanisms between norfloxacin biodegradation and environmental implications.

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.

Enhanced degradation of bisphenol A: Influence of optimization of removal, kinetic model studies, application of machine learning and microalgae-bacteria consortia.

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.