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Single-cell analysis reveals an antiviral network that controls Zika virus infection in human dendritic cells.

Overview of attention for article published in Journal of Virology, April 2024
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

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Title
Single-cell analysis reveals an antiviral network that controls Zika virus infection in human dendritic cells.
Published in
Journal of Virology, April 2024
DOI 10.1128/jvi.00194-24
Pubmed ID
Authors

Kathryn M Moore, Adam-Nicolas Pelletier, Stacey Lapp, Amanda Metz, Gregory K Tharp, Michelle Lee, Swati Sharma Bhasin, Manoj Bhasin, Rafick-Pierre Sékaly, Steven E Bosinger, Mehul S Suthar

Abstract

Zika virus (ZIKV) is a mosquito-borne flavivirus that caused an epidemic in the Americas in 2016 and is linked to severe neonatal birth defects, including microcephaly and spontaneous abortion. To better understand the host response to ZIKV infection, we adapted the 10× Genomics Chromium single-cell RNA sequencing (scRNA-seq) assay to simultaneously capture viral RNA and host mRNA. Using this assay, we profiled the antiviral landscape in a population of human monocyte-derived dendritic cells infected with ZIKV at the single-cell level. The bystander cells, which lacked detectable viral RNA, expressed an antiviral state that was enriched for genes coinciding predominantly with a type I interferon (IFN) response. Within the infected cells, viral RNA negatively correlated with type I IFN-dependent and -independent genes (the antiviral module). We modeled the ZIKV-specific antiviral state at the protein level, leveraging experimentally derived protein interaction data. We identified a highly interconnected network between the antiviral module and other host proteins. In this work, we propose a new paradigm for evaluating the antiviral response to a specific virus, combining an unbiased list of genes that highly correlate with viral RNA on a per-cell basis with experimental protein interaction data. Zika virus (ZIKV) remains a public health threat given its potential for re-emergence and the detrimental fetal outcomes associated with infection during pregnancy. Understanding the dynamics between ZIKV and its host is critical to understanding ZIKV pathogenesis. Through ZIKV-inclusive single-cell RNA sequencing (scRNA-seq), we demonstrate on the single-cell level the dynamic interplay between ZIKV and the host: the transcriptional program that restricts viral infection and ZIKV-mediated inhibition of that response. Our ZIKV-inclusive scRNA-seq assay will serve as a useful tool for gaining greater insight into the host response to ZIKV and can be applied more broadly to the flavivirus field.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 25%
Student > Ph. D. Student 1 25%
Unknown 2 50%
Readers by discipline Count As %
Unspecified 1 25%
Immunology and Microbiology 1 25%
Unknown 2 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 05 April 2024.
All research outputs
#4,371,341
of 25,649,244 outputs
Outputs from Journal of Virology
#4,618
of 25,801 outputs
Outputs of similar age
#26,238
of 166,638 outputs
Outputs of similar age from Journal of Virology
#7
of 66 outputs
Altmetric has tracked 25,649,244 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 25,801 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.5. This one has done well, scoring higher than 82% 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 166,638 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 66 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.