4.3 Article

Comparison of sequencing the D2 region of the large subunit ribosomal RNA gene (MicroSEQ®) versus the internal transcribed spacer (ITS) regions using two public databases for identification of common and uncommon clinically relevant fungal species

期刊

JOURNAL OF MICROBIOLOGICAL METHODS
卷 140, 期 -, 页码 40-46

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ELSEVIER SCIENCE BV
DOI: 10.1016/j.mimet.2017.06.015

关键词

Mould; Identification; Sequencing; D2 region of the large-subunit rRNA gene; Internal transcribed spacer (ITS) regions; GenBank; MycoBank

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  1. Department of Laboratory Medicine and Pathology, University of Minnesota Medical School

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Context Fungal infections cause considerable morbidity and mortality in immunocompromised patients. Rapid and accurate identification of fungi is essential to guide accurately targeted antifungal therapy. With the advent of molecular methods, clinical laboratories can use new technologies to supplement traditional phenotypic identification of fungi. Objective: The aims of the study were to evaluate the sole commercially available MicroSEQ (R) D2 LSU rDNA Fungal Identification Kit compared to the in-house developed internal transcribed spacer (ITS) regions assay in identifying moulds, using two well-known online public databases to analyze sequenced data. Design: 85 common and uncommon clinically relevant fungi isolated from clinical specimens were sequenced for the D2 region of the large subunit (LSU) of ribosomal RNA (rRNA) gene with the MicroSEQ (R) Kit and the ITS regions with the in house developed assay. The generated sequenced data were analyzed with the online GenBank and MycoBank public databases. Results: The D2 region of the LSU rRNA gene identified 89.4% or 92.9% of the 85 isolates to the genus level and the full ITS region (f-ITS) 96.5% or 100%, using GenBank or MycoBank, respectively, when compared to the consensus ID. When comparing species-level designations to the consensus ID, D2 region of the LSU rRNA gene aligned with 44.7% (38/85) or 52.9% (45/85) of these isolates in GenBank or MycoBank, respectively. By comparison, f-ITS possessed greater specificity, followed by ITS1, then ITS2 regions using GenBank or MycoBank. Using GenBank or MycoBank, D2 region of the LSU rRNA gene outperformed phenotypic based ID at the genus level. Comparing rates of ID between D2 region of the LSU rRNA gene and the ITS regions in GenBank or MycoBank at the species level against the consensus ID, f-ITS and ITS2 exceeded performance of the D2 region of the LSU rRNA gene, but ITS1 had similar performance to the D2 region of the LSU rRNA gene using MycoBank. Conclusion: Our results indicated that the MicroSEQ (R) D2 LSU rDNA Fungal Identification Kit was equivalent to the in-house developed ITS regions assay to identify fungi at the genus level. The MycoBank database gave a better curated database and thus allowed a better genus and species identification for both D2 region of the LSU rRNA gene and ITS regions.

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