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Efficient and sensitive identification and quantification of airborne pollen using next-generation DNA sequencing

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Abstract

Pollen monitoring is an important and widely used tool in allergy research and creation of awareness in pollen-allergic patients. Current pollen monitoring methods are microscope-based, labour intensive and cannot identify pollen to the genus level in some relevant allergenic plant groups. Therefore, a more efficient, cost-effective and sensitive method is needed. Here, we present a method for identification and quantification of airborne pollen using DNA sequencing. Pollen is collected from ambient air using standard techniques. DNA is extracted from the collected pollen, and a fragment of the chloroplast gene trnL is amplified using PCR. The PCR product is subsequently sequenced on a next-generation sequencing platform (Ion Torrent). Amplicon molecules are sequenced individually, allowing identification of different sequences from a mixed sample. We show that this method provides an accurate qualitative and quantitative view of the species composition of samples of airborne pollen grains. We also show that it correctly identifies the individual grass genera present in a mixed sample of grass pollen, which cannot be achieved using microscopic pollen identification. We conclude that our method is more efficient and sensitive than current pollen monitoring techniques and therefore has the potential to increase the throughput of pollen monitoring.

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