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Title: | Implementation of an in-house real-time reverse transcription-PCR assay for the rapid detection of the SARS-CoV-2 Marseille-4 variant | Authors: | Bedotto, Marielle Fournier, Pierre-Edouard Houhamdi, Linda Levasseur, Anthony Delerce, Jeremy Pinault, Lucile Padane, Abdou Chamieh, Amanda Tissot-Dupont, Hervé Brouqui, Philippe Sokhna, Cheikh Azar, Eid Saile, Rachid Mboup, Souleymane Bitam, Idir Colson, Philippe Raoult, Didier |
Affiliations: | Faculty of Medicine | Keywords: | Covid-19 Diagnosis Marseille-4 Molecular epidemiology SARS-CoV-2 Variant qPCR |
Issue Date: | 2021 | Publisher: | Elsevier | Part of: | Journal of Clinical Virology | Volume: | 139 | Abstract: | Introduction The SARS-CoV-2 pandemic has been associated with the occurrence since summer 2020 of several viral variants that overlapped or succeeded each other in time. Those of current concern harbor mutations within the spike receptor binding domain (RBD) that may be associated with viral escape to immune responses. In our geographical area a viral variant we named Marseille-4 harbors a S477 N substitution in this RBD. Materials and methods We aimed to implement an in-house one-step real-time reverse transcription-PCR (qPCR) assay with a hydrolysis probe that specifically detects the SARS-CoV-2 Marseille-4 variant. Results All 6 cDNA samples from Marseille-4 variant strains identified in our institute by genome next-generation sequencing (NGS) tested positive using our Marseille-4 specific qPCR, whereas all 32 cDNA samples from other variants tested negative. In addition, 39/42 (93 %) respiratory samples identified by NGS as containing a Marseille-4 variant strain and 0/26 samples identified as containing non-Marseille-4 variant strains were positive. Finally, 2018/3960 (51%) patients SARS-CoV-2-diagnosed in our institute, 10/277 (3.6 %) respiratory samples collected in Algeria, and none of 207 respiratory samples collected in Senegal, Morocco, or Lebanon tested positive using our Marseille-4 specific qPCR. Discussion Our in-house qPCR system was found reliable to detect specifically the Marseille-4 variant and allowed estimating it is involved in about half of our SARS-CoV-2 diagnoses since December 2020. Such approach allows the real-time surveillance of SARS-CoV-2 variants, which is warranted to monitor and assess their epidemiological and clinical characterics based on comprehensive sets of data.Introduction The SARS-CoV-2 pandemic has been associated with the occurrence since summer 2020 of several viral variants that overlapped or succeeded each other in time. Those of current concern harbor mutations within the spike receptor binding domain (RBD) that may be associated with viral escape to immune responses. In our geographical area a viral variant we named Marseille-4 harbors a S477 N substitution in this RBD. Materials and methods We aimed to implement an in-house one-step real-time reverse transcription-PCR (qPCR) assay with a hydrolysis probe that specifically detects the SARS-CoV-2 Marseille-4 variant. Results All 6 cDNA samples from Marseille-4 variant strains identified in our institute by genome next-generation sequencing (NGS) tested positive using our Marseille-4 specific qPCR, whereas all 32 cDNA samples from other variants tested negative. In addition, 39/42 (93 %) respiratory samples identified by NGS as containing a Marseille-4 variant strain and 0/26 samples identified as containing non-Marseille-4 variant strains were positive. Finally, 2018/3960 (51%) patients SARS-CoV-2-diagnosed in our institute, 10/277 (3.6 %) respiratory samples collected in Algeria, and none of 207 respiratory samples collected in Senegal, Morocco, or Lebanon tested positive using our Marseille-4 specific qPCR. Discussion Our in-house qPCR system was found reliable to detect specifically the Marseille-4 variant and allowed estimating it is involved in about half of our SARS-CoV-2 diagnoses since December 2020. Such approach allows the real-time surveillance of SARS-CoV-2 variants, which is warranted to monitor and assess their epidemiological and clinical characterics based on comprehensive sets of data. |
URI: | https://scholarhub.balamand.edu.lb/handle/uob/5289 | ISSN: | 13866532 | DOI: | 10.1016/j.jcv.2021.104814 | Ezproxy URL: | Link to full text | Type: | Journal Article |
Appears in Collections: | Faculty of Medicine |
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