SSL5-AnxA5 Fusion Protein Constructed Based on Human Atherosclerotic Plaque scRNA-Seq Data Preventing the Binding of Apoptotic Endothelial Cells, Platelets, and Inflammatory Cells

Abstract

Background and aims: Coronary obstruction following plaque rupture is a critical pathophysiological change in the progression of stable angina (SAP) to acute coronary syndrome (ACS). The accumulation of platelets and various inflammatory cells on apoptotic endothelial cells is a key factor in arterial obstruction after plaque rupture. Through single-cell sequencing analysis (scRNA-seq) of plaques from SAP and ACS patients, we identified significant changes in the annexin V and P-selectin glycoprotein ligand 1 pathways. Staphylococcal superantigen-like 5 (SSL5) is an optimal antagonist P-selectin glycoprotein ligand 1 (PSGL1), while annexin V (AnxA5) can precisely detect dead cells in vivo. We constructed the SSL5-AnxA5 fusion protein and observed its role in preventing the interaction between apoptotic endothelial cells, platelets, and inflammatory cells. Methods: The scRNA-seq data were extracted from the Gene Expression Omnibus (GEO) database. Single-cell transcriptome analysis results and cell-cell communication were analyzed to identify the ACS and SAP cell clusters and elucidate the intercellular communication differences. Then, we constructed and verified a fusion protein comprising SSL5 and AnxA5 domains via polymerase chain reaction (PCR) and Western blot. The binding capacity of the fusion protein to P-selectin and apoptotic cells was evaluated by flow cytometry and AnxA5-FITC apoptosis detection kit, respectively. Furthermore, co-incubation and immunofluorescence allowed us to describe the mediation effect of it between inflammatory cells and endothelial cells or activated platelets. Results: Our analysis of the scRNA-seq data showed that SELPLG (PSGL1 gene) and ANNEXIN had higher information flowing in ACS compared to SAP. The SELPLG signaling pathway network demonstrated a higher number of interactions in ACS, while the ANNEXIN signaling pathway network revealed stronger signaling from macrophages toward monocytes in ACS compared to SAP. Competition binding experiments with P-selectin showed that SSL5-AnxA5 induced a decrease in the affinity of PSGL1. SSL5-AnxA5 effectively inhibited the combination of endothelial cells with inflammatory cells and the interaction of activated platelets with inflammatory cells. Additionally, this fusion protein exhibited remarkable capability in binding to apoptotic cells. Conclusions: The bifunctional protein SSL5-AnxA5 exhibits promising potential as a protective agent against local inflammation in arterial tissues, making it an excellent candidate for PSGL1-related therapeutic interventions.

Keywords: P-selectin; acute coronary syndrome; fusion protein; stable angina; superantigen-like 5.

Figure 1

Analysis of single-cell RNA sequencing data in the ACS and SAP groups. (A) UMAP plots showing cell clusters from the ACS and SAP groups. Each dot represents a single cell, color-coded by cluster identity. Cells from both the ACS and SAP groups are distributed across multiple clusters, representing different cell types. (B) Heatmap displaying the expression levels of marker genes across the identified clusters (0–16). (C) UMAP plot showing the annotation of major cell types across both the ACS and SAP groups. (D) Dot plot showing the expression of key marker genes across the identified cell types. (E) Uniform manifold approximation and projection (UMAP) plot showing the distribution of major cell types in the ACS and SAP groups. (F) Stacked bar plot displaying the proportion of different cell types in the ACS and SAP groups. Each bar represents the relative abundance of major cell types, allowing for a comparison of the cell composition between the two groups.

Figure 2

Comparative analysis of the signaling pathways between the ACS and SAP groups. (A) Bar plot comparing the relative information flow of the signaling pathways between the ACS (red) and SAP (blue) groups. Pathways are ranked based on their contribution to cell–cell communication. (B) Heatmap showing the overall signaling patterns for the ACS (left) and SAP (right) groups. Each square represents the communication strength between a source and a target cell type for a given pathway, with darker colors indicating stronger signaling interactions. (C) Heatmap of the outgoing signaling patterns, comparing the ACS (left) and SAP (right) groups. The signaling strength is color-coded, with darker green representing higher outgoing signaling levels for each cell type. (D) Circle plots showing the number of interactions between cell types in the ACS (left) and SAP (right) groups. The thickness of the lines represents the number of interactions, with thicker lines indicating stronger communication between cell types. (E) Network diagrams illustrating the SELPLG signaling pathway in the ACS (left) and SAP (right) groups. The lines represent interactions between different cell types, with the line thickness indicating the strength of the interaction. (F) Network diagrams illustrating the ANNEXIN signaling pathway in the ACS (left) and SAP (right) groups. (G) Heatmaps comparing the differential number of interactions (left) and the interaction strength (right) between cell types in the ACS and SAP groups. The color intensity represents the degree of difference, with red indicating higher interactions/strength in SAP and blue indicating higher values in ACS. (H) Heatmaps of the SELPLG signaling pathway showing the differential expression of signaling components between the ACS (left) and SAP (right) groups. The color intensity indicates the relative strength of the signaling, with red representing higher expression and blue representing lower expression.

Figure 3

The preparation and purification of SSL5-AnxA5. (A) Schematic illustration of the SSL5-AnxA5 sequence. (B) Agarose gel electrophoresis analysis of SSL5, linker, AnxA5 and SSL5-AnxA5. (C) SDS-PAGE analysis of nickel agarose affinity chromatography purification of SSL5-AnxA5, M: protein marker; 1: loading sample; 2: flow-through; 3: 20 mM imidazole elution fraction; 4–5: 50 mM imidazole elution fractions; 6: 500 mM imidazole elution fraction. (D) SDS-PAGE analysis of the final protein purification, M: protein marker; 1: target proteins. (E) Western blot analysis of the final protein purification, M: protein marker; 1: target proteins.

Figure 4

SSL5-AnxA5 binds to PSGL-1 and apoptosis cells. (A) The binding capacity of SSL5-AnxA5 to U937 cell-surface PSGL1. The dark purple area means the binding percentage of P-selectin with PSGL1 in the surface of U937. (B) Statistical results of the binding capacity of SSL5-AnxA5 to U937 cell-surface PSGL1 (n = 3, * p < 0.010; vs. saline group). (C) The binding capacity of SSL5-AnxA5 to apoptosis cells comparing to AnxA5. (D) Statistical results of the binding capacity of SSL5-AnxA5 to apoptosis cells comparing to AnxA5 (n = 3, * p < 0.010; vs. AnxA5 group).

Figure 5

SSL5-AnxA5 inhibits the interaction of inflammatory cells. (A) SSL5-AnxA5 inhibits interaction of the HUVECs and THP-1. (B) Statistical results of the inhibition capacity of SSL5-AnxA5 in different concentrations (n = 3, * p < 0.010; vs. saline group). (C) SSL5-AnxA5 against the combination of activated platelets with neutrophils. (D) SSL5-AnxA5 against the combination of activated platelets with monocytes. (E) Statistical results of combination between monocytes or neutrophils with platelets in different groups (n = 3, * p < 0.010; vs. saline group).