Single cell analysis reveals an antiviral network that controls Zika virus infection in human dendritic cells.
Kathryn M MooreAdam-Nicolas PelletierStacey LappAmanda MetzGregory K TharpMichelle LeeSwati Sharma BhasinManoj K BhasinRafick-Pierre SékalySteven E BosingerMehul S SutharPublished in: bioRxiv : the preprint server for biology (2024)
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 10x 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 moDCs 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 (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. Our ZIKV-inclusive scRNA-seq assay will serve as a useful tool to gaining greater insight into the host response to ZIKV and can be applied more broadly to the flavivirus field.
Keyphrases
- zika virus
- single cell
- rna seq
- high throughput
- dengue virus
- dendritic cells
- aedes aegypti
- sars cov
- genome wide
- induced apoptosis
- immune response
- endothelial cells
- cell cycle arrest
- binding protein
- autism spectrum disorder
- cell proliferation
- electronic health record
- signaling pathway
- stem cells
- bone marrow
- bioinformatics analysis
- intellectual disability
- endoplasmic reticulum stress
- pregnant women
- regulatory t cells
- deep learning
- mesenchymal stem cells
- pi k akt