Precision Nanotherapy for Spinal Cord Injury: Modulating SLC16A3 With Methylprednisolone-Loaded Nanoparticles
Article information
Abstract
Objective
Spinal cord injury (SCI) leads to severe motor and sensory deficits, with limited treatment options. This study investigates how methylprednisolone-loaded nanoparticles (MP-NPs) modulate SCI repair by targeting solute carrier family 16 member 3 (SLC16A3) and reshaping the macrophage-inflammatory microenvironment.
Methods
Transcriptome data were analyzed to identify differentially expressed genes (DEGs) associated with SCI. Immune infiltration and WGCNA (Weighted Gene Co-expression Network Analysis) identified genes linked to M2 macrophage polarization, pinpointing SLC16A3 as a key regulatory factor. MP-NPs were synthesized, characterized, and tested for their effects on macrophage polarization, neuronal protection, and SCI recovery in rats.
Results
We identified 612 DEGs related to inflammation and immune response in SCI. SLC16A3, upregulated in SCI, was downregulated by MP-NPs. In vitro, MP-NPs promoted M2 macrophage polarization, enhanced neuronal survival, and supported neural stem cell differentiation. In vivo, MP-NPs significantly improved motor recovery, reduced inflammation, and facilitated neural repair in SCI rats.
Conclusion
MP-NPs downregulate SLC16A3 and modulate the macrophage-inflammatory environment, promoting neural repair and functional recovery in SCI, offering a promising therapeutic strategy.
INTRODUCTION
Spinal cord injury (SCI) is a severe central nervous system damage often caused by incidents such as traffic accidents, sports injuries, or falls [1]. SCI not only results in significant loss of motor and sensory functions but can also lead to a range of complications, including chronic pain, autonomic nervous dysfunction, and secondary infections, greatly impacting the quality of life for patients [2,3]. Patients with SCI require long-term medical and rehabilitation care, imposing a heavy economic burden on families and society [4,5]. While current treatment modalities, such as surgical decompression, pharmacotherapy, and rehabilitation training, can, to some extent, ameliorate symptoms and facilitate partial functional recovery, most patients still struggle to fully regain normal functionality [6,7]. The main limitation of existing treatments lies in their inability to effectively curb the secondary injury processes following the initial damage, particularly inflammation and neuronal death [8-10]. Therefore, exploring novel therapeutic strategies for SCI, especially comprehensive approaches targeting inflammation control and neuronal repair, holds crucial clinical and social significance [11-13].
Macrophages are pivotal in the inflammatory response following SCI [14-16]. After SCI, macrophages are rapidly recruited to the injury site and differentiate into distinct functional subtypes under the influence of the local microenvironment, primarily including M1 (proinflammatory) and M2 (anti-inflammatory) macrophages [14,15,17]. M1 macrophages amplify the inflammatory response by secreting proinflammatory cytokines such as tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and IL-6, further exacerbating inflammation, leading to further damage and death of nerve cells [18-20]. In contrast, M2 macrophages promote tissue repair and regeneration by secreting anti-inflammatory cytokines like IL-10 and TGF-β [21,22]. The dynamic balance between M1 and M2 macrophages is crucial for the repair of neural tissue postinjury [23-25]. Studies indicate that early after SCI, M1 macrophages dominate, leading to intense inflammation and neuronal death; however, over time, the population of M2 macrophages increases, aiding in inflammation resolution and tissue repair. Therefore, regulating the polarization state of macrophages to shift from M1 to M2 is important in promoting neural tissue repair and functional recovery post-SCI [26,27].
Nanoparticles have shown significant potential in drug delivery applications due to their unique physicochemical properties. Nanoparticles offer advantages such as high surface area, high drug loading capacity, and controlled release, enabling efficient drug delivery to diseased areas, reducing nonspecific drug distribution in the body, and minimizing side effects. In recent years, nanoparticles (NPs) have made notable progress in treating various conditions, including cancer, cardiovascular diseases, and neurological disorders. Methylprednisolone (MP) is a commonly used glucocorticoid drug for treating SCI, known for its potent anti-inflammatory and immune-regulating effects [28-30]. However, traditional drug delivery methods suffer from low drug utilization and significant side effects, restricting their clinical efficacy [31-33]. Through MP-loaded NPs (MP-NPs), drug targeting and therapeutic efficacy can be enhanced while simultaneously decreasing systemic side effects. Studies indicate that NPs, by mimicking cell membrane structures, can improve drug permeability and stability on cell membranes, enhancing drug bioavailability [34,35]. Therefore, optimizing the drug delivery system with MP-NPs holds promise as a novel strategy for SCI treatment.
Solute carrier family 16 member 3 (SLC16A3), also known as MCT4, is a monocarboxylate transporter protein expressed in various cell types, involved in the transmembrane transport of metabolites such as lactate and pyruvate [36]. Recently, the role of SLC16A3 in inflammation and metabolic regulation has garnered increasing attention [37,38]. Studies have observed upregulation of SLC16A3 in SCI, potentially influencing macrophage polarization by regulating their metabolic state [39,40]. Specifically, the upregulation of SLC16A3 is associated with enhanced proinflammatory response in M1 macrophages, while inhibiting SLC16A3 expression can promote macrophage transition to the M2 phenotype, reducing inflammation and facilitating tissue repair [41,42]. MP, a glucocorticoid, can modulate the inflammatory response through various mechanisms, including downregulating SLC16A3 expression [43-45]. Through transcriptomic data analysis and immune infiltration profiling, this study identifies SLC16A3 as a critical regulatory factor in SCI, offering a new molecular basis for SCI treatment. Targeted modulation of SLC16A3 holds the promise of precise control over macrophage polarization states, optimizing the inflammatory microenvironment and promoting neural tissue repair.
This study investigated the multifunctional MP-NPs’ mechanism in promoting SCI repair in rats by downregulating the key regulatory factor SLC16A3 to reshape the macrophage-inflammatory microenvironment. By integrating transcriptomic datasets related to SCI, differential expression and functional enrichment analyses were conducted, along with immune infiltration analysis and Weighted Gene Co-expression Network Analysis (WGCNA), to identify a gene set significantly associated with the M2 macrophage module and to pinpoint the key regulatory factor SLC16A3 targeted by MP. MP-NPs were synthesized using a self-assembly method, followed by a series of physicochemical characterizations and in vitro and in vivo experiments to evaluate drug loading efficiency, release kinetics, and biological effects. In vitro experiments involved assessing the nanoparticles’ effects on lipopolysaccharide (LPS)-induced RAW264.7 cell viability, proinflammatory cytokine expression, macrophage polarization marker expression, and the impact on apoptosis, astrocyte, and neuron marker expression through cocultures of RAW264.7 cells with neural stem cells (NSCs). In vivo experiments included establishing a rat SCI model to evaluate the MP-NP’s effects on rat motor function recovery, inflammation factor levels, neural tissue repair, and M1/M2 macrophage marker expression. This study confirmed the efficacy of MP-NPs in SCI treatment, offering a novel strategy for SCI therapy. By modulating SLC16A3 and macrophage polarization, this research provides new theoretical basis and treatment targets for SCI repair, potentially improving prognosis for SCI patients, with significant scientific and clinical implications.
MATERIALS AND METHODS
1. Public Data Download
Five transcriptome datasets related to SCI, namely GSE45006, GSE15878, GSE185600, GSE229618, and GSE151371, were retrieved from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/). Detailed information about these datasets can be found in Supplementary Table 1. Initially, probe IDs were converted into gene names utilizing the probe annotation files. In cases where multiple probes corresponded to the same gene, the average value was calculated to represent the final gene expression value. Furthermore, the “sva” R package mitigated batch effects across the different datasets. GSE151371 was utilized as an external validation dataset.
2. Differential Expression Analysis
Differentially expressed genes (DEGs) were selected from the integrated transcriptome data using the “limma” R package with thresholds set at |log2FoldChange|>0.5 and p<0.05. DEGs were visualized using the “ggplot2” and “pheatmap” R packages to generate volcano plots and heatmaps, respectively.
3. Gene Ontology/Kyoto Encyclopedia of Genes and Genomes Enrichment Analysis
The “clusterProfiler” R package was employed for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on the DEGs. A significance threshold of p<0.05 was set for the analysis.
4. Immune Infiltration Analysis
The CIBERSORT method was utilized to quantitatively analyze the composition of immune cells in the SCI samples. The permutations were set to 1000, with a significance threshold of p<0.05 during runtime to quantify the relative abundance of 25 immune cell types. The percentage of immune cells in the samples was visualized using the “ggpubr” and “vioplot” packages in R, which generated bar plots and violin plots, respectively.
5. Weighted Gene Co-expression Network Analysis
The gene co-expression network was constructed using the WGCNA package to identify gene modules significantly associated with M2 macrophage infiltration. The optimal soft-thresholding power β was determined to establish a scale-free network. Genes with similar expression profiles were hierarchically clustered using average linkage clustering to form gene modules. Subsequently, the correlation between modules and M2 macrophage infiltration was calculated, and the module with the highest correlation to M2 macrophage infiltration was selected.
6. Identification of Key Regulatory Factors
Differential analysis was performed on SCI rats treated with and without MP in the GSE15878 dataset to identify potential target genes of MP. The interaction between MP target genes and previously identified SCI-related genes and M2-related genes was analyzed using online tools to ascertain key regulatory factors involved in MP treatment of SCI. GSE151371 was utilized as an external dataset to further validate key gene expressions.
7. Preparation of MP-NPs Using Ultrasonic Dispersion
MP-NPs were prepared using ultrasonic cavitation and mechanical effects. MP was encapsulated within poly (lactic-coglycolic acid) (PLGA) nanoparticles through ultrasonic cavitation and mechanical effects, which loosened the PLGA exterior, allowing the drug to be successfully encapsulated within the nanoparticles without forming covalent bonds [46,47]. Briefly, 3 mg of MP (V1703, InvivoChem) was mixed with 15 mg of blank nanoparticle powder (LA=75:25, Mw=20,000, PLGA-COOH, Daigang Biomaterial Co., Ltd.). The mixture was dispersed in 5 mL of ultrapure water and subjected to intermittent ultrasonication at 90 W for 5 minutes in an ice-cold water bath. To remove excess small molecules, the mixture was centrifuged at 6,000 g for 10 minutes using ultrafiltration centrifuge tubes with a molecular weight cutoff of 30 kDa, and the ultrafiltration was repeated 4 times to obtain purified MP-NPs.
8. Dynamic Light Scattering Analysis
The average particle size and zeta potential of MP-loaded PLGA nanoparticles were measured using the Zetasizer Nano ZS instrument (Malvern Instruments). Nanoparticle samples were diluted to an appropriate concentration and measured at 25°C to ensure accuracy, with 3 replicate measurements conducted.
9. Transmission Electron Microscopy Observation
The morphology of the nanoparticles was assessed using transmission electron microscopy (TEM) (JEM-2100, JEOL). Nanoparticle suspension droplets were placed on carbon-coated copper grids, dried at room temperature, and observed using an electron microscope with an acceleration voltage of 200 kV.
10. High-Performance Liquid Chromatography Analysis
High-performance liquid chromatography analysis of the encapsulation efficiency and drug loading content of PLGA and MP-NPs was conducted using a Waters system (Waters Corp.) equipped with a UV detector and Waters Symmetry C18 column (250×4.6 mm, 5 μm). A sample injection volume of 10 μL was used, with the column temperature set at 30°C. The mobile phase comprised methanol and water with 0.5% triethylamine (methanol: water, 60:40, v/v). The flow rate was set at 1.0 mL/min, and detection occurred at 225 nm. Each sample was analyzed in triplicate for accuracy.
11. Construction of Lentivirus
Lentivirus packaging services were provided by Sengong Biotechnology. The pHAGE-puro plasmid series and auxiliary plasmids pSPAX2, pMD2.G; the pSuper-retro-puro plasmid series and auxiliary plasmids gag/pol, VSVG were co-transfected into 293T cells (CRL-3216, ATCC, USA). After 48 hours of cell culture, the supernatant was collected, filtered through a 0.45-μm filter, centrifuged, and the viral supernatant was collected. After 72 hours, the supernatant was collected again and concentrated by centrifugation; the 2 viral batches were mixed, and the titer was determined. The overexpression efficiency was validated in the RAW264.7 cell line (TIB-71, ATCC).
For lentivirus-mediated cell transfection, 5×105 cells were seeded in a 6-well plate. When the confluence of RAW264.7 cells reached 70%–90%, the culture medium containing an appropriate amount of packaged lentivirus (MOI=10, working titer about 5×106 TU/mL) and 5-μg/mL polybrene (TR-1003, Merck) was added for transfection. After 4 hours of transfection, an equal amount of medium was added to dilute polybrene, and after 24 hours of transfection, a fresh medium was replaced. Transfection was observed using a luciferase reporter gene after 48 hours, and 1 μg/mL puromycin (A1113803, Gibco) was used for resistance selection to obtain stable cell lines. Cells were collected when they no longer died in the puromycin-containing medium, and the overexpression efficiency was confirmed by real-time quantitative polymerase chain reaction (RT-qPCR).
12. Cell Culture and Grouping
The Raw264.7 cell line was cultured in modified Dulbecco’s Eagle medium (Sigma) supplemented with 10% fetal bovine serum (Gibco), 100-U/mL penicillin, and 100-μg/mL streptomycin. The cells were maintained in a humidified incubator at 37°C with 5% CO2. The Raw264.7 cells were categorized as follows: (1) Control group; (2) LPS group: treatment with 200 ng/mL (LPS, SMB00704, Sigma-Aldrich) for 24 hours; (3) LPS+MPNPs group: after 24 hours of 200 ng/mL LPS treatment, intervention with 50-μg/mL MP-NPs for 24 hours; (4) LPS+MP-NPs+ overexpression negative control group: transfection with the overexpression control lentiviral vector for 48 hours, cells were treated with 200-ng/mL LPS for 24 hours and then with 50-μg/mL MP-NPs for an additional 24 hours; (5) LPS+MP-NPs+oe-SLC16A3 group: transfection with lentivirus overexpressing SLC16A3 for 48 hours, followed by 200-ng/mL LPS treatment for 24 hours, and then 50-μg/mL MP-NPs intervention for 24 hours.
Specifically, the LPS concentration of 200 ng/mL was chosen based on previous studies showing its established effect in inducing a proinflammatory response in RAW264.7 cells [48]. The MP-NPs intervention at 50 μg/mL followed established procedures [30].
NSCs were extracted from the embryonic cortex of C57/BL6 female mice under aseptic conditions on day 14 of pregnancy. The embryonic cortex was dissected and cut into small pieces, digested with DNase I (11284932001, Sigma) and papain (1010 8014001, Sigma) for 10 minutes to obtain a single-cell suspension, which was then cultured at 37°C with 5% CO2.
Following the above grouping, Raw264.7 and NSCs were cocultured at 1:1 to ensure cell interaction. The total cell count of Raw264.7 and NSCs in each well was maintained at 2×105 [49,50].
13. Apoptosis Analysis by Flow Cytometry
Cell apoptosis was analyzed using the Annexin V-FITC/PI apoptosis detection kit (CA1020, Solarbio) following the manufacturer’s instructions. Posttreatment, cells were collected and resuspended in a binding buffer, then incubated with Annexin V-FITC and PI dyes for 15 minutes in the dark at room temperature. Flow cytometry was utilized for analysis using a BD Biosciences flow cytometer, and the percentage of apoptotic cells was calculated using analytical software.
14. Cell Counting Kit-8
Cells were co-incubated in Nunc 96-well flat-bottom culture plates (Thermo Fisher Scientific, Cat. No.: 167008) for 0, 12, 24, 36, 48, 60, and 72 hours, with a cell density of 4×103 cells per well. Before measurements, cells in each group were washed with phosphate-buffered saline and then incubated with 100 μL of cell counting kit-8 (CCK-8) solution at 37°C for 1 hour. Absorbance was measured at 450 nm using a microplate reader (Thermo Fisher Scientific, Inc.). Each independent experiment was performed 3 times. Data are presented as mean±standard deviation.
15. Immunofluorescence Staining
Cells were plated on coverslips in a 12-well cell culture plate. After cell attachment, the culture medium was removed, and the coverslips were rinsed 3 times with PBS for 5 minutes each. Cells were fixed with 4% paraformaldehyde (PFA) (30525-89-4, Qian Derivative Technology Co., Ltd.) and blocked with 0.1% Triton X-100 and 10% donkey serum. Primary antibodies - inducible nitric oxide synthase (iNOS) (ab178945, Abcam), Arg-1 (ab313496, Abcam), or Nestin (ab313787, Abcam), microtubule-associated protein 2 (MAP2) (ab183830, Abcam), Tuj1 (TUBB3, ab18207, Abcam), and glial fibrillary acidic protein (GFAP) (ab279290, Abcam)—were added, and cells were incubated overnight at 4°C. After rinsing with PBS, the coverslips were incubated with goat anti-rabbit IgG H&L (ab150080, Abcam, 1:1,000, USA) or goat anti-mouse IgG H&L (ab150113, Abcam, 1:1,000, USA) for 1 hour at room temperature. After washing with PBS, the cells were stained with 4´-6-diamidino-2-phenylindole (DAPI) (C1002, Beyotime) for 5 minutes to stain nuclei. The coverslips were rinsed 3 times in PBS for 5 minutes each to remove excess DAPI. The coverslips were then carefully removed from the culture plate and mounted on glass slides with an antifade mounting medium. Observations and imaging were performed using a fluorescence microscope (FV-1000/ES, Olympus). Quantification was done by counting the ratio of positive cells to total cells in fixed fields, with 6 fields averaged per group.
The spinal cord tissue of rats was quickly immersed in 4% PFA (30525-89-4, Hubei Xian Chemical Technology Co., Ltd.) after removal and fixed for 24 hours. Subsequently, the tissue was dehydrated progressively in 15% and 30% sucrose solutions until it settled. The tissue was then embedded in an OCT compound, rapidly frozen, and stored at -80°C. The tissue was sectioned into 20-μm slices using a cryostat and then mounted on positively charged glass slides. Following the preparation of the sections, they were rinsed 3 times with PBS for 5 minutes each time. Subsequently, the sections were treated with 0.3% Triton X-100 for 20 minutes to enhance the permeability of cell membranes. Next, a 10% goat serum was applied for 1 hour to block nonspecific binding. Primary antibodies, including iNOS, Arg-1, and CD68 (ab955, Abcam), were then added. The next day, the sections were washed thrice with PBS for 5 minutes each to remove unbound primary antibodies. Subsequently, secondary antibodies were applied, and the sections were incubated in the dark at room temperature for 1 hour. After incubation, the sections were washed thrice with PBS for 5 minutes each. Finally, the sections were counterstained with DAPI for 5 minutes, washed 3 times with PBS for 5 minutes each, and mounted with antifade mounting medium under a cover glass. Observations and image capture were conducted using a confocal microscope to document the fluorescent signals. Quantitative analysis was performed by calculating the ratio of positive cells to total cells in 6 randomly selected fields per group, with the mean value determined for each group.
16. SCI Model Establishment
Forty female Sprague Dawley rats (180–200 g) (Liaoning Changsheng Biotechnology Co., Ltd.; License No. SCXK (Liao) 2020-0001) were randomly divided into 6 groups: sham group, model group (SCI only, no treatment), model+MP group (50 μg/mL MP), model+MP-NPs group, model+MP-NPs+oe-NC group, and model+MP-NPs+oe-SLC16A3 group [30]. The SCI model was created using the aneurysm clip compression method. The specific procedure was as follows: rats were anesthetized with Zoletil 50 (30 mg/kg; Virbac, Nice) at the posterior end of the T6–7 spine, and the muscles and fascia were vertically incised to expose the intervertebral disc space. The T6–7 spine and posterior lamina were exposed and partially removed to expose the spinal cord segment for laminectomy. The SCI model was established by compressing the spinal cord with an aneurysm clip. In the sham group, only the spinal cord was exposed without compression. After surgery, the rats were transferred to preprepared cages and observed daily. Successful modeling was confirmed when rats exhibited dragging hind limbs while walking.
All animal experiments in this study strictly adhered to international ethical standards for animal research and were approved by the relevant ethics committee of Tianjin hospital Tianjin University. Specifically, the welfare and comfort of the experimental animals were fully considered during the study, with all procedures aimed at minimizing animal pain and discomfort.
MP-NP treatment was administered via intrathecal injection by inserting a needle into the gap between the laminae, accessing the subarachnoid space, with a daily injection dose of 100 μL (50 μg/mL) [30] for 7 consecutive days [51,52]. Additionally, all groups of animals were administered cefazolin (100 mg/kg, PHR1291, Sigma-Aldrich) via intramuscular injection once daily for 7 days to prevent infection.
All lentiviruses were administered by intraperitoneal injection at the lower right quadrant, with an injection titer of 1×10⁷ TU. Following lentivirus administration, a 7-day recovery period was required before subsequent procedures [53].
Behavioral tests were conducted on the day of model creation, the following day, day 3, and day 7. Tissue sampling was performed the day after completing the behavioral tests and sacrificing the animals [49,50].
17. Western Blot
Cell or tissue extracts were obtained by lysing with RIPA (radio immunoprecipitation assay) buffer (P0013B, Beyotime) containing 1% phenylmethanesulfonyl fluoride. The extraction was performed according to the manufacturer’s instructions. The supernatant was collected and the total protein concentration of each sample was determined using a BCA protein assay kit (P0011, Beyotime). Protein concentrations were adjusted to 1 μg/μL, and 100 μL of each sample was boiled at 100°C for 10 minutes to denature the proteins, then stored at -80°C. An 8%–12% sodium dodecyl sulfate polyacrylamide gel electrophoresis gel was prepared based on the size of the target protein bands. Fifty micrograms of protein samples were loaded into each lane using a microloader, and electrophoresis was conducted at a constant voltage of 80 V to 120 V for 2 hours. Protein transfer from the gel to a PVDF membrane (1620177, Bio-Rad) was achieved by wet transfer at a constant current of 250 mA for 90 minutes.
The membrane was blocked at room temperature with 1× TBST (tris buffered saline with tween-20) containing 5% nonfat milk for 1 hour, followed by washing with 1×TBST for 10 minutes. Primary antibodies (details in Supplementary Table 2) were then incubated overnight at 4°C, followed by 3 washes with 1× TBST for 10 minutes each at room temperature and an additional 3 washes for 5 minutes each. The membrane was then incubated with an horseradish peroxidase (HRP)-conjugated secondary antibody, either goat anti-rabbit IgG (ab6721, Abcam, Cambridge, UK, dilution 1:5,000) or goat anti-mouse IgG (ab205719, Abcam; dilution 1:5,000), at room temperature for 1 hour. Subsequently, the membrane was washed thrice for 5 minutes each with 1×TBST at room temperature. The membrane was then immersed in ECL reagent (1705062, Bio-Rad) and incubated at room temperature for 1 minute. After draining the solution, the membrane was covered with plastic wrap and exposed to an Image Quant LAS 4000C gel imaging system (GE Healthcare) for band visualization. The protein expression levels were evaluated by comparing the density ratios of the target bands to the β-actin reference bands for each lane. Each experiment was replicated 3 times to ensure accuracy.
18. Real-Time Quantitative Polymerase Chain Reaction
Total RNA from cells was extracted using the Trizol reagent kit. Subsequently, cDNA was synthesized using the reverse transcription kit (RR047A, Takara). The reaction system was prepared using the SYBR Premix Ex TaqTM II kit (DRR081, Takara) for RT-qPCR in an ABI7500 real-time PCR instrument (Thermo Fisher). The PCR program was set as follows: initial denaturation at 95°C for 30 seconds, then entering the cycling stage with denaturation at 95°C for 5 seconds, annealing at 60°C for 30 seconds for 40 cycles, followed by extension at 95°C for 15 seconds, extension at 60°C for 60 seconds, and a final extension at 90°C for 15 seconds to generate amplification curves. GAPDH was used as an internal control, with triplicate reactions for each RT-qPCR setting and 3 experimental replicates. The experimental groups’ gene expression fold change relative to the control group was calculated using the 2-ΔΔCt method, where ΔΔCt=ΔCt (experimental group)–ΔCt (control group), and ΔCt=Ct (target gene)–Ct (reference gene). Ct represents the cycle threshold when the real-time fluorescence intensity reaches a set threshold, indicating exponential amplification. Primer sequences are detailed in Supplementary Table 3.
19. Behavioral Assessment
The blood-brain barrier (BBB) locomotor rating scale was employed to assess SCI. A double-blind approach was implemented in the experiment to minimize result inaccuracies, where 2 individuals independently observed and recorded the outcomes and then averaged the results.
20. H&E Staining
Rats were anesthetized via intraperitoneal injection of Zoletil 50 (30 mg/kg) and euthanized using cervical dislocation. The spinal cord at the injury site was exposed and isolated surgically. The spinal cord was fixed in 4% paraformaldehyde for one day before undergoing H&E staining. Tissue sections were first stained in a solution containing hematoxylin (H3136, Sigma- Aldrich) for 5 minutes to stain the cell nuclei. Subsequently, the sections were rapidly differentiated in 1% acid alcohol and counterstained in eosin solution (230251, Sigma-Aldrich) for 3 minutes to stain the cytoplasm and intercellular matrix. Following staining, the sections were dehydrated twice in 95% alcohol, cleared, and mounted with neutral resin. Morphological images were observed and captured using an optical microscope (Leica Microsystems). Image analysis for nuclear and cytoplasmic quantification and morphological features was performed using ImageJ software (ver. 1.52a; National Institutes of Health). All procedures were conducted at room temperature, thoroughly rinsing the sections with distilled water after each step to remove excess staining agents. At least 3 sections were prepared under each experimental condition and repeated 3 times to ensure result reproducibility. In the safety evaluation experiment of MPNPs, rats were euthanized after anesthesia via intraperitoneal injection, and organs including the heart, liver, lungs, and kidneys were collected. The tissues were embedded, fixed, sectioned, and stained.
21. Enzyme-Linked Immunosorbent Assay
Rat serum samples were analyzed for IL-1β, IL-6, and TNF levels using enzyme-linked immunosorbent assay (ELISA) kits. Initially, blood samples were collected from rats into blood collection tubes containing anticoagulants and spun down (3,000 rpm, 10 minutes) to separate the serum. A commercial ELISA kit (IL-1β: RLB00-1, IL-6: R6000B, TNF: RTA00-1, R&D Systems) was used following the manufacturer’s instructions. The capture antibody was coated on a 96-well plate using 200 μL of coating buffer and left incubating at 4°C overnight. The next day, the coating buffer was discarded, and the plate was washed 3 times with 300 μL of wash buffer per well for 5 minutes each wash. Subsequently, 100 μL of blocking buffer was added to each well and left to incubate at room temperature for 2 hours. After removing the blocking buffer, 100 μL of diluted serum samples (1:2 dilution) and standards were added to each well and incubated for 2 hours. Following 4 washes, 100 μL of diluted biotinylated detection antibody was added to each well and incubated for 1 hour. After another 4 washes, 100 μL of HRP-conjugated streptavidin was added to each well, and incubation at room temperature continued for 20 minutes. Four final washes were performed before adding 100 μL of substrate solution to each well for incubation in the dark for 20 minutes until the color reaction developed. Stop solution was added (50 μL per well), and the absorbance was read at 450 nm wavelength using a microplate reader (SpectraMax i3x, Molecular Devices) with background correction at 540 nm. Finally, the samples’ concentrations of IL-1β, IL-6, and TNF were calculated based on standard curves. Each sample was tested in triplicate, and the data were presented as mean±standard deviation (SD). Statistical analysis was conducted using GraphPad Prism 9 (GraphPad Software, Inc.). In the safety evaluation experiment of MP-NPs, blood was collected from the rats via the retro-orbital sinus, and serum was obtained by centrifugation. Relevant biochemical indicators were measured using ELISA kits (alanine aminotransferase: ab234579, aspartate aminotransferase: ab263883, α-fetoprotein: ELK5657, creatinine: ab204537, blood urea nitrogen: EIABUN, uric acid: ab65344) [30].
22. Statistical Analysis
Data were derived from at least 3 independent experiments, presented as mean±SD. For most experiments, including the evaluation of cytokines related to macrophage polarization induced by nanoparticles, assessment of apoptosis and protein levels in NSC differentiation, and therapeutic efficacy in the rat SCI model, a t-test was used. Comparisons between the 2 groups were performed using a 2-sample independent t-test, with significance levels set at p<0.05 and p<0.01. For data that were not normally distributed or had unequal variances (such as immune cell content and expression differences of 4 key genes), the Mann-Whitney U-test or the Kruskal-Wallis H-test was used.
In the CCK-8 experiment and behavioral BBB scoring, a 2-way analysis of variance (ANOVA) was used to compare 3 or more groups at different time points. If a significant difference was detected, Tukey honestly significant difference post hoc test was applied for pairwise group comparisons. For multi-group comparisons in experiments evaluating cytokines related to macrophage polarization induced by nanoparticles, assessment of apoptosis and protein levels in NSC differentiation, and therapeutic efficacy in the SCI model, 1-way ANOVA was used. All statistical analyses were performed using GraphPad Prism 9 (GraphPad Software, Inc.) and R software. A significance level of 0.05 was set for all tests, and a 2-sided p-value less than 0.05 was considered statistically significant.
RESULTS
1. Integration Transcriptome Analysis of Reduced M2 Macrophage Infiltration and Associated Gene Modules in SCI
To investigate the molecular mechanisms in SCI, we retrieved 4 transcriptome datasets related to SCI from the GEO database: GSE45006, GSE15878, GSE185600, and GSE229618. After merging the data and removing batch effects using the R package “sva,” we obtained a merged expression matrix comprising 29 control and 45 SCI samples (Fig. 1A and B). Differential analysis revealed 612 genes with significant differential expression between control and SCI samples, including 562 upregulated genes and 50 downregulated genes (Fig. 1C and D). Further, GO and KEGG functional enrichment analyses indicated that these DEGs were mainly involved in regulating inflammatory responses, leukocyte activation, immune responses, and immune response modulation signaling pathways, among other crucial biological processes and pathways (Fig. 1E and F). These results provide initial insights into the close relationship between DEGs and immune responses.
Differentially expressed genes (DEGs) in spinal cord samples of spinal cord injury (SCI) rats were analyzed through the Gene Expression Omnibus database. (A) Principal component analysis (PCA) plot of data distribution before batch effect removal. (B) PCA plot of data distribution after batch effect removal. (C) Volcano plot of DEGs between control and SCI samples. (D) Heatmap of the top 50 upregulated and downregulated DEGs between control and SCI samples. (E) Gene ontology functional enrichment analysis of DEGs. (F) Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of DEGs. Control: n=29, SCI: n=45. NOD, nucleotide-binding and oligomerization domain; NF-κB, nuclear factor-κB; TNF, tumor necrosis factor; ECM, extracellular matrix.
To assess the immune infiltration status in control and SCI samples, we used the CIBERSORT algorithm to evaluate the distribution of 25 immune cell types (Fig. 2A). The results demonstrated significant differences in macrophage populations in SCI samples, particularly a notable decrease in M2 macrophage infiltration (Fig. 2B). This observation suggests a key role for M2 macrophages in the post-SCI inflammatory microenvironment.
Immune infiltration landscape in spinal cord tissues of control and spinal cord injury (SCI) rats. (A) Composition of 25 immune cell subtypes in spinal cord samples of control and SCI rats. (B) Violin plot showing differences in immune cell content between control and SCI spinal cord samples. Control: n=29, SCI: n=45. Nonnormally distributed data were analyzed using the Mann-Whitney U-test or the Kruskal-Wallis H-test. A significance level of p<0.05 was considered statistically significant. NK, natural killer; DC, dendritic cell.
Utilizing WGCNA, we identified gene modules significantly correlated with M2 macrophage infiltration. A soft-threshold power of β=12 (R2=0.9) was determined to construct a scale-free network (Fig. 3A). Hierarchical clustering was employed to merge feature genes highly associated with each module, identifying 7 modules (Fig. 3B). Subsequent analysis focused on exploring the correlation of these modules with immune cells. Among these 7 modules, the black module exhibited the highest correlation with M2 macrophages (r=-0.37, p=0.01) (Fig. 3C), suggesting that genes within the black module regulate macrophage infiltration in SCI.
Construction of a weighted co-expression network for M2 macrophage-related modules. (A) Selection of the optimal soft-threshold power β, with β=12 chosen to achieve both a scale-free topology fit index (R2>0.9) and optimal mean connectivity. (B) Cluster dendrogram used to identify co-expression modules, where each branch represents a gene and different colors below represent different co-expression modules. (C) Module-trait relationships between co-expression modules and immune cells. NK, natural killer; DC, dendritic cell.
Integrative analysis of transcriptome data from SCI samples revealed a notable reduction in M2 macrophages and identified gene modules closely related to them through WGCNA.
2. Molecular Mechanism Analysis of MP Influencing Macrophage Polarization to Promote SCI Repair via SLC16A3 Gene Regulation
Differential analysis was conducted on SCI rats treated with MP and untreated SCI rats using the GSE15878 dataset to identify potential target genes of MP. The results revealed 143 DEGs, with 109 genes upregulated, and 34 genes downregulated following MP treatment (Fig. 4A and B).
Analysis of key regulatory factors of methylprednisolone (MP) in spinal cord injury (SCI) repair. (A) Volcano plot of differentially expressed genes (DEGs) between MP-treated SCI rats and untreated SCI rats. (B) Heatmap of the top 50 upregulated and downregulated DEGs between MP-treated SCI rats and untreated SCI rats. (C) Intersection analysis of MP targets with SCIrelated genes and M2-related genes. (D) Volcano plot of DEGs between healthy controls and SCI patients. (E) Violin plot of the expression of 4 key genes in spinal cord samples of control and SCI rats. (F) Violin plot of the expression of 4 key genes in spinal cord samples of MP-treated and untreated SCI rats. For nonnormally distributed data, analysis was conducted using the Mann- Whitney U-test or Kruskal-Wallis H-test. *p<0.05 compared with the SCI_EtOH group. **p<0.01 compared with the SCI_ EtOH group. ***p<0.001 compared with the control group. EtOH, ethanol. Control: n=29, SCI: n=45, SCI_EtOH: n=16, SCI_ MP: n=14.
Further intersecting the target genes of MP with SCI-related genes and M2-related genes enabled us to successfully identify 4 key regulatory factors (Fig. 4C). Using the GSE151371 dataset as an external validation set for key gene expression, it was found that only MGST2 and SLC16A3 were DEGs in SCI patients, exhibiting higher expression levels in SCI patients (Fig. 4D). Particularly noteworthy is the upregulation of the SLC16A3 gene in SCI, which is downregulated upon MP treatment (Fig. 4E and F). Previous studies have shown that the inhibition of SLC16A3 reduces the levels of proinflammatory molecules in LPSstimulated macrophages of the M1 phenotype, including IL-1β, IL-6, TNFα, and iNOS, thereby alleviating inflammation [54].
In light of the results above, we propose that MP may affect macrophage polarization by modulating SLC16A3, mediating SCI repair.
3. Synthesis, Characteristics, and In Vitro Release Behavior of MP-Loaded PLGA Nanoparticles
We successfully synthesized PLGA nanoparticles using a selfassembly method, and MP was successfully loaded by loosening the PLGA exterior through the cavitation and mechanical effects of ultrasound. As shown in Supplementary Table 4, the higher the molecular weight, the greater the drug loading content and particle size. To achieve a higher drug loading content and smaller particle size, PLGA (50:50) with a molecular weight between 30,000 and 60,000 was selected for further study, resulting in an encapsulation efficiency of 63.8%±1.7% and a drug loading content of 5.8%±0.3%. Further mixing formed the polymer (MP-NPs), with results showing an encapsulation efficiency of 62.9%±1.9% and a drug loading content of 5.6%±0.4% (Supplementary Table 5). The particle size was sufficiently small (≤200 nm) to avoid detection and destruction by the reticuloendothelial system, allowing for extended circulation time and passive targeting of cancer through the enhanced permeability and retention effect [55]. TEM imaging of MP-NPs revealed spherical nanoparticles with a smooth surface and an approximate particle size of 100 nm (Fig. 5A). The average particle size of MP-NPs was 156.4±1.4 nm, with an unimodal size distribution and a low polydispersity index. The zeta potential was -23.6±1.3 mV. Detailed assessments of particle size, morphology, and distribution characteristics were conducted using dynamic light scattering (DLS) and TEM techniques (Fig. 5B and C).
Characterization and drug release behavior of multifunctional methylprednisolone-loaded nanoparticles (MP-NPs). (A) Transmission electron microscopy images of MP-NPs. (B, C) Dynamic light scattering analysis showing the size distribution and zeta potential of MP-NPs. (D) Differential scanning calorimetry curves of the physical mixture, MP, poly(lactic-co-glycolic acid (PLGA), and MP-PLGA nanoparticles. (E) In vitro cumulative release percentage of MP-loaded PLGA nanoparticles and MP physical mixture in phosphate-buffered saline at 37°C.
The DSC curves of PLGA, MP, the physical mixture (MP and PLGA at a ratio of 1:10), and MP-NPs are shown in Fig. 5D. By comparing these DSC curves, it can be inferred that new interactions occurred between MP and PLGA, altering their thermal properties. The sharp endothermic peak of MP at 230°C is absent in MP-NPs, and a new endothermic peak appears at 160°C, which is attributed to the encapsulation process. This shift indicates changes in the crystalline structure of MP due to interactions with PLGA during nanoparticle preparation. However, MP-NPs still exhibit sharp endothermic peaks, consistent with the crystalline properties of the encapsulated drug.
Subsequently, the in vitro release behavior of the MP physical mixture and MP-NPs over 180 hours was studied (Fig. 5E). The results demonstrate that the physical mixture and MP-NPs exhibit a biphasic burst release pattern followed by sustained release. Due to burst release effects, the drug in the physical mixture is rapidly released within 20 hours. The cumulative release rate of MP-NPs reveals an initial burst release phase, likely due to MP attached to the surface of nanoparticles detaching from PLGA and entering the dissolution medium. MP-NPs achieved 70% sustained release over 180 hours. Consequently, PLGA polymer prevents burst release of MP and controls its release rate. Moreover, the in vitro release profiles indicate that MP-NPs exhibit significant prolongation of MP release and excellent long-term physical stability. This release pattern suggests nanoparticles can serve as effective sustained-release carriers for MP.
4. MP-NPs Promote M2 Macrophage Polarization by Regulating the Expression of SLC16A3
Based on the results of bioinformatics analysis, we consider SLC16A3 to be a likely key target for the action of MP in SCI. First, we evaluated the in vitro safety of MP-NPs. Through the CCK8 assay, we found no significant difference in cell viability between the control group and the MP and MP-NPs groups, suggesting that MP-NPs have a certain level of biocompatibility (Fig. 6A) [30]. To further verify this, we first examined the effects of MP-NPs and the SLC16A3 gene in the RAW264.7 cell line. To induce proinflammatory cytokine release and M1 polarization in macrophages, we stimulated the cells with 20-μM LPS, followed by MP-NP treatment and SLC16A3 overexpression intervention. CCK8 assay results showed that LPS stimulation significantly reduced the viability of RAW264.7 cells, which was restored under MP and MP-NP treatment, whereas oe-SLC16A3 inhibited the therapeutic effects of MP-NPs (Fig. 6C and D).
Study on the promotion of macrophage polarization by methylprednisolone-loaded nanoparticles (MP-NPs). (A) CCK8 assay measuring viability of RAW264.7 cells after different treatments. (B) CCK8 assay measuring viability of RAW264.7 cells after various interventions, with group and time differences analyzed by 2-way analysis of variance (ANOVA). (C) Western blot analysis of proinflammatory cytokines and solute carrier family 16 member 3 (SLC16A3) expression levels in each group, with statistical analysis of grayscale values. (D) Real-time quantitative polymerase chain reaction analysis of proinflammatory cytokine and SLC16A3 expression levels. (E, F) Immunofluorescence detection of M1 and M2 macrophage markers, inducible nitric oxide synthase and Arg-1, in each group, with bar graphs showing the positive rate. Bar=25 μm. Here, group and time differences following a normal distribution were analyzed using ANOVA. Compared with the control group, *p<0.05, **p<0.01; compared with the lipopolysaccharide (LPS) group, #p<0.05, ##p<0.01; compared with the LPS+MP-NPs+overexpression negative control group, ^p<0.05, ^^p<0.01. All cell experiments were repeated 3 times.
To observe macrophage polarization in different groups, we conducted immunofluorescence staining to detect the expression of macrophage polarization markers iNOS and Arg-1. The results demonstrated that LPS-induced M1 macrophage polarization, which was inhibited by MP-NPs. Under the influence of LPS, the quantity of M2 macrophages showed no significant difference compared to the control group. MP-NPs induced M2 macrophage polarization, as indicated by elevated M2 macrophage marker Arg-1 levels. Moreover, overexpression of SLC16A3 reversed the inhibitory effect of MP-NPs on M1 polarization and the promoting effect on M2 polarization (Fig. 6E and F).
These findings suggest that MP-NPs can promote M2 macrophage polarization and suppress the release of inflammatory cytokines by modulating the expression of SLC16A3.
5. MP-NPs Induce NSCs Differentiation by Regulating SLC16A3 and Macrophage Polarization
To further validate the effect of MP-NPs on NSCs differentiation, and the roles of SLC16A3 expression and macrophage polarization in this process, NSCs were extracted from C57BL/6 mice and cocultured with RAW264.7 cells subjected to various interventions. The isolated cells were identified through immunofluorescence staining, revealing that Nestin-positive cells accounted for 99%, while markers for astrocytes (GFAP) and neurons (MAP2) were negative, indicating the cells were NSCs (Supplementary Fig. 1).
Subsequently, we evaluated the level of cell apoptosis through flow cytometry. Results showed that in the coculture group of macrophages induced by LPS compared to the control group, the apoptosis level of NSCs significantly increased. Treatment with MP-NPs reduced the level of apoptosis, while overexpression of SLC16A3 reversed the therapeutic effects of MP-NPs (Fig. 7A).
Methylprednisolone-loaded nanoparticles (MP-NPs) induce neural stem cells differentiation. (A) Apoptosis levels of cells in each group detected by flow cytometry. (B) Western Blot analysis of protein levels of Nestin, Tuj1, MAP2, and GFAP in each group, with bar graphs showing grayscale value statistics. (C) Real-time quantitative polymerase chain reaction analysis of mRNA levels of Nestin, Tuj1, MAP2, and GFAP in each group, with bar graphs showing statistical results. (D) Immunofluorescence detection of Tuj1 and GFAP expression in each group, with bar graphs showing the percentage of positive cells. Bar=25 μm. Multiple group comparative data analysis was conducted using a 1-way analysis of variance test. Compared with the control group, *p<0.05, **p<0.01; compared with the lipopolysaccharide (LPS) group, #p<0.05, ##p<0.01; compared with the LPS+MP-NPs+ overexpression negative control (oe-NC) group, ^p<0.05, ^^p<0.01. All cell experiments were repeated 3 times. FITC, fluorescein isothiocyanate; SLC16A3, solute carrier family 16 member 3.
To observe the impact of MP-NPs on the differentiation of NSCs, we also examined the differentiation status of NSCs cells in each group. Using Western blot and RT-PCR, we assessed Nestin, GFAP, Tuj1, and MAP2 expression levels. The results showed a significant decrease in Nestin expression levels in the other 4 groups of cells compared to the control group, indicating a reduction in undifferentiated NSCs, suggesting cellular differentiation. Specifically, the expression level of the astrocyte marker GFAP was significantly increased in the LPS group, which was inhibited by MP-NP treatment, and the intervention of oe-SLC16A3 reversed this inhibitory effect, whereas the expression levels of the immature neuron marker Tuj1 and mature neuron marker MAP2 showed an opposite trend: in the LPS group, the expression of Tuj1 and MAP2 decreased, while in the LPS+MP-NPs group, the expression increased, and under the influence of oe-SLC16A3, the expression was once again inhibited (Fig. 7B and C).
In our immunofluorescence staining validation, the results showed that in the LPS group, the Tuj1 fluorescence positivity was only 5.2%, but with MP-NP treatment, the proportion of Tuj1 positivity reached 35.9%, and oe-SLC16A3 reduced the Tuj1 positivity back to 9.2%; whereas for GFAP, the LPS group exhibited significantly strong positive expression, with a positivity rate of 42.3%, the treatment with MP-NPs significantly inhibited GFAP expression, reducing it to approximately 15.6%, under the intervention of oe-SLC16A3, GFAP positivity rate increased again to 39.9% (Fig. 7D). This indicates that LPS-induced macrophages drive NSCs towards excessive differentiation into astrocytes, impacting the normal function of the nervous system, whereas MP-NPs can inhibit NSCs differentiation into astrocytes, promoting differentiation into neurons, suggesting the promoting effect of MP-NPs on neural system regeneration function, and the inhibitory effect on glial scar formation.
In conclusion, our in vitro experiments demonstrated that MP-NPs promote M2 macrophage polarization through regulating SLC16A3 expression, thus facilitating NSCs differentiation into neurons, enhancing their regenerative and reparative abilities.
6. MP-NPs Promote Rat SCI Repair via Regulating SLC16A3 Expression
By constructing a rat SCI model, we further observed the effect of MP-NPs in promoting injury repair. First, we assessed the safety of MP and MP-NPs. Compared to the control group, administration of MP or MP-NPs did not lead to significant pathological changes in the organ tissues of the animal model, and there were no noticeable differences in key blood biochemical parameters, suggesting that MP and MP-NPs have a certain level of safety (Fig. 8A). Motor function recovery in rats was evaluated using the BBB scoring system, where the MP-NP treatment group showed significant improvement in motor function. Specifically, after 7 days of treatment, the BBB score in this group increased from an initial average of 2 to 8, while the score decreased again in the SLC16A3 overexpression group (Fig. 8B). Statistical analysis showed that both the MP and MP-NP treatment groups had higher BBB scores compared to the control group (model group), with the MP-NPs group showing better therapeutic efficacy than the MP group. The footprint tracking images (Fig. 8C) indicated that rats in the model group dragged their hind legs, and the MP group showed a slight improvement in gait. Compared to the MP group, MP-NP treatment resulted in significant improvement in walking, although this improvement was reversed under oe-SLC16A3 intervention. These results suggest that MP-NPs can significantly promote functional recovery after SCI in rats, possibly through SLC16A3 regulation.
Therapeutic effects of methylprednisolone-loaded nanoparticles (MP-NPs) in a rat spinal cord injury (SCI) model. (A) Hematoxyling and eosin (H&E) staining of multiple organs and blood biochemical indicator assessment in rats after different treatments. (B) Statistical graph of behavioral score (blood-brain barrier [BBB] score), with significance analyzed using 2-way analysis of variance (ANOVA). (C) Motor footprint images of rats in each group. (D) H&E staining images with inflammatory cells marked in blue and hemorrhage points in red, Bar=50 & 10 μm. (E) Enzyme-linked immunosorbent assay results showing inflammatory cytokine levels in the serum of each group. (F) Real-time quantitative polymerase chain reaction analysis of SLC16A3 mRNA expression levels in each group. (G) Immunofluorescence staining showing co-expression of CD68 with either inducible nitric oxide synthase or Arg-1 in tissue sections and positive rate bar graph, Bar=25 μm. All statistical analyses in panels A, D, E, and F were conducted using ANOVA. Compared with the Sham group, *p<0.05, **p<0.01; compared with the model+ MP group, Δp<0.05, ΔΔp<0.01; compared with the model group, #p<0.05, ##p<0.01; compared with the Model+MP-NPs+oe-NC group, ^p<0.05, ^^p<0.01. Six rats per group. ALT, alanine aminotransferase; AST, aspartate aminotransferase; ALP, α-fetoprotein; BUN, blood urea nitrogen; UA, uric acid; SLC16A3, solute carrier family 16 member 3.
H&E staining in the images shows severe inflammatory cell infiltration and hemorrhage in the model group, while the MP group displayed a slight reduction in hemorrhage. Compared to the MP group, MP-NP treatment produced marked improvement, although pathological features reappeared under oe-SLC16A3 intervention (Fig. 8D).
To verify the findings from in vitro experiments, we measured the levels of proinflammatory cytokines in the serum of rats from each group. ELISA results showed that compared to the sham group, proinflammatory cytokine release increased in the model group, while the MP group reduced this release. Compared to the MP group, MP-NP treatment further inhibited the release of proinflammatory cytokines, an effect reversed by oe-SLC16A3 (Fig. 8E). Additionally, Western blot results indicated increased expression of the SLC16A3 protein in the tissues of the model group, with reduced expression in the MP group. Compared to the MP group, MP-NP treatment significantly lowered SLC16A3 protein expression, which was again increased under oe-SLC16A3 treatment (Fig. 8F).
Further in vivo validation was performed to investigate the therapeutic mechanism of MP-NPs. Immunofluorescence staining was used to examine CD68, Arg-1, and iNOS double markers in tissue sections to observe M1 and M2 macrophage polarization. Results showed that iNOS-positive expression in the model group was significantly higher than in the sham group, indicating M1 macrophage polarization, while the MP group slightly reduced iNOS expression levels. Compared to the MP group, MP-NP treatment inhibited iNOS expression, an effect that was reversed by oe-SLC16A3 intervention. Compared to the model group, there was a slight increase in the strong fluorescence-positive expression level of Arg-1 in the tissues of the MP group. Compared to the MP group, MP-NPs intervention led to an increase in Arg-1 fluorescence positivity, indicating M2 macrophage polarization, which was inhibited under oe-SLC16A3 intervention, demonstrating the important role of SLC16A3 in MP-NPs-induced macrophage polarization (Fig. 8G).
These findings indicate that MP-NP treatment significantly enhances therapeutic efficacy and demonstrates high specificity compared to MP alone. Overall, the results show that MP-loaded composite nanoparticles effectively remodel the macrophage-inflammatory microenvironment by downregulating the SLC16A3 gene, promoting SCI repair in rats, and providing a potential new strategy for future SCI treatment.
DISCUSSION
Nanoparticles exhibit unique advantages in drug delivery. In previous studies, multifunctional nanoparticles have been widely applied in areas such as cancer and cardiovascular diseases, achieving significant outcomes [56-58]. Research has shown that PLGA is one of the most widely used biodegradable materials due to its excellent biocompatibility, making it suitable for various applications in drug delivery, including the delivery of anticancer drugs, protein or peptide drugs, and bacterial or viral DNA [59]. In this study, nanoparticle technology was innovatively applied to SCI treatment. Using DLS and TEM, we thoroughly evaluated the size, morphology, and distribution characteristics of the nanoparticles, which were found to have a uniform particle size and good dispersibility. Drug loading and release curve experiments further demonstrated that MP could be efficiently loaded into the nanoparticles, allowing MP to diffuse to the surrounding surface in a controlled release manner, thus extending the drug’s effective action time. Additionally, the CCK8 assay results indicated that MP-loaded nanoparticles were nontoxic to cells, confirming the biomimetic properties of blank PLGA.
Existing research has shown that polydopamine nanoparticles (PDA NPs) can effectively scavenge excessive reactive oxygen and nitrogen species ithin neurons, protecting them from oxidative damage. In a rat SCI model, PDA NPs significantly reduced neutrophil infiltration, remodeled the inflammatory and oxidative microenvironment, and promoted neurological recovery in SCI rats [60]. However, this approach primarily targets early-stage inflammation and oxidative stress to facilitate chronic- phase neural recovery. High-dose MP treatment has been recognized for its positive effects on nerve repair in the acute phase of SCI [61-63]. While traditional MP treatment has anti-inflammatory effects, its widespread use is limited due to systemic side effects [43,64,65]. Existing research has not fully leveraged this effective therapeutic drug. In contrast, our study innovatively combines nanoparticle technology with effective therapeutic agents, providing notable advantages. Compared with conventional MP treatment, the novelty of our study lies in enhancing drug delivery efficiency and targeting through nanoparticles. Our study not only improved the accumulation of MP at the injury site but also achieved controlled release, prolonging the drug’s effective action time. This novel drug delivery approach significantly improved motor function recovery and neural tissue repair in the rat SCI model, demonstrating the great potential of nanoparticles in neural repair and offering new directions for the clinical treatment of SCI patients.
Macrophages play a crucial role in the inflammatory response after SCI, and the balance between M1 (proinflammatory) and M2 (anti-inflammatory) phenotypes is essential for neural tissue repair [66-68]. In this study, MP-loaded nanoparticles significantly promoted the shift of macrophages from M1 to M2 phenotype, thereby reducing the proinflammatory response and promoting tissue repair. Through a series of in vitro and in vivo experiments, this study confirmed the beneficial role of M2 macrophages in SCI repair and observed that MP-loaded nanoparticles effectively induced this shift. Compared with previous studies, this research not only emphasizes the importance of M2 macrophages in SCI repair but also reveals the key molecular mechanism of this process, specifically through the regulation of SLC16A3. The study found that SLC16A3 expression was upregulated in SCI, and MP treatment downregulated its expression, thus promoting the transition of M1 macrophages to M2. This finding provides a new perspective on the role of macrophage polarization in SCI repair and offers important theoretical and experimental data for developing future therapeutic strategies.
This study is the first to reveal the critical regulatory role of SLC16A3 in SCI. Previous studies primarily focused on the function of SLC16A3 as a metabolism-related transporter, and its specific role in SCI was unclear [69]. Using transcriptome data and WGCNA analysis, we found that SLC16A3 was significantly upregulated in SCI and that its expression was closely related to macrophage polarization status. MP treatment downregulated SLC16A3 expression and promoted the transition of macrophages from the M1 to the M2 phenotype. This finding provides a new molecular target for regulating the inflammatory response in SCI, expands the research scope of SLC16A3, and enriches its functional mechanism in neuroinflammation.
Despite the significant findings of this study, there are still some limitations. First, the study was conducted mainly on a rat model; future studies should verify its efficacy and safety in higher animal models and clinical trials. Second, while nanoparticle technology shows great potential in drug delivery, its long-term biosafety and potential immune responses need further evaluation. This study utilized a PLGA system for drug loading, and we hope to explore various nanoparticle delivery systems in the future. Furthermore, this study focused only on the role of SLC16A3 in SCI, and future research should investigate other potential regulatory factors and their roles in the inflammatory response. This study did not include a blank PLGA group or an effective treatment group with PDA nanoparticles as a positive control, thus not fully demonstrating its clinical preference. Future exploration in this direction is planned. Additionally, challenges remain in translating these research findings to clinical applications, such as long-term safety and scaling up nanoparticle production.
In conclusion, this study, by using multifunctional nanoparticles loaded with MP, revealed the key role of SLC16A3 downregulation in SCI treatment, remodeling the macrophage-inflammatory microenvironment and promoting neural tissue repair and functional recovery (Fig. 9). Moreover, the identification of SLC16A3 as a decisive regulatory factor and its role in directing macrophage polarization toward neural regeneration represents a novel approach. This finding offers a new strategy for SCI treatment, with significant scientific and clinical implications. By regulating macrophage polarization and the inflammatory microenvironment, this study provides new theoretical support and therapeutic targets for SCI repair, with the potential to improve outcomes for SCI patients. Future work will focus on further optimizing nanoparticle design, enhancing biosafety and clinical translational potential, and addressing the challenges of scaling up nanoparticle production. Additionally, combining other potential molecular targets and exploring multitarget combination therapies may further improve the therapeutic efficacy of SCI, offering greater benefits for patients.
Multifunctional methylprednisolone-loaded nanoparticles (MP-NPs) promote M2 macrophage polarization and spinal cord injury (SCI) repair by downregulating SLC16A3 expression. TNF, tumor necrosis factor; IL, interleukin.
CONCLUSION
This study successfully demonstrated, through a series of precisely designed experiments, that multifunctional MP-NPs can significantly downregulate the expression of the SLC16A3 gene, thereby effectively promoting the polarization shift of macrophages from proinflammatory M1 to anti-inflammatory M2 phenotypes and reshaping the post-SCI inflammatory microenvironment (Fig. 9). This strategy notably enhanced the neural tissue repair capacity and motor function recovery in a rat SCI model, offering a fresh perspective and strategy for SCI treatment. The research uncovered the critical role of the SLC16A3 in SCI repair and provided new experimental evidence for using nanotechnology-mediated drug delivery systems in modulating the immune microenvironment and promoting tissue repair. This paves the way for clinical studies on SCI treatment, particularly regarding the precise regulation of inflammatory responses using nanoparticles as drug delivery platforms. Despite encouraging experimental outcomes, this research still faces certain limitations, including the need for further evaluation of the long-term stability and safety of therapeutic effects. Future studies should focus on the in vivo distribution, metabolism, and excretion of nanoparticles, as well as the treatment efficacy across different types and severities of SCI, to further explore and optimize this treatment strategy toward meeting clinical standards.
Supplementary Materials
Supplementary Tables 1-5 and Supplementary Fig. 1 are available at https://doi.org/10.14245/ns.2448814.407.
The detail information of GEO datasets
Antibody information and dilution factors
RT-qPCR primer sequences
Impact of copolymer composition on nanoparticle properties
Characterization of MP-NPs
Identification results of neural stem cells. Immunofluorescence staining of cells was performed to detect the expression of Nestin, GAFP, and MAP2 in the extracted primary cells (scale bar 25 μm). DAPI, 4´-6-diamidino-2-phenylindole; GFAP, glial fibrillary acidic protein; MAP2, microtubule-associated protein 2.
Notes
Conflict of Interest
The authors have nothing to disclose.
Funding/Support
This study was supported by Tianjin Health Science and Technology Project (TJWJ2022QN056).
Author Contribution
Conceptualization: JL; Data curation: JL, SM; Formal analysis: JL; Funding acquisition: DS; Methodology: JL, S Ma; Project administration: DS; Writing – original draft: SM; Writing – review & editing: DS.