Impacts of hnRNP A1 Splicing Inhibition on the Brain Remyelination Proteome

ABSTRACT

Oligodendrocytes, the myelinating cells in the central nervous system, are implicated in several neurological disorders marked by dysfunctional RNA–binding proteins (RBPs). The present study aimed at investigating the role of hnRNP A1 in the proteome of the corpus callosum, prefrontal cortex, and hippocampus of a murine cuprizone–induced demyelination model. Right after the cuprizone insult, we administered an hnRNP A1 splicing activity inhibitor and analyzed its impact on brain remyelination by nanoESI‐LC‐MS/MS label‐free proteomic analysis to assess the biological processes affected in these brain regions. Significant alterations in essential myelination proteins highlighted the involvement of hnRNP A1 in maintaining myelin integrity. Pathways related to sphingolipid and endocannabinoid signaling were affected, as well as the synaptic vesicle cycle and GABAergic synapses. Although behavioral impairments were not observed, molecular changes suggest potential links to memory, synaptic function, and neurotransmission processes. These findings enhance our understanding of the multifaceted roles of hnRNP A1 in the central nervous system, providing valuable insights for future investigations and therapeutic interventions in neurodegenerative and demyelinating diseases.

This study highlights the effects of hnRNP A1 on myelin proteins in the prefrontal cortex, corpus callosum, and hippocampus of adult mice following cuprizone‐induced demyelination and subsequent hnRNP A1 splicing inhibition (VPC‐8001) during remyelination. VPC‐8001 exposure induced significant changes in myelination proteins such as MOG, MAG, MBP, CNP, and PLP, underscoring the role of hnRNP A1 in myelin composition. Additionally, sphingolipid metabolism (ASAH1 and FYN), endocannabinoid signaling (FAAH), synaptic vesicle cycle (DNM1, DNM2, and DNM3), and GABAergic synapses (GAD1 and GAD2) were found to be dysregulated in proteomic data. ASAH1, acid ceramidase; CNP, 2′,3′‐cyclic nucleotide 3′‐phosphodiesterase; DNM1, dynamin 1; DNM2, dynamin 2; DNM3, dynamin 3; FAAH, fatty acid amide hydrolase; Fyn, tyrosine‐protein kinase fyn; GAD1, glutamate decarboxylase 1; GAD2, glutamate decarboxylase 2; MAG, myelin‐associated glycoprotein; MBP, myelin basic protein; MOG, myelin oligodendrocyte protein; PLP, proteolipid protein.

Abbreviations

ACDase

acid ceramidase

ACTB

β‐actin

AMPAR

α‐amino‐3‐hydroxy‐5‐methyl‐4‐isoxazolepropionic acid receptor

ANOVA

analysis of variance

BGT‐1

betaine/GABA transporter

BSA

bovine serum albumin

cAMP

cyclic adenosine monophosphate

CC

corpus callosum

cDNA

complementary deoxyribonucleic acid

CEUA

Ethics Committee for Animal Use

cGMP

cyclic guanosine monophosphate

Cnp

2′,3′‐cyclic‐nucleotide 3′‐phosphodiesterase

CNS

central nervous system

CTL

control

CUP

cuprizone

DIA

data‐independent acquisition

DMSO

dimethyl sulfoxide

EAE

experimental autoimmune encephalomyelitis

EDTA

ethylenediaminetetraacetic acid

EMRT

exact mass retention time

FA

formic acid

FAAH

fatty acid amide hydrolase

FASP

filter‐aided sample preparation

FDR

false discovery rate

FYN

tyrosine‐protein kinase Fyn

GABAergic

gamma‐aminobutyric acid

GAD65

glutamate decarboxylase 2

GAD67

glutamate decarboxylase 1

hnRNP A1

heterogeneous nuclear ribonucleoprotein A1

hnRNP A/B

heterogeneous nuclear ribonucleoprotein A/B

hnRNP E1

heterogeneous nuclear ribonucleoprotein E1

hnRNP K

heterogeneous nuclear ribonucleoprotein K

HPC

hippocampus

ICC‐IF

immunofluorescence

INFABIC

National Institute of Science and Technology on Photonics Applied to Cell Biology

KEGG

Kyoto Encyclopedia of Genes and Genomes

LC‐MS/MS

liquid chromatography‐mass spectrometry

LFB

Luxol fast blue

MAG

myelin‐associated glycoprotein

MAPK13

mitogen‐activated protein kinase 13

MBP

myelin basic protein

MOG

myelin oligodendrocyte protein

mRNA

messenger ribonucleic acid

NaCl

sodium chloride

nanoESI‐LC‐MS/MS

nano liquid chromatography‐electrospray ionization‐tandem mass spectrometry

NMDA

N‐methyl‐d‐aspartate

NOR

novel object recognition

OFT

open‐field test

OLs

oligodendrocytes

PB

phosphate buffer

PBS

phosphate‐buffered saline

PCA

principal component analysis

PFA

paraformaldehyde

PFC

prefrontal cortex

PKC

protein kinase C gamma type

PKG

protein kinase G

PLP

proteolipid protein

qRT‐PCR

real‐time quantitative reverse transcription‐polymerase chain reaction

RBPs

RNA–binding proteins

RNA

ribonucleic acid

SEM

standard error of the mean

snRNAs

small nuclear RNAs

SR‐family proteins

serine/arginine‐rich proteins

Tris–HCl

Tris hydrochloride

U2

U2 small nuclear ribonucleoprotein complex

UPLC

ultra performance liquid chromatography

VPC

VPC‐80051

1. Introduction

Oligodendrocytes (OLs), the myelinating cells in the central nervous system (CNS), play a vital role in myelin formation during CNS development and are crucial for myelin regeneration after injury (Nave 2010). Damage to and the loss of OLs are critical features observed in diverse disease phenotypes, ranging from developmental disorders like schizophrenia to degenerative conditions such as Alzheimer's disease and multiple sclerosis (Hof et al. 2002; Yeung et al. 2019; Depp et al. 2023; Marlinge, Bellivier, and Houenou 2014). A commonality among all these disorders is the presence of dysfunctional RNA–binding proteins (RBPs) contributing to their pathogenesis. The pathology of dysfunctional RBPs, including mislocalization and altered expression, is also characteristic of other neurological diseases, including amyotrophic lateral sclerosis and frontotemporal lobar degeneration (Bampton et al. 2021). Although the role of dysfunctional RBP pathology and its impact on cellular function in various neurological disorders has been extensively characterized, our understanding of how RBP dysfunction specifically influences myelination is still in its early stages.

The heterogeneous ribonucleoprotein (hnRNPs) family plays roles in various critical functions within OLs, encompassing crucial aspects such as OL proliferation, differentiation, morphology, and viability. Additionally, hnRNPs play a crucial role in regulating the expression of essential proteins for these cells, such as proteolipid protein (PLP) and myelin basic protein (MBP), as reviewed by Brandão‐Teles et al. (2024). For instance, specific variants within the hnRNP A/B family have demonstrated indispensability in the cytoplasmic transportation of Mbp mRNA (Hatfield, Rothnagel, and Smith 2002). Furthermore, both hnRNP K and hnRNP E1 have exhibited active participation in regulating MBP expression (Torvund‐Jensen et al. 2014). Recently, dysfunction of hnRNP A1 in OLs was shown to be a characteristic feature in conditions like multiple sclerosis and experimental autoimmune encephalomyelitis (EAE), which correlates with the concomitant loss of OLs and myelin (Jahanbazi Jahan‐Abad et al. 2023). Additionally, hnRNP A1 has been implicated in the intricate regulation of alternative splicing of myelin‐associated glycoprotein (MAG) (Zearfoss et al. 2011).

Splicing in complex organisms achieves accuracy by minimizing the misuse of non‐authentic splice sites, ensuring the production of functional proteins. Simultaneously, it maintains flexibility, generating diverse protein variants from the pre‐mRNA of a single gene. The spliceosome, guided by small nuclear RNAs (snRNAs) and proteins, relies on splice sites with diverse sequences and limited evolutionary conservation (Wahl, Will, and Lührmann 2009). In this context, hnRNP A1 plays a crucial role in splicing mechanisms through direct RNA binding and interactions with other RBPs. Along with other hnRNPs, hnRNP A1 is involved in constitutive and alternative splicing throughout the splicing cycle, collaborating with U2‐associated and SR‐family proteins to significantly impact cellular processes and contribute to disease pathways, making it a noteworthy component in this context (Bekenstein and Soreq 2013).

In this study, we investigated the impact of the inhibition of hnRNP A1 splicing activity on the proteomes of the corpus callosum (CC), prefrontal cortex (PFC), and hippocampus (HPC) in adult male C57BL/6 mice. To achieve this, we induced demyelination by exposing the mice to cuprizone (CUP, bis‐cyclohexanone oxaldihydrazone) (0.2%) in powdered chow for 5 weeks, followed by the administration of VPC‐80051 (VPC), an inhibitor of hnRNP A1 splicing activity (Carabet et al. 2019), during the subsequent 5‐week remyelination period with standard chow. We employed nanoESI‐LC‐MS/MS label‐free proteomics to assess the proteomes of the three brain regions. Second, we assessed long‐term VPC treatment to determine outcomes on behavior and myelin itself. The CC, the main white matter structure in the brain, is responsible for connecting the left and right cerebral hemispheres, allowing communication between them (Paul et al. 2007). The PFC plays a crucial role in higher brain functions, such as cognition, motivation, reward, and emotion (Fuster 2009). Dysfunction in this area has been linked to various neuropsychiatric disorders (Schubert, Martens, and Kolk 2015; Parenti et al. 2020). Finally, the HPC, extensively studied in rodents, is a robust circuit model for understanding memory formation and spatial navigation (Fumagalli and Priori 2012). Hippocampal circuits exhibit a remarkable capacity to process multisensory information streams and collectively encode them into long‐term memories (MacDonald, Jackson, and Beazely 2006). The dysregulated proteins and pathways in the CC, PFC, and HPC found in this study shed light on myelination‐associated alterations resulting from the inhibition of hnRNP A1 splicing activity.

2. Methods

2.1. Reagents

CUP (Sigma‐Aldrich, cat# C9012‐25G) was mixed with powdered feed at a final concentration of 0.2%. VPC was commercially acquired from ProbeChem (cat# PC‐36117) and diluted in dimethyl sulfoxide (DMSO, Sigma‐Aldrich, cat# D8418).

2.2. Animals

Adult male C57BL/6 (C57BL/6JUnib_RRID:MGI:2159769) mice (8 weeks old), were obtained from CEMIB, Unicamp (Campinas, São Paulo, Brazil). All animals were kept in polyethylene cages suitable for mice and accommodated on ventilated racks with controlled temperature (22°C ± 2°C) and humidity (55% ± 5%), and a photoperiod system of 12 h light/dark with access to water and food ad libitum. The animals were randomly assigned (by a single researcher) and housed in propylene cages, with 3–4 animals per cage. All experimental procedures were done during the light phase of the cycle, specifically between 7 a.m. and 5 p.m. The animals were allocated to control (CTL) and CUP groups through simple randomization and assigned an ID number in Excel for behavioral experiment blinding. This phase represented the demyelination period. After 5 weeks of the demyelination phase, the CTL and CUP groups were further subdivided into vehicle and VPC subgroups using a second round of simple, blinded randomization. We started with 26 animals in the CUP group and 24 animals in the CTL group. After characterizing the model, we categorized the animals into different treatments: CUP, CTL, CUP + VPC, and CTL + VPC (VPC). Following all treatments and behavior tests, we divided the animals for proteomics and RT‐PCR, with the number of animals indicated in each figure. All procedures performed were conducted following Brazilian Federal Law (no. 11 794; 10/08/2008) and international guidelines for the care of animals used in scientific research. The Ethics Committee for Animal Use (CEUA) approved all procedures conducted under protocols CEUA 5744‐1/2021 and 5744‐1(A)/2022.

2.3. Demyelination Model

Demyelination was modeled by feeding mice with 0.2% w/w CUP in powdered chow for 5 weeks. Remyelination was modeled by 5 weeks of CUP feeding, followed by 5 weeks of recovery with standard chow. Food was monitored and changed daily. Age‐matched untreated CTLs were fed powdered chow without CUP for the full 10‐week period. Body weight was evaluated every 2 days. Exposure to CUP led to a reduction in body weight in both the CUP and CUP_VPC groups compared to the CTL group, observed 16 days after exposure (interaction effect time × treatment: p < 0.0001, F(51, 493) = 11.82; time factor: p < 0.0001, F(4,848, 140,6) = 191.3; and treatment factor: p = 0.0121; F(3, 29) = 4.34). During the subsequent remyelination process, mice in the CUP group exhibited weight regain compared to the CTL group starting at Day 40. The CUP_VPC group showed weight regain starting at Day 44 (Figure S1).

2.4. Animal Treatment

VPC was solubilized in DMSO and further diluted with a 0.1% Tween‐80 (Sigma‐Aldrich, cat# P1754) solution in saline (v/v; NaCl 0.9%) and administered intraperitoneally (i.p.) at a dose of 3 mg/kg body weight. The animals were assigned to the following groups (Figure 2A): (1) CTL group (CTL), animals fed a normal diet (5 W) and treated with vehicle solution (5 W); (2) VPC group, animals fed a normal diet (5 W) and treated with VPC (5 W); (3) CUP group, animals fed a CUP diet (5 W) and treated with vehicle solution (5 W); and (4) CUP + VPC group, animals fed a CUP diet (5 W) and treated with VPC (5 W). The groups administered with the vehicle were given the same volume as those treated with VPC. The compounds were injected i.p. at a standardized volume of 10 mL/kg.

FIGURE 2.

(A) Schematic representation of the experimental design for cuprizone and VPC‐80051 treatment. (B) Effects of cuprizone and VPC‐80051 exposure on mice locomotion (open‐field test) and memory (novel object recognition test). After 10 weeks (demyelination period + remyelination phase), no significant difference was seen due to VPC‐80051 exposure for (a) distance moved or (c) time spent in the center. Two‐way ANOVA identified impacts on (b) time spent in the periphery (p = 0.0397; F(1,30) = 4.623), (d) mobility (p = 0.0182; F(1,30) = 6.244), and (e) immobility below 0.5% (p = 0.0162; F(1,30) = 6.491). Two‐way ANOVA also indicated that cuprizone affected (f) velocity (p = 0.0383; F(1,30) = 4.694); (d) mobility (p = 0.0046; F(1,30) = 9.383); and (e) immobility below 0.5% (p = 0.0076; F(1,30) = 8.202). After applying Tukey's multiple comparison test, differences between VPC and CUP + VPC were observed for (f) velocity (p = 0.0114) and (e) immobility below 5% (p = 0.0143). Regarding the novel object recognition test, no significant differences were observed between the groups after the 5‐week remyelination period, regardless of the presence or absence of the inhibitor VPC‐80051 (h, j). Data represent the mean ± SEM (n = 6–8). Shapiro–Wilk and Kolmogorov–Smirnov normality tests were applied to ensure that the data met the criteria for performing parametric tests. Once the criteria were accepted, the results were expressed as a mean ± 95% CI.

2.5. Behavioral Tests

2.5.1. Open‐Field Test (OFT)

The OFT session was video recorded using a Sony Action Cam 4K for analysis with Ethovision software. Animals were placed in the center of an open‐field apparatus with a square wooden arena (30 × 30 cm) in an isolated room and illuminated with an incandescent lamp (60 lx at the arena floor level). The distance moved was evaluated for 15 min once the animal was placed in the center of the apparatus; the time the animal stayed in the center and the peripheral parts of the square were also calculated, as delimited with the software used. The mobility (%) and immobility below 0.5% were also evaluated. The software defines the immobility parameter as the calculation of the duration during which the entire area of the animal between two image frames remains under the threshold, regardless of the center point of the image of the animal. After each session, the open field was cleaned with a 10% ethanol solution in water. The tests were performed after the initial 5‐week exposure period and repeated after the remyelination period (10th week).

2.5.2. Novel Object Recognition (NOR)

The NOR test relies predominantly on a rodent's inherent exploratory behavior, devoid of externally applied rules or reinforcement. The open‐field arena was used for the test. Before testing, each animal underwent a 15‐min familiarization period with the field (OFT). After a 24‐h interval, the animal was placed at the center of the open‐field arena and allowed to explore two identical objects (A) freely for 10 min. The objects, indistinguishable in shape and volume, remained stationary and could not be displaced by the animal.

Short‐term memory assessment occurred 1 h after exposure to the identical objects (A). During this phase, the animal encountered one of the training objects (A) alongside a new object of a different shape (B). The animal was then allowed to explore the new object, the familiar object, and the environment for 5 min to evaluate cognition. The evaluation of long‐term memory took place 24‐h after the short‐term memory test. At this stage, the animal encountered one of the training objects (A) and another new object with a different shape (C).

Between tests, both the arena and the objects underwent cleaning with 10% alcohol in water to eliminate potential olfactory cues. The time spent exploring the objects was assessed over 5 min, defined as the time the animal spent sniffing, licking, or touching the object with its snout or forepaws, or when the animal turned its snout to the object at a distance of less than or equal to 1 cm (Leger et al. 2013). The recognition index was determined by measuring the time spent exploring object B (first phase) or C (second phase) divided by the total time spent exploring the objects (A + B or A + C). All objects used were of the same size and volume, with similar textures and complementary colors, but differed in shape. All sessions were recorded on video. The behavioral tests were conducted by an experimenter blind to CUP and treatment conditions.

2.6. Brain Tissue Collection

Animals were anesthetized with ketamine (100 mg/kg) and xylazine (25 mg/kg) i.p., followed by transcardiac perfusion with 30 mL of 0.1 M phosphate‐buffered saline (PBS). Brains were then rapidly extracted and placed on a brain slicer matrix. Brains were cut into 0.5–1.0 mm coronal sections using a brain matrix and arranged on a frozen glass plate. Landmarks within each section were referenced against the Allen Mouse Brain Atlas or Paxinos and Franklin's The Mouse Brain in Stereotaxic Coordinates (Paxinos and Franklin 2007). The PFC, CC, and HPC were dissected using a cold scalpel following the coordinates described by Paxinos and Franklin (2007), rapidly frozen in liquid nitrogen, and stored at −80°C until mRNA and protein were extracted (Wager‐Miller et al. 2020).

2.7. Immunofluorescence (ICC‐IF)

Anesthetized and perfused animals, as described above, were then fixed with a solution composed of 4% paraformaldehyde dissolved in 0.1 M phosphate buffer (PB, pH 7.4). Subsequently, the brains were collected and immersed in 4% paraformaldehyde for 24 h. Afterward, the brain samples were transferred to a cryoprotectant solution of 30% sucrose in 0.01 M PB. After 4 days, the brain samples were frozen in isopentane for 60 s and stored in a biofreezer at −80°C. Brain samples were sectioned to a thickness of 30 μm using a freezing sliding microtome. The histological sections were arranged in culture plates in a storage buffer solution (0.1 M PBS with 0.05% azide) and maintained at 4°C.

For the ICC‐IF assay, sections were rinsed with 0.1 M PBS (Gibco, cat# 70013‐032) three times for 10 min each and then incubated in a blocking solution (PBS containing 1% Triton X‐100 and 30% BSA [Sigma‐Aldrich, cat# A7906]) for 1 h. Subsequently, sections were exposed to the primary anti‐MBP antibody (1:1000, Cell Signaling Technology, cat# 788965) in blocking solution for 14–18 h at 4°C. After three 10‐min washes with PBS at room temperature, sections were incubated for 2h with a secondary antibody (Alexa Fluor 488, 1:500, Cell Signaling Technology, cat# 4412) in blocking solution. Following three 10‐min washes with 0.1 M PBS to remove excess reagent, sections were mounted on gelatinized glass slides and covered with coverslips, utilizing Permount mounting medium (Sigma, cat#C0612). Samples were examined in the National Institute of Science and Technology in Photonics Applied to Cell Biology (INFABIC) at the University of Campinas, using a Zeiss LSM 780‐NLO confocal laser on an Axio Observer Z.1 microscope (Carl Zeiss AG, Germany) with a ×10 objective.

2.8. Luxol Fast Blue (LFB)

The lipoproteins of myelin sheaths were stained using LFB (Sigma‐Aldrich, cat# L0294) to observe demyelination and remyelination after CUP exposure. Cryosections were placed on a coverslip and allowed to dry overnight. The samples were then dehydrated using a series of ethanol concentrations including 70%, 80%, and 96% for 20 s each. Afterward, the tissue sections were incubated in a 0.1% LFB solution on a hotplate set to 58°C for 4 h. Each section was washed and differentiated individually. The washing steps were performed consecutively in 96% alcohol for 2–3 s and Milli‐Q water for 3 s. Then, the differentiation steps were carefully carried out in 0.05% lithium carbonate and 70% ethanol for 5–7 s until the cortical gray matter was decolored, whereas the white matter remained blue. LFB staining was checked microscopically to ensure the homogeneity of the staining. The differentiation steps were repeated if needed. Afterward, the sections were rinsed with Milli‐Q water. Nissl bodies in neurons were stained by incubation in a cresyl violet stain solution (0.1%) for 10 min. Finally, the samples were dehydrated with 96% ethanol for 3–5 min, 100% ethanol for 2 × 5 min, and xylene for 3 × 5 min. The sections were then mounted with Fluoromount and a coverslip.

2.9. RNA Isolation and qRT‐PCR

The day following behavioral testing, the mice were euthanized, and total RNA was extracted from the brain tissues using TRIzol (Invitrogen, cat# 5596026) according to the manufacturer's instructions. Total RNA was quantified using a DeNovix spectrophotometer. To generate cDNA, 500 ng of RNA was reverse transcribed using the Promega reverse transcription kit (cat# A5003). For each 10 μL of the qPCR reaction, 1 μL of cDNA diluted 1:10 was mixed with 200 nM of the primers listed in Table 1 (Exxtend, Campinas, São Paulo, SP, BRA), 5 μL of Evagreen master mix (Cellco, cat# PCK‐100XL), and nuclease‐free water. The expression of mRNA was carried out by quantitative real‐time PCR. The reactions were carried out on a CFX 384 Touch Real‐Time PCR Detection System (Bio‐Rad). The PCR product dissociation curves were executed as follows: initial heating of the samples at 50°C for 2 min and 95°C for 10 min; 40 cycles were performed at 95°C for 15 s and 60°C for 1 min. To assess the specificity of the primers, the samples were heated from 65°C to 99°C (increase of 1°C every 5 s). The data were normalized using the expression of the housekeeping genes Actb (β‐actin; 100 nM) and Rn18s (18S rRNA; 50 nM). The relative quantification value for each target gene was analyzed using a comparative CT method (Livak and Schmittgen 2001; Schmittgen and Livak 2008; Vandesompele et al. 2002). The primer sequences used are detailed in Table 1. The efficiency of all the primers used ranged from 95% to 120%.

TABLE 1.

List of primers used in this study.

GENE	Forward primer (5′−3′)	Reverse primer (5′−3′)
Actb	CCAGCCTTCCTTCTTGGGTAT	CATAGAGGTCTTTACGGATGTCAAC
Cnp	AGAGTGATCCTTGGAGCCAGA	CGGAGGGGAATGGTGGATTT
Mbp	GTGACACCTCGTACACCCCCTCCAT	GCTAAATCTGCTGAGGGACAGGCCT
Plp	TCAGTCTATTGCCTTCCCTAGC	AGCATTCCATGGGAGAACAC
18S	CCCAACTTCTTAGAGGGACAAG	CATCTAAGGGCATCACAGACC

2.10. Protein Digestion and LC‐MS/MS Analysis

Brains were extracted after 10 weeks, and the CC, CPF, and HPC were isolated. The tissues were homogenized in lysis buffer (100 mM Tris–HCl, 1 mM EDTA, 150 nM NaCl, 0.5% Triton X‐100, and protease inhibitor cocktail; Roche, cat# 05 892 791 001) and mechanically lysed by maceration with a pestle and ultrasonication for 30 s, performed twice. The total protein extract was quantified using the BCA method following the manufacturer's instructions (Thermo Scientific, cat# 23225). A total of 30 μg of protein extract from each sample was transferred to a Microcon‐10 Centrifugal Filter with a 10 kDa cut‐off for FASP–based digestion (Distler et al. 2016; Wiśniewski et al. 2009). After tryptic digestion, the peptides were dried and stored at −20°C before being resuspended in 0.1% formic acid (FA) and subsequently subjected to LC‐MS/MS analysis. Using a Waters M‐Class UPLC system, 1 μg of each digested sample was loaded onto a trapping column (M‐Class Symmetry C18 Trap Column, 100 Å, 5 μm, 180 μm × 20 mm; Waters Corp.) and subsequently separated by a 120‐min reverse‐phase chromatography at 300 nL/min using an HSS T3 C18 analytical column (1.8 μm, 75 μm × 150 mm; Waters Corp.) maintained at 40°C. Peptides were separated over a 90‐min linear gradient from 3% to 40% Solvent B (acetonitrile + 0.1% FA, v/v) before spiking to 85% B for 10 min and re‐equilibrating with 97% Solvent A (H₂O + 0.1% FA, v/v). Eluted peptides were analyzed in a Synapt G2‐Si mass spectrometer (Waters Corp.), coupled online to the UPLC system, using positive‐mode electrospray ionization. Data were acquired by data‐independent acquisition (DIA) with ramping collision energy after separation by ion mobility (HDMS^E; LE: 2 eV; HE: 25–60 eV or 16–50 eV), in positive resolution mode, from 50 to 2000 m/z with a scan time of 1 s. Ion mobility separation was active with a wave velocity of 1000 m/s. Human (Glu1)‐fibrinopeptide B standard (Waters Corp.) was used as the lock mass through the dedicated lockspray system, sampled every 45 s for five scans, providing an automated, time‐aligned, corrected inventory of accurate mass measurements for both low and elevated energy. Technical duplicates were acquired for each biological triplicate.

2.11. Database Search and Protein Identification

Progenesis QI for Proteomics (Nonlinear Dynamics; Version 4.0.6x), incorporating Apex3D, Peptide 3D, and Ion Accounting, was employed to process, align, and normalize spectra before identification and label‐free quantification. Protein identification was performed by searching against the UniProt Mus musculus database (Swiss‐Prot; Taxonomy ID 10090; obtained 09/2022; 17 179 entries) with the following parameters for peptide identification: (1) trypsin digestion allowing up to one missed cleavage; (2) variable modification by oxidation (M) and fixed modification by carbamidomethyl (C); (3) false‐discovery rate (FDR) below 1%, calculated using a reverse sequence database generated on‐the‐fly; (4) a minimum of one fragment ion matched per peptide, a minimum of three fragment ions per protein, and a minimum of one unique peptide per protein; (5) a maximum protein mass of 600 kDa; and (6) mass error tolerances of 15 ppm for parent ions and 20 ppm for ion fragments. Relative quantitation was performed using all peptides for a given protein group. Differential expression of proteins was assessed by comparing CUP and CUP + VPC, employing an analysis of variance (ANOVA) with a significance threshold of p value < 0.05.

2.12. In Silico Systems Biology Analysis

The protein tables with normalized intensity values were exported by Progenesis QI for Proteomics and subjected to downstream analysis using OmicScope (Reis‐de‐Oliveira et al. 2024) with default parameters. Differentially regulated proteins (p value < 0.05) underwent enrichment analysis against the Biological Processes and Cellular Compartments Gene Ontology (GO) libraries. The target organism was mouse. Data generated by individual analyses in OmicScope were further integrated into the Nebula module. CPF, HPC, and CC files were collectively imported into Nebula, considering both protein and enrichment information levels.

2.13. Statistical Analysis

Statistical planning was performed using G Power software. For the evaluation of behavioral and molecular parameters, F‐tests were conducted using a one‐way ANOVA, with an effect size of 0.5, a significance level of p = 0.05, and a statistical power of 0.8. We conducted normality tests for all analyses except for proteomic data using the Shapiro–Wilk and Kolmogorov–Smirnov normality tests. After passing the normality tests, we used either unpaired Student's t‐test (two‐tailed) or one‐ or two‐way ANOVA. Statistical analyses of multiple groups were performed using one‐way ANOVA followed by Tukey's multiple comparison test or Brown–Forsythe ANOVA test followed by Dunnett's T3 multiple comparisons test, when appropriate. All data are presented as arithmetic means ± standard error of the mean (SEM) or standard deviation (SD). Significant effects are denoted by asterisks compared to CTL s (*p < 0.05, **p < 0.01, and ***p < 0.001) and are shown in the respective figures. No test for outliers was conducted. The complete statistical reports for all data sets are provided as Table S1.

3. Results

3.1. Characterization of Demyelination and Remyelination in the CUP‐Induced Model

To induce demyelination, 8‐week‐old male C57BL6/J mice were fed a standard rodent chow containing 0.2% CUP for 5 weeks, following established protocols. After removing the CUP from the diet, mice were given a 5‐week remyelination period (Figure 1A). To confirm demyelination after CUP exposure, we used LFB to stain myelin (Figure 1B), immunohistochemistry to label MBP (Figure 1C), and RT‐PCR to detect Mbp, Plp, and Cnp (Figure 1D). After 5 weeks of CUP exposure (demyelination group), LFB staining and immunohistochemistry for MBP indicated a reduction in myelin levels in the animals (Figure 1B,C). After the remyelination period, myelin levels were restored. Furthermore, Plp and Mbp mRNA levels were found to be decreased in the CC, PFC, and HPC following the CUP diet (Figure 1D, p < 0.05). Reductions in myelin levels were reversed after the remyelination phase. The results of body weight measurement during CUP treatment and the recovery phase are available in the Figure S1.

FIGURE 1.

(A) Schematic figure of the experimental design related to cuprizone model characterization. (B) Representative Luxol fast blue–crystal violet staining in the corpus callosum of the control and cuprizone‐treated groups. A notable reduction in myelin content was evident in the fifth week among cuprizone‐treated animals (demyelination) compared to the control group; a noticeable recovery was observed after the subsequent recovery phase (remyelination). (C) Representative immunofluorescence in the corpus callosum of the control and cuprizone‐treated groups during the fifth week of cuprizone treatment (demyelination) and the 10th week of the experiment, corresponding to the recovery phase (remyelination). (D) mRNA expression levels of Mbp, Plp, and Cnp were assessed in the corpus callosum, prefrontal cortex, and hippocampus of animals exposed to cuprizone for 5 weeks (demyelination), followed by a 5‐week recovery phase (remyelination). The mRNA expression levels of each gene were normalized with the endogenous controls Actb and 18S. Data are represented as mean ± SD, n = 3–6 animals per group. Statistical significance was determined by one‐way ANOVA followed by Tukey's post test, *p < 0.05, **p < 0.005, and ***p < 0.0005 compared to the control group. (E) Effects of cuprizone exposure on locomotion of mice as evaluated by the open‐field test (OFT) and on short‐ and long‐term memory as evaluated by the novel object recognition (NOR) behavioral test. In the OFT, there was no statistically significant difference between the groups after 5 weeks of cuprizone exposure in relation to: (a) distance moved; (b) periphery time; (c) time spent in the center; (d) mobility; and (e) immobile state below 0.5%. However, the demyelination group had a lower velocity parameter than the control group (f; p = 0.0085). Cognitive impairment was observed in animals treated with cuprizone (demyelination) compared to the vehicle group (control) after the demyelination process (h, j). The discrimination index was calculated by the time spent exploring the novel object/total exploring time. No differences were found in the overall interaction time. Data represent the mean ± SEM (n = 24–26). Statistical significance was determined by Student's t‐test, ****p < 0.0001 compared to the control group. Shapiro–Wilk and Kolmogorov–Smirnov normality tests were applied to ensure that the data met the criteria for performing parametric tests. Once the criteria were met, the results were expressed as a mean ± 95% confidence interval (CI).

Behavioral changes induced by CUP treatment were evaluated using the OFT. The OFT is primarily used to evaluate locomotor activity; however, it can also be employed to assess parameters related to anxiety and depression (Bronstein 1972; Wang et al. 2017). The present study focused on the locomotor parameters observed in the OFT to validate the alterations observed in the NOR test. After 5 weeks of CUP exposure, there was no statistically significant difference between the CTL group and CUP group (demyelination) for the measured parameters, as shown in Figure 1E: (a) distance moved; (b) periphery time; (c) time spent in the center; (d) mobility; and (e) immobile state below 0.5%. However, the demyelination group had a lower velocity parameter than the CTL (p = 0.0085; Figure 1E:f).

We also investigated whether demyelination impaired cognition through the NOR test, a behavioral analysis to assess memory. After 5 weeks of CUP exposure (demyelination period), while the animals exhibited no statistical difference in the object exploration total time in both short‐ and long‐term memory tests (Figure 1E:g,i), the demyelination group exhibited a significantly lower discrimination index compared to the CTL group (p < 0.0001), indicating cognitive impairments in both short‐ and long‐term memory (Figure 1E:h,j).

3.2. Impact of CUP and Inhibitor VPC on Locomotion and Cognitive Behavioral Parameters

To investigate the impact of hnRNP A1 splicing inhibition on behavioral and proteomic changes in the CC, PFC, and HPC of adult male C57BL/6 mice, we induced demyelination using a CUP diet (0.2% in powdered chow) for 5 weeks. Subsequently, CUP was removed from the diet, and animals received either VPC, an hnRNP A1 inhibitor, or a vehicle CTL. We divided animals into four groups (Figure 2A): (1) CTL (normal diet, vehicle), (2) VPC (normal diet, VPC), (3) CUP (CUP diet, vehicle), and (4) CUP + VPC (CUP diet, VPC). After 10 weeks (demyelination period + remyelination period), no statistically significant difference in (a) distance moved or (c) time spent in the center were observed as a result of VPC (Figure 2B). Two‐way ANOVA indicated differences in (b) time spent in the periphery (p = 0.0397; F(1,30) = 4.623), (d) mobility (p = 0.0182; F(1,30) = 6.244), and (e) immobility below 0.5% (p = 0.0162; F(1,30) = 6.491). Thus, our findings suggest that demyelination and subsequent inhibition of hnRNP A1 splicing activity may contribute to depressive‐like behaviors without impacting locomotor parameters. CUP was also observed to affect (f) velocity (p = 0.0383; F(1,30) = 4.694); (d) mobility (p = 0.0046; F(1,30) = 9.383); and (e) immobility below 0.5% (p = 0.0076; F(1,30) = 8.202). After applying Tukey's multiple comparison test, velocity (p = 0.0114) and immobility below 0.5% (p = 0.0143) were found to be different between the VPC and CUP + VPC groups.

Concerning cognitive behavior assessed through the NOR test, we observed that, after a 5‐week remyelination period, the animals recovered from the damage caused during the demyelination period (Figure 2B:h,j). Analysis of total time spent in object interaction revealed no statistically significant difference between the groups in the short‐ and long‐term memory tests (Figure 2B:g,i).

3.3. Shared Molecular Responses to Remyelination After CUP Exposure

To assess remyelination after CUP exposure, differences in proteomic profiles and associated biological processes and biochemical pathways were determined by comparing animals subjected to 5 weeks of CUP‐induced demyelination followed by 5 weeks of remyelination (CUP group) against those maintained on a standard chow diet without demyelination or remyelination (CTL group; Figure 2A). In the CC proteome, 2043 proteins were quantified, and among them, 309 displayed differential expression (p < 0.05). Similarly, in the PFC proteome, 2060 proteins were quantified, with 261 showing differential expression between the CUP‐receiving and CTL groups. Conversely, 1454 proteins were quantified in the HPC, with only four differentially expressed in response to CUP exposure, suggesting a nonsignificant dysregulation of biological processes in this brain region. A volcano plot was generated for each comparison to visualize protein distribution regarding expression levels in relation to their p value (Figure S2). Hierarchical cluster analysis of the brain regions, apart from the HPC, revealed that CUP impacted protein levels in such a way as to distinguish the CTL group from the CUP group, also corroborated by principal component analysis (PCA; Figures S3 and S4).

A total of 33 proteins were differentially regulated in both the CC and PFC. These include reticulon‐4, regulator of G‐protein signaling 7‐binding protein, galectin‐1, alpha‐crystallin B chain, calreticulin, aspartoacylase, and stearoyl‐CoA desaturase 2 (Figure 3A).

FIGURE 3.

Upset plot (A) illustrating the proteins identified as differentially expressed in the corpus callosum (CC) and prefrontal cortex (PFC) of animals exposed to cuprizone for 5 weeks followed by a remyelination period (CUP), compared to those not receiving cuprizone (CTL). The lower bar plot shows the number of entities associated with each group, while the upper bar plot displays the intersection size for each comparison. This is visually represented by colored and linked circles within the frame. (B) The cellular compartment analysis demonstrates the enrichment of various cellular compartments by differentially expressed proteins from CC and PFC. Circle size represents the number of proteins found in a specific cellular compartment, whereas colors indicate the enrichment‐adjusted p value. (C) The Circos plot visually represents differentially expressed myelin sheath proteins in the PFC and CC. Edge colors depict the log2 fold‐change, comparing animals exposed to cuprizone followed by remyelination (CUP) against those not receiving cuprizone (CTL).

The GO analysis for differentially regulated proteins provided insights into the overrepresentation of cellular compartments in the CC and PFC (Figure 3B). Despite the absence of similarities between the regions, some of the myelin‐related proteins, such as stearoyl‐CoA desaturase 2, alpha‐crystallin B chain, and reticulon‐4, were observed to be affected in both regions, confirming their potential significance in myelination (Figure 3C). Additionally, the PFC exhibited a downregulation of PLP, suggesting a slower progression of remyelination in this brain region (Figure 3C).

3.4. Quantitative Proteomics Elucidates VPC–Induced Alterations in Multiple Brain Regions

To assess the impact of the use of the inhibitor during the remyelination period, we compared the proteins and pathways in the CC, PFC, and HPC proteomes for CUP‐exposed animals treated with the inhibitor (CUP + VPC) against those that received the vehicle after demyelination (CUP; Figure 2A). We observed that 260, 579, and 89 proteins exhibited differential regulation (p < 0.05) between inhibitor‐treated and CTL animals in the CC, PFC, and HPC, respectively. A common alteration across all brain regions involved the dysregulation of myelin‐associated markers, such as PLP and mitogen‐activated protein kinase 13 (MAPK13; Figure 4A).

FIGURE 4.

Upset plot (A) showing the differentially expressed proteins in each brain region in response to VPC exposure (CUP + VPC) during the remyelination period compared to controls (CUP). The lower bar plot shows the number of entities associated with each group, whereas the upper bar plot displays the intersection size for each comparison. This is visually represented by colored and linked circles within the frame. (B) The cellular compartment analysis demonstrates the enrichment of differentially expressed proteins in the CC, PFC, and HPC for various cellular compartments. Bubble size represents the number of proteins found in a specific cellular compartment, whereas color indicates the enrichment‐adjusted p value. (C) The Circos plot shows differentially expressed myelin sheath proteins in the PFC, CC, and HPC. Edge colors depict the log2 fold‐change, comparing animals exposed to CUP followed by a period of remyelination against those treated with VPC‐80051 during the remyelination period. (D) The abundance of PLP protein was found to be differentially expressed across the proteomic data obtained from the PFC, CC, and HPC regions. (E) The mRNA expression of Plp in the PFC, CC, and HPC is illustrated. mRNA expression levels for each gene were normalized with the endogenous controls Actb and 18S. Data are represented as mean ± SD, n = 3–4 animals per group. Statistics: Two‐way ANOVA followed by Tukey's post test.

The GO analysis for the aforementioned differentially regulated proteins yielded insights into the overrepresentation of cellular compartments associated with each brain region (Figure 4B). Overrepresented cellular compartments across brain regions included the cytoplasm, intracellular region, cytosol, cell junctions, mitochondria, synapses, and the myelin sheath. Notably, the downregulation of proteins specific to myelin structure, such as myelin oligodendrocyte protein (MOG), MAG, MBP, 2′,3′‐cyclic nucleotide 3′‐phosphodiesterase (CNP), and PLP, was primarily observed in the PFC (Figure 4C), with the exception of PLP, which was affected in all brain regions analyzed (Figure 4D). Although the gene expression of Plp was not statistically altered, its levels seemed to be lower in the PFC and HPC, as shown in Figure 4E. Interestingly, in the PFC, the downregulation of PLP observed in the presence of the inhibitor was less pronounced than that observed in its absence (Figure 3C). Moreover, presynaptic proteins were identified in both the PFC and HPC, whereas postsynaptic proteins were exclusively found in the PFC.

Functional enrichment analyses were carried out using the Kyoto Encyclopedia of Genes and Genomes (KEGG) to identify the biological processes enriched by differentially expressed proteins in each group and to assess similarities across the three brain regions (Figure 5A). Results revealed several shared pathways enriched in all brain regions, including endocytosis, oxidative phosphorylation, retrograde endocannabinoid signaling, and sphingolipid signaling pathways (Figure 5A,B). Additionally, all three brain regions exhibited enrichment for neurodegenerative diseases, specifically Alzheimer's disease, Huntington's disease, and Parkinson's disease, which provides evidence for a putative contributory role of hnRNPs in their pathophysiology (Figure 5A). The comparative analysis of the PFC and HPC unveiled several overlaps in enriched pathways, including long‐term potentiation, dopaminergic synapse, cAMP and cGMP‐PKG signaling pathways, Ras signaling pathway, and the calcium signaling pathway (Figure 5A). Alterations in both the CC and PFC were observed in proteins associated with the synaptic vesicle cycle, as well as the regulation of propanoate metabolism, tight junctions, and ribosomes. At the same time, changes in gamma‐aminobutyric acid (GABAergic) synapses and beta‐alanine, aspartate, and glutamate metabolism were noted in both the CC and HPC (Figure 5C). The findings suggest shared molecular signaling mechanisms among different brain regions and highlight the importance of further studies into the pathways involved in the contexts of brain function and pathology.

FIGURE 5.

The Top 20 dysregulated KEGG pathways identified through the analysis of differentially expressed proteins in the PFC, CC, and HPC between cuprizone‐exposed animals treated with the inhibitor VPC‐80051 during the remyelination period (CUP + VPC) and those that received the vehicle during the remyelination period (CUP) (A). The Circos plot showcases the differentially expressed proteins in the PFC, CC, and HPC that are related to the sphingolipid signaling pathway, retrograde endocannabinoid signaling pathway (B), and synaptic vesicle, GABAergic, and dopaminergic synapses (C). The Circos plot edge color illustrates the log2 fold‐change, comparing animals exposed to cuprizone followed by remyelination against cuprizone‐exposed animals treated with VPC‐80051 during the remyelination period. N = 3 animals per group.

Enrichment analyses focusing on cellular compartments in the CC– of CUP ‐exposed animals treated with the inhibitor highlighted intracellular membrane‐bounded organelles, neuron projections, and protein‐containing complexes. In the PFC, alterations in the regulatory levels of proteins related to the postsynapse, plasma membrane‐bounded cell projections, and general cell projections were noted. Moreover, in the HPC, the mitochondrial membrane and actin cytoskeleton were enriched. Among the Top 20 KEGG‐enriched pathways, the CC exclusively featured proteins linked to proximal tubule bicarbonate reclamation. In the PFC, the inhibition of hnRNP A1 splicing activity modulated proteins associated with protein processing in the endoplasmic reticulum, regulation of the actin cytoskeleton, and valine, leucine, and isoleucine degradation. There were no alterations specifically observed in the Top 20 KEGG–enriched pathways in the HPC.

4. Discussion

RBPs are integral to RNA metabolism, regulating critical functions such as splicing, transport, transcription, and translation. Dysfunctions in RBPs can lead to cellular damage, including issues such as nucleocytoplasmic mislocalization and altered protein expression. It is hypothesized that the initial event or trigger‐inducing RBP dysfunction can initiate a cascade of alterations in RNA metabolism, which can negatively impact cellular function. This highlights the importance of maintaining proper RBP function to ensure optimal cellular health. The present study demonstrates that the inhibition of hnRNP A1 splicing activity during remyelination after CUP ‐induced demyelination leads to significant alterations in the expression of essential proteins involved in myelination, such as MOG, MAG, MBP, CNP, and PLP, with a more pronounced effect observed in the PFC when compared to the CC and HPC.

CUP has been widely employed as a model for studying demyelination and remyelination in the CNS. The histopathological features associated with CUP exposure include OL death and subsequent demyelination in the CC, cortex, HPC, cerebellum, and various other regions of the mouse brain (reviewed in Vega‐Riquer et al. 2019). In the CC, 5–6 weeks after CUP exposure is withdrawn, white matter remyelination occurs; however, in cortical gray matter, remyelination does not occur as efficiently within the same timeframe (Wergeland et al. 2012). This difference in remyelination dynamics between white and gray matter was substantiated by our results. Animals exposed to CUP for 5 weeks followed by 5 weeks of remyelination displayed few commonly dysregulated proteins among brain regions. Nonetheless, some similarities were observed between the CC and PFC, such as stearoyl‐CoA desaturase 2, alpha‐crystallin B chain, and reticulon‐4. However, in contrast, a prominent downregulation of PLP persists in the PFC. The differing dynamics of remyelination between white and gray matter highlight the complexity of myelination processes in distinct brain regions and may have implications for understanding the underlying mechanisms and potential therapeutic strategies for promoting remyelination in different areas of the brain.

Consistent with the expectations of the CUP model, we observed behavioral changes, including short‐ and long‐term cognitive impairment, triggered by CUP exposure during 5 weeks (Serra‐de‐Oliveira et al. 2015; Sen et al. 2019). Although our study identified altered velocity parameters in the CUP group at 5 weeks, these animals did not exhibit changes in total distance traveled or time spent exploring objects, suggesting a specific impairment in movement coordination rather than overall locomotion.

Myelin consists mostly of lipids, which make up 70%–80% of its dry weight. The most abundant lipids in myelin sheath are cholesterol and ethanolamine plasmalogen. Proteins constitute the other approximately 20%–30% of its content (Norton and Poduslo 1973). Extracellular compaction of CNS myelin is accomplished by proteins MOG and MAG, both members of the immunoglobulin superfamily. Compact myelin predominantly comprises two significant proteins, MBP and PLP, which significantly enhance myelin membrane adhesion and ensure its stability (Lee et al. 2014; Bakhti et al. 2013). In contrast to MOG and MAG, CNP is crucial in preventing myelin compaction through cytoskeletal reorganization. The proper balance among these proteins is paramount in maintaining the appropriate level of compaction and stabilizing myelin (Domingues et al. 2018; Snaidero et al. 2017).

Several hnRNPs affect myelin mRNA post‐transcriptional processes, including the synthesis, transportation, and translation of MBP, as well as the alternative splicing of PLP (Wang et al. 2012; Ainger et al. 1997; Hoek et al. 1998; Torvund‐Jensen et al. 2014; Laursen, Chan, and Ffrench‐Constant 2011). PLP and DM20 are two protein isoforms generated through alternative splicing of the PLP gene. PLP is exclusively expressed in myelin and has distinctive signaling functions crucial for maintaining axonal integrity, primarily attributed to the inclusion of Exon 3B (Timsit et al. 1992). In the mammalian postnatal brain, the PLP protein isoform is more prevalent than DM20, and the inclusion of Exon 3B confers unique signaling functions to PLP, which play a critical role in maintaining axonal integrity through axo‐glial interactions (Hobson et al. 2006; Stecca et al. 2000). Throughout the course of OL maturation, the ratio of PLP to DM20 increases alongside a reduction in the expression of hnRNP H and F. Knockdown of hnRNP H resulted in an elevated PLP/DM20 ratio, with no effect by hnRNP F knockdown. Interestingly, the combined silencing of both hnRNP H and F exhibited a synergistic effect, leading to a more substantial increase in the PLP/DM20 ratio compared to the impact observed by hnRNP H knockdown alone (Wang, Dimova, and Cambi 2007). hnRNP A1 knockdown is also detrimental to OLs, inducing apoptosis and necroptosis (Jahanbazi Jahan‐Abad et al. 2023). In the absence of the inhibitor VPC, a downregulation of PLP is observed in the PFC. Furthermore, alterations in PLP expression continue to occur even in the presence of the inhibitor, and additional key myelin proteins are also affected not only in the PFC but also in the CC and HPC. These findings underscore the substantial role of hnRNP A1 in regulating the expression of myelin proteins and may explain the differences in the remyelination process among brain regions.

Further supporting this idea, expression levels of proteins involved in the sphingolipid signaling pathway were altered, including acid ceramidase (ACDase), tyrosine‐protein kinase Fyn (FYN), cathepsin D (CTSD), and MAPK family proteins. ACDase breaks down sphingolipids in lysosomes by converting ceramide into sphingosine and a free fatty acid. A deficiency in ACDase results in a wide array of alterations in the CNS (Sikora et al. 2017). FYN, a crucial protein for CNS myelination, activates signaling pathways necessary for both the initial stages of brain development and myelin regeneration in chronic demyelinating diseases (Baer et al. 2009; Sperber et al. 2001). Mutations in the Ctsd gene can cause severe neurological diseases and lead to a loss of neurons, myelin, and gliosis. Ctsd‐knockout mice also exhibit significant myelin changes in the brain, suggesting that CTSD plays an essential role in CNS myelination by influencing the trafficking of PLP (Fritchie et al. 2009; Trajkovic et al. 2006; Mutka et al. 2010; Guo et al. 2018).

The process of myelin formation in the CNS is a complex one, involving several intricate steps. First, OL precursor cells that have proliferated must migrate to their final location within the brain. Upon reaching this stage, they differentiate into postmitotic OLs that will myelinate multiple axons. Any anomaly in these processes can severely compromise the myelination process (reviewed by Gouvêa‐Junqueira et al. 2020). Our findings highlighted the crucial role that hnRNP A1 splicing activity plays in regulating these steps, thereby underscoring the need for further, in‐depth investigations into the potential of modulators of hnRNP A1 splicing activity as a therapeutic target for demyelinating disorders.

Endocannabinoids function as retrograde messengers within the CNS, regulating synaptic function and plasticity (Alger 2012). They are involved in various cognitive and physiological processes, such as learning, memory, feeding behavior, stress response, and reward (Kruk‐Slomka et al. 2017; Morena et al. 2016; Sagheddu et al. 2015; Bermudez‐Silva et al. 2010). These messengers also play a role in synaptic maturation and neurogenesis during development (Harkany et al. 2007). Dysregulation of endocannabinoid signaling is linked to psychiatric, neurological, and neurodevelopmental disorders such as anxiety, depression, epilepsy, Alzheimer's disease, Huntington's disease, and autism (Cristino, Bisogno, and Di Marzo 2020). There are variations in proteins that play a significant role in retrograde endocannabinoid signaling in all three brain regions that were studied; however, there is limited similarity in the individual proteins that are shared among regions. The dysregulation of the endocannabinoid system in the PFC impacts various cognitive abilities, including decision‐making, attention, motivation, and controlling emotions. In the HPC, dysfunctions can lead to difficulties in learning and memory, as well as affect emotional balance and stress responses (Liu et al. 2017).

Fatty acid amide hydrolase (FAAH), an enzyme responsible for metabolizing the endocannabinoid anandamide in postsynaptic neurons, was found to be dysregulated in the hippocampal proteome. FAAH overexpression at the postsynaptic site of CA1‐CA3 neurons has been associated with an increase in anxiety‐like behavior, and deficits in both object recognition memory and the extinction of aversive memory (Zimmermann et al. 2019). Although the use of the inhibitor VPC during the remyelination period did not impact the evaluated behaviors, the observed alteration in FAAH expression suggests a potential role for hnRNP A1 splicing in regulating FAAH expression, particularly in the context of myelination processes. Notably, high FAAH levels, which increase with OLs maturation, were found in OLs of the cortex and spinal cord (Moreno‐Luna et al. 2020). This modulation of FAAH expression, triggered by the inhibition of hnRNP A1 activity, likely reflects an adaptive response to the remyelination process. Many neuronal processes, such as axogenesis, synaptic maturation, and long‐term potentiation, are regulated by hnRNPs (Folci et al. 2014; Kim et al. 2013; Proepper et al. 2011). Indeed, exposure to an inhibitor of hnRNP A1 altered the expression of proteins involved in the synaptic vesicle cycle in the CC and PFC. More specifically, neural‐specific syntaxin‐binding protein 1, a regulator of synaptic vesicle docking and fusion (Pevsner, Hsu, and Scheller 1994), was dysregulated in both regions. The PFC alone exhibited additional changes, such as in adaptor protein complex 2, associated with clathrin‐mediated endocytosis. Moreover, modifications were noted in calmodulin components, which were identified in preparations of presynaptic cytoplasm and highly enriched synaptic vesicle fractions. Calmodulin also regulates the phosphorylation of several proteins in response to Ca²⁺ in fractions, such as synaptic vesicles, synaptic membranes, synaptic junctions, and postsynaptic densities (Collins et al. 2002; Xue et al. 2021). As such, the inhibition of hnRNP A1 splicing activity could potentially impact the function of synaptic vesicles in a remyelination context.

Although we did not find any evidence of impaired long‐ or short‐term memory in the mice exposed to the VPC inhibitor during the remyelination period, we observed alterations in the expression levels of proteins related to GABAergic synapses in the HPC and CC, as well as dopaminergic synapses and long‐term potentiation in the PFC. These alterations could potentially be linked to the modifications in endocannabinoid signaling that were observed within these same regions.

Information storage in long‐term memory is believed to involve changes to the relevant synapses. In mammals, the major experimental model for memory formation at the synaptic level is long‐term potentiation (Bliss and Collingridge 1993). The model's validity relies on similarities between cellular mechanisms in HPC ‐dependent learning and hippocampal long‐term potentiation, particularly their reliance on NMDA receptors (Tsien, Huerta, and Tonegawa 1996). There is increasing evidence that GABAergic interneurons have a significant impact on the ability of hippocampal principal neurons to undergo synaptic changes during learning (Paulsen and Moser 1998). Our analysis revealed alterations in the expression levels of key proteins for GABAergic synapses in the HPC, such as protein kinase C gamma type (PKC), Na(+)/Cl(−) betaine/GABA transporter (BGT‐1), and glutamate decarboxylase 2 (GAD65). PKC is a kinase with broad activity that participates in multiple signaling pathways in the brain. By phosphorylating postsynaptic transporters such as NMDA‐type glutamate receptors and GABA receptors, PKC plays a vital role in regulating synaptic plasticity (Bright and Smart 2013; Foster and Vaughan 2017). Moreover, PKC–mediated phosphorylation of GluA2 subunits of AMPARs is necessary for the internalization of AMPARs from the postsynaptic membrane, which promotes long‐term depression (Boehm et al. 2006). The enzyme responsible for GABA synthesis and regulation of vesicular release in GABAergic neurons, GAD65, was found to be upregulated in the HPC. Other GABAergic synapse proteins were also dysregulated in the CC, specifically glutamate decarboxylase 1 (GAD67) and glutamine synthetase. GAD67, a component of the GABA‐A receptor, plays a significant role in neurotransmission by synthesizing cytoplasmic GABA, whereas glutamine synthetase converts glutamate to glutamine. Glutamine synthetase is exclusively expressed in glial cells, but its product can be transferred to neurons, where it can be reconverted to glutamate, serving as a precursor of GABA. This process significantly contributes to regulating the glutamine–glutamate–GABA cycle (Grone and Maruska 2016; Walls et al. 2015). These findings provide additional evidence of multiple alterations in the GABAergic system following the inhibition of hnRNP A1 splicing activity. Although no behavioral impairments were observed in the animal model, molecular changes seemed to underlie alterations at the cellular and synaptic levels. Specifically, it appears that hnRNP A1 splicing can modulate the GABAergic system, but other molecular changes may also be required before a phenotypic alteration can be observed.

Potential limitations of the present study are: (1) we exclusively utilized male subjects, and therefore, it would be useful to expand the investigation to include female subjects to determine any potential sex‐specific differences; and (2) since hnRNP A1 is present in various cell types, the observed alterations may not be exclusively attributed to impaired OLs, but could involve other neuronal cell types such as neurons, astrocytes, and microglia, thereby warranting further exploration. Addressing these limitations would contribute to a more comprehensive understanding of the role of hnRNP A1 in neurobiology and pathology.

5. Conclusion

Based on the discussed results, this study has led to the identification of proteins and their constituent pathways that undergo alterations in the PFC, CC, and HPC of adult mice in response to the inhibition of hnRNP A1 splicing activity during remyelination following CUP‐induced demyelination. Proteins integral to myelination were dysregulated, such as MOG, MAG, MBP, CNP, and PLP, emphasizing the intricate interplay between RBPs and myelin‐related proteins. The role of hnRNP A1 in maintaining the appropriate compaction and stability of myelin, as well as modulating the sphingolipid signaling pathway, endocannabinoid signaling, synaptic vesicle cycle, and GABAergic synapses, was all reinforced due to the dysregulation of proteins like FAAH, FYN, and CTSD. While no obvious behavioral impairments were observed in the animals that were exposed to the hnRNP A1 inhibitor during remyelination, some changes in protein expression suggest molecular changes in processes related to memory, synaptic function, and neurotransmission. Although these changes were slight and not enough to affect behavior, they indicate that hnRNP A1 may be involved in these processes. As a result, further exploration of hnRNP A1 splicing activity is necessary to gain a better understanding of its role in these processes.

Moving forward, these results could pave the way for innovative advancements in several key areas involving myelination and demyelinating disorders. First, further investigation into the precise mechanisms underlying the observed protein alterations could provide valuable insights into the pathophysiology of neurodegenerative disorders and demyelinating diseases. Additionally, exploring the functional implications of these alterations in terms of synaptic transmission, memory processes, and overall brain function holds promise for uncovering novel therapeutic targets. Overall, our research enhances our understanding of the many different roles played by hnRNP A1 in the CNS, paving the way for future investigations and potential therapeutic interventions in the realm of neurodegenerative disorders and demyelinating diseases.

Author Contributions

Caroline Brandão‐Teles: conceptualization, writing – original draft, investigation, methodology, data curation, formal analysis, validation, visualization, writing – review and editing. Victor Corasolla Carregari: writing – review and editing, methodology, formal analysis, software. Guilherme Reis‐de‐Oliveira: methodology, formal analysis, software. Bradley J. Smith: methodology, writing – review and editing. Yane Chaves: formal analysis, methodology, writing – review and editing. Aline Valéria Sousa Santos: methodology. Erick Martins de Carvalho Pinheiro: methodology. Caio C. Oliveira: methodology. Andre Schwambach Vieira: resources. Fernanda Crunfli: investigation, writing – review and editing, supervision, methodology, formal analysis, conceptualization, validation, writing – original draft. Daniel Martins‐de‐Souza: supervision, resources, funding acquisition, writing – review and editing, project administration, conceptualization.

Conflicts of Interest

The authors declare no conflicts of interest.

Peer Review

The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer‐review/10.1111/jnc.16304.

Supporting information

Figures S1–S4

Table S1

Data S1

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.