[Characterizing Beijing's Airborne Bacterial Communities in PM2.5 and PM1 Samples During Haze Pollution Episodes Using 16S rRNA Gene Analysis Method]

Bu-ying Wang, Ji-dong Lang, Li-na Zhang, Jian-huo Fang, Chen Cao, Ji-ming Hao, Ting Zhu, Geng Tian, Jing-kun Jiang
Huan Jing Ke Xue= Huanjing Kexue 2015, 36 (8): 2727-34
During 8th-14th Jan., 2013, severe particulate matter (PM) pollution episodes happened in Beijing. These air pollution events lead to high risks for public health. In addition to various PM chemical compositions, biological components in the air may also impose threaten. Little is known about airborne microbial community in such severe air pollution conditions. PM2.5 and PM10 samples were collected during that 7-day pollution period. The 16S rRNA gene V3 amplification and the MiSeq sequencing were performed for analyzing these samples. It is found that there is no significant difference at phylum level for PM2.5 bacterial communities during that 7-day pollution period both at phylum and at genus level. At genus level, Arthrobacter and Frankia are the major airborne microbes presented in Beijing winter.samples. At genus level, there are 39 common genera (combined by first 50 genera bacterial of the two analysis) between the 16S rRNA gene analysis and those are found by Metagenomic analysis on the same PM samples. Frankia and Paracoccus are relatively more abundant in 16S rRNA gene data, while Kocuria and Geodermatophilus are relatively more abundant in Meta-data. PM10 bacterial communities are similar to those of PM2.5 with some noticeable differences, i.e., at phylum level, more Firmicutes and less Actinobacteria present in PM10 samples than in PM2.5 samples, while at genus level, more Clostridium presents in PM10 samples. The findings in Beijing were compared with three 16S rRNA gene studies in other countries. Although the sampling locations and times are different from each other, compositions of bacterial community are similar for those sampled at the ground atmosphere. Airborne microbial communities near the ground surface are different from those sampled in the upper troposphere.


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