ena-STUDY-NATURALIS-06-06-2021-20:07:43:042-716
DNA metabarcoding of airborne pollen samples
Airborne pollen monitoring is of global socio-economic importance as it provides information on presence and prevalence of allergenic pollen in ambient air. Traditionally, this task has been performed by microscopic investigation, but novel techniques are being developed to automate this process. Among these, DNA metabarcoding has the highest potential of increasing the taxonomic resolution, but uncertainty exists about whether the results can be used to quantify pollen abundance. In this study, it is shown that DNA metabarcoding using trnL and nrITS2 provides highly improved taxonomic resolution in airborne pollen samples from the Netherlands. A total of 168 species from 143 genera and 56 plant families was recognized, while microscopic pollen counts identified 23 genera and 22 plant families. NrITS2 showed almost double the number of OTUs and much higher percentage of identifications to species level (80.1%) than trnL (27.6%). Furthermore, regressing relative read abundances from both markers against the relative abundances of microscopic pollen counts showed a better correlation for nrITS2 (R2 = 0.821) than for trnL (R2 = 0.620). Using three target taxa commonly encountered in early spring and fall in the Netherlands (Alnus sp., Cupressaceae/Taxaceae and Urticaceae) the nrITS2 results showed that these were dominated by single species (Alnus glutinosa/incana, Taxus baccata and Urtica dioica). Furthermore, perMANOVA analysis indicated spatiotemporal patterns that could be more clearly distinguished for all taxa using nrITS2 than trnL. These results indicate that nrITS2 should be the preferred marker of choice in molecular airborne pollen monitoring.
Airborne pollen monitoring is of global socio-economic importance as it provides information on presence and prevalence of allergenic pollen in ambient air. Traditionally, this task has been performed by microscopic investigation, but novel techniques are being developed to automate this process. Among these, DNA metabarcoding has the highest potential of increasing the taxonomic resolution, but uncertainty exists about whether the results can be used to quantify pollen abundance. In this study, it is shown that DNA metabarcoding using trnL and nrITS2 provides highly improved taxonomic resolution in airborne pollen samples from the Netherlands. A total of 168 species from 143 genera and 56 plant families was recognized, while microscopic pollen counts identified 23 genera and 22 plant families. NrITS2 showed almost double the number of OTUs and much higher percentage of identifications to species level (80.1%) than trnL (27.6%). Furthermore, regressing relative read abundances from both markers against the relative abundances of microscopic pollen counts showed a better correlation for nrITS2 (R2 = 0.821) than for trnL (R2 = 0.620). Using three target taxa commonly encountered in early spring and fall in the Netherlands (Alnus sp., Cupressaceae/Taxaceae and Urticaceae) the nrITS2 results showed that these were dominated by single species (Alnus glutinosa/incana, Taxus baccata and Urtica dioica). Furthermore, perMANOVA analysis indicated spatiotemporal patterns that could be more clearly distinguished for all taxa using nrITS2 than trnL. These results indicate that nrITS2 should be the preferred marker of choice in molecular airborne pollen monitoring.