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Detection of SARS-CoV-2 Reinfections by Rapid Inexpensive Methods
ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY ; 10(1):44-48, 2022.
Article in English | Web of Science | ID: covidwho-1912237
ABSTRACT
New SARS-CoV-2 infections are difficult to be verified, whether they are reinfections or persistent infections. The most prominent factors used for differentiating reinfections from persistent infections are whole-genome sequencing and phylogenetic analyses that require time and funds, which may not be feasible in most developing countries. This study explores reinfections with COVID-19 that harbors D614G and N501Y mutations by rapid inexpensive methods. It exploits the previously developed rapid economic methods that identified both D614G and N501Y mutations in clinical samples using real-time reverse transcriptase polymerase chain reaction (rRT-PCR) probes and conventional PCR specific primers. In the present study, an immunocompetent patient has been found with a SARS-CoV-2 N501Y reinfection without comorbidities. According to the obtained results, this study suggests that the initial infection was due to a variant that contained only D614G mutation whereas the reinfection was potentially a result of alpha variant contained three mutations confirmed by DNA sequencing, including D614G, N501Y, and A570D mutations. These techniques will support rapid detection of SARS-CoV-2 reinfections through the identification of common spike mutations in the developing countries where sequencing tools are unavailable. Furthermore, seven cases of reinfections were also confirmed by these methods. These rapid methods can also be applied to large samples of reinfections that may increase our understanding epidemiology of the pandemic.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY Year: 2022 Document Type: Article