Immunoregulatory and neutrophil-like monocyte subsets with distinct single-cell transcriptomic signatures emerge following brain injury

Abstract

Monocytes represent key cellular elements that contribute to the neurological sequela following brain injury. The current study reveals that trauma induces the augmented release of a transcriptionally distinct CD115⁺/Ly6C^hi monocyte population into the circulation of mice pre-exposed to clodronate depletion conditions. This phenomenon correlates with tissue protection, blood-brain barrier stability, and cerebral blood flow improvement. Uniquely, this shifted the innate immune cell profile in the cortical milieu and reduced the expression of pro-inflammatory Il6, IL1r1, MCP-1, Cxcl1, and Ccl3 cytokines. Monocytes that emerged under these conditions displayed a morphological and gene profile consistent with a subset commonly seen during emergency monopoiesis. Single-cell RNA sequencing delineated distinct clusters of monocytes and revealed a key transcriptional signature of Ly6C^hi monocytes enriched for Apoe and chitinase-like protein 3 (Chil3/Ym1), commonly expressed in pro-resolving immunoregulatory monocytes, as well as granule genes Elane, Prtn3, MPO, and Ctsg unique to neutrophil-like monocytes. The predominate shift in cell clusters included subsets with low expression of transcription factors involved in monocyte conversion, Pou2f2, Na4a1, and a robust enrichment of genes in the oxidative phosphorylation pathway which favors an anti-inflammatory phenotype. Transfer of this monocyte assemblage into brain-injured recipient mice demonstrated their direct role in neuroprotection. These findings reveal a multifaceted innate immune response to brain injury and suggest targeting surrogate monocyte subsets may foster tissue protection in the brain.

Keywords: Clodronate; Innate immunity; Neuroinflammation; Traumatic brain injury.

Fig. 1

CCI-injured mice pre-treated with Cl-LPM show reduced lesion volume, maintained BBB integrity, and restored cortical blood perfusion. A Lesion volume at 1- and 3-dpi alongside representative Nissl images at 1dpi. B Evans blue absorbance (610 nm) analysis in the cortex at 1dpi. C Representative images for ipsilateral cortex of control and CL-LPM-treated mice stained with mouse anti-IgG (green) at 1dpi. D Representative gross images of baseline brain-meningeal surface after craniectomy and laser speckle contrast imaging. Scale bar = 1 mm. E Quantification of perfusion units (percent of baseline) following CCI injury. (n = 5–8 per group). *p < 0.05; **p < 0.01; ***P < 0.001; ****p < 0.0001. Two-way ANOVA with Bonferroni post hoc. Scale bar in A and C = 500 µm. F Lesion volume of control LPM or Cl-LPM treated mice, reconstituted with GFP⁺ BMMs or BMDMs at 1 dpi. G Representative Nissl-stained coronal sections. H Confocal image analysis showing GFP⁺ cells located in the damaged ipsilateral cortex, confirming co-labeling with monocyte-specific marker Ccr2 (H1–H3) or CD45 (H4–H6) Scale bar = 100um. I, J Relative mRNA expression in BMDMs vs. BMMs. n = 5–10 mice/group. **p < 0.01; ***p < 0.001, ****p < 0.0001. One-way ANOVA with Bonferroni post hoc (B, F); t-test (A, I, J); 2-way ANOVA repeated measures (E)

Fig. 2

Monocyte population shift in blood following CCI injury and CL-LPM treatment. A Schematic representation of experimental timeline. B, C Flow cytometry analysis for the percentage (%) of CD45⁺/CD11b⁺ cell population that are Ly6G⁻, Ly6G⁻/CD115⁺, or Ly6G⁺ in CL-LPM or control-LPM treated naïve mice (0 dpi, B) as well as absolute numbers (C). D, E Flow cytometry analysis for the percentage (%) of myeloid population, including absolute numbers (F). G–J Flow cytometry gating strategy to select live/singlets, CD11b⁺/CD45⁺, and Ly6G^–/CD115⁺ monocytes. n = 5 per group. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.00001. Student’s t-test (B, C); one-way ANOVA with Bonferroni post hoc (D–F)

Fig. 3

Distinctive morphology and gene expression signature in circulating CD115 + /Ly6C^hi monocytes of sham and CCI-injured mice pre-treated with control or Cl-LPM at 1dpi. A Representative contour plots of side (SSC-A) and forward (FSC-A) scattering of Ly6C^hi monocytes from sham and CCI-injured mice pre-treated with control or CL-LPM at 1 dpi. B The mean size (FSC-A) of Ly6C^hi monocytes is significantly increased in Cl-LPM or control LPM- treated CCI-injured mice compared to control sham cells. C The mean granularity (SSC-A) of Ly6C^hi monocytes is significantly increased in Cl-LPM-treated CCI-injured mice compared to other groups. D Cell size of whole blood monocytes from Cl-LPM treated mice at 1 dpi. E, F Representative images of differential quick cytology. G–J Relative mRNA expression Ly6c and neutrophil-like gene Gfi1 (G), primary granules (H), anti-inflammatory (I), and monocytes TF (J) in circulating CL-LPM monocytes relative to control injured mice at 1 dpi. n = 5/group, *p < 0.05; **p < 0.01; ****p < 0.0001. One-way ANOVA with Bonferroni post hoc (B–D); t-test (G–J)

Fig. 4

Phenotypic shift of infiltrating immune cells and reduced inflammatory cytokines in the cortex of Cl-LPM injured mice. A, B Flow cytometry gating for CD45^hi/CD11b + cells and CD54^lo/CD11b + microglia (A) followed by Ly6G⁺ selection of neutrophils and Ly6G⁻ myeloid (B). C Percentage of CD11b⁺/CD45^hi infiltrating immune cells, CD11b⁺/CD45^hi/Ly6G⁺ neutrophils, and CD11b⁺/CD45^hi/Ly6G-myeloid/macrophages in the ipsilateral cortex of Cl-LPM or control CCI-injured mice at 1 dpi. D Representative gating of Ly6C and Ly6G expressing cells from CD11b⁺/CD45^hi infiltrating immune cells in the damaged cortex. E The percentage of CD11b⁺/CD45^hi/Ly6G⁺ and CD11b⁺/CD45^hi/Ly6G⁻ cells co-labeled as Ly6C^hi or Ly6C^lo expression. F Representative FSC-A/SSC-A gating to evaluate size and granularity of Ly6C^hi cells in the injured cortex. G Quantification for the size and granularity of CD11b + /CD45^hi/Ly6G-/Ly6C.^hi cell in the injured cortex at 1 dpi. H–K Cytokine Array protein quantification showing the top differentially expressed cytokines in the ipsilateral cortex at 1 dpi. M String analysis of the top differentially expressed cytokines. n = 5/group, *p < 0.05; **p < 0.01; ****p < 0.0001. t-test (C, E, G)

Fig. 5

Single-cell RNA sequencing analysis shows distinctive transcriptomics of blood monocytes treated with Cl-LPM compared to control at 1 dpi. ScRNAseq was performed on monocytes isolated from blood of mice pre-treated with Cl-LPM or Control-LPM at 1 dpi. A Heatmap plotting of the top 15 up and down differentially expressed genes from CL-LPM compared to control-LPM pre-treated mice. B Violin plots of selected genes differentially expressed in CL-LPM monocytes vs control-LPM. C Enhanced volcano plot of DGEs. D GO plot shows top 10 relevant GO pathways related to all significant up and down regulated genes in CL-LPM relative to control monocytes

Fig. 6

scRNAseq analysis displays altered monocyte clustering for blood monocytes isolated from Cl-LPM and control mice at 1 dpi. A Monocytes from control and Cl-LPM treated mice are clustered based on RNA gene expression in a Uniform Manifold Approximation and Projection (UMAP) plot. B Heatmap distinguishing each of the 11 clusters between samples. C UMAP following custom cell annotation and the percentage of cell types in each sample (D). E, F UMAP of control and Cl-LPM, respectively. G Heatmaps of top 10 up DEG’s DGE (Y axis) per cluster (X axis) for control and Cl-LPM samples showing distinctive gene expression profiles. H Dot plot of top genes expressed by annotated cell types. I Feature maps highlighting spatial expression across clusters of Cx3cr1, Na4a1, Pou2f2, Ccr2, Ly6c, Fn1 in control and Cl-LPM cells

Fig. 7

Top DGEs and Gene Ontology using scRNAseq cluster analysis of control and Cl-LPM monocytes. A Heatmap of top 10 genes in each annotated cell cluster in control monocytes. B Cell trajectory analysis using pseudotime shows a hub in Cluster (C) 0. C Volcano plot of DGEs in C0, non-classical. D GO analysis shows migration, cell–cell adhesion, actin assembly, regulation of inflammatory response and TNF production as top biological processes in C0. E Top 5 UP and down regulated genes in C0 that show inverse expression compared to C4. F Heatmap of top 10 genes in each annotated cell cluster in Cl-LPM monocytes. G Cell trajectory analysis using pseudotime. H Volcano plot of DGEs in C0, non-classical. I GO analysis shows oxidative phosphorylation, aerobic respiration, etc., as top biological processes in C0. J Top 5 UP and down regulated genes in C0. K Analysis of top DGE in neutrophil-like monocytes, C9. L GO analysis for C0. M–O Transfer of peripheral-derived monocytes (PDMs) by i.v. injection immediately following CCI injury. P, Q Gross images of injured brain at 1dpi shows tissue protection in mice receiving Cl-LPM PDMs (R). n = 5–8 *p < 0.05; one-way ANOVA, Bonferroni post hoc. Scale = 500 um in M–O and 0.5 cm in P and Q

Fig. 8

IPA analysis of C0, C4 and C9. A, D, G Graphical summary of top signaling predicted to be activated (orange) or inhibited (blue). B, E, H Top analysis ready molecules. C, F, I Horizontal bar of top canonical pathways identified for each monocyte cluster base don −log(p-value). Orange = predicted to be activated; blue = predicted to be inhibited