Innate Immune Cells Activating Receptors Are Crucial Factors Regulating Inflammation and Cell Death in Traumatic Brain Injury

doi:10.21203/rs.3.rs-2612464/v1

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Innate Immune Cells Activating Receptors Are Crucial Factors Regulating Inflammation and Cell Death in Traumatic Brain Injury

https://doi.org/10.21203/rs.3.rs-2612464/v1

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After traumatic brain injury (TBI), excessive or persisting inflammatory responses often lead to neuronal death and chronic traumatic encephalopathy. However, effective targeted drugs for this mechanism are lacking. Therefore, comprehensive understanding of neuroinflammatory response mechanisms and search for new therapeutic targets are particularly important for neurological function recovery after brain trauma. In this study, we collated and analyzed multiple RNA expression profiling microarray, bulk RNA high throughput sequencing and single-cell sequencing data. The results revealed that after TBI, there was an infiltration of innate immune cells into brain tissue, with a significantly higher proportion of macrophages in the cortex and hippocampus compared to the thalamus and hypothalamus. The inflammatory response was strongest within one week, then gradually decreased in the following month, and aggravated again three months later. After brain trauma, CD86, CCR5, PTPRC, ITGB2, FCGR2B, TLR2, and TYROBP were identified as the seven key nodes that trigger inflammation. Interestingly, all these proteins are activating receptors or cofactors on the surface of innate immune cells. Clustering analysis revealed that these immune activating receptors can collectively regulate the occurrence of TBI-induced cell death. Among them, ferroptosis, necrosis and apoptosis were most strongly correlated with these activating receptors, while autophagy was negatively correlated with them. In single-cell analysis, microglia, monocytes and dendritic cells were found to be the main subjects expressing these immune node genes. Cell-cell communication of chemokine-related pathways such as CXC chemokine ligand (CXCL) and CC chemokine ligand (CCL) dominate the immune response after brain trauma, and tumor necrosis factor (TNF), vascular endothelial growth factor (VEGF) and transforming growth factor b (TGF-b) are also involved in the process of inflammation.

Biological sciences/Neuroscience/Cell death in the nervous system

Biological sciences/Neuroscience/Neuroimmunology

Innate Immune Cell

Ferroptosis

Necrosis

Apoptosis

Traumatic Brain Injury

Cytokine Receptor

Traumatic brain injury (TBI) is a global public health problem. Severe TBI is characterized by high disability and fatality rates, with nearly 60% of survivors experiencing sequelae such as neurological and psychiatric diseases, psychological disorders, etc., which places a significant burden on society and families¹. Following brain trauma, the stress response pathway in the damaged area and surrounding tissues is activated, leading to neuroinflammation, excitatory amino acid toxicity, mitochondrial dysfunction, oxidative stress, calcium overload, and damage to the blood-brain barrier (BBB), resulting in immediate cerebral ischemia, edema, cytotoxic swelling, and increased intracranial pressure. Among these factors, inflammation is an important contributor to the expansion of nervous system damage.

Neuroinflammation involves cellular and molecular regulation mechanisms, including the activation of microglia and astrocytes, which causes the release of cytokines in the brain and the recruitment of peripheral immune cells. Neuroinflammation after injury has both positive and negative effects. It can not only protect the central nervous system from infection and damage, remove cell fragments, promote the differentiation of glial cells, regenerate blood vessels and restore nerve function, but also is an important reason for secondary injury after brain trauma. In case of brain trauma, the microenvironment in the brain changes, causing the polarization of microglia, thereby promoting the production of chemokines, proinflammatory factors and reactive oxygen species (ROS), leading to the increase of cellular phagocytosis, and enhancing inflammatory response through Notch signal pathway². Heme oxygenase-1 secreted by macrophage cells decomposes heme to produce iron, heme and carbon monoxide, thus promoting oxidative stress reaction, increasing the content of free radicals in mitochondria, inhibiting cell respiration, leading to the destruction of BBB and aggravation of brain damage². After brain injury, astrocytes can also be activated by nuclear factor kappa B (NF- κB) signal pathway aggravates brain cell swelling^{3, 4}. Activated oligodendrocytes can promote the aggregation of inflammatory cells such as neutrophils by secreting CXCL and CCL family chemokines and aggravate the inflammatory damage. It can also increase the permeability of BBB and induce macrophage and neutrophil infiltration by secreting MMP-9. Oligodendrocytes can also secrete collagenase, metalloproteinase, tumor necrosis factors, proinflammatory cytokines aggravating BBB damage and nerve cells death⁵.

During the pathological process of TBI, multiple modes of cell death occur simultaneously. Necrosis represents the initial stage of brain injury, and it is characterized by the widespread release of immunogenic substances that trigger inflammatory cascade reactions. This process involves activating glial cells, increasing the permeability of the BBB, and releasing ROS, cytokines, and chemokines. Apoptosis is a key link in the pathological process of TBI, as it determines the outcome of damaged neurons and nerve cells. Inhibiting neuronal apoptosis can alleviate secondary brain injury after trauma. Autophagy is another process that can help maintain cell stability and remove damaged proteins or organelles, but it is also a double-edged sword.

Excessive autophagy can also lead to cell death⁶. Ferroptosis is a newly identified non-apoptotic cell death mode that is characterized by the excessive accumulation of lethal iron and ROS in cells and the depletion of endogenous ferroptosis inhibitors, such as reduced glutathione (GSH), glutathione peroxidase 4 (GPX4), or vitamin E. In recent years, studies have shown that ferroptosis is closely related to nervous system diseases and shares similarities in the mechanism⁷. Some researchers have pointed out that ferroptosis is involved in the TBI process, and the use of ferroptosis inhibitors can alleviate the disease progression⁸. Pyroptosis is a typical pro-inflammatory programmed cell death that is characterized by the GSDMD protein molecules forming pores in the cell membrane, leading to cell lysis and death, the release of inflammatory factors, and the induction of a strong inflammatory response⁹. The occurrence of various central nervous system diseases, including traumatic brain injury, Alzheimer's disease (AD), and multiple sclerosis (MS), is closely related to pyroptosis¹⁰.

To sum up, immune homeostasis is a key factor affecting the prognosis of TBI. Excessive inflammatory response can lead to various forms of cell death and irreversible brain damage. In this study, we deeply explored changes of neuroimmune microenvironment after brain trauma and the role of different cell death pathways by integrating microarray, bulk RNA sequencing and single-cell RNA sequencing data sets, in order to find an effective therapeutic strategy and theoretical reference for the precise treatment of TBI (Fig. 1).

1. Data sorting and difference analysis

We retrieved RNA expression profiling microarray and high throughput sequencing datasets related to TBI from the GEO database (https://www.ncbi.nlm.nih.gov/geo). The samples were obtained from a mouse model, with the control group (Sham) undergoing craniotomy and sham surgery, and the TBI group receiving hydraulic shocks, free fall shocks, or similar interventions after craniotomy. We identified a total of 8 RNA sequencing datasets (GSE192979, GSE173975, GSE167459, GSE163415, GSE173431, GSE144193, GSE129927, GSE79441) and 2 microarray datasets (GSE180811, GSE71846) for further analysis.

The sequencing data was imported into the R project platform, and the ComBat function in the sva package was applied to integrate eight sequencing datasets to eliminate batch effects. The normalizeBetweenArrays function was applied to calibrate each sample. The DESeq2 package was applied for difference analysis. P-value < 0.05 and logFC > 0.5 were considered as the boundary of significant difference. After the batch effect was eliminated, the two microarray datasets were analyzed using the limma package.

The heatmap was generated using the pheatmap function in the ComplexHeatmap package, while the volcano plot was created using the tools available on the chiplot website (https://www.chiplot.online).

2. Enrichment analysis

Integrated differentially expressed genes in TBI obtained from sequencing and microarray datasets in the previous step were imported into MetaScape (https://metascape.org) database (Version is 2022-10-01) for enrichment analysis.

Pathway and process enrichment analysis were carried out with the following ontology sources: KEGG Pathway, GO Biological Processes, Reactome Gene Sets, Canonical Pathways, CORUM, WikiPathways and PANTHER Pathway. Terms with a P-value < 0.01, a minimum count of 3, and an enrichment factor > 1.5 are collected and grouped into clusters based on their membership similarities¹¹.

To further capture the relationships between the terms, a subset of enriched terms has been selected and rendered as a network plot, where terms with a similarity > 0.3 are connected by edges.

Then we applied STRING, BioGrid, OmnIPath and InWeb IM databases to detect the protein-protein interaction (PPI) of the obtained terms, and built a visual network. The Molecular Complex Detection (MCODE) algorithm was applied to identify densely connected network components.

3. Immune infiltration score

The RNA sequencing data was processed and normalized into transcripts per million (TPM) format for downstream analysis. We employed the CIBERSORT package to analyze the type and proportion of immune cell infiltration in the brain tissue samples, and the ggpubr package was used for visualizing the results. To evaluate the overall degree of immune infiltration in each sample, we also calculated the ESTIMATE score.

The sequencing data set was divided into brain injury group (TBI) and sham operation group (Sham) according to the processing method. The data set was divided into one week group, one month group and three months group according to the detection time after processing. Then, the data set was divided into cortex group, thalamus group, hypothalamus group and hippocampus group according to tissue type. T test was applied to evaluate the significance of the difference between groups.

4. Weighted gene co-expression network analysis

The process of inflammatory response after brain trauma requires the cooperation of multiple immune-related genes. To identify the co-expressed gene group that is most closely related to neuroinflammation after brain trauma and reveal the key links of the immune mechanism, we applied the weighted gene co-expression network analysis (WGCNA) method¹².

According to the steps provided by WGCNA package in R language, the following steps were carried out in sequence: input and clean data, remove missing values, outliers and redundant data, associate visual phenotypic data with gene expression data, construct sample clustering tree, construct network and module detection, screen appropriate soft threshold and average connectivity, associate modules with phenotypic data and identify important gene groups.

To further screen genes that is crucial to immune regulation in TBI, the gene set identified by WGCNA was constructed in the String database in advance to construct a PPI network. The minimum required interaction score was set to high confidence. Key genes with node degree ≥ 5 were selected for the next step of cluster analysis.

5. Cell death

Five cell death related gene sets were obtained from GSEA database (https://www.gsea-msigdb.org), including: Apoptosis (ALCALA_APOPTOSIS. v2022.1. Hs), Necrosis (GOBP_NECROSIS. v2022.1. Hs), Autophagy (GOBP_ AUTOPHAGY. v2022.1. Hs), Ferroptosis (WP_FERROPTOSIS. v2022.1. Hs) and Pyroptosis (GOBP_PYROPTOSIS. v2022.1. Hs). According to the difference of expression level of these gene sets in sequencing data, five forms of cell death scores after brain trauma were constructed (Fig. 7F). Cell death score was applied to compare the difference of cell death degree and mode between Sham group and TBI group. The samples of TBI group were further divided into several sub-groups according to the detection time and tissue type, and the differences between groups were compared by cell death score. T test was applied to evaluate the significance of the difference between groups.

6. Cluster analysis

The purpose of cluster analysis was to group TBI samples based on the immune-related gene set obtained previously and to perform correlation analysis between immune-related genes and cell death score. Cluster analysis was performed using the ConsensusClusterPlus package¹³ in the R project platform. First, the matrix was normalized based on the selected genes. Subsequently, the ConsensusClusterPlus function was applied for consensus clustering. Then, cluster consensus and item consensus matrices were constructed, and visual results were generated. Finally, a group-cell death mode box plot was created, and a t-test was used to assess the differences in cell death among groups.

7. Single-cell sequencing analysis

Three single-cell sequencing datasets (GSE180862, GSE160763, GSE101901) of TBI were obtained from GEO database. Quality control was performed on the data set obtained. The quality control parameters were: nFeature RNA > 200, nFeature RNA < 2500 and percent mt < 5. After integrating the above data sets with the merge function, the Harmony method was applied to remove the batch effect, and the tSNE method was applied to reduce dimension. In order to refine microglia subgroups and analyze the role of different subgroups in TBI, a proposed time-series analysis of microglia was conducted in the TBI group using the monocle2 package. AverageExpression function was used to integrate the gene expression of each cell in each cluster, and subsequently, GSVA was used to analyze differences in biological processes between clusters, and the results were presented as heat maps. Gene expression-Pseudotime plots were constructed by the plot_genes_in_pseudotime function to further explore the role played by immune cell surface activating receptors at different times after brain trauma¹⁴. The rest of the data sorting steps follow the standard process of the Seurat package¹⁵. FeaturePlot function was applied to draw the distribution map of immune key node genes among cells, and VlnPlot function was performed to draw the violin map of key node gene distribution differences. Gene set variation analysis (GSVA) was applied to evaluate the difference of gene expression between Sham group and TBI group, and enrichment analysis was conducted according to KEGG data set.

8. Cell-cell communication analysis

CellChat¹⁶package in R project platform was applied for cell communication analysis. The sorted single-cell data were divided into Sham group and TBI group, and the gene expression matrix and meta data were derived, respectively. The createCellChat function was performed to build the CellChat object for subsequent analysis.

After loading the CellChatDB-mouse database, the "Secreted Signaling" sub-database was selected to evaluate the intercellular communication. The following steps were carried out according to the CellChat standardized process, and the cell communication results were saved. In addition, the mergeCellChat function was applied to merge the two CellChat datasets for subsequent analysis.

The compareInteractions function was applied to analyze the total number and strength of interactions between the two groups of cells. Changes in communication between innate immunocyte and central nervous system cells were highlighted. RankNet function was used to analyze the difference of enrichment degree of intercellular communication pathway between the two groups. NetVisual_diffInteraction function showed the changes of cell communication in TBI group compared with Sham group.

The hierarchy plot constructed by netVisual_individual function showed an overview of the inferential intercellular communication network of each signal pathway or ligand receptor pair. The direction and strength changes of CCL pathway signal transduction were emphatically analyzed. The identified Communication Patterns function was performed to analyze how multiple cell populations and signal pathways work in harmony, and the netAnalysis_river function was applied to build a visual Sankey diagram.

1. Data sorting and difference analysis

Based on the 8 RNA sequencing datasets retrieved from the GEO database, all the datasets were processed into Counts format for differential analysis. The results showed that there were some differences in the total amount of expression among the different datasets and samples prior to standardization (Fig. 2A). However, after standardization, the differences between datasets were eliminated, and the total expression amount of each sample was essentially equal (Fig. 2B).

The DESeq2 package was applied for differential analysis of RNA sequencing data set, and 103 differentially expressed genes were obtained, including 40 down regulated genes and 63 up regulated genes after brain trauma (Fig. 2CD). The most significant differentially expressed genes between Sham group and TBI group included CCL13, TREM1, CXCL2, SELE, etc.

2 microarray datasets were analyzed by the limma package, and a total of 135 differentially expressed genes were obtained. The most significant differential genes included PPBP, CD77, LIF, CCL12, etc. (Fig. 2EF). Among them, 10 differential genes appear in both RNA sequencing gene sets and microarray gene sets, including: CCL13, CXCL2, MARCO, IL1R2, CXCR2, SELL, TREM1, C4A, C4B and S100A8. (Fig. 2G). TREM1, MARCO, IL1R2 and CXCR2 are activating receptors expressed on neutrophils, monocytes and macrophages. SELL, CXCL2 and CCL13 are adhesion molecules and chemokines of immune cell. C4A and C4B play a role in complement activation, promoting phagocytosis, preventing immune complex deposition and neutralizing viruses. S100A8 mainly mediates intracellular inflammatory signal transduction by activating Toll like receptors.

2. Enrichment analysis

The results of Metascape enrichment analysis showed that the pathways with the strongest correlation with the differential gene set obtained in the previous step are inflammatory response (GO: 0006954), Cytokine Signaling in Immune system (R-HSA-1280215), Cytokine receptor interaction (hsa04060) and positive regulation of cytokine production (GO: 0001819) (Fig. 3A). These results indicated that after brain trauma, immune response related pathways are fully activated, and cytokine mediated intercellular communication is crucial in the process of inflammatory.

The purpose of building a network of enriched terms was to show the interaction between each signal path more intuitively. The results showed that the most important nodes in the network were positive regulation of the response to external stimulus and positive regulation of leukocyte activation. The enrichment of terms related to NF-kappa B signaling pathway and neutral precipitation was also noteworthy (Fig. 3B). In the following picture, the nodes of the Network of enriched terms were colored with P-values. The results demonstrated that the relevance of most terms in the network was highly reliable (Fig. 3C).

In order to further analyze the interactions of differential genes at the protein level, we carried out protein-protein interaction enrichment analysis. The MCODE algorithm was performed to divide the nodes in the PPI network into 10 modules (sorted by importance). For example, Module 1 was Signaling by Interleukins. Module 2 was Cytokine-cytokine receptor interaction. Module 3 was MyD88 deficiency (TLR2/4). Module 4 was RHO GTPases Activate NADPH Oxidases.et.al. (Fig. 3DE). Therefore, we verified the interaction of immune response related factors at the protein level, and found that the imbalance of oxidative stress is also an important part of the pathological results of TBI.

3. Immune infiltration score

The Estimate method was applied to evaluate the overall level of immune infiltration. We found that the total score of TBI group was higher than Sham group in the three evaluation methods of Estimate, Immune signature and Strategic signature, which means a higher level of immune cell infiltration. (Fig. 4A).

By time grouping, the degree of immune infiltration reached a peak within one week after brain trauma, and gradually decreased within one month. With the brain injury entering the chronic phase of the 2-3 months, the immune infiltration gradually increased again (Fig. 4B). In terms of tissue type, the hippocampus has the highest immune score, followed by the cerebral cortex. The immune scores of thalamus and hypothalamus were low, and there was no significant difference between TBI and Sham group in these parts (Fig. 4C).

CIBERSORT analysis showed that compared with Sham group, the proportion of macrophages (M1, M2), Neutrophils and plasma cells in TBI group increased significantly, while the proportion of Tregs cells (Tregs) and follicular helper T cells (Tfh) decreased relatively (Fig. 4D).

The proportion of macrophages in cortex and hippocampus was significantly higher than that in thalamus and hypothalamus. The proportion of Treg cells was lower in cortex and hippocampus. However, mast cells in hypothalamus were significantly enriched (Fig. 4E).

4. Weighted gene co-expression network analysis

After sorting out, we found that the collected data did not have missing values or outliers. After building the automatic network and detection module, the system recommends a soft threshold of 15. As shown in the figure (Fig. 5A), when the soft threshold is 15, the downward trend of the curve tends to be gentle, indicating that the average connectivity is good. Using the blockwiseModules function, 228 differentially expressed genes were classified into 7 co-expressed modules and a hierarchical clustering tree diagram of module identification was drawn (Fig. 5B). The module-phenotype data association showed that the turquoise module has the highest correlation with the immune score (Fig. 5CD). This module included 29 co-expressed genes such as LYZ, TYROBP, CDK1, PDCD1 and RGS1. Subsequently, we constructed a GS-MM histogram for the co-expressed genes in turquoise group. The results demonstrated that genes in the group had good correlation with other genes in the group (module membership) and with immune score (gene significance) (Fig. 5EFG).

The gene set of immune related modules obtained from WGCNA analysis was imported into String database for PPI network analysis, and the results verified the relevance of these genes and their role in immune response. We screened the key node genes with more than 4 connections. As a result, seven key nodes were found, namely, CD86, CCR5, PTPRC, ITGB2, FCGR2B, TLR2, TYROBP (Fig. 6E).

5. Cell death

Most researchers believe that brain injury leads to death of nerve cells through variety ways. We selected apoptosis, necrosis, autophagy, ferroptosis and pyroptosis as the five most common cell death pathways for evaluation.

The results demonstrated that the total cell death index of TBI group was significantly higher than Sham group (Fig. 6A).

At the beginning of the establishment of model, the death rate of brain cells in mice gradually increased, the cell death index rose to the highest within one month, and gradually decreased in 2-3 months (Fig. 6B). Among them, the cell death index of cerebral cortex, hippocampus and thalamus was higher, while the cell death score of hypothalamuses was lower (Fig. 6C). Apoptosis and pyroptosis were the main brain cell death modes after brain trauma (Fig. 6D). However, the score of autophagy in TBI group was lower than that in Sham group. It can be seen that cell death is the most serious within one month after brain trauma, which is the key period for treatment. Apoptosis and pyroptosis are the main forms of cell death after brain trauma, from which we can find the key targets for treatment. Activating autophagy pathway will enhance the tolerance of nerve cells to the harsh environment of injury, hunger and oxidative stress, so it is considered as a possible effective strategy.

6. Cluster analysis

The ConsensusClusterPlus method was performed to construct a consistency matrix for each grouping number (K) value. The results showed that when K = 2, cluster assignments were stable. When K > 2, the new clusters were very small, and mixed color blocks appeared around them. This shows that the data should be divided into two groups to cover most of the characteristics of the data set, and the grouping is relatively stable (Fig. 7A). Empirical cumulative distribution (CDF) plots display consensus distributions for each K. When K is between 2 and 4, the data results are relatively stable (Fig. 7BC).

After grouping, the expression of each gene is displayed by heat map (Fig. 7D). We found that the expression of each immune key node gene in group 1 was significantly higher than that in group 2. The cell death scores of the two groups were compared. The results demonstrated that the ferroptosis, necrosis, and pyroptosis score in group 2 was significantly higher than that in group 1, while the autophagy score was lower than that in group 1 (Fig. 7E).

This showed that the immune related node genes in TBI were involved in the process of ferroptosis, necrosis and pyroptosis of the nervous system after brain trauma, and it were negatively correlated with autophagy.

7. Single-cell sequencing analysis

We integrated three single-cell sequencing data sets of TBI and carried out quality control. The Harmony method was applied to eliminate the batch effect of components (Fig. 8C). Finally, we obtained the sequencing data of 37621 high-quality cells. The tSNE method was applied for dimension reduction. According to the selected marker genes, the sequencing samples were classified into 12 cell types (Fig. 8B). The results showed that the proportion of microglia and macrophages in TBI group increased significantly (Fig. 8A), indicating that the inflammatory process of TBI could jointly participated by monocyte macrophage system and microglia.

Pseudotime analysis revealed that after brain trauma, microglia evolved through 3 nodes and then differentiated in two different directions (Fig. 8D). According to the nodes of differentiation, monocle2 divided microglia into 7 clusters (Fig. 8D). GSVA results revealed that the RESPONSE TO CGMP pathway was most active in cluster 1. The EOSINOPHIL DIFFERENTIATION, MATURE RIBOSOME ASSEMBLY, and NEGATIVE REGULATION OF INTERLEUKIN 6 MEDIATED SIGNALING PATHWAY pathways were generally active in clusters 2-5. Cluster 6 and cluster 7 represent two directions of microglia evolution, which differ in REGULATION OF MACROPHAGE FUSION, NEGATIVE REGULATION OF INTERLEUKIN 1 ALPHA PRODUCTION and NEGATIVE REGULATION OF INTERLEUKIN 6 MEDIATED SIGNALING PATHWAY (Fig. 8E). Gene expression analysis showed that the expression of immune cell surface activating receptors CCR5, FCGR2B, LTGB2, PTPRC and TLR2 increased with time after traumatic brain injury, and after a plateau period, the expression increased again. These results are consistent with the previously found trend of inflammatory response over time after traumatic brain injury. CD86 expression began to increase only in the mid to late post-traumatic brain injury period. However, TYROBP expression remained stable (Fig. 8F).

We analyzed the distribution analysis of immune related key node genes in TBI obtained previously. The results indicated that these genes were mainly distributed in microglia, followed by monocyte nuclear dendritic cells (Fig. 9ABC). This shows that after brain trauma, a variety of immune cells are activated, and the innate immune cells are the main participants in the nervous system inflammation after brain trauma.

GSVA enrichment analysis showed that MTOR, oxidative phosphorylation and other signal pathways were significantly up regulated in TBI group (Fig. 9D). These signal pathways are not only related to respiration, but can also regulate the nutrition and energy metabolism of cells under stress.

8. Cell-cell communication analysis

Cell-cell communication analysis mainly reflects paracrine and autocrine, which is of great significance for analyzing the changes in tissue microenvironment under pathological conditions. On the whole, the number of cell communication in TBI group was slightly higher than that in Sham group, while the strength of communication was significantly increased (Fig. 10A). In TBI group, CCL, CX3C, PTN, PSAP, MK and DEN signal pathways were dominant, while TGFB, VEGF and TNF pathways related intercellular communication was slightly weakened (Fig. 10B). From the perspective of ligand-receptor pairs, the interaction of CCL5-CCR5 was enhanced after brain trauma (Fig. 10C). This may be an important factor causing microglia and macrophages to accumulate in the damaged area.

From the perspective of the number and strength of cell communication, after brain trauma, the communication between nerve cells, astrocytes, microglia, parietal cells and surrounding cells is generally enhanced (Fig. 10D). Among them, we separately analyzed the microglia and macrophages that play the most important role in the innate immunity of the central nervous system. The results demonstrated that under TBI conditions, macrophages could receive paracrine signals from most cells, including damaged nerve cells, astrocytes, endothelial cells, and parietal cells (Fig. 10E). These signals may trigger macrophages to migrate to damaged cells, and eventually destroy and phagocytosis them. Microglia can also receive paracrine signals from most surrounding cells, and the strength of receiving nerve cell communication signals was stronger (Fig. 10E).

In the signal transmission intensity/quantity diagram, we found that the signal transmission strength of astrocytes was the highest (Fig. 10FG). The intercellular communication map showed that the main communication pathways of astrocytes in TBI group included PSAP, PTN and MK. PSAP is closely related to ferroptosis of nerve cells. PTN is associated with nerve cell regeneration and repair. MK pathway plays an important role in the process of inflammation and tissue cell repair. The main intercellular communication pathways of astrocytes in TBI group included PSAP, PTN and MK. PSAP is closely related to ferroptosis of nerve cells. PTN is associated with nerve cell regeneration and repair. MK pathway is crucial in the process of inflammation and tissue cell repair.

From the hierarchical map, the number of microglia receiving signals in TBI group increased significantly, which verified our previous results (Fig. 10HI). The oligodendrocyte precursor receives less intercellular communication signals, including TGFb, VEGF, and PDGF, which are related to cell growth and differentiation. This may inhibit oligodendrocyte maturation, leading to neurological repair disorders and demyelinating diseases.

CCL pathway plays an important role in the aggregation, killing and phagocytosis of innate immune cells. Therefore, we separately constructed a hierarchical map (Fig. 10JK). It was found that after brain trauma, not only the signal of CCL pathway between nervous system and immune cells was enhanced, but also the communication between microglia and macrophages was enhanced. This indicates that there is a synergistic effect between microglia and macrophages in the process of TBI induced inflammation.

To fully display the changes in intercellular communication before and after brain trauma, we constructed the ligand receptor map and the cell type pathway map of intercellular communication (Fig. 11ABCDEF). The results indicated that macrophages and microglia were more active in the communication of CCL immune and other immune pathways after brain trauma. This confirms our previous results.

The results of cell communication clustering showed that the signal pathways involved in the microglial cell related communication signal pattern (Pattern 1) included not only the chemokines CCL and CX3C, but also TNF and TGFb pathways. TNF pathway can induce programmed cell death in inflammatory state. In addition to participating in cell growth and differentiation, TGFb can also regulate cell apoptosis (Fig. 11GH). This means that microglia may play an immunomodulatory role and mediate cell death through these pathways.

Among the cell communication modes related to macrophages, besides CCL and TNF, GSA and GALECTIN signal pathways (Fig11. IJ) were also included. Among them, GSA pathway has a wide range of functions, which can reduce inflammation and apoptosis through NF-κB, TNF and MAPK. GALECTIN is a signal pathway recognized by the danger associated molecular patterns (DAMPs) in innate immunity, and is considered to be a key regulator of macrophage and microglial activity. It is also an attractive drug target in neurodegenerative diseases. In normal tissues, inflammation usually plays a role in fighting invading pathogens and maintaining tissue health. However, under pathological conditions such as trauma, inflammation can also aggravate tissue damage. The inflammation induced by TBI was once thought to occur through the damaged BBB by peripheral immune mediators.

Traumatic brain injury (TBI) is the damage of nervous system function or structure caused by external force, which is a public health problem of great concern in the whole medical community. It was found that post-traumatic stress disorder, memory disorder, Parkinson's disease, epilepsy, chronic traumatic encephalopathy, and Alzheimer's disease are all related to neuroinflammation¹⁷. In normal tissues, inflammation usually plays a role in fighting against invading pathogens and maintaining tissue health. However, under pathological conditions such as trauma, inflammation can also aggravate tissue damage. The inflammation of TBI was once thought to be caused by peripheral immune cells passing through the damaged BBB¹⁸. But new evidence shows that there are a series of complex interactions between central immune cells, peripheral immune cells and soluble cytokines in the inflammatory process, which affect immune homeostasis and change the disease process¹⁹. The beneficial aspects of inflammatory response after brain trauma include promoting debris clearance, neuronal regeneration, glial cell differentiation and angiogenesis. However, excessive immune response can also produce adverse effects, such as mediated neuronal death and neurodegenerative diseases²⁰. Therefore, it is particularly important to maintain the stable immune response of the nervous system for the protection of the nervous system.

In this study, it was found that TBI related differentially expressed genes were most enriched in Inflammatory response pathway (sorted by q-value), indicating that immune response played a prominent role in the pathology of TBI. Followed by Cytokine signaling in immune system, Cytokine receptor interaction and Positive regulation of cytokine production pathway. Cytokines are small molecule polypeptides or glycoproteins with immune function, which often transmit signals through paracrine or autocrine to promote the growth, differentiation, maturation of immune cells, regulate immune response, and promote wound healing²¹.

However, current research mainly focuses on the synthesis and secretion of cytokines, while research on receptors is relatively limited. This study found that the cytokine receptor is a key node in regulating immune system response after brain trauma and is closely related to cell death. After brain trauma, the overexpression of activating receptors on the surface of innate immune cells can lead to their long-term sensitivity to cytokines; this can eventually trigger chronic inflammatory response in the central nervous system.

The enrichment of TBI-related differentially expressed genes in the NF-κB pathway is also noteworthy. NF-κB is the first responder to harmful cellular stimulation. Under stress conditions, this signal pathway can accept the stimulus signal to initiate and expand the inflammatory response, leading to cell apoptosis. Incorrect regulation of NF-κB could lead to autoimmune diseases, chronic inflammation, and many types of cancer; and is also related to synaptic plasticity; and memory²².

Neutrophil degranulation is also involved in the pathological process of TBI. Neutrophil granules are rich in enzymes such as myeloperoxidase, lysozyme, alkaline phosphatase, and a large number of inflammatory mediators. After activation, neutrophils can attack host cells and digest pathogens. Excessive neutrophil degranulation is closely related to an acute and purulent infections, various tissue injuries, acute massive hemorrhage, and acute hemolysis.

The results of PPI enrichment analysis showed that Signaling by interleukins is the most important component of the interaction network. Among them, the more important factors including Interleukin-4, Interleukin-13 and Interleukin-10 signaling pathways. The information transmitted by these pathways is closely related to Th2 T cell differentiation, M2 macrophage polarization, MHCII expression, B cell and plasma cell differentiation, and antibody homeotype conversion.

The results also showed that MyD88 is an important node in the TBI-related PPI network, which may represent another mechanism by which immune cells activate receptors to regulate immune homeostasis after brain trauma. MyD88 belongs to the Toll/IL-1R family and the death domain family. It serves as a junction molecule of the immune system to initiate the apoptosis signal pathway and is closely associated with cell survival. MyD88 interacts with IRAK4 via its N-terminal death domain, thus transmitting signals downstream. Its classical functions include the activation of downstream NF-κB and AP-1 transcription factors, as well as the induction of inflammatory factors, cytokines, and chemokines^23,24.

"TBI-related neuroinflammation is characterized by the activation of microglia and astrocytes, as well as the secretion of inflammatory cytokines to recruit peripheral macrophages. The function of microglia is similar to that of peripheral macrophages, and they are easily influenced by the surrounding microenvironment and can be transformed into different phenotypes²⁵. The M1-like phenotype is generally induced by hazard-associated molecular patterns (DAMPs), free radicals, or pro-inflammatory cytokines. This phenotype is characterized by the promotion of the production of chemokines, pro-inflammatory cytokines, ROS, and increased phagocytosis. M2-like microglia can be induced by stimulation of IL-4 and IL-13 and have dual pro-inflammatory and anti-inflammatory effects. M2-like microglia can promote the repair and remodeling of damaged tissues."

Neutrophils can cross BBB to perform immune function under pathological conditions ,such as infection, trauma, ischemia and hemorrhage. Neutrophils can also break down BBB, helping to recruit more peripheral immune cells. However, this will inevitably lead to tissue damage.

Treg cells are suppressors of the immune system and play a very important role in maintaining autoimmune tolerance and balance. Studies have confirmed that improving the endogenous response of Treg cells can improve the chronic inflammatory state of the nervous system after brain trauma²⁶.

Our study confirmed the infiltration of neutrophils, macrophage M1 and M2 types in brain tissue after brain trauma, and found that Tregs cells were less distributed in the nervous system. The proportion of macrophages in cortex and hippocampus was significantly higher than that in thalamus and hypothalamus. However, the proportion of Treg cells was low in the cortex and hippocampus. This means that there are differences in the degree of inflammation in different regions of brain tissue. The cortex and hippocampus are more vulnerable to inflammatory damage, resulting in motor, sensory, emotional and memory dysfunction. This may be due to different tissue characteristics and degrees of damage.

Long-term chronic inflammation after brain injury may cause chronic traumatic encephalopathy, which is characterized by emotional instability, personality change, memory disorder, dementia, cerebellar injury, pyramidal and extrapyramidal dysfunction²⁷.

Our research found that immune cell infiltration reached a peak within one week of brain injury and gradually decreased within one month. However, as brain injury enters the chronic period of 2-3 months, the level of immune infiltration increases again, so brain tissue suffers a "second attack" caused by the imbalance of the immune system. These results indicate that after a remission period of 2-3 months, the inflammation is aggravated again may an important feature of chronic traumatic encephalopathy.

The inflammatory response after brain trauma is controlled by a series of complex regulatory networks. By building a PPI network of key genes, our research screened seven of the most important molecular nodes. The results showed that these central nodes were all activating receptors on the surface of immune cells.

CD86 belongs to the immunoglobulin superfamily. It can activate the CD28 receptor pathway on the surface of T cells, give signals to the initial activation of T cells, and promote the activation, proliferation and differentiation of T cells; Induce the up regulation of IL-2 receptor on the surface of T cells and promote the secretion of cytokines. It can also regulate the Fas/FasL mediated apoptosis pathway.

CCR5 is a membrane protein belonging to the G protein coupling factor superfamily. It is the receptor of intracellular β-chemokines (RANTES, MIP1α and MIP1β) and has the function of regulating the migration, proliferation and immunity of T cells, monocytes and megalophils²⁸.

PTPRC is a transmembrane glycoprotein, which plays an important role in the innate immune system. The balance destruction between protein tyrosine kinase and phosphatase caused by PTPRC may lead to immune deficiency, autoimmunity or malignant tumor²⁹.

ITGB2 is a receptor for ICAM1, ICAM2, ICAM3 and ICAM4, which helps NK cells exert cytotoxicity. ITGB2 can also participate in the adhesion and migration of T cells and neutrophils. ITGB2 plays an important role in the inherent discussion. The defect of this gene leads to leukocyte adhesion defect³⁰.

FcγRIIB regulates the innate immune system by inhibiting the activation of Toll-like receptors. It is worth noting that FcγRIIB has been proved to regulate the migration of B cells and dendritic cells in the germinal center, which has a potential impact on the development of autoimmune diseases³¹.

TLR2 is an important protein molecule involved in innate immunity, and also a bridge connecting innate immunity and acquired immunity. TLR2 is a single transmembrane non-catalytic protein, which can identify molecules with conservative structure from microorganisms. When microorganisms break through the physical barrier of the body, TLR2 can recognize them and activate the immune system to respond.

TYROBP is a transmembrane adaptor protein, which is the downstream junction and signal chaperone of several immune related receptors (including SIRP1β, CD33, CR3 and TREM2). TYROBP has attracted much attention because it transmits signals from these receptors to maintain the stability of the brain immune microenvironment³².

We found that after brain trauma, most of the key nodes of immune response serve as receptors on the cell membrane, and some are transmembrane receptors and cofactors. This may be related to their receiving injury, stress response signals and playing the immune response function. Single-cell analysis showed that these membrane receptors were mainly distributed in microglia, followed by monocytes and dendritic cells. This proves that these innate immune cells are the main body of inflammation after brain trauma. Therefore, we infer that activating receptors on the surface of innate immune cells after brain trauma are the key nodes regulating the immune microenvironment of the nervous system. Overexpression of these receptors may lead to the destruction of immune system homeostasis, leading to chronic inflammation.

Neuronal cell death occurs extensively during development and pathology, where it is especially important because of the limited capacity of adult neurons to proliferate or be replaced. Research confirmed that there are at least a dozen ways for neurons to die, that blocking a particular mechanism of cell death may not prevent the cell from dying, and that non-neuronal cells also contribute to neuronal death³³. In this study, we comprehensively analyzed five cell death types in TBI, including apoptosis, ferroptosis, pyroptosis, necrosis and autophagy, and explored the relationship between immune response and these cell death types.

Apoptosis is the most common process of programmed cell death and the common outcome of damaged cells. Recent studies have found that in the absence of active caspase, the cGAS/STING inflammatory pathway is activated to release IFN, and then a large number of BAX/BAK oligomers attach to the outer membrane of mitochondria to form large channels, which can release mtDNA and trigger the inflammatory pathway³⁴.

Pyroptosis is an important immune response of the body. Moderate pyroptosis can eliminate pathogenic microorganisms, stimulate adaptive immune response and enhance host survival, while excessive pyroptosis will lead to the occurrence of body diseases. At present, it is found that pyroptosis is widely involved in the occurrence and development of tumors, infectious diseases, metabolic diseases, and nervous system diseases³⁵.

Ferroptosis is related to the pathological process of immune response. After ferroptosis, cells release a large number of inflammatory factors that activate innate immunity. It was found that in ferroptosis tissues sensitized by lipoxygenase (LOX) and cyclooxygenase (COX), arachidonic acid metabolism leads to the release of inflammatory mediators and regulates the differentiation of immune cells through LOX and COX³⁶.

Autophagy can inhibit the inflammatory response caused by mitochondrial damage by decomposing inflammatory bodies³⁷. However, autophagy can also positively regulate inflammation. It was found that hunger-induced non-classical autophagy can promote the activation of caspase and the secretion of IL-1β and IL-18. After treatment with the autophagy inhibitor chloroquine, the secretion of IL-1β decreases, and the same phenomenon occurs when the autophagy related LC3 gene is knocked out³⁸.

Our research found that pyroptosis, apoptosis and autophagy are the main forms of cell death after brain trauma. Ferroptosis, autophagy, pyroptosis and necrosis were significantly correlated with inflammation. These results are helpful to fully understand the mechanism of cell death after brain trauma.

Cell-cell communication is one of the basic ways of signal transduction in the nervous, endocrine and immune regulatory systems, including paracrine and autocrine. Autocrine function in cell communication contributes to the growth, differentiation and maturation of immune cells. Paracrine plays an important role in the recognition, aggregation, adhesion and phagocytosis of immune cells³⁹.

As mentioned above, we found that cytokine receptors such as CCR5, PTPRC, ITGB2 and FcRIIB play an important role in the pathological process after brain trauma. Most of these receptors can accept paracrine signals from adjacent cells. So, we applied CellChat software to further analyze them at the single-cell level. The main purpose was to predict the cell types, upstream and downstream pathways and physiological effects of these signaling factors.

The results indicated that microglia and macrophages could receive paracrine signals from nerve cells, astrocytes, endothelial cells and parietal cells. These signals mainly activate CCL and CX3C signal pathways, and their main functions include guiding leukocytes to gather at the target location during inflammation. Immune cells attracted by chemokines migrate along the direction of increasing chemokine concentration. CCL is chemokine for monocyte and macrophage. In addition to chemotaxis, it can also provide specific signals for immune cell maturation. CX3C can recruit T lymphocytes and neutrophils, and can activate these cells to initiate immune response⁴⁰.

TNF and TGFb signaling pathways play a synergistic role in this process, which can reduce cell regeneration and induce apoptosis. Being one of the most important pro-inflammatory cytokines, TNF-α participates in vasodilatation and edema formation, and leukocyte adhesion to epithelium through expression of adhesion molecules; it regulates blood coagulation, contributes to oxidative stress in sites of inflammation, and indirectly induces cell death. TGFb is a multifunctional cytokine widely distributed in the nervous system. Its functions include regulating the repair of the injured nervous system and inducing the growth, proliferation, migration and differentiation of neurons and glial cells. It can also activate microglia and participate in the inflammation of nervous system⁴¹.

Excessive inflammation exacerbates damage to the nervous system following brain trauma and is directly linked to cell death. In this study, we identified key gene groups that contribute to inflammation after brain trauma, including CD86, CCR5, PTPRC, ITGB2, FCGR2B, TLR2, and TYROBP. These proteins are active receptors or co-factors on the surface of innate immune cells, suggesting that chronic or excessive inflammation after brain trauma may be associated with their overexpression. We also found that the primary forms of brain cell death after trauma were autophagy, apoptosis, and necrosis, and that immunoregulatory genes are closely linked to ferroptosis, autophagy, pyroptosis, and necrosis of brain cells. At the cellular level, macrophages and microglia are the primary cell types that mediate the immune response in the nervous system, while astrocytes play a supporting role. Immune signaling pathways, such as CCL and CX3C, can facilitate immune cell infiltration and induce inflammatory responses through autocrine and paracrine effects. TNF, VEGF, and TGFb signaling pathways act synergistically in this process.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Authors Contributions

XZ: conception and design, writing the article, data collection. AY: data analysis and interpretation. JH: data collection, analysis and interpretation. WH: provides guidance on algorithms and statistics. HS: conduct single-cell data analysis. XL: offering text editing assistance. WH: correcting statistical results, images and data. QL: writing the article, analysis and interpretation. All authors contributed to the article and approved the submitted version.

Data Availability Statement

All data generated or analysed during this study are included in this published article (and its Supplementary Information files).

Ethics declarations

The data for this study are from available databases and do not involve animal or human experiments, so there are no ethical concerns.

Funding

This work was funded by the National Natural Science Foundation of China [grant numbers: 82071465, 81571283], Sanming Project of Medicine in Shenzhen [grant numbers: SZSM201911007], the Natural Science Foundation of Shandong [grant numbers ZR2020MH154], and the Key Project of Research and Development of Shandong Province [grant numbers 2018GSF118215].

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No competing interests reported.

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Innate Immune Cells Activating Receptors Are Crucial Factors Regulating Inflammation and Cell Death in Traumatic Brain Injury

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