Covid-19: aspectos do diagnostico e vigilância genômica das linhagens circulantes no estado do Ceará

• Ano de defesa: 2022
• Autor(a) principal: Lima, Luina Benevides
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Genoma; Variação Genética; SARS-CoV-2; Pandemias; Prevalência
• Link de acesso: http://www.repositorio.ufc.br/handle/riufc/66201

SARS-CoV-2 virus emerged in December 2019 and has rapidly spread around the world. In January 2020, the first genome sequence was available, with approximately 30000 bases. Since then, the virus accumulated diverse mutations, leading to the emergence of different lineages. In this work, a review was carried out on the gold standard method for SARS-CoV-2 detection, addressing the factors that may contribute to the achievement of false negative or false positive results. An in-silico analysis identified the formation of primer and/or probe homodimers in the China CDC (ORF1ab target), Charité (E gene) and HKU (N gene) diagnostic kits; and heterodimers in the China CDC (N gene), Charité (E gene), and US CDC (N2 and N3 genes) kits, these being the kits more likely to generate false results. In this work, 34 genomes of SARS-CoV-2 were sequenced, from samples obtained between July/20 and July/21 in Ceará. These sequences, analyzed together with sequences deposited in the GISAID database in this period for Ceará, revealed the occurrence of 8 lineages between March and December 2020. The most prevalent strain was B.1.1.33 (n=45), followed by B.1 (n=21), B.1.212 (n=19) and P.2 (n=14). In this work, 202 SNVs (Single Nucleotide Variant) were identified among the 34 sequenced genomes. Mutations with >40% prevalence include p.F924F and p. P4715, both in ORF1ab; p.D614G in the S gene; p.I33T in ORF6; p.R203K, p.R203R, p.G204R and p.I292T in the N gene. The only mutation detected in 100% of our sequenced genomes was D614G in the S gene. Genomic surveillance of circulating lineages allows us to monitor the pandemic, assisting in government decision-making and in monitoring the virus. In GISAID database, few SARS-CoV-2 genomes come from samples collected in the first months of the pandemic in Ceará. Our data aim to fill these gaps and contribute to a better understanding of SARS-CoV-2 variants genetic diversity and their prevalence in Ceará.state.