Literature DB >> 32738297

Amplicon-Based Next-Generation Sequencing for Detection of Fungi in Formalin-Fixed, Paraffin-Embedded Tissues: Correlation with Histopathology and Clinical Applications.

Paige M K Larkin1, Katy L Lawson1, Deisy A Contreras1, Catherine Q Le1, Marisol Trejo1, Susan Realegeno1, Evann E Hilt1, Sukantha Chandrasekaran1, Omai B Garner1, Gregory A Fishbein1, Shangxin Yang2.   

Abstract

Invasive fungal infections are increasing in prevalence because of an expanding population of immunocompromised individuals. To reduce morbidity and mortality, it is critical to accurately identify fungal pathogens to guide treatment. Current methods rely on histopathology, fungal culture, and serology, which are often insufficient for diagnosis. Herein, we describe the use of a laboratory-developed internal transcribed spacer-targeted amplicon-based next-generation sequencing (NGS) assay for the identification of fungal etiology in fungal stain-positive formalin-fixed, paraffin-embedded tissues by using Illumina MiSeq. A total of 44 specimens from 35 patients were included in this study, with varying degrees of fungal burden from multiple anatomic sites. NGS identified 20 unique species across the 54 total organisms detected, including 40 molds, 10 yeasts, and 4 dimorphic fungi. The histopathologic morphology and the organisms suspected by surgical pathologist were compared with the organisms identified by NGS, with 100% (44/44) and 93.2% (41/44) concordance, respectively. In contrast, fungal culture only provided an identification in 27.3% (12/44) of specimens. We demonstrated that NGS is a powerful method for accurate and unbiased fungal identification in formalin-fixed, paraffin-embedded tissues. A retrospective evaluation of the clinical utility of the NGS results also suggests this technology can potentially improve both the speed and the accuracy of diagnosis for invasive fungal infections.
Copyright © 2020 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Entities:  

Year:  2020        PMID: 32738297     DOI: 10.1016/j.jmoldx.2020.06.017

Source DB:  PubMed          Journal:  J Mol Diagn        ISSN: 1525-1578            Impact factor:   5.568


  4 in total

1.  Recognition of Diagnostic Gaps for Laboratory Diagnosis of Fungal Diseases: Expert Opinion from the Fungal Diagnostics Laboratories Consortium (FDLC).

Authors:  Sean X Zhang; N Esther Babady; Kimberly E Hanson; Amanda T Harrington; Paige M K Larkin; Sixto M Leal; Paul M Luethy; Isabella W Martin; Preeti Pancholi; Gary W Procop; Stefan Riedel; Seyedmojtaba Seyedmousavi; Kaede V Sullivan; Thomas J Walsh; Shawn R Lockhart
Journal:  J Clin Microbiol       Date:  2021-06-18       Impact factor: 5.948

2.  Evaluating a semi-nested PCR to support histopathology reports of fungal rhinosinusitis in formalin-fixed paraffin-embedded tissue samples.

Authors:  Mohammad Javad Ashraf; Mohammad Kord; Hamid Morovati; Saham Ansari; Golsa Shekarkhar; Hamid Badali; Kayvan Pakshir; Forough Shamsizadeh; Bijan Khademi; Mahmood Shishegar; Kazem Ahmadikia; Kamiar Zomorodian
Journal:  J Clin Lab Anal       Date:  2022-01-08       Impact factor: 2.352

Review 3.  Next Generation and Other Sequencing Technologies in Diagnostic Microbiology and Infectious Diseases.

Authors:  Evann E Hilt; Patricia Ferrieri
Journal:  Genes (Basel)       Date:  2022-08-31       Impact factor: 4.141

4.  Exclusion of Mucorales Co-Infection in a Patient with Aspergillus flavus Sinusitis by Fluorescence In Situ Hybridization (FISH).

Authors:  Johanna Kessel; Michael Hogardt; Lukas Aspacher; Thomas A Wichelhaus; Jasmin Gerkrath; Emely Rosenow; Jan Springer; Volker Rickerts
Journal:  J Fungi (Basel)       Date:  2022-03-16
  4 in total

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