Selected article for: "common cold and high level"

Author: Van Phan, Hoang; van Gent, Michiel; Drayman, Nir; Basu, Anindita; Gack, Michaela U.; Tay, SavaÅŸ
Title: Fixed single-cell RNA sequencing for understanding virus infection and host response
  • Cord-id: yys4jo5w
  • Document date: 2020_9_17
  • ID: yys4jo5w
    Snippet: Single-cell RNA sequencing studies requiring intracellular protein staining, rare-cell sorting, or pathogen inactivation are severely limited because current high-throughput methods are incompatible with paraformaldehyde treatment, a very common and simple tissue/cell fixation and preservation technique. Here we present FD-seq, a high-throughput method for droplet-based RNA sequencing of paraformaldehyde-fixed, stained and sorted single-cells. We used FD-seq to address two important questions in
    Document: Single-cell RNA sequencing studies requiring intracellular protein staining, rare-cell sorting, or pathogen inactivation are severely limited because current high-throughput methods are incompatible with paraformaldehyde treatment, a very common and simple tissue/cell fixation and preservation technique. Here we present FD-seq, a high-throughput method for droplet-based RNA sequencing of paraformaldehyde-fixed, stained and sorted single-cells. We used FD-seq to address two important questions in virology. First, by analyzing a rare population of cells supporting lytic reactivation of the human tumor virus KSHV, we identified TMEM119 as a host factor that mediates reactivation. Second, we studied the transcriptome of lung cells infected with the coronavirus OC43, which causes the common cold and also serves as a safer model pathogen for SARS-CoV-2. We found that pro-inflammatory pathways are primarily upregulated in abortively-infected or uninfected bystander cells, which are exposed to the virus but fail to express high level of viral genes. FD-seq is suitable for characterizing rare cell populations of interest, for studying high-containment biological samples after inactivation, and for integrating intracellular phenotypic with transcriptomic information.

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