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268. Fungal NGS: Identification of Etiological Agents of Invasive Fungal Infection by High-throughput Sequencing

BACKGROUND: Invasive fungal infections (IFI) cause severe symptoms that affect immunocompromised and transplant patient populations. Antifungal therapies vary depending on the pathogenic species, and delays in diagnosis can lead to graft loss and an increase in morbidity and mortality. Therefore, ra...

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Autores principales: Nelsen, Donald J, Sinha, Rohita, Tyler, Aaron J, Westergaard, Jordyn, Nutt, Jamie, Wissel, Mark, Kleiboeker, Steve, Altrich, Michelle
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6809827/
http://dx.doi.org/10.1093/ofid/ofz360.343
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author Nelsen, Donald J
Sinha, Rohita
Tyler, Aaron J
Westergaard, Jordyn
Nutt, Jamie
Wissel, Mark
Kleiboeker, Steve
Altrich, Michelle
author_facet Nelsen, Donald J
Sinha, Rohita
Tyler, Aaron J
Westergaard, Jordyn
Nutt, Jamie
Wissel, Mark
Kleiboeker, Steve
Altrich, Michelle
author_sort Nelsen, Donald J
collection PubMed
description BACKGROUND: Invasive fungal infections (IFI) cause severe symptoms that affect immunocompromised and transplant patient populations. Antifungal therapies vary depending on the pathogenic species, and delays in diagnosis can lead to graft loss and an increase in morbidity and mortality. Therefore, rapid identification of fungi causing IFI is critical for informing antifungal therapy. Such actionable genus/species information can be obtained quickly via Next-generation Sequencing (NGS). In this study, an NGS assay was developed to identify fungal species responsible for IFI, allowing for selection of effective antifungal therapies. METHODS: Internal transcribed spacer (ITS) regions 1 and 2 were used for fungal identification. Primers were taken from published research and/or designed/modified by assessment in fungal sequence alignments. A DNA sequence database was compiled and a reference-assisted assembly approach utilizing % sequence ID and % coverage was developed for species identification. End-point PCR was conducted on DNA extracted from 19 pathogenic fungal species, and mixed communities (MC) for preliminary sensitivity and inclusivity. Sensitivity was assessed using dilutions of template DNA into the PCR reaction. RESULTS: NGS data of 14 individual species and 4 MC passed quality control checks. Using only ITS1 and ITS2, species identification was expected for 10 of 14 individuals. We observed species identification in 9 individual samples, and 13 were identified within the top 5 results. All individuals were identified to genus. In MC analyses, combinations of 3, 4, 6, and 10 fungal species resolved 100% of the genera present, but failed to resolve species adequately with only 2 loci evaluated. Unexpectedly, 3 tested Aspergillus spp. were correctly identified with this limited data in both single and MC samples. The lower limit of detection was assessed at 5,000 genomic equivalents/mL of eluate. CONCLUSION: The inclusivity and sensitivity demonstrated here of an NGS approach for identification of etiological agents of IFI support this assay’s potential utility as an aid in the treatment of IFI in at-risk patient groups. This assay allows for rapid identification (<4 days) of fungal species to aid clinicians in improving case outcomes. DISCLOSURES: All authors: No reported disclosures.
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spelling pubmed-68098272019-10-28 268. Fungal NGS: Identification of Etiological Agents of Invasive Fungal Infection by High-throughput Sequencing Nelsen, Donald J Sinha, Rohita Tyler, Aaron J Westergaard, Jordyn Nutt, Jamie Wissel, Mark Kleiboeker, Steve Altrich, Michelle Open Forum Infect Dis Abstracts BACKGROUND: Invasive fungal infections (IFI) cause severe symptoms that affect immunocompromised and transplant patient populations. Antifungal therapies vary depending on the pathogenic species, and delays in diagnosis can lead to graft loss and an increase in morbidity and mortality. Therefore, rapid identification of fungi causing IFI is critical for informing antifungal therapy. Such actionable genus/species information can be obtained quickly via Next-generation Sequencing (NGS). In this study, an NGS assay was developed to identify fungal species responsible for IFI, allowing for selection of effective antifungal therapies. METHODS: Internal transcribed spacer (ITS) regions 1 and 2 were used for fungal identification. Primers were taken from published research and/or designed/modified by assessment in fungal sequence alignments. A DNA sequence database was compiled and a reference-assisted assembly approach utilizing % sequence ID and % coverage was developed for species identification. End-point PCR was conducted on DNA extracted from 19 pathogenic fungal species, and mixed communities (MC) for preliminary sensitivity and inclusivity. Sensitivity was assessed using dilutions of template DNA into the PCR reaction. RESULTS: NGS data of 14 individual species and 4 MC passed quality control checks. Using only ITS1 and ITS2, species identification was expected for 10 of 14 individuals. We observed species identification in 9 individual samples, and 13 were identified within the top 5 results. All individuals were identified to genus. In MC analyses, combinations of 3, 4, 6, and 10 fungal species resolved 100% of the genera present, but failed to resolve species adequately with only 2 loci evaluated. Unexpectedly, 3 tested Aspergillus spp. were correctly identified with this limited data in both single and MC samples. The lower limit of detection was assessed at 5,000 genomic equivalents/mL of eluate. CONCLUSION: The inclusivity and sensitivity demonstrated here of an NGS approach for identification of etiological agents of IFI support this assay’s potential utility as an aid in the treatment of IFI in at-risk patient groups. This assay allows for rapid identification (<4 days) of fungal species to aid clinicians in improving case outcomes. DISCLOSURES: All authors: No reported disclosures. Oxford University Press 2019-10-23 /pmc/articles/PMC6809827/ http://dx.doi.org/10.1093/ofid/ofz360.343 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Infectious Diseases Society of America. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Abstracts
Nelsen, Donald J
Sinha, Rohita
Tyler, Aaron J
Westergaard, Jordyn
Nutt, Jamie
Wissel, Mark
Kleiboeker, Steve
Altrich, Michelle
268. Fungal NGS: Identification of Etiological Agents of Invasive Fungal Infection by High-throughput Sequencing
title 268. Fungal NGS: Identification of Etiological Agents of Invasive Fungal Infection by High-throughput Sequencing
title_full 268. Fungal NGS: Identification of Etiological Agents of Invasive Fungal Infection by High-throughput Sequencing
title_fullStr 268. Fungal NGS: Identification of Etiological Agents of Invasive Fungal Infection by High-throughput Sequencing
title_full_unstemmed 268. Fungal NGS: Identification of Etiological Agents of Invasive Fungal Infection by High-throughput Sequencing
title_short 268. Fungal NGS: Identification of Etiological Agents of Invasive Fungal Infection by High-throughput Sequencing
title_sort 268. fungal ngs: identification of etiological agents of invasive fungal infection by high-throughput sequencing
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6809827/
http://dx.doi.org/10.1093/ofid/ofz360.343
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