Quantitative proteomic and phosphoproteomic analyses of the hippocampus reveal the involvement of NMDAR1 signaling in repetitive mild traumatic brain injury : Neural Regeneration Research

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Quantitative proteomic and phosphoproteomic analyses of the hippocampus reveal the involvement of NMDAR1 signaling in repetitive mild traumatic brain injury

Tian, Zhicheng1,#; Cao, Zixuan2,#; Yang, Erwan1,#; Li, Juan1; Liao, Dan1; Wang, Fei3,4; Wang, Taozhi3,5; Zhang, Zhuoyuan1,6; Zhang, Haofuzi1; Jiang, Xiaofan1,*; Li, Xin7,*; Luo, Peng1,*

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Neural Regeneration Research 18(12):p 2711-2719, December 2023. | DOI: 10.4103/1673-5374.374654
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Traumatic brain injury (TBI) is defined as brain damage caused by an external physical assault and is the leading cause of death and disability in adults worldwide (Khellaf et al., 2019; Capizzi et al., 2020). Although TBI can have serious consequences, approximately 80% of all TBIs are mild TBIs (mTBIs), and these are often overlooked owing to the minor postinjury symptoms (Heyburn et al., 2019). However, some mTBIs, especially repetitive mTBIs (rmTBIs), lead to secondary brain injury because of the accumulation of damage, gradually leading to neurodegeneration (Gao and Chen, 2011; Gilmore et al., 2020). This neurodegeneration can impair motor and cognitive functions, resulting in the development of neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, and chronic traumatic encephalopathy (VanItallie, 2019; Delic et al., 2020; Ayubcha et al., 2021; Wu et al., 2021).

In contrast to motor function impairment, rmTBI-induced changes in cognitive function, including reduced learning and memory capacity, are more insidious (Xu et al., 2021). Structurally, these alterations in cognitive function are closely associated with dysregulation of the hippocampus (Castellano et al., 2017). Even though the surface of the cerebral cortex is usually the site of primary injury, the hippocampus gradually becomes affected by secondary brain injury, probably because of its interconnection with the cerebral cortex (Ho et al., 2021; Zheng et al., 2022). Structural changes in the hippocampus have been implicated in patients with cognitive deficits after rmTBI (Jorge et al., 2007; Aungst et al., 2014). Neural circuits involving the hippocampus have also been shown to be related to decreases in learning and memory capacity after rmTBI (Li et al., 2017, 2022).

Understanding the molecular bases of the changes that occur in the hippocampus after rmTBI is important to clarify the pathogenesis of rmTBI and identify effective targets for intervention. Currently, proteomics-based methods are widely used in the study of neurological diseases (Liao et al., 2009; Hosp and Mann, 2017; Bharucha et al., 2019). In a previous study, we used a proteomic and phosphoproteomic approach to explore changes in protein networks within the injured cerebral cortex at different times after TBI (Huang et al., 2022). Similarly, a recent study investigated alterations in the proteome and phosphoproteome during the subacute and chronic phases after rmTBI (Morin et al., 2022). In addition, proteomic studies of postmortem brains have also been conducted to clarify the pathogenesis of chronic traumatic encephalopathy (Cherry et al., 2018; Bi et al., 2019; Gutierrez-Quiceno et al., 2021). However, the global alterations in protein expression and phosphorylation that occur in the hippocampus after rmTBI remain largely unknown.

To investigate the specific molecular mechanisms of the cognitive impairment that arises owing to hippocampal damage after rmTBI, we performed quantitative proteomic and phosphoproteomic analyses and identified N-methyl-D-aspartate receptor 1 (NMDAR1) as being the key molecule associated with this effect. To our knowledge, this is the first study to assess the role of NMDAR1 phosphorylation in cognitive impairment after rmTBI.



Experiments were performed on 24 healthy male C57BL/6 wild-type mice aged 6 to 8 weeks, weighing 20 to 25 g, and provided by the Experimental Animal Center of Air Force Medical University (Xi’an, China) (license No. SCXK (Shaan) 2019-001). All mice were naïve and specific pathogen-free (SPF)-grade. All mice were housed under the same conditions in a 25°C temperature-controlled facility with a 12/12-hour light/dark cycle and humidity at 50–60%, were fed normal mouse chow, and were provided clean water in regularly disinfected water bottles. The mice were housed six to a cage. All procedures performed on animals were reviewed and approved by the Institutional Animal Care and Use Committee of the Air Force Medical University (approval No. 20210419) on April 19, 2021. The mice were randomly divided into sham group, rmTBI group, saline group and CGP78608 group (6 mice per group) using the random number table method.

Closed and rmTBI

A detailed description of the repetitive mild traumatic brain injury model has been previously published (Mouzon et al., 2012, 2014). For all mice, anesthesia was induced with 3% isoflurane (RWD Life Science, Shenzhen, China) and the hair was shaved from the head. Anesthesia was maintained with 2% isoflurane. Each animal was placed below the impactor on a sponge block to absorb the shock and maintain body temperature. Animals received a mild controlled cortical impact directly centered on the area between the bregma and the posterior fontanelle. The electromagnetically driven impactor (Hatteras Instruments Inc. PinPoint™ PCI3000, Grantsboro, NC, USA) (Additional Figure 1) was fitted with a custom-made, 4 mm-diameter metal tip that was used to deliver an impact to a depth of 3 mm at a velocity of 3 m/s and with a dwell time of 200 ms. Five impacts were delivered over 9 days, with a 48-hour interval between each impact. The sham group underwent the same procedures as the rmTBI group but did not receive the impact.

Additional Figure 1:
The impact device.

Novel object recognition test

To assess cognition and memory 6 weeks after injury, a novel object recognition (NOR) test was carried out in three phases (habituation, familiarization, and discrimination) for 2 days, as described previously (Semple et al., 2016). In brief, individual mice were allowed to explore the open field (40 × 40 × 40 cm3) for 10 minutes during the habituation phase. Twenty hours later, the mice were on the same field containing two identical objects and were allowed to explore for 10 minutes for the familiarization phase. Six hours later, in the discrimination phase, one of the two objects was replaced with a novel object of a different shape and color, and mice were returned to the open field for 10 minutes. To eliminate the effect of olfactory cues, the objects and the field were cleaned with 75% ethanol before each trial. To reduce the effect of visual cues, mice were placed into the field an equal distance away from the object, with their backs to the objects. The behavior of mice in the open field was recorded for subsequent analysis. Touching the object or approaching the object to within 2 cm of the whiskers, front paws, or nose was considered exploratory behavior. The amount of time the mice spent exploring the objects was measured using a stopwatch, with a precision of 0.1 second. The NOR index (%) was calculated as follows: [time spent exploring the novel object/total time spent exploring the two objects] × 100.

Morris water maze test

Six weeks after injury, mice underwent the Morris water maze (MWM) test (Mobile Datum, RD1101-MWM-M, Shanghai, China) to assess learning and memory. The details of the process have been described previously (Titus et al., 2016). In short, the mice need to find and stand on a platform submerged under 5 mm of water in a circular pool by observing four visual cues in different locations around the pool. White pigment was added to the water to enhance the background for video recording. The MWM test involved two parts: training and testing. On the training days, the mice were given a maximum of 60 seconds to find the platform, and recording was stopped when the mice remained on the platform for 5 seconds. Mice that did not find the platform within 60 seconds were guided to the platform and allowed to remain on it for 10 seconds. The training phase lasted for 4 days, during which the mice were placed in the pool four times every day (different starting points: 1st, 2nd, 3rd, and 4th quadrant). On the fifth day, the test was performed be placing the mice in the pool from which the platform had been removed and allowing them to explore for 60 seconds. The video data were analyzed using MWM software, and the parameters measured included latency to finding the platform during the training phase and the time spent in each quadrant in the testing phase.

Tissue processing and immunofluorescence staining

After the behavioral experiments were complete, the mice were anesthetized with 3% isoflurane (RWD Life Science), maintained under anesthesia with 2% isoflurane, sacrificed by perfusion with ice-cold 0.01 M phosphate-buffered saline (PBS) (pH 7.4), and then fixed with 4% paraformaldehyde. Next, the brains were removed and postfixed for 4 hours, followed by dehydration in a 30% sucrose solution for 48 hours. The brains were then embedded in optimal cutting temperature compound (Tissue-Tek, SAKURA 4583, Torrance, CA, USA) and cut into 16-μm coronal sections using a freezing microtome (Leica CM 1950, Wetzlar, Germany). Hippocampal tissue sections were collected, placed on slides, washed in 0.01 M PBS (three times for 10 minutes each), and blocked with 5% bovine serum albumin solution and 0.3% Triton-X100/PBS for 1 hour. Then tissue sections were incubated overnight at 4°C with primary antibody (p-tau, mouse, 1:200, Cat# AT8, Invitrogen, Grand Island, NY, USA), followed by incubation at room temperature for 3 hours with secondary antibody (donkey anti-mouse, Alexa Fluor™ 488, 1:800, Cat# A-21202, Invitrogen). The primary and secondary antibodies were diluted in 5% bovine serum albumin and 0.1% Triton-X100/PBS. Cellular nuclei were stained by incubating the slides for 10 minutes in 4′,6-diamidino-2-phenylindole (DAPI) (1:1000, Sigma, St. Louis, MO, USA, D9564) diluted in PBS. Finally, the slides were coverslipped with 50% glycerin mounting medium.

TUNEL staining

Using a One Step TUNEL Apoptosis Assay Kit (Beyotime Biotechnology, C1086, Shanghai, China), hippocampal sections were fixed with 4% paraformaldehyde for 30 minutes, washed with 0.01 M PBS (twice for 10 minutes each), and incubated at room temperature for 5 minutes with 0.5% Triton-X100/PBS. Subsequently, the prepared TUNEL assay solution was placed onto the slides, which were covered with anti-evaporation film and incubated at 37°C for 60 minutes in the dark. Cellular nuclei were stained by incubating the slides with DAPI for 10 minutes, and the slides were then washed three times for 5 minutes each. Finally, the slides were coverslipped with 50% glycerin mounting medium.

Staining analysis

Images of the stained sections were captured using an Olympus FV3000 laser confocal microscope (Olympus, Tokyo, Japan). Images were processed and analyzed using Image-Pro Plus 6.0 software (Media Cybernetics, Rockville, Maryland, USA) to obtain the integrated optical density (IOD) value of each image.

Western blotting

Mice were anesthetized with isoflurane (RWD Life Science), and the brains were removed quickly and placed in precooled brain matrices (RWD Life Science, Cat# 68707) to isolate the hippocampal region. The hippocampal tissue was then collected and homogenized in ice-cold RIPA buffer containing protease inhibitors (Glpbio, Montclair, CA, USA, Cat# GK10014) and phosphatase inhibitors (Glpbio, Cat# 23227 GK10012) to isolate total protein. The protein samples were quantified using a BCA assay kit (Cat# 23227, Thermo Fisher Scientific, Waltham, MA, USA). Next, the samples were loaded onto an 8% SDS-PAGE gel (Cat# M00661, Genscript, Nanjing, China) separated by electrophoresis. Subsequently, the proteins were transferred to PVDF membranes (Millipore, Darmstadt, Germany) that were blocked with 5% nonfat milk for 1 hour and incubated with the following primary antibodies overnight at 4°C: anti-NMDAR1 (rabbit, 1:2000, EPR2481(2), Cat# ab109182, Abcam, Cambridge, UK); anti-pNMDAR1 (rabbit, 1:700, Cat# ab195002, Abcam); β-tubulin (rabbit, 1:2000, ARC0203, Cat# A12289, ABclonal, Wuhan, China). Then, the membranes were incubated with a horseradish peroxidase–conjugated secondary antibody (goat anti-rabbit IgG, 1:10,000, BS13278, Bioworld, Minneapolis, MN, USA) for 1 hour. Finally, the membranes were incubated with a chemiluminescence reagent (RM00021, ABclonal) and imaged with a CHEMIL-MAGER chemiluminescence imaging system (Bio-Rad, Hercules, CA, USA). ImageJ software (fiji-2.11.0, NIH, Bethesda, MD, USA) was used to measure the intensity of each band. Relative protein expression was normalized to β-tubulin.

Golgi-Cox staining

Fresh brains perfused with 0.01 M PBS were stained with prepared Golgi-Cox solution (PK401, FD NeuroTechnologies, Columbia, MD, USA) for 7 days at room temperature in the dark. The brains were then cut into 150-μm coronal slices using a vibratome (Leica VT1000S), transferred to distilled water, and washed two times for 5 minutes each. The following steps were then performed: dehydration with 50% alcohol for 5 minutes, ammoniation with ammonia solution (ammonia: distilled water = 3:1) for 5–10 minutes, and treatment with 5% Na2S2O3 for 10 minutes. After each of these steps, the sections were washed as described above to remove the remaining liquid, except for the alcohol owing to its volatility. The brain tissue, which was distended owing to water absorption, was then restored by washing with 0.01 M PBS three times for 5 minutes each. Next, the brain sections were mounted on glass slides, air-dried, and dehydrated with an alcohol gradient (50%, 70%, 80%, 95%, 100%, and 100%, each for 5–10 minutes). Finally, the sections were destained with xylene for 10 minutes and sealed with neutral balsam mounting medium.

Dendritic spine analysis

Images of Golgi-COX–stained neurons were captured using an Olympus FV3000 laser confocal microscope (Olympus). The images were then transferred to Imaris 9.0.1 software (Bitplane, Zurich, Switzerland) to determine the total dendritic spine density of neurons in the hippocampus, measure dendrite length, and classify the different types of dendritic spines (stubby, mushroom, long and thin, filopodia-like). In addition, the total and average dendritic spine volumes were calculated.

Protein extraction

At 6 weeks after rmTBI, mice were perfused with ice-cold 0.01 M PBS, the brain was rapidly harvested, the hippocampus was removed and placed into a 5-mL centrifuge tube that was then placed into liquid nitrogen, and the flash-frozen hippocampal tissue was homogenized. Subsequently, lysis buffer (8 M urea (V900119-500G, Sigma), 1% phosphatase inhibitor (Millipore), and 1% protease inhibitor (Millipore)) was added to the tube, and an ultrasonic processor (JY92-IIN, Scientz, Ningbo, China) was used to sonicate the tissue. Finally, the samples were centrifuged at 12,000 × g at 4°C for 10 minutes, the supernatant was collected, and the protein concentration was measured.

Trypsin digestion

Equal amounts of each sample were enzymatically digested, and the same volume of lysis buffer was added to the sample. After adding one volume of precooled acetone, the mixture was shaken, four volumes of precooled acetone were then added, and the mixture was allowed to stand at 20°C for 2 hours. After centrifugation at 4500 × g for 5 minutes, the precipitate was collected and washed twice with precooled acetone. TEAB (200 mM) (17902, Sigma) was added to the dried precipitate, which was then disrupted by ultrasonication (Scientz); trypsin was added at a 1:50 ratio of trypsin to protein; and the mixture was allowed to sit overnight. Subsequently, the samples were digested by incubating with 5 mM dithiothreitol (DTT) for 30 minutes at 56°C and 11 mM iodoacetamide at room temperature in the dark for 15 minutes.

High performance liquid chromatography fractionation

The samples were separated on an Agilent 300 Extend C18 column (4.6 mm ID, 250 mm length, 214 nm wavelength, 35°C chamber temperature) (770450-902, Agilent, Santa Clara, CA, USA). In short, the column was prepared by flushing 95% buffer A for 30 minutes, after which the peptides were loaded onto the column and subjected to graded gradient flow. The eluted samples were collected at a rate of 1 minute per tube. The 11th tube to the 46th tube were combined into 12 samples and vacuum-dried for subsequent analysis.

Enrichment of phosphorylated peptides

First, the peptide mixture obtained as described above was mixed with and an immobilized metal ion affinity chromatography (IMAC) microsphere suspension and loading buffer (50% acetonitrile (ThermoFisher) and 0.5% acetic acid (Gaojing, Hangzhou, China)) and incubated with shaking at room temperature for 50 minutes. The IMAC microspheres were washed sequentially with loading buffer and 30% acetonitrile/0.1% trifluoroacetic acid to remove nonspecifically adsorbed peptides. To collect the enriched phosphorylated peptides, the IMAC microspheres were shaken with elution buffer containing 10% NH4OH (Gaojing). The supernatant was then freeze-dried for subsequent liquid chromatography-tandem mass spectrometry analysis.

liquid chromatography-tandem mass spectrometry analysis

Construction of the spectral library: The peptides were dissolved in solvent A and then separated using a NanoElute UHPLC system (EASY-nLC 1000, Thermo Fisher Scientific). In short, solvent A consisted of 0.1% formic acid and 2% acetonitrile in water, and solvent B consisted of 0.1% formic acid in acetonitrile. The liquid phase gradient setting was as follows: from 6% to 24% solvent B for 70 minutes; from 24% to 35% for 14 minutes; from 35% to 80% for 3 minutes; and 80% for 3 minutes. The flow rate was set at a constant rate of 450 nL/minute. The separated peptides were injected into a capillary ion source for ionization, followed by timsTOF mass spectrometry (timsTOF Pro, Bruker, Billerica, MA, USA).

Data independent acquisition (DIA): The liquid phase parameters use were the same as those used for building the spectral library. The ion source voltage was set at 1.7 kV, and both the peptide parent ion and its secondary fragments were detected and analyzed using timsTOF mass spectrometry (Bruker). The data acquisition mode used was parallel accumulation-serial fragmentation combined with DIA (dia-PASEF) mode. The primary mass spectrometry scan range was set to 400–1500 m/z, with one primary mass spectrometry acquisition followed by 10 PASEF mode acquisitions and secondary mass spectrometry scans in the interval 100–1700 m/z with a window of every 25 m/z.

Database search

Data dependent acquisition and DIA data were retrieved using the MSFragger (v 2.3) search engine (https://github.com/Nesvilab/MSFragger) with default software parameters. The database used was Mus_musculus_10090_SP_20210721.fasta (17089 sequences), and the inverse database was added to calculate the false discovery rate (FDR) due to random matching. The FDR for protein, peptide, and peptide-spectrum match identification was set to 1%. Subsequently, DIA-NN (version 1.8) software (https://github.com/vdemichev/DiaNN) was used for processing, and the corresponding spectral library was imported to predict the peptide retention time by nonlinear correction.

Quantitative analysis

We obtained the normalized intensity of each protein in different hippocampal samples from the search results. The normalized intensity (I) of proteins in different samples was transformed by centralization to obtain the relative quantitative values (R) of proteins in different samples. The following formula was used to perform the calculations: \[R_{ij}=I_{ij}/Mean(I_j)\], where i represents the sample and j represents the protein. To eliminate the effect of protein expression on modification, we divided the R of the modification site by the R of the protein corresponding to the modification site.

Differential protein screening

The ratio of the mean of the R values of each protein/modification site in samples from the rmTBI group and sham group was taken as the fold change (FC). For example, the FC of proteins/modification sites between samples A and B was calculated as follows: \[FC_{A/B,k} = Mean(R_{ik},i\in A)/Mean(R_{ik}, i\in B)\], where R represents the relative quantitative value of the protein/modification site, i represents the sample, and k represents the protein/modification site. To estimate the significance of the difference, the R value of each protein/modification site in the samples was subjected to a T test (P < 0.05). To make the data fit a normal distribution, the R value of the protein/modification site was log2-transformed using the following formula: \[P_{k}=T.test(Log2(R_{ik},i\in A),Log2(R_{ik}, i\in B))\]. The differentially expressed proteins (DEPs) were mapped using a volcano plot tool (

Motif analysis

Using the MoMo analysis tool (https://meme-suite.org/meme/index.html), which is based on the motif-x algorithm, phosphorylated sites were analyzed with peptide sequences consisting of six amino acids upstream and downstream of the modification site. When there were more than 20 peptides in a specific sequence and the p-value was < 0.000001, the sequence was considered to be a phosphorylated motif. Based on the results of the MoMo analysis, a heatmap was created showing the degree of frequency change (DS) of amino acids near the phosphorylated site. The DS was calculated as follows: \[DS = -Log10(p.value)*sign(diff.percent) \].

Functional enrichment

Through Gene Ontology (GO) annotation, proteins were classified into three categories: biological process, cellular component, and molecular function. For all three categories, the enrichment of the DEPs compared with all identified proteins was determined by two-tailed Fisher’s exact test, and a P value < 0.05 was regarded as significant. We used the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (Kanehisa and Goto, 2000) (https://www.genome.jp/kegg/) to identify enriched pathways by applying a two-tailed Fisher’s exact test (P < 0.05) and classify these pathways into hierarchical categories. The InterPro database (https://www.ebi.ac.uk/interpro/; Apweiler et al., 2001) was used to identify domains in all of proteins analyzed as described above.

Drug delivery to the hippocampus

At 5 weeks after injury, mice were anesthetized with isoflurane (RWD Life Science) and fixed on a stereotaxic apparatus (RWD Life Science), an incision was made on the top of the head, and the head was leveled. Drug delivery tubes were placed 1.5 mm/–1.5 mm medial-lateral (ML), –2.0 mm anterior-posterior (AP), and –2.0 mm dorsal-ventral (DV) (Paxinos G, Franklin KBJ, 2013) into the right and left hippocampi, and the tubes and skull were fixed with dental cement (GC FIT CHECKER II). One week after surgery, the mice were anesthetized with 3% isoflurane (RWD Life Science), anesthesia was maintained with 2% isoflurane, and 200 µL of an NMDAR1 antagonist (CGP78608, 10 μM, 1493, Tocris, Bristol, UK) or 200 µL normal saline was delivered through the tubes via microinjector pump. The mice were allowed to recover for 30 minutes before the NOR test was performed.

Statistical analysis

Statistical analysis of all data was performed with GraphPad Prism 9.0 (GraphPad, San Diego, CA, USA, www.graphpad.com). The Shapiro-Wilk normality test was used to test the normality of the variable distribution. Data that exhibited normal distribution or conformed to the parametric test were analyzed by unpaired t-test or two-way analysis of variance. All other were analyzed by Mann-Whitney U test. All data in this paper are presented as the mean ± standard error of mean (SEM).


rmTBI induced delayed neurological dysfunction and structural lesions in the hippocampus

To mimic rmTBI in mice, brain injury was induced five times with a 48-hour interval between each injury (Figure 1A). Because rmTBI usually causes chronic neurological impairment, NOR and MWM tests were performed to detect delayed neurological dysfunction 6 weeks after rmTBI. As expected, the NOR index in the rmTBI group was significantly lower than that in the sham group (P = 0.0438; Figure 1B). In addition, in the MWM test, (1) the time needed to find the platform was significantly longer in the rmTBI group than in the sham group (P = 0.0006; Figure 1C), and (2) the time that the mice in the rmTBI group spent in the fourth quadrant (the platform quadrant) was significantly shorter than that in the sham group (P = 0.0115) and was not significantly different from the average time that the mice in the rmTBI group spent in other quadrants (Figure 1D). The swimming trajectories of the mice in the sham group and the rmTBI group are shown in Figure 1E. Taken together, these results suggest that rmTBI led to learning and memory deficits in mice at the chronic stage of rmTBI.

Figure 1:
rmTBI induced delayed neurological dysfunction in the hippocampus.(A) Experimental design. (B) Novel object recognition index in the sham group (n = 6) and in the rmTBI group after injury (n = 6) (unpaired t-test, t = 2.306, P = 0.0438). (C–E) Morris water maze test (n = 6). Latency to find the platform (C) during the 4-day training phase (two-way analysis of variance, F = 23.80, P = 0.0006), average time spent in quadrants (Q1–3: the 1st–3rd quadrant; Q4: the 4th quadrant) (D) (two-way analysis of variance, F = 6.791, shamQ1–3 vs. shamQ4: P = 0.0014, rmTBIQ1–3 vs. rmTBIQ4: P = 0.9859, shamQ4 vs. rmTBIQ4: P = 0.0115) and representative traces (E) of swimming trajectories in the sham group and rmTBI group in the test phase. Q4 is the target quadrant. All data are expressed as the mean ± SEM. *P < 0.05, **P < 0.01, ***P < 0.001. MWM: Morris water maze; NOR: novel object recognition; ns: not significant; rmTBI: repetitive mild traumatic brain injury.

Next, to clarify whether the observed neurological impairments were associated with damage to specific brain regions, we detected apoptotic neurons by TUNEL staining and phosphorylated microtubule-associated protein tau (p-tau) expression by immunofluorescence. Based on previous studies, cognitive impairment, such as reduced learning and memory capacity, is closely associated with structural damage to the hippocampus (Anacker and Hen, 2017; Lieberman et al., 2019; Xu et al., 2019). Therefore, we focused on histological alterations in the hippocampus after rmTBI. There was no significant difference in TUNEL staining of cellular bodies in the hippocampus of the rmTBI group compared with the sham group; tissue sections from a mouse with acute brain injury (3rd day of brain ischemia) were used as a positive control (Figure 2A). The hippocampus of the rmTBI group exhibited more positive staining for p-tau than the sham group (Figure 2B), and the relative integrated optical density (IOD) of p-tau was significantly different between the sham group and the rmTBI group (P < 0.0001; Figure 2C).

Figure 2:
rmTBI induces structural lesions in the hippocampus.(A) Representative images of terminal deoxynucleotidyl transferase dUTP nick-end labeling (TUNEL) staining and relative integrated optical density (IOD) of TUNEL signals (n = 3) (unpaired t test, t = 0.2743, P = 0.7974). Blue: 4′,6-diamidino-2-phenylindole (DAPI), nucleus; green: TUNEL, apoptotic cells. (B and C) Immunostaining with an anti-p-tau antibody. Representative images with p-tau-positive staining (B) and the relative IOD of p-tau staining (C) in the hippocampus in the sham and rmTBI groups (six sections from three mice (two sections per mouse) from each group) (unpaired t-test, t = 6.218, P < 0.0001). Blue: DAPI, nucleus; green: p-tau. (D) Representative image and software-remodeled drawing of Golgi staining. (E) Total density of dendritic spines in hippocampal neurons in the sham group and in the rmTBI group after injury (unpaired t-test, t = 5.762, P < 0.0001), as well as the average volume of spines in two groups (unpaired t-test, t = 0.818, P = 0.4299). (F) Stubby spine density (unpaired t-test, t = 2.911, P = 0.0073) and mushroom spine density (Mann-Whitney U test, P = 0.0287) in hippocampal neurons in the sham group and in the rmTBI group after injury. Data are expressed as the mean ± SEM. *P < 0.05, **P < 0.01, ****P < 0.0001. ns: Not significant; rmTBI: repetitive mild traumatic brain injury.

To determine whether synaptic connections and plasticity were altered in the hippocampus after rmTBI, we conducted Golgi staining to observe neuronal dendrites and dendritic spines. The total density of dendritic spines in hippocampal neurons in the rmTBI group was significantly lower than that in the sham group (P < 0.0001), but there was no significant difference in the average volume of spines between the two groups (Figure 2E). The densities of stubby spines (P = 0.0073) and mushroom spines (P = 0.0287) were significantly lower in the rmTBI group than in the sham group (Figure 2F). A representative image and software-remodeled drawings are shown in Figure 2D. These results demonstrated that rmTBI mainly causes neurodegeneration in brain tissue at the chronic stage, which differs from the apoptosis caused by acute brain injury. The neurodegeneration that occurs in the hippocampus could explain the neurological impairment observed after rmTBI.

Differential protein expression in the hippocampus after rmTBI

Based on the obtained neurofunctional and histopathological results, we further investigated global protein expression changes in the hippocampus after rmTBI using proteomics. Protein samples were analyzed using a combination of cutting-edge technologies including protein extraction, enzymatic digestion, high-performance liquid chromatography fractionation, liquid chromatography-mass spectrometry tandem analysis, and bioinformatics analysis. In total, 53,795 peptides were identified that corresponded to 8480 proteins (Additional Figure 2A). Next, we filtered out all proteins that did not satisfy the following criteria: FDR (false discovery rate) of 1%, and proteins containing at least one unique peptide. After filtering, 8097 (95.5%) proteins were retained for subsequent analysis (Additional Figure 2A). To ensure the accuracy of the results, we performed a quality evaluation and sample repeatability tests, including peptide length distribution, peptide quantity distribution, Pearson’s correlation coefficient (PCC), principal component analysis (PCA), and relative standard deviation (RSD) tests (Additional Figure 2B and C). The results from these tests showed high reproducibility and reliability of the proteomic analysis results.

Additional Figure 2:
Global proteomic analysis.(A) Overview of protein identification. (B) Data quality evaluation, including distribution plots of peptide length and number of peptides per protein. (C) Sample repeatability test, including heatmap of the Pearson correlation coefficient (PCC) between all samples, plot of protein quantitative principal component analysis (PCA) results for all samples, and boxplot of the relative standard deviation (RSD) of quantitative values between replicates in each group. (D) Heatmap representation of all differentially expressed proteins (DEPs) grouped by hierarchical clustering. The color range indicates z scores.

Compared with the sham group, 101 DEPs were identified in the hippocampus in the rmTBI group, including 64 upregulated proteins and 37 downregulated proteins (Figure 3A and B). Heatmaps of some of the DEPs (the top 9 upregulated DEPs and the top 10 downregulated DEPs) and all of the DEPs are shown in Figure 3C and Additional Figure 2D, respectively. We then performed a GO enrichment analysis of DEPs in the hippocampus that included three categories: biological processes, molecular functions, and cellular components. For upregulated proteins, 14 biological processes (the top five were blood coagulation, protein activation cascade, negative regulation of hemostasis, negative regulation of coagulation, and acute inflammatory response), eight molecular functions (the top three were T-cell receptor binding, cofactor transmembrane transporter activity, and antigen binding), and eight cellular components (the top three were fibrinogen complex, blood microparticle, and platelet alpha granule lumen) were enriched (Figure 3D). In contrast, the downregulated proteins were significantly enriched in 14 biological processes (the top five were cellular response to ionizing radiation, cellular response to mechanical stimulus, apoptotic mitochondrial changes, regulation of viral genome replication, and lipoprotein biosynthetic process), three molecular functions (promoter-specific chromatin binding, beta-catenin binding, and chromatin binding), and one cellular component (basal dendrite) (Figure 3E). KEGG pathway analysis showed that upregulated proteins were enriched in 24 pathways (the top five were complement and coagulation cascades, Staphylococcus aureus infection, bladder cancer, extracellular matrix (ECM)-receptor interaction, and acute myeloid leukemia) (Figure 3F), and downregulated proteins were enriched in seven pathways (the top three were lysine degradation, Fc epsilon RI signaling pathway, and signaling pathway regulating pluripotency of stem cells) (Figure 3G). The upregulated DEPs were enriched in three domains, including immunoglobulin C1-set, trypsin, and von Willebrand factor type A (Figure 3H). Protein-protein interaction (PPI) analysis did not identify any significant DEP clusters (Figure 3I). Taken together, these results suggest that the hippocampal DEPs were mainly associated with inflammation, immunity, and coagulation. These three events are major changes that occur soon after rmTBI, suggesting that inflammation and the immune response may persist in the hippocampus in the chronic phase after rmTBI. Indeed, the expression of proteins involved in these processes changed after rmTBI (Additional Figure 3).

Figure 3:
Proteomic analysis of hippocampal tissue in a mouse model of rmTBI.(A) Number of differentially expressed proteins (DEPs) in the hippocampus. (B) Volcano plot of DEPs in the hippocampus. (C) Heatmap of selected DEPs. Light red represents high expression, while light blue represents low expression. (D and E) Bubble chart of GO enrichment analysis of upregulated (D) and downregulated (E) proteins. The bubbles display the terms in each GO category, including BP, CC, and MF. (F and G) Bubble chart of KEGG pathway analysis results for upregulated (F) and downregulated (G) proteins. The bubbles display the KEGG pathway terms. (H) Bubble chart of domains identified in the upregulated proteins. (I) DEP protein-protein interaction network. Red represents upregulated proteins, while green represents downregulated proteins. BP: Biological process; CC: cellular component; GO: Gene Ontology; HPC: hippocampus; KEGG: Kyoto Encyclopedia of Genes and Genomes; MF: molecular function; rmTBI: repetitive mild traumatic brain injury.
Additional Figure 3:
Heatmap of differentially expressed proteins enriched in three biological processes.

Differential protein phosphorylation in the hippocampus after rmTBI

Previous studies have shown that changes in the function of many proteins taking part in the regulation of neurofunction are not dependent on transcriptional regulation, but rather are affected by posttranslational modifications, notably phosphorylation (Walaas and Greengard, 1991; Bilbrough et al., 2022). Thus, we investigated changes in the phosphoproteome of the hippocampus after rmTBI. In total, we identified 17,311 peptides that assembled into 12,144 sites and 10,991 modified peptides that assembled into 3926 proteins. After applying the same filtering criteria described above for the proteomic analysis, we obtained 11,144 (91.8%) sites and 3402 (86.7%) proteins for follow-up analysis (Additional Figure 4A). Quality evaluation and sample repeatability tests (peptide length distribution, PCC, PCA, and RSD; Additional Figure 4B and C) indicated the high repeatability and credibility of the phosphoproteomic analysis results.

Additional Figure 4:
Global phosphoproteomic analysis.(A) Overview of phosphorylated protein identification. (B) Distribution plots of peptide lengths generated for data quality evaluation. (C) Sample repeatability test, including Pearson’s correlation coefficient (PCC), principal component analysis (PCA), and relative standard deviation (RSD). (D) Heatmap of all differentially expressed phosphorylated proteins (DEPPs) grouped by hierarchical clustering. The color range indicates z scores. (E) The protein-protein interaction (PPI) network for all DEPPs. Red represents upregulation, while green represents downregulation.

Compared with the sham group, 689 DEP sites and 516 differentially expressed phosphorylated proteins (DEPPs) were identified in the hippocampus in the rmTBI group, including 506 upregulated DEPSs in 345 upregulated DEPPs and 183 downregulated DEPSs in 171 downregulated DEPPs (Figure 4A and B). Heatmaps of some of the DEPPs (The top 8 upregulated DEPPs and the top 7 downregulated DEPPs) and all of the DEPPs are shown in Figure 4C and Additional Figure 4D, respectively. Next, GO enrichment analysis, KEGG pathway analysis, and protein domain analysis were performed. The results from the GO enrichment analysis indicated that the upregulated DEPPs were enriched in 14 biological processes (the top five were learning, signal release, cell projection morphogenesis, cell part morphogenesis, and trans-synaptic signaling), eight enriched molecular functions (the top three were ionotropic glutamate receptor binding, glutamate receptor binding, and SH3 domain binding), and eight enriched cellular components (the top three were postsynaptic specialization, postsynaptic density, and post-synapse) (Figure 4D). In contrast, the downregulated DEPPs were enriched in 14 biological processes (the top five were regulation of branching morphogenesis of a nerve, synapse maturation, DNA damage response, maintenance of synapse structure, and regulation of posttranscriptional gene silencing), eight molecular functions (the top three were structural constituent of post-synapse, structural constituent of postsynaptic density, and phosphatidylinositol transfer activity), and eight cellular components (the top three were U2-type catalytic step 2 spliceosome, Golgi cisterna membrane, and ribosome) (Figure 4E). The phosphoproteomic analysis results showed that DEPPs were mainly associated with synapses, microtubules, the cytoskeleton, dendrites, the regulation of signaling and neuron projections, which are all related to neurostructure and neurofunction. KEGG pathway analysis indicated that the upregulated DEPPs were enriched in 15 pathways (the top five were systemic lupus erythematosus, cocaine addiction, inositol phosphate metabolism, B-cell receptor signaling pathway, PD-L1 expression, and PD-1 checkpoint pathway in cancer) (Figure 4F), whereas the downregulated DEPPs were enriched in the glucagon signaling, apelin signaling, and Rap1 signaling pathways (Figure 4G). These results suggested that DEPPs in the hippocampus were related not only to the cellular immune system, as indicated by hippocampal proteomic analysis, but also to neuronal structure and function.

Figure 4:
Phosphoproteomic analysis of hippocampal tissue in a mouse model of rmTBI.(A) Number of differentially expressed phosphorylated sites (DEPSs) and differentially expressed phosphorylated proteins (DEPPs). (B) Volcano plot of DEPSs in the hippocampus. (C) Heatmap of partial DEPSs. Light red represents high expression, while light blue represents low expression. (D and E) Bubble chart of GO enrichment analysis results for upregulated (D) and downregulated (E) phosphorylated proteins. The GO categories include BP, CC, and MF. (F and G) Bubble chart of KEGG pathway analysis results for upregulated (F) and downregulated (G) phosphorylated proteins. (H and I) Bubble chart of the domains identified in upregulated (H) and downregulated (I) phosphorylated proteins. The bubbles display terms corresponding to each GO category, KEGG pathway, or domain. (J) DEPP PPI network and clusters. The bar blot displays the terms associated with each cluster. BP: Biological process; CC: cellular component; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; MF: molecular function; PPI: protein-protein interaction; rmTBI: repetitive mild traumatic brain injury.

Next, we performed protein domain analysis of the DEPPs. The upregulated DEPPs were enriched in 28 domains, such as the Homer-binding domain of the metabotropic glutamate receptor, synapsin N-terminal domain, death domain, calponin homology (CH) domain, SH3 domain, and protein kinase domain (Figure 4H), while the downregulated DEPPs were enriched in 10 domains, including the miro-like protein domain, Zn-finger domain in ubiquitin-hydrolases and other proteins, phosphoinositide domain, sushi domain, cofilin/tropomyosin-type actin-binding protein domain, Sec7 domain, myb-like DNA-binding domain, F-box-like domain, and regulator of G protein signaling domain (Figure 4I). The DEPPs were enriched in domains associated with synapses and glutamate receptors, which better reflected the changes in protein function seen after rmTBI than did the enriched DEPs. DEPP PPI analysis showed that the DEPPs grouped into nine clusters, including endocytosis, MAPK signaling pathway, adipocytokine signaling pathway, spliceosome, aldosterone-regulated sodium reabsorption, axon guidance, metabolic pathways, protein processing in the endoplasmic reticulum, and Wnt signaling pathway (Figure 4J and Additional Figure 4E). Taken together, the above results suggest that DEPPs after rmTBI were associated with synapses, learning, signaling regulation, and cytoskeletal proteins, all of which are involved in neuronal function and structure. Thus, compared with the pathways enriched in DEPs, the pathways enriched in DEPPs were more consistent with neurodegeneration induced by neuronal dysfunction and structural changes, which are in keeping with the biological phenotype of the rmTBI mouse model.

Analysis results of phosphorylation motifs and upstream kinases

To explore how the DEPPs identified as described above are regulated by phosphorylation after rmTBI, we analyzed the sequences of the phosphorylated peptides using the Motif-X program (MoMo analysis tool). Motif-X analysis found 67 serine motifs (Additional Figure 5A) and 12 threonine motifs in the hippocampal DEPPs (Additional Figure 5B). For serine motifs, the maximal fold increase (69.2) found was for motif 11 (xxxxxK_S_PxxxKS) (“x” represents a random amino acid residue), while motif 49 (xxxxxx_S_xExxxx) was enriched only 1.7-fold (Figure 5A). For threonine motifs, the maximal fold increase (83.7) found was for motif 1 (xxxRxx_T_PPxxxx), and the minimal (2.4) was for motif 12 (xxxxxx_T_xPxxxx) (Figure 5B). The conserved amino acid residues surrounding these two types of phosphorylated sites (serines and threonines) exhibited different characteristics. In both types of motifs, proline (P) and arginine (R) displayed similar enrichment modes, but these amino acids displayed a higher frequency in the serine motifs (Figure 5C and D). Among serine motifs, aspartic acid (D) was common at position -1 and positions 1 to 6, glutamic acid (E) typically appeared at positions 2 to 6, and lysine (K) was conserved at positions -6 to -1 and 6 (Figure 5C). However, glutamic acid (E) was more common at positions 2 to 4 in the threonine motifs (Figure 5D).

Additional Figure 5:
All phosphorylation motifs, including serine motifs (A) and threonine motifs (B).Each letter represents an amino acid. The size of the letter represents the frequency of the residue at that position.
Figure 5:
Analysis of phosphorylation motifs and upstream kinases.(A) Serine motifs with the maximal (11) and minimal (49) fold increase. (B) Threonine motifs with the maximal (1) and minimal (12) fold increase. (C and D) Heatmaps of phosphorylated sites around serine (C) and threonine (D) residues. Red represents high frequency, and blue represents low frequency. Each letter represents an amino acid. (E) Number of predicted upstream kinases. (F) The interaction network of upstream kinases and substrates. (G and H) UpSet plots of GO (G) and KEGG (H) pathways. The bar plots and table are arranged from highest to lowest degree of intersection. The tables display the name of the intersection gene. GO: Gene Ontology; HPC: hippocampus; KEGG: Kyoto Encyclopedia of Genes and Genomes; rmTBI: repetitive mild traumatic brain injury.

To identify the active kinases that are responsible for phosphorylating proteins in the hippocampus after rmTBI, we performed a kinase prediction analysis using iGPS/GPS software, which predicts upstream activated kinases based on the coordinated changes detected in their known substrates. Kinase prediction analysis and condition filtering (sham group vs. rmTBI group: kinases and substrates both were significantly different) identified 13 kinases predicted to mediate phosphorylation of DEPPs in the hippocampus: ribosomal protein S6 kinase alpha-1/3 (RSK1/2), nuclear mitogen- and stress-activated protein kinase 1 (MSK1), 70 kDa ribosomal protein S6 kinase beta (P70S6KB), protein kinase B beta/gamma (AKT2/3), serine/threonine-protein kinase pim-2 (PIM2), doublecortin-like kinase 3 (DCLK3), serum/glucocorticoid-regulated kinase 1/3 (SGK1/3), checkpoint kinase 2 (CHK2), 5’-AMP-activated protein kinase catalytic subunit alpha-1 (AMPKA1), cAMP-dependent protein kinase catalytic subunit alpha (PKACA)) and 1 negative kinase (casein kinase II subunit alpha’ (CK2A2) (Figure 5E and F). Among these kinases, the AKT family and CK2A2 regulate multiple DEPPs. In addition, we found that Shank3-Ser1577 was regulated by many kinases (RSK1/2, MSK1, and P70S6KB). Shank3 is a multifunctional synaptic protein associated with the neurological disorder autism, and changes in Shank3 affect neurofunction after rmTBI (Ehlers, 2002; Jiang and Ehlers, 2013).

NMDAR1 helps regulate hippocampus-mediated cognitive function after rmTBI

Based on our findings of learning and memory deficits and decreased dendritic spine density after rmTBI, we focused on DEPP GO enrichment analysis results associated with neuronal function and structure (Table 1) to further identify important molecules that participate in changes in neurons after rmTBI. Creating set intersections of the above GO enrichment analysis results using the UpSet plots tool ( showed that the maximum degree of intersection contained two proteins: Grin1 and Grin2a (Figure 5G). Applying the same method, we generated an UpSet plot of selected KEGG pathway analysis results and found that the maximum degree of intersection contained three proteins: Grin1, Grin2a, and Grin2b (Figure 5H). Thus, Grin1 and Grin2a, two subunits of the N-methyl-D-aspartate receptor (NMDAR), were regarded as potential hub molecules.

Table 1:
GO term and KEGG pathway enrichment analyses results associated with neuronal function and structure

NMDAR is closely linked to synaptic plasticity, learning, and memory. Most research about NMDAR in TBI has focused on NMDAR2 (Osteen et al., 2004; Giza et al., 2006; Park et al., 2013; Mei et al., 2018; Carvajal and Cerpa, 2021), and a role for NMDAR1 phosphorylation in the hippocampus after rmTBI has not been reported. NMDAR1 (also called Grin1) is the basic subunit of NMDAR and is necessary for NMDAR to perform its function (Xia et al., 2005; Wang and Peng, 2016). Therefore, we next tested the role of NMDAR1 in the hippocampal changes observed after rmTBI. Compared with the sham group, NMDAR1 expression was not significantly changed in the hippocampus at 6 weeks in the rmTBI group (Figure 6A). In contrast, phosphorylated NMDAR1 (pNMDAR1) was significantly increased in the rmTBI group compared with the sham group (P = 0.0475) (Figure 6A). These results are consistent with the proteomic and phosphoproteomic results. To examine whether NMDAR1 is involved in the behavioral changes seen in mice after rmTBI, we administered an NMDAR1 antagonist (CGP78608, 10 μM, 200 μL) or vehicle (saline, 200 μL) to the hippocampus before inducing rmTBI (Figure 6B). At 6 weeks after rmTBI, the NOR index of the CGP78608 group was significantly higher than that of the saline group (P = 0.0100; Figure 6C), which suggests that NMDAR1 is necessary for mice to develop cognitive deficits after rmTBI.

Figure 6:
NMDAR1 helps regulate hippocampus-mediated cognitive dysfunction after rmTBI.(A) Western blot of hippocampal NMDAR1 and pNMDAR1. No change in NMDAR1 protein expression was detected (unpaired t-test, t = 1.406, P = 0.2324), and a relative increase in pNMDAR1 protein expression (unpaired t-test, t = 2.827, P = 0.0475) was detected (n = 3). NMDAR1: 105 kDa, pNMDAR1: 105 kDa, Tubulin: 55 kDa. (B) Schematic showing how saline and CGP78608 were injected into the hippocampus. (C) The decreased NOR index induced by rmTBI was almost abolished by treatment with CGP78608, but not saline (n = 6) (unpaired t-test, t = 3.168, P = 0.0100). (D) Interaction network among Grin1 and its upstream kinases. (E) Grin1 PPI network. All data are expressed as the mean ± SEM. *P < 0.05. NMDAR1: N-methyl-D-aspartate receptor 1; NOR: novel object recognition; pNMDAR1: phosphorylation N-methyl-D-aspartate receptor 1; rmTBI: repetitive mild traumatic brain injury.

After confirming the effects of hippocampal NMDAR1 in rmTBI, we explored which kinases were responsible for phosphorylating NMDAR1 in the hippocampus after rmTBI using iGPS/GPS software (http://igps.biocuckoo.org/index.php; http://gps.biocuckoo.cn/). PKC and RAF were identified as two potential protein kinases targeting NMDAR1 (Figure 6D). In addition, PPI analysis showed that 12 upregulated and seven downregulated DEPPs interact with NMDAR1 (Figure 6E), including some that are particularly important for neuron structure and function, namely Map2, Shank2, Shank3, and Syngap1. These molecules are highly promising as key downstream targets of NMDAR1 in the regulation of hippocampal neuronal function after rmTBI.


The aim of our study was to identify potential targets for rmTBI intervention and treatment by investigating the mechanism of cognitive impairment in the hippocampus at the chronic stage of injury through proteomic and phosphoproteomic analyses. First, we found that mice exhibited cognitive impairment at 6 weeks after rmTBI. Then, we showed that the expression of many proteins in the hippocampus was altered after injury, and that most of these proteins are associated with inflammation, immunity, and coagulation, suggesting that inflammation and the immune response persist in the hippocampus after rmTBI. Indeed, these changes in protein expression were seen in non-neuronal cells (astrocytes, microglia, and other cells; Guttikonda et al., 2021). In contrast, most of the DEPPs that we identified between the sham and rmTBI groups were altered in neurons. In keeping with this, the hippocampal pathways that were enriched in DEPPs were clearly associated with the neurodegeneration observed in the injured animals. Enrichment analysis of the DEPPs also identified NMDAR1 as a core molecule participating in rmTBI pathology. Injecting an NMDAR1 antagonist into the hippocampus ameliorated cognitive impairment in mice at 6 weeks after rmTBI. Overall, our findings suggest that NMDAR1 could be an important target for treating cognitive impairment after rmTBI.

Proteomics is an important tool and method for investigating the molecular pathology of neurological diseases, and has been applied to various diseases, such as stroke and neurodegeneration. Numerous studies have used a proteomics approach to analyze the mechanisms of TBI and have identified a variety of potential biological markers and intervention targets (Sowers et al., 2018; Lindblad et al., 2021; Wang et al., 2021; Huang et al., 2022). However, the pathogenesis of rmTBI may involve different alterations at the molecular level compared with single-strike TBI. A previous proteomic study of cortical and hippocampal tissue identified the phosphatidylinositol-3-kinase/AKT (PI3K/AKT) signaling pathway, protein kinase A signaling pathway, peroxisome proliferator-activated receptor alpha and retinoid X receptor alpha (PPARa/RXRa) pathway, gonadotropin-releasing hormone signaling pathway (GNRH), and B-cell receptor signaling pathway (Ojo et al., 2020) as being activated after rmTBI. It is well known that the cortex contains many different brain regions that are responsible for different functions, so performing proteomics for the whole cortex is crude and can obscure changes in individual brain regions consistent with their functions. Because hippocampal damage is closely associated with altered cognitive function, we further explored proteomic changes in the hippocampus. Similar to previous studies, we found that the PI3K/AKT signaling pathway, GNRH signaling pathway, and B-cell receptor signaling pathway are important in rmTBI. We also identified new signaling pathways, such as the complement and coagulation cascades and positive regulation of the immune response, that were significantly linked to hippocampal damage after rmTBI. However, these results are probably more related to the function of non-neuronal cells, such as glial cells, and are not directly reflective of changes in the function of the neurons themselves.

In addition to alterations in protein expression, posttranslational modification (PTM) of proteins is of great importance in neurological disease occurrence and development. A previous study by our group showed that signals detected by phosphoproteomic analysis were more relevant to changes in nerves injured after TBI than those detected by proteomic analysis alone (Huang et al., 2022). Phosphoproteomic studies of rmTBI have also suggested that phosphorylation, an important PTM, plays an essential role in rmTBI (Song et al., 2019; Morin et al., 2022). A recent study (Morin et al., 2022) explored changes in cortical protein phosphorylation in the subacute and chronic stage after rmTBI; however, it did not analyze protein changes in relation to dysfunction. Another advantage of our study is that we focused specifically on the hippocampus, which we believe is more relevant to rmTBI-related cognitive impairment. Comparing the cortical DEPPs from Morin’s study with the hippocampal DEPPs from our study showed that only a few proteins appeared on both lists (Additional Figure 6). In particular, there were fewer DEPPs associated with cognitive function in cortex than hippocampus. For example, we identified several DEPPs in the hippocampus that were enriched in the learning process, but only five of these DEPPs were identified in the cortex. Thus, phosphoproteomic analysis of the hippocampus after rmTBI is more relevant to cognitive impairment than phosphoproteomic analysis of the cortex. Our phosphoproteomic study targeting hippocampal regions identified key signaling pathways, such as the glutamatergic synapse, long-term potentiation, axon guidance, MAPK signaling, Ras signaling, and Alzheimer’s disease pathways. Of these signaling pathways, the glutamatergic synapse, long-term potentiation, axon guidance, and MAPK signaling pathways have been previously reported to be associated with rmTBI (Song et al., 2019; Morin et al., 2022). Ours is the first study to report an association between the Ras signaling and Alzheimer’s disease pathways and rmTBI, although the relationship of these signaling pathways to cognitive function is supported by previous studies (Sweatt and Weeber, 2003; Ye and Carew, 2010; Bruno et al., 2022). Therefore, these signaling pathways identified by phosphoproteomic screening could directly reflect changes in neuron-related functions, which may be important intervention targets.

Additional Figure 6:
Differentially expressed phosphorylated proteins in the cortex, in the hippocampus, and associated with the learning process.

Protein phosphorylation depends on the action of upstream protein kinases, which play an important role in central nervous system pathology. Previous studies have shown that protein kinases, such as AKT/PKB, AMPK, and PKA, participate in rmTBI regulation and play a functional role in pro-survival signaling, energy consumption, and neuroprotection (Shapira et al., 2007; Li et al., 2015; Rozas et al., 2015; Bader et al., 2019). In addition to identifying key kinases with known functions, such as AKT, AMPK, and PKA, our study also found that kinases such as CK2, SGK, and CHK2 may be involved in rmTBI regulation. Among them, CK2 and its downstream molecule GAP-43 play a role in regulating nerve growth in the hippocampus and thus may be new treatment targets for cognitive impairment after rmTBI (Edgar et al., 1997; Blanquet, 2000; Zhu et al., 2019). Our study also found that the same kinase may have opposite functional regulatory effects in different substrates, which may be related to the differential functional regulation of different cell types of kinases after rmTBI; however, this possibility still needs to be verified and explored.

Through comprehensive analysis of DEPs and DEPPs, we found that NMDAR1 may be a hub site for postinjury regulation of hippocampal neurons. Under physiological conditions, NMDAR1 functions as a basic subunit of NMDAR that mediates glutamatergic neuronal transmission and plays a key role in synaptic plasticity, synaptogenesis, excitotoxicity, memory acquisition, and learning (Tingley et al., 1993; Zhou and Wollmuth, 2017). We previously reported that NMDAR-mediated excitotoxicity is an important mechanism underlying secondary injury after TBI (Luo et al., 2019). Altered expression of NMDAR subunits has been widely reported to be associated with TBI (Osteen et al., 2004; Giza et al., 2006; Park et al., 2013; Mei et al., 2018; Carvajal and Cerpa, 2021). However, for specific NMDAR subunits, most research has focused on changes in expression (Additional Table 1). In addition, research on phosphorylation of NMDAR subunits has mainly focused on NR2B. Thus, the role of NMDAR1 phosphorylation in the hippocampus after rmTBI remains unclear. In the present study, we verified the function and effect of NMDAR1 in rmTBI for the first time, and found that inhibiting NMDAR1 in the hippocampus could improve cognitive impairment in mice after rmTBI. Further analysis suggested that RAF and PKC may be the upstream kinases responsible for NMDAR1 phosphorylation. PKC, which mediates β-catenin protein stability via GSK3β phosphorylation to promote axonal remodeling, has been reported to be associated with TBI (Zhang et al., 2019), and the RAF/MEK/MAPK cascade has been reported to play an important role in TBI-induced brain edema and neuronal damage (Lu et al., 2008). Moreover, we identified some proteins that may be downstream effectors of phosphorylated NMDAR1, such as Map2, Shank2/3, and Syngap1. Map2, microtubule-associated protein 2, regulates microtubule structure and stability, neuronal morphogenesis, cytoskeletal dynamics, and organelle transport in neuronal axons and dendrites (Sanchez et al., 2000). Shank is a scaffold protein in the postsynaptic dense region of neurons, and studies have shown that it is involved in autism and neurodegenerative diseases (Grabrucker et al., 2011). Syngap1 is mainly localized in the dendritic spines of neurons and inhibits signaling pathways related to NMDA receptor-mediated synaptic plasticity and AMPA receptor intramembrane insertion (Hamdan et al., 2009).

Additional Table 1:
Summary of previous research on the association between NMDAR and traumatic brain injury

Our study had several limitations. First, we focused exclusively on the hippocampus, while changes in other brain areas may also account for the cognitive dysfunction seen after rmTBI. Future studies on changes in protein expression in different brain areas may help reveal the unique molecular mechanisms of pathogenesis after rmTBI that relate to the observed biological phenotypes. Second, we specifically analyzed neurons, while other cell types such as glial cells play important roles in the nervous system, and studying them separately could help implement targeted intervention measures. Finally, in terms of mechanism, we have only preliminarily verified the role of NMDAR1 in the chronic phase of rmTBI, and its specific regulatory mechanism needs further in-depth verification and research. In the future, we will continue to conduct comprehensive studies in a model of mild traumatic brain injury and strive to fully reveal the pathological mechanism.

In conclusion, our study showed that the hippocampus was damaged and mice developed cognitive impairment after rmTBI. Furthermore, we found the increased phosphorylation of NMDAR1 was involved in the development of cognitive impairment in mice after rmTBI.

Author contributions:Study design: PL, XL, XJ; experimental implementation: ZT, ZC, EY, JL; experimental assistance: DL, FW, TW, ZZ, HZ; data analysis and figure production: ZT, ZC; manuscript writing, editing and reviewing: ZT, PL. All authors read and approved the final version of the manuscript.

Conflicts of interest:The authors declare no conflict of interest.

Data availability statement:All relevant data are within the paper and its Additional files.

Additional files:

Additional Figure 1: The impact device.

Additional Figure 2: Global proteomic analysis.

Additional Figure 3: Heatmap of differentially expressed proteins enriched in three biological processes.

Additional Figure 4: Global phosphoproteomic analysis.

Additional Figure 5: All phosphorylation motifs, including serine motifs (A) and threonine motifs (B).

Additional Figure 6: Differentially expressed phosphorylated proteins in the cortex, in the hippocampus, and associated with the learning process.

Additional Table 1: Summary of previous research on the association between NMDAR and traumatic brain injury.

C-Editors: Zhao M, Li CH; S-Editor: Li CH; L-Editors: Crow E, Li CH, Song LP; T-Editor: Jia Y


We gratefully thank Jingjie PTM BioLab (Hangzhou) Co. Inc for its technical support in proteomic and phosphoproteomic.


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cognitive impairment; Grin1; hippocampus; learning; memory; N-methyl-D-aspartate; N-methyl-D-aspartate receptor 1; phosphoproteomic; proteomic; repetitive mild traumatic brain injury (rmTBI); secondary injury

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