Computational analysis of bioaerosol : the analysis of molecular genetic datasets in context of environmental factors

From an ecological perspective, primary biological aerosol particles (PBAP) play a central role in the spread and reproduction of many organisms. Many pathogens of plants and humans, as well as allergens, spread through the atmosphere. They can be highly efficient ice nuclei, potentially influencing the hydrological cycle and global energy budget. Despite the farreaching influences in ecology, agriculture, human health and climate, the spatial and temporal dynamics in composition and abundancy of PBAP are not well characterised. In this thesis, the atmospheric diversity and abundancies of heterogeneous types of PBAP are investigated. For this, data science methods are utilised to programmatically process and analyse complex data structures within a database system. The focus is on Sanger, NGS and quantitative PCR datasets of the highly allergenic plants, ragweed and mugwort, plant pathogenic oomycetes, fungi and prokaryotic archaea. A novel insight into the fine fraction (<3 μm) concentrations of mugwort and ragweed revealed higher concentrations of ragweed despite it being far less abundant in the local flora. Wind back trajectory analysis point to pollen-rupture during long-range transport from the Mediterranean, which also may explain the higher allergenic potential of ragweed compared to mugwort. Both fungi and oomycetes diversity displayed high seasonal dynamics. Average temperature, more than close temporal vicinity, led to similar compositions. Similar tendencies in the abundancies of different oomycetes taxa indicate the same factors influencing atmospheric occurrence. For fungi independent communities were identified on coarse and fine filter samples. Patterns in the temporal and size fraction occurrences of the most abundant taxa allowed the identification of sporulation strategies amongst fungi with similar lifestyles. Comparison of Archaea datasets from continental and marine air samples revealed higher proportions of the soil-associated Thaumarchaeota in continental samples (86% vs 60%) and increase of Euryarchaeota in marine samples (40% vs 14%). Thaumarchaeota and methanogenic Euryarchaeota peaked late in the year, presumably due to increased emissions from bare soil and fertilisation on agricultural land. These results provide new information and insights into the dynamics of PBAP which can be beneficial for diverse fields such as atmospheric, agricultural and medical sciences.Aus ökologischer Sicht spielen Primäre Biologische Aerosolpartikel (PBAP) eine zentrale Rolle bei der Verbreitung und Vermehrung vieler Organismen. Viele Pflanzen- und Humanpathogene, wie auch Allergene, sind in der Atmosphäre präsent. Als effiziente Eiskeime könnten PBAP einen Einfluss auf den Wasserzyklus und globalen Energiehaushalt haben. Trotz der weitreichenden potenziellen Einflüsse, sind die räumlichen und zeitlichen Dynamiken in Zusammensetzung und Vielfalt nur unzureichend charakterisiert. In dieser Arbeit werden atmosphärische Diversität und Abundanzen heterogener Typen von PBAP untersucht. Hierbei werden Methoden der data science eingesetzt um programmatisch komplexe Datenstrukturen innerhalb eines Datenbanksystems zu prozessieren und analysieren. Der Fokus liegt auf Sanger- NGS- und quantitativen PCR Datensätzen von Oomyceten, Fungi, Archaea und den Allergenen Pflanzen Ambrosia und Artemisia. Neue Einblicke in die Feinstaubkonzentrationen (