Dengue and Zika viral infections affect millions of people annually and can be complicated by hemorrhage or neurological manifestations, respectively. However, a thorough understanding of the host response to these viruses is lacking, partly because conventional approaches ignore heterogeneity in virus abundance across cells. Stanford University engineers present viscRNA-Seq (virus-inclusive single cell RNA-Seq), an approach to probe the host transcriptome together with intracellular viral RNA at the single cell level. They applied viscRNA-Seq to monitor dengue and Zika virus infection in cultured cells and discovered extreme heterogeneity in virus abundance. They exploited this variation to identify host factors that show complex dynamics and a high degree of specificity for either virus, including proteins involved in the endoplasmic reticulum translocon, signal peptide processing, and membrane trafficking. The researchers validated the viscRNA-Seq hits and discovered novel proviral and antiviral factors. viscRNA-Seq is a powerful approach to assess the genome-wide virus-host dynamics at single cell level.
viscRNA-Seq quantifies gene expression and virus RNA from the same cell
(A to F) Experimental design: (A) human hepatoma (Huh7) cells are infected with dengue or Zika virus at time 0 at multiplicity of infection (MOI) 0 (control), 1, or 10, then (B) harvested at different time points, (C) sorted and lysed into single wells. (D) Both mRNA and viral RNA (vRNA) are reverse transcribed and amplified from each cell, then (E) cells are screened for virus infection by qPCR. (F) Libraries are made and sequenced on an illumina NextSeq with a coverage of ~400,000 reads per cell. (G) The fraction of cells with more than 10 virus reads increases with MOI and time, saturating at 48 hours post infection. (H) Distributions of number of virus reads (left) and expression of an example stress response gene (right) inside single cells, showing the different dynamics of pathogen replication and host response. Whereas virus content can increase 1,000 fold and shows no saturation, expression of DDIT3/CHOP saturates after a 10 fold increase.
Zanini F, Pu SY, Bekerman E, Einav S, Quake SR. (2018) Single-cell transcriptional dynamics of flavivirus infection. Elife [Epub ahead of print]. [abstract]