Proteomic profile of Laser-dissected Motoneurons and Ependymal Cell Layer and of Dorsal Root Ganglia after Spinal Cord Injury in Rat

Proteomic profile of Laser-dissected Motoneurons and Ependymal Cell Layer and of Dorsal Root Ganglia after Spinal Cord Injury in Rat | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Data Note Proteomic profile of Laser-dissected Motoneurons and Ependymal Cell Layer and of Dorsal Root Ganglia after Spinal Cord Injury in Rat Olga Gajewska-Woźniak, Agata Pytyś, Tomasz Wójtowicz, Remigiusz Serwa, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8134246/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Spinal cord injury induces profound molecular changes in surrounding tissue. Deciphering these changes with cell type-specific resolution shall facilitate discovery of new molecular targets that promote recovery. Here, we performed a proteomic analysis of laser-dissected motor neurons (MN) and ependymal cells (EC), dorsal root ganglia (DRG) obtained from adult control and spinal rats, 2 or 6 weeks after spinal cord transection at Th9. We traced with fluorescent cholera toxin and microdissected on average 172+/-39 MNs innervating soleus (SOL) muscle and 262+/-74 MNs innervating tibialis anterior (TA) muscle per animal. In parallel, we microdissected the EC layer that surrounds the central canal and the L3-6 spinal cord (the same levels as isolated MNs). We isolated the DRG bilaterally from L3, L4, L5 segments. Mass spectrometry analysis of the samples from 5 animals per group, allowed us to detect 1221 proteins in SOL MNs, 1186 in TA MNs, 1520 in EC layer and 5087, 3740 and 3086 in DRG L3, L4 and L5, respectively. Here we describe how this data was obtained and made available for further use. Our data may help to identify and characterize molecular mechanisms involved in early and late subacute period after spinalization in the rat spinal MNs, DRG and ECs. Design Type(s) parallel group design • injury design • disease process modeling objective Measurement Type protein expression profiling Technology Type laser capture microdissection • mass spectrometry assay • computer analysis with MaxQuant software Factor Type Procedure Sample Characteristic (s) Rattus norvegicus • lumbar motoneurons • DRG • ependymal cells of central canal Cellular & Molecular Neuroscience Spinal cord injury Laser microdissection TMT-based proteomics Motorneurons Dorsal root ganglia Figures Figure 1 Figure 2 Figure 3 Introduction Spinal cord injuries (SCI) remain a critical health and societal challenge worldwide, leading to severe and often irreversible functional impairments. Despite significant advances in therapeutic approaches, including epidural stimulation and treatment with biomaterials with cell-based systems, many obstacles to effective recovery persist. A growing body of evidence highlights that motoneurons (MNs) innervating distinct muscle groups possess unique physiological and molecular characteristics. We recently demonstrated that spinalization in rats alters protein and gene expression of neurotransmitter and neurotrophin receptors in tracer-identified, isolated MNs innervating ankle joint extensor and flexor muscles, both at 2nd and 6th week post-lesion (Chopek et al., 2015 ; Głowacka et al., 2022 ; Ji et al., 2022 ; Skup et al., 2012 ; Wieckowska et al., 2018 ). However, detailed proteomic profiles of these MNs are lacking. Deciphering the proteomic heterogeneity of MNs innervating different muscles, as well as their adaptive responses to injury and stimulation, is crucial for identifying novel therapeutic targets and strategies of precision medicine. However, a significant methodological challenge remains: reliably distinguishing and isolating homogeneous populations of MNs for proteomic analyses. While amyotrophic lateral sclerosis (ALS) studies have used fluorescence-activated cell sorting (FACS) of cultured neurons (Garone et al., 2020 ) or laser microdissection (LMD) (Guise et al., 2024 ; Hale et al., 2024 ) to isolate unidentified MNs from murine and human spinal cords for mass spectrometry analyses, so far no study has examined proteomic profiles of target-defined MNs in healthy and diseased state. To address this gap, the present study utilizes proteomic profiling of retrogradely labeled MNs isolated via laser microdissection (LMD). We focus on antagonistic hindlimb muscle groups in rats - the soleus (SOL) and tibialis anterior (TA) - to characterize respective MN proteomes in no-treated animals and at two post- spinal cord injury time points (2 and 6 weeks). In addition, we performed proteomic analysis of DRG from L3, L4, L5 lumbar segments corresponding to the MN pools under study, which house the cell bodies of sensory neurons that transmit peripheral information to the central nervous system, including monosynaptic inputs to MNs. These structures play a pivotal role in pain perception and other sensory modalities, which are often altered after SCI. We included in the study ependymal cells (EC) lining the spinal cord’s central canal, which contribute to cerebrospinal fluid (CSF) production and distribution. In the light of data showing the stimulatory effect of injury on ECs proliferation, we expected that their proteome undergoes remodeling (Lacroix et al., 2014 ). ECs have been proposed as adult neural stem cells with therapeutic potential for spinal cord repair. Although their regenerative capacity was reported as limited and localized (Ren et al., 2017 ), analyzing proteomic changes can confirm their phenotypic adaptations. Together, this study offers a comprehensive proteomic dataset obtained from target-defined MNs, DRGs and ECs, key cell types involved in motor and sensory function and regeneration after spinal cord injury, paving the way for more targeted and effective therapies. Materials and Methods Animals Experiments were conducted on 19 adult male Wistar rats (body weight: 270–325 g at the start of the study), bred and housed at the Nencki Institute of Experimental Biology PAS in Warsaw, Poland. Animals had free access to standard pellet food and water and were maintained on a 12-hour light/dark cycle, in groups of 4–6. All experimental procedures, including surgeries and postoperative care, were approved by the 1st Local Ethics Committee in Warsaw (decision numbers 1481P1/2023 and 1482P2/2023), in accordance with Directive 2010/63/EU of the European Parliament and Council on the protection of animals used for scientific purposes. The main experiment was carried out on 16 rats. Fluorescent retrograde tracers were injected into hindlimb muscles, the soleus (SOL) and tibialis anterior (TA). In 10 animals, spinal cord transection (SCT) was performed at the Th9 level. Five rats were sacrificed 2 weeks post-SCT (Sp2W group), and five at 6 weeks post-SCT (Sp6W). Retrograde Tracing of Motoneurons As in our previous studies (Grycz et al., 2019 , 2022 ; Skup et al., 2012 ), animals were premedicated with subcutaneous Butomidor (butorphanol, 1.5 mg/300 g body weight; Richter Pharma, Wels, Austria) and anesthetized with isoflurane (1–2.5% in oxygen; Baxter, Lessines, Belgium) delivered via a face mask. The skin over the target muscles—SOL and TA—was shaved and cleaned using 70% ethanol. To retrogradely label motoneurons (MNs) innervating these muscles, cholera toxin subunit B (CTx) conjugated with Alexa Fluor 555 or Alexa Fluor 488 (0.01% in phosphate-buffered saline; Molecular Probes, USA) was bilaterally injected into the SOL and TA muscles, respectively, using a Hamilton microsyringe equipped with a 26- or 22-gauge needle (Fig. 1 ). Injection sites were chosen based on prior motor endplate staining (Mohan et al., 2015b , 2015a ), and each injection lasted approximately 10 minutes. To minimize tracer leakage, the needle was left in place for 3 minutes following injection. Afterward, the site was rinsed with sterile saline and the skin was sutured. Postoperative care included subcutaneous administration of Tolfedine (tolfenamic acid 4%, 4 mg/kg; Vetoquinol, Lure Cedex, France) for analgesia over five days, and Baytril (enrofloxacin, 5 mg/kg; Bayer GmbH, Leverkusen, Germany) once daily for five consecutive days to prevent infection. After recovery from anesthesia, animals were returned to their home cages with ad libitum access to food and water. Spinal Cord Transection Approximately one week after tracer administration, rats from the Sp2W and Sp6W groups underwent complete SCT. Surgical procedures (Fig. 1 ) were performed as previously described (Ziemlinska et al., 2014 ). Briefly, the dorsal skin was shaved and cleaned with 70% ethanol, then incised at the level of the lower thoracic vertebrae. Muscles and ligaments were carefully separated to expose the vertebrae. Following identification of the Th9 and Th10 vertebral levels, a laminectomy was performed. The dura mater was opened, and 2% lidocaine (Lignocainum hydrochloricum; Polfa Warszawa S.A., Poland) was applied topically to the spinal cord before it was completely transected using fine surgical scissors. The lesion gap was then gently enlarged to approximately 0.5 mm by aspiration, and the site was rinsed with a 0.9% NaCl solution. The lesion area was carefully inspected under a surgical microscope (Nikon SMZ 1000) to confirm completeness of transection. Surrounding tissues were repositioned, and the muscle and skin layers were sutured. Following surgery, approximately 5 ml of 0.9% NaCl was administered subcutaneously for rehydration. Postoperative care included subcutaneous administration of the antibiotic Sultridin (30 mg/kg; Norbrook, Ireland) once daily for five consecutive days, and the analgesic Vetaflunix (2.5 mg/kg; VET AGRO, Poland) for three days. Immediately post-surgery, each animal was placed in a clean recovery cage on a heated mat and monitored until fully awake (approximately 1 hour), after which they were returned to their home cages with free access to food and water. Animals were monitored three times daily during the first postoperative week, and twice daily during the second week. Care included general health inspection, cleaning of the perineal area, and manual bladder expression when necessary. Spontaneous micturition typically resumed during the second postoperative week. No major health complications were observed in any animal throughout the duration of the experiment. Tissue Preparation and Laser Microdissection (LMD) Animals were anesthetized with isoflurane and euthanized by a lethal intraperitoneal injection of pentobarbital (120 mg/kg body weight; Morbital, Biowet, Poland). Rats were then transcardially perfused with 250 ml of ice-cold 0.01 M phosphate-buffered saline (PBS: 154 mM NaCl, 1.3 mM Na₂HPO₄, 2.5 mM NaH₂PO₄; pH 7.4). The vertebral column was excised and placed on ice. Lumbar spinal cord segments (L3–L6, Fig. 1 B), approximately 1.2 cm long, were rapidly dissected, snap-frozen in dry ice-cooled tubes, and stored at − 80°C until further processing (within one month). Dorsal root ganglia (DRGs) from segments L3, L4, and L5 were dissected bilaterally as whole structures. The L3 and L4 DRGs are the largest ganglia within the lumbar region and can be easily distinguished based on their size and anatomical location. Left and right ganglia from each lumbar level were pooled and frozen. Frozen L3–L6 spinal cord segments were embedded in Jung tissue-freezing medium (Leica, cat. no. 14020108926) and sectioned longitudinally at 20 µm thickness using a cryostat (Slee MEV, SLEE Medical GmbH) at − 20°C. Sections were mounted onto RNase-free PEN membrane frame slides (Leica No. 11505190 or Applied Biosystems™ LCM0521), with 6–9 sections per slide and approximately 3 slides per animal. Slides were stored on dry ice or at − 80°C for up to one week prior to microdissection. Prior to microdissection, slides were dehydrated through a graded ethanol series (70%, 80%, 90%, and 2 × 100%, each for 30 s), followed by two xylene washes (30 s and 180 s), and air-dried for 3–5 minutes. MNs and EC tissue samples were isolated using the Leica LMD7000 Laser Microdissection System. PEN membrane frame slides were placed in the slide holder, and RNase-free 0.2 ml tube caps were positioned in tube holders for gravity-based sample collection. Labeled MNs (SOL with Alexa Fluor 555, and TA with Alexa 488) were visualized under the microscope using first 10× (NA 0.32) and then 63× (NA 0.7) objectives, and individually dissected using a UV laser. Laser parameters (power, aperture, speed, and pulse frequency) were set automatically for each objective and adjusted to minimize laser power while maintaining efficient tissue cutting. Collected MNs were captured directly into the tube caps by gravity. Following MNcollection from each membrane slide (typically up to 3 hours/slide), tubes were sealed and stored on dry ice or at − 80°C (inverted, cap-down) until the next step. ECs were identified in the same tissue sections, and microdissected. ECs were easily distinguished by their morphology and autofluorescence of the surrounding tissue (Fig. 1 .C) observed in the green fluorescence channel under 10× or 20× objective. Sample Preparation Samples were processed following a modified trifluoroacetic acid (TFA)-based protocol (Doellinger et al., 2020 ). Tissue-containing caps from laser microdissection were supplemented with trifluoroacetic acid (≥ 99% TFA (302031, Sigma Aldrich), 10 µL for MN and EC samples, 40 µL for DRG L3, L4, and 30 µL for DRG L5 samples. Samples were mixed by shaking for 3 min, followed by brief centrifugation and 1 min of sonication in an ultrasonic water bath. Following centrifugation, each sample was neutralized by adding a 10-fold volume of 2 M Tris (T1503, Sigma Aldrich) buffer (pH 8.5). Subsequently, a reduction/alkylation buffer - containing 100 mM tris(2-carboxyethyl)phosphine, TCEP (75259, Sigma Aldrich) and 400 mM CAA (2-chloroacetamide, C0267, Sigma Aldrich) - was added in a volume equal to 1.1× that of the original TFA volume. Samples were incubated at 95°C for 5 min. Protein digestion was carried out using sequencing grade modified trypsin (V5111, Promega) at 37°C overnight. Digestion was halted by the addition of TFA to a final concentration of 1% v/v. Tryptic peptides were labeled using an on-column tandem mass tag (TMT) labeling protocol (Myers et al., 2019 ). Individual TMT-labeled peptide samples were pooled into multiplex samples and concentrated using a SpeedVac concentrator. The multiplex peptide samples were fractionated (6 fractions) using Pierce™ High pH Reversed-Phase Peptide Fractionation Kit (84868, Thermo Fisher Scientific). Liquid Chromatography–Mass Spectrometry (LC-MS/MS) Measurement Mass spectrometry analysis was performed in the Proteomics Core Facility, International Institute of Molecular Mechanisms and Machines Polish Academy of Sciences (IMol PAS), Warsaw, Poland. Peptide fractions were resuspended in 0.1% trifluoroacetic acid (TFA) and LC-MS grade 2% acetonitrile (1.00029, Supelco) in water (1.15333, Supelco) prior to analysis. Chromatographic separation was carried out using an Easy-Spray Acclaim PepMap column (50 cm × 75 µm ID; PN ES903, Thermo Fisher Scientific) maintained at 55°C. Peptides were eluted over a 90-minute gradient of acetonitrile in 0.1% aqueous formic acid at a flow rate of 300 nL/min using an UltiMate 3000 nano-LC system (Thermo Fisher Scientific). The LC system was coupled via an Easy-Spray ion source to a Q Exactive HF-X Orbitrap mass spectrometer (Thermo Fisher Scientific), operating in TMT mode. Full MS (survey) scans were acquired at a resolution of 60,000 at m/z 200. Up to 15 of the most abundant isotope patterns with charges 2–5 were selected for MS/MS fragmentation using higher-energy collision dissociation (HCD) with a normalized collision energy (NCE) of 32. Precursor ions were isolated with a 0.7 m/z window, and a dynamic exclusion of 35 seconds was applied. The maximum injection times were set to 50 ms for MS and 150 ms for MS/MS scans. MS/MS spectra were acquired at a resolution of 45,000 (at m/z 200). The automatic gain control (AGC) target values were 3e6 for MS and 1e5 for MS/MS, with a minimum AGC target of 1e3. LC-MS/MS Data Processing Raw MS data files were processed using MaxQuant software (version 1.6.17.0), with peptide identification performed via the built-in Andromeda search engine (Tyanova et al., 2016 ). Spectra were searched against the UniProt Rattus norvegicus reference proteome (UP000002494). Reporter ion MS2-based quantification was employed with a reporter mass tolerance of 0.003 Da and a minimum reporter ion purity (PIF) threshold of 0.75. Carbamidomethylation of cysteines was set as a fixed modification, while oxidation of methionine, deamidation of asparagine/glutamine, and N-terminal acetylation were set as variable modifications. Protein digestion was simulated with trypsin/P specificity (cleavage after lysine or arginine, including before proline), allowing for up to two missed cleavages. False discovery rates (FDR) were set at 1% (0.01) for peptides, proteins, and modification sites. The “match between runs” feature was enabled to increase peptide identification across samples. Other parameters were used at default settings. Reporter intensity-corrected values for protein groups were imported into Perseus (version 1.6.10) for statistical analysis (Tyanova et al., 2016 ). Standard filtering steps were applied to remove: reverse hits (from decoy database), proteins identified only by modification site, common contaminants (based on MaxQuant’s internal list). Reporter intensities were log₂-transformed, and only protein groups quantified across all samples were retained. Data were normalized by median subtraction within TMT channels to correct for systematic variation. Differential expression analysis was performed using two-sided Student’s t-tests with permutation-based FDR correction (FDR = 0.1, S₀ = 0.1). The final statistical tables were exported from Perseus and formatted using Microsoft Excel 2016. Data Records The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (Deutsch et al., 2023 ) via the PRIDE (Perez-Riverol et al., 2025 ) partner repository with the dataset identifier PXD070428 (accessed with credentials provided in the letter to the editor). The submission includes 36 raw LC–MS/MS files (6 sets, 6 fractions each), MaxQuant outputs (three txt folders corresponding to three independent processing runs: sets 1–2, MN samples, processed together; set 3, EC of the central canal, processed separately; and sets 4–6, DRG, processed together), and documentation describing the six TMT-multiplexed sample sets. Alternatively, tables with processed data and comparisons between sample groups, were deposited at RepOD (Open Data Repository) and can be accessed via the following link: https://repod.icm.edu.pl/privateurl.xhtml?token=3657bdbb-26ea-43db-9660-7ec3a8ea0e85 . These tables include normalized protein intensities, differential abundance analyses, and functional annotations, complementing the PRIDE raw data with user-ready, comparative results. Data Overview Table 1 Summary of protein identification and differential expression across analyzed cell types and time points following spinal cord transection (SCT). The table reports the total number of proteins identified in each sample type using the analytical workflow described in the Methods section, as well as the number of proteins significantly up- or downregulated at 2 weeks (Sp2W) and 6 weeks (Sp6W) post-SCT relative to controls. Differentially expressed proteins between 2 and 6 weeks post-injury are also included. Sample number of detected proteins number of up- or down- regulated proteins Sp2W vs CTRL Sp6W vs CTRL Sp2W vs Sp6W SOL MNs 1221 36 15 11 TA MNs 1186 11 4 5 Ependymal cells (EC) 1520 84 19 22 DRG L3 5087 24 88 19 DRG L4 3740 24 36 54 DRG L5 3086 59 31 12 Technical validation Optimization of neurotracing and lysis strategies for proteomic analysis of PEN-mounted cryosections In preliminary experiments Fast Blue neurotracer (2% aqueous solution; Dr. Illing Plastics GmbH, Germany) to retrogradely label MNs was tested; due to rapid fluorescence fading and suboptimal motoneuron yield it was excluded from further use and was replaced successfully with a photostable fluorescent cholera toxin subunit B conjugate. A pilot experiment was conducted to assess whether it is feasible to identify proteins in frozen tissue sections that were cut together with the fragments of PEN membrane onto which they were mounted. Several protein extraction methods were tested, including trifluoroacetic acid (TFA), formic acid (FA), and the ProteaseMAX surfactant reagent (V2071, Promega) in HEPES buffer (Fig. 2 ). The best results for small spinal cord samples (1 mm², 20 µm thickness) were obtained using TFA, which enabled the identification of 2 492 proteins. In comparison, the application of ProteaseMAX or FA allowed the identification of 2 054 and 618 proteins, respectively. It was also confirmed that the PEN membrane remains stable in acidic conditions and does not interfere with analytical results. Experimental reproducibility and design Each experimental group (three conditions: healthy control, 2 and 6 weeks post-SCT) included five biological replicates ( n = 5 rats per group ). Samples were analysed in 6 batches. To minimize inter-batch variation, samples of a given type (SOL MNs, TA MNs, DRG L3, DRG L4, DRG L5 or EC) were analyzed within a single TMT 16-plex set/batch. Consistency of laser microdissection of motoneurons and ependymal cell layer Retrogradely traced SOL and TA MNs, as well as EC layers were laser microdissected. DRG L3-5 were dissected as whole structures (4–8 mg wet mass per left + right ganglion). The average dissected tissue area per animal was 0.24 ± 0,058 mm² for SOL MNs, 0.34 ± 0.078 mm² for TA MNs, and 0.89 ± 0.038 mm² for EC layer. Corresponding numbers of dissected MNs were 172 ± 39 for SOL, 262 ± 74 for TA, and 30 ± 18 fragments for EC layer. The mean area of cut MN sections was relatively consistent across groups, with 1428 ± 101 µm² for SOL and 1 341 ± 220 µm² for TA. This value was not determined for individual ECs because of their small dimensions (6–8 micrometers) and tight fit; they were cut as a layer. We calculated tissue volume by multiplying the dissected total area by the slice thickness (25 µm), then tissue mass was estimated with assumption of brain tissue density as 1 g/cm³ (Barber et al., 1970 ). The estimated wet mass of sampled tissue was: 6.11 ± 1.45 ng for SOL MNs, 8.48 ± 1.95 ng for TA MNs, and 22.27 ± 9.59 ng for EC (Table 2 ). Table 2 Parameters of microdissected samples Averaged parameters of microdissected samples per animal (± SD) number of cells/fragments mean area of cell [µm 2 ] total dissected area [mm 2 ] tissue mass* [ng] SOL MNs 172 ± 39 1428 ± 101 (Control: 1499 ± 51, Sp2W: 1376 ± 137, Sp6W: 1377 ± 74) 0.24 ± 0,058 6.11 ± 1.45 TA MNs 262 ± 74 1341 ± 220 (Control: 1468 ± 243, Sp2W: 1143 ± 77, Sp6W: 1331 ± 133) 0.34 ± 0.078 8.48 ± 1.95 EC layer 30 ± 18 - 0.89 ± 0.038 22.27 ± 9.59 *estimated Data quality and reproducibility Principal component analysis (PCA) was performed to assess the consistency and separation of proteomic profiles across 6 data sets (for each sample type) and 3 experimental groups (control, Sp2W, Sp6W). In motoneurons, the first two components explained 36.0% (PC1) and 19.2% (PC2) of the total variance for SOL MNs, and 51.7% (PC1) and 13.5% (PC2) for TA MNs, demonstrating good within-group homogeneity and clear distinction between subtypes. In ependymal cells (EC), PCA captured 60.3% (PC1) and 11.4% (PC2) of the variance, indicating highly consistent expression patterns and a strong injury-associated signature. In dorsal root ganglia (DRG), variance explained by PC1 and PC2 ranged from 38.1% / 23.5% (L3) and 39.6% / 32.3% (L4) to 60.3% / 23.8% (L5), reflecting robust reproducibility and distinct segmental differentiation. Overall, PCA confirmed high biological consistency within each sample type and separation between experimental conditions. Table 3 PCA analysis of 6 datasets from 3 experimental groups of Control, SP2W and SP6W rats Sample type PC1 variance % PC2 variance % Interpretation SOL MNs 36% 19.2% Moderate variance capture; samples show good internal consistency and distinct but partly overlapping proteomic profiles across groups. Indicates heterogeneous responses after SCT. TA MNs 51.7% 13.5% High variance capture; clear separation between experimental groups and strong internal homogeneity. Ependymal cells (EC) 60.3% 11.4% High explained variance; consistent proteomic profiles and pronounced injury-related clustering. Indicates a highly coherent and time-dependent response after SCT. DRG L3 38.1% 23.5% Moderate variance explained; stable grouping and reliable biological reproducibility. DRG L4 39.6% 32.3% High cumulative variance (≈ 72%); distinct and homogeneous injury-related pattern. DRG L5 60.3% 23.8% Large variance captured, nearly complete separation between experimental groups, indicating pronounced injury-related molecular shifts. In the DRG (L3–L5) datasets, two outliers were observed in each segment, including one recurring outlier from animal Hb14 (control group). Technical notes indicate digestion issues for these samples during digestion (including unintended prolonged exposure to room temperature), which may have contributed to their higher variability. Please note that this sample was not removed from the dataset, as it still met the inclusion criteria and retained sufficient data quality for downstream analysis. Biological validation of MNs and EC identity Validation of Cell-Type Identity Proteomic profiles confirmed the expected molecular identities of both motoneuron (MN) and ependymal cell (EC) isolates, validating the accuracy of laser microdissection and sample preparation. In MN samples, detection of neuronal and motoneuron-enriched proteins such as: Cytoskeletal and axonal transport proteins: Tubb3, Tuba1a, Nefh, Nefm, Nefl, Kif5a, Dync1h1, Map1b, Ank2; Synaptic vesicle and neurotransmission components: Snap25, Syt2, Syn1, Syp, Vamp1, Stx1b, Rab3a, Cplx1; Neuron-specific RNA-binding proteins: Elavl3 (HuC), Rbfox3 (NeuN), Nova1. These neuronal markers confirm the integrity of the motoneuron proteome and validate successful retrograde labeling and laser microdissection. In EC isolates, proteomic signatures were consistent with the epithelial phenotype of the spinal central canal lining. Strong expression of junctional and desmosomal proteins— jup , dsp , dsg1 , and ctnna1 —confirmed preserved cell-cell adhesion complexes typical of the ependymal barrier. The detection of sparcl1 and dclk1 supported an ependymal and radial-glia-like identity, while mitochondrial proteins ( tomm34 , timm44 , ndufa12 ) reflected the high metabolic activity characteristic of this epithelium. The presence of s100a13 and ro60 , associated with epithelial stress and remodeling, aligned with post-injury activation of the central canal region. Limitations and cellular overlap Although the motoneuron (MN) proteomes show a strong neuronal signature, several canonical cholinergic markers expected in MNs — including chat (choline acetyltransferase) and slc18a3 (vesicular acetylcholine transporter, VAChT) — were not detected. This likely reflects the low abundance of these proteins in microdissected cell bodies, as these proteins are mostly accumulated in the axonal compartment and therefore are underrepresented in LC-MS/MS datasets. Likewise, muscarinic receptors ( chrm2 , chrm4 ) were absent, consistent with poor recovery of GPCRs in standard proteomic workflows. Low-level detection of astrocytic proteins such as gfap and aldh1l1 likely results from perisomatic glial processes that are difficult to exclude during microdissection. Overall, MN datasets are neuronally dominated and biologically consistent, though membrane receptor coverage and minor glial signals remain inherent technical limitations. Although EC proteomes showed strong epithelial and junctional signatures, several classical ependymal and ciliary markers (e.g., foxj1, dnaic1 ) were not detected. Low-level detection of glial and extracellular matrix proteins probably reflects partial inclusion of periependymal tissue during microdissection. Declarations Data Availability The data deposited online (PXD070428, accessed with credentials provided in the letter to the editor) was supplied as raw LC-MS/MS files and result files from MaxQuant. The raw files can be used for additional searches (e.g. with different parameters, different software). The results of MaxQuant searches can be further processed (filtered, normalized, analyzed statistically, visualized, etc.). Alternatively, tables with processed data and comparisons between sample groups, were deposited at RepOD (Open Data Repository) and can be accessed via the following link: https://repod.icm.edu.pl/privateurl.xhtml?token=3657bdbb-26ea-43db-9660-7ec3a8ea0e85. Code Availability No custom code has been used. Author contributions OGW and MS conceived and designed the study. Experimental methodology, including sample preparation and optimization of the proteomic workflow, was developed by OGW and RS. Data acquisition, processing, and analysis were performed by OGW, RS, TW and KR. RS curated the proteomic data and prepared the repository submission. Figures and visualizations were generated by OGW and AP. OGW drafted the manuscript, and all authors contributed to its review and editing. Funding was provided by OGW and MS. Disclosure of Conflicts of Interest None of the authors has any conflict of interest to disclose. Funding This work received support from the Polish National Science Center grants 2022/06/X/NZ3/01783 (OGW) and 2018/31/B/NZ4/02789 (MS). References Barber, T. W., Brockway, J. A., & Higgins, L. S. (1970). The density of tissues in and about the head. Acta Neurologica Scandinavica , 46 (1), 85–92. https://doi.org/10.1111/j.1600-0404.1970.tb05606.x Chopek, J. W., Sheppard, P. C., Gardiner, K., & Gardiner, P. F. (2015). Serotonin receptor and KCC2 gene expression in lumbar flexor and extensor motoneurons posttransection with and without passive cycling. Journal of Neurophysiology , 113 (5), 1369–1376. https://doi.org/10.1152/jn.00550.2014 Deutsch, E. W., Bandeira, N., Perez-Riverol, Y., Sharma, V., Carver, J. J., Mendoza, L., Kundu, D. J., Wang, S., Bandla, C., Kamatchinathan, S., Hewapathirana, S., Pullman, B. 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Regulation of perineuronal net components in the synaptic bouton vicinity on lumbar alpha-motoneurons in the rat after spinalization and locomotor training: New insights from spatio-temporal changes in gene, protein expression and WFA labeling. Exp Neurol , 354 , 114098. Guise, A. J., Misal, S. A., Carson, R., Chu, J.-H., Boekweg, H., Van Der Watt, D., Welsh, N. C., Truong, T., Liang, Y., Xu, S., Benedetto, G., Gagnon, J., Payne, S. H., Plowey, E. D., & Kelly, R. T. (2024). TDP-43-stratified single-cell proteomics of postmortem human spinal motor neurons reveals protein dynamics in amyotrophic lateral sclerosis. Cell Reports , 43 (1), 113636. https://doi.org/10.1016/j.celrep.2023.113636 Hale, O. J., Wells, T. R., Mead, R. J., & Cooper, H. J. (2024). Mass spectrometry imaging of SOD1 protein-metal complexes in SOD1G93A transgenic mice implicates demetalation with pathology. Nature Communications , 15 (1), 6518. https://doi.org/10.1038/s41467-024-50514-7 Ji, B., Wojtaś, B., & Skup, M. (2022). Molecular Identification of Pro-Excitogenic Receptor and Channel Phenotypes of the Deafferented Lumbar Motoneurons in the Early Phase after SCT in Rats. International Journal of Molecular Sciences , 23 (19), 11133. https://doi.org/10.3390/ijms231911133 Lacroix, S., Hamilton, L. K., Vaugeois, A., Beaudoin, S., Breault-Dugas, C., Pineau, I., Lévesque, S. A., Grégoire, C.-A., & Fernandes, K. J. L. (2014). Central Canal Ependymal Cells Proliferate Extensively in Response to Traumatic Spinal Cord Injury but Not Demyelinating Lesions. PLOS ONE , 9 (1), e85916. https://doi.org/10.1371/journal.pone.0085916 Mohan, R., Tosolini, A. P., & Morris, R. (2015a). Intramuscular Injections Along the Motor End Plates: A Minimally Invasive Approach to Shuttle Tracers Directly into Motor Neurons. Journal of Visualized Experiments: JoVE , 101 , e52846. https://doi.org/10.3791/52846 Mohan, R., Tosolini, A. P., & Morris, R. (2015b). Segmental distribution of the motor neuron columns that supply the rat hindlimb: A muscle/motor neuron tract-tracing analysis targeting the motor end plates. Neuroscience , 307 , 98–108. https://doi.org/10.1016/j.neuroscience.2015.08.030 Myers, S. A., Rhoads, A., Cocco, A. R., Peckner, R., Haber, A. L., Schweitzer, L. D., Krug, K., Mani, D. R., Clauser, K. R., Rozenblatt-Rosen, O., Hacohen, N., Regev, A., & Carr, S. A. (2019). Streamlined Protocol for Deep Proteomic Profiling of FAC-sorted Cells and Its Application to Freshly Isolated Murine Immune Cells*. Molecular & Cellular Proteomics , 18 (5), 995a–1009. https://doi.org/10.1074/mcp.RA118.001259 Perez-Riverol, Y., Bandla, C., Kundu, D. J., Kamatchinathan, S., Bai, J., Hewapathirana, S., John, N. S., Prakash, A., Walzer, M., Wang, S., & Vizcaíno, J. A. (2025). The PRIDE database at 20 years: 2025 update. Nucleic Acids Research , 53 (D1), D543–D553. https://doi.org/10.1093/nar/gkae1011 Ren, Y., Ao, Y., O’Shea, T. M., Burda, J. E., Bernstein, A. M., Brumm, A. J., Muthusamy, N., Ghashghaei, H. T., Carmichael, S. T., Cheng, L., & Sofroniew, M. V. (2017). Ependymal cell contribution to scar formation after spinal cord injury is minimal, local and dependent on direct ependymal injury. Scientific Reports , 7 (1), 41122. https://doi.org/10.1038/srep41122 Skup, M., Gajewska-Wozniak, O., Grygielewicz, P., Mankovskaya, T., & Czarkowska-Bauch, J. (2012). Different effects of spinalization and locomotor training of spinal animals on cholinergic innervation of the soleus and tibialis anterior motoneurons. Eur J Neurosci , 36 (5), Article 5. https://doi.org/10.1111/j.1460-9568.2012.08182.x Tyanova, S., Temu, T., & Cox, J. (2016). The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nature Protocols , 11 (12), 2301–2319. https://doi.org/10.1038/nprot.2016.136 Wieckowska, A., Gajewska-Wozniak, O., Glowacka, A., Ji, B., Grycz, K., Czarkowska-Bauch, J., & Skup, M. (2018). Spinalization and locomotor training differentially affect muscarinic acetylcholine receptor type 2 abutting on alpha-motoneurons innervating the ankle extensor and flexor muscles. J Neurochem . https://doi.org/10.1111/jnc.14567 Ziemlinska, E., Kugler, S., Schachner, M., Wewior, I., Czarkowska-Bauch, J., & Skup, M. (2014). Overexpression of BDNF increases excitability of the lumbar spinal network and leads to robust early locomotor recovery in completely spinalized rats. PLoS One , 9 (2), Article 2. https://doi.org/10.1371/journal.pone.0088833 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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18:54:12","extension":"html","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":101491,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8134246/v1/356a44de5e9392464033cede.html"},{"id":96211921,"identity":"46a398b7-5364-4ad8-8f52-54092388ced2","added_by":"auto","created_at":"2025-11-18 18:54:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":406429,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExperimental design. A.\u003c/strong\u003e To label SOL and TA MNs, adult Wistar rats (n=19) received injections of retrograde tracers into SOL or TA muscles. \u003cstrong\u003eB.\u003c/strong\u003e Rats were sacrificed 2 (Sp2W, n=5) or 6 weeks (Sp6W, n=5) after thoracic (Th9) spinal cord transection (SCT); nine rats served as healthy controls. \u003cstrong\u003eC.\u003c/strong\u003e Labeled MNs and ECs were isolated by laser microdissection (Leica LMD7000).\u003cstrong\u003e D.\u003c/strong\u003e Proteins were extracted, digested, and labeled with tandem mass tags (TMT). \u003cstrong\u003eE.\u003c/strong\u003e Peptides were separated using an Easy-Spray PepMap column on an UltiMate 3000 nano-LC system coupled to a Q Exactive HF-X mass spectrometer. \u003cstrong\u003eF.\u003c/strong\u003e Data was processed in MaxQuant (v1.6.17.0) with identification via the Andromeda search engine against the \u003cem\u003eRattus norvegicus\u003c/em\u003e UniProt database. Figure generated with Biorender.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8134246/v1/4d00b39edf706cf2ba457f15.png"},{"id":96252746,"identity":"9efbfa26-2ce0-4cce-ae5a-7a5be90b69bf","added_by":"auto","created_at":"2025-11-19 07:41:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":154298,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of protein extraction methods from frozen spinal cord sections mounted on PEN membranes. Representative total ion current (TIC) chromatograms after extraction with trifluoroacetic acid (TFA; black), formic acid (FA; brown), or ProteaseMAX (green). TFA produced the highest TIC and yielded the greatest number of protein identifications relative to FA and ProteaseMAX. TIC intensity (y-axis) is plotted against chromatographic time (x-axis). Chromatograms were exported with Thermo Scientific FreeStyle (v1.5).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8134246/v1/389ef481f0e078a95c7226f7.png"},{"id":96252839,"identity":"57c3838a-5e64-4392-bd66-8f10859948f9","added_by":"auto","created_at":"2025-11-19 07:41:31","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":182928,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component analysis (PCA) of proteomic profiles across all 6 sample types and 3 experimental groups. Each plot displays the distribution of biological replicates along PC1 and PC2 for: SOL and TA MNs, ependymal cells, and DRG from L3, L4, and L5 segments. Percent variance explained by each component is indicated on the corresponding axes.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8134246/v1/e5517ff5cd00331548ef1587.png"},{"id":96257213,"identity":"4227184e-b0ab-478d-91ab-74c58e06bd1c","added_by":"auto","created_at":"2025-11-19 07:51:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1668590,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8134246/v1/65e2071c-561f-4473-a388-307cdd72a4a8.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eProteomic profile of Laser-dissected Motoneurons and Ependymal Cell Layer and of Dorsal Root Ganglia after Spinal Cord Injury in Rat\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSpinal cord injuries (SCI) remain a critical health and societal challenge worldwide, leading to severe and often irreversible functional impairments. Despite significant advances in therapeutic approaches, including epidural stimulation and treatment with biomaterials with cell-based systems, many obstacles to effective recovery persist. A growing body of evidence highlights that motoneurons (MNs) innervating distinct muscle groups possess unique physiological and molecular characteristics. We recently demonstrated that spinalization in rats alters protein and gene expression of neurotransmitter and neurotrophin receptors in tracer-identified, isolated MNs innervating ankle joint extensor and flexor muscles, both at 2nd and 6th week post-lesion (Chopek et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Głowacka et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ji et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Skup et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Wieckowska et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, detailed proteomic profiles of these MNs are lacking.\u003c/p\u003e\u003cp\u003eDeciphering the proteomic heterogeneity of MNs innervating different muscles, as well as their adaptive responses to injury and stimulation, is crucial for identifying novel therapeutic targets and strategies of precision medicine. However, a significant methodological challenge remains: reliably distinguishing and isolating homogeneous populations of MNs for proteomic analyses. While amyotrophic lateral sclerosis (ALS) studies have used fluorescence-activated cell sorting (FACS) of cultured neurons (Garone et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) or laser microdissection (LMD) (Guise et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Hale et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) to isolate unidentified MNs from murine and human spinal cords for mass spectrometry analyses, so far no study has examined proteomic profiles of target-defined MNs in healthy and diseased state.\u003c/p\u003e\u003cp\u003eTo address this gap, the present study utilizes proteomic profiling of retrogradely labeled MNs isolated via laser microdissection (LMD). We focus on antagonistic hindlimb muscle groups in rats - the soleus (SOL) and tibialis anterior (TA) - to characterize respective MN proteomes in no-treated animals and at two post- spinal cord injury time points (2 and 6 weeks). In addition, we performed proteomic analysis of DRG from L3, L4, L5 lumbar segments corresponding to the MN pools under study, which house the cell bodies of sensory neurons that transmit peripheral information to the central nervous system, including monosynaptic inputs to MNs. These structures play a pivotal role in pain perception and other sensory modalities, which are often altered after SCI.\u003c/p\u003e\u003cp\u003eWe included in the study ependymal cells (EC) lining the spinal cord\u0026rsquo;s central canal, which contribute to cerebrospinal fluid (CSF) production and distribution. In the light of data showing the stimulatory effect of injury on ECs proliferation, we expected that their proteome undergoes remodeling (Lacroix et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). ECs have been proposed as adult neural stem cells with therapeutic potential for spinal cord repair. Although their regenerative capacity was reported as limited and localized (Ren et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), analyzing proteomic changes can confirm their phenotypic adaptations.\u003c/p\u003e\u003cp\u003eTogether, this study offers a comprehensive proteomic dataset obtained from target-defined MNs, DRGs and ECs, key cell types involved in motor and sensory function and regeneration after spinal cord injury, paving the way for more targeted and effective therapies.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eAnimals\u003c/h2\u003e\u003cp\u003eExperiments were conducted on 19 adult male Wistar rats (body weight: 270\u0026ndash;325 g at the start of the study), bred and housed at the Nencki Institute of Experimental Biology PAS in Warsaw, Poland. Animals had free access to standard pellet food and water and were maintained on a 12-hour light/dark cycle, in groups of 4\u0026ndash;6.\u003c/p\u003e\u003cp\u003e All experimental procedures, including surgeries and postoperative care, were approved by the 1st Local Ethics Committee in Warsaw (decision numbers 1481P1/2023 and 1482P2/2023), in accordance with Directive 2010/63/EU of the European Parliament and Council on the protection of animals used for scientific purposes.\u003c/p\u003e\u003cp\u003eThe main experiment was carried out on 16 rats. Fluorescent retrograde tracers were injected into hindlimb muscles, the soleus (SOL) and tibialis anterior (TA). In 10 animals, spinal cord transection (SCT) was performed at the Th9 level. Five rats were sacrificed 2 weeks post-SCT (Sp2W group), and five at 6 weeks post-SCT (Sp6W).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eRetrograde Tracing of Motoneurons\u003c/h3\u003e\n\u003cp\u003eAs in our previous studies (Grycz et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Skup et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), animals were premedicated with subcutaneous Butomidor (butorphanol, 1.5 mg/300 g body weight; Richter Pharma, Wels, Austria) and anesthetized with isoflurane (1\u0026ndash;2.5% in oxygen; Baxter, Lessines, Belgium) delivered via a face mask.\u003c/p\u003e\u003cp\u003eThe skin over the target muscles\u0026mdash;SOL and TA\u0026mdash;was shaved and cleaned using 70% ethanol. To retrogradely label motoneurons (MNs) innervating these muscles, cholera toxin subunit B (CTx) conjugated with Alexa Fluor 555 or Alexa Fluor 488 (0.01% in phosphate-buffered saline; Molecular Probes, USA) was bilaterally injected into the SOL and TA muscles, respectively, using a Hamilton microsyringe equipped with a 26- or 22-gauge needle (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eInjection sites were chosen based on prior motor endplate staining (Mohan et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015b\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015a\u003c/span\u003e), and each injection lasted approximately 10 minutes. To minimize tracer leakage, the needle was left in place for 3 minutes following injection. Afterward, the site was rinsed with sterile saline and the skin was sutured.\u003c/p\u003e\u003cp\u003ePostoperative care included subcutaneous administration of Tolfedine (tolfenamic acid 4%, 4 mg/kg; Vetoquinol, Lure Cedex, France) for analgesia over five days, and Baytril (enrofloxacin, 5 mg/kg; Bayer GmbH, Leverkusen, Germany) once daily for five consecutive days to prevent infection. After recovery from anesthesia, animals were returned to their home cages with \u003cem\u003ead libitum\u003c/em\u003e access to food and water.\u003c/p\u003e\n\u003ch3\u003eSpinal Cord Transection\u003c/h3\u003e\n\u003cp\u003eApproximately one week after tracer administration, rats from the Sp2W and Sp6W groups underwent complete SCT. Surgical procedures (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) were performed as previously described (Ziemlinska et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBriefly, the dorsal skin was shaved and cleaned with 70% ethanol, then incised at the level of the lower thoracic vertebrae. Muscles and ligaments were carefully separated to expose the vertebrae. Following identification of the Th9 and Th10 vertebral levels, a laminectomy was performed. The dura mater was opened, and 2% lidocaine (Lignocainum hydrochloricum; Polfa Warszawa S.A., Poland) was applied topically to the spinal cord before it was completely transected using fine surgical scissors. The lesion gap was then gently enlarged to approximately 0.5 mm by aspiration, and the site was rinsed with a 0.9% NaCl solution.\u003c/p\u003e\u003cp\u003eThe lesion area was carefully inspected under a surgical microscope (Nikon SMZ 1000) to confirm completeness of transection. Surrounding tissues were repositioned, and the muscle and skin layers were sutured.\u003c/p\u003e\u003cp\u003eFollowing surgery, approximately 5 ml of 0.9% NaCl was administered subcutaneously for rehydration. Postoperative care included subcutaneous administration of the antibiotic Sultridin (30 mg/kg; Norbrook, Ireland) once daily for five consecutive days, and the analgesic Vetaflunix (2.5 mg/kg; VET AGRO, Poland) for three days.\u003c/p\u003e\u003cp\u003eImmediately post-surgery, each animal was placed in a clean recovery cage on a heated mat and monitored until fully awake (approximately 1 hour), after which they were returned to their home cages with free access to food and water.\u003c/p\u003e\u003cp\u003eAnimals were monitored three times daily during the first postoperative week, and twice daily during the second week. Care included general health inspection, cleaning of the perineal area, and manual bladder expression when necessary. Spontaneous micturition typically resumed during the second postoperative week. No major health complications were observed in any animal throughout the duration of the experiment.\u003c/p\u003e\n\u003ch3\u003eTissue Preparation and Laser Microdissection (LMD)\u003c/h3\u003e\n\u003cp\u003eAnimals were anesthetized with isoflurane and euthanized by a lethal intraperitoneal injection of pentobarbital (120 mg/kg body weight; Morbital, Biowet, Poland).\u003c/p\u003e\u003cp\u003eRats were then transcardially perfused with 250 ml of ice-cold 0.01 M phosphate-buffered saline (PBS: 154 mM NaCl, 1.3 mM Na₂HPO₄, 2.5 mM NaH₂PO₄; pH 7.4). The vertebral column was excised and placed on ice. Lumbar spinal cord segments (L3\u0026ndash;L6, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), approximately 1.2 cm long, were rapidly dissected, snap-frozen in dry ice-cooled tubes, and stored at \u0026minus;\u0026thinsp;80\u0026deg;C until further processing (within one month). Dorsal root ganglia (DRGs) from segments L3, L4, and L5 were dissected bilaterally as whole structures. The L3 and L4 DRGs are the largest ganglia within the lumbar region and can be easily distinguished based on their size and anatomical location. Left and right ganglia from each lumbar level were pooled and frozen. Frozen L3\u0026ndash;L6 spinal cord segments were embedded in Jung tissue-freezing medium (Leica, cat. no. 14020108926) and sectioned longitudinally at 20 \u0026micro;m thickness using a cryostat (Slee MEV, SLEE Medical GmbH) at \u0026minus;\u0026thinsp;20\u0026deg;C. Sections were mounted onto RNase-free PEN membrane frame slides (Leica No. 11505190 or Applied Biosystems\u0026trade; LCM0521), with 6\u0026ndash;9 sections per slide and approximately 3 slides per animal. Slides were stored on dry ice or at \u0026minus;\u0026thinsp;80\u0026deg;C for up to one week prior to microdissection.\u003c/p\u003e\u003cp\u003ePrior to microdissection, slides were dehydrated through a graded ethanol series (70%, 80%, 90%, and 2 \u0026times; 100%, each for 30 s), followed by two xylene washes (30 s and 180 s), and air-dried for 3\u0026ndash;5 minutes.\u003c/p\u003e\u003cp\u003eMNs and EC tissue samples were isolated using the Leica LMD7000 Laser Microdissection System. PEN membrane frame slides were placed in the slide holder, and RNase-free 0.2 ml tube caps were positioned in tube holders for gravity-based sample collection. Labeled MNs (SOL with Alexa Fluor 555, and TA with Alexa 488) were visualized under the microscope using first 10\u0026times; (NA 0.32) and then 63\u0026times; (NA 0.7) objectives, and individually dissected using a UV laser. Laser parameters (power, aperture, speed, and pulse frequency) were set automatically for each objective and adjusted to minimize laser power while maintaining efficient tissue cutting.\u003c/p\u003e\u003cp\u003eCollected MNs were captured directly into the tube caps by gravity. Following MNcollection from each membrane slide (typically up to 3 hours/slide), tubes were sealed and stored on dry ice or at \u0026minus;\u0026thinsp;80\u0026deg;C (inverted, cap-down) until the next step. ECs were identified in the same tissue sections, and microdissected. ECs were easily distinguished by their morphology and autofluorescence of the surrounding tissue (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.C) observed in the green fluorescence channel under 10\u0026times; or 20\u0026times; objective.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eSample Preparation\u003c/h3\u003e\n\u003cp\u003eSamples were processed following a modified trifluoroacetic acid (TFA)-based protocol (Doellinger et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Tissue-containing caps from laser microdissection were supplemented with trifluoroacetic acid (\u0026ge;\u0026thinsp;99% TFA (302031, Sigma Aldrich), 10 \u0026micro;L for MN and EC samples, 40 \u0026micro;L for DRG L3, L4, and 30 \u0026micro;L for DRG L5 samples. Samples were mixed by shaking for 3 min, followed by brief centrifugation and 1 min of sonication in an ultrasonic water bath. Following centrifugation, each sample was neutralized by adding a 10-fold volume of 2 M Tris (T1503, Sigma Aldrich) buffer (pH 8.5). Subsequently, a reduction/alkylation buffer - containing 100 mM tris(2-carboxyethyl)phosphine, TCEP (75259, Sigma Aldrich) and 400 mM CAA (2-chloroacetamide, C0267, Sigma Aldrich) - was added in a volume equal to 1.1\u0026times; that of the original TFA volume. Samples were incubated at 95\u0026deg;C for 5 min. Protein digestion was carried out using sequencing grade modified trypsin (V5111, Promega) at 37\u0026deg;C overnight. Digestion was halted by the addition of TFA to a final concentration of 1% v/v. Tryptic peptides were labeled using an on-column tandem mass tag (TMT) labeling protocol (Myers et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Individual TMT-labeled peptide samples were pooled into multiplex samples and concentrated using a SpeedVac concentrator. The multiplex peptide samples were fractionated (6 fractions) using Pierce\u0026trade; High pH Reversed-Phase Peptide Fractionation Kit (84868, Thermo Fisher Scientific).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eLiquid Chromatography\u0026ndash;Mass Spectrometry (LC-MS/MS) Measurement\u003c/h2\u003e\u003cp\u003eMass spectrometry analysis was performed in the Proteomics Core Facility, International Institute of Molecular Mechanisms and Machines Polish Academy of Sciences (IMol PAS), Warsaw, Poland. Peptide fractions were resuspended in 0.1% trifluoroacetic acid (TFA) and LC-MS grade 2% acetonitrile (1.00029, Supelco) in water (1.15333, Supelco) prior to analysis. Chromatographic separation was carried out using an Easy-Spray Acclaim PepMap column (50 cm \u0026times; 75 \u0026micro;m ID; PN ES903, Thermo Fisher Scientific) maintained at 55\u0026deg;C. Peptides were eluted over a 90-minute gradient of acetonitrile in 0.1% aqueous formic acid at a flow rate of 300 nL/min using an UltiMate 3000 nano-LC system (Thermo Fisher Scientific). The LC system was coupled via an Easy-Spray ion source to a Q Exactive HF-X Orbitrap mass spectrometer (Thermo Fisher Scientific), operating in TMT mode. Full MS (survey) scans were acquired at a resolution of 60,000 at m/z 200. Up to 15 of the most abundant isotope patterns with charges 2\u0026ndash;5 were selected for MS/MS fragmentation using higher-energy collision dissociation (HCD) with a normalized collision energy (NCE) of 32. Precursor ions were isolated with a 0.7 m/z window, and a dynamic exclusion of 35 seconds was applied. The maximum injection times were set to 50 ms for MS and 150 ms for MS/MS scans. MS/MS spectra were acquired at a resolution of 45,000 (at m/z 200). The automatic gain control (AGC) target values were 3e6 for MS and 1e5 for MS/MS, with a minimum AGC target of 1e3.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eLC-MS/MS Data Processing\u003c/h3\u003e\n\u003cp\u003eRaw MS data files were processed using MaxQuant software (version 1.6.17.0), with peptide identification performed via the built-in Andromeda search engine (Tyanova et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Spectra were searched against the UniProt \u003cem\u003eRattus norvegicus\u003c/em\u003e reference proteome (UP000002494). Reporter ion MS2-based quantification was employed with a reporter mass tolerance of 0.003 Da and a minimum reporter ion purity (PIF) threshold of 0.75. Carbamidomethylation of cysteines was set as a fixed modification, while oxidation of methionine, deamidation of asparagine/glutamine, and N-terminal acetylation were set as variable modifications. Protein digestion was simulated with trypsin/P specificity (cleavage after lysine or arginine, including before proline), allowing for up to two missed cleavages. False discovery rates (FDR) were set at 1% (0.01) for peptides, proteins, and modification sites. The \u0026ldquo;match between runs\u0026rdquo; feature was enabled to increase peptide identification across samples. Other parameters were used at default settings. Reporter intensity-corrected values for protein groups were imported into Perseus (version 1.6.10) for statistical analysis (Tyanova et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Standard filtering steps were applied to remove: reverse hits (from decoy database), proteins identified only by modification site, common contaminants (based on MaxQuant\u0026rsquo;s internal list). Reporter intensities were log₂-transformed, and only protein groups quantified across all samples were retained. Data were normalized by median subtraction within TMT channels to correct for systematic variation. Differential expression analysis was performed using two-sided Student\u0026rsquo;s t-tests with permutation-based FDR correction (FDR\u0026thinsp;=\u0026thinsp;0.1, S₀ = 0.1). The final statistical tables were exported from Perseus and formatted using Microsoft Excel 2016.\u003c/p\u003e"},{"header":"Data Records","content":"\u003cp\u003eThe mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (Deutsch et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) via the PRIDE (Perez-Riverol et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) partner repository with the dataset identifier PXD070428 (accessed with credentials provided in the letter to the editor). The submission includes 36 raw LC–MS/MS files (6 sets, 6 fractions each), MaxQuant outputs (three txt folders corresponding to three independent processing runs: sets 1–2, MN samples, processed together; set 3, EC of the central canal, processed separately; and sets 4–6, DRG, processed together), and documentation describing the six TMT-multiplexed sample sets. Alternatively, tables with processed data and comparisons between sample groups, were deposited at RepOD (Open Data Repository) and can be accessed via the following link: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://repod.icm.edu.pl/privateurl.xhtml?token=3657bdbb-26ea-43db-9660-7ec3a8ea0e85\u003c/span\u003e\u003cspan address=\"https://repod.icm.edu.pl/privateurl.xhtml?token=3657bdbb-26ea-43db-9660-7ec3a8ea0e85\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. These tables include normalized protein intensities, differential abundance analyses, and functional annotations, complementing the PRIDE raw data with user-ready, comparative results.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eData Overview\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cb\u003eSummary of protein identification and differential expression across analyzed cell types and time points following spinal cord transection (SCT).\u003c/b\u003e The table reports the total number of proteins identified in each sample type using the analytical workflow described in the Methods section, as well as the number of proteins significantly up- or downregulated at 2 weeks (Sp2W) and 6 weeks (Sp6W) post-SCT relative to controls. Differentially expressed proteins between 2 and 6 weeks post-injury are also included.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSample\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003enumber of detected proteins\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003enumber of up- or down- regulated proteins\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSp2W vs CTRL\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSp6W vs CTRL\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSp2W vs Sp6W\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSOL MNs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTA MNs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1186\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEpendymal cells (EC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1520\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDRG L3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5087\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDRG L4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3740\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDRG L5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3086\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eTechnical validation\u003c/h2\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003eOptimization of neurotracing and lysis strategies for proteomic analysis of PEN-mounted cryosections\u003c/h2\u003e\u003cp\u003eIn preliminary experiments Fast Blue neurotracer (2% aqueous solution; Dr. Illing Plastics GmbH, Germany) to retrogradely label MNs was tested; due to rapid fluorescence fading and suboptimal motoneuron yield it was excluded from further use and was replaced successfully with a photostable fluorescent cholera toxin subunit B conjugate.\u003c/p\u003e\u003cp\u003eA pilot experiment was conducted to assess whether it is feasible to identify proteins in frozen tissue sections that were cut together with the fragments of PEN membrane onto which they were mounted. Several protein extraction methods were tested, including trifluoroacetic acid (TFA), formic acid (FA), and the ProteaseMAX surfactant reagent (V2071, Promega) in HEPES buffer (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The best results for small spinal cord samples (1 mm², 20 µm thickness) were obtained using TFA, which enabled the identification of 2 492 proteins. In comparison, the application of ProteaseMAX or FA allowed the identification of 2 054 and 618 proteins, respectively. It was also confirmed that the PEN membrane remains stable in acidic conditions and does not interfere with analytical results.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Experimental reproducibility and design","content":"\u003cp\u003eEach experimental group (three conditions: healthy control, 2 and 6 weeks post-SCT) included five biological replicates (\u003cem\u003en = 5 rats per group\u003c/em\u003e). Samples were analysed in 6 batches. To minimize inter-batch variation, samples of a given type (SOL MNs, TA MNs, DRG L3, DRG L4, DRG L5 or EC) were analyzed within a single TMT 16-plex set/batch.\u003c/p\u003e\u003ch2\u003eConsistency of laser microdissection of motoneurons and ependymal cell layer\u003c/h2\u003e\u003cp\u003eRetrogradely traced SOL and TA MNs, as well as EC layers were laser microdissected. DRG L3-5 were dissected as whole structures (4–8 mg wet mass per left + right ganglion). The average dissected tissue area per animal was 0.24 ± 0,058 mm² for SOL MNs, 0.34 ± 0.078 mm² for TA MNs, and 0.89 ± 0.038 mm² for EC layer. Corresponding numbers of dissected MNs were 172 ± 39 for SOL, 262 ± 74 for TA, and 30 ± 18 fragments for EC layer. The mean area of cut MN sections was relatively consistent across groups, with 1428 ± 101 µm² for SOL and 1 341 ± 220 µm² for TA. This value was not determined for individual ECs because of their small dimensions (6–8 micrometers) and tight fit; they were cut as a layer.\u003c/p\u003e\u003cp\u003eWe calculated tissue volume by multiplying the dissected total area by the slice thickness (25 µm), then tissue mass was estimated with assumption of brain tissue density as 1 g/cm³ (Barber et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1970\u003c/span\u003e). The estimated wet mass of sampled tissue was: 6.11 ± 1.45 ng for SOL MNs, 8.48 ± 1.95 ng for TA MNs, and 22.27 ± 9.59 ng for EC (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e ).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eParameters of microdissected samples\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eAveraged parameters of microdissected samples per animal (± SD)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003enumber of cells/fragments\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003emean area of cell [µm\u003csup\u003e2\u003c/sup\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003etotal dissected area [mm\u003csup\u003e2\u003c/sup\u003e]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003etissue mass* [ng]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSOL MNs\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e172 ± 39\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e1428 ± 101\u003c/b\u003e\u003c/p\u003e\u003cp\u003e(Control: 1499 ± 51,\u003c/p\u003e\u003cp\u003eSp2W: 1376 ± 137, Sp6W: 1377 ± 74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.24 ± 0,058\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e6.11 ± 1.45\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTA MNs\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e262 ± 74\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e1341 ± 220\u003c/b\u003e\u003c/p\u003e\u003cp\u003e(Control: 1468 ± 243,\u003c/p\u003e\u003cp\u003eSp2W: 1143 ± 77, Sp6W: 1331 ± 133)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.34 ± 0.078\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e8.48 ± 1.95\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEC layer\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e30 ± 18\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.89 ± 0.038\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e22.27 ± 9.59\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*estimated\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003eData quality and reproducibility\u003c/h2\u003e\u003cp\u003ePrincipal component analysis (PCA) was performed to assess the consistency and separation of proteomic profiles across 6 data sets (for each sample type) and 3 experimental groups (control, Sp2W, Sp6W). In motoneurons, the first two components explained 36.0% (PC1) and 19.2% (PC2) of the total variance for SOL MNs, and 51.7% (PC1) and 13.5% (PC2) for TA MNs, demonstrating good within-group homogeneity and clear distinction between subtypes. In ependymal cells (EC), PCA captured 60.3% (PC1) and 11.4% (PC2) of the variance, indicating highly consistent expression patterns and a strong injury-associated signature. In dorsal root ganglia (DRG), variance explained by PC1 and PC2 ranged from 38.1% / 23.5% (L3) and 39.6% / 32.3% (L4) to 60.3% / 23.8% (L5), reflecting robust reproducibility and distinct segmental differentiation. Overall, PCA confirmed high biological consistency within each sample type and separation between experimental conditions.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePCA analysis of 6 datasets from 3 experimental groups of Control, SP2W and SP6W rats\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePC1 variance %\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePC2 variance %\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInterpretation\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSOL MNs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate variance capture; samples show good internal consistency and distinct but partly overlapping proteomic profiles across groups. Indicates heterogeneous responses after SCT.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTA MNs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e51.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHigh variance capture; clear separation between experimental groups and strong internal homogeneity.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEpendymal cells (EC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHigh explained variance; consistent proteomic profiles and pronounced injury-related clustering. Indicates a highly coherent and time-dependent response after SCT.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDRG L3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate variance explained; stable grouping and reliable biological reproducibility.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDRG L4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39.6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHigh cumulative variance (≈ 72%); distinct and homogeneous injury-related pattern.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDRG L5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLarge variance captured, nearly complete separation between experimental groups, indicating pronounced injury-related molecular shifts.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn the DRG (L3–L5) datasets, two outliers were observed in each segment, including one recurring outlier from animal Hb14 (control group). Technical notes indicate digestion issues for these samples during digestion (including unintended prolonged exposure to room temperature), which may have contributed to their higher variability. Please note that this sample was not removed from the dataset, as it still met the inclusion criteria and retained sufficient data quality for downstream analysis.\u003c/p\u003e\u003ch2\u003eBiological validation of MNs and EC identity\u003c/h2\u003e\u003ch2\u003eValidation of Cell-Type Identity\u003c/h2\u003e\u003cp\u003eProteomic profiles confirmed the expected molecular identities of both motoneuron (MN) and ependymal cell (EC) isolates, validating the accuracy of laser microdissection and sample preparation.\u003c/p\u003e\u003cp\u003eIn MN samples, detection of neuronal and motoneuron-enriched proteins such as: Cytoskeletal and axonal transport proteins: \u003cem\u003eTubb3, Tuba1a, Nefh, Nefm, Nefl, Kif5a, Dync1h1, Map1b, Ank2;\u003c/em\u003e Synaptic vesicle and neurotransmission components: \u003cem\u003eSnap25, Syt2, Syn1, Syp, Vamp1, Stx1b, Rab3a, Cplx1;\u003c/em\u003e Neuron-specific RNA-binding proteins: \u003cem\u003eElavl3 (HuC), Rbfox3 (NeuN), Nova1.\u003c/em\u003e These neuronal markers confirm the integrity of the motoneuron proteome and validate successful retrograde labeling and laser microdissection.\u003c/p\u003e\u003cp\u003eIn EC isolates, proteomic signatures were consistent with the epithelial phenotype of the spinal central canal lining. Strong expression of junctional and desmosomal proteins—\u003cem\u003ejup\u003c/em\u003e, \u003cem\u003edsp\u003c/em\u003e, \u003cem\u003edsg1\u003c/em\u003e, and \u003cem\u003ectnna1\u003c/em\u003e—confirmed preserved cell-cell adhesion complexes typical of the ependymal barrier. The detection of \u003cem\u003esparcl1\u003c/em\u003e and \u003cem\u003edclk1\u003c/em\u003e supported an ependymal and radial-glia-like identity, while mitochondrial proteins (\u003cem\u003etomm34\u003c/em\u003e, \u003cem\u003etimm44\u003c/em\u003e, \u003cem\u003endufa12\u003c/em\u003e) reflected the high metabolic activity characteristic of this epithelium. The presence of \u003cem\u003es100a13\u003c/em\u003e and \u003cem\u003ero60\u003c/em\u003e, associated with epithelial stress and remodeling, aligned with post-injury activation of the central canal region.\u003c/p\u003e\u003ch2\u003eLimitations and cellular overlap\u003c/h2\u003e\u003cp\u003eAlthough the motoneuron (MN) proteomes show a strong neuronal signature, several canonical cholinergic markers expected in MNs — including \u003cem\u003echat\u003c/em\u003e (choline acetyltransferase) and \u003cem\u003eslc18a3\u003c/em\u003e (vesicular acetylcholine transporter, VAChT) — were not detected. This likely reflects the low abundance of these proteins in microdissected cell bodies, as these proteins are mostly accumulated in the axonal compartment and therefore are underrepresented in LC-MS/MS datasets. Likewise, muscarinic receptors (\u003cem\u003echrm2\u003c/em\u003e, \u003cem\u003echrm4\u003c/em\u003e) were absent, consistent with poor recovery of GPCRs in standard proteomic workflows. Low-level detection of astrocytic proteins such as \u003cem\u003egfap\u003c/em\u003e and \u003cem\u003ealdh1l1\u003c/em\u003e likely results from perisomatic glial processes that are difficult to exclude during microdissection. Overall, MN datasets are neuronally dominated and biologically consistent, though membrane receptor coverage and minor glial signals remain inherent technical limitations.\u003c/p\u003e\u003cp\u003eAlthough EC proteomes showed strong epithelial and junctional signatures, several classical ependymal and ciliary markers (e.g., \u003cem\u003efoxj1, dnaic1\u003c/em\u003e) were not detected. Low-level detection of glial and extracellular matrix proteins probably reflects partial inclusion of periependymal tissue during microdissection.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data deposited online (PXD070428, accessed with credentials provided in the letter to the editor) was supplied as raw LC-MS/MS files and result files from MaxQuant. The raw files can be used for additional searches (e.g. with different parameters, different software). The results of MaxQuant searches can be further processed (filtered, normalized, analyzed statistically, visualized, etc.). Alternatively, tables with processed data and comparisons between sample groups, were deposited at RepOD (Open Data Repository) and can be accessed via the following link: https://repod.icm.edu.pl/privateurl.xhtml?token=3657bdbb-26ea-43db-9660-7ec3a8ea0e85.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode Availability \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo custom code has been used.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOGW and MS conceived and designed the study. Experimental methodology, including sample preparation and optimization of the proteomic workflow, was developed by OGW and RS. Data acquisition, processing, and analysis were performed by OGW, RS, TW and KR. RS curated the proteomic data and prepared the repository submission. Figures and visualizations were generated by OGW and AP. OGW drafted the manuscript, and all authors contributed to its review and editing. Funding was provided by OGW and MS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure of Conflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone of the authors has any conflict of interest to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work received support from the Polish National Science Center grants 2022/06/X/NZ3/01783 (OGW) and 2018/31/B/NZ4/02789 (MS). \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBarber, T. W., Brockway, J. A., \u0026amp; Higgins, L. S. (1970). The density of tissues in and about the head. \u003cem\u003eActa Neurologica Scandinavica\u003c/em\u003e, \u003cem\u003e46\u003c/em\u003e(1), 85\u0026ndash;92. https://doi.org/10.1111/j.1600-0404.1970.tb05606.x \u003c/li\u003e\n\u003cli\u003eChopek, J. W., Sheppard, P. C., Gardiner, K., \u0026amp; Gardiner, P. F. (2015). 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Overexpression of BDNF increases excitability of the lumbar spinal network and leads to robust early locomotor recovery in completely spinalized rats. \u003cem\u003ePLoS One\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(2), Article 2. https://doi.org/10.1371/journal.pone.0088833 \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"0ecc0482-7e8c-4a14-9298-287940550707","identifier":"10.13039/501100004281","name":"Narodowe Centrum Nauki","awardNumber":"2022/06/X/NZ3/01783","order_by":0},{"identity":"6528b387-615c-4d9b-a5fd-b878ea5c6b66","identifier":"10.13039/501100004281","name":"Narodowe Centrum Nauki","awardNumber":"2018/31/B/NZ4/02789","order_by":1}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Instytut Biologii Doświadczalnej im. Marcelego Nenckiego","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Spinal cord injury, Laser microdissection, TMT-based proteomics, Motorneurons, Dorsal root ganglia","lastPublishedDoi":"10.21203/rs.3.rs-8134246/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8134246/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSpinal cord injury induces profound molecular changes in surrounding tissue. Deciphering these changes with cell type-specific resolution shall facilitate discovery of new molecular targets that promote recovery. Here, we performed a proteomic analysis of laser-dissected motor neurons (MN) and ependymal cells (EC), dorsal root ganglia (DRG) obtained from adult control and spinal rats, 2 or 6 weeks after spinal cord transection at Th9. We traced with fluorescent cholera toxin and microdissected on average 172+/-39 MNs innervating soleus (SOL) muscle and 262+/-74 MNs innervating tibialis anterior (TA) muscle per animal. In parallel, we microdissected the EC layer that surrounds the central canal and the L3-6 spinal cord (the same levels as isolated MNs). We isolated the DRG bilaterally from L3, L4, L5 segments. Mass spectrometry analysis of the samples from 5 animals per group, allowed us to detect 1221 proteins in SOL MNs, 1186 in TA MNs, 1520 in EC layer and 5087, 3740 and 3086 in DRG L3, L4 and L5, respectively. Here we describe how this data was obtained and made available for further use. Our data may help to identify and characterize molecular mechanisms involved in early and late subacute period after spinalization in the rat spinal MNs, DRG and ECs.\u003c/p\u003e\n\u003cp\u003eDesign Type(s) parallel group design • injury \u0026nbsp;\u0026nbsp;design • disease process modeling objective\u003c/p\u003e\n\u003cp\u003eMeasurement Type protein expression profiling\u003c/p\u003e\n\u003cp\u003eTechnology Type laser capture microdissection • \u0026nbsp;\u0026nbsp;mass spectrometry assay • computer analysis with MaxQuant software\u003c/p\u003e\n\u003cp\u003eFactor Type Procedure\u003c/p\u003e\n\u003cp\u003eSample Characteristic (s) Rattus norvegicus • lumbar \u0026nbsp;\u0026nbsp;motoneurons • DRG • ependymal cells of central canal\u003c/p\u003e","manuscriptTitle":"Proteomic profile of Laser-dissected Motoneurons and Ependymal Cell Layer and of Dorsal Root Ganglia after Spinal Cord Injury in Rat","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-18 18:54:07","doi":"10.21203/rs.3.rs-8134246/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"af17700b-0f67-468b-b259-3e97611943cb","owner":[],"postedDate":"November 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":58104747,"name":"Cellular \u0026 Molecular Neuroscience"}],"tags":[],"updatedAt":"2025-11-18T18:54:07+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-18 18:54:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8134246","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8134246","identity":"rs-8134246","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}