scholarly journals Molecular evolution and genetic diversity analysis of SFTS virus based on next-generation sequencing

Author(s):  
Aqian Li ◽  
Lin Liu ◽  
Wei Wu ◽  
Yang Liu ◽  
Xiaoxia Huang ◽  
...  
2021 ◽  
Vol 11 (4) ◽  
pp. 20200063 ◽  
Author(s):  
Amanda Araújo Serrão de Andrade ◽  
André E. R. Soares ◽  
Luiz Gonzaga Paula de Almeida ◽  
Luciane Prioli Ciapina ◽  
Cristiane Pinheiro Pestana ◽  
...  

The live attenuated yellow fever (YF) vaccine was developed in the 1930s. Currently, the 17D and 17DD attenuated substrains are used for vaccine production. The 17D strain is used for vaccine production by several countries, while the 17DD strain is used exclusively in Brazil. The cell passages carried out through the seed-lot system of vaccine production influence the presence of quasispecies causing changes in the stability and immunogenicity of attenuated genotypes by increasing attenuation or virulence. Using next-generation sequencing, we carried out genomic characterization and genetic diversity analysis between vaccine lots of the Brazilian YF vaccine, produced by BioManguinhos–Fiocruz, and used during 11 years of vaccination in Brazil. We present 20 assembled and annotated genomes from the Brazilian 17DD vaccine strain, eight single nucleotide polymorphisms and the quasispecies spectrum reconstruction for the 17DD vaccine, through a pipeline here introduced. The V2IDA pipeline provided a relationship between low genetic diversity, maintained through the seed lot system, and the confirmation of genetic stability of lots of the Brazilian vaccine against YF. Our study sets precedents for use of V2IDA in genetic diversity analysis and in silico stability investigation of attenuated viral vaccines, facilitating genetic surveillance during the vaccine production process.


2018 ◽  
Vol 108 ◽  
pp. 26-31 ◽  
Author(s):  
Sana Saleem ◽  
Amjad Ali ◽  
Bushra Khubaib ◽  
Madiha Akram ◽  
Zareen Fatima ◽  
...  

PLoS ONE ◽  
2017 ◽  
Vol 12 (7) ◽  
pp. e0181279 ◽  
Author(s):  
Amanda D. Barbosa ◽  
Alexander W. Gofton ◽  
Andrea Paparini ◽  
Annachiara Codello ◽  
Telleasha Greay ◽  
...  

mSphere ◽  
2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Bei Li ◽  
Hao-Rui Si ◽  
Yan Zhu ◽  
Xing-Lou Yang ◽  
Danielle E. Anderson ◽  
...  

ABSTRACT Coronaviruses (CoVs) of bat origin have caused two pandemics in this century. Severe acute respiratory syndrome (SARS)-CoV and Middle East respiratory syndrome (MERS)-CoV both originated from bats, and it is highly likely that bat coronaviruses will cause future outbreaks. Active surveillance is both urgent and essential to predict and mitigate the emergence of these viruses in humans. Next-generation sequencing (NGS) is currently the preferred methodology for virus discovery to ensure unbiased sequencing of bat CoVs, considering their high genetic diversity. However, unbiased NGS is an expensive methodology and is prone to missing low-abundance CoV sequences due to the high background level of nonviral sequences present in surveillance field samples. Here, we employ a capture-based NGS approach using baits targeting most of the CoV species. Using this technology, we effectively reduced sequencing costs by increasing the sensitivity of detection. We discovered nine full genomes of bat CoVs in this study and revealed great genetic diversity for eight of them. IMPORTANCE Active surveillance is both urgent and essential to predict and mitigate the emergence of bat-origin CoV in humans and livestock. However, great genetic diversity increases the chance of homologous recombination among CoVs. Performing targeted PCR, a common practice for many surveillance studies, would not reflect this diversity. NGS, on the other hand, is an expensive methodology and is prone to missing low-abundance CoV sequences. Here, we employ a capture-based NGS approach using baits targeting all CoVs. Our work demonstrates that targeted, cost-effective, large-scale, genome-level surveillance of bat CoVs is now highly feasible.


2020 ◽  
Vol 11 ◽  
Author(s):  
Fen Wu ◽  
Hao Sun ◽  
Shaoxiong Lu ◽  
Xiao Gou ◽  
Dawei Yan ◽  
...  

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