Evidence map›Paper›PMID 41555453›Full record

ArticleMicrobiome2026

Spatial and temporal patterns of public transit aerobiomes.

Russell J S Orr, Ola Brynildsrud, Kari O Bøifot, Jostein Gohli, Gunnar Skogan, Frank J Kelly, Mark T Hernandez, Klas Udekwu, Patrick K H Lee, Christopher E Mason and 1 more

Abstract read
In one paragraph

Article in Microbiome, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Russell J S Orr *Total Defence Division, Norwegian Defence Research Establishment FFI, Kjeller, Norway. russell-john-scott.orr@ffi.no.
Ola Brynildsrud *Total Defence Division, Norwegian Defence Research Establishment FFI, Kjeller, Norway.
Kari O BøifotTotal Defence Division, Norwegian Defence Research Establishment FFI, Kjeller, Norway.
Jostein GohliTotal Defence Division, Norwegian Defence Research Establishment FFI, Kjeller, Norway.
Gunnar SkoganTotal Defence Division, Norwegian Defence Research Establishment FFI, Kjeller, Norway.
Frank J KellyEnvironmental Research Group, School of Public Health, Imperial College London, London, UK.
Mark T HernandezEnvironmental Engineering Program, College of Engineering and Applied Science, University of Colorado, Boulder, CO, USA.
Klas UdekwuDepartment of Biological Sciences, Bioinformatics and Computational Biology Program, University of Idaho, Moscow, ID, USA.
Patrick K H LeeSchool of Energy and Environment and State Key Laboratory of Marine Pollution, City University of Hong Kong, Hong Kong SAR, China.
Christopher E MasonDepartment of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.
Marius DybwadTotal Defence Division, Norwegian Defence Research Establishment FFI, Kjeller, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAerobiome diversity is extensive; however, species-level community structure remains poorly resolved. Likewise, microbiomes of public transit systems are of public interest due to their importance for health, though few studies have focused on these ecosystems whilst utilising shotgun metagenomics. Aerosol studies have focused predominantly on individual cities, with limited between-city comparisons suggesting specific community structures. Longitudinal studies show aerobiome diversity as dynamic, fluctuating during seasonal and daily cycles, though interannual cycles remains to be considered. Further, a bacterial bias has limited fungal aerobiome studies, with few considering both fractions collectively. As such, the objective of this study was to examine spatial and temporal patterns in the species diversity of public transit aerobiomes, with an emphasis on bacteria and fungi.

resultsAir samples taken over a 3-year period (2017-2019) from six global cities were subjected to shotgun metagenomic sequencing. Improved classification databases, notably for fungi, applying stringent parameters for trimming, exogenous contamination removal and classification yielded high species-level resolution. Microbial diversity varied substantially among cities, while human and environmental factors, recorded in parallel, were of secondary significance. Bacteria dominated the public transit aerobiome with increased presence in cities with higher population densities. All aerobiomes had complex compositions, consisting of hundreds to thousands of species. Interannual variation had limited significance on the public transit aerobiome diversity and community structure.

conclusionsCities were the most important factor contributing to diversity and community structure, demonstrating specific bacterial and fungal signatures. Further, possible correlation between geographical distance and genetic signatures of aerobiomes is suggested. Bacteria are the most abundant constituent of public transit aerobiomes, though no single species is globally dominant, conversely indicating a large inter-city variation in community structure. The presence of a ubiquitous global species core is rejected, though an aerobiome sub-core is confirmed. For the first time, local public transit aerobiome cores are presented for each city and related to ecological niches. Further, the importance of a robust bioinformatics analysis pipeline to identify and remove exogenous contaminants for studying low-biomass samples is highlighted. Lastly, a core and sub-core definition of contaminant aerobiome species with taxon tables, to facilitate future environmental studies, is presented. Video Abstract.

Indexed as

Air MicrobiologyBacteriaFungiMicrobiotaAerosolsBiodiversityCitiesHumansMetagenomicsSeasonsShotgun SequencingSpatio-Temporal AnalysisAerosolsAerosolBacteriaFungiLow-biomassMicrobiomeShotgun

Identifiers

PMID41555453
PMCPMC12896060

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.