ABSTRACT: The structural variation of the bacterial community associated with particulate matter (PM) was assessed in an urban area of Beijing during hazy and nonhazy days. Sampling for different PM fractions (PM2.5 [<2.5 ?m], PM10 [<10 ?m], and total suspended particulate) was conducted using three portable air samplers from September 2014 to February 2015. The airborne bacterial community in these samples was analyzed using the Illumina MiSeq platform with bacterium-specific primers targeting the 16S rRNA gene. A total of 1,707,072 reads belonging to 6,009 operational taxonomic units were observed. The airborne bacterial community composition was significantly affected by PM fractions (R = 0.157, P < 0.01). In addition, the relative abundances of several genera significantly differed between samples with various haze levels; for example, Methylobacillus, Tumebacillus, and Desulfurispora spp. increased in heavy-haze days. Canonical correspondence analysis and permutation tests showed that temperature, SO2 concentration, relative humidity, PM10 concentration, and CO concentration were significant factors that associated with airborne bacterial community composition. Only six genera increased across PM10 samples (Dokdonella, Caenimonas, Geminicoccus, and Sphingopyxis) and PM2.5 samples (Cellulomonas and Rhizobacter), while a large number of taxa significantly increased in total suspended particulate samples, such as Paracoccus, Kocuria, and Sphingomonas Network analysis indicated that Paracoccus, Rubellimicrobium, Kocuria, and Arthrobacter were the key genera in the airborne PM samples. Overall, the findings presented here suggest that diverse airborne bacterial communities are associated with PM and provide further understanding of bacterial community structure in the atmosphere during hazy and nonhazy days.IMPORTANCE The results presented here represent an analysis of the airborne bacterial community associated with particulate matter (PM) and advance our understanding of the structural variation of these communities. We observed a shift in bacterial community composition with PM fractions but no significant difference with haze levels. This may be because the bacterial differences are obscured by high bacterial diversity in the atmosphere. However, we also observed that a few genera (such as Methylobacillus, Tumebacillus, and Desulfurispora) increased significantly on heavy-haze days. In addition, Paracoccus, Rubellimicrobium, Kocuria, and Arthrobacter were the key genera in the airborne PM samples. Accurate and real-time techniques, such as metagenomics and metatranscriptomics, should be developed for a future survey of the relationship of airborne bacteria and haze.
