Cite this article: Gao, J.F., Fan, X.Y., Li, H.Y. and Pan, K.L. (2017). Airborne Bacterial Communities of PM2.5 in Beijing-Tianjin-Hebei Megalopolis, China as Revealed By Illumina MiSeq Sequencing: A Case Study.
Aerosol Air Qual. Res.
17: 788-798. https://doi.org/10.4209/aaqr.2016.02.0087
HIGHLIGHTS
Bacteria of PM2.5 contained 1054 OTUs with mean number of 1.19 × 105 cell m–3 air.
Proteobacteria, Cyanobacteria and Actinobacteria were the three dominant bacterial phyla.
18 potential pathogens species (3.61% of total sequences) were detected in PM2.5.
Plants and soil are probably the main sources of bacteria of PM2.5 in BTH.
Environmental factors explained 81.83% of the variations in bacterial communities.
ABSTRACT
Bacteria are ubiquitous and abundant in the atmosphere and some of them are potential pathogens known to cause diseases or allergies in humans. However, the quantities and compositions of total airborne bacterial community and their relationships with environmental factors remain poorly investigated. Here, a case study of the total airborne bacteria of PM2.5 collected at six cities in Beijing-Tianjin-Hebei (BTH) megalopolis, China were profiled using quantitative polymerase chain reaction (qPCR) and Illumina MiSeq (PE300) sequencing. qPCR results showed the high abundance of total airborne bacteria of PM2.5 in BTH, ranging from 4.82 × 104 ± 1.58 × 103 to 2.64 × 105 ± 9.63 × 104 cell m–3 air, and averaged 1.19 × 105 cell m–3 air. The six PM2.5 samples were classified into three groups. Proteobacteria, Cyanobacteria, Actinobacteria and Firmicutes were the four dominant phyla of PM2.5. 18 common potential pathogens with extremely low percentage (3.61%) were observed, which were dominated by Enterococcus faecium and Escherichia coli. Plants and soil are probably the main sources of bacteria in PM2.5, as suggested by the high percentages of Chloroplast, plant-associated bacteria (e.g., Rhizobiales and Sphingomonadales) and soil-inhabiting bacteria (e.g., Burkholderiales and Pseudomonadales). Variation partitioning analysis (VPA) indicated that the atmospheric pollutants explained the most of the variation (31.90%) in community structure of PM2.5, followed by meteorological conditions (15.73%) and the chemical compositions of PM2.5 (11.32%). The case study furthers our understanding of the diversity and composition of airborne bacterial communities of PM2.5 in BTH, and also identified the main factors shaping the bacterial communities.
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