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dc.contributor.authorGohli, Josteinen_GB
dc.contributor.authorBøifot, Kari Olineen_GB
dc.contributor.authorMoen, Line Victoriaen_GB
dc.contributor.authorPastuszek, Paulinaen_GB
dc.contributor.authorSkogan, Gunnaren_GB
dc.contributor.authorUdekwu, Klas Ien_GB
dc.contributor.authorDybwad, Mariusen_GB
dc.date.accessioned2021-03-11T08:36:33Z
dc.date.accessioned2021-03-22T10:01:12Z
dc.date.available2021-03-11T08:36:33Z
dc.date.available2021-03-22T10:01:12Z
dc.date.issued2019-12-19
dc.identifier.citationGohli J, Bøifot KO, Moen LV, Pastuszek, Skogan G, Udekwu, Dybwad M. The subway microbiome: Seasonal dynamics and direct comparison of air and surface bacterial communities. Microbiome. 2019;7(1)en_GB
dc.identifier.urihttp://hdl.handle.net/20.500.12242/2858
dc.descriptionGohli, Jostein; Bøifot, Kari Oline; Moen, Line Victoria; Pastuszek, Paulina; Skogan, Gunnar; Udekwu, Klas I; Dybwad, Marius. The subway microbiome: Seasonal dynamics and direct comparison of air and surface bacterial communities. Microbiome 2019 ;Volum 7.(1)en_GB
dc.description.abstractBackground Mass transit environments, such as subways, are uniquely important for transmission of microbes among humans and built environments, and for their ability to spread pathogens and impact large numbers of people. In order to gain a deeper understanding of microbiome dynamics in subways, we must identify variables that affect microbial composition and those microorganisms that are unique to specific habitats. Methods We performed high-throughput 16S rRNA gene sequencing of air and surface samples from 16 subway stations in Oslo, Norway, across all four seasons. Distinguishing features across seasons and between air and surface were identified using random forest classification analyses, followed by in-depth diversity analyses. Results There were significant differences between the air and surface bacterial communities, and across seasons. Highly abundant groups were generally ubiquitous; however, a large number of taxa with low prevalence and abundance were exclusively present in only one sample matrix or one season. Among the highly abundant families and genera, we found that some were uniquely so in air samples. In surface samples, all highly abundant groups were also well represented in air samples. This is congruent with a pattern observed for the entire dataset, namely that air samples had significantly higher within-sample diversity. We also observed a seasonal pattern: diversity was higher during spring and summer. Temperature had a strong effect on diversity in air but not on surface diversity. Among-sample diversity was also significantly associated with air/surface, season, and temperature. Conclusions The results presented here provide the first direct comparison of air and surface bacterial microbiomes, and the first assessment of seasonal variation in subways using culture-independent methods. While there were strong similarities between air and surface and across seasons, we found both diversity and the abundances of certain taxa to differ. This constitutes a significant step towards understanding the composition and dynamics of bacterial communities in subways, a highly important environment in our increasingly urbanized and interconnect world.en_GB
dc.language.isoenen_GB
dc.subjectBakterieren_GB
dc.subjectUndergrunnsbaneren_GB
dc.titleThe subway microbiome: Seasonal dynamics and direct comparison of air and surface bacterial communitiesen_GB
dc.typeArticleen_GB
dc.date.updated2021-03-11T08:36:33Z
dc.identifier.cristinID1797732
dc.identifier.doi10.1186/s40168-019-0772-9
dc.source.issn2049-2618
dc.type.documentJournal article
dc.relation.journalMicrobiome


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