Department of Biological & Environmental Engineering, Cornell University, Ithaca, NY, USA.
Department of Microbiology, Cornell University, Ithaca, NY, USA.
Environ Microbiol. 2019 Apr;21(4):1255-1266. doi: 10.1111/1462-2920.14587. Epub 2019 Mar 21.
This study coupled a landscape-scale metagenomic survey of denitrification gene abundance in soils with in situ denitrification measurements to show how environmental factors shape distinct denitrification communities that exhibit varying denitrification activity. Across a hydrologic gradient, the distribution of total denitrification genes (nap/nar + nirK/nirS + cNor/qNor + nosZ) inferred from metagenomic read abundance exhibited no consistent patterns. However, when genes were considered independently, nirS, cNor and nosZ read abundance was positively associated with areas of higher soil moisture, higher nitrate and higher annual denitrification rates, whereas nirK and qNor read abundance was negatively associated with these factors. These results suggest that environmental conditions, in particular soil moisture and nitrate, select for distinct denitrification communities that are characterized by differential abundance of genes encoding apparently functionally redundant proteins. In contrast, taxonomic analysis did not identify notable variability in denitrifying community composition across sites. While the capacity to denitrify was ubiquitous across sites, denitrification genes with higher energetic costs, such as nirS and cNor, appear to confer a selective advantage in microbial communities experiencing more frequent soil saturation and greater nitrate inputs. This study suggests metagenomics can help identify denitrification hotspots that could be protected or enhanced to treat non-point source nitrogen pollution.
本研究结合了土壤中反硝化基因丰度的景观尺度宏基因组调查和原位反硝化测量，以展示环境因素如何塑造表现出不同反硝化活性的独特反硝化群落。在水文学梯度上，从宏基因组读数丰度推断的总反硝化基因（nap/nar + nirK/nirS + cNor/qNor + nosZ）的分布没有一致的模式。然而，当单独考虑基因时，nirS、cNor 和 nosZ 的读数丰度与较高的土壤湿度、较高的硝酸盐和较高的年反硝化速率呈正相关，而 nirK 和 qNor 的读数丰度与这些因素呈负相关。这些结果表明，环境条件，特别是土壤湿度和硝酸盐，选择了具有不同丰度的反硝化群落，这些群落的特征是编码明显功能冗余蛋白的基因丰度不同。相比之下，分类分析并没有在不同地点的反硝化群落组成中发现明显的可变性。虽然在所有地点都具有反硝化能力，但具有更高能量成本的反硝化基因，如 nirS 和 cNor，在经历更频繁的土壤饱和和更大的硝酸盐输入的微生物群落中似乎具有选择性优势。本研究表明，宏基因组学可以帮助识别反硝化热点，可以对其进行保护或增强，以处理非点源氮污染。
