Evidence map›Paper›PMID 31412780›Full record

ArticleBMC microbiology2019

Laboratory contamination in airway microbiome studies.

Christine Drengenes, Harald G Wiker, Tharmini Kalananthan, Eli Nordeide, Tomas M L Eagan, Rune Nielsen

Abstract read
In one paragraph

Article in BMC microbiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 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

35 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. The Human Respiratory Microbiome: Current Understandings and Future Directions.American journal of respiratory cell and molecular biology · 2023
    Pooled it
  2. Review
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  14. E-Cigarette Use, Cigarette Smoking, and Sex Are Associated With Nasal Microbiome Dysbiosis.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2024
    Article
  15. Article
  16. Sample Collection Methods in Upper Gastrointestinal Research.Journal of Korean medical science · 2023
    Review
  17. Article
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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

6 authors.

Christine DrengenesDepartment of Thoracic Medicine, Haukeland University Hospital, Bergen, Norway. Christine.Drengenes@gmail.com.ORCID 0000-0003-4012-5492
Harald G WikerDepartment of Clinical Science, Faculty of Medicine, University of Bergen, Bergen, Norway.
Tharmini KalananthanDepartment of Microbiology, Haukeland University Hospital, Bergen, Norway.
Eli NordeideDepartment of Thoracic Medicine, Haukeland University Hospital, Bergen, Norway.
Tomas M L EaganDepartment of Thoracic Medicine, Haukeland University Hospital, Bergen, Norway.
Rune NielsenDepartment of Thoracic Medicine, Haukeland University Hospital, Bergen, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe low bacterial load in samples acquired from the lungs, have made studies on the airway microbiome vulnerable to contamination from bacterial DNA introduced during sampling and laboratory processing. We have examined the impact of laboratory contamination on samples collected from the lower airways by protected (through a sterile catheter) bronchoscopy and explored various in silico approaches to dealing with the contamination post-sequencing. Our analyses included quantitative PCR and targeted amplicon sequencing of the bacterial 16S rRNA gene.

resultsThe mean bacterial load varied by sample type for the 23 study subjects (oral wash>1st fraction of protected bronchoalveolar lavage>protected specimen brush>2nd fraction of protected bronchoalveolar lavage; p < 0.001). By comparison to a dilution series of know bacterial composition and load, an estimated 10-50% of the bacterial community profiles for lower airway samples could be traced back to contaminating bacterial DNA introduced from the laboratory. We determined the main source of laboratory contaminants to be the DNA extraction kit (FastDNA Spin Kit). The removal of contaminants identified using tools within the Decontam R package appeared to provide a balance between keeping and removing taxa found in both negative controls and study samples.

conclusionsThe influence of laboratory contamination will vary across airway microbiome studies. By reporting estimates of contaminant levels and taking use of contaminant identification tools (e.g. the Decontam R package) based on statistical models that limit the subjectivity of the researcher, the accuracy of inter-study comparisons can be improved.

Indexed as

MicrobiotaAgedAir MicrobiologyBacteriaBacterial LoadBronchoalveolar LavageDNA, BacterialEquipment ContaminationFemaleHumansLaboratoriesMaleMiddle AgedRespiratory SystemRNA, Ribosomal, 16SDNA, BacterialRNA, Ribosomal, 16S16S rRNA geneContaminationLow biomassMicrobiomeRespiratory

Identifiers

PMID31412780
PMCPMC6694601

What OpenQuestion holds

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LicenceCC BY
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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.