Evidence map›Paper›PMID 39775995›Full record

ArticleMycopathologia2025

First Step on the Way to Identify Dermatophytes Using Odour Fingerprints.

Lenka Machová, Meriem Gaida, Jaroslav Semerád, Miroslav Kolařík, Michaela Švarcová, Andrej Jašica, Alena Grasserová, Sandra Awokunle Hollá, Vit Hubka, Pierre-Hugues Stefanuto and 3 more

Abstract read
In one paragraph

Article in Mycopathologia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

13 authors.

Lenka MachováLaboratory of Fungal Genetics and Metabolism, Institute of Microbiology of the Czech Academy of Sciences, Prague, Czech Republic.
Meriem GaidaOrganic and Biological Analytical Chemistry Group, Chemistry Department, University of Liège, Liège, Belgium.
Jaroslav SemerádLaboratory of Environmental Biotechnology, Institute of Microbiology of the Czech Academy of Sciences, Prague, Czech Republic.
Miroslav KolaříkLaboratory of Fungal Genetics and Metabolism, Institute of Microbiology of the Czech Academy of Sciences, Prague, Czech Republic. mkolarik@biomed.cas.cz.
Michaela ŠvarcováLaboratory of Fungal Genetics and Metabolism, Institute of Microbiology of the Czech Academy of Sciences, Prague, Czech Republic.
Andrej JašicaLaboratory of Fungal Genetics and Metabolism, Institute of Microbiology of the Czech Academy of Sciences, Prague, Czech Republic.
Alena GrasserováLaboratory of Environmental Biotechnology, Institute of Microbiology of the Czech Academy of Sciences, Prague, Czech Republic.
Sandra Awokunle HolláLaboratory of Environmental Microbiology, Institute of Microbiology of the Czech Academy of Sciences, Prague, Czech Republic.
Vit HubkaLaboratory of Fungal Genetics and Metabolism, Institute of Microbiology of the Czech Academy of Sciences, Prague, Czech Republic.
Pierre-Hugues StefanutoOrganic and Biological Analytical Chemistry Group, Chemistry Department, University of Liège, Liège, Belgium.
Tomáš CajthamlLaboratory of Environmental Biotechnology, Institute of Microbiology of the Czech Academy of Sciences, Prague, Czech Republic.
Jean-François FocantOrganic and Biological Analytical Chemistry Group, Chemistry Department, University of Liège, Liège, Belgium.
Adéla WennrichLaboratory of Fungal Genetics and Metabolism, Institute of Microbiology of the Czech Academy of Sciences, Prague, Czech Republic. cmokova@gmail.com.ORCID http://orcid.org/0000-0002-7986-6688

Funding

Akademie Věd České Republiky RVO: 61388971Akademie Věd České Republiky VP33 MycoLife - the world of fungiMinisterstvo Zdravotnictví Ceské Republiky NU21-05-00681Univerzita Karlova v Praze START/SCI092
6 · The paper itself

Abstract

The clinical diagnosis of dermatophytosis and identification of dermatophytes face challenges due to reliance on culture-based methods. Rapid, cost-effective detection techniques for volatile organic compounds (VOCs) have been developed for other microorganisms, but their application to dermatophytes is limited. This study explores using VOCs as diagnostic markers for dermatophytes. We compared VOC profiles across different dermatophyte taxa using solid-phase microextraction (SPME) and advanced analytical methods: gas chromatography-mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-TOFMS). We analyzed 47 dermatophyte strains from 15 taxa grown on sheep wool, including clinically significant species. Additionally, we examined phylogenetic relationships among the strains to correlate genetic relatedness with metabolite production. Our results showed that GC×GC-TOFMS offered superior resolution but similar differentiation of VOC profiles compared to GC-MS. VOC spectra allowed reliable distinction of taxonomic units at the species level and below, however, these distinctions showed only a slight correlation with phylogenetic data. We identified pan-dermatophyte and species- or strain-specific VOC profiles, indicating their potential for rapid, non-invasive detection of dermatophyte infections, including epidemic strains. These patterns could enable future taxa-specific identification. Our study highlights the potential of VOCs as tools for dermatophyte taxonomy and diagnosis.

Indexed as

ArthrodermataceaeGas Chromatography-Mass SpectrometryPhylogenyVolatile Organic CompoundsAnimalsHumansOdorantsSheepSolid Phase MicroextractionVolatile Organic CompoundsDermatophytesGas chromatography-mass spectrometryMetabolite profilesVolatile organic compounds

Identifiers

PMID39775995
PMCPMC11706917

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.