Publication date: Available online 23 December 2016
Source:Annals of Allergy, Asthma & Immunology
Author(s): Rashmi Prava Mohanty, Mark Alan Buchheim, Estelle Levetin
BackgroundPollen monitoring is a common and vital tool in the field of allergy, creating awareness in pollen sensitive individuals. Traditionally, pollen monitoring has been based on conventional microscopic counting techniques that are labor intensive and limited in the identification to the genus or family level. Molecular techniques provide an alternative approach that is less labor intensive and enable identification of any species by its genetic fingerprint.ObjectiveTo use quantitative polymerase chain reaction (qPCR) to evaluate pollen concentrations in air samples.MethodsJuniperus pollen was selected as our model because of the importance of this pollen in the southcentral United States. We analyzed 105 air samples collected with a Burkard spore trap from 2013 to 2015 using species-specific primers and probes. To evaluate the feasibility of a molecular approach, we used duplicate air samples that allowed us to compare results from classical identification based on light microscopy with our qPCR results.ResultsPollen concentrations from the qPCR data were significantly correlated with concentrations determined through light microscopy (R = 0.902, P < .001). We also confirmed an overlap in the pollination seasons between Juniperus ashei and Juniperus pinchotii and between J ashei and Juniperus virginiana.ConclusionWe found that this method correctly identified different Juniperus species present in mixed air samples in the southcentral United States, an accomplishment that cannot be achieved using microscopic identification. We conclude that the qPCR method is more accurate and sensitive than current pollen monitoring techniques and, therefore, has the potential to be used in various pollen monitoring stations.
http://ift.tt/2hTHw4P
Σφακιανάκης Αλέξανδρος
ΩτοΡινοΛαρυγγολόγος
Αναπαύσεως 5 Άγιος Νικόλαος
Κρήτη 72100
00302841026182
00306932607174
alsfakia@gmail.com
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