Single-cell transcriptomics to explore the immune system in health and disease

The immune system varies in cell types, states, and locations. The complex networks, interactions, and responses of immune cells produce diverse cellular ecosystems composed of multiple cell types, accompanied by genetic diversity in antigen receptors. Within this ecosystem, innate and adaptive immune cells maintain and protect tissue function, integrity, and homeostasis upon changes in functional demands and diverse insults. Characterizing this inherent complexity requires studies at single-cell resolution. Recent advances such as massively parallel single-cell RNA sequencing and sophisticated computational methods are catalyzing a revolution in our understanding of immunology. Here researchers at the Wellcome Trust Sanger Institute provide an overview of the state of single-cell genomics methods and an outlook on the use of single-cell techniques to decipher the adaptive and innate components of immunity.

 Inferring cellular trajectories from single-cell data

(A) During a differentiation process, individual cells can be aligned along “pseudotime,” which represents their progression within the differentiation pathway. The processes described in this way can be linear or can involve branches to multiple eventual fates. (B) Examples of biological processes analyzed in terms of cellular trajectories include the progression of stem cells to terminally differentiated fates, the response of naïve immune cells to infection, and the adaptation of circulating immune cells to the tissues where they ultimately reside. (C) A bifurcating pseudotime trajectory inferred from scRNA-seq data generated from a mouse malaria infection model.