Evidence map›Paper›PMID 36326257›Full record

ArticleJournal of clinical microbiology2022

A Practical Workflow for the Identification of Aspergillus, Fusarium, Mucorales by MALDI-TOF MS: Database, Medium, and Incubation Optimization.

Kevin R Barker, Julianne V Kus, Anne-Cecile Normand, Farhad Gharabaghi, Lisa McTaggart, Coleman Rotstein, Susan E Richardson, Aaron Campigotto, Manal Tadros

Abstract read
In one paragraph

Article in Journal of clinical microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Optimizing filamentous fungi identification by MALDI-TOF MS: A comparative analysis of key factors.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Mucormycosis.Infectious disease clinics of North America · 2025
    Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Invasive fusariosis.Clinical microbiology reviews · 2023
    Review
  17. A comparative study for optimization of MALDI-TOF MS identification of filamentous fungi.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2023
    Article
  18. Article
  19. Article
  20. 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

9 authors.

Kevin R BarkerDivision of Microbiology, Department of Laboratory Medicine and Genetics, Trillium Health Partners, Mississauga, Ontario, Canada.ORCID 0000-0002-9288-6544
Julianne V KusDepartment of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.ORCID 0000-0001-6033-7244
Anne-Cecile NormandService de Parasitologie Mycologie, AP-HP, Groupe Hospitalier La Pitié-Salpêtrière, Paris, France.ORCID 0000-0002-9589-4603
Farhad GharabaghiDivision of Microbiology, Department of Paediatric Laboratory Medicine, Hospital for Sick Childrengrid.42327.30, Toronto, Ontario, Canada.
Lisa McTaggartPublic Health Ontariogrid.415400.4, Toronto, Ontario, Canada.
Coleman RotsteinDivision of Infectious Diseases, Department of Medicine, Immunocompromised Host Infectious Diseases Service, University Health Network, Toronto, Canada.
Susan E RichardsonDepartment of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.
Aaron CampigottoDepartment of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.
Manal TadrosDepartment of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is an increasing body of literature on the utility of MALDI-TOF MS in the identification of filamentous fungi. However, the process still lacks standardization. In this study, we attempted to establish a practical workflow for the identification of three clinically important molds: Aspergillus, Fusarium, and Mucorales using MALDI-TOF MS. We evaluated the performance of Bruker Filamentous Fungi database v3.0 for the identification of these fungi, highlighting when there would be a benefit of using an additional database, the MSI-2 for further identification. We also examined two other variables, namely, medium effect and incubation time on the accuracy of fungal identification. The Bruker database achieved correct species level identification in 85.7% of Aspergillus and 90% of Mucorales, and correct species-complex level in 94.4% of Fusarium. Analysis of spectra using the MSI-2 database would also offer additional value for species identification of Aspergillus species, especially when suspecting species with known identification limits within the Bruker database. This issue would only be of importance in selected cases where species-level identification would impact therapeutic options. Id-Fungi plates (IDFP) had almost equivalent performance to Sabouraud dextrose agar (SDA) for species-level identification of isolates and enabled an easier harvest of the isolates with occasional faster identification. Our study showed accurate identification at 24 h for Fusarium and Mucorales species, but not for Aspergillus species, which generally required 48 h.

Indexed as

FusariumMucoralesAspergillusFungiHumansSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationWorkflowAspergillusclinical mycologycryptic speciesfilamentous fungiFusariumIDFPimmunocompromisedimmunocompromised hostsimmunosuppressedMALDI-TOFmass spectrometrymoldsMucoralesmycologyproteomics

Identifiers

PMID36326257
PMCPMC9769873

What OpenQuestion holds

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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.