Evidence map›Paper›PMID 25172855›Full record

ArticleApplied and environmental microbiology2014

Indoor-air microbiome in an urban subway network: diversity and dynamics.

Marcus H Y Leung, David Wilkins, Ellen K T Li, Fred K F Kong, Patrick K H Lee

Abstract read
In one paragraph

Article in Applied and environmental microbiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed, 2 pooled it
–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

76 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. The Indoor Microbiome: Sampling, Analysis and Emerging Trends.Environmental microbiology reports · 2026
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16 more citing papers are in PubMed but not listed here.

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

5 authors.

Marcus H Y LeungSchool of Energy and Environment, City University of Hong Kong, Hong Kong.ORCID http://orcid.org/0000-0002-6342-8181
David WilkinsSchool of Energy and Environment, City University of Hong Kong, Hong Kong.
Ellen K T LiSchool of Energy and Environment, City University of Hong Kong, Hong Kong.
Fred K F KongSchool of Energy and Environment, City University of Hong Kong, Hong Kong.
Patrick K H LeeSchool of Energy and Environment, City University of Hong Kong, Hong Kong patrick.kh.lee@cityu.edu.hk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Subway systems are indispensable for urban societies, but microbiological characteristics of subway aerosols are relatively unknown. Previous studies investigating microbial compositions in subways employed methodologies that underestimated the diversity of microbial exposure for commuters, with little focus on factors governing subway air microbiology, which may have public health implications. Here, a culture-independent approach unraveling the bacterial diversity within the urban subway network in Hong Kong is presented. Aerosol samples from multiple subway lines and outdoor locations were collected. Targeting the 16S rRNA gene V4 region, extensive taxonomic diversity was found, with the most common bacterial genera in the subway environment among those associated with skin. Overall, subway lines harbored different phylogenetic communities based on α- and β-diversity comparisons, and closer inspection suggests that each community within a line is dependent on architectural characteristics, nearby outdoor microbiomes, and connectedness with other lines. Microbial diversities and assemblages also varied depending on the day sampled, as well as the time of day, and changes in microbial communities between peak and nonpeak commuting hours were attributed largely to increases in skin-associated genera in peak samples. Microbial diversities within the subway were influenced by temperature and relative humidity, while carbon dioxide levels showed a positive correlation with abundances of commuter-associated genera. This Hong Kong data set and communities from previous studies conducted in the United States formed distinct community clusters, indicating that additional work is required to unravel the mechanisms that shape subway microbiomes around the globe.

Indexed as

Air MicrobiologyMicrobiotaRailroadsBacteriaCluster AnalysisDNA, RibosomalGenetic VariationHong KongMolecular Sequence DataPhylogenyRNA, Ribosomal, 16SSequence Analysis, DNADNA, RibosomalRNA, Ribosomal, 16S

Identifiers

PMID25172855
PMCPMC4249038

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.