Disturbed flow impairs MerTK-mediated efferocytosis in aortic endothelial cells during atherosclerosis

Abstract

Background: MER proto-oncogene tyrosine kinase (MerTK) is a key receptor for efferocytosis, a process for the clearance of apoptotic cells. MerTK is mainly expressed in macrophages and immature dendritic cells. There are very limited reports focused on MerTK biology in aortic endothelial cells (ECs). It remains unclear for the role of blood flow patterns in regulating MerTK-mediated efferocytosis in aortic ECs. This study was designed to investigate whether endothelial MerTK and EC efferocytosis respond to blood flow patterns during atherosclerosis. Methods: Big data analytics, RNA-seq and proteomics combined with our in vitro and in vivo studies were applied to reveal the potential molecular mechanisms. Partial carotid artery ligation combined with AAV-PCSK9 and high fat diet were used to set up acute atherosclerosis in 4 weeks. Results: Our data showed that MerTK is sensitive to blood flow patterns and is inhibited by disturbed flow and oscillatory shear stress in primary human aortic ECs (HAECs). The RNA-seq data in HAECs incubated with apoptotic cells showed that d-flow promotes pro-inflammatory pathway and senescence pathway. Our in vivo data of proteomics and immunostaining showed that, compared with WT group, MerTK^-/- aggravates atherosclerosis in d-flow areas through upregulation of endothelial dysfunction markers (e.g. IL-1β, NF-κB, TLR4, MAPK signaling, vWF, VCAM-1 and p22^phox) and mitochondrial dysfunction. Interestingly, MerTK^-/-induces obvious abnormal endothelial thickening accompanied with decreased endothelial efferocytosis, promoting the development of atherosclerosis. Conclusions: Our data suggests that blood flow patterns play an important role in regulating MerTK-mediated efferocytosis in aortic ECs, revealing a new promising therapeutic strategy with EC efferocytosis restoration to against atherosclerosis.

Keywords: Disturbed flow; MerTK; RNA-seq; atherosclerosis; efferocytosis; proteomics.

Figure 1

Efferocytosis in ECs and the role of d-flow in regulation of MerTK. (A) Epigenetic maps for MerTK expression in hematopoietic cells from healthy individuals based on IPA gene FPKM. (B) MerTK expression in vascular system based on IPA tissue GTEx. (C) Western blotting for MerTK expression in HAECs incubated with apoptotic Jurkat cells for 1 h. (D) Efferocytosis in HAECs incubated with apoptotic Jurkat cells for 1 h. Green cells: apoptotic Jurkat cells labeled with PKH67 Green Fluorescent Cell Linker Kit (PKH67GL-1KT, Sigma); Green/red small round cells: apoptotic Jurkat cells that were engulfed by HAECs; Large red cells: HAECs labeled with PKH26 Red Fluorescent Cell Linker Kit (PKH26GL-1KT, Sigma) according to the provided protocol. (E-F) Immunostaining for MerTK expression in HAECs incubated with apoptotic Jurkat cells for 30 min, 1 h or 2 h; or incubated with apoptotic Jurkat cells with a different ratio of 1:1, 3:1 or 5:1. (G) Immunostaining for MerTK expression in HAECs incubated with non-apoptotic or apoptotic Jurkat cells with a ratio of 3:1. (H-K) Efferocytosis and expression of p70s6k, EIF2α and EIF3A in HAECs subjected to OSS or in a static condition. (L) Effect of d-flow in regulation of MerTK and endothelial function in a step-flow chamber (12 ± 4 dynes/cm² for 1 h). (M) Effect of OSS (± 5 dynes/cm² with 1Hz in a µ-Slide I ^0.4 Luer for 1 h) in regulation of MerTK and endothelial function in an ibidi pump system. Statistical analyses were performed with GraphPad Prism 9.4.1 using a two-tailed unpaired t-test. Data represents mean ± SD (n=3-6).

Figure 2

RNA-seq in HAECs that are exposed to d-flow and incubated with apoptotic cells. (A) Graphical summary of RNA-seq data in HAECs exposed to d-flow or static conditions (orange: upregulated; blue: downregulated). (B) IPA comparative analysis between d-flow vs static and atherosclerosis based on activation z-score. (C) Expression of cytokines or chemokines in HAECs based on activation z-score. (D-E) Top 50 representative proteins upregulated or downregulated by d-flow in HAECs, based on activation z-score. (F) Endothelial function evaluation based on activation score. (G) Top ingenuity canonical pathways in HAECs based on activation z-score. HAECs were kept in static conditions or subjected to step-flow chamber with physiological laminar shear stress (12 ± 4 dynes/cm²) for 24 h and then were incubated for 1 h with PKH67-green linker-labeled apoptotic Jurkat cells at 3:1 ratio (apoptotic cells:HAECs). For HAECs in d-flow area, RNA was extracted from 5 randomly selected frozen specimens per experimental group and RNA-seq was done at UAMS Genomics Core using Next Generation Sequencing.

Figure 3

PCL surgery and atherosclerosis model in WT and MerTK^-/- mice. (A) Schematic diagram for acute atherosclerosis model combined with PCL surgery and AAV8-PCSK9 injection. (B) Westen blotting for MerTK expression in RCA or LCA from WT mice with PCL surgery. (C) Immunostaining for MerTK in the straight section of thoracic aorta and aortic arch. (D) Immunostaining for Caspase-3 in LCA from WT mice with PCL surgery. (E) Representative immunostaining for cleaved IL-1β and Caspase-3 in RCA and LCA from MerTK^-/- and WT mice, respectively. (F-J) Immunostaining for MerTK, Caspase-3, NF-kB, TLR4, vWF, VACAM-1 and p22^phox in aortic arch from MerTK^-/- and WT mice. Mice (n=5-7) were injected with one dose of AAV8-PCSK9, and PCL surgery was performed 1-week later. The mice were fed HFD for 4 weeks

Figure 4

Proteomics comparison of LCA vs. RCA in WT mice subjected to PCL surgery. (A) Volcano plot illustrating differentially expressed proteins in RCA and LCA. Relative protein abundance (log2) plotted against significance level (- log10 P-value), showing significantly (p < 0.05) downregulated (blue), upregulated (red) or non-differentially expressed proteins (gray). (B) Top 10 activated proteins based on Log2 fold change. (C) Graphical summary based on IPA. (D) Bubble chart for canonical pathways. (E-F) Top 50 representative proteins upregulated or downregulated in LCA compared to RCA based on activation z-score. (G) IPA analysis for microRNA in LCA vs. RCA. (H-K) Representative vascular functions and their related signaling.

Figure 5

Proteomics comparison of LCA vs. RCA in MerTK^-/- mice subjected to PCL surgery. (A) Volcano plot illustrating differentially expressed proteins in RCA and LCA. Relative protein abundance (log2) plotted against significance level (- log10 P-value), showing significantly (p < 0.05) downregulated (blue), upregulated (red) or non-differentially expressed proteins (gray). (B) Volcano plot illustration for top 10 changed proteins based on adjusted p value and Log2 fold change, which are detailed shown in (C). (D) Top 50 activated proteins based on activation z-score. (E-H) Representative activated proteins related to MAPK pathways based on activation z-score. (I) Top 50 inhibited proteins based on activation z-score. (J) Collagen-related proteins in LCA and RCA. (K) Overlapping networks in LCA compared to RCA.

Figure 6

Proteomics comparison in LCA from WT and MerTK^-/- mice subjected to PCL surgery. (A) Volcano plot illustrating differentially expressed proteins in LCA compared MerTK^-/- with WT. Relative protein abundance (log2) plotted against significance level (- log10 P-value), showing significantly (p < 0.05) downregulated (blue), upregulated (red) or non-differentially expressed proteins (gray). (B) Graphical summary for the down downregulated (blue) and upregulated (red) proteins. (C) Top 10 upregulated proteins based on Log2 fold-change. (D) To 10 downregulated proteins based on Log2 fold-change. (E) Upstream signaling for top 50 activated proteins based on activation z-score. (F) Upstream signaling for top 50 inhibited proteins based on activation z-score. (G) Canonical pathways based on -log (p value) shown as downregulated (blue) and upregulated (red) signaling. (H-I) Representative upregulated signaling such as JUN and FOS as well as downregulated signaling such as IL-4 and IL-4R. (J) IPA for disease pathways in LCA compared MerTK^-/- with WT.