The explosive hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) is a contaminant at many military sites. RDX bioremediation as a clean-up approach has been gaining popularity because of cost benefits compared to other methods. RDX biodegradation has primarily been linked to six functional genes (diaA, nfsI, pnrB, xenA, xenB, xplA). However, current methods for gene quantification have the risk of false negative results because of low theoretical primer coverage. To address this, the current study designed new primer sets using the EcoFunPrimer tool based on sequences collected by the Functional Gene Pipeline and Repository and these were verified based on residues and motifs. The primers were also designed to be co... More
The explosive hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) is a contaminant at many military sites. RDX bioremediation as a clean-up approach has been gaining popularity because of cost benefits compared to other methods. RDX biodegradation has primarily been linked to six functional genes (diaA, nfsI, pnrB, xenA, xenB, xplA). However, current methods for gene quantification have the risk of false negative results because of low theoretical primer coverage. To address this, the current study designed new primer sets using the EcoFunPrimer tool based on sequences collected by the Functional Gene Pipeline and Repository and these were verified based on residues and motifs. The primers were also designed to be compatible with the SmartChip Real-Time PCR system, a massively parallel singleplex PCR platform (high throughput qPCR), that enables quantitative gene analysis using 5,184 simultaneous reactions on a single chip with low volumes of reagents. This allows multiple genes and/or multiple primer sets for a single gene to be used with multiple samples. Following primer design, the six genes were quantified in RDX-contaminated groundwater (before and after biostimulation), RDX-contaminated sediment, and uncontaminated samples. The final 49 newly designed primer sets improved upon the theoretical coverage of published primer sets, and this corresponded to more detections in the environmental samples. All genes, except diaA, were detected in the environmental samples, with xenA and xenB being the most predominant. In the sediment samples, nfsI was the only gene detected. The new approach provides a more comprehensive tool for understanding RDX biodegradation potential at contaminated sites.
