Deep sequencing approach for genetic stability evaluation of influenza A viruses

Bidzhieva, Bella; Zagorodnyaya, Tatiana; Karagiannis, Konstantinos; Simonyan, Vahan; Laassri, Majid; Chumakov, Konstantin

doi:10.1016/j.jviromet.2013.12.018

Cited by 7 publications

(14 citation statements)

References 33 publications

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“…It is important to mention different external sources of potential variation and bias, including sequencing (Ross et al, 2013), depth of coverage (Bidzhieva et al, 2014), PCR (Archer et al, 2012;Cummings et al, 2010) and sampling or intra-assay bias or error. The platform we used, i.e.…”

Section: Discussionmentioning

confidence: 99%

“…The 454 has proven to accurately detect human immunodeficiency virus mutants at a prevalence as low as 0.1 % (Shao et al, 2013). Nevertheless, the variability on NGS reads mapped and depth of coverage throughout the complete genome of IAVs remains an issue to better estimate the genetic diversity of the viral populations (Bidzhieva et al, 2014;Bourret et al, 2013). Additionally, PCR (especially when the polymerase is stalled) generates in vitro recombinants that inflate and distort the estimates of the number and structure of the true alleles (Cummings et al, 2010;S.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Genome plasticity of triple-reassortant H1N1 influenza A virus during infection of vaccinated pigs

Díaz

Enomoto

Romagosa

et al. 2015

Journal of General Virology

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To gain insight into the evolution of influenza A viruses (IAVs) during infection of vaccinated pigs, we experimentally infected a 3-week-old naive pig with a triple-reassortant H1N1 IAV and placed the seeder pig in direct contact with a group of age-matched vaccinated pigs (n510). We indexed the genetic diversity and evolution of the virus at an intra-host level by deep sequencing the entire genome directly from nasal swabs collected at two separate samplings during infection. We obtained 13 IAV metagenomes from 13 samples, which included the virus inoculum and two samples from each of the six pigs that tested positive for IAV during the study. The infection produced a population of heterogeneous alleles (sequence variants) that was dynamic over time. Overall, 794 polymorphisms were identified amongst all samples, which yielded 327 alleles, 214 of which were unique sequences. A total of 43 distinct haemagglutinin proteins were translated, two of which were observed in multiple pigs, whereas the neuraminidase (NA) was conserved and only one dominant NA was found throughout the study. The genetic diversity of IAVs changed dynamically within and between pigs. However, most of the substitutions observed in the internal gene segments were synonymous. Our results demonstrated remarkable IAV diversity, and the complex, rapid and dynamic evolution of IAV during infection of vaccinated pigs that can only be appreciated with repeated sampling of individual animals and deep sequence analysis.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Genome plasticity of triple-reassortant H1N1 influenza A virus during infection of vaccinated pigs

Díaz

Enomoto

Romagosa

et al. 2015

Journal of General Virology

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“…Deep sequencing-based methods have recently been proposed for the assessment of influenza A viruses diversity and rates of evolution [124–126], as well as antigenic stability [127] using complete influenza A genomes and exploiting the ability to detect and quantify mutations in heterogeneous viral populations. Others have focused on the evolution of avian influenza strains with potential to become pandemic in humans [128–132], as well as the detection of virulence signatures [133] and reassortment patterns [134].…”

Section: Applications In General Virologymentioning

confidence: 99%

Deep sequencing: Becoming a critical tool in clinical virology

Quiñones‐Mateu¹,

Ávila²,

Reyes‐Terán³

et al. 2014

Journal of Clinical Virology

115

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Population (Sanger) sequencing has been the standard method in basic and clinical DNA sequencing for almost 40 years; however, next-generation (deep) sequencing methodologies are now revolutionizing the field of genomics, and clinical virology is no exception. Deep sequencing is highly efficient, producing an enormous amount of information at low cost in a relatively short period of time. High-throughput sequencing techniques have enabled significant contributions to multiples areas in virology, including virus discovery and metagenomics (viromes), molecular epidemiology, pathogenesis, and studies of how viruses to escape the host immune system and antiviral pressures. In addition, new and more affordable deep sequencing-based assays are now being implemented in clinical laboratories. Here we review the use of the current deep sequencing platforms in virology, focusing on three of the most studied viruses: human immunodeficiency virus (HIV), hepatitis C virus (HCV), and influenza virus.

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“…Previously, it was demonstrated that deep sequencing can be used to monitor the genetic stability of oral polio vaccines, and could replace the WHO-recommended MAPREC assay for lot release of OPV [59]. Recently we showed that deep sequencing is suitable for evaluation of genetic consistency of influenza vaccine viruses [36,60].…”

Section: Methods Used For Evaluation Of Genetic Consistency Of Vaccinmentioning

confidence: 99%

“…The cost of deep sequencing has decreased to an affordable price due to the competition between vendors and the ability to analyze multiple samples run in one lane of the sequencing flow cell. This has allowed virologists to study a huge number of viral samples, including mixture of viral populations, and study lowlevel mutants in a wide range of viruses [36,[59][60][61].…”

Section: Description Of the Most Used Deep Sequencing Platformsmentioning

confidence: 99%

Application of the New Generation of Sequencing Technologies for Evaluation of Genetic Consistency of Influenza A Vaccine Viruses

Plant¹,

Zagorodnyaya²,

Rodionova³

et al. 2016

Steps Forwards in Diagnosing and Controlling Influenza

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For almost half a century, Sanger sequencing has been the conventional method for sequencing DNA. However, its utility for sequencing heterogeneous viral populations is limited because it can only detect mutations that are present in a significant portion of the DNA molecules. Several molecular methods that quantify mutations present at low levels in viral populations were proposed for evaluation of genetic consistency of viral vaccines; however, these methods are only suitable for single site polymorphisms, and cannot be used to screen for unknown mutations. Next-generation (deep) sequencing methods have enabled the determination of sequences of the entire viral population, including minority components. They enable not only sequencing, but also accurate quantification of mutations. This technique has great value for monitoring the genetic consistency of viral vaccines. Recently, a number of new deep sequencing platforms were introduced (MiSeq, Iron Torrent, etc.) that made such an analysis quite affordable for individual research labs. Here, we review the use of current deep sequencing approaches for influenza virus studies, focusing on the evaluation of the genetic consistency of influenza A vaccine viruses. We also describe a new bioinformatic tool to analyze deep sequencing data and identify artifacts from the true mutants.

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Deep sequencing approach for genetic stability evaluation of influenza A viruses

Cited by 7 publications

References 33 publications

Genome plasticity of triple-reassortant H1N1 influenza A virus during infection of vaccinated pigs

Genome plasticity of triple-reassortant H1N1 influenza A virus during infection of vaccinated pigs

Deep sequencing: Becoming a critical tool in clinical virology

Application of the New Generation of Sequencing Technologies for Evaluation of Genetic Consistency of Influenza A Vaccine Viruses

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