Integrated eDNA metabarcoding and morphological analyses assess spatio-temporal patterns of airborne fungal spores

Abstract

Fungi represent relevant allergens and plant pathogens that can disperse on long ranges, potentially producing severe consequences on public health and agriculture. Up to 11% of the bioaerosol particles are fungal spores and mycelium fragments. Estimation of fungal species diversity in time and space is decisive but may be biased by abiotic conditions and sampling methods. Traditional morphological analyses of fungal spores have been widely applied in aerobiology in the past, while recently eDNA metabarcoding can complement these studies. Here, we used both morphological analysis (spore count and taxon identification) and high-throughput sequencing to disentangle spatio-temporal variation of fungi across Northern and Central Italy and to evaluate the detection efficiency of the two approaches. Our results showed that eDNA metabarcoding detects about three times more genera and has a higher detection efficiency than the morphological analyses. However, the efficiency is high in both spore count and eDNA metabarcoding methods when the most abundant or the rarest genera are considered but it can substantially vary between the two approaches when moderately abundant genera are analyzed. Furthermore, morphological spore determination resulted in higher variance explained by PERMANOVA analysis with respect to eDNA metabarcoding (26% and 13%, respectively), which leads to a better spatio-temporal characterization of the fungal genera. As both morphological analyses and eDNA metabarcoding methods capture significant interactions between seasons and sites, they could be preferably used as complementing approaches to reliably study airborne fungal diversity and variation.

Keywords

• Aerobiology
• Co-correspondence analysis
• Detection efficiency
• Next-generation sequencing
• Sampling
• Species diversity