Anaerobic oxidation of methane (AOM) reduces methane emissions from marine ecosystems but we know little about AOM in rivers, whose role in the global carbon cycle is increasingly recognized. We measured AOM potentials driven by different electron acceptors, including nitrite, nitrate, sulfate, and ferric iron, and identified microorganisms involved across contrasting riverbeds. AOM activity was confined to the more reduced, sandy riverbeds, whereas no activity was measured in the less reduced, gravel riverbeds where there were few anaerobic methanotrophs. Nitrite-dependent and nitrate-dependent AOM occurred in all sandy riverbeds, with the maximum rates of 61.0 and 20.0 nmol CO₂ g⁻¹ (dry sediment) d⁻¹, respectively, while sulfate-dependent and ferric iron-dependent AOM occurred only where methane concentration was highest and the diversity of AOM pathways greatest. Diverse Candidatus Methylomirabilis oxyfera (M. oxyfera)-like bacteria and Candidatus Methanoperedens nitroreducens (M. nitroreducens)-like archaea were detected in the sandy riverbeds (16S rRNA gene abundance of 9.3 × 10⁵ to 1.5 × 10⁷ and 2.1 × 10⁴ to 2.5 × 10⁵ copies g⁻¹ dry sediment, respectively) but no other known anaerobic methanotrophs. Further, we found M. oxyfera-like bacteria and M. nitroreducens-like archaea to be actively involved in nitrite- and nitrate/ferric iron-dependent AOM, respectively. Hence, we demonstrate multiple pathways of AOM in relation to methane, though the activities of M. oxyfera-like bacteria and M. nitroreducens-like archaea are dominant.

Municipal wastewater treatment plants (WWTPs) use functional microorganisms in activated sludge (AS) to reduce the environmental threat posed by wastewater. In this study, Illumina NovaSeq sequencing of 16S rRNA genes was performed to explore the microbial communities of AS at different stages of the two WWTP projects in Shenzhen, China. Results showed that Proteobacteria, Bacteroidetes, Acidobacteria, Firmicutes, and Nitrospirae were the dominant phyla in all the samples, with Proteobacteria being the most abundant and reaching a maximum proportion of 59.63%. There was no significant difference in biodiversity between the two water plants, but Stage 1 and Stage 2 were significantly different. The Mantel test indicated that nitrate, total nitrogen (TN), chemical oxygen demand (COD), and nutrients were essential factors affecting the bacterial community structure. FAPROTAX analysis emphasized that the leading functional gene families include nitrification, aerobic nitrite oxidation, human pathogens, and phototrophy. This study reveals changes in the community structure of AS in different treatment units of Banxuegang WWTP, which can help engineers to optimize the wastewater treatment process.

A novel malachite green molecularly imprinted membrane (MG-MIM) with specific selectivity for malachite green (MG) and leucomalachite green (LMG) was prepared using a hydrophobic glass fiber membrane as the polymer substrate, methyl violet as a template analog, 4-vinyl benzoic acid as the functional monomer, and ethyleneglycol dimethacrylate as the crosslinking agent. MG-MIM and non-imprinted membrane (NIM) were structurally characterized using scanning electron microscopy, surface area analyzer, Fourier-transform infrared spectrometer and synchronous thermal analyzer. The results showed that MG-MIM possessed a fluffier surface, porous and looser structure, and had good thermal stability. Adsorption properties of MG-MIM were investigated under optimal conditions, and adsorption equilibrium was reached in 20 min. The saturated adsorption capacities for MG and LMG were 24.25 ng·cm⁻² and 13.40 ng·cm⁻², and the maximum imprinting factors were 2.41 and 3.20, respectively. Issues such as “template leakage” and “embedding” were resolved. The specific recognition ability for the targets was good and the adsorption capacity was stable even after five cycles. The proposed method was successfully applied for the detection of MG and LMG in real samples, and it showed good linear correlation in the range of 0 to 10.0 μg·L⁻¹ (R² = 0.9991 and 0.9982), and high detection sensitivity (detection limits of MG and LMG of 0.005 μg/kg and 0.02 μg·kg⁻¹ in shrimp, and 0.005 μg/kg and 0.02 μg/kg in fish sample). The recoveries and relative standard deviations were in the range of 76.31–93.26% and 0.73–3.72%, respectively. The proposed method provides a simple, efficient and promising alternative for monitoring MG and LMG in aquatic products.