Single-cell RNA-sequencing and data processing

To generate single-cell gel beads in the emulsion (GEMs), single-cell suspensions were loaded onto a Chromium Controller (10x Genomics) using Chromium Next GEM Single Cell 3ʹ GEM kit v3.1. Approximately 3,000 target cells were recovered for each group, and a scRNA-seq library was constructed using Chromium Next GEM Single Cell 3ʹ Library Kit v3.1. All preparation steps were performed according to the manufacturer’s specifications. Constructed libraries were sequenced using an Illumina NovaSeq6000 (Illumina) with 150-bp paired-end reads. Sequencing data were processed using Cell Ranger software (v4.0.0) and aligned to the human reference genome GRCh37/hg19. Downstream analysis of filtered gene expression matrices was performed using the Seurat package (v4.0.1) running in R software (v4.0.5).

In the process of analysis, mitochondria-rich cells and cells with low UMI counts indicating low-quality cells were trimmed using the following criteria: 2.5 < mitochondria (%) < 9 and 2000 < nFeatureRNA < 6000. The trimmed data was normalized by “LogNormalize” method. The normalized data from each group of cells (control vs. infected) were then integrated by following the described at “https://satijalab.org/seurat/articles/integration_introduction.html”. The integrated dataset was further processed to cluster the cells using linear dimensional reduction (“RunPCA” function with default option) and nonlinear dimensional reduction (“RunUMAP” function with following option: dims = 1:30), followed by clustering analysis (“FindNeighbors” and “FindClusters” function with following option: dims = 1:30, resolution = 0.5).