Unexpected mould diversity in clinical isolates from French Guiana and associated identification difficulties.

DNA sequencing Mass spectrometry diagnosis diversity molds

Journal

Medical mycology
ISSN: 1460-2709
Titre abrégé: Med Mycol
Pays: England
ID NLM: 9815835

Informations de publication

Date de publication:
27 Oct 2020
Historique:
received: 10 08 2020
revised: 05 10 2020
accepted: 12 10 2020
entrez: 28 10 2020
pubmed: 29 10 2020
medline: 29 10 2020
Statut: aheadofprint

Résumé

New mold species are increasingly reported in invasive fungal infections. However, these fungi are often misdiagnosed or undiagnosed due to the use of inappropriate laboratory diagnostic tools. Tropical countries, such as French Guiana, harbor a vast diversity of environmental fungi representing a potential source of emerging pathogens. To assess the impact of this diversity on the accuracy of mold-infection diagnoses, we identified mold clinical isolates in French Guiana during a five-month follow-up using both microscopy and matrix-assisted laser desorption ionization time-of-flight mass spectrometry. In total, 38.8% of the 98 obtained molds isolates could not be identified and required a DNA-based identification. Fungal diversity was high, including 46 species, 26 genera, and 13 orders. Fungal ecology was unusual, as Aspergillus species accounted for only 27% of all isolates, and the Nigri section was the most abundant out of the six detected Aspergillus sections. Macromycetes (orders Agaricales, Polyporales, and Russulales) and endophytic fungi accounted for respectively 11% and 14% of all isolates. Thus, in tropical areas with high fungal diversity, such as French Guiana, routine mold identification tools are inadequate. Molecular identifications, as well as morphological descriptions, are necessary for the construction of region-specific mass spectrum databases. These advances will improve the diagnosis and clinical management of new fungal infections. In French Guiana, environmental fungal diversity may be a source of emerging pathogens. We evaluated microscopy and mass spectrometry to identify mold clinical isolates. With 39% of unidentified isolates, a region-specific mass spectrum database would improve the diagnosis of new fungal infections.

Identifiants

pubmed: 33111143
pii: 5941768
doi: 10.1093/mmy/myaa091
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press on behalf of The International Society for Human and Animal Mycology.

Auteurs

C Nabet (C)

Sorbonne Université, INSERM, Institut Pierre-Louis d'Epidémiologie et de Santé Publique, AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Service de Parasitologie-Mycologie, Paris, France.

S Imbert (S)

Sorbonne Université, INSERM, CNRS, Centre d'Immunologie et des Maladies Infectieuses, Cimi-Paris, AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Service de Parasitologie-Mycologie, Paris, France.

A C Normand (AC)

Sorbonne Université, INSERM, Institut Pierre-Louis d'Epidémiologie et de Santé Publique, AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Service de Parasitologie-Mycologie, Paris, France.

D Blanchet (D)

Department of Parasitology-Mycology, Hôpital Andrée Rosemon, Cayenne, French Guiana.

R Chanlin (R)

Department of Parasitology-Mycology, Hôpital Andrée Rosemon, Cayenne, French Guiana.

P Becker (P)

Sciensano, BCCM/IHEM collection, Mycology and Aerobiology Unit, Brussels, Belgium.

M Demar (M)

Department of Parasitology-Mycology, Hôpital Andrée Rosemon, Cayenne, French Guiana.
EA 3593, Ecosystèmes Amazoniens et Pathologies Tropicales, Université de Guyane, Cayenne, French Guiana.

R Piarroux (R)

Sorbonne Université, INSERM, Institut Pierre-Louis d'Epidémiologie et de Santé Publique, AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Service de Parasitologie-Mycologie, Paris, France.

Classifications MeSH