Ablation of CD11b gene limits acute proinflammatory response to SCI
As a first step in exploring the role that CD11b plays in acute neuroinflammation, we used qPCR analysis to examine the changes to its expression level at multiple timepoints after SCI. We observed a significant increase of CD11b mRNA expression starting at 1 d post-injury, reaching its peak at 7 d and remained persistently high for up to 28 d (Fig. 1A). Next, we examined the effects of CD11b ablation on microglia and monocyte markers, along with genes that reflect their phenotypic functions. At 1d after SCI, qPCR analysis showed near-zero levels of CD11b (Itgam) mRNA expression in both Sham and SCI of CD11b KO mice, as expected (Fig. 1B). Furthermore, the gene Cxcl10, a chemokine well-known for inducing microglia migration and initiating microglial activation (57), showed significant increases in the injured spinal cord of both genotype groups, with CD11b KO mice showing even higher levels (Fig. 1C). In contrast, the gene Trem2, which is expressed in microglia and other myeloid cells of the CNS, showed a marked increase in SCI/WT mice, but no injury-induced changes were observed in CD11b KO mice (Fig. 1D). As a member of the transforming growth factor beta superfamily and known as macrophage inhibitory cytokine-1 (MIC-1), the expression levels of Gdf15 were very low in both sham groups but showed significant increases after injury. Pairwise comparison of SCI/WT with SCI/CD11b KO mice showed significantly lower expression levels in the latter group (Fig. 1E). Other microglia and myeloid cell markers that we tested included P2ry12, Tmem119, CD83, and Csf1r. The markers P2ry12 (Fig. 1F) and Tmem119 (Fig. 1G), both of which are abundantly expressed in ramified microglia (58, 59), showed a significant decrease after 1d SCI without genotype effects. The gene CD83 plays a critical role in controlling and resolving immune responses, showed significantly lower mRNA levels in injury groups (Fig. 1H), but no genotypic differences were observed. Finally, the gene that encodes microglial receptor Csf1r showed neither injury nor genotype effects (Fig. 1I). In addition, both WT and CD11b KO mice showed marked upregulation of Gfap at 1 d post-injury, but no genotype effects were observed, suggesting that genetic depletion of CD11b didn’t affect astrocyte function (Fig. 1J). Collectively, acute SCI leads to increased levels of genes that initiate inflammation-resolving processes and drive myeloid cells towards clearance of damaged tissue and debris, which was not affected by CD11b ablation.
Depletion of CD11b reduces the number of microglia and infiltration of neutrophils in the injured spinal cord
At d3 after SCI when infiltration peaks in the spinal cord, flow cytometry was used to examine the cellular inflammatory response in the lesion site. Due to the absence of CD11b protein in the CD11b KO mice, we used other known microglia and monocyte markers for gating myeloid cell populations. The cell surface marker CX3CR1 is expressed specifically in microglia (60). As indicated in Fig. 2A, microglia were gated on the criteria of CD45 intermediate (int), Ly6C low, and CX3CR1 positive (+), which was validated in WT groups with the traditional gating strategy of CD45intCD11b+. For infiltrating myeloid cells, the gating strategy of CD45hiLy6C+Ly6G− was used to identify monocytes, while Ly6G+ indicated neutrophils. Using this new strategy, we were able to observe a significant increase of microglia cell counts at the lesion site of both WT and CD11b KO mice compared to sham groups of the same genotype, however, the number of microglia were markedly lower in SCI/CD11b KO mice (Fig. 2B), suggesting lower levels of injury-induced proliferation. Although the number of infiltrating monocytes remained the same between the two genotypes, CD11b KO mice had significantly lower number of neutrophils (Fig. 2C). Furthermore, ROS production was significantly attenuated in both microglia (Fig. 2D-E) and infiltrating myeloid cells of SCI/CD11b KO (Fig. 2F-G) mice compared to the injured control group, as determined by DCF mean fluorescence intensity. Together, these results demonstrate that CD11b is critical to promoting microglia proliferation, infiltration of peripheral immune cells, and ROS production after SCI.
CD11b KO mice show robust changes in neuroinflammation-related genes after SCI
To determine the consequences of CD11b deletion on acute inflammatory response following SCI, we evaluated spinal cord tissue at the injury site with NanoString Neuroinflammation panel. Partial least square discrimination analysis (PLSDA) was used on all normalized transcription count data to reveal a distinct separation between samples of each group, which was clustered into four quadrants (Fig. 3A). The two main variants of the PLSDA model separated samples by injury (variate 1) and genotype (variate 2), accounting for 52% and 10% of the total variation between samples respectively. Furthermore, the gene Itgam regulating expression of CD11b showed significant reduction in the spinal cord of KO mice compared to their WT littermates, which further confirms the validity of the global KO model (Fig. 3B). Pairwise comparison between groups yielded a total of 95 (20 downregulated, 75 upregulated) in Sham/CD11b KO vs. Sham/WT and 123 (54 downregulated, 69 upregulated) genes in SCI/CD11b KO vs. SCI/WT, which indicated robust genotype effects in both baseline and after SCI conditions (Fig. 3C-D). Interestingly, more than double the number of genes showed genotype-induced downregulation in SCI mice than Sham groups. In terms of injury effects, we were able to observe a total of 390 (175 downregulated, 215 upregulated) when comparing 1d SCI vs. Sham in WT (Fig. S1A), as well as 385 (184 downregulated, 201 upregulated) genes in SCI/CD11b KO vs. Sham/CD11b KO groups (Fig. S1B). As expected, the majority of genes related to neuroinflammation showed dramatic increase at 1d post-injury. Next, we sought to find differentially expressed genes (DEGs) between groups, which yielded the top 20 DEGs in the SCI/CD11b KO vs. SCI/WT comparison set ranked by p-value (Fig. 3E). Amongst the top DEGs with the lowest p-value, Itgam and Mapk14 are involved in the regulation of innate immune response, both of which showed significant reduction in CD11b KO mice after SCI. For cellular function, genes involved with microglia (Stmn1, Dst) are also downregulated in the injured spinal cord of CD11b KO mice, while the gene Dlg1 (neurons and neurotransmission) and Opalin (oligodendrocyte function) followed similar trends. In addition, four genes (Apc, Agt, Fkbp5, and Cp) are involved with the regulation of astrocyte function. Moreover, the genes Apoe and Ep300 are regulators of lipid metabolism, which showed significant upregulation in the spinal cord of CD11b KO mice. There are also several genes that are part of the epigenetic regulation process: Smarca5, Kdm4a, Eif1, Brd4, and Smarca4. Finally, the genes Cd47 and Ms4a4a, both of which showed significant upregulation in the KO mice, are enriched on the surface of neurons and microglia, respectively.
To confirm the changes observed in NanoString, we performed validation on several DEGs with qPCR. We first examined the mRNA expression levels of four genes that had significant downregulation in NanoString analysis. Opalin, a marker for oligodendrocytes (61, 62), showed significant injury-induced downregulation in WT mice (Fig. S2A) and even lower levels in CD11b KO mice after SCI. The gene Fcrls that modulates Fc receptor-like protein 2, only showed a significant injury-induced upregulation in WT mice (Fig. S2B) but not in CD11b KO mice, which was markedly lower at the same timepoint after SCI. The genes Pllp and Ennp6 showed significant downregulation after SCI in both WT and CD11b KO, with no significant differentiation between the two genotypes after injury (Fig. S2C-D). We next examined three DEGs that were upregulated in NanoString analysis, the first was Plekhp1 which showed significant upregulations after injury but no differences between genotypes (Fig. S2E). In the case of the genes H2-T23 and Fkbp5, SCI/CD11b KO mice showed significant increases at 1 d SCI compared to sham groups (Fig. S2F-G), which was also significantly higher than the SCI/WT group.
NanoString pathway enrichment analysis of DEGs showed Interferon Alpha Response as the top pathway upregulated in the SCI/CD11b KO vs. SCI/WT comparison set, with Interferon Gamma Response, Inflammatory Response, Apoptosis and TNF-alpha signaling via NF-kB as part of the top enriched pathways (Fig. 4A). Within the top enriched pathway of Interferon Alpha Response, genes included Ifitm2, Rsad2, Irf1, Ifih1, Cd47, and Gbp2 (Fig. 4B). Pathway enrichment analysis of downregulated DEGs in SCI/CD11b KO vs. SCI/WT comparison yielded E2F Targets as the top pathway (Fig. 4C). Other downregulated pathways include UV Response Dn, Hypoxia, Reactive Oxygen Species Pathway and Apoptosis. Specific DEGs within the top-downregulated pathway include Xrcc6, Prkdc, Stmn1, Rpa1, and Rad1 (Fig. 4D). Due to the critical role that CD11b plays in the acute immune response to SCI, it is reasonable to assume that the pathways activated by injury in WT mice may be different than those activated CD11b KO mice. Based on this hypothesis, we next examined the injury induced DEGs in WT and CD11b KO groups through pathway enrichment analysis. For WT mice, SCI led to the upregulation of genes in the pathways of Interferon Gamma Response, Inflammatory Response, IL-6/JAK/STAT3 Signaling, TNF-alpha signaling via NF-kB and Apoptosis (Fig. S1C). Moreover, SCI also led to downregulation of Reactive Oxygen Species Pathway, E2F Targets, Apoptosis, TGF-beta Signaling, and UV Response Dn in WT mice (Fig. S1D). On the other hand, in CD11b KO mice, the top upregulated pathway is IL-6/JAK/STAT3 Signaling, while the top downregulated pathway is UV Response Dn (Fig. S1E-F).
To further investigate the effects of CD11b ablation on the transcriptomic profile of injured spinal cords, we used bulk RNA sequencing to examine spinal cord tissue at 1d post-injury. Using a cutoff point of FDR < 0.05, we were able to screen a total of 137 DEGs (59 downregulated and 78 upregulated) from SCI/CD11b KO vs. SCI/WT and depict them in a volcano plot (Fig. 5A). In addition, our analysis also yielded the top 10 DEGs (Fig. 5B), with CD11b, Cfh, Gpr182, Ube2a, and Cyp51 being the top 5 genes with the lowest FDR value (Fig. 5C). Moreover, pathway enrichment analysis with the Bioplanet 2019 database showed “Interleukin-1 regulation of extracellular matrix” as the top upregulated pathway (Fig. 5D), while “Cholesterol biosynthesis” is the top downregulated one in the KO mice (Fig. 5E).
In summary, our NanoString and bulk RNAseq results showed upregulation of proinflammatory genes involved with interferon alpha, interferon gamma and other pathways that participate in the development of innate and adaptive immune responses, suggesting that CD11b KO mice had upregulated acute neuroinflammation in response to spinal cord injury, which is a necessary mechanism of defense for the CNS protection.
Ablation of CD11b improves functional recovery and reduces tissue damage after SCI
Finally, we assessed behavior and histopathology to determine the chronic impact of CD11b ablation on recovery. Weekly assessment of BMS scores and subscores showed that SCI/CD11b KO mice were recovering at a faster rate than their WT littermates (Fig. 6A-B). Starting from as early as 7 days post-injury, the average score for the SCI/WT mice was 1.11 ± 0.423, indicating that most WT mice within the group only showed slight ankle movement. At the same time point, SCI/CD11b KO mice had an average score of 1.875 ± 0.524, which is indicative of extensive ankle movement but no plantar placement. This dramatic genotype difference at 7 d post-injury (n = 9 for WT, n = 8 for CD11b KO, p = 0.025) was the start of a persistent trend that would continue for 6 weeks (p < 0.001), after which both injury groups appeared to have reached a plateau for motor function recovery. The average BMS scores at the plateau period was 4.6 for WT mice, indicating that mice had occasional or frequent plantar stepping. In contrast, CD11b KO mice had an average BMS of 5.7 to 5.9, which suggests that animals had frequent or consistent plantar stepping. Moreover, BMS subscores also reflected consistent plantar stepping and better coordination. We detected a significant main effect of genotypes [F(1, 15) = 5.549, p = 0.033 for BMS scores and F(1, 15) = 5.525, p = 0.033 for BMS subscores].
Next, we tested whether CD11b is involved in the development of post-injury allodynia evoked by mechanical and thermal stimuli. At 6 w following SCI, mice that regained adequate locomotor function to be able to withdraw a hind paw from a stimulus were selected for further nocifensive behavioral testing. In both tests of nociceptive behavior, there was no difference in mechanical/thermal threshold between the sham groups of either genotype (Fig. 6C-D). After SCI, the 50% mechanical pain threshold of SCI/WT was considerably lower than their uninjured counterparts (Fig. 6C), whereas CD11b KO mice showed little difference between sham and injury groups. Further examination of results demonstrated that the 50% pain threshold of SCI/CD11b KO mice was significantly higher than SCI/WT mice at 6 w post-injury (Fig. 6C), which indicates that hyperesthesia was effectively alleviated by CD11b genetic ablation. In hot plate test, the temperature threshold for WT mice was significantly decreased after SCI (p < 0.05 vs. SCI/WT, Fig. 6D), but no differences were observed between the sham and SCI groups of CD11b KO mice, which further confirms the attenuation of SCI-induced allodynia. After completion of the behavioral tests, we examined tissue damage by lesion volume (LV). Quantification of lesion volume by unbiased stereology showed a much smaller area of glial scarring in CD11b KO compared to their WT littermates (p < 0.01 vs. SCI/WT, Fig. 6E-F). Taken together, the results indicate that CD11b depletion improves recovery after SCI, which is associated with reduced tissue damage.
For further assessment of motor coordination, we used Catwalk XT gait analysis to examine fine motor differences beyond that recognizable by BMS scores. Stride length is the distance between successive placements of the same paw (Fig. 7A), which showed significant main genotype effect between groups [F (1, 28) = 6.130, P = 0.0196], but no injury effect. Measurement of print length and width also found significant main genotype effects [F (1, 28) = 18.03, P = 0.0002 for print length, F (1, 28) = 17.29, P = 0.0003 for print width], along with marked decrease of both parameters in WT mice following SCI (p < 0.01, Fig. 7B-C), Representative foot print images are indicated in Fig S3. Next, we evaluated motor coordination with regularity index, a parameter that tracks the order of paw placement in a step cycle (Fig. 7D). A single step cycle is defined as each of the four paws being placed on the walking surface in sequence, which was analyzed by attributing each set of steps into either a normal stepping pattern or abnormal gain. The result being a percentage of normal stepping out of all step cycles analyzed. As expected, the step sequence regularity index was significantly lower in SCI/WT mice compared to Sham/WT (p < 0.01 vs. Sham/WT, Fig. 7D, S4), indicating clear deficits in motor coordination, but this decrease was not significant in CD11b KO mice. Phase dispersions, a parameter that describes the temporal relationship between placement of two paws within a step cycle, was used to measure inter-paw coordination (Fig. 7E-F). Assessment of the phase dispersions between right forepaw (RF) and left hind paw (LH) yielded significant increase in WT mice following SCI (p < 0.001, Fig. 7E), but the deficits in CD11b KO weren’t significant. On the other side, which examines the diagonal dispersion of left forepaws (LF) and right hindpaws (RH), deficits from SCI could be observed in both WT (p < 0.001) and CD11b KO mice (p < 0.05, Fig. 7F). Moreover, bother parameters showed significant main genotype effects [F (1, 28) = 18.58, P = 0.0002 for RF->LH; F (1, 28) = 31.56, P < 0.0001 for LF->RH]. Print position is defined as the distance between a pair of hind paw and forepaw of the same side. Ideally, healthy C57BL/6 mice should be able to place their hind paw next to the location of the forepaw that has just been lifted from the walkway. Following SCI, the print positions of both WT and CD11b KO mice were significantly increased (p < 0.001, Fig. 7G), while also showing a genotype main effect [F (1, 28) = 44.44, P < 0.0001]. However, pairwise comparison of SCI/WT and SCI/CD11b KO yielded no statistical significance. Hindlimb base-of-support is a parameter that measures the average width of the track (distance between RH and LH) made by the animal, in which the farther apart the feet are placed during locomotion, the less likely the animal is to fall and the larger the base-of-support (BOS). Following SCI, WT mice showed significant decrease in hindlimb BOS (p < 0.05, Fig. 7H), indicating a lack of coordination and trunk stability. We next examined print area, max contact area and max contact max intensity, which could reflect spontaneous pain activity in mice (Fig. 7I-J). The SCI/WT group showed a significant decrease in all three parameters, which suggests reduced contact with the Catwalk surface and the potential presence of spontaneous pain.