Cargando…

Sensitivity and specificity of metatranscriptomics as an arbovirus surveillance tool

The ability to identify all the viruses within a sample makes metatranscriptomic sequencing an attractive tool to screen mosquitoes for arboviruses. Practical application of this technique, however, requires a clear understanding of its analytical sensitivity and specificity. To assess this, five di...

Descripción completa

Detalles Bibliográficos
Autores principales: Batovska, Jana, Mee, Peter T., Lynch, Stacey E., Sawbridge, Tim I., Rodoni, Brendan C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6920425/
https://www.ncbi.nlm.nih.gov/pubmed/31852942
http://dx.doi.org/10.1038/s41598-019-55741-3
_version_ 1783480952151867392
author Batovska, Jana
Mee, Peter T.
Lynch, Stacey E.
Sawbridge, Tim I.
Rodoni, Brendan C.
author_facet Batovska, Jana
Mee, Peter T.
Lynch, Stacey E.
Sawbridge, Tim I.
Rodoni, Brendan C.
author_sort Batovska, Jana
collection PubMed
description The ability to identify all the viruses within a sample makes metatranscriptomic sequencing an attractive tool to screen mosquitoes for arboviruses. Practical application of this technique, however, requires a clear understanding of its analytical sensitivity and specificity. To assess this, five dilutions (1:1, 1:20, 1:400, 1:8,000 and 1:160,000) of Ross River virus (RRV) and Umatilla virus (UMAV) isolates were spiked into subsamples of a pool of 100 Culex australicus mosquitoes. The 1:1 dilution represented the viral load of one RRV-infected mosquito in a pool of 100 mosquitoes. The subsamples underwent nucleic acid extraction, mosquito-specific ribosomal RNA depletion, and Illumina HiSeq sequencing. The viral load of the subsamples was also measured using reverse transcription droplet digital PCR (RT-ddPCR) and quantitative PCR (RT-qPCR). Metatranscriptomic sequencing detected both RRV and UMAV in the 1:1, 1:20 and 1:400 subsamples. A high specificity was achieved, with 100% of RRV and 99.6% of UMAV assembled contigs correctly identified. Metatranscriptomic sequencing was not as sensitive as RT-qPCR or RT-ddPCR; however, it recovered whole genome information and detected 19 other viruses, including four first detections for Australia. These findings will assist arbovirus surveillance programs in utilising metatranscriptomics in routine surveillance activities to enhance arbovirus detection.
format Online
Article
Text
id pubmed-6920425
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-69204252019-12-20 Sensitivity and specificity of metatranscriptomics as an arbovirus surveillance tool Batovska, Jana Mee, Peter T. Lynch, Stacey E. Sawbridge, Tim I. Rodoni, Brendan C. Sci Rep Article The ability to identify all the viruses within a sample makes metatranscriptomic sequencing an attractive tool to screen mosquitoes for arboviruses. Practical application of this technique, however, requires a clear understanding of its analytical sensitivity and specificity. To assess this, five dilutions (1:1, 1:20, 1:400, 1:8,000 and 1:160,000) of Ross River virus (RRV) and Umatilla virus (UMAV) isolates were spiked into subsamples of a pool of 100 Culex australicus mosquitoes. The 1:1 dilution represented the viral load of one RRV-infected mosquito in a pool of 100 mosquitoes. The subsamples underwent nucleic acid extraction, mosquito-specific ribosomal RNA depletion, and Illumina HiSeq sequencing. The viral load of the subsamples was also measured using reverse transcription droplet digital PCR (RT-ddPCR) and quantitative PCR (RT-qPCR). Metatranscriptomic sequencing detected both RRV and UMAV in the 1:1, 1:20 and 1:400 subsamples. A high specificity was achieved, with 100% of RRV and 99.6% of UMAV assembled contigs correctly identified. Metatranscriptomic sequencing was not as sensitive as RT-qPCR or RT-ddPCR; however, it recovered whole genome information and detected 19 other viruses, including four first detections for Australia. These findings will assist arbovirus surveillance programs in utilising metatranscriptomics in routine surveillance activities to enhance arbovirus detection. Nature Publishing Group UK 2019-12-18 /pmc/articles/PMC6920425/ /pubmed/31852942 http://dx.doi.org/10.1038/s41598-019-55741-3 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Batovska, Jana
Mee, Peter T.
Lynch, Stacey E.
Sawbridge, Tim I.
Rodoni, Brendan C.
Sensitivity and specificity of metatranscriptomics as an arbovirus surveillance tool
title Sensitivity and specificity of metatranscriptomics as an arbovirus surveillance tool
title_full Sensitivity and specificity of metatranscriptomics as an arbovirus surveillance tool
title_fullStr Sensitivity and specificity of metatranscriptomics as an arbovirus surveillance tool
title_full_unstemmed Sensitivity and specificity of metatranscriptomics as an arbovirus surveillance tool
title_short Sensitivity and specificity of metatranscriptomics as an arbovirus surveillance tool
title_sort sensitivity and specificity of metatranscriptomics as an arbovirus surveillance tool
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6920425/
https://www.ncbi.nlm.nih.gov/pubmed/31852942
http://dx.doi.org/10.1038/s41598-019-55741-3
work_keys_str_mv AT batovskajana sensitivityandspecificityofmetatranscriptomicsasanarbovirussurveillancetool
AT meepetert sensitivityandspecificityofmetatranscriptomicsasanarbovirussurveillancetool
AT lynchstaceye sensitivityandspecificityofmetatranscriptomicsasanarbovirussurveillancetool
AT sawbridgetimi sensitivityandspecificityofmetatranscriptomicsasanarbovirussurveillancetool
AT rodonibrendanc sensitivityandspecificityofmetatranscriptomicsasanarbovirussurveillancetool