School of Resources and Environmental Engineering, Anhui University, Hefei, 230601, Anhui Province, China.
Key Laboratory of Wetland Ecological Protection and Restoration, Hefei, China.
Environ Sci Pollut Res Int. 2021 Oct;28(37):51928-51939. doi: 10.1007/s11356-021-14348-w. Epub 2021 May 15.
Denitrification in river sediments plays a very important role in removing nitrogen in aquatic ecosystem. To gain insight into the key factors driving denitrification at large spatial scales, a total of 135 sediment samples were collected from Huaihe River and its branches located in the northern of Anhui province. Bacterial community composition and denitrifying functional genes (nirS, nirK, and nosZ) were measured by high-throughput sequencing and real-time PCR approaches. Potential denitrification rate (PDR) was measured by acetylene inhibition method, which varied from 0.01 to 15.69 μg N g h. The sequencing results based on 16S rRNA gene found that the main denitrification bacterial taxa included Bacillus, Thiobacillus, Acinetobacter, Halomonas, Denitratisoma, Pseudomonas, Rhodanobacter, and Thauera. Therein, Thiobacillus might play key roles in the denitrification. Total nitrogen and N:P ratio were the only chemical factors related with all denitrification genes. Furthermore, nirS gene abundance could be more susceptible to environmental parameters compared with nirK and nosZ genes. Canonical correspondence analysis indicated that NO, NO, NH and IP had the significant impacts on the nirS-encoding bacterial community and spatial distributions. There was a significantly positive correlation between Thiobacillus and nirS gene. We considered that higher numbers of nosZ appeared in nutrient rich sediments. More strikingly, PDR was positively correlated with the abundance of three functional genes. Random forest analysis showed that NH was the most powerful predictor of PDR. These findings can yield practical and important reference for the bioremediation or evaluation of wetland systems.
河流沉积物中的反硝化作用在去除水生生态系统中的氮方面起着非常重要的作用。为了深入了解在大空间尺度上驱动反硝化作用的关键因素，从安徽省北部的淮河及其支流中采集了总共 135 个沉积物样本。通过高通量测序和实时 PCR 方法测量了细菌群落组成和反硝化功能基因（nirS、nirK 和 nosZ）。通过乙炔抑制法测量了潜在的反硝化速率（PDR），其范围从 0.01 到 15.69 μg N g h。基于 16S rRNA 基因的测序结果发现，主要的反硝化细菌类群包括芽孢杆菌、硫杆菌、不动杆菌、盐单胞菌、脱氮硫杆菌、假单胞菌、罗得丹菌和陶厄氏菌。其中，硫杆菌可能在反硝化过程中起关键作用。总氮和 N:P 比是与所有反硝化基因相关的唯一化学因素。此外，与 nirK 和 nosZ 基因相比，nirS 基因的丰度可能更容易受到环境参数的影响。典范对应分析表明，NO3-、NO2-、NH4+和 IP 对 nirS 编码细菌群落和空间分布有显著影响。硫杆菌与 nirS 基因呈显著正相关。我们认为，在营养丰富的沉积物中，nosZ 的数量更高。更引人注目的是，PDR 与三个功能基因的丰度呈正相关。随机森林分析表明，NH4+是 PDR 的最有力预测因子。这些发现可为生物修复或湿地系统的评估提供实用和重要的参考。
