An expert program has been developed for users working in industrial laboratories who are not experts in the identification of filamentous fungi. The database of morphological growth features currently contains 12 species from the genera Aspergillus and Penicillium grown under standard conditions. The identification algorithm implemented in the database takes into account the reliability of users, which can vary over a wide range depending on the identification feature. The reliability of users was estimated on the basis of a questionnaire survey conducted among 27 non-experts, as the likelihood of a response consistent with the assessment of experts. The program works through comparative analysis of features of the fungus being identified with the expert-developed database and selection of the most likely species among the species represented by reference strains. The expert program reduces subjective mistakes and may be extended to include further fungal species and genera; it can also be supplemented with chemotaxonomic, genetic and other data.
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J Clin Microbiol
January 2025
Department of Pathology and Immunology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA.
Unlabelled: Rapid and accurate identification of cultured molds is important to determine clinical significance and therapeutic decision-making. Conventional mold identification uses phenotypic macroscopic and microscopic characterization; however, this can take days or weeks for colony maturity and definitive microscopic structure formation, be limited to genus-level identification, and be misidentified due to morphologic mimics or similarities between closely related species. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) revolutionized bacterial and yeast identification but remains uncommon for molds in part because of limited reference libraries.
View Article and Find Full Text PDFMicrobiome
January 2025
Instituto de Investigación de La Viña y El Vino, Escuela de Ingeniería Agraria, Universidad de León, Avenida de Portugal, 41, León, 24009, Spain.
Plant Dis
January 2025
Guizhou University, Guizhou University, Guiyang, Guiyang, Guizhou, China, 550025;
During a field study in the Baili Azalea Forest Area in Guizhou Province, China (27°12'N, 105°48'E) between May and July 2023, symptoms of leaf spot were observed on Franch. The incidence of leaf spot on leaves was about 12% in a field of 1 hm2, significantly reducing their ornamental and economic value. The affected leaves bore irregular, grey-white lesions with distinct dark brown borders, accompanied by black conidiomata.
View Article and Find Full Text PDFIntroduction Mucormycosis is an uncommon fungal infection caused by filamentous fungi of the Mucorales order, namely Rhizopus, Lichthemia, andMucor species. The incidence and prevalence of mucormycosis reached an all-time high during the COVID-19 pandemic due to excessive steroid use and other factors, leading to the coining of the term CAM (COVID Associated Mucormycosis). The diagnosis of mucormycosis is by a combination of histopathology and microbiological techniques, such as KOH mount and culture.
View Article and Find Full Text PDFBMC Genomics
January 2025
The Key Lab for Biology of Crop Pathogens and Insect Pests and Their Ecological Regulation of Zhejiang Province, College of Advanced Agricultural Sciences, Zhejiang A&F University, Hangzhou, 311300, China.
Long non-coding RNA (lncRNA) plays important roles in animals and plants. In filamentous fungi, however, their biological function in infection stage has been poorly studied. Here, we investigated the landscape and regulation of lncRNA in the filamentous plant pathogenic fungus Botrytis cinerea by strand-specific RNA-seq of multiple infection stages.
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