PS 44-82 - Identifying Microorganisms Responsible for Dissimilatory Nitrate Reduction to Ammonium (DNRA) in Soil Ecosystems

Wednesday, August 14, 2019
Exhibit Hall, Kentucky International Convention Center
Joanne C. Chee-Sanford, USDA-ARS, Urbana, Jordan Cannon, Dept. of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, IL, Robert A. Sanford, Department of Geology, University of Illinois at Urbana-Champaign, Urbana, IL and Wendy H. Yang, Departments of Plant Biology and Geology, University of Illinois at Urbana-Champaign, Urbana, IL
Background/Question/Methods

Nitrite ammonification or DNRA is now known to be a more prevalent process in terrestrial ecosystems than previously thought. The key enzyme, a pentaheme cytochrome c nitrite reductase NrfA, is encoded by the nrfA gene in a broad phylogeny of bacteria. The lack of reliable and comprehensive molecular tools to detect diverse nrfA from environmental samples has hampered efforts to meaningfully characterize the genetic potential for DNRA in different ecosystems. In this study, we optimized the design of PCR primers that target the diagnostic coding region of NrfA between the conserved third- and fourth heme binding domains. We applied the use of these primers to artificial assemblages of microorganisms and to DNA extracted from agricultural soil and shallow groundwater wells. Amplicons were subjected to sequencing using Illumina MiSeq or amplicon fragment length polymorphism (AFLP) community fingerprint analysis.

Results/Conclusions

Using an alignment of the primers to >270 bacterial nrfA genes affiliated with 18 distinct clades, primer sets were designed and validated to show improved coverage, minimized amplification artifacts, and yielded the predicted product sizes from reference-, soil-, and groundwater DNA. Illumina sequencing of amplicons showed the successful recovery of nrfA gene fragments from environmental DNA representing six different clades based on alignments of the translated sequences. AFLP analyses demonstrated the detection of all eight reference nrfA genes used in defined bacterial assemblages, differentiating fragment length differences and GC content of the gene fragment. Soil AFLP analysis demonstrated that nrfA community profiles from two different agricultural soils (sandy and silty-loam) could be differentiated based the fragment sizes present. This type of analysis could be applied to nrfA mRNA transcripts to define the community of active DNRA organisms in any ecosystem. The optimized primers developed in this study are more efficient in PCR reactions, have a broader spectrum of detection and were validated rigorously for use in detecting nrfA from natural environments. These are suitable for conventional PCR, qPCR, and use in PCR access array technologies that allow multiplex gene amplification for downstream high throughput sequencing platforms.