Integrated time-series analysis and high-content CRISPR screening delineate the dynamics of macrophage immune regulation [CROP-seq KO15]

Macrophages are innate immune cells involved in host defense. Dissecting the regulatory landscape that enables their swift and specific response to pathogens, we performed time-series analysis of gene expression and chromatin accessibility in murine macrophages exposed to various immune stimuli, and we functionally evaluated gene knockouts at scale using a combined CROP-seq and CITE-seq assay. We identified new roles of transcription regulators such as Spi1/PU.1 and JAK-STAT pathway members in immune cell homeostasis and response to pathogens. Macrophage activity was modulated by splicing proteins SFPQ and SF3B1, histone acetyltransferase EP300, cohesin subunit SMC1A, and mediator complex proteins MED8 and MED14. We further observed crosstalk among immune signaling pathways and identified molecular drivers of pathogen-induced dynamics. In summary, this study establishes a time-resolved regulatory map of pathogen response in macrophages, and it describes a broadly applicable method for dissecting immune-regulatory programs through integrative time-series analysis and high-content CRISPR screening. To complement our time series analysis of macrophage stimulation with a functional dissection of macrophage regulons, we utilized our CROP-seq method for pooled CRISPR screening with single-cell transcriptome readout to genetically perturb putative key regulators involved in the macrophage response. Furthermore, we augmented CROP-seq with a CITE-seq readout for 11 macrophage surface marker proteins. We validated this integrated CROP-seq and CITE-seq assay in a targeted screen of 15 regulatory proteins over the time course of Listeria infection. CROP-seq screening was performed in RAW 264.7 macrophages engineered to express Cas9. We delivered the CRISPR guide RNAs with a lentiviral vector at a multiplicity of infection of 0.1, in order to minimize the fraction of cells that may express more than one guide RNA. Moreover, to mitigate potential autocrine and paracrine effects of individual CRISPR perturbations, the guide RNA expressing cells were co-cultured with 90% of untransduced wildtype cells. The cells were challenged with Listeria infection and collected at three time points: 0 hours (prior to Listeria treatment), 2 hours, and 6 hours. CRISPR guide RNA expressing cells were purified via FACS and subjected to single-cell RNA-seq with specific enrichment for the guide RNAs that identify the CRISPR perturbations as part of the single-cell transcriptomes. We targeted regulatory genes involved in Listeria infection (Rela/p65), endogenous interferon response (Jak1, Tyk2, Stat1, Stat2, Irf9), macrophage differentiation (Spi1, Csf1r, Irf8), epigenetic regulation (Ep300, Hdac6, Kdm1b, Kdm6b), and cell stress response (Jun, Creb1). Each gene was targeted with four different guide RNAs, and we included 10% non-targeting guide RNAs as controls. In addition to the single-cell transcriptome readout and sequencing of expressed guide RNAs, we quantified 11 cell-surface proteins using a CITE-seq readout, which included the classical macrophage markers CD11b, CD14, CD115, CD163, and MAC2; activation markers CD64, CD69, CD80, and CD95; and immune checkpoints CD274/PD-L1 and CD172a.