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Emerging Landscape of SARS-CoV-2 Variants and Detection Technologies
In 2019, a new coronavirus was identified that has caused significant morbidity and mortality worldwide. Like all RNA viruses, severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) evolves over time through random mutation resulting in genetic variations in the population. Although the curren...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9797111/ https://www.ncbi.nlm.nih.gov/pubmed/36577887 http://dx.doi.org/10.1007/s40291-022-00631-0 |
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author | Li, Xianghui Wang, Jing Geng, Jingping Xiao, Liming Wang, Hu |
author_facet | Li, Xianghui Wang, Jing Geng, Jingping Xiao, Liming Wang, Hu |
author_sort | Li, Xianghui |
collection | PubMed |
description | In 2019, a new coronavirus was identified that has caused significant morbidity and mortality worldwide. Like all RNA viruses, severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) evolves over time through random mutation resulting in genetic variations in the population. Although the currently approved coronavirus disease 2019 vaccines can be given to those over 5 years of age and older in most countries, strikingly, the number of people diagnosed positive for SARS-Cov-2 is still increasing. Therefore, to prevent and control this epidemic, early diagnosis of infected individuals is of great importance. The current detection of SARS-Cov-2 coronavirus variants are mainly based on reverse transcription-polymerase chain reaction. Although the sensitivity of reverse transcription-polymerase chain reaction is high, it has some disadvantages, for example, multiple temperature changes, long detection time, complicated operation, expensive instruments, and the need for professional personnel, which brings considerable inconvenience to the early diagnosis of this virus. This review comprehensively summarizes the development and application of various current detection technologies for novel coronaviruses, including isothermal amplification, CRISPR-Cas detection, serological detection, biosensor, ensemble, and microfluidic technology, along with next-generation sequencing. Those findings offer us a great potential to replace or combine with reverse transcription-polymerase chain reaction detection to achieve the purpose of allowing predictive diagnostics and targeted prevention of SARS-Cov-2 in the future. |
format | Online Article Text |
id | pubmed-9797111 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-97971112022-12-29 Emerging Landscape of SARS-CoV-2 Variants and Detection Technologies Li, Xianghui Wang, Jing Geng, Jingping Xiao, Liming Wang, Hu Mol Diagn Ther Review Article In 2019, a new coronavirus was identified that has caused significant morbidity and mortality worldwide. Like all RNA viruses, severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) evolves over time through random mutation resulting in genetic variations in the population. Although the currently approved coronavirus disease 2019 vaccines can be given to those over 5 years of age and older in most countries, strikingly, the number of people diagnosed positive for SARS-Cov-2 is still increasing. Therefore, to prevent and control this epidemic, early diagnosis of infected individuals is of great importance. The current detection of SARS-Cov-2 coronavirus variants are mainly based on reverse transcription-polymerase chain reaction. Although the sensitivity of reverse transcription-polymerase chain reaction is high, it has some disadvantages, for example, multiple temperature changes, long detection time, complicated operation, expensive instruments, and the need for professional personnel, which brings considerable inconvenience to the early diagnosis of this virus. This review comprehensively summarizes the development and application of various current detection technologies for novel coronaviruses, including isothermal amplification, CRISPR-Cas detection, serological detection, biosensor, ensemble, and microfluidic technology, along with next-generation sequencing. Those findings offer us a great potential to replace or combine with reverse transcription-polymerase chain reaction detection to achieve the purpose of allowing predictive diagnostics and targeted prevention of SARS-Cov-2 in the future. Springer International Publishing 2022-12-28 2023 /pmc/articles/PMC9797111/ /pubmed/36577887 http://dx.doi.org/10.1007/s40291-022-00631-0 Text en © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Review Article Li, Xianghui Wang, Jing Geng, Jingping Xiao, Liming Wang, Hu Emerging Landscape of SARS-CoV-2 Variants and Detection Technologies |
title | Emerging Landscape of SARS-CoV-2 Variants and Detection Technologies |
title_full | Emerging Landscape of SARS-CoV-2 Variants and Detection Technologies |
title_fullStr | Emerging Landscape of SARS-CoV-2 Variants and Detection Technologies |
title_full_unstemmed | Emerging Landscape of SARS-CoV-2 Variants and Detection Technologies |
title_short | Emerging Landscape of SARS-CoV-2 Variants and Detection Technologies |
title_sort | emerging landscape of sars-cov-2 variants and detection technologies |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9797111/ https://www.ncbi.nlm.nih.gov/pubmed/36577887 http://dx.doi.org/10.1007/s40291-022-00631-0 |
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