Aerobiological Monitoring and Metabarcoding of Grass Pollen

Grass pollen is one of the leading causes of pollinosis, affecting 10-30% of the world's population. The allergenicity of pollen from different Poaceae species is not the same and is estimated from moderate to high. Aerobiological monitoring is a standard method that allows one to track and predict the dynamics of allergen concentration in the air. Poaceae is a stenopalynous family, and thus grass pollen can usually be identified only at the family level with optical microscopy. Molecular methods, in particular the DNA barcoding technique, can be used to conduct a more accurate analysis of aerobiological samples containing the DNA of various plant species. This study aimed to test the possibility of using the ITS1 and ITS2 nuclear loci for determining the presence of grass pollen from air samples via metabarcoding and to compare the analysis results with the results of phenological observations. Based on the high-throughput sequencing data, we analyzed the changes in the composition of aerobiological samples taken in the Moscow and Ryazan regions for three years during the period of active flowering of grasses. Ten genera of the Poaceae family were detected in airborne pollen samples. The representation for most of them for ITS1 and ITS2 barcodes was similar. At the same time, in some samples, the presence of specific genera was characterized by only one sequence: either ITS1 or ITS2. Based on the analysis of the abundance of both barcode reads in the samples, the following order could describe the change with time in the dominant species in the air: Poa, Alopecurus, and Arrhenatherum in early mid-June, Lolium, Bromus, Dactylis, and Briza in mid-late June, Phleum, Elymus in late June to early July, and Calamagrostis in early mid-July. In most samples, the number of taxa found via metabarcoding analysis was higher compared to that in the phenological observations. The semi-quantitative analysis of high-throughput sequencing data well reflects the abundance of only major grass species at the flowering stage.

Automated summary

Grass pollen is a major cause of allergies, affecting 10-30% of the global population. Aerobiological monitoring allows for tracking and predicting allergen concentrations in the air. This study used high-throughput sequencing data to analyze the composition changes in grass pollen samples from Moscow and Ryazan regions over three years. The results showed that metabarcoding analysis detected a greater number of taxa compared to phenological observations, and semi-quantitative analysis reflected the abundance of major grass species during flowering.