Article open access publication

A universal primer-independent next-generation sequencing approach for investigations of norovirus outbreaks and novel variants

Scientific Reports, Springer Nature, ISSN 2045-2322

Volume 7, 1, 2017

DOI:10.1038/s41598-017-00926-x, Dimensions: pub.1084537955, PMC: PMC5429772, PMID: 28400558,

Affiliations

Organisations

  1. (1) State Serum Institute, grid.6203.7
  2. (2) University of Copenhagen, grid.5254.6, KU
  3. (3) University of Southern Denmark, grid.10825.3e, SDU

Countries

Denmark

Continents

Europe

Description

Norovirus (NoV) is the most common cause of non-bacterial gastroenteritis and is a major agent associated with outbreaks of gastroenteritis. Conventional molecular genotyping analysis of NoV, used for the identification of transmission routes, relies on standard typing methods (STM) by Sanger-sequencing of only a limited part of the NoV genome, which could lead to wrong conclusions. Here, we combined a NoV capture method with next generation sequencing (NGS), which increased the proportion of norovirus reads by ~40 fold compared to NGS without prior capture. Of 15 NoV samples from 6 single-genotype outbreaks, near full-genome coverage (>90%) was obtained from 9 samples. Fourteen polymerase (RdRp) and 15 capsid (cap) genotypes were identified compared to 12 and 13 for the STM, respectively. Analysis of 9 samples from two mixed-genotype outbreaks identified 6 RdRp and 6 cap genotypes (two at >90% NoV genome coverage) compared to 4 and 2 for the STM, respectively. Furthermore, complete or partial sequences from the P2 hypervariable region were obtained from 7 of 8 outbreaks and a new NoV recombinant was identified. This approach could therefore strengthen outbreak investigations and could be applied to other important viruses in stool samples such as hepatitis A and enterovirus.

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NORA University Profiles

University of Copenhagen

University of Southern Denmark

Danish Open Access Indicator

2017: Realized

Research area: Medicine

Danish Bibliometrics Indicator

2017: Level 1

Research area: Medicine

Dimensions Citation Indicators

Times Cited: 9

Field Citation Ratio (FCR): 1.91

Relative Citation ratio (RCR): 0.67

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