He Tao, Chen Yudong, Wang Yutao, Peng Zongyi, Mou You, Wang Longfei
China Yangtze Power Co, Ltd. (CYPC), Wuhan, 430000, China.
National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, Nanjing, 210098, China.
Microb Ecol. 2025 Jul 2;88(1):71. doi: 10.1007/s00248-025-02569-2.
The hyporheic zone (HZ) of treated sewage-dominated rivers serves as a critical biogeochemical hotspot for dissolved organic nitrogen (DON) transformation, yet the mechanisms linking DON chemodiversity to microbial community dynamics remain poorly resolved. This study integrated spectroscopic fingerprinting, machine learning, and partial least squares path modeling (PLS-PM) to unravel the interactions between redox-stratified DON fractions and microbial consortia in two effluent-impacted rivers (Xi'an, China). The results revealed that DOM spectral parameters associated with distinct DON characteristics posed distinct effects on microbial communities, with the communities in oxic zones largely impacted by autobiogenic, aromatic, and protein-like DON, while the communities in suboxic zones were more intensely impacted by the humification degree of DON. Microbial communities exhibited redox-dependent niche differentiation; i.e., keystone taxa in oxic zones (e.g., Gamma-Proteobacteria) drove nitrogen assimilation, while suboxic taxa (e.g., Verrucomicrobia) prioritized stress-resistant D-amino acid metabolism. PLS-PM demonstrated that biomarkers exerted stronger control on nitrogen cycling (|path coefficients|> 0.6, P < 0.05) than keystone taxa, with summer communities showing higher model fit. Treated sewage-derived DON fostered specialized consortia through biochemical trade-offs, i.e., methionine recycling in oxic zones versus peptidoglycan modification in suboxic zones, thus highlighting the critical role of HZ in mitigating nitrogen pollution. These findings advance predictive modeling of DON-microbe interactions in anthropogenically perturbed aquatic ecosystems.
以处理后的污水为主的河流的潜流带（HZ）是溶解有机氮（DON）转化的关键生物地球化学热点，但将DON化学多样性与微生物群落动态联系起来的机制仍未得到很好的解析。本研究整合了光谱指纹识别、机器学习和偏最小二乘路径建模（PLS-PM），以揭示两条受废水影响的河流（中国西安）中氧化还原分层的DON组分与微生物群落之间的相互作用。结果表明，与不同DON特征相关的DOM光谱参数对微生物群落有不同的影响，有氧区的群落主要受自生、芳香和蛋白质类DON的影响，而缺氧区的群落则受DON腐殖化程度的影响更大。微生物群落表现出氧化还原依赖性的生态位分化；即有氧区的关键类群（如γ-变形菌）驱动氮同化，而缺氧类群（如疣微菌）则优先进行抗逆性D-氨基酸代谢。PLS-PM表明，生物标志物对氮循环的控制作用（|路径系数|>0.6，P<0.05）比关键类群更强，夏季群落的模型拟合度更高。处理后的污水衍生的DON通过生化权衡促进了专门的群落形成，即有氧区的蛋氨酸循环与缺氧区的肽聚糖修饰，从而突出了HZ在减轻氮污染方面的关键作用。这些发现推进了人为扰动的水生生态系统中DON-微生物相互作用的预测模型。
