Evidence map›Paper›PMID 29079080›Full record

ArticleThe Science of the total environment2018

Analysis of airborne microbial communities using 16S ribosomal RNA: Potential bias due to air sampling stress.

Huajun Zhen, Valdis Krumins, Donna E Fennell, Gediminas Mainelis

Abstract read
In one paragraph

Article in The Science of the total environment, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.2field-weighted citation impact, top 15% of its field
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

9 citing papers in PubMed, 34 citations in OpenAlex.

  1. Article
  2. Advancing transcriptomic profiling of airborne bacteria.Applied and environmental microbiology · 2025
    Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Bioaerosol Sampling: Classical Approaches, Advances, and Perspectives.Aerosol science and technology : the journal of the American Association for Aerosol Research · 2020
    Article
  9. Article
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

4 authors at 1 institution in 1 country.

Huajun ZhenRutgers University, Department of Environmental Sciences, 14 College Farm Rd., New Brunswick, NJ 08901, United States.
Valdis KruminsRutgers University, Department of Environmental Sciences, 14 College Farm Rd., New Brunswick, NJ 08901, United States.
Donna E FennellRutgers University, Department of Environmental Sciences, 14 College Farm Rd., New Brunswick, NJ 08901, United States.
Gediminas MainelisRutgers University, Department of Environmental Sciences, 14 College Farm Rd., New Brunswick, NJ 08901, United States. Electronic address: mainelis@envsci.rutgers.edu.
Rutgers, The State University of New Jersey · US

Funding

Advanced Sampler for Measuring Exposure to Biological AerosolsR01OH009783 · OH · RUTGERS, THE STATE UNIV OF N.J. · PI HAN, TAEWON T, MAINELIS, GEDIMINAS · 2010 to 2018
$1.9M
ACL HHS R01OH009783NIOSH CDC HHS R01 OH009783
6 · The paper itself

Abstract

A limited number of studies have been conducted to analyze ribosomal RNA (rRNA, present in the ribosome) in bioaerosol samples to identify currently or potentially active airborne microbes, although its genomic counterpart, the rRNA gene (on the chromosome) has been frequently targeted for airborne microbial community analysis. A knowledge gap still exists regarding whether the bioaerosol rRNA abundances are affected by the bioaerosol collection process. We investigated the effect of air sampling stress on the measurement and characterization of 16S rRNA for bioaerosols in the laboratory and field experiments using quantitative polymerase chain reaction (qPCR) and high-throughput sequencing techniques. In a laboratory study, known quantities of freshly grown Escherichia coli cells were spiked onto the filter of a Button Aerosol Sampler and into liquids of BioSampler and SpinCon air samplers and then exposed to sampling stress when the samplers were operated for 2h. We found that the recovered cellular 16S rRNA abundance as determined by qPCR was dependent on sampler type. Further, two devices (Button Aerosol Sampler and BioSampler) that exhibited markedly different efficiency in preserving 16S rRNA were employed in an outdoor environment to collect bioaerosols simultaneously on eight days in two different seasons. The abundance of 16S rRNA in the outdoor air sample (1.3×10

Indexed as

Air MicrobiologyBiasAerosolsBacteriaRNA, Ribosomal, 16SSeasonsSpecimen HandlingAerosolsRNA, Ribosomal, 16S16S rRNA sequencingBioaerosolsMicrobial communityrRNA:rDNA ratioSampling deviceStress

Identifiers

PMID29079080
PMCPMC5805565
OpenAlexW2766685633

What OpenQuestion holds

Textmetadata
LicenceTDM
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.