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Research Paper

Spinal cord injury in mice affects central and peripheral pathology in a severity-dependent manner

Bannerman, Courtney A.a; Douchant, Katyaa,b; Segal, Julia P.a; Knezic, Mitraa; Mack, Alexandra E.a; Lundell-Creagh, Caitlina; Silva, Jaqueline R.a,c,d; Duggan, Scottc; Sheth, Prameeta,e,b,f; Ghasemlou, Nadera,c,d,*

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doi: 10.1097/j.pain.0000000000002471
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1. Introduction

Most people living with spinal cord injury (SCI) also present with central neuropathic pain,16 often contributing significantly to decreased quality of life.71,114 This pain usually manifests at or below the injury site and is characterized by allodynia and hyperalgesia66 to mechanical and thermal stimuli, as well as spontaneous pain. Despite the high prevalence of central neuropathic pain after SCI, relatively few treatment options exist and underlying mechanisms remain largely unknown.136

The immune response to nervous system injury is critical for the development and maintenance of central neuropathic pain, as evidenced by the immune-mediated hypersensitivity in animal models of multiple sclerosis117 and SCI,33 as well as in models of peripheral nerve injury.62,92,106 This neuroinflammation can include the activation of resident glial cells, including astrocytes30 and microglia,26 and the recruitment of peripheral immune cells, including neutrophils,46 monocytes,43 T,122 and B cells.132 In rodents, injury severity alters the infiltration and activation of these cells in the spinal cord and dorsal root ganglia (DRG),7,21,27,105 which leads to changes in white matter loss and locomotor recovery and often hypersensitivity.60,126 In humans, most contusive injuries include prolonged compression of the spinal cord, with earlier decompression associated with a better neurological prognosis.44,78,79,101 Most preclinical contusion injury models, however, do not include compression of the cord and thus may not accurately represent the clinical image.

In addition to injury itself regulating immune responses, the gastrointestinal microbiome (GIM) has also been shown to play an influential role in developing and regulating the peripheral immune system.12 Moreover, injury can regulate GIM composition: Studies performed in both rodents and patients have demonstrated a shift in microbial communities after SCI.68,74,82,85 Shifts in the microbiome have also been implicated in other conditions, including chemotherapy-induced pain,118 fibromyalgia,29 multiple sclerosis,64 and rheumatoid arthritis,146 all of which exhibit a pain profile. However, it is not fully known to what extent the gut microbiome influences the onset of pain or how the severity of the condition could alter the microbiome. Using 2 degrees of injury severities, we were able to begin to understand the role the GIM plays in SCI pain.

Given the reciprocal relationships between the immune system, injury, and GIM, we sought to determine longitudinal changes in neuroinflammation, locomotor or sensory outcomes, and gut microbiota in a spinal cord contusion injury model in female C57BL/6J mice. Our results showed that cord compression increased immune cell infiltration into the spinal cord and DRG, decreased white matter sparing, increased expression of key inflammatory mediators, and increased gut dysbiosis longitudinally after injury and that these results scaled with injury severity. Temporal profiles for mechanical and thermal heat hyperalgesia were also dependent on injury severity. Our results provide a behavioural, cellular, and molecular characterization across multiple timepoints and severities of injury, laying the groundwork for future studies seeking to identify mechanisms underlying pain in SCI.

2. Materials and methods

2.1. Animals

All experiments were performed using female C57BL/6J mice bred in-house (Jackson Laboratory, Bar Harbor, ME) between 6 and 12 weeks of age, housed at a maximum of 4 per cage on a 12-hour light or dark cycle in a temperature-controlled and humidity-controlled room, with food and water provided ad libitum. All cage mates received the same injury. All animals used for locomotor analysis were also used for behaviour and either flow cytometry or histology. All protocols were approved by the Queen's University Animal Care Committee, following the ARRIVE guidelines and those of the Canadian Council on Animal Care.

2.2. Spinal cord contusion injury

The Infinite Horizons Spinal Cord Impactor (Precision Scientific Instrumentation, Lexington, KY) was used to injure the mouse spinal cord using a protocol similar to one previously reported.52 In brief, mice were anesthetized using a ketamine or xylazine or acepromazine cocktail (50:5:1 mg/kg), and a partial laminectomy was performed at the vertebral levels T10-11. Adjacent vertebrae were immobilized using serrated Adson forceps (Fine Science Tools, Vancouver, BC). Mice were split into 3 groups: sham (control), contusion, or compression. All injuries had an impact force of 50 ± 5 kdyn and registered displacement between 400 and 600 μm. Mice received either 0 seconds (contusion group) or 60 seconds of sustained compression on impact (compression group). Sham-injured mice received only a laminectomy. Buprenorphine (0.05 mg/kg, subcutaneously) was administered once immediately after surgery. Moist chow was provided for the first 3 days after surgery, and bladders were expressed twice daily until mice achieved voluntary voiding. Animals received intraperitoneal injections of saline, and weight was monitored daily until significant weight gain was observed.

2.3. Locomotor analysis

Mice were assessed for locomotor outcomes using the Basso Mouse Scale (BMS),9 a well-established tool used to evaluate locomotor recovery in mice. Mice were placed in an open-field environment and allowed to freely move. Their behaviours were scored by 2 individuals blinded to experimental conditions; scores for each animal were pooled and averaged. The BMS score and subscore (total of 9 and 11 points, respectively) were used to assess locomotion (gross and fine) and gait aspects, respectively. The BMS included both hind paws in the analysis.

2.4. Mechanical and thermal hypersensitivity

Mice were assessed for mechanical, heat, and cold sensitivity changes using the von Frey monofilament test, Hargreaves radiant heat test, and acetone test, respectively, as previously described.50,103 In brief, mice were habituated to each testing apparatus for at least 30 minutes per day over 5 consecutive days, followed by 3 separate baseline measurements for each test, taken at least 24 hours apart. Responses to mechanical or thermal stimuli were defined as licking or biting, rapid withdrawal, or rapid flexing of the paw accompanied by splaying of the toes. Data were collected from both hind paws and averaged for each test. The von Frey threshold value was determined to be the weight of the filament in which the mouse responds at least 5 of 10 times.

2.5. Fecal collection and DNA extraction

Fecal pellets were collected from each mouse at baseline and 3, 13, and 41 days postinjury (dpi). The number of pellets collected was noted for each mouse, and pellets were stored in 95% ethanol at −80°C until analysis. Fecal samples were mechanically disrupted using sterile sticks, and DNA was extracted using a Maxwell Instrument for Automated Nucleic Acid Extraction (Promega, Madison, WI) according to the manufacturer's instructions.

2.6. 16s rRNA sequencing

16S rRNA genes were amplified and barcoded using the Nextera DNA Library Preparation Kit (Illumina, FC-121-1011). In brief, 1 μL of extracted DNA (including a nuclease-free water–negative control and an E. coli–positive control) was amplified using region of interest–specific primers with overhand adapters (Forward: 5′ TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG-3′, Reverse: 5′- GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC-3′) for the 16S V3 and V4 regions, in a polymerase chain reaction (PCR) with Invitrogen Platinum Taq DNA Polymerase. Illumina flow cell adapter sequences and a 12-bp barcode were then incorporated into the PCR primers, resulting in a fully Illumina-compatible sequencing library. DNA amplicon purity and concentration were quantified on a 2100 BioAnalyzer (Agilent Technologies, Santa Clara, CA) and Qubit 3.0 Fluorometer (Thermo Fisher Scientific, Waltham, MA).

2.7. Sequence data processing

Bioinformatics analysis was performed on the Queen's University high-performance computing cluster using an inhouse designed analysis pipeline. Raw sequencing read quality was assessed using the tool FastQC. Sequencing read quality or adapter contamination were corrected using seqtk, FASTX-Toolkit, and Cutadapt. Reads passing quality control were preprocessed using the QIIME 2 suite of analysis tools. Preprocessed reads were used as input for operational taxonomic unit (OTU) picking against the Greengenes database with QIIME's pick_open_reference_otus.py script and clustered at 97% identity. Generated OTUs were normalized in R using the MetagenomeSeq statistical package to eliminate sampling biases. Visualization of normalized OTU data was completed with QIIME's plot_taxa_summary.py.

2.8. Histology

Spinal cord tissue was prepared, and immunohistochemistry was performed as previously described.49,90,103 In brief, mice were deeply anesthetized and perfused with 4% paraformaldehyde in 0.1M phosphate buffer. A 10-mm length of the spinal cord centred on the epicentre of injury was removed, postfixed in 4% paraformaldehyde, and cryoprotected for processing on a frozen cryostat (Leica, Wetzlar, Germany) where serial 12-μm sections were collected. Spinal cord sections on slides were incubated in phosphate-buffered saline with 0.25% Triton-X 100 with 10% normal donkey and goat sera (Jackson Immunoresearch Labs, West Grove, PA) and 2% bovine serum albumin (Bioshop Canada Inc, Burlington, ON) and then stained with primary antibodies with 2% normal sera overnight (polyclonal rabbit anti-glial fibrillary acidic protein [#Z033429-2, 1:10,000; Agilent Technologies Canada Inc] and monoclonal rat anti-CD11b [#MCA711G, 1:200; Bio-Rad Antibodies, Hercules, CA]). Sections were then incubated with goat anti-rabbit Alexa 488 (A21209, 1:1000; Fisher Scientific, Hampton, NH) and donkey anti-rat Alexa 594 (A11008, 1:500; Fisher Scientific) for 2 hours, mounted with DAPI-containing medium (Vector Laboratories, Burlingame, CA), and imaged using an Eclipse Ti2 microscope (Nikon, Tokyo, Japan).

Myelin was visualized by staining with Solvent blue 38 (Luxol fast blue; Fisher Scientific) for 3 hours at 60°C followed by 1 minute in lithium carbonate and dehydration through serial alcohols, as previously described.51

All histological quantification was performed using NIS-Elements AR (Nikon): (1) percent area of spinal cord positive for CD11b was quantified in serial sections 1008 μm rostral and caudal from injury epicentre; (2) extent of CD11b+ cell infiltration was determined by measuring the distance between the rostral-most and caudal-most sections with CD11b immunoreactivity above sham levels, with a similar method used to measure demyelination with Luxol fast blue sections; (3) glial scar volume was determined by measuring the area of the glial scar every 252 µm over the entire injury site and then summed, as previously reported48,59; and (4) myelin sparing was measured as the percent area of the myelinated spinal cord, stained blue using Luxol fast blue, and normalized to sham spinal cords at the same spinal level.

2.9. Flow cytometry

Analysis of immune cell infiltration or recruitment was performed as previously described.3 A 1 cm length of the spinal cord, centred on the injury site, was minced and digested in a mixture of 1 mg/mL collagenase type IV (Gibco, Waltham, MA) and 1 mg/mL DNase I (Sigma-Aldrich, Oakville, Ontario) in 1× HBSS for 1 hour. Bilateral DRG from spinal levels L4, L5, and L6 were removed and pooled from 2 mice for flow cytometry (ie, 12 DRG per biological replicate were used). The DRG were mechanically digested using a syringe before undergoing enzymatic digestion like the spinal cord. Spinal cord and DRG cells were then triturated by the pipette, washed with HBSS and 10% fetal bovine serum, and filtered through a 70-μm nylon mesh. Spinal cord cells were incubated with mouse anti-CD16/CD32 (Fc block; 1:100; Biolegend, San Diego, CA) on ice for 10 minutes, followed by a 30-minute incubation with the following primary antibodies: anti-CD45 (APC/Fire), anti-CD11b (FITC), anti-Ly6c (APC), and anti-F4/80 (PE) (all used at 1:200; BioLegend). Dorsal root ganglia cells were also incubated with mouse anti-CD16/CD32 on ice for 10 minutes, before being stained with the following primary antibodies: anti-CD11b (FITC), anti-TCRb (PECy5.5), anti-Ly6G (PECy7), and anti-Ly6c (APC) (all used at 1:200, except PECy7 which was used at 1:5000; BioLegend) for 30 minutes. Flow cytometry was performed on a CytoFlex cytometer (Beckman Coulter, Miami, FL), and data were analyzed using CytExpert software (Beckman Coulter).

2.10. Quantitative real-time polymerase chain reaction

Thoracic spinal cords (T8-T12) were harvested from mice euthanized by Euthanyl, frozen on dry ice, and stored at −80°C until processing. Tissues were homogenized in Qiazol (Qiagen, Hilden, Germany) using a BeadRuptor 24 (Omni International, Kennesaw, GA) followed by RNA extraction by ethanol precipitation. RNA was reverse transcribed according to manufacturer's instructions using the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Forester City, CA) and then run on a SimpliAmp Thermal Cycler (Applied Biosystems) with the following protocol: 10 minutes at 25°C, 120 minutes at 37°C, and 5 minutes at 85°C. cDNA was loaded in duplicates with TaqMan Fast Advanced Master Mix (Applied Biosystems), and the following probes were used: Tnfα (Mm00443258_m1), Il1β (Mm00434228_m1), and Ifn-γ (Mm01168134_m1); glyceraldehyde 3-phosphate dehydrogenase (GAPDH, Mm99999915_g1) was used as the control gene. Quantitative PCR (qPCR) was run on a QuantStudio 12 K Flex Real-Time PCR system (Applied Biosystems) using the following protocol: 120 seconds at 50°C and 20 seconds at 95°C, followed by 40 cycles of 1 second at 95°C and 20 seconds at 60°C. The relative gene expression was calculated using the 2−ΔΔCT method88 and log transformed.

2.11. Statistical Analysis

All statistical analyses were performed using SigmaStat or SigmaPlot software packages (Systat Software, Chicago, IL). Behavioural and locomotor recovery data were analyzed using two-way repeated-measures analysis of variance (ANOVAs) with post hoc Tukey tests. Histological analysis was analyzed using two-way repeated-measures ANOVAs with a post hoc Tukey test or a t test. Flow cytometry data were analyzed using a one-way ANOVA with a post hoc Tukey test. Quantitative real-time PCR data were analyzed using an unpaired two-tailed t test. Significance was set at P < 0.05 for all tests. All data are presented as mean ± SEM. Statistical and graphical analyses of microbiome data were conducted with the Statistical Analysis of Metagenomic Profiles and MicrobiomeAnalyst analysis packages.38 Specifically, permutational analysis of variance (PERMANOVA) was performed to measure statistical differences at the community level and visualized using Principal Component Ordination (PCA). Friedman ANOVA with the Dunn test for multiple comparisons was performed to compare OTUs of interest at each time point, and fold changes were graphed using GraphPad Prism version 8.0.0 for Mac (GraphPad Software, San Diego, CA,www.graphpad.com).

3. Results

3.1. Compression spinal cord injury reduces locomotor recovery and increases hypersensitivity compared with contusion spinal cord injury

We first sought to determine whether moderate contusion injury (50 kdyn, 400-600 μm displacement52) altered locomotor recovery relative to moderate injury with a 60seconds compression of the cord. Locomotor recovery, assessed using the Basso Mouse Scale (BMS) score and subscore,9 showed significant differences between the contusion, compression, and sham (laminectomy only) groups (P < 0.001; Figs. 1A and B). Basso Mouse Scale score demonstrated that both injury models showed significantly reduced locomotor ability compared with sham from 1 to 41 dpi (P ≤ 0.004; Fig. 1A), except at 35dpi for the contusion model (P = 0.074). Gross locomotor control was significantly impaired in mice with compression injury from 3 to 41 dpi, relative to contusion mice (P < 0.001). A similar pattern was observed in the BMS subscore, which measures fine locomotor activity, with significant differences observed between the 3 groups (P < 0.001; Fig. 1B). Both severities of SCI showed significantly reduced the BMS subscore from 1 to 41 dpi in comparison with sham (P < 0.001). Compression mice showed significantly reduced fine locomotor recovery compared with contusion mice from 3 to 41 dpi (P ≤ 0.014). Together, our data revealed that compression injury exacerbates locomotor dysfunction and slows recovery vs contusion injury alone.

F1
Figure 1.:
Compression of the spinal cord caused greater locomotor dysfunction and mechanical hypersensitivity than contusion injury. (A) Locomotor recovery was assessed after spinal cord contusion and compression injury using the 9-point BMS scale. Compression and contusion injuries resulted in significantly reduced locomotor recovery compared with sham controls (n = 8 per group). The compression group also exhibited greater locomotor dysfunction relative to the contusion group starting 3 days after SCI. No significant changes were observed in sham mice relative to baseline control values. (B) The BMS subscore, which measures finer aspects of locomotor control using an 11-point BMS, was also significantly lower in the compression group across the entire follow-up period, whereas the contusion group showed some recovery of function up to day 14, when it is stabilized. The compression group showed significantly reduced recovery relative to the contusion group at all timepoints after day 1. No significant changes were observed in sham mice relative to baseline controls values. (C) Rapid onset of mechanical hypersensitivity, measured as the 50% withdrawal threshold, was observed in mice with compression injury, showing significantly reduced thresholds from day 7 postinjury. Contusion injury, on the other hand, led to significant reductions in mechanical thresholds starting at 21dpi. Compression injury resulted in significantly greater mechanical hypersensitivity relative to contusion injury at all timepoints after injury, except on day 43. Sham-injured controls did not exhibit changes in mechanical thresholds (n = 13 per group). (D) Thermal heat hypersensitivity was measured as the latency of response to a heat stimulus. Earlier onset of thermal heat hypersensitivity was observed after a compression injury compared with a contusion injury (n = 13 per group). (E) No significant differences were observed in thermal cold hypersensitivity between the 3 spinal cord injury groups (n = 13 per group). (A) Two-way repeated-measures ANOVA with a Tukey post hoc test were used for assessing group differences in panels (A–E). *P < 0.05, **P < 0.01, ***P < 0.001. Black * denotes significance between compression and contusion, Red * denotes significance between compression and sham, # denotes significance between contusion and sham. ANOVA, analysis of variance; BMS, Basso Mouse Scale; SCI, spinal cord injury

Mice were assessed periodically for 43 days after injury for mechanical, heat, and cold hypersensitivity using the von Frey, Hargreaves radiant heat, and acetone tests, respectively. Mice with compression injury exhibited earlier and more severe reductions relative to both the sham-injured and contusion-injured groups in mechanical thresholds starting at 7 dpi (P ≤ 0.001; Fig. 1C). Mechanical thresholds were significantly reduced in the compression compared with contusion injury group between 8 to 36 dpi (P ≤ 0.001), but not at 43 dpi (P = 0.089). Mice with contusion injury alone showed increased mechanical hypersensitivity relative to sham-injured controls starting at 21 dpi (P < 0.001). Thermal heat thresholds showed significant differences between all 3 groups over time (P < 0.001; Fig. 1D). Latency to withdrawal showed significant changes from sham controls starting at 8dpi for the compression group (P < 0.001) and 11dpi for the contusion group (P < 0.001). Changes in thermal heat thresholds were significantly different between the compression and contusion groups at 8 and 11 dpi (P ≤ 0.028), but not at 14 dpi and later (P ≥ 0.397). No significant differences were observed between the 3 groups for the acetone test, which measures cold sensitivity, over time (P = 0.304; Fig. 1E). However, the compression group exhibited significantly higher response times relative to sham controls (P = 0.003). These results suggest that the compression of the spinal cord results in an earlier onset of mechanical and thermal hypersensitivity compared with contusion injury and that the magnitude of mechanical hypersensitivity is dependent on injury severity; cold hypersensitivity is largely unaffected.

3.2. Gastrointestinal microbiota changes in spinal cord injury severity–dependent manner

There is now compelling evidence that the GIM shifts in both people living with SCI and animal models of disease,6,67,75,76,130 with several chronic pain conditions known to be affected by these changes.4,55,107,116 The GIM also plays an important role in immune system maturation and activation,70,81,113,129 a key driver of central and neuropathic pain.6,55,75,76,116 Given its multifaceted role, we first sought to perform a longitudinal analysis of the GIM in the compression and contusion models of SCI, which exhibit differing pain profiles. A significant shift in the overall bacterial population was observed in mice that underwent a compression injury (PERMANOVA, P < 0.012), but not in those that received a contusion injury (PERMANOVA, P = 0.057; Figs. 2A–C) or in sham controls (PERMANOVA, P = 0.437). We next visualized the overall community composition of mice in the 3 experimental groups (sham, contusion, and compression) at baseline and 3, 13, and 41 dpi and saw changes in specific orders of bacteria throughout time and within compression mice compared with sham mice (Fig. 1D). Specifically, we observed a depletion of the orders Bifidobacteriales, Lactobacillales, Erysipelotrichales, and Verrucomicrobiales (Fig. 2D), for which we calculated the percent abundance of each genus within each sample and the fold change from baseline (0 dpi) to 3, 13, and 41 dpi. We found a significant depletion in Bifidobacterium, within the order Bifidobacteriales, at 3 dpi in both the sham and compression groups (9.5-fold decrease [P < 0.006] and 7.2-fold decrease [P < 0.023], respectively; Fig. 2E). We also found a significant decrease in the genus Akkermansia, within the order Verrucomicrobiales, at 13 dpi within the compression injury group (13.3-fold decrease, P < 0.043; Fig. 2F). Thus, the GIM exhibits injury severity–dependent and time-dependent shifts after SCI.

F2
Figure 2.:
Severity of gut dysbiosis was influenced by the severity of spinal cord injury. (A) PCA ordination of sham mice throughout time. (B) PCA ordination of contusion mice throughout time. (C) PCA ordination of compression mice throughout time. Black triangles represent baseline, red squares represent 3dpi, yellow diamonds represent 13dpi, and blue circles represent 43dpi. (D) Overall community composition of the GIM, grouped by injury severity and day of injury. Each different colour represents a different order of bacteria. The size of the coloured band represents the percent abundance of that specific order. (E and F) Fold change of each day compared with baseline. Black bars represent the sham group, blue bars represent the contusion injury group, and red bars represent the compression injury group. (E) There was a significant depletion in Bifidobacterium levels 3 days postinjury in the sham and compression groups. Reductions, although not significant, were still observed at 13 and 41 days after SCI. (F) Akkermansia levels were reduced in the compression group at all timepoints, reaching significance 13 days after SCI. There was minimal change in Akkermansia in both sham and contusion groups. *P < 0.05, **P < 0.01, ***P < 0.001. PCA, principal component ordination; SCI, spinal cord injury.

3.3. Compression to the spinal cord reduces myelin sparing and increases CD11b+ staining but does not affect glial scar manifestation compared with contusion injury

We next sought to determine whether changes in recovery were correlated with histopathology, potentially suggesting the mechanisms underlying the observed behaviour, locomotor, and microbiome differences observed. Myelin sparing, which negatively correlates with hypersensitivity,32,63 was assessed using Luxol fast blue (Fig. 3A, bottom row) by measuring the length of total demyelination and percentage of myelin loss throughout the spinal cord. Myelin loss measured in coronal sections revealed significantly less myelin sparing in the spinal cord of mice with a compression injury, relative to the contusion group, at and up to 500 μm rostral to the epicentre of injury at 7 dpi (P ≤ 0.05; Fig. 3B), as well as at and up to 252 μm rostral to the epicentre at 43 dpi (P ≤ 0.043; Fig. 3B). However, compression injury did not result in an increase in the total length of demyelination in the spinal cord relative to the contusion injury group at 7 dpi (P = 0.188; Fig. 3C) or 43 dpi (P = 0.055).

F3
Figure 3.:
Spinal cord lesion, but not glial scar, and CD11b+ cell infiltration were increased with compression vs contusion injury. (A) Representative images of fluorescent (top) and Luxol fast blue (bottom) staining. Scale bar is 500 µm. (B) Significantly less myelin was spared at both 7 and 43dpi in the compression vs contusion injury group. (C) However, a significantly longer lesion length was not observed in mice that received compression compared with those that received contusion alone (n = 4-7 per group for B and C). (D) A significantly larger spinal cord area was stained positive for CD11b, a marker of microglia or macrophages, at 43dpi in compression injury vs contusion injury mice. (E) At 43dpi, a longer length of CD11b expression was observed rostral and caudal to the epicentre. A significant difference was not observed in the (F) area or (G) volume of the glial scar, as measured by GFAP-positive staining (n = 3-6 per group for D–G). Negative values denote rostral to the epicentre of injury, whereas positive denotes caudal (B, D, and F). A two-way repeated-measures ANOVA with the Tukey post hoc test were used for panels B, D, and F. A one-way repeated-measures ANOVA was used for panels (C, E, and G). *P < 0.05, **P < 0.01, ***P < 0.001. *Denotes significance at 7 dpi, and # denotes significance at 43dpi between contusion and compression injuries. ANOVA, analysis of variance.

Myelin loss is often the result of an inflammatory response in the spinal cord. In particular, microglia or macrophages contribute to secondary damage, and astrocytes control the formation of a glial scar.100,148 Therefore, we performed immunostaining for CD11b (microglia or macrophages) and GFAP (astrocytes) to quantify levels of these 2 cell types (Fig. 3A). We did not find a significant difference in CD11b+ immunostaining between the 2 injury groups at 7 dpi, which was measured as the percent area of the cord with CD11b immunoreactivity; however, at 43 dpi, a significantly higher infiltration of macrophages was observed both rostral and caudal to the epicentre for the compression model compared with the contusion model (P ≤ 0.007; Fig. 3D). There was no significant difference in CD11b immunoreactivity length along the spinal cord between injury models at 7dpi (P = 0.575; Fig. 3E), whereas there was at 43dpi (P = 0.041). The percent area of the spinal cord taken up by the glial scar and the total volume of the glial scar were not significantly different between injury groups at either tested time point (P = 0.529 and P ≥ 0.115, respectively; Figs. 3F and G). The scar volume tended to be larger at 7 dpi compared with 43 dpi for both injury types, and overall, the compression injury tended to display a larger volume compared with the contusion injury at both timepoints, although this was not significant. These results suggest that the compression model induced a more robust myeloid response than contusion alone but did not significantly exacerbate astrocytic responses in the spinal cord. However, both injury groups showed significantly increased glial fibrillary acidic protein (GFAP)--immunoreactivity compared with laminectomy controls, in which a glial scar was not observed, with the percent area of the glial scar peaking at or near the injury epicentre. Our work demonstrated that a more severe SCI resulted in decreased myelin sparing in the spinal cord and CD11b expression. However, GFAP expression and the glial scar were unaffected by differing severity.

3.4. Immune cell infiltration occurs to a greater extent after compression injury compared with contusion injury

Owing to the differences of CD11b staining observed using IHC, flow cytometry was used to more deeply phenotype the immune cell difference in the 2 injury models. Flow cytometry was used to examine the presence of myeloid and lymphoid cells in the spinal cord near the injury epicentre. There was no significant difference in the proportion of microglia (CD45lowCD11b+) between the 2 injury groups (contusion and compression) at either 7 or 43 dpi. However, there were significantly higher proportions of microglia in the compression injury at 7 dpi compared with both the compression group at 43 dpi and the sham control (P < 0.001; Fig. 4A). Although there was, on average, a two-fold greater proportion of microglia at 7 dpi in the contusion group compared with shams, this effect was not significant. A significantly higher proportion of infiltrating macrophages (CD45highCD11b+) was observed relative to sham controls for both the contusion and compression groups at 7 dpi and the compression group at 43 dpi (P < 0.046; Fig. 4B). There was a significantly greater proportion of macrophages in the compression compared with contusion injury at 7 dpi (P < 0.001), but this difference was lost at 43 dpi (P = 0.828). Infiltrating lymphoid cells (CD45highCD11b), which include T and B cells, were significantly increased by both contusion (P = 0.002) and compression (P < 0.001) injuries at 7 dpi relative to sham (Fig. 4C). We also observed an overall decrease in the proportion of these cells at 43 dpi relative to 7 dpi (P < 0.002), but there were no differences between the 2 injury severities at either timepoint (P = 0.196 and P = 0.909, respectively).

F4
Figure 4.:
Increased proportions of Ly6C+ macrophages are observed in the spinal cord after a compression SCI. Flow cytometry of the thoracic spinal cord at 7 and 43dpi was used to assess the proportions of microglia (CD45LowCD11b+), monocytes or macrophages (CD45HighCD11b+), and lymphoid cells (CD45HighCD11b). F4/80 and Ly6C were used to assess the activation states of microglia (CD45LowCD11b+F4/80+) and macrophages (CD45HighCD11b+Ly6C+, n = 6-10 per group). Graphs are shown as percent of singlets. (A) Microglia numbers peaked 7dpi in the compression model, whereas no significant difference was observed in the contusion injury in comparison with other conditions tested. (B) Infiltrating monocyte or macrophages peaked at 7dpi for both injury models; however, significantly more monocytes or macrophages were seen in the compression injury. (C) Infiltrating lymphoid cells also peak at 7dpi for both injuries, with no differences observed between injury groups. (D) The proportion of microglia that is F4/80 peaked at 7dpi for a compression injury, with no significant differences observed in the contusion injury. (E) The proportion of Ly6C+ macrophages peaked at 7dpi for both injury models, but significantly more were observed in the compression model than a contusion injury. One-way RM ANOVA was used for figures A-E. *P < 0.05, **P < 0.01, ***P < 0.001. ANOVA, analysis of variance; SCI, spinal cord injury.

We also assessed specific states of myeloid cells using F4/80+, a marker of phagocytic microglia, and Ly6C, a cell-surface marker of proinflammatory macrophages. The proportion of phagocytic microglia was increased at 7 dpi in the compression group relative to sham controls (P = 0.005; Fig. 4D) and vs that of the same group at 43 dpi (P = 0.001). There were no significant differences in the proportion of phagocytic microglia in the contusion model at 7 or 43 dpi in comparison with sham (P = 0.619 and P = 0.963, respectively). Finally, we assessed the proportion of proinflammatory macrophages and found a significant increase at 7 dpi in both the contusion and compression groups relative to sham (P < 0.001; Fig. 4E), with significantly greater cells in the compression relative to the contusion group at this timepoint (P = 0.008). Although there were a greater proportion of these proinflammatory cells in both groups at 43 dpi, this was not significant relative to sham controls (P > 0.080). There were significantly greater proportions of Ly6C+ cells 7dpi in comparison with 43dpi in the compression model (P < 0.001); this trend was not observed in the contusion model (P = 0.220).

3.5. Inflammatory cytokine expression increases in the spinal cord after injury and is exacerbated in mice with a compression vs contusion injury

Given that we identified differences in immune cell profiles between the 2 injury groups, we wondered whether there were also differences in levels of key cytokines that might mediate effects of these immune cells. We used quantitative real-time PCR to assess the expression of specific cytokines and chemokines at the spinal cord injury site. We found a significantly higher expression of both Tnfα and Il1β transcripts in both contusion and compression injury groups relative to sham controls at 3 dpi and extending out to 43dpi (P ≤ 0.026, and P ≤ 0.024; Figs. 5A and B). In comparison, Infγ expression was a significantly increased beginning 7dpi in the contusion injury compared with shams (P ≤ 0.027; Fig. 5C), whereas a significance between compression injury and sham was observed beginning 14dpi (P ≤ 0.013). Significant differences were observed between the contusion and compression groups at 3 and 7 dpi for Tnfα (P ≤ 0.022) and at 3 dpi for Il1β (P = 0.012). There were no significant differences in Ifnγ expression between the injury models over the 43-day follow-up period after injury (P ≥ 0.094). These results suggest an increase in inflammation after SCI and that the amount of inflammation is injury severity dependent. The differences in Tnfα and Il1β expression between the 2 injury groups are seen acutely after injury, aligning with the differences in Ly6C+ macrophage infiltration seen in the spinal cord.

F5
Figure 5.:
Compression SCI results in an acute increase in proinflammatory cytokines compared with a contusion SCI. TNF-α, IL-1β, and IFN-γ RNA expression in the thoracic spinal cord were measured using quantitative real-time PCR (n = 3-5/per group). Relative gene expression was calculated using the 2-ΔΔCT method and log transformed. Significantly higher expression of (A) Tnfα and (B) Il1β were measured in the compression injury early after injury, compared with the contusion injury. (C) No significant differences were observed between the injury models for Ifnγ. An unpaired two-tailed t test was used to test for significance. *P < 0.05, **P < 0.01, ***P < 0.001. SCI, spinal cord injury.

3.6. Proportions of Ly6C+ macrophages are increased in the dorsal root ganglia after compression injury vs contusion injury

In addition to examining immune cell changes in the spinal cord, we assessed immune cell infiltration into the DRG using flow cytometry, focusing on levels L4, L5, and L6. These DRGs were selected as their dorsal root will enter the spinal cord around the location of the injury. Dorsal root ganglia were examined as they have been shown to be a key location in pain processing in other nervous system injuries.14,58,145 There was no significant difference in the proportion of T cells (CD11bTCRβ+) in any condition investigated in comparison with sham controls (P ≥ 0.326; Fig. 6A). There was, however, a significant decrease in T cells from 7 dpi to 43 dpi in the compression model (P = 0.041). Unlike in the spinal cord, there were no differences observed for the proportion of infiltrating monocytes or macrophages (CD11b+Ly6G) between the injury groups at any timepoint (P = 0.986; Fig. 6B). There were also no significant differences observed in the proportion of neutrophils (CD11b+Ly6G+; P = 0.066; Fig. 6C), although there was a trend of increased neutrophils at 7 dpi compared with 43 dpi and sham groups. The proportion of proinflammatory monocytes or macrophages, however, was increased in the compression group at 43 dpi relative to sham controls (CD11b+Ly6GLy6C+, P = 0.003; Fig. 6D) and to the contusion group (P = 0.0022). Overall, we found that the immune response after SCI is tissue specific and differs based on injury severity, with increased immune cell infiltration and activation occurring after a more severe injury.

F6
Figure 6.:
The spinal cord's compression results in increased proportions of Ly6C+ macrophages in the DRG. Flow cytometry of DRG L4, L5, and L6 was used to determine the proportions of T cells (CD11bTCRβ+), monocytes or macrophages (CD11b+Ly6G), neutrophils (CD11b+Ly6G+), and Ly6C+ macrophages (CD11b+Ly6GLy6C+). Both L4, L5, and L6 DRG were extracted and pooled with a second mouse, n = 4 to 5 per group. Graphs are displayed as a percent of singlets. (A) A significant decrease in T cells was observed from 7 to 43dpi in the compression model, with no other significance being seen between other tested conditions. No significant differences were observed in the proportions of (B) monocytes or macrophages and (C) neutrophils. (D) A significant increase in the proportion of macrophages that are Ly6C+ was observed 43 days after a compression injury compared with the contusion injury and sham control. One-way RM ANOVA was used for figures A-E. *P < 0.05, **P < 0.01, ***P < 0.001. DRG, dorsal root ganglia.

4. Discussion

Compression of the spinal cord occurs in most SCI cases, which contributes to worsened clinical recovery.56 Chronic pain is one of the most common clinical sequelae of SCI and can significantly impact the quality of life.18 Many rodent studies do not evaluate compression during SCI but those that do have shown that the extent of neurological deficit is often determined by the magnitude and duration of compression.20,35,121,124 Dysbiosis of the GIM can result in altered states of neuroinflammation39 and a reduction of locomotor recovery after SCI.74 We therefore sought to determine how compression of the spinal cord in the mouse alters functional outcomes, neuroinflammation, and GIM composition. Our work demonstrates that many outcomes after SCI are severity dependent, including hypersensitivity, GIM dysbiosis, locomotor recovery, demyelination, and immune cell infiltration. This work represents an in-depth, longitudinal assessment of SCI and its pain component, focusing on acute and chronic timepoints.

There is extensive literature demonstrating the presence of an altered microbiome after SCI in both patients and laboratory models.68,74,82,85,99,142,143 People living with SCI frequently experience bowel dysfunction after injury, with the GIM implicated in bowel dysfunction.143 There is a great deal of variability in microbiota populations that change after injury in the current literature, which may be due to a multitude of factors unrelated to the injury, including sex, race, age, or geographical location of the study.23,65,89,141 Decreased Dialister, Megamonas, and Pseudobutyrivibrio54,85,142,143 and increased Bacteroides, Blautia, and Escherichia shigella142,143 are generally observed in SCI patients. We now provide the first demonstration that this GIM dysbiosis is dependent on injury severity. We observed a decrease in Akkermansia at 13dpi after compression SCI and Bifidobacterium at 3dpi in the sham control and compression SCI. Although we observe different changes in the bacterial populations as previously reported, this could be due to differences in the water, food, and bedding of the mice across these studies. Although animal studies have shown correlations between severity of dysbiosis and decreased locomotor recovery and white matter sparing and increased macrophage infiltration into the spinal cord,74 our study is the first to demonstrate that the severity of the injury influences the degree of GIM dysbiosis. Previous studies investigating changes to the GIM after SCI in rodents have found a decrease in Firmicutes68,95 and an increase in Bacteroidetes and Clostridiales.68,74,95 Providing or increasing Akkermansia reduces pain or hypersensitivity in humans31 and rodents25,53 and decreased levels of Akkermansia are correlated with the presence of pain.109Bifidobacterium is a part of the family Bifidobacteriaceae, which has been shown to increase at 8 weeks post-SCI.99 Interestingly, patients with fibromyalgia have significantly less Bifidobacterium than age-matched and environment-matched controls.29 It is possible that the increased dysbiosis in our compression model is affecting the immune system, resulting in differing pain outcomes because of the prominent role of the GIM in immune system regulation.6

Various studies have provided detailed characterizations of the development and maintenance of pain-like response in rodents after clip-compression injury,17,61 with some studies having assessed longitudinal changes in pain.41,69,83 Mechanical hypersensitivity is most often observed by 14dpi, although some have found it to develop as early as 7dpi or late as 28dpi.42,72,84,91,108,119,128,131,134 The emergence of thermal heat hypersensitivity shows greater variability but often has an onset between 7 to 21dpi.22,24,41,87,93,97 Our results show that hypersensitivity after moderate contusion injury follows trends like those observed by others who used similar injury severities.73,128,137 Moreover, we observed that the compression SCI exhibited an earlier and more severe onset of mechanical hypersensitivity as well as an earlier onset in thermal heat hypersensitivity. Although there is some conflicting evidence as to how completeness of injury influences the incidence of pain,36,94,120 patients who live with a more severe complete SCI report a greater pain intensity.34,110 This trend is similar to those observed here: Mice with a more severe injury also showed an increase in hypersensitivity.

Spinal cord injury mice develop chronic hypersensitivity dependent on injury severity, with more severe contusion of the spinal cord resulting in an earlier and more severe reduction in mechanical and thermal thresholds.10,37 Although these studies investigated how increasing the force of impact altered the pathology of SCI, we identified similar trends in hypersensitivity, locomotor ability, demyelination, and neuroinflammation as compression time is increased. Similar effects have been observed in the development of chronic pain in humans.77 In most cases of SCI in humans, pain starts within a year after injury and can be experienced for many years thereafter.115,133 Therefore, our compression model recapitulates aspects of pain experienced by patients with SCI.

The influx of peripheral immune cells into the spinal cord after injury has been well documented in previous studies.11,125 However, whether compression of the spinal cord affects the immune response in the spinal cord and DRG remains understudied. Our results showed significantly greater numbers of macrophages at 7dpi after compression injury than with contusion SCI, aligning with previous studies.45,47 This work suggests that the extent of macrophage infiltration could depend on the severity of the injury; others have shown similar results.52,86 Although these studies assessed whether force of impact affected the immune response, we studied the contribution of spinal cord compression. Our results suggest that compression of the spinal cord does not influence the proportion of lymphoid cells in the spinal cord, which appear at 7dpi. However, our results suggest that compression of the spinal cord results in greater proportions of proinflammatory macrophages acutely after injury, which could affect pain, locomotor outcomes, and myelin sparing. Recruitment of peripheral blood monocytes and activation of both monocytes and microglia in the cord are critical in the development of chronic pain in the spinal cord through the release of proinflammatory cytokines such as TNF-α and IL-1β.60,104 Interestingly, we found increased expression of both Tnfα and Il1β in the spinal cord after compression injury compared with contusion at several timepoints, consistent with previous findings.60,139

Inflammation in the DRG is not commonly evaluated after SCI but has been studied in other conditions, such as diabetic neuropathy and peripheral nerve injury.1,98,135,144 A recent SCI study that did examine the DRG 30dpi found that the number of macrophages entering the DRG correlated with an increase in pain.27 We did not observe a change in the proportion of macrophages infiltrating the DRG compared with sham; however, we did observe a change to a more proinflammatory activation state (Ly6C+) 43dpi in the compression model, but not after contusion. The differences observed may be due to a species effect, as Chhaya and colleagues used Sprague–Dawley rats, or a methodological difference, as they identified macrophages by ED1 histological staining.27 The presence of Ly6C+ macrophages in the DRG could play a role in the secretion of proinflammatory cytokines that help regulate nociception.98 Activation of these cells, and their presence in the DRG,15 may be regulated by bacterial translocation from the GI tract because of a breakdown of the intestinal epithelium because of gut dysbiosis.19,112

Our study provides an extensive, longitudinal characterization of neuroinflammation, hypersensitivity, and GIM in mice after different degrees of SCI. Although the molecular or cellular mechanisms regulating the disparity that occurs between contusion and compression injury remains unknown, several possibilities arise. First, compression SCI likely results in increased vascular leakage at the site of injury. Recruitment and activation of immune cells are known to be regulated by hypoxia or ischemia or reperfusion. After an ischemia or reperfusion event, there is an accumulation of inflammatory cells in the gray matter.102 Specifically, increasing numbers of peripheral macrophages and levels of TNF-α and Il-1β were observed with more extensive paralysis.2,57,96 There is also evidence of changes to the GIM after ischemic events, which was shown to increase peripheral inflammation.13,111,140 Second, the increased damage in the cord after compression may damage nociceptor afferents to a greater degree than contusion injury. This damage would not only alter sensory neuron excitability in the DRG123,138,147 but may also cause increased neuropeptide secretion along the nociceptor arc. Substance P, vasoactive intestinal peptide, and calcitonin gene–related peptide, eg, are secreted by nociceptors after nerve injury and can regulate the GIM5,40,80 and immune cell activation.8,28,127 Increased gut dysbiosis has also been correlated with increased inflammation and decreased locomotor recovery after SCI.95 Future studies focusing on these and other pathways will help uncover how injury severity can control these changes in neuroinflammation and GIM dysbiosis. Although there are currently no effective therapeutics available for the treatment SCI pain, our modified injury model may aid in the understanding of mechanisms contributing to SCI pain.

Conflict of interest statement

The authors have no conflicts of interest to declare.

Acknowledgements

This work was supported by grants from the Chronic Pain Network of the Canadian Institutes of Health Research Strategy for Patient-Oriented Research (CIHR-SPOR grant SCA-145102), Conquer Paralysis Now Foundation (to NG), and the Bryon Riesch Paralysis Foundation (to NG). CAB is funded by a Queen Elizabeth II Graduate Student Fellowship and Faculty of Medicine Dean's PhD Award. The authors declare no conflicts of interest related to the research or article.

References

[1]. Agarwal N, Helmstadter J, Rojas DR, Bali KK, Gangadharan V, Kuner R. Evoked hypoalgesia is accompanied by tonic pain and immune cell infiltration in the dorsal root ganglia at late stages of diabetic neuropathy in mice. Mol Pain 2018;14:1744806918817975.
[2]. Akuzawa S, Kazui T, Shi E, Yamashita K, Bashar AH, Terada H. Interleukin-1 receptor antagonist attenuates the severity of spinal cord ischemic injury in rabbits. J Vasc Surg 2008;48:694–700.
[3]. Amo-Aparicio J, Martinez-Muriana A, Sanchez-Fernandez A, Lopez-Vales R. Neuroinflammation quantification for spinal cord injury. Curr Protoc Immunol 2018;123:e57.
[4]. Arora HC, Eng C, Shoskes DA. Gut microbiome and chronic prostatitis/chronic pelvic pain syndrome. Ann Transl Med 2017;5:30.
[5]. Augustyniak D, Nowak J, Lundy FT. Direct and indirect antimicrobial activities of neuropeptides and their therapeutic potential. Curr Protein Pept Sci 2012;13:723–38.
[6]. Bannerman CA, Douchant K, Sheth PM, Ghasemlou N. The gut-brain axis and beyond: microbiome control of spinal cord injury pain in humans and rodents. Neurobiol Pain 2021;9:100059.
[7]. Bao F, Fleming JC, Golshani R, Pearse DD, Kasabov L, Brown A, Weaver LC. A selective phosphodiesterase-4 inhibitor reduces leukocyte infiltration, oxidative processes, and tissue damage after spinal cord injury. J Neurotrauma 2011;28:1035–49.
[8]. Baral P, Umans BD, Li L, Wallrapp A, Bist M, Kirschbaum T, Wei Y, Zhou Y, Kuchroo VK, Burkett PR, Yipp BG, Liberles SD, Chiu IM. Nociceptor sensory neurons suppress neutrophil and gammadelta T cell responses in bacterial lung infections and lethal pneumonia. Nat Med 2018;24:417–26.
[9]. Basso DM, Fisher LC, Anderson AJ, Jakeman LB, McTigue DM, Popovich PG. Basso Mouse Scale for locomotion detects differences in recovery after spinal cord injury in five common mouse strains. J Neurotrauma 2006;23:635–59.
[10]. Batista CM, Mariano ED, Onuchic F, Dale CS, Dos Santos GB, Cristante AF, Otoch JP, Teixeira MJ, Morgalla M, Lepski G. Characterization of traumatic spinal cord injury model in relation to neuropathic pain in the rat. Somatosens Mot Res 2019;36:14–23.
[11]. Beck KD, Nguyen HX, Galvan MD, Salazar DL, Woodruff TM, Anderson AJ. Quantitative analysis of cellular inflammation after traumatic spinal cord injury: evidence for a multiphasic inflammatory response in the acute to chronic environment. Brain 2010;133:433–47.
[12]. Belkaid Y, Harrison OJ. Homeostatic immunity and the microbiota. Immunity 2017;46:562–76.
[13]. Benakis C, Brea D, Caballero S, Faraco G, Moore J, Murphy M, Sita G, Racchumi G, Ling L, Pamer EG, Iadecola C, Anrather J. Commensal microbiota affects ischemic stroke outcome by regulating intestinal gammadelta T cells. Nat Med 2016;22:516–23.
[14]. Bravo-Caparros I, Ruiz-Cantero MC, Perazzoli G, Cronin SJF, Vela JM, Hamed MF, Penninger JM, Baeyens JM, Cobos EJ, Nieto FR. Sigma-1 receptors control neuropathic pain and macrophage infiltration into the dorsal root ganglion after peripheral nerve injury. FASEB J 2020;34:5951–66.
[15]. Brenchley JM, Price DA, Schacker TW, Asher TE, Silvestri G, Rao S, Kazzaz Z, Bornstein E, Lambotte O, Altmann D, Blazar BR, Rodriguez B, Teixeira-Johnson L, Landay A, Martin JN, Hecht FM, Picker LJ, Lederman MM, Deeks SG, Douek DC. Microbial translocation is a cause of systemic immune activation in chronic HIV infection. Nat Med 2006;12:1365–71.
[16]. Brinkhof MW, Al-Khodairy A, Eriks-Hoogland I, Fekete C, Hinrichs T, Hund-Georgiadis M, Meier S, Scheel-Sailer A, Schubert M, Reinhardt JD, Swi SCISG. Health conditions in people with spinal cord injury: contemporary evidence from a population-based community survey in Switzerland. J Rehabil Med 2016;48:197–209.
[17]. Bruce JC, Oatway MA, Weaver LC. Chronic pain after clip-compression injury of the rat spinal cord. Exp Neurol 2002;178:33–48.
[18]. Burke D, Lennon O, Fullen BM. Quality of life after spinal cord injury: the impact of pain. Eur J Pain 2018;22:1662–72.
[19]. Canani RB, Costanzo MD, Leone L, Pedata M, Meli R, Calignano A. Potential beneficial effects of butyrate in intestinal and extraintestinal diseases. World J Gastroenterol 2011;17:1519–28.
[20]. Carlson GD, Gorden CD, Nakazowa S, Wada E, Warden K, LaManna JC. Perfusion-limited recovery of evoked potential function after spinal cord injury. Spine 2000;25:1218–26.
[21]. Carpenter RS, Jiang RR, Brennan FH, Hall JCE, Gottipati MK, Niewiesk S, Popovich PG. Human immune cells infiltrate the spinal cord and impair recovery after spinal cord injury in humanized mice. Sci Rep 2019;9:19105.
[22]. Castany S, Gris G, Vela JM, Verdu E, Boadas-Vaello P. Critical role of sigma-1 receptors in central neuropathic pain-related behaviours after mild spinal cord injury in mice. Sci Rep 2018;8:3873.
[23]. Chen L, Zhang YH, Huang T, Cai YD. Gene expression profiling gut microbiota in different races of humans. Sci Rep 2016;6:23075.
[24]. Chen MJ, Kress B, Han X, Moll K, Peng W, Ji RR, Nedergaard M. Astrocytic CX43 hemichannels and gap junctions play a crucial role in development of chronic neuropathic pain following spinal cord injury. Glia 2012;60:1660–70.
[25]. Chen Y, Xiao S, Gong Z, Zhu X, Yang Q, Li Y, Gao S, Dong Y, Shi Z, Wang Y, Weng X, Li Q, Cai W, Qiang W. Wuji wan formula ameliorates diarrhea and disordered colonic motility in post-inflammation irritable bowel syndrome rats by modulating the gut microbiota. Front Microbiol 2017;8:2307.
[26]. Cherry JD, Olschowka JA, O'Banion MK. Neuroinflammation and M2 microglia: the good, the bad, and the inflamed. J Neuroinflammation 2014;11:98.
[27]. Chhaya SJ, Quiros-Molina D, Tamashiro-Orrego AD, Houle JD, Detloff MR. Exercise-induced changes to the macrophage response in the dorsal root ganglia prevent neuropathic pain after spinal cord injury. J Neurotrauma 2019;36:877–90.
[28]. Chiu IM, Heesters BA, Ghasemlou N, Von Hehn CA, Zhao F, Tran J, Wainger B, Strominger A, Muralidharan S, Horswill AR, Bubeck Wardenburg J, Hwang SW, Carroll MC, Woolf CJ. Bacteria activate sensory neurons that modulate pain and inflammation. Nature 2013;501:52–7.
[29]. Clos-Garcia M, Andres-Marin N, Fernandez-Eulate G, Abecia L, Lavin JL, van Liempd S, Cabrera D, Royo F, Valero A, Errazquin N, Vega MCG, Govillard L, Tackett MR, Tejada G, Gonzalez E, Anguita J, Bujanda L, Orcasitas AMC, Aransay AM, Maiz O, Lopez de Munain A, Falcon-Perez JM. Gut microbiome and serum metabolome analyses identify molecular biomarkers and altered glutamate metabolism in fibromyalgia. EBioMedicine 2019;46:499–511.
[30]. Colombo E, Farina C. Astrocytes: key regulators of neuroinflammation. Trends Immunol 2016;37:608–20.
[31]. Cruz-Aguliar RM, Wantia N, Clavel T, Vehreschild M, Buch T, Bajbouj M, Haller D, Busch D, Schmid RM, Stein-Thoeringer CK. An open-labeled study on fecal microbiota transfer in irritable bowel syndrome patients reveals improvement in abdominal pain associated with the relative abundance of Akkermansia muciniphila. Digestion 2019;100:127–38.
[32]. David BT, Sampath S, Dong W, Heiman A, Rella CE, Elkabes S, Heary RF. A toll-like receptor 9 antagonist improves bladder function and white matter sparing in spinal cord injury. J Neurotrauma 2014;31:1800–6.
[33]. David S, Zarruk JG, Ghasemlou N. Inflammatory pathways in spinal cord injury. Int Rev Neurobiol 2012;106:127–52.
[34]. Defrin R, Ohry A, Blumen N, Urca G. Acute pain threshold in subjects with chronic pain following spinal cord injury. PAIN 1999;83:275–82.
[35]. Delamarter RB, Sherman J, Carr JB. Pathophysiology of spinal cord injury. Recovery after immediate and delayed decompression. J Bone Joint Surg Am 1995;77:1042–9.
[36]. Demirel G, Yllmaz H, Gencosmanoglu B, Kesiktas N. Pain following spinal cord injury. Spinal Cord 1998;36:25–8.
[37]. Detloff MR, Fisher LC, McGaughy V, Longbrake EE, Popovich PG, Basso DM. Remote activation of microglia and pro-inflammatory cytokines predict the onset and severity of below-level neuropathic pain after spinal cord injury in rats. Exp Neurol 2008;212:337–47.
[38]. Dhariwal A, Chong J, Habib S, King IL, Agellon LB, Xia J. MicrobiomeAnalyst: a web-based tool for comprehensive statistical, visual and meta-analysis of microbiome data. Nucleic Acids Res 2017;45:W180–8.
[39]. Dworsky-Fried Z, Kerr BJ, Taylor AMW. Microbes, microglia, and pain. Neurobiol Pain 2020;7:100045.
[40]. El Karim IA, Linden GJ, Orr DF, Lundy FT. Antimicrobial activity of neuropeptides against a range of micro-organisms from skin, oral, respiratory and gastrointestinal tract sites. J Neuroimmunol 2008;200:11–16.
[41]. Falnikar A, Hala TJ, Poulsen DJ, Lepore AC. GLT1 overexpression reverses established neuropathic pain-related behavior and attenuates chronic dorsal horn neuron activation following cervical spinal cord injury. Glia 2016;64:396–406.
[42]. Fandel TM, Trivedi A, Nicholas CR, Zhang H, Chen J, Martinez AF, Noble-Haeusslein LJ, Kriegstein AR. Transplanted human stem cell-derived interneuron precursors mitigate mouse bladder dysfunction and central neuropathic pain after spinal cord injury. Cell Stem Cell 2016;19:544–57.
[43]. Fani Maleki A, Rivest S. Innate immune cells: monocytes, monocyte-derived macrophages and microglia as therapeutic targets for alzheimer's disease and multiple sclerosis. Front Cell Neurosci 2019;13:355.
[44]. Fehlings MG, Vaccaro A, Wilson JR, Singh A, Harrop JS, Aarabi B, Shaffrey C, Dvorak M, Fisher C, Arnold P, Massicotte EM, Lewis S, Rampersaud R. Early versus delayed decompression for traumatic cervical spinal cord injury: results of the Surgical Timing in Acute Spinal Cord Injury Study (STASCIS). PLoS One 2012;7:e32037.
[45]. Fleming JC, Norenberg MD, Ramsay DA, Dekaban GA, Marcillo AE, Saenz AD, Pasquale-Styles M, Dietrich WD, Weaver LC. The cellular inflammatory response in human spinal cords after injury. Brain 2006;129:3249–69.
[46]. Garcia-Culebras A, Duran-Laforet V, Pena-Martinez C, Ballesteros I, Pradillo JM, Diaz-Guzman J, Lizasoain I, Moro MA. Myeloid cells as therapeutic targets in neuroinflammation after stroke: specific roles of neutrophils and neutrophil-platelet interactions. J Cereb Blood Flow Metab 2018;38:2150–64.
[47]. Gensel JC, Zhang B. Macrophage activation and its role in repair and pathology after spinal cord injury. Brain Res 2015;1619:1–11.
[48]. Gerber YN, Saint-Martin GP, Bringuier CM, Bartolami S, Goze-Bac C, Noristani HN, Perrin FE. CSF1R inhibition reduces microglia proliferation, promotes tissue preservation and improves motor recovery after spinal cord injury. Front Cell Neurosci 2018;12:368.
[49]. Ghasemlou N, Bouhy D, Yang J, Lopez-Vales R, Haber M, Thuraisingam T, He G, Radzioch D, Ding A, David S. Beneficial effects of secretory leukocyte protease inhibitor after spinal cord injury. Brain 2010;133:126–38.
[50]. Ghasemlou N, Chiu IM, Julien JP, Woolf CJ. CD11b+Ly6G- myeloid cells mediate mechanical inflammatory pain hypersensitivity. Proc Natl Acad Sci U S A 2015;112:E6808–6817.
[51]. Ghasemlou N, Jeong SY, Lacroix S, David S. T cells contribute to lysophosphatidylcholine-induced macrophage activation and demyelination in the CNS. Glia 2007;55:294–302.
[52]. Ghasemlou N, Kerr BJ, David S. Tissue displacement and impact force are important contributors to outcome after spinal cord contusion injury. Exp Neurol 2005;196:9–17.
[53]. Guida F, Boccella S, Belardo C, Iannotta M, Piscitelli F, De Filippis F, Paino S, Ricciardi F, Siniscalco D, Marabese I, Luongo L, Ercolini D, Di Marzo V, Maione S. Altered gut microbiota and endocannabinoid system tone in vitamin D deficiency-mediated chronic pain. Brain Behav Immun 2020;85:128–41.
[54]. Gungor B, Adiguzel E, Gursel I, Yilmaz B, Gursel M. Intestinal microbiota in patients with spinal cord injury. PLoS One 2016;11:e0145878.
[55]. Guo R, Chen LH, Xing C, Liu T. Pain regulation by gut microbiota: molecular mechanisms and therapeutic potential. Br J Anaesth 2019;123:637–54.
[56]. Hachem LD, Ahuja CS, Fehlings MG. Assessment and management of acute spinal cord injury: from point of injury to rehabilitation. J Spinal Cord Med 2017;40:665–75.
[57]. Hasturk A, Atalay B, Calisaneller T, Ozdemir O, Oruckaptan H, Altinors N. Analysis of serum pro-inflammatory cytokine levels after rat spinal cord ischemia/reperfusion injury and correlation with tissue damage. Turk Neurosurg 2009;19:353–9.
[58]. He XT, Hu XF, Zhu C, Zhou KX, Zhao WJ, Zhang C, Han X, Wu CL, Wei YY, Wang W, Deng JP, Chen FM, Gu ZX, Dong YL. Suppression of histone deacetylases by SAHA relieves bone cancer pain in rats via inhibiting activation of glial cells in spinal dorsal horn and dorsal root ganglia. J Neuroinflammation 2020;17:125.
[59]. Herrmann JE, Imura T, Song B, Qi J, Ao Y, Nguyen TK, Korsak RA, Takeda K, Akira S, Sofroniew MV. STAT3 is a critical regulator of astrogliosis and scar formation after spinal cord injury. J Neurosci 2008;28:7231–43.
[60]. Honjoh K, Nakajima H, Hirai T, Watanabe S, Matsumine A. Relationship of inflammatory cytokines from M1-type microglia/macrophages at the injured site and lumbar enlargement with neuropathic pain after spinal cord injury in the CCL21 knockout (plt) mouse. Front Cell Neurosci 2019;13:525.
[61]. Hurtado A, Marcillo A, Frydel B, Bunge MB, Bramlett HM, Dietrich WD. Anti-CD11d monoclonal antibody treatment for rat spinal cord compression injury. Exp Neurol 2012;233:606–11.
[62]. Inoue K, Tsuda M. Microglia in neuropathic pain: cellular and molecular mechanisms and therapeutic potential. Nat Rev Neurosci 2018;19:138–52.
[63]. Jalan D, Saini N, Zaidi M, Pallottie A, Elkabes S, Heary RF. Effects of early surgical decompression on functional and histological outcomes after severe experimental thoracic spinal cord injury. J Neurosurg Spine 2017;26:62–75.
[64]. Jangi S, Gandhi R, Cox LM, Li N, von Glehn F, Yan R, Patel B, Mazzola MA, Liu S, Glanz BL, Cook S, Tankou S, Stuart F, Melo K, Nejad P, Smith K, Topcuolu BD, Holden J, Kivisakk P, Chitnis T, De Jager PL, Quintana FJ, Gerber GK, Bry L, Weiner HL. Alterations of the human gut microbiome in multiple sclerosis. Nat Commun 2016;7:12015.
[65]. Jasarevic E, Morrison KE, Bale TL. Sex differences in the gut microbiome-brain axis across the lifespan. Philos Trans R Soc Lond B Biol Sci 2016;371:20150122.
[66]. Jensen TS, Finnerup NB. Allodynia and hyperalgesia in neuropathic pain: clinical manifestations and mechanisms. Lancet Neurol 2014;13:924–35.
[67]. Jing Y, Bai F, Yu Y. Spinal cord injury and gut microbiota: a review. Life Sci 2021;266:118865.
[68]. Jing Y, Yang D, Bai F, Zhang C, Qin C, Li D, Wang L, Yang M, Chen Z, Li J. Melatonin treatment alleviates spinal cord injury-induced gut dysbiosis in mice. J Neurotrauma 2019;36:2646–64.
[69]. Karimi-Abdolrezaee S, Eftekharpour E, Wang J, Schut D, Fehlings MG. Synergistic effects of transplanted adult neural stem/progenitor cells, chondroitinase, and growth factors promote functional repair and plasticity of the chronically injured spinal cord. J Neurosci 2010;30:1657–76.
[70]. Kau AL, Ahern PP, Griffin NW, Goodman AL, Gordon JI. Human nutrition, the gut microbiome and the immune system. Nature 2011;474:327–36.
[71]. Kennedy P, Hasson L. The relationship between pain and mood following spinal cord injury. J Spinal Cord Med 2017;40:275–9.
[72]. Kerr BJ, David S. Pain behaviors after spinal cord contusion injury in two commonly used mouse strains. Exp Neurol 2007;206:240–7.
[73]. Khuyagbaatar B, Kim K, Kim YH. Conversion equation between the drop height in the New York university impactor and the impact force in the infinite horizon impactor in the contusion spinal cord injury model. J Neurotrauma 2015;32:1987–93.
[74]. Kigerl KA, Hall JC, Wang L, Mo X, Yu Z, Popovich PG. Gut dysbiosis impairs recovery after spinal cord injury. J Exp Med 2016;213:2603–20.
[75]. Kigerl KA, Mostacada K, Popovich PG. Gut microbiota are disease-modifying factors after traumatic spinal cord injury. Neurotherapeutics 2018;15:60–7.
[76]. Kigerl KA, Zane K, Adams K, Sullivan MB, Popovich PG. The spinal cord-gut-immune axis as a master regulator of health and neurological function after spinal cord injury. Exp Neurol 2020;323:113085.
[77]. Kolstadbraaten KM, Spreng UJ, Wisloeff-Aase K, Gaarder C, Naess PA, Raeder J. Incidence of chronic pain 6 y after major trauma. Acta Anaesthesiol Scand 2019;63:1074–8.
[78]. Konomi T, Yasuda A, Fujiyoshi K, Yamane J, Kaneko S, Komiyama T, Takemitsu M, Yato Y, Tsuji O, Matsumoto M, Nakamura M, Asazuma T. Clinical outcomes of late decompression surgery following cervical spinal cord injury with pre-existing cord compression. Spinal Cord 2018;56:366–71.
[79]. Kubota K, Saiwai H, Kumamaru H, Kobayakawa K, Maeda T, Matsumoto Y, Harimaya K, Iwamoto Y, Okada S. Neurological recovery is impaired by concurrent but not by asymptomatic pre-existing spinal cord compression after traumatic spinal cord injury. Spine 2012;37:1448–55.
[80]. Lai NY, Musser MA, Pinho-Ribeiro FA, Baral P, Jacobson A, Ma P, Potts DE, Chen Z, Paik D, Soualhi S, Yan Y, Misra A, Goldstein K, Lagomarsino VN, Nordstrom A, Sivanathan KN, Wallrapp A, Kuchroo VK, Nowarski R, Starnbach MN, Shi H, Surana NK, An D, Wu C, Huh JR, Rao M, Chiu IM. Gut-innervating nociceptor neurons regulate peyer's patch microfold cells and SFB levels to mediate Salmonella host defense. Cell 2020;180:33–49 e22.
[81]. Levy M, Kolodziejczyk AA, Thaiss CA, Elinav E. Dysbiosis and the immune system. Nat Rev Immunol 2017;17:219–32.
[82]. Li J, Van Der Pol W, Eraslan M, McLain A, Cetin H, Cetin B, Morrow C, Carson T, Yarar-Fisher C. Comparison of the gut microbiome composition among individuals with acute or long-standing spinal cord injury vs. able-bodied controls. J Spinal Cord Med 2020. doi: 10.1080/10790268.2020.1769949 [Epub ahead of print].
[83]. Li XM, Meng J, Li LT, Guo T, Yang LK, Shi QX, Li XB, Chen Y, Yang Q, Zhao JN. Effect of ZBD-2 on chronic pain, depressive-like behaviors, and recovery of motor function following spinal cord injury in mice. Behav Brain Res 2017;322:92–9.
[84]. Li Z, Wu F, Xu D, Zhi Z, Xu G. Inhibition of TREM1 reduces inflammation and oxidative stress after spinal cord injury (SCI) associated with HO-1 expressions. Biomed Pharmacother 2019;109:2014–21.
[85]. Lin R, Xu J, Ma Q, Chen M, Wang L, Wen S, Yang C, Ma C, Wang Y, Luo Q, Zhu N. Alterations in the fecal microbiota of patients with spinal cord injury. PLoS One 2020;15:e0236470.
[86]. Lin TH, Sun P, Hallman M, Hwang FC, Wallendorf M, Ray WZ, Spees WM, Song SK. Noninvasive quantification of axonal loss in the presence of tissue swelling in traumatic spinal cord injury mice. J Neurotrauma 2019;36:2308–15.
[87]. Liu S, Huang Q, He S, Chen Z, Gao X, Ma D, Duan W, Ford N, Yang F, Chen X, Raja SN, Hao D, Guan Y. Dermorphin [D-Arg2, Lys4] (1-4) amide inhibits below-level heat hypersensitivity in mice after contusive thoracic spinal cord injury. PAIN 2019;160:2710–23.
[88]. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 2001;25:402–8.
[89]. Markle JG, Frank DN, Mortin-Toth S, Robertson CE, Feazel LM, Rolle-Kampczyk U, von Bergen M, McCoy KD, Macpherson AJ, Danska JS. Sex differences in the gut microbiome drive hormone-dependent regulation of autoimmunity. Science 2013;339:1084–8.
[90]. Marshall AS, Silva JR, Bannerman CA, Gilron I, Ghasemlou N. Skin-Resident gammadelta T Cells exhibit site-specific morphology and activation states. J Immunol Res 2019;2019:9020234.
[91]. Martini AC, Berta T, Forner S, Chen G, Bento AF, Ji RR, Rae GA. Lipoxin A4 inhibits microglial activation and reduces neuroinflammation and neuropathic pain after spinal cord hemisection. J Neuroinflammation 2016;13:75.
[92]. Matsuda M, Huh Y, Ji RR. Roles of inflammation, neurogenic inflammation, and neuroinflammation in pain. J Anesth 2019;33:131–9.
[93]. Meisner JG, Marsh AD, Marsh DR. Loss of GABAergic interneurons in laminae I-III of the spinal cord dorsal horn contributes to reduced GABAergic tone and neuropathic pain after spinal cord injury. J Neurotrauma 2010;27:729–37.
[94]. Modirian E, Pirouzi P, Soroush M, Karbalaei-Esmaeili S, Shojaei H, Zamani H. Chronic pain after spinal cord injury: results of a long-term study. Pain Med 2010;11:1037–43.
[95]. Myers SA, Gobejishvili L, Saraswat Ohri S, Garrett Wilson C, Andres KR, Riegler AS, Donde H, Joshi-Barve S, Barve S, Whittemore SR. Following spinal cord injury, PDE4B drives an acute, local inflammatory response and a chronic, systemic response exacerbated by gut dysbiosis and endotoxemia. Neurobiol Dis 2019;124:353–63.
[96]. Nakata T, Kawachi K, Nagashima M, Yasugi T, Izutani H, Ryugo M, Okamura T, Shikata F, Imagawa H, Yano H, Takahashi H, Tanaka J. Transient ischemia-induced paresis and complete paraplegia displayed distinct reactions of microglia and macrophages. Brain Res 2011;1420:114–24.
[97]. Nees TA, Tappe-Theodor A, Sliwinski C, Motsch M, Rupp R, Kuner R, Weidner N, Blesch A. Early-onset treadmill training reduces mechanical allodynia and modulates calcitonin gene-related peptide fiber density in lamina III/IV in a mouse model of spinal cord contusion injury. PAIN 2016;157:687–97.
[98]. North RY, Li Y, Ray P, Rhines LD, Tatsui CE, Rao G, Johansson CA, Zhang H, Kim YH, Zhang B, Dussor G, Kim TH, Price TJ, Dougherty PM. Electrophysiological and transcriptomic correlates of neuropathic pain in human dorsal root ganglion neurons. Brain 2019;142:1215–26.
[99]. O'Connor G, Jeffrey E, Madorma D, Marcillo A, Abreu MT, Deo SK, Dietrich WD, Daunert S. Investigation of microbiota alterations and intestinal inflammation post-spinal cord injury in rat model. J Neurotrauma 2018;35:2159–66.
[100]. Okada S, Hara M, Kobayakawa K, Matsumoto Y, Nakashima Y. Astrocyte reactivity and astrogliosis after spinal cord injury. Neurosci Res 2018;126:39–43.
[101]. Papadopoulos SM, Selden NR, Quint DJ, Patel N, Gillespie B, Grube S. Immediate spinal cord decompression for cervical spinal cord injury: feasibility and outcome. J Trauma 2002;52:323–32.
[102]. Papakostas JC, Matsagas MI, Toumpoulis IK, Malamou-Mitsi VD, Pappa LS, Gkrepi C, Anagnostopoulos CE, Kappas AM. Evolution of spinal cord injury in a porcine model of prolonged aortic occlusion. J Surg Res 2006;133:159–66.
[103]. Petrovic J, Silva JR, Bannerman CA, Segal JP, Marshall AS, Haird CM, Gilron I, Ghasemlou N. Gammadelta T cells modulate myeloid cell recruitment but not pain during peripheral inflammation. Front Immunol 2019;10:473.
[104]. Pineau I, Lacroix S. Proinflammatory cytokine synthesis in the injured mouse spinal cord: multiphasic expression pattern and identification of the cell types involved. J Comp Neurol 2007;500:267–85.
[105]. Pineau I, Sun L, Bastien D, Lacroix S. Astrocytes initiate inflammation in the injured mouse spinal cord by promoting the entry of neutrophils and inflammatory monocytes in an IL-1 receptor/MyD88-dependent fashion. Brain Behav Immun 2010;24:540–53.
[106]. Pinho-Ribeiro FA, Verri WA Jr, Chiu IM. Nociceptor sensory neuron-immune interactions in pain and inflammation. Trends Immunol 2017;38:5–19.
[107]. Pusceddu MM, Gareau MG. Visceral pain: gut microbiota, a new hope? J Biomed Sci 2018;25:73.
[108]. Qian J, Zhu W, Lu M, Ni B, Yang J. D-beta-hydroxybutyrate promotes functional recovery and relieves pain hypersensitivity in mice with spinal cord injury. Br J Pharmacol 2017;174:1961–71.
[109]. Ramakrishna C, Corleto J, Ruegger PM, Logan GD, Peacock BB, Mendonca S, Yamaki S, Adamson T, Ermel R, McKemy D, Borneman J, Cantin EM. Dominant role of the gut microbiota in chemotherapy induced neuropathic pain. Sci Rep 2019;9:20324.
[110]. Ravenscroft A, Ahmed YS, Burnside IG. Chronic pain after SCI. A patient survey. Spinal Cord 2000;38:611–14.
[111]. Rice MW, Pandya JD, Shear DA. Gut microbiota as a therapeutic target to ameliorate the biochemical, neuroanatomical, and behavioral effects of traumatic brain injuries. Front Neurol 2019;10:875.
[112]. Rios-Covian D, Ruas-Madiedo P, Margolles A, Gueimonde M, de Los Reyes-Gavilan CG, Salazar N. Intestinal short chain fatty acids and their link with diet and human health. Front Microbiol 2016;7:185.
[113]. Rizzetto L, Fava F, Tuohy KM, Selmi C. Connecting the immune system, systemic chronic inflammation and the gut microbiome: the role of sex. J Autoimmun 2018;92:12–34.
[114]. Rodrigues D, Tran Y, Wijesuriya N, Guest R, Middleton J, Craig A. Pain intensity and its association with negative mood States in patients with spinal cord injury. Pain Ther 2013;2:113–19.
[115]. Rosner J, Lutolf R, Hostettler P, Villiger M, Clijsen R, Hohenauer E, Barbero M, Curt A, Hubli M. Assessment of neuropathic pain after spinal cord injury using quantitative pain drawings. Spinal Cord 2021;59:529–37.
[116]. Russo R, Cristiano C, Avagliano C, De Caro C, La Rana G, Raso GM, Canani RB, Meli R, Calignano A. Gut-brain Axis: role of lipids in the regulation of inflammation, pain and CNS diseases. Curr Med Chem 2018;25:3930–52.
[117]. Segal JP, Bannerman CA, Silva JR, Haird CM, Baharnoori M, Gilron I, Ghasemlou N. Chronic mechanical hypersensitivity in experimental autoimmune encephalomyelitis is regulated by disease severity and neuroinflammation. Brain Behav Immun 2020;89:314314–25.
[118]. Shen S, Lim G, You Z, Ding W, Huang P, Ran C, Doheny J, Caravan P, Tate S, Hu K, Kim H, McCabe M, Huang B, Xie Z, Kwon D, Chen L, Mao J. Gut microbiota is critical for the induction of chemotherapy-induced pain. Nat Neurosci 2017;20:1213–16.
[119]. Shin JE, Jung K, Kim M, Hwang K, Lee H, Kim IS, Lee BH, Lee IS, Park KI. Brain and spinal cord injury repair by implantation of human neural progenitor cells seeded onto polymer scaffolds. Exp Mol Med 2018;50:39.
[120]. Siddall PJ, Taylor DA, McClelland JM, Rutkowski SB, Cousins MJ. Pain report and the relationship of pain to physical factors in the first 6 months following spinal cord injury. PAIN 1999;81:187–97.
[121]. Sjovold SG, Mattucci SF, Choo AM, Liu J, Dvorak MF, Kwon BK, Tetzlaff W, Oxland TR. Histological effects of residual compression sustained for 60 minutes at different depths in a novel rat spinal cord injury contusion model. J Neurotrauma 2013;30:1374–84.
[122]. Sonar SA, Lal G. Differentiation and transmigration of CD4 T cells in neuroinflammation and autoimmunity. Front Immunol 2017;8:1695.
[123]. Song XJ, Wang ZB, Gan Q, Walters ET. cAMP and cGMP contribute to sensory neuron hyperexcitability and hyperalgesia in rats with dorsal root ganglia compression. J Neurophysiol 2006;95:479–92.
[124]. Squair JW, Belanger LM, Tsang A, Ritchie L, Mac-Thiong JM, Parent S, Christie S, Bailey C, Dhall S, Street J, Ailon T, Paquette S, Dea N, Fisher CG, Dvorak MF, West CR, Kwon BK. Spinal cord perfusion pressure predicts neurologic recovery in acute spinal cord injury. Neurology 2017;89:1660–7.
[125]. Sroga JM, Jones TB, Kigerl KA, McGaughy VM, Popovich PG. Rats and mice exhibit distinct inflammatory reactions after spinal cord injury. J Comp Neurol 2003;462:223–40.
[126]. Takeura N, Nakajima H, Watanabe S, Honjoh K, Takahashi A, Matsumine A. Role of macrophages and activated microglia in neuropathic pain associated with chronic progressive spinal cord compression. Sci Rep 2019;9:15656.
[127]. Talbot S, Abdulnour RE, Burkett PR, Lee S, Cronin SJ, Pascal MA, Laedermann C, Foster SL, Tran JV, Lai N, Chiu IM, Ghasemlou N, DiBiase M, Roberson D, Von Hehn C, Agac B, Haworth O, Seki H, Penninger JM, Kuchroo VK, Bean BP, Levy BD, Woolf CJ. Silencing nociceptor neurons reduces allergic airway inflammation. Neuron 2015;87:341–54.
[128]. Tateda S, Kanno H, Ozawa H, Sekiguchi A, Yahata K, Yamaya S, Itoi E. Rapamycin suppresses microglial activation and reduces the development of neuropathic pain after spinal cord injury. J Orthop Res 2017;35:93–103.
[129]. Thaiss CA, Zmora N, Levy M, Elinav E. The microbiome and innate immunity. Nature 2016;535:65–74.
[130]. Wallace DJ, Sayre NL, Patterson TT, Nicholson SE, Hilton D, Grandhi R. Spinal cord injury and the human microbiome: beyond the brain-gut axis. Neurosurg Focus 2019;46:E11.
[131]. Wang Y, Xu X, Hu P, Jia N, Ji S, Yuan H. Effect of Toll-Like Receptor 4/Myeloid Differentiation Factor 88 Inhibition by Salvianolic Acid B on Neuropathic Pain After Spinal Cord Injury in Mice. World Neurosurg, 2019;132:e529–e534.
[132]. Wanleenuwat P, Iwanowski P. Role of B cells and antibodies in multiple sclerosis. Mult Scler Relat Disord 2019;36:101416.
[133]. Warner FM, Cragg JJ, Jutzeler CR, Finnerup NB, Werhagen L, Weidner N, Maier D, Kalke YB, Curt A, Kramer JLK. Progression of neuropathic pain after acute spinal cord injury: a meta-analysis and framework for clinical trials. J Neurotrauma 2019;36:1461–8.
[134]. Watanabe S, Uchida K, Nakajima H, Matsuo H, Sugita D, Yoshida A, Honjoh K, Johnson WE, Baba H. Early transplantation of mesenchymal stem cells after spinal cord injury relieves pain hypersensitivity through suppression of pain-related signaling cascades and reduced inflammatory cell recruitment. Stem Cells 2015;33:1902–14.
[135]. White FA, Sun J, Waters SM, Ma C, Ren D, Ripsch M, Steflik J, Cortright DN, Lamotte RH, Miller RJ. Excitatory monocyte chemoattractant protein-1 signaling is up-regulated in sensory neurons after chronic compression of the dorsal root ganglion. Proc Natl Acad Sci U S A 2005;102:14092–7.
[136]. Widerstrom-Noga E. Neuropathic pain and spinal cord injury: phenotypes and pharmacological management. Drugs 2017;77:967–84.
[137]. Wu J, Zhao Z, Zhu X, Renn CL, Dorsey SG, Faden AI. Cell cycle inhibition limits development and maintenance of neuropathic pain following spinal cord injury. PAIN 2016;157:488–503.
[138]. Wu Z, Li L, Xie F, Du J, Zuo Y, Frost JA, Carlton SM, Walters ET, Yang Q. Activation of KCNQ channels suppresses spontaneous activity in dorsal root ganglion neurons and reduces chronic pain after spinal cord injury. J Neurotrauma 2017;34:1260–70.
[139]. Xian S, Ding R, Li M, Chen F. LncRNA NEAT1/miR-128-3p/AQP4 axis regulating spinal cord injury-induced neuropathic pain progression. J Neuroimmunol 2021;351:577457.
[140]. Yamashiro K, Tanaka R, Urabe T, Ueno Y, Yamashiro Y, Nomoto K, Takahashi T, Tsuji H, Asahara T, Hattori N. Gut dysbiosis is associated with metabolism and systemic inflammation in patients with ischemic stroke. PLoS One 2017;12:e0171521.
[141]. Yatsunenko T, Rey FE, Manary MJ, Trehan I, Dominguez-Bello MG, Contreras M, Magris M, Hidalgo G, Baldassano RN, Anokhin AP, Heath AC, Warner B, Reeder J, Kuczynski J, Caporaso JG, Lozupone CA, Lauber C, Clemente JC, Knights D, Knight R, Gordon JI. Human gut microbiome viewed across age and geography. Nature 2012;486:222–7.
[142]. Zhang C, Jing Y, Zhang W, Zhang J, Yang M, Du L, Jia Y, Chen L, Gong H, Li J, Gao F, Liu H, Qin C, Liu C, Wang Y, Shi W, Zhou H, Liu Z, Yang D, Li J. Dysbiosis of gut microbiota is associated with serum lipid profiles in male patients with chronic traumatic cervical spinal cord injury. Am J Transl Res 2019;11:4817–34.
[143]. Zhang C, Zhang W, Zhang J, Jing Y, Yang M, Du L, Gao F, Gong H, Chen L, Li J, Liu H, Qin C, Jia Y, Qiao J, Wei B, Yu Y, Zhou H, Liu Z, Yang D, Li J. Gut microbiota dysbiosis in male patients with chronic traumatic complete spinal cord injury. J Transl Med 2018;16:353.
[144]. Zhang H, Boyette-Davis JA, Kosturakis AK, Li Y, Yoon SY, Walters ET, Dougherty PM. Induction of monocyte chemoattractant protein-1 (MCP-1) and its receptor CCR2 in primary sensory neurons contributes to paclitaxel-induced peripheral neuropathy. J Pain 2013;14:1031–44.
[145]. Zhang L, Xie R, Yang J, Zhao Y, Qi C, Bian G, Wang M, Shan J, Wang C, Wang D, Luo C, Wang Y, Wu S. Chronic pain induces nociceptive neurogenesis in dorsal root ganglia from Sox2-positive satellite cells. Glia 2019;67:1062–75.
[146]. Zhang X, Zhang D, Jia H, Feng Q, Wang D, Liang D, Wu X, Li J, Tang L, Li Y, Lan Z, Chen B, Li Y, Zhong H, Xie H, Jie Z, Chen W, Tang S, Xu X, Wang X, Cai X, Liu S, Xia Y, Li J, Qiao X, Al-Aama JY, Chen H, Wang L, Wu QJ, Zhang F, Zheng W, Li Y, Zhang M, Luo G, Xue W, Xiao L, Li J, Chen W, Xu X, Yin Y, Yang H, Wang J, Kristiansen K, Liu L, Li T, Huang Q, Li Y, Wang J. The oral and gut microbiomes are perturbed in rheumatoid arthritis and partly normalized after treatment. Nat Med 2015;21:895–905.
[147]. Zheng JH, Walters ET, Song XJ. Dissociation of dorsal root ganglion neurons induces hyperexcitability that is maintained by increased responsiveness to cAMP and cGMP. J Neurophysiol 2007;97:15–25.
[148]. Zhou X, He X, Ren Y. Function of microglia and macrophages in secondary damage after spinal cord injury. Neural Regen Res 2014;9:1787–95.
Keywords:

Spinal cord injury; Contusion; Pain; Neuroinflammation; Gut dysbiosis

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