A new method to quantify atmospheric Poaceae pollen DNA based on the trnT-F cpDNA region
Sahin, Aydan Acar
Pinar, Nur Munevver
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Background: Pollen, mold spores, bacteria and viruses are the main biological substances in the atmosphere causing allergic symptoms and disease. Distinguishing pollen and spores is quite time consuming and requires a trained expert. There is a different approach to identification of these substances such as microscopic analysis. However, DNA based identification of these is becoming popular recently. Objective: We evaluated the correlation between the quantity of DNA, which was amplified using trnT-F cpDNA specific primers in samples obtained from a high volume air sampler (HVAS), and concentration of Poaceae pollen collected with a Burkard trap. Materials and methods: Here, we present a method for identifying and quantifying airborne Poaceae pollen using a single step polymerase chain reaction (PCR) technique. Forty daily air samples were collected by HVAS. The method was optimised using two different methods (M1 and M2) and the trnT-F cpDNA region was amplified using a Poaceae specific primer pair. The correlation between the quantity of DNA and pollen concentration was tested using R statistical programming language. Results: Although a significant correlation was obtained between the M1 and M2 methods (R-2 = 0.655, p <0.01), the M2 method was more correlated with pollen concentration. The correlation between pollen and DNA content changed due to episodes that were observed during the pollen season. DNA concentrations from the PCR data were significantly correlated with pollen concentrations determined by light microscopy (R-2 =0.767, p <0.01) in episode II using the M2 method and during the entire season (R-2 =0.469, p <0.01) using M2. Conclusions: The M2 method correctly identified Poaceae pollen in mixed air samples from Zonguldak Province. The non-coding trnT-F cpDNA region was used for the first time in aerobiological samples to identify Poaceae pollen. Use of this method that does not require DNA extraction may be a crucial step for real-time pollen monitoring devices to be developed in the future. The correlation strength between pollen and amplified DNA content could be improved using a sampler that has a lower absorption rate, and a more sensitive technique, such as qPCR.