Identifying and quantifying airborne pollen is important for causal assessment of allergic symptoms, for determining which pollens should be tested and for interpreting the results of allergy tests. Present pollen counting methods are time-consuming, require specific expertise and training, and are prone to subjective variability. Our goal is to devise a sensitive, high throughput method of quantifying pollen load in environmental samples.
9 different pure pollen samples, including grass (Paspalum notatum), trees (Morella cerifera, Morus alba, Juniperus ashei, Pinus strobus, Quercus virginiana, Taxodium distichum, Ulmus americana), and ragweed (Ambrosia artemisifolia) were used for analysis (courtesy of Tom Greer PhD, Greer Laboratories). Genomic DNA (gDNA) was extracted from pure pollens using a modification of the DNAzol ES procedure. Primers specific for the 5.8S rRNA genes of the different pollens were designed for quantitative real-time PCR (qPCR) using a SYBRGreen-based PCR assay.
Individual gDNA from the pollens was detectable to sub nanogram levels. Individual pollen gDNA was detected in samples consisting of a mixture of all 9 pollen gDNAs. Specific pollens were detected in gDNA extracted from randomly admixed samples of the various pollen samples. The selected primers provided accurate identification in mixed samples with variable efficiency.
qPCR detection of the pollen gDNA is sensitive and specific. The current assay can be expanded to include additional species and/or modified to detect pollens native to distinct geographical regions. Actual environmental sample quantification is necessary to prove applicability.