↓ Skip to main content

A next generation sequencing-based method to study the intra-host genetic diversity of norovirus in patients with acute and chronic infection

Overview of attention for article published in BMC Genomics, July 2016
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

Mentioned by

twitter
7 X users

Citations

dimensions_citation
25 Dimensions

Readers on

mendeley
50 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A next generation sequencing-based method to study the intra-host genetic diversity of norovirus in patients with acute and chronic infection
Published in
BMC Genomics, July 2016
DOI 10.1186/s12864-016-2831-y
Pubmed ID
Authors

Maria E. Hasing, Bart Hazes, Bonita E. Lee, Jutta K. Preiksaitis, Xiaoli L. Pang

Abstract

Immunocompromised individuals with chronic norovirus (NoV) infection and elderly patients are hypothesized to be reservoirs where NoV might accumulate mutations and evolve into pandemic strains. Next generation sequencing (NGS) methods can monitor the intra-host diversity of NoV and its evolution but low abundance of viral RNA results in sub-optimal efficiency. In this study, we: 1) established a next generation sequencing-based method for NoV using bacterial rRNA depletion as a viral RNA enrichment strategy, and 2) measured the intra-host genetic diversity of NoV in specimens of patients with acute NoV infection (n = 4) and in longitudinal specimens of an immunocompromised patient with chronic NoV infection (n = 2). A single Illumina MiSeq dataset resulted in near full-length genome sequences for 5 out of 6 multiplexed samples. Experimental depletion of bacterial rRNA in stool RNA provided up to 1.9 % of NoV reads. The intra-host viral population in patients with acute NoV infection was homogenous and no single nucleotide variants (SNVs) were detected. In contrast, the NoV population from the immunocompromised patient was highly diverse and accumulated SNVs over time (51 SNVs in the first sample and 122 SNVs in the second sample collected 4 months later). The percentages of SNVs causing non-synonymous mutations were 27.5 % and 20.5 % for the first and second samples, respectively. The majority of non-synonymous mutations occurred, in increasing order of frequency, in p22, the major capsid (VP1) and minor capsid (VP2) genes. The results provide data useful for the selection and improvement of NoV RNA enrichment strategies for NGS. Whole genome analysis using next generation sequencing confirmed that the within-host population of NoV in an immunocompromised individual with chronic NoV infection was more diverse compared to that in individuals with acute infection. We also observed an accumulation of non-synonymous mutations at the minor capsid gene that has not been reported in previous studies and might have a role in NoV adaptation.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 26%
Student > Ph. D. Student 9 18%
Student > Doctoral Student 5 10%
Student > Bachelor 5 10%
Student > Master 5 10%
Other 6 12%
Unknown 7 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 24%
Biochemistry, Genetics and Molecular Biology 9 18%
Immunology and Microbiology 8 16%
Environmental Science 2 4%
Veterinary Science and Veterinary Medicine 2 4%
Other 7 14%
Unknown 10 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 July 2016.
All research outputs
#13,566,023
of 23,881,329 outputs
Outputs from BMC Genomics
#4,717
of 10,793 outputs
Outputs of similar age
#182,453
of 355,903 outputs
Outputs of similar age from BMC Genomics
#99
of 233 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,793 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 54% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 355,903 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 233 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.