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Surveillance of emerging SARS-CoV-2 variants by nanopore technology-based genome sequencing 被引量:1
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作者 J.I.Abeynayake G.P.Chathuranga +1 位作者 M.A.Y.Fernando M.K.Sahoo 《Asian Pacific Journal of Tropical Medicine》 SCIE CAS 2023年第7期313-320,共8页
Objective:To surveill emerging variants by nanopore technology-based genome sequencing in different COVID-19 waves in Sri Lanka and to examine the association with the sample characteristics,and vaccination status.Met... Objective:To surveill emerging variants by nanopore technology-based genome sequencing in different COVID-19 waves in Sri Lanka and to examine the association with the sample characteristics,and vaccination status.Methods:The study analyzed 207 RNA positive swab samples received to sequence laboratory during different waves.The N gene cut-off threshold of less than 30 was considered as the major inclusion criteria.Viral RNA was extracted,and elutes were subjected to nanopore sequencing.All the sequencing data were uploaded in the publicly accessible database,GISAID.Results:The Omicron,Delta and Alpha variants accounted for 58%,22%and 4%of the variants throughout the period.Less than 1%were Kappa variant and 16%of the study samples remained unassigned.Omicron variant was circulated among all age groups and in all the provinces.Ct value and variants assigned percentage was 100%in Ct values of 10-15 while only 45%assigned Ct value over 25.Conclusions:The present study examined the emergence,prevalence,and distribution of SARS-CoV-2 variants locally and has shown that nanopore technology-based genome sequencing enables whole genome sequencing in a low resource setting country. 展开更多
关键词 Emerging SARS-CoV-2 variants Laboratory surveillance Nanopore technology Genome sequencing Bioinformatics analysis and phylogeny Sociodemographic and sample cutoff(Ct)threshold global sharing of genomic data/GISAID
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A Review on D 614G Mutation with Bangladesh Scenario
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作者 Arifa Akram Mohammad Jahidur Rahman Khan +4 位作者 Md. Bayzid Bin Monir Md. Reaz Uddin Chowdhury Mahmuda Yeasmin Md. Maruf Ahmed Molla Tasnim Nafisa 《Advances in Infectious Diseases》 2020年第3期249-255,共7页
With the COVID-19 pandemic, disparities between the infection rate and death rate in different countries become a major concern. In some countries, lower mortality rate compared to others can be explained by better te... With the COVID-19 pandemic, disparities between the infection rate and death rate in different countries become a major concern. In some countries, lower mortality rate compared to others can be explained by better testing capacity and intensive care facilities. Complete SARS-CoV-2 genome sequences from different countries of the world are continually submitted to Global Initiative for Sharing All Influenza Data using Next Generation Sequencing method. A SARS-CoV-2 variant with a D 614G Mutation in the spike (S) protein has become the most dominant form in the global pandemic. There are a number of ongoing studies trying to relate this mutation with the infectivity, mortality, transmissibility of the virus and its impact on vaccine development. This review aims to accumulate the major findings from some of these studies and focus its future implication. Some studies suggested D 614G strain has increased binding capacity, it affects more cells at a faster rate, so has a high transmissibility. Patients infected with this strain were found with high viral load. But still now there is no such evidence that this strain produces more severe disease as well as increased mortality. The structural change of spike protein produced by D 614G mutation was minor and did not hamper the vaccine efficacy. Some studies showed antibodies produced against D614 strain can neutralize G614 strain and <em>vice versa</em>. Whenever a mutation occurs in spike protein there are always chances of affecting the infectivity, transmissibility, vaccine efficacy. Therefore, more studies are required to find out the overall effect of D 614G mutation. 展开更多
关键词 CORONAVIRUS D 614G Mutation SARS-CoV-2 Spike Protein global Initiative for sharing All Influenza data (GISAID)
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