Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
Department of Natural Resources and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
Environ Microbiol. 2019 Apr;21(4):1196-1210. doi: 10.1111/1462-2920.14555. Epub 2019 Mar 10.
Microbial populations provide nitrogen cycling ecosystem services at the nexus of agriculture, environmental quality and climate change. Denitrification, in particular, impacts socio-environmental systems in both positive and negative ways, through reduction of aquatic and atmospheric nitrogen pollution, but also reduction of soil fertility and production of greenhouse gases. However, denitrification rates are quite variable in time and space, and therefore difficult to model. Microbial ecology is working to improve the predictive ecology of denitrifiers by quantifying and describing the diversity of microbial functional groups. However, metagenomic sequencing has revealed previously undescribed diversity within these functional groups, and highlighted a need to reevaluate coverage of existing DNA primers for denitrification functional genes. We provide here a comprehensive in silico evaluation of primer sets that target diagnostic genes in the denitrification pathway. This analysis makes use of current DNA sequence data available for each functional gene. It contributes a comparative analysis of the strengths and limitations of each primer set for describing denitrifier functional groups. This analysis identifies genes for which development of new tools is needed, and aids in interpretation of existing datasets, both of which will facilitate application of molecular methods to further develop the predictive ecology of denitrifiers.
微生物种群在农业、环境质量和气候变化的交叉点提供氮循环生态系统服务。反硝化作用，特别是通过减少水和大气氮污染，以及减少土壤肥力和产生温室气体，对社会-环境系统产生了积极和消极的影响。然而，反硝化作用速率在时间和空间上具有很大的可变性，因此难以建模。微生物生态学通过量化和描述微生物功能群的多样性来努力提高反硝化菌的预测生态学。然而，宏基因组测序揭示了这些功能群中以前未描述的多样性，并强调需要重新评估现有的用于反硝化功能基因的 DNA 引物的覆盖范围。我们在这里提供了对靶向反硝化途径中诊断基因的引物的综合计算机评估。该分析利用了每个功能基因的现有 DNA 序列数据。它对每个引物组描述反硝化功能群的优缺点进行了比较分析。该分析确定了需要开发新工具的基因，并有助于解释现有数据集，这两者都将有助于分子方法的应用，以进一步发展反硝化菌的预测生态学。
