CellCall: integrating paired ligand-receptor and transcription factor activities for cell-cell communication

Abstract

With the dramatic development of single-cell RNA sequencing (scRNA-seq) technologies, the systematic decoding of cell-cell communication has received great research interest. To date, several in-silico methods have been developed, but most of them lack the ability to predict the communication pathways connecting the insides and outsides of cells. Here, we developed CellCall, a toolkit to infer inter- and intracellular communication pathways by integrating paired ligand-receptor and transcription factor (TF) activity. Moreover, CellCall uses an embedded pathway activity analysis method to identify the significantly activated pathways involved in intercellular crosstalk between certain cell types. Additionally, CellCall offers a rich suite of visualization options (Circos plot, Sankey plot, bubble plot, ridge plot, etc.) to present the analysis results. Case studies on scRNA-seq datasets of human testicular cells and the tumor immune microenvironment demonstrated the reliable and unique functionality of CellCall in intercellular communication analysis and internal TF activity exploration, which were further validated experimentally. Comparative analysis of CellCall and other tools indicated that CellCall was more accurate and offered more functions. In summary, CellCall provides a sophisticated and practical tool allowing researchers to decipher intercellular communication and related internal regulatory signals based on scRNA-seq data. CellCall is freely available at https://github.com/ShellyCoder/cellcall.

Figure 1.

Overview of CellCall. (A) The schematic diagram of intercellular communication. (B) The biological model of intercellular communication. (C) The statistical model of intercellular communication. (D) CellCall provides a variety of functions including intercellular communication analysis and pathway activity analysis and offers a rich suite of visualization tools to intuitively present the results of the analysis, including heatmap, Circos plot, bubble plot, Sankey plot, TF enrichment plot and ridge plot.

Figure 2.

Case study of the application of CellCall on human testicular cells. (A) UMAP of 2532 human testicular cells. (B) Circos plot of intercellular communication from Sertoli cells to other germ cells. (C) Pathway activity analysis of intercellular communications from Sertoli cells to other germ cells. (D) The intercellular communications from Sertoli cells to other germ cells (normalized score greater than 0.5). (E) Sankey plot of intercellular communications from Sertoli cells to SSCs.

Figure 3.

Enrichment analysis of downstream TFs and immunofluorescence of the INHBB-ACVR2A/B-pSMAD2 axes. (A) Enrichment analysis of the six top TFs in SSCs. (B) Ridge plot of the density distribution of FC of TGs for the six TFs. (C) Dual immunofluorescence of VASA (red) and INHBB (green) in adult human testicular paraffin sections. (D) Dual immunofluorescence of ACVR2B (red) and INHBB (green) in adult human testicular paraffin sections. (E) Dual immunofluorescence of ACVR2B (red) and pSMAD2 (green) in adult human testicular paraffin sections. (F) Dual immunofluorescence of FGFR3 (red) and ACVR1B (green) in adult human testicular paraffin sections. Triangles and circles indicate SSCs, and arrows indicate Sertoli cells. The scale bars represent 10 μm.

Figure 4.

Analysis of intercellular communication from other germ cells to SSCs. (A) Circos plot of intercellular communication from other germ cells to SSCs. (B) The intercellular communications from other germ cells to SSCs (normalized score greater than 0.5). (C) Sankey plot of intercellular communications from P to SSCs. (D) The expression of GDF5, BMPR1B and SMAD1 across different cell types. (E) Dual immunofluorescence of γH2AX (red) and GDF5 (green) in adult human testicular paraffin sections. Dual immunofluorescence of BMPR1B (red) and GDF5 or pSMAD1 (green) in adult human testicular paraffin sections. Yellow triangles indicate P, white triangles and circles indicate SSCs. The scale bars represent 10 μm.

Figure 5.

Case study of the application of CellCall in the TIME. (A) Circos plot of intercellular communication among immune cells in the NSCLC dataset (GSE139555). (B) Common tumor-specific intercellular communications in 10 TIME datasets. (C) Intercellular crosstalk from other immune cells to Mono/Macro cells in the TIME. (D) Sankey plot of seven common tumor-specific intercellular communications and downstream TFs. (E) Association of TF expression with patient survival in the TCGA pan-cancer data. (F) Kaplan–Meier curves of selected TFs. Statistical significance and hazard ratios were calculated using multivariate Cox regression.

Figure 6.

Comparison of the performance of CellCall with CellPhoneDB, CellChat, iTALK and SingleCellSignalR on the scRNA-seq dataset of human testicular cells (from ST cells to SSCs). (A) UpSetR plot of results from the five tools with their own default cut-offs. (B) Comparison of the literature support rates of CellCall and four other tools (Fisher's exact test). (C) The ROC curves of these methods. (D) UpSetR plot of results from the five tools with their own optimal cut-point values (the black dots on the curves, which defined by Youden Index).