Characteristics of bacterial community in cloud water at Mt Tai: similarity and disparity under polluted and non-polluted cloud episodes

• Main Authors: M. Wei, C. Xu, J. Chen, C. Zhu, J. Li, G. Lv
• Format: Article
• Language: English
• Published: Copernicus Publications 2017-04-01
• Series: Atmospheric Chemistry and Physics
• Online Access: http://www.atmos-chem-phys.net/17/5253/2017/acp-17-5253-2017.pdf

Bacteria are widely distributed in atmospheric aerosols and are indispensable components of clouds, playing an important role in the atmospheric hydrological cycle. However, limited information is available about the bacterial community structure and function, especially for the increasing air pollution in the North China Plain. Here, we present a comprehensive characterization of bacterial community composition, function, variation, and environmental influence for cloud water collected at Mt Tai from 24 July to 23 August 2014. Using Miseq 16S rRNA gene sequencing, the highly diverse bacterial community in cloud water and the predominant phyla of Proteobacteria, Bacteroidetes, Cyanobacteria, and Firmicutes were investigated. Bacteria that survive at low temperature, radiation, and poor nutrient conditions were found in cloud water, suggesting adaption to an extreme environment. The bacterial gene functions predicted from the 16S rRNA gene using the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) suggested that the pathways related to metabolism and disease infections were significantly correlated with the predominant genera. The abundant genera <i>Acinetobacter</i>, <i>Stenotrophomonas</i>, <i>Pseudomonas</i>, and <i>Empedobacter</i> originated from a wide range of habitats including cloud condensation nuclei and ice nuclei active species, opportunistic pathogens, and functional species, demonstrating the importance of ecology and health in cloud water. Cluster analysis including hierarchical cluster (Hcluster) and principal coordinate analysis (PCoA) indicated a significant disparity between polluted and non-polluted samples. Linear discriminant analysis effect size (LEfSe) demonstrated that potential pathogens were enriched in the polluted cloud samples, whereas the diverse ecological function groups were significant in the non-polluted samples. Discrepant community structure determined by redundancy analysis (RDA) indicated that the major ions in cloud water and PM_2. 5 in the atmosphere have a negative impact on bacteria, playing a vital role in shaping microbial community structure. The major ions might provide nutrition to bacteria and directly influence the bacterial community, whereas PM_2. 5 in air has an indirect impact on bacterial community structure. During wet deposition, soluble particulate matter was dissolved in water droplets resulting in elevated concentration in cloud water. PM_2. 5 was possibly associated with different origins and pathways of air mass as determined using source tracking by the backward trajectory, mainly related to long-range transport. This work enhanced our understanding of the characteristics of bacterial ecology in the atmospheric aqueous phase, highlighting the potential influence of environmental variables on the bacterial community in cloud processes. It may provide fundamental information of the bacterial community response in cloud water under increasing pollution. However, due to the limited sample size (13 samples) collected at the summit of Mt Tai, these issues need in-depth discussion. Further studies based on an annual series of field observation experiments and laboratory simulations will continue to track these issues.