The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Inhalable Microorganisms in Beijing’s PM2.5 and PM10 Pollutants during a Severe Smog Event
Open accessAbstract
Particulate matter (PM) air pollution poses a formidable public health threat to the city of Beijing. Among the various hazards of PM pollutants, microorganisms in PM2.5 and PM10 are thought to be responsible for various allergies and for the spread of respiratory diseases. While the physical and chemical properties of PM pollutants have been extensively studied, much less is known about the inhalable microorganisms. Most existing data on airborne microbial communities using 16S or 18S rRNA gene sequencing to categorize bacteria or fungi into the family or genus levels do not provide information on their allergenic and pathogenic potentials. Here we employed metagenomic methods to analyze the microbial composition of Beijing's PM pollutants during a severe January smog event. We show that with sufficient sequencing depth, airborne microbes including bacteria, archaea, fungi, and dsDNA viruses can be identified at the species level. Our results suggested that the majority of the inhalable microorganisms were soil-associated and nonpathogenic to human. Nevertheless, the sequences of several respiratory microbial allergens and pathogens were identified and their relative abundance appeared to have increased with increased concentrations of PM pollution. Our findings may serve as an important reference for environmental scientists, health workers, and city planners.
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Cites
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Self-citationGreengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB
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A metagenome-wide association study of gut microbiota in type 2 diabetes
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Comunian, S., Dongo, D., Milani, C., & Palestini, P. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17124487 · Cited by 464
Review on recent progress in observations, source identifications and countermeasures of PM2.5
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Wang, Y., Zhang, Q., Jiang, J., Zhou, W., Wang, B., He, K., Duan, F., Zhang, Q., Philip, S., & Xie, Y. (2014) · Journal of Geophysical Research: Atmospheres · doi:10.1002/2013jd021426 · Cited by 366
Self-citationAn evaluation of the accuracy and speed of metagenome analysis tools
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Dynamic Human Environmental Exposome Revealed by Longitudinal Personal Monitoring
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Bourdrel, T., Annesi-Maesano, I., Alahmad, B., Maesano, C. N., & Bind, M.-A. (2021) · European Respiratory Review · doi:10.1183/16000617.0242-2020 · Cited by 224
SARS-CoV-2 infection, COVID-19 pathogenesis, and exposure to air pollution: What is the connection?
Woodby, B., Arnold, M. M., & Valacchi, G. (2021) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.14512 · Cited by 160
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Atmospheric antibiotic resistome driven by air pollutants
Gao, M., Zhang, Q., Lei, C., Lu, T., & Qian, H. (2023) · Science of The Total Environment · doi:10.1016/j.scitotenv.2023.165942 · Cited by 33
Lai, A., Chang, M. L., O'Donnell, R. P., Zhou, C., Sumner, J. A., & Hsiai, T. K. (2021) · Science of The Total Environment · doi:10.1016/j.scitotenv.2021.146464 · Cited by 25
Metadata
- Authors
- Cao, C., Jiang, W., Wang, B., Fang, J., Lang, J., Tian, G., Jiang, J., & Zhu, T. F.
- Venue
- Environmental Science & Technology
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-01-23
- Volume
- 48
- Issue
- 3
- Pages
- 1499-1507
- ISSN
- 0013-936X (ISSN-L)
- 1520-5851
- OpenAlex
- W127352138
- Cited by
- 669
- References
- 7
- FWCI
- 25.79
- Type
- journal article
- Language
- en
- Open access
- hybrid
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