Evidence map›Paper›PMID 37384659›Full record

ArticlePloS one2023

AirDNA sampler: An efficient and simple device enabling high-yield, high-quality airborne environment DNA for metagenomic applications.

Piyanun Harnpicharnchai, Panyapon Pumkaeo, Paopit Siriarchawatana, Somsak Likhitrattanapisal, Sermsiri Mayteeworakoon, Lily Ingsrisawang, Worawongsin Boonsin, Lily Eurwilaichitr, Supawadee Ingsriswang

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. 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
3.3field-weighted citation impact, top 8% 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, 21 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Piyanun HarnpicharnchaiNational Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Khlong Luang, Pathum Thani, Thailand.
Panyapon PumkaeoNational Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Khlong Luang, Pathum Thani, Thailand.
Paopit SiriarchawatanaNational Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Khlong Luang, Pathum Thani, Thailand.
Somsak LikhitrattanapisalNational Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Khlong Luang, Pathum Thani, Thailand.ORCID 0000-0003-0824-722X
Sermsiri MayteeworakoonNational Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Khlong Luang, Pathum Thani, Thailand.
Lily IngsrisawangDepartment of Statistics, Faculty of Science, Kasetsart University, Chatuchak, Bangkok, Thailand.
Worawongsin BoonsinNational Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Khlong Luang, Pathum Thani, Thailand.
Lily EurwilaichitrNational Energy Technology Center, National Science and Technology Development Agency, Khlong Luang, Pathum Thani, Thailand.
Supawadee IngsriswangNational Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Khlong Luang, Pathum Thani, Thailand.ORCID 0000-0002-3183-5997
National Science and Technology Development Agency · THKasetsart University · TH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Analyzing temporal and spatial distributions of airborne particles of biological origins is vital for the assessment and monitoring of air quality, especially with regard to public health, environmental ecology, and atmospheric chemistry. However, the analysis is frequently impeded by the low levels of biomass in the air, especially with metagenomic DNA analysis to explore diversity and composition of living organisms and their components in the air. To obtain sufficient amounts of metagenomic DNA from bioaerosols, researchers usually need a long sampling time with an expensive high-volume air sampler. This work shows the utilization of an air sampling device containing an economical, high-volume portable ventilation fan in combination with customized multi-sheet filter holders to effectively obtain high yields of genomic DNA in a relatively short time. The device, named 'AirDNA' sampler, performed better than other commercial air samplers, including MD8 Airport and Coriolis compact air samplers. Using the AirDNA sampler, an average DNA yield of 40.49 ng (12.47-23.24 ng at 95% CI) was obtained in only 1 hour of air sampling with a 0.85 probability of obtaining ≥10 ng of genomic DNA. The genomic DNA obtained by the AirDNA system is of suitable quantity and quality to be further used for amplicon metabarcoding sequencing of 16S, 18S, and cytochrome c oxidase I (COI) regions, indicating that it can be used to detect various prokaryotes and eukaryotes. Our results showed the effectiveness of our AirDNA sampling apparatus with a simple setup and affordable devices to obtain metagenomic DNA for short-term or long-term spatiotemporal analysis. The technique is well suited for monitoring air in built environments, especially monitoring bioaerosols for health purposes and for fine-scale spatiotemporal environmental studies.

Indexed as

DNA, EnvironmentalAirportsBiomassBuilt EnvironmentMetagenomicsDNA, Environmental

Identifiers

PMID37384659
PMCPMC10309600
OpenAlexW4382632526

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.