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DeepSARS: simultaneous diagnostic detection and genomic surveillance of SARS-CoV-2
BACKGROUND: The continued spread of SARS-CoV-2 and emergence of new variants with higher transmission rates and/or partial resistance to vaccines has further highlighted the need for large-scale testing and genomic surveillance. However, current diagnostic testing (e.g., PCR) and genomic surveillanc...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8995413/ https://www.ncbi.nlm.nih.gov/pubmed/35410128 http://dx.doi.org/10.1186/s12864-022-08403-0 |
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author | Yermanos, Alexander Hong, Kai-Lin Agrafiotis, Andreas Han, Jiami Nadeau, Sarah Valenzuela, Cecilia Azizoglu, Asli Ehling, Roy Gao, Beichen Spahr, Michael Neumeier, Daniel Chang, Ching-Hsiang Dounas, Andreas Petrillo, Ezequiel Nissen, Ina Burcklen, Elodie Feldkamp, Mirjam Beisel, Christian Oxenius, Annette Savic, Miodrag Stadler, Tanja Rudolf, Fabian Reddy, Sai T. |
author_facet | Yermanos, Alexander Hong, Kai-Lin Agrafiotis, Andreas Han, Jiami Nadeau, Sarah Valenzuela, Cecilia Azizoglu, Asli Ehling, Roy Gao, Beichen Spahr, Michael Neumeier, Daniel Chang, Ching-Hsiang Dounas, Andreas Petrillo, Ezequiel Nissen, Ina Burcklen, Elodie Feldkamp, Mirjam Beisel, Christian Oxenius, Annette Savic, Miodrag Stadler, Tanja Rudolf, Fabian Reddy, Sai T. |
author_sort | Yermanos, Alexander |
collection | PubMed |
description | BACKGROUND: The continued spread of SARS-CoV-2 and emergence of new variants with higher transmission rates and/or partial resistance to vaccines has further highlighted the need for large-scale testing and genomic surveillance. However, current diagnostic testing (e.g., PCR) and genomic surveillance methods (e.g., whole genome sequencing) are performed separately, thus limiting the detection and tracing of SARS-CoV-2 and emerging variants. RESULTS: Here, we developed DeepSARS, a high-throughput platform for simultaneous diagnostic detection and genomic surveillance of SARS-CoV-2 by the integration of molecular barcoding, targeted deep sequencing, and computational phylogenetics. DeepSARS enables highly sensitive viral detection, while also capturing genomic diversity and viral evolution. We show that DeepSARS can be rapidly adapted for identification of emerging variants, such as alpha, beta, gamma, and delta strains, and profile mutational changes at the population level. CONCLUSIONS: DeepSARS sets the foundation for quantitative diagnostics that capture viral evolution and diversity. GRAPHICAL ABSTRACT: DeepSARS uses molecular barcodes (BCs) and multiplexed targeted deep sequencing (NGS) to enable simultaneous diagnostic detection and genomic surveillance of SARS-CoV-2. Image was created using Biorender.com. [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-08403-0. |
format | Online Article Text |
id | pubmed-8995413 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-89954132022-04-11 DeepSARS: simultaneous diagnostic detection and genomic surveillance of SARS-CoV-2 Yermanos, Alexander Hong, Kai-Lin Agrafiotis, Andreas Han, Jiami Nadeau, Sarah Valenzuela, Cecilia Azizoglu, Asli Ehling, Roy Gao, Beichen Spahr, Michael Neumeier, Daniel Chang, Ching-Hsiang Dounas, Andreas Petrillo, Ezequiel Nissen, Ina Burcklen, Elodie Feldkamp, Mirjam Beisel, Christian Oxenius, Annette Savic, Miodrag Stadler, Tanja Rudolf, Fabian Reddy, Sai T. BMC Genomics Research Article BACKGROUND: The continued spread of SARS-CoV-2 and emergence of new variants with higher transmission rates and/or partial resistance to vaccines has further highlighted the need for large-scale testing and genomic surveillance. However, current diagnostic testing (e.g., PCR) and genomic surveillance methods (e.g., whole genome sequencing) are performed separately, thus limiting the detection and tracing of SARS-CoV-2 and emerging variants. RESULTS: Here, we developed DeepSARS, a high-throughput platform for simultaneous diagnostic detection and genomic surveillance of SARS-CoV-2 by the integration of molecular barcoding, targeted deep sequencing, and computational phylogenetics. DeepSARS enables highly sensitive viral detection, while also capturing genomic diversity and viral evolution. We show that DeepSARS can be rapidly adapted for identification of emerging variants, such as alpha, beta, gamma, and delta strains, and profile mutational changes at the population level. CONCLUSIONS: DeepSARS sets the foundation for quantitative diagnostics that capture viral evolution and diversity. GRAPHICAL ABSTRACT: DeepSARS uses molecular barcodes (BCs) and multiplexed targeted deep sequencing (NGS) to enable simultaneous diagnostic detection and genomic surveillance of SARS-CoV-2. Image was created using Biorender.com. [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-08403-0. BioMed Central 2022-04-11 /pmc/articles/PMC8995413/ /pubmed/35410128 http://dx.doi.org/10.1186/s12864-022-08403-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Yermanos, Alexander Hong, Kai-Lin Agrafiotis, Andreas Han, Jiami Nadeau, Sarah Valenzuela, Cecilia Azizoglu, Asli Ehling, Roy Gao, Beichen Spahr, Michael Neumeier, Daniel Chang, Ching-Hsiang Dounas, Andreas Petrillo, Ezequiel Nissen, Ina Burcklen, Elodie Feldkamp, Mirjam Beisel, Christian Oxenius, Annette Savic, Miodrag Stadler, Tanja Rudolf, Fabian Reddy, Sai T. DeepSARS: simultaneous diagnostic detection and genomic surveillance of SARS-CoV-2 |
title | DeepSARS: simultaneous diagnostic detection and genomic surveillance of SARS-CoV-2 |
title_full | DeepSARS: simultaneous diagnostic detection and genomic surveillance of SARS-CoV-2 |
title_fullStr | DeepSARS: simultaneous diagnostic detection and genomic surveillance of SARS-CoV-2 |
title_full_unstemmed | DeepSARS: simultaneous diagnostic detection and genomic surveillance of SARS-CoV-2 |
title_short | DeepSARS: simultaneous diagnostic detection and genomic surveillance of SARS-CoV-2 |
title_sort | deepsars: simultaneous diagnostic detection and genomic surveillance of sars-cov-2 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8995413/ https://www.ncbi.nlm.nih.gov/pubmed/35410128 http://dx.doi.org/10.1186/s12864-022-08403-0 |
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