The aerobiome uncovered: Multi-marker metabarcoding reveals potential drivers of turn-over in the full microbial community in the air

Environment International

卷:154

Liz Meulenbroek¹  Dennis R. Lammertsma²  Stefan Geisen²  Pieter A. Slim²  E.R. Jasper Wubs³  Ivo Laros⁴  Lars H. Hansen⁵  G. Arjen de Groot⁵  L. Basten Snoek⁵ 

[1] Corresponding author.;

[2] Research, PO Box 47, 6700 AA Wageningen, the Netherlands;

[3] Laboratory of Nematology, Wageningen University, 6700 AA Wageningen, the Netherlands;

[4] Sustainable Agroecosystems Group, Institute of Agricultural Sciences, Department of Environmental Systems Science, ETH Zürich, Universitätstrasse 2, 8092 Zürich, Switzerland;

[5] Wageningen Environmental Research, Wageningen University &

关键词: Aerobiome monitoring;    Microbiome;    Microbial dispersal;    Potential pathogens;    Early-warning system;    Meteorology;   

DOI  :  

来源: DOAJ

【 摘 要 】

Air is a major conduit for the dispersal of organisms at the local and the global scale. Most research has focused on the dispersal of plants, vertebrates and human disease agents. However, the air represents a key dispersal medium also for bacteria, fungi and protists. Many of those represent potential pathogens of animals and plants and have until now gone largely unrecorded. Here we studied the turnover in composition of the entire aerobiome, the collective diversity of airborne microorganisms. For that we performed daily analyses of all prokaryotes and eukaryotes (including plants) using multi-marker high-throughput sequencing for a total of three weeks. We linked the resulting communities to local weather conditions, to assess determinants of aerobiome composition and distribution. We observed hundreds of microbial taxa, mostly belonging to spore-forming organisms including fungi, but also protists. Additionally, we detected many potential human- and plant-pathogens. Community composition fluctuated on a daily basis and was linked to concurrent weather conditions, particularly air pressure and temperature. Using network analyses, we identified taxonomically diverse groups of organisms with correlated temporal dynamics. In part, this was due to co-variation with environmental conditions, while we could also detect specific host-parasite interactions. This study provides the first full inventory of the aerobiome and identifies putative drivers of its dynamics in terms of taxon composition. This knowledge can help develop early warning systems against pathogens and improve our understanding of microbial dispersal.

【 授权许可】

Unknown