Diversity and Composition of Airborne Fungal Community Associated with Particulate Matters in Beijing during Haze and Non-haze Days - Yan, Dong; Zhang, Tao; Su, Jing; Zhao, Li-Li; Wang, Hao; Fang, Xiao-Mei; Zhang, Yu-Qin; Liu, Hong-Yu; Yu, Li-Yan (Frontiers in Microbiology, 2016)
To assess the diversity and composition of airborne fungi associated with particulate matters (PMs) in Beijing, China, a total of 81 PM samples were collected, which were derived from PM2.5, PM10 fractions, and total suspended particles during haze and non-haze days. The airborne fungal community in these samples was analyzed using the Illumina Miseq platform with fungi-specific primers targeting the internal transcribed spacer 1 region of the large subunit rRNA gene. A total of 797,040 reads belonging to 1633 operational taxonomic units were observed. Of these, 1102 belonged to Ascomycota, 502 to Basidiomycota, 24 to Zygomycota, and 5 to Chytridiomycota. The dominant orders were Pleosporales (29.39%), Capnodiales (27.96%), Eurotiales (10.64%), and Hypocreales (9.01%). The dominant genera were Cladosporium, Alternaria, Fusarium, Penicillium, Sporisorium, and Aspergilus. Analysis of similarities revealed that both particulate matter sizes (R = 0.175, p = 0.001) and air quality levels (R = 0.076, p = 0.006) significantly affected the airborne fungal community composition. The relative abundance of many fungal genera was found to significantly differ among various PM types and air quality levels. Alternaria and Epicoccum were more abundant in total suspended particles samples, Aspergillus in heavy-haze days and PM2.5 samples, and Malassezia in PM2.5 samples and heavy-haze days. Canonical correspondence analysis and permutation tests showed that temperature (p < 0.01), NO2 (p < 0.01), PM10 (p < 0.01), SO2(p < 0.01), CO (p < 0.01), and relative humidity (p < 0.05) were significant factors that determine airborne fungal community composition. The results suggest that diverse airborne fungal communities are associated with particulate matters and may provide reliable data for studying the responses of human body to the increasing level of air pollution in Beijing.