TITLE: “Quantifying response-specificity to diverse immune threats from single cell transcriptomes”
ABSTRACT: Innate immune sentinel cells such as macrophages upregulate over a thousand genes in the minutes to hours following an encounter with pathogen invaders or damage signals. Previous bulk transcriptomic studies suggest there is stimulus-specificity in the combinations of genes that are activated. However, bulk measurements do not reveal the distribution of responses, precluding a quantification of response-specificity. Here, we measure time-series single cell transcriptomic profiles of macrophages responding to diverse bacterial, viral, and host cytokine stimuli. We employ information theoretic and machine learning approaches to quantify how faithfully macrophage gene expression profiles relay information about the ligand encountered, and which genes are important for distinguishing ligands, based on their expression distributions across single cells. We find that microenvironmental context alters response-specificity, and thus quantifying response-specificity may identify marks of inflammatory disease.
