Profiling Cell Signaling Networks at Single-cell Resolution

Abstract

Signaling networks process intra- and extracellular information to modulate the functions of a cell. Deregulation of signaling networks results in abnormal cellular physiological states and often drives diseases. Network responses to a stimulus or a drug treatment can be highly heterogeneous across cells in a tissue because of many sources of cellular genetic and non-genetic variance. Signaling network heterogeneity is the key to many biological processes, such as cell differentiation and drug resistance. Only recently, the emergence of multiplexed single-cell measurement technologies has made it possible to evaluate this heterogeneity. In this review, we categorize currently established single-cell signaling network profiling approaches by their methodology, coverage, and application, and we discuss the advantages and limitations of each type of technology. We also describe the available computational tools for network characterization using single-cell data and discuss potential confounding factors that need to be considered in single-cell signaling network analyses.

Keywords: Signaling circuits; assay development; pathway analysis; phosphoproteome; single-cell analysis; systems biology.

Graphical abstract

Fig. 1.

Signaling network heterogeneity in cell populations. A, Mutated signaling proteins (e.g., kinases) may cause genetic heterogeneity in a population of cells and leads to differential signaling networks. B, Non-genetic signaling network heterogeneity may origin from extrinsic factors including stimulus concentration, matrix stiffness, local crowdedness, oxygen and nutrient gradients, as well as the intrinsic noise. C, Signaling network heterogeneity results in phenotypical variances in a population of cells. Bulk analysis averages these variances, resulting in misinterpretation of cell signaling network behaviors and cell phenotypes.

Fig. 2.

Approaches to analyze cell signaling networks at single-cell resolution. Information on signaling network states in individual cells can be analyzed in cell suspension with mass cytometry, which allows simultaneous measurement of about 50 markers such as phosphorylation levels of signaling proteins and markers of cell phenotype. Single-cell RNA sequencing technologies allow transcriptomics profiling that can be used to infer cell signaling states. Multiplexed cell signaling profiling can be performed in situ with mass spectrometry-based imaging methods or with sequential immuno-based fluorescence imaging; these methods preserve spatial information. Live-cell imaging methods (e.g., kinase translocation reporters, FRET) can be used to monitor dynamic signaling behaviors in real time with single-cell resolution, although with lower multiplexing capability.