Transcriptomics, i.e., the quantification of cellular RNA transcripts, is a powerful way to gauge the physiological state of either bacterial or eukaryotic cells under a given condition. However, traditional approaches were unsuitable to measure the abundance of transcripts across kingdoms, which is relevant for biological processes such as bacterial infections of mammalian host cells. This changed with the establishment of "Dual RNA-seq," which profiles gene expression simultaneously in an infecting bacterium and its infected host. Here, we describe a detailed Dual RNA-seq protocol optimized for-but not restricted to-the study of human cell culture models infected with the Gram-negative model pathogen Salmonella Typhimurium. Furthermore, we provide experimental data demonstrating the benefits of some of the key steps of this protocol, including transcriptome stabilization (RNA fixation), FACS-based enrichment of invaded cells, and double rRNA depletion. While our focus is on data generation, we also include a section describing suitable computational methods to analyze the obtained datasets.
Keywords: Cell sorting; Dual RNA-seq; Fixation; Host-pathogen interaction; Infection; Noncoding RNA; RNA-seq; Salmonella; Transcriptomics; rRNA depletion.