Published in

MDPI, Atmosphere, 8(11), p. 802, 2020

DOI: 10.3390/atmos11080802

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Airborne Bacterial and Eukaryotic Community Structure across the United Kingdom Revealed by High-Throughput Sequencing

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Primary biological aerosols often include allergenic and pathogenic microorganisms posing potential risks to human health. Moreover, there are airborne plant and animal pathogens that may have ecological and economic impact. In this study, we used high-throughput sequencing techniques (Illumina, MiSeq) targeting the 16S rRNA genes of bacteria and the 18S rRNA genes of eukaryotes, to characterize airborne primary biological aerosols. We used a filtration system on the UK Facility for Airborne Atmospheric Measurements (FAAM) research aircraft to sample a range of primary biological aerosols across southern England overflying surface measurement sites from Chilbolton to Weybourne. We identified 30 to 60 bacterial operational taxonomic units (OTUs) and 108 to 224 eukaryotic OTUs per sample. Moreover, 16S rRNA gene sequencing identified significant numbers of genera that have not been found in atmospheric samples previously or only been described in limited number of atmospheric field studies, which are rather old or published in local journals. This includes the genera Gordonia, Lautropia, and Psychroglaciecola. Some of the bacterial genera found in this study include potential human pathogens, for example, Gordonia, Sphingomonas, Chryseobacterium, Morganella, Fusobacterium, and Streptococcus. 18S rRNA gene sequencing showed Cladosporium to be the major genus in all of the samples, which is a well-known allergen and often found in the atmosphere. There were also genetic signatures of potentially allergenic taxa; for example, Pleosporales, Phoma, and Brassicales. Although there was no significant clustering of bacterial and eukaryotic communities depending on the sampling location, we found meteorological factors explaining significant variations in the community composition. The findings in this study support the application of DNA-based sequencing technologies for atmospheric science studies in combination with complementary spectroscopic and microscopic techniques for improved identification of primary biological aerosols.