The diversity and seasonality of the indoor mycobiome

Buildings harbor unique and complex microbial communities, including fungi. From earlier work, we know that indoor fungal communities, the indoor mycobiome, can vary significantly in different geographic regions and in different seasons. However, more baseline information about the indoor mycobiome is necessary for improved indoor air quality and for identification of tentative health risks. This thesis aims to improve our understanding about the indoor mycobiome in Norway. One approach to investigate the indoor mycobiome composition is DNA metabarcoding, which is based on high throughput sequencing (HTS) of amplified markers. Ideally, the amplified marker will discriminate among species. The rDNA ITS region is the recognized barcoding region for fungi, and the ITS1 or ITS2 regions are the most commonly used markers for fungal DNA metabarcoding studies. In this thesis, ITS2 was used during the DNA metabarcoding analyses of all four papers. However, the ITS region may include considerable intraspecific variation. This variation can lead to over-splitting of species during DNA metabarcoding analyses. In Paper I, we assessed the effects of intraspecific sequence variation in DNA metabarcoding by analyzing local populations of eleven fungal species. All the eleven species, except one, included some level of intraspecific variation in the ITS2 region. The presence of this intraspecific variation in ITS2 suggest that clustering is needed to approach species‐level resolution in metabarcoding studies of fungal communities. In order to improve the knowledge of the indoor mycobiome, we analysed fungal communities in indoor environments associated with private homes (Paper II) and daycare centers (Paper III) at large geographic scales in Norway using a citizen science approach. Dust samples were collected from doorframes from 125 daycares and 271 private homes in three different house compartments: outside the building (main entrance), living room and bathroom. The fungal community composition and diversity were determined by DNA metabarcoding. The fungal community composition was clearly different between indoor and outdoor samples in both daycares and private homes, but there were no marked differences between the two indoor compartments in either of the studies. The fungal richness and compositional variation could be ascribed to numerous indoor and outdoor variables, and there was a clear geographic signal in the indoor mycobiome composition that mirrored the outdoor climate. In both studies, the indoor mycobiomes represent a mixture of fungi from both indoor and outdoor sources. In the daycares, the indoor mycobiomes included considerably more yeasts and molds compared to the outdoor, with Saccharomycetales as the dominant fungal order. In the private homes, the mycobiomes were mainly dominated by molds from the fungal orders Capnodiales and Eurotiales. The observed differences between the daycares and private homes may be due to the large number of occupants, and children in particular, in the daycares. Finally, we investigated the spatiotemporal dynamics of the indoor mycobiomes in two daycare centers (Paper IV). Dust samples were collected throughout a year in order to evaluate indoor air quality, and the effect of occupancy and seasonality. We collected dust samples from different rooms and analyzed their mycobiomes using DNA metabarcoding. The fungal community composition in rooms with limited occupancy was different from rooms with high occupancy and more similar to the outdoor samples. A strong seasonal pattern was observed in the mycobiome composition, mainly structured by the outdoor weather conditions. Therefore, the temporal variability should be accounted for in indoor mycobiome studies and in evaluations of indoor air quality.