College of Bio-systems Engineering and Food Science, Zhejiang University, Hangzhou, PR China; Ocean Academy, Zhejiang University, Zhoushan, PR China.
College of Bio-systems Engineering and Food Science, Zhejiang University, Hangzhou, PR China.
Sci Total Environ. 2023 Jan 20;857(Pt 3):159637. doi: 10.1016/j.scitotenv.2022.159637. Epub 2022 Oct 21.
Nitrate accumulation is a common phenomenon in aquaculture that can lead to eutrophication of surrounding water bodies. This study used poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) as a carbon source and substrate and performed a microbial co-occurrence network ecological analysis to elucidate the denitrification processes in two packed-bed reactors with different salinities. The denitrification rate reached maximum values of 0.438 and 0.446 kg m d in reactor I (salinity 0 ‰) and reactor II (salinity 20 ‰), respectively. Although ammonia was formed in both systems based on dissimilation nitrate reduction to ammonia (DNRA), the concentration was very low (2.47 ± 1.99 and 2.84 ± 1.79 mg L); moreover, the nitrite content was average (1.01 ± 0.87 and 0.96 ± 0.86 mg L). These results suggested that denitrification dominated in both reactors. PHBV generally presented a stable release of DOC, although a sharp increase was observed in the start-up period of reactor II. 16S rRNA results showed that reactor I had richer microbial diversity than reactor II. Among the top ten taxa, Betaproteobacteria was the dominant class in reactor I while Gammaproteobacteria was the dominant class in reactor II. In the stable period, Thauera and Denitromonas was the most abundant genera in reactor I and reactor II, respectively. In addition, the bacterial co-occurrence network showed that reactor I had a more complex node and edge network and faster start-up time compared to reactor II; however, reactor II had a more stable nitrogen removal capacity. Higher expression of NorB and NosZ genes in reactor II indicated higher efficient denitrification in seawater system. The SEM and FTIR showed bacterial development and materials surface erosion. These findings verified the denitrification performance and niche differences between freshwater and seawater environments.
硝酸盐积累是水产养殖中的一种常见现象，会导致周围水体富营养化。本研究以聚（3-羟基丁酸-co-3-羟基戊酸）（PHBV）为碳源和底物，进行微生物共现网络生态分析，阐明了两个不同盐度填充床反应器中的反硝化过程。在盐度为 0‰的反应器 I 和盐度为 20‰的反应器 II 中，反硝化速率分别达到了 0.438 和 0.446 kg m d 的最大值。尽管两个系统都基于异化硝酸盐还原为氨（DNRA）形成了氨，但浓度非常低（2.47±1.99 和 2.84±1.79 mg L）；此外，亚硝酸盐含量也较低（1.01±0.87 和 0.96±0.86 mg L）。这些结果表明，两个反应器中都以反硝化作用为主。尽管在反应器 II 的启动阶段观察到 PHBV 有一个急剧的 DOC 释放，但 PHBV 通常呈现出稳定的释放。16S rRNA 结果表明，反应器 I 的微生物多样性比反应器 II 更丰富。在排名前十的类群中，Betaproteobacteria 是反应器 I 的优势类群，而 Gammaproteobacteria 是反应器 II 的优势类群。在稳定期，Thauera 和 Denitromonas 分别是反应器 I 和反应器 II 中最丰富的属。此外，细菌共现网络表明，与反应器 II 相比，反应器 I 具有更复杂的节点和边缘网络，启动时间更快；然而，反应器 II 具有更稳定的脱氮能力。反应器 II 中 NorB 和 NosZ 基因的高表达表明，在海水系统中具有更高效率的反硝化作用。SEM 和 FTIR 显示了细菌的生长和材料表面的侵蚀。这些发现验证了淡水和海水环境中反硝化性能和生态位差异。
