Evidence map›Paper›PMID 28376723›Full record

ArticleBMC microbiology2017

Discrimination of three genetically close Aspergillus species by using high resolution melting analysis applied to indoor air as case study.

Xavier Libert, Ann Packeu, Fabrice Bureau, Nancy H Roosens, Sigrid C J De Keersmaecker

Abstract read
In one paragraph

Article in BMC microbiology, 2017. 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
–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

9 citing papers in PubMed.

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  7. Spectral Grouping of NominallyMicroorganisms · 2019
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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

5 authors.

Xavier LibertPlatform Biotechnology and Molecular Biology, Scientific Institute of Public Health (WIV-ISP), J. Wytsmanstraat 14, 1050, Brussels, Belgium.
Ann PackeuMycology and Aerobiology, Scientific Institute of Public Health (WIV-ISP), J. Wytsmanstraat 14, 1050, Brussels, Belgium.
Fabrice BureauCellular and Molecular Immunology, Groupe Interdisciplinaire de Génoprotéomique Appliquée (GIGA), Université de Liège (ULg), Avenue de l'Hôpital, 1 (B34), 4000, Sart-Tilman, Belgium.
Nancy H RoosensPlatform Biotechnology and Molecular Biology, Scientific Institute of Public Health (WIV-ISP), J. Wytsmanstraat 14, 1050, Brussels, Belgium.
Sigrid C J De KeersmaeckerPlatform Biotechnology and Molecular Biology, Scientific Institute of Public Health (WIV-ISP), J. Wytsmanstraat 14, 1050, Brussels, Belgium. sigrid.dekeersmaecker@wiv-isp.be.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIndoor air pollution caused by fungal contamination is suspected to have a public health impact. Monitoring of the composition of the indoor airborne fungal contaminants is therefore important. To avoid problems linked to culture-dependent protocols, molecular methods are increasingly being proposed as an alternative. Among these molecular methods, the polymerase chain reaction (PCR) and the real-time PCR are the most frequently used tools for indoor fungal detection. However, even if these tools have demonstrated their appropriate performance, some of them are not able to discriminate between species which are genetically close. A solution to this could be the use of a post-qPCR high resolution melting (HRM) analysis, which would allow the discrimination of these species based on the highly accurate determination of the difference in melting temperature of the obtained amplicon. In this study, we provide a proof-of-concept for this approach, using a dye adapted version of our previously developed qPCR SYBR®Green method to detect Aspergillus versicolor in indoor air, an important airborne fungus in terms of occurrence and cause of health problems. Despite the good performance observed for that qPCR method, no discrimination could previously be made between A. versicolor, Aspergillus creber and Aspergillus sydowii.

methodsIn this study, we developed and evaluated an HRM assay for the discrimination between A. versicolor, Aspergillus creber and Aspergillus sydowii.

resultsUsing HRM analysis, the discrimination of the 3 Aspergillus species could be made. No false positive, nor false negatives were observed during the performance assessment including 20 strains of Aspergillus. The limit of detection was determined for each species i.e., 0.5 pg of gDNA for A. creber and A. sydowii, and 0.1 pg of gDNA for A. versicolor. The HRM analysis was also successfully tested on environmental samples.

conclusionWe reported the development of HRM tools for the discrimination of A. versicolor, A. creber and A. sydowii. However, this study could be considered as a study case demonstrating that HRM based on existing qPCR assays, allows a more accurate identification of indoor air contaminants. This contributes to an improved insight in the diversity of indoor airborne fungi and hence, eventually in the causal link with health problems.

Indexed as

Air MicrobiologyAir Pollution, IndoorAspergillusDNA, FungalEnvironmental MonitoringFungiHumansLimit of DetectionProof of Concept StudyPublic HealthReal-Time Polymerase Chain ReactionSensitivity and SpecificityDNA, FungalAspergillusHigh resolution melting analysisIndoor airMolecular methodPublic health

Identifiers

PMID28376723
PMCPMC5381056

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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.