Next Article in Journal
Laccase-Mimicking Cu-Tannic Acid Nanozyme for Zearalenone Detoxification: Mechanism and Application in Corn Oil
Previous Article in Journal
Impact of Storage Duration on the Structural and Functional Properties of Starch in Spicy Strips
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Gut–Brain Metabolic Remodeling Mediates the Neuroprotective Effects of Combined Shrimp and Corn Peptides in Scopolamine-Induced Cognitive Impairment

1
State Key Laboratory of Marine Food Processing & Safety Control, School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, China
2
National Engineering Research Center of Seafood, School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, China
3
Ganzhou Quanbiao Biological Technology Co., Ltd., Ganzhou 341100, China
*
Author to whom correspondence should be addressed.
Foods 2026, 15(5), 827; https://doi.org/10.3390/foods15050827
Submission received: 4 January 2026 / Revised: 2 February 2026 / Accepted: 22 February 2026 / Published: 2 March 2026
(This article belongs to the Section Nutraceuticals, Functional Foods, and Novel Foods)

Abstract

(1) Background: Bioactive peptides from marine and plant sources show neuroprotective potential, yet how their combination ratios affect memory regulation via the gut–brain axis remains unclear. This study investigated the effects of different ratios of marine peptide QMDDQ (Glutamine-Methionine-Aspartate-Aspartate-Glutamine) and plant peptide AGLPM (Alanine-Glycine-Leucine-Proline-Methionine) on scopolamine-induced memory impairment in mice. (2) Methods: Cognitive function was assessed using the Morris water maze and novel object recognition tests. Nissl staining, microplate-based assays for acetylcholine (ACh) content and acetylcholinesterase (AChE) activity, Western blotting for neurotrophic factors, LC-MS/MS-based intestinal peptide profiling, and HPLC-based brain amino acid analysis were performed. (3) Results: The 1:1 ratio most effectively restored learning and memory, regulated hippocampal cholinergic function, mitigated neuronal damage, and elevated BDNF, NGF, and NTF-3 expression. In the gut, peptides were hydrolyzed into glutamate- and proline-rich fragments, which influenced brain amino acid balance by elevating glutamate and proline levels while reducing NH3-related signaling. (4) Conclusions: These results highlight the ratio-dependent efficacy of QMDDQ-AGLPM combinations and provide evidence for a gut peptide remodeling-brain metabolic link relevant to cognitive impairment.

Graphical Abstract

1. Introduction

Global life expectancy is rising, and with it the prevalence of age-related cognitive decline. Accordingly, the demographic structure has changed, with a greater proportion of older people and an increase in the prevalence of age-related diseases [1]. Mounting evidence shows that chronic stress, now common among younger adults, raises Alzheimer’s disease (AD) risk and worsens its course [2,3]. There is therefore an urgent need for effective strategies to mitigate the increasing burden associated with AD. Despite extensive basic and clinical research around the world, effective interventions remain limited, and it is difficult to intervene directly without specific drugs for such diseases [4,5]. Therefore, it is crucial to develop functional foods that can improve memory. Shrimp and corn are widely consumed food sources, and their protein hydrolysates have attracted attention for their safety and high biological value.
AD, which constitutes 60–70% of the approximately 50 million dementia cases globally, is typified by progressive cognitive decline, particularly in memory, thinking, and reasoning abilities. A wealth of research has demonstrated that this debilitating neurodegenerative disorder is inextricably linked to dysregulation of the cholinergic system [6]. AD symptoms emerge as cholinergic synapses deteriorate, acetylcholine (ACh)-receptor subtypes are lost, and ACh-producing neurons die [7]. Cholinergic neurons are widely distributed in the human brain. Cholinergic signaling associated with memory and learning depends on ACh. ACh levels can be influenced by the central cholinergic nervous system by regulating the synthesis and release of ACh [8]. Acetylcholinesterase (AChE) is a key enzyme responsible for the degradation of acetylcholine, thereby terminating postsynaptic signaling. The cholinergic system plays a crucial role in regulating neurogenesis, neuronal differentiation, synaptic plasticity, and neuroprotection in the central nervous system [9]. Scopolamine has been utilized as a pharmacologic model for cognitive impairment in dementia and AD [10]. It compromises learning and memory abilities by promoting AChE activity and inhibiting ACh [11]. Zeng investigated the effects of water-soluble ginseng oligosaccharides on the cholinergic system using scopolamine-induced cholinergic dysfunction in mice [12]. Meanwhile, Yun investigated the alleviating effects of sesamol on cognitive dysfunction using a mouse model induced by scopolamine [13]. Wu et al. reported that combined QMDDQ + AGLPM reversed scopolamine-induced amnesia while restoring hippocampal ACh and AChE levels. [14]. However, how different combination ratios influence cognitive outcomes and gut–brain-related metabolic readouts remains unclear.
Natural and non-toxic active substances are increasingly popular, with various plants. Studies indicate that the synergistic effects of multiple substances can yield benefits greater than the sum of their individual effects. Specifically, Vitis vinifera L. and Centella asiatica demonstrate synergistic protective effects against hepatic injury through their antioxidant, anti-inflammatory, and anti-apoptotic properties, effectively combating oxidative stress, inflammation, and apoptosis [15]. Shen demonstrated that collagen peptides and taurine work synergistically to mitigate hypertensive kidney injury induced by a high-salt diet through the gut–kidney axis [16]. Liu reported that benzyl isothiocyanate and resveratrol exhibited synergistic effects by remodeling intestinal flora and modulating serum levels of inflammatory cellular factors, thereby providing a protective effect against colitis [17].
Neurotrophic factors are a class of proteins that play an important role in neuronal development, survival, and apoptosis, and are a collection of structurally and functionally related proteins. Its members include Nerve Growth Factor (NGF), Brain-Derived Neurotrophic Factor (BDNF), Neurotrophic Factor 3 (NTF-3), etc., and these proteins are potential drug targets for the treatment of neurological injuries and other diseases. NGF is expressed in neuronal and non-neuronal cells of the central and peripheral nervous system. Various regions of the brain, such as the hippocampus, cortex, and pituitary, are thought to have the highest NGF expression. In contrast, BDNF is expressed in areas such as the hippocampal region, cerebral cortex, cerebellum, and amygdala [18]. Neurotrophic factor can bind to two different classes of receptors, the p75 neurotrophic factor receptor and the pro-myosin receptor kinase receptor. There is growing evidence that BDNF and NGF are key regulators of AD pathology [19].
Beyond central neurotrophic regulation, the gut–brain axis (GBA) was an important medium that connected dietary components with brain health. Communication between the gut and the brain occurred through neural, immune, endocrine, and metabolic pathways, allowing intestinal metabolites to modulate central nervous system function [16]. In particular, dietary peptides hardly came back into the brain. Rather, they were heavily hydrolyzed in the gut into small peptides that may interfere indirectly in neuroprotective regulation of neurotransmitter production, energy metabolism, and signaling. Amino acids were known to play important signaling roles in brain function. Amino acids were not only building blocks for protein synthesis, but also precursors of different neurotransmitters and were responsible for energy metabolism and redox homeostasis, in a manner that can have effects on neuronal survival and synaptic plasticity [20]. Amino acid changes in the intestines could affect central amino acid and neurotransmitter balance, thus affecting cognitive functioning.
This study aimed to investigate the molecular mechanisms by which scopolamine-induced memory damage in mice was improved by different ratios of shrimp peptide QMDDQ (Glutamine-Methionine-Aspartate-Aspartate-Glutamine) and corn peptide AGLPM (Alanine-Glycine-Leucine-Proline-Methionine) through the regulation of the GBA. The synergistic neuroprotective effects of the two peptides were validated by behavioral methods and tissue biochemical indicators. Potential neuroprotective mechanisms were explored by histological analysis and Western blotting. Molecular mechanisms underlying GBA-mediated neuronal protection were investigated via intestinal peptide identification and brain-tissue amino acid analysis. Theoretical support for the synergistic enhancement of memory function by peptide substances was provided by this study, and a foundation for future functional-food development was laid.

2. Materials and Methods

2.1. Materials and Chemicals

Shrimp peptides Gln-Met-Asp-Asp-Gln (QMDDQ) and the corn peptide Ala-Gly-Leu-Pro-Met (AGLPM) were chemically synthesized by Cellmano Biotech Limited Corporation (Hefei, China). Scopolamine was provided by Aladdin (Shanghai, China). The experimental kits, ACh (A105-1-1) and AChE (A024-1-1), were procured from Nanjing Jianjian Bioengineering Institute (Nanjing, China). NGF, NTF-3, β-actin, and secondary antibodies were purchased from ABclonal Co., Ltd. (Wuhan, China). BDNF was purchased from Beyotime Biotechnology Co., Ltd. (Shanghai, China). All the remaining reagents used were of analytical grade.

2.2. Animals and Experiment Design

Kunming mice (male, 7 weeks old, 30–40 g) were purchased from Liaoning Changsheng Biotechnology Co., Ltd. Mice were housed at 25 ± 2 °C and 50 ± 15% relative humidity under a 12 h light/dark cycle, with free access to food and water. All animal procedures were approved by the Animal Ethics Committee of Dalian Polytechnic University (approval No. DLPU2024076), and efforts were made to minimize animal suffering. The animal experimental procedure is shown in Figure 1A. After 7 days of acclimatization, 50 mice were randomly allocated into five groups (n = 10 per group): Con, Scop, 2:1, 1:1, and 1:2. The Con and Scop groups received saline by gavage. Peptide-treated groups received a fixed daily 30 mg/kg mixture (shrimp:corn = 2:1, 1:1, or 1:2) dissolved in saline (0.2 mL) by gavage for 40 days.
From day 31, saline was injected intraperitoneally for 10 consecutive days in the control group, whereas scopolamine (1 mg/kg/day) was injected intraperitoneally in the remaining four groups. Gavage administration was continued during the intraperitoneal injection period. Mice were weighed on Days 0, 10, 20, 30, and 40. The Morris water maze (MWM) consisted of training sessions (Days 5–9, 19, 27, and 37) and a testing phase (Days 10, 20, 28, and 38). Novel object recognition (NOR) training and testing were conducted on Days 29–30 and 39–40. Body composition was measured on Days 30 and 40. At the conclusion of the experiment, all mice were euthanized under isoflurane anesthesia. Tissues were immediately removed and stored at −80 °C for subsequent analysis.

2.3. Morris Water Maze Test

The Morris water maze test (MWM) was conducted according to the method of Lu et al. with slight modifications [21]. The experimental apparatus consists of a circular water tank measuring 100 cm in diameter and 40 cm in height, along with a circular platform with a diameter of 10 cm. The tank is divided into four equal quadrants, with the platform fixed in Quadrant I and kept stationary. Prior to the experiment, warm water is added to a level 1 cm above the platform. The experiment comprises training and testing phases. Training is performed on days 5–9 (4 trials per day), 19 (4 trials), 27 (4 trials), and 37 (4 trials). During training, if unsuccessful within 60 s, they are guided to the platform and allowed to remain there for 20 s. Probe tests with the platform removed were conducted on days 10, 20, 28, and 38. For probe tests on days 10 and 20, escape latency to the former platform location was recorded manually. For probe tests on days 28 and 38, swimming trajectories were analyzed using Smart 3.0 software to measure time in the target quadrant and platform crossings. All swimming trajectories and quantitative data were analyzed using Smart 3.0 tracking software. After testing, the mouse is immediately dried and returned to its original cage.

2.4. Novel Object Recognition Test

Novel object recognition test (NORT) is a method of assessing short-term memory that relies on hippocampal function [22]. The experimental setup was a 40 × 40 × 40 cm cardboard box. On days 29 and 39, the mice first received a 5 min empty-box habituation, followed by a 10 min familiarization session with two identical green cubes. Twenty-four hours later (day 30 or 40), they were tested for 5 min with one cube replaced by a novel object (day 30: red cylinder, day 40: purple triangular block). The mice were again placed in the cardboard box to explore freely for five minutes, recording the time the mice spent exploring each of the two objects within 2 cm or even less of the object block. The cartons and blocks were cleaned using 75% ethanol before the start of each experiment to eliminate the effect of odor on the results. The recognition index is the ratio of the time a mouse spends exploring the novel object to the total time spent exploring both objects.

2.5. Body Composition Analysis

According to Madhu, with slight adjustments, we measured the lean muscle mass, fat, and free water content of each group of mice [23]. The mice were fasted for 12 h prior to low-field (0.5 T) MRI (MesoMR23-060V-1, Niumag, Shanghai, China). They were placed in plastic imaging tubes and restricted at the bottom of the cylinder. The imaging tubes were oriented horizontally within a 60 mm radio-frequency coil. A multislice spin-echo sequence (TR 2000 ms, TE 20 ms, slice thickness 2 mm, in-plane resolution 0.47 × 0.47 mm2) was applied, and fat, lean-muscle, and free-water compartments were automatically segmented by the instrument’s built-in T2-threshold algorithm (NMR-Analyzer v4.0), allowing for the determination of the body composition of the mice via MRI.

2.6. Detection of Physical Indexes in Mice

The methods were modified with reference to Yan [24]. After the mice were euthanized, the heart, liver, spleen, kidney, lung, brain, and hippocampus were removed, and the liquid on the surface was gently wiped dry. The coefficients of each organ were calculated according to the following formula: Organ index (mg/g) = organ weight (mg)/body weight (g).

2.7. Tissue Storage and Preparation

Tissue fixation was performed with reference to Zhao’s method by placing the brains, livers, and jejunum of the removed mice in centrifuge tubes containing 4% paraformaldehyde fixative at room temperature [25]. After 24 h, the old solution in the centrifuge tube was replaced with a new paraformaldehyde solution. The fixed tissues were rinsed three times with double-distilled water to remove the 4% paraformaldehyde fixative from the tissues, and then dehydrated in a stepwise manner in 70–100% ethanol solution for 30 min. After 15 min of xylene clearing, the tissues were embedded in xylene-paraffin and kept at 50 °C for 40 min. After removal, the tissues were sealed with paraffin around the embedding cassette, cooled and dried, and used for subsequent experiments.

2.8. Hematoxylin and Eosin (HE) Staining in the Liver and Jejunum of Mice

H&E staining of mouse tissues was performed according to the method described by Luo with modifications [26]. The embedded liver and jejunum were sectioned at 5 μm using a paraffin microtome. Slices were blanched in hot water and dried. The dewaxing treatment was carried out by immersion in xylene solution for 30 min, followed by immersion in xylene and ethanol. Finally, a stepwise 100–70% ethanol solution immersion for 30 min was performed for HE staining. The sections were stained using an HE staining kit, which included hematoxylin for 9 min and eosin for 1 min. After staining was completed, morphological and pathological changes in the tissues were observed using a microscope at 20×.

2.9. Nissl Staining in the Hippocampus of Mice

Sections of brain wax blocks that had been cut into 5 μm were deparaffinized using xylene and gradually hydrated using ethanol [11]. Sections were stained for 60 min at 56 °C using Nissl staining solution (cresyl violet). The slices were soaked in distilled water for 5 min to remove floating color, infiltrated with a gradient of ethanol solution (70–100%), and then cleared with xylene twice for 5 min each. Neutral gum was used to seal the slices and stored away from light for histopathological observation. Hippocampal CA1 and CA3 regions were observed using a microscope and analyzed for the number of Nissl bodies within intact neurons. Intact neurons were defined as those with a continuous plasma membrane, a distinct nucleolus, and visible Nissl substance. Nissl bodies were manually counted as discrete, deep blue-violet-stained granules within the somata of these intact neurons. Three mice per group were examined; for each mouse, two non-overlapping fields, each of CA1 and CA3, were imaged and manually counted.

2.10. Determination of the ACh Content and AChE Activity

After the mice were euthanized, the hippocampus was rapidly stripped on ice and frozen in liquid nitrogen. Hippocampus was ground with saline on ice in the ratio of 1:9, and the resulting suspension was centrifuged at 4 °C (12,000× g for 15 min), and the supernatant was collected [27]. The protein concentration in the supernatant was determined using a BCA protein assay kit. ACh content was measured using a microplate-based colorimetric assay kit (A105-1-1, Nanjing Jiancheng Bioengineering Institute, Nanjing, China) based on the hydroxylamine-iron chloride method. The absorbance was measured at 550 nm using a microplate reader. AChE activity was determined using a microplate-based colorimetric assay kit (A024-1-1, Nanjing Jiancheng Bioengineering Institute, China) based on the Ellman method. The absorbance was measured at 412 nm using a microplate reader. Each assay was performed on n = 3 mice per group.

2.11. Western Blot Analysis

Western blotting analysis was conducted according to the method of Xu with modifications [28]. The hippocampus was ground in RIPA lysis buffer and added to PMSF. The protein concentration of the supernatant obtained after centrifugation (Legend Micro 17R, Thermo Fisher Scientific, Waltham, MA, USA) was determined by the BCA kit (Nanjing Jiancheng, Nanjing, China). The sample was added to the sodium dodecyl sulfate (SDS) sample buffer and boiled. 30 μg protein was loaded per lane. The proteins were separated by SDS-polyacrylamide gel using a Mini-PROTEAN Tetra electrophoresis bath (Bio-Rad, Hercules, CA, USA) and transferred to PVDF membranes. The membranes closed with 5% non-fat dried milk of TBST were incubated with the primary antibody (β-actin, BDNF, NGF, and NTF-3) at 4 °C overnight: β-actin (1:10,000, AC038), BDNF (1:1000, AF1423), NGF (1:1000, A13922), NTF-3 (1:2000, A3179). The membrane was washed three times with TBST, then incubated with the secondary antibody (AS014 1:10,000) at room temperature for 1 h. Finally, the supersensitive ECL (P0018S, Beyotime Biotechnology, Shanghai, China) chemiluminescence reagent was used to make the strip color, the gel imager took pictures, and the Image J software v1.54d performed gray level analysis.

2.12. Intestinal Fluid LC-MS/MS Analysis and Data Processing

Peptide profiles in intestinal fluid were analyzed by LC-MS/MS following Xue [29] with minor modifications. After 3 kDa ultrafiltration (Ultrafiltration Spin Columns, Millipore, Billerica, MA, USA) and C18 desalting (Pierce C18 Spin Tips, Thermo Fisher Scientific, Waltham, MA, USA), samples (0.1 µL) were injected into an UltiMate 3000 RSLCnano coupled to an Orbitrap Eclipse (Thermo Fisher Scientific, Waltham, MA, USA). Separation was performed on a 25 cm × 75 µm column packed with 1.9 µm resin (Dr. Maisch GmbH, Ammerbuch, Germany) at 40 °C and 400 nL min−1 using a 60 min gradient of 0.1% formic acid in water (A) and 80% acetonitrile with 0.1% formic acid (B): 2.2–44% B in 45 min, then 90% B for 12 min. DDA settings: full scan 200–1200 m/z at R = 60,000 (AGC 4 × 105, 50 ms); MS2 via HCD 30% at R = 15 000 (AGC 5 × 104, 22 ms, 30 s dynamic exclusion). Data were processed with PEAKS Studio 12 (Bioinformatics Solutions Inc., Waterloo, ON, Canada). Samples consisted of pooled intestinal fluid from 10 mice per group, measured once. Searches were run against a custom-target database plus Mus musculus UniProt 2024 (21,709 entries), precursor tolerance 10 ppm, fragment 0.02 Da, variable mods Oxidation (M) and Deamidation (N, Q). Peptides were accepted at −10lgP ≥ 20, and proteins required ≥ 1 unique peptide. Each group consisted of a single pooled sample (n = 10 mice); no statistical tests or FDR correction were applied; differences are reported as descriptive trends.

2.13. Amino Acid Analysis

Amino acids were determined by acid hydrolysis followed by pre-column derivatization and HPLC [30]. The total amino acid composition released after complete hydrolysis of brain protein was detected. Freeze-dried brain was suspended in 6 mL of 1:1 6 M HCl, N2-flushed, and sealed. Hydrolysis was performed at 110 °C for 24 h. After cooling, the hydrolysate was diluted to 100 mL with ultrapure water. An aliquot (2 mL) was dried at 60 °C and reconstituted in 0.02 M HCl. The solution was filtered through a 0.22 μm aqueous membrane before injection. Samples consisted of pooled half-brains from 3 mice per group, measured once. Quantification was carried out a Hitachi LA-8080 amino-acid analyzer (Hitachi, Tokyo, Japan) equipped with a Hitachi 2622F ion-exchange column (4.6 × 60 mm, 3 µm) operated at 57 °C with post-column ninhydrin derivatization, using external standards and calculated as: content (%) = c × V/m × 100, where c is the mass concentration given by HPLC (mg mL−1), V is the final volume (mL), and m is the sample mass (mg). Each group was analyzed as a single pooled sample (3 mice pooled); no statistical tests or FDR correction were applied.

2.14. Statistical Analysis

Statistical analysis and data processing were performed using GraphPad Prism 9.0. All quantitative data are presented as the mean ± standard deviation (SD). Normality was verified by the Shapiro–Wilk test (p > 0.05) before analysis of variance (ANOVA). Comparisons among groups were analyzed using one-way analysis of variance (ANOVA). One-way ANOVA followed by Tukey’s multiple comparisons test was performed. p < 0.05 was considered statistically significant. For data visualization, Sankey diagrams were constructed using SankeyMATIC (http://sankeymatic.com, accessed on 4 December 2025). Heatmaps were generated using TBtools-II v2.323. Venn diagrams and stacked bar charts were plotted using the online platform bioinformatics.com (accessed on 4 December 2025). Polar bar charts were created using the ggplot2 package in the R programming language, and network diagrams were visualized using Cytoscape v3.10.4).

3. Results

3.1. Assessment of General Health and Safety Profile of Marine and Terrestrial Heterologous Polypeptides QMDDQ and AGLPM on Mice

To evaluate the potential toxicity and physiological impact of the QMDDQ and AGLPM peptides at different ratios, a comprehensive safety assessment was conducted. Body weight was monitored as a primary indicator of health status. As illustrated in Figure 1B, a steady upward trend in body weight was exhibited by mice in the control, Scop, and three peptide intervention groups (2:1, 1:1, and 1:2) throughout the 41-day experimental period. There were no statistically significant differences between groups at any time point (p > 0.05). To further investigate fat and lean tissue distribution in mice, body composition was analyzed using MRI on days 30 and 40 (Figure 1C,D). Consistent with the body weight results, no significant differences were observed in the proportions of lean muscle, fat, or free water among the five groups (p > 0.05). In addition, organ coefficients were calculated for the lung (Figure 1E), spleen (Figure 1F), liver (Figure 1G), kidney (Figure 1H), and heart (Figure 1I). No significant differences in these indices were revealed by statistical analysis among the five groups of mice (p > 0.05). Safety was further confirmed by histological examinations (Figure 1J). In H&E-stained liver sections, hepatocytes were arranged in regular cords, and no signs of necrosis or fatty degeneration were observed. Similarly, intact mucosal structures with neatly arranged villi were displayed in the small intestine.

3.2. Protective Effects of Marine and Terrestrial Heterologous Polypeptides on Spatial Memory and Learning Impairments in Behavioral Test in Mice

Cognitive function was assessed using MWM and NORT (Figure 2A). No significant differences were observed in probe trials on Days 10 and 20 (Supplementary Figure S2). Figure 2B shows the swimming trajectories of mice in the Morris water maze after 28 days of gavage (green and red dots indicate the start and end positions, respectively). In Figure 2C, the peptide-treated groups crossed the platform (removed) slightly more often than the control group, but the difference was not statistically significant (p > 0.05). However, as shown in Figure 2D,E, the 1:1 group exhibited a significantly higher proportion of time spent in the target quadrant compared to the control group (p < 0.01). Additionally, the latency to first platform access was significantly shorter in the peptide-treated groups (2:1 and 1:1) than in the control group (p < 0.05). Figure 2F displays the swimming trajectories of mice in the Morris water maze after scopolamine-induced modeling. Figure 2G–I reveals that the Scop group exhibited significantly reduced platform crossings and time spent in the target quadrant compared to the control group, along with a significantly prolonged latency to first platform arrival (p < 0.001), confirming successful establishment of the memory impairment model. Peptide intervention significantly reversed these cognitive deficits, with the 1:1 dosage group demonstrating the most pronounced improvement in memory impairment. As shown in Figure 2J, on day 30, the peptide-treated groups exhibited improved performance in the NORT compared to the control group, with the 1:1 group showing the most significant improvement (p < 0.01). On day 40 (Figure 2K), the Scop group demonstrated significantly lower recognition ability than the Con group (p < 0.01). Nevertheless, the peptide-treated groups showed improved cognitive performance compared to the Scop group. Notably, the 1:1 group displayed the most significant recovery (p < 0.05).

3.3. Effects of Three Different Ratios of QMDDQ and AGLPM on Hippocampal Neuronal Morphology and Cholinergic Neurotransmission in Mice

Memory formation was related to neuronal morphology. As depicted in Figure 3A, a large number of normal neuronal cells with regular shape and tightly ordered arrangement were observed in the Con group in both CA1 and CA3 regions (indicated by yellow arrows). In contrast, most neurons in the CA3 region of the scop group showed severe atrophy and shrinkage, while some neurons in the CA1 region were damaged (red arrows). Neuronal cell damage was improved in all three groups of mice with combined gavage of QMDDQ and AGLPM, with an increase in the number of rounded, intact neuronal cells compared to the Scop group. To quantitatively assess the functional status of neurons, we quantified Nissl bodies, with the analysis specifically focused on morphologically intact neurons. As shown in Figure 3B,C, the Scop group had the lowest number of Nissl bodies, indicating that intraperitoneal injection of scopolamine caused neuronal damage in mice. Compared with the Scop group, all three groups of QMDDQ and AGLPM that combined gavage effectively increased the number of Nissl bodies in the CA1 and CA3 regions, with the 1:1 group having the most Nissl bodies (p < 0.0001).
ACh and AChE are key biomarkers for assessing cognitive performance in mice. As depicted in Figure 3D, the Scop group exhibited the lowest ACh content (p < 0.0001). In contrast, 2:1, 1:1 and 1:2 groups had significantly increased levels of ACh (p < 0.0001), with the 1:1 group exhibiting the highest level of ACh. Figure 3E illustrates the activity of hippocampal AChE across five groups of mice. The Scop group exhibited the highest enzyme activity. AChE activity was significantly reduced in the 2:1, 1:1, and 1:2 groups, with the 1:1 group showing the most significant decrease (p < 0.0001).

3.4. QMDDQ and AGLPM Ameliorate Scopolamine-Induced Memory Deficits by Activating the BDNF/NGF/NTF-3 Pathway

BDNF, NGF, and NTF-3 are members of the neurotrophic factor family. They maintain neuronal survival and promote synaptic plasticity by activating Trk receptors, thereby enhancing learning and memory capabilities in mice. Figure 4A presents the representative Western blot images of BDNF, NGF, and NTF-3 in the hippocampal tissues of the five groups. As shown in Figure 4B–D, the Scop group showed the lowest protein expression levels of BDNF, NGF, and NTF-3. Relative to the Scop group, the 2:1 and 1:1 groups exhibited significant up-regulation of BDNF, NGF, and NTF-3 protein expression levels (p < 0.01). These results indicated that peptide treatment can effectively restore neurotrophic factor levels in mice, with 2:1 and 1:1 groups demonstrating the most significant efficacy.

3.5. Effects of Three Different Ratios of QMDDQ and AGLPM on Functional Peptide Profiling in Mice Intestines

The results described above demonstrated that QMDDQ and AGLPM treatment effectively ameliorate memory deficits in mice. To further explore the mechanisms by which these three peptide preparations modulate the GBA, the peptide profiles in intestinal fluid and amino acid levels in brain tissue were analyzed. As shown in Figure 5A, mass spectrometry (MS) analysis of the intestinal fluid identified a total of 47,485 peptides. Notably, no intact QMDDQ or AGLPM sequences were detected. However, numerous peptides containing Glu, Gly, and Pro (e.g., EAGL, GLP, and AGASGV) were observed. Among them, the highest total number of peptides and the largest shared intersection with other groups were exhibited by the 1:1 group. As depicted in Figure 5B,C, abundance patterns were further characterized by cluster and Z-score heatmaps derived from 25 representative peptide segments. Specifically, significantly higher enrichment of peptide segments, particularly EAGL, GLP, GEFDQGS, and HEALPM derivatives, was demonstrated by the 1:1 group. Notably, QMDDQ degradation was associated with GEFDQ-related fragments (rich in Glu/Gln), while EALPM/GLP fragments were determined to be derived from AGLPM. It was confirmed by Z-score analysis that these fragments were higher abundance in the 1:1 group compared with the control or Scop groups. This observation was further supported by the peak area bar chart (Figure 5D), in which the higher peak areas for peptides such as AGV and GEFDQGS were achieved in the 1:1 group.

3.6. Effects of Three Different Ratios of QMDDQ and AGLPM on Amino Acids in Mice

To visually evaluate the remodeling effect of different peptide ratios on the cerebral metabolic environment, amino acids and metabolites in brain tissues were categorized into four functional modules: memory-related amino acids (green), peptide-derived amino acids (blue), negatively correlated metabolites (red), and other amino acids (gray). These were visualized using polar bar charts (Figure 6A). In the Scop group, an increased NH3-related signal in the acid-hydrolyzed amino acid profile was observed. Peptide treatment mitigated this increase to varying degrees, with the 2:1 and 1:1 groups effectively maintaining a lower relative NH3 proportion in the brain hydrolysate. Glutamate (Glu), Serine (Ser), and Tyrosine (Tyr) were maintained at the highest levels in the 1:1 group. Additionally, the 1:1 group exhibited the highest Proline (Pro) levels in brain tissue. As shown in Figure 6B, the Scop group had the highest NH3 proportion in the hydrolysate, while the combined QMDDQ and AGLPM treatment reduced this proportion, with the 1:1 group showing the lowest NH3 proportion. As depicted in Figure 6C, functional amino acids were generally depleted in the Scop group, whereas the 1:1 group transitioned toward enriched states. In summary, the 1:1 group exhibited the highest levels of amino acids such as Glu and Pro, along with the lowest NH3-related signal in the hydrolysate.

4. Discussion

Research indicated that shrimp and corn peptides enhanced learning and memory capabilities. However, previous studies had primarily focused on their regulatory effects on synaptic plasticity [31,32]. However, the synergistic mechanisms by which the combined administration of these peptides operates via the GBA remain largely unexplored. In this study, we provide the first demonstration that co-administration of QMDDQ and AGLPM at different ratios significantly ameliorates scopolamine-induced cognitive impairment. Crucially, this therapeutic effect is mediated by the remodeling of the GBA, the restoration of cholinergic homeostasis, and the upregulation of neurotrophic factors.
Safety is a prerequisite for evaluating bioactive peptides. Throughout the 41-day intervention, neither altered body-weight gain nor abnormal MRI-based body composition was detected, indicating that scopolamine specifically affected the nervous system without inducing systemic physiological changes or obesity [33]. The absence of pathological alterations in liver and small-intestine sections, together with stable organ coefficients, suggests that oral administration of QMDDQ and AGLPM caused no gastrointestinal irritation or barrier compromise. These findings align with previous reports that food-derived hydrolysates are generally safe [34].
Behavioral experiments serve as a crucial method for evaluating learning and memory capabilities in mice. This study employed the MWM and NORT to investigate the effects of different ratios of QMDDQ and AGLPM on learning, memory, and cognitive abilities in mice. The MWM assesses spatial learning and memory in rodents [35], and it is widely used to examine hippocampal-dependent memory [36]. The peptide-treated group, particularly the 1:1 group, significantly reversed scopolamine-induced reductions in platform crossings and target quadrant dwell time, suggesting not only restoration of spatial navigation abilities but also effective improvement of scopolamine-induced long-term memory impairment. The NORT is a simple, widely used non-spatial memory behavioral test that relies on rodents’ innate ability to explore novelty in the absence of external stimuli [37]. The enhanced novel object recognition ability in the peptide-treated group further demonstrates that peptide treatment, particularly in the 1:1 group, improves non-spatial recognition memory in mice. Melgar-Locatelli demonstrated that a high-flavanol cocoa diet enhances long-term object recognition memory in adult mice by upregulating BDNF expression and promoting neuronal proliferation [38]. This indicated that the QMDDQ-AGLPM combination significantly ameliorates scopolamine-induced learning and memory deficits, with the 1:1 ratio showing the most pronounced effect.
The structural integrity of hippocampal neurons is closely related to memory. Neurons, as the basic components of the nervous system, play an important role in memory formation, and a more complete neuronal cell structure contributes to memory formation and storage [39]. Nissl bodies are important structures within neurons. Their morphology and quantity serve as key indicators for assessing neuronal functional activity. Nissl bodies are particularly abundant in metabolically active neurons. Neuronal injury or overexertion reduces Nissl bodies to dust-like fragments; with rest or repair, these granules regenerate and swiftly regain their normal abundance [40]. Hence, the abundance of Nissl bodies serves as a proxy for neuronal health, and Nissl staining provides a simple means to quantify them. Scop caused a marked reduction in Nissl bodies in CA1/CA3, whereas QMDDQ-AGLPM (1:1) largely restored their abundance. The results showed that combined gavage of QMDDQ and AGLPM ameliorated neuronal shape abnormalities caused by scopolamine. Building on this rescue of morphology, the accompanying restoration of Nissl-body abundance implies that the peptide complex may promote repair and regeneration of damaged neurons by activating intracellular protein-synthesis mechanisms. Weng demonstrated that glabridin was able to restore the number of Nissl bodies in mice with LPS-induced cognitive decline, thereby reducing neuroinflammation [41]. Therefore, combined QMDDQ and AGLPM intragastric administration can improve neuronal morphological abnormalities and loss of Nissl bodies, thereby mitigating scopolamine-induced memory impairment.
The central cholinergic system helps regulate memory formation and facilitates the transmission of inter-neuronal or neuron-to-effector signaling [42]. Mice with reduced ACh levels in the brain show reduced social interactions and impaired memory, and cholinergic transmission in the hippocampus is important for regulating memory [43]. QMDDQ-AGLPM (1:1) reversed the scopolamine-induced AChE/ACH imbalance. This indicates that the combination of these two peptides can inhibit the abnormal elevation of AChE activity in mice and reduce ACh hydrolysis. AChE metabolizes ACh in the synaptic cleft into acetic acid and choline, and hyperactivity of AChE may lead to ACh deficiency, interrupting cholinergic neurotransmission and leading to learning and memory problems [44]. These findings support the concept that regulating AChE and ACh levels is a key mechanism by which QMDDQ and AGLPM modulate the cholinergic system.
NGF, NTF-3, and BDNF are the most widely studied neurotrophic factors [45]. Encoded in the brain, BDNF fuels differentiation, survival, plasticity, and memory, crowding the hippocampus and neocortex to drive neurogenesis [11]. NGF was the first neurotrophin to be discovered and plays an important role in the growth and development of peripheral and central neurons and maintenance of neuronal survival, and it plays a key role in neuronal plasticity and neurogenesis by inhibiting CREB phosphorylation [46]. NTF-3 is a member of the neurotrophic factor family that promotes the survival of sympathetic and sensory neurons during development. It supports neuronal survival and development, synaptic plasticity, neural injury repair, and exerts anti-inflammatory and neuroprotective effects [47]. Earlier work shows walnut peptides boost neurotrophic factor levels in zebrafish and rats, easing memory deficits. Consistent with these reports, our experiments demonstrate that the synergistic intervention of QMDDQ and AGLPM, particularly at a 1:1 ratio, upregulates hippocampal neurotrophic factor levels. This activates the BDNF/NGF/NTF-3 neurotrophic axis to support neuronal survival and synaptic plasticity. The experimental results above indicated that the combination of QMDDQ and AGLPM can modulate the cholinergic system, reduce loss of Nissl bodies, and regulate the protein expression levels of BDNF, NGF, and NTF-3, thereby enhancing learning and memory abilities in mice.
The fate of exogenous bioactive peptides will determine the ultimate neuroprotective effect of those peptides. Unlike previous ideas that peptides must enter the bloodstream intact to produce their effects, there is accumulating evidence that certain short peptides or amino acid fragments released after digestion may be more bioactive and can cross the intestinal barrier by peptide transporters like PepT1 [48]. The intestinal fluid mass spectrometry data show that hydrolysis of QMDDQ and AGLPM in the gut produces a secondary functional peptide pool of biological activity. According to quantitative MS analysis, the abundance of specific short peptides was greater in the 1:1 group than in the other groups. GEFDQGS (Glu/Gln-rich fragment from QMDDQ) and GLP (Pro-rich fragment from AGLPM) both peaked in the 1:1 group. It was interesting to find that the fragment EAGL was only hyper-abundant for 1:1. Network analysis (Figure 7A) found a high positive correlation between these intestinal peptides and cerebral amino acid values, suggesting that these intestinal products may act as peripheral precursors to cerebral metabolism. The full-length peptide sequences corresponding to Pep can be found in Supplementary Tables S1 and S2. Glu, the major excitatory neurotransmitter of the brain, is required to maintain long-term potentiation (LTP) and synaptic plasticity [49]. In this study, Glu levels were significantly depleted in the Scop group and achieved recovery in the 1:1 group, as shown in the flow analysis in the Sankey diagram (Figure 7B), due to the QMDDQ-derived Glu/Asp-rich fragments (e.g., GEFDQGS, EAGL) with sufficient supply of glutamate donors. The restoration of Glu levels directly promotes excitatory transmission at the postsynaptic membrane, accounting for the significant improvement in learning ability observed in the MWM test. Concurrently, brain Pro levels also increased in the 1:1 group. Pro not only participates in the production of structural proteins but also stabilizes glutamatergic transmission, exerting neuroprotective and antioxidant effects [50]. The Scop group showed the highest relative NH3 signal, whereas the 1:1 group showed the lowest. Cerebral metabolic disturbances and oxidative stress are considered important toxic factors in Alzheimer’s pathology and can contribute to astrocytic energy failure and neuronal apoptosis [51]. The lower NH3 signal in the 1:1 group is consistent with higher cerebral Glu levels, which are critical substrates for ammonia detoxification. Through the glutamine synthetase pathway, Glu and NH3 are converted to non-toxic Gln. Therefore, the 1:1 group may provide Glu substrates from QMDDQ and antioxidants from AGLPM to alleviate nitrogen- and stress-related neurotoxicity. An NH3-related signal in the acid-hydrolyzed amino acid profile was observed, which may reflect disturbed nitrogen metabolism associated with neuroinflammation and cognitive impairment. Glutamate (Glu), a key driver of memory formation and an excitatory neurotransmitter, as well as Serine (Ser) and Tyrosine (Tyr), which are involved in neuroplasticity and dopamine synthesis, were therefore prioritized for quantitative validation in follow-up studies.
GBA control hinges on cholinergic balance and boosted neurotrophic factors. A 1:1 ratio of QMDDQ and AGLPM was associated with altered intestinal metabolic profiles and increased Ser levels in brain tissue. Research indicates that Ser can enhance ACh release, increase the SAM/SAH ratio, elevate AChE promoter methylation levels, and inhibit AChE activity [52,53]. Oxidative stress and activation of the p38 MAPK pathway can suppress the transcription of BDNF, NTF-3, and metabolism-related genes by promoting histone H3 phosphorylation and the formation of repressive complexes such as p38-HDAC5, thereby inhibiting NGF promoter activation [54,55]. Glu directly activates BDNF and NTF-3 through Ca2+ pathways, and the derived acetyl-CoA enhances NGF transcription elongation rate via HAT [49,55]. Pro provides substrates for the synthesis of Glu, choline, and other compounds, and can enhance ATP production through the Pro-Glu cycle to supply energy for ACh synthesis. Therefore, the environment characterized by high levels of Ser, Glu, and Pro and a lower hydrolysis-derived NH3 signal in the brain tissue of the 1:1 group mice promoted ACh synthesis, inhibited AChE activity, and increased the protein expression levels of BDNF, NGF, and NTF-3.
This experiment represents only a preliminary exploration of the gut–brain axis. Therefore, mixed samples were used for brain amino acid profiling and intestinal fluid mass spectrometry identification to screen for qualitative differences between treatment groups, making it impossible to assess inter-individual variability. Future studies will employ biological replicate samples combined with targeted liquid chromatography–mass spectrometry/mass spectrometry (LC-MS/MS) or protein relabeling (PRM) techniques to validate the candidate peptides and amino acids identified in this study. Additionally, we plan to determine the three-dimensional structures of the major marine- and plant-derived peptides using circular dichroism and NMR, which should clarify structure-activity relationships and further strengthen the mechanistic link between gut-derived metabolites and hippocampal neurochemistry.

5. Conclusions

In summary, this study confirms that a 1:1 mixture of QMDDQ and AGLPM improves scopolamine-induced memory impairment by restoring cholinergic balance, maintaining neuronal structure, and enhancing neurotrophic signaling. As food-derived hydrolysates enriched with gut peptides and brain Glu/Pro levels while inhibiting NH3-related metabolites, the combination of QMDDQ and AGLPM provides proof-of-concept for functional seafood–cereal foods targeting cognitive health. Such functional foods may offer safe nutritional intervention strategies for high-stress populations, the elderly, or early-stage Alzheimer’s disease groups to delay or improve memory decline, laying a theoretical foundation for clinical trial development.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/foods15050827/s1, Table S1: The gut–brain network edge list; Table S2: The gut–brain network node attributes. Table S3: normality tests (Shapiro–Wilk) for all variables, p-values are given for each group; Figure S1: escape latency during Morris water maze training sessions; Figure S2: escape latency in probe trials on Days 10 and 20; Figure S3: original Western blot image; Figure S4: coomassie blue staining of the gel and Ponceau S staining of the membrane after transfer.

Author Contributions

Conceptualization, S.L.; methodology, S.L. and R.L.; software, X.X. and E.M.; validation, X.X. and R.L.; formal analysis, X.X.; investigation, R.L.; resources, S.L.; data curation, E.M. and L.Z.; writing—original draft preparation, X.X.; writing—review and editing, X.X., R.L. and S.L.; visualization, X.X. and R.L.; supervision, S.L.; project administration, L.Z. and S.L.; funding acquisition, S.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Key R and D Program of China, grant number 2024YFD2101202.

Institutional Review Board Statement

All animal procedures were approved by the Animal Ethics Committee of Dalian Polytechnic University (approval No. DLPU2024076, approved date 16 July 2024), and efforts were made to minimize animal suffering.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Materials. Further inquiries can be directed to the corresponding author.

Acknowledgments

We are grateful to BioGDP (https://biogdp.com/workspace, accessed on 17 December 2025) for providing the free online flow-chart drawing platform, which greatly facilitated the preparation of our graphical abstract. During the preparation of this manuscript, the authors used a large language model ChatGPT (version GPT-4) for language editing. The authors have reviewed and edited the output and take full responsibility for the content of this publication.

Conflicts of Interest

Author Limin Zhong was employed by Ganzhou Quanbiao Biological Technology Co., Ltd. He participated in data curation in the study. The company supplied no funding, equipment, or reagents and was not involved in study design, data interpretation, or manuscript writing. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Abbreviations

The following abbreviations are used in this manuscript:
QMDDQGln-Met-Asp-Asp-Gln
AGLPMAla-Gly-Leu-Pro-Met
AChAcetylcholine
AChEAcetylcholinesterase
BDNFBrain-Derived Growth Factor
NGFNerve Growth Factor
NTF-3Neurotrophic Factor 3
ADAlzheimer’s disease
MWMMorris water maze test
NORTNovel object recognition test

References

  1. Chang, A.Y.; Bolongaita, S.; Cao, B.; Castro, M.C.; Karlsson, O.; Mao, W.; Norheim, O.F.; Ogbuoji, O.; Jamison, D.T. Epidemiological and demographic trends and projections in global health from 1970 to 2050: A descriptive analysis from the third Lancet Commission on Investing in Health, Global Health 2050. Lancet 2025, 406, 940–949. [Google Scholar] [CrossRef]
  2. Zheng, Q.; Wang, X. Alzheimer’s disease: Insights into pathology, molecular mechanisms, and therapy. Protein Cell 2025, 16, 83–120. [Google Scholar] [CrossRef]
  3. Mohammadi, S.; Zandi, M.; Dousti Kataj, P.; Karimi Zandi, L. Chronic stress and Alzheimer’s disease. Biotechnol. Appl. Biochem. 2022, 69, 1451–1458. [Google Scholar] [CrossRef]
  4. Tatulian, S.A. Challenges and hopes for Alzheimer’s disease. Drug Discov. Today 2022, 27, 1027–1043. [Google Scholar] [CrossRef] [PubMed]
  5. Yang, Y.; Lu, S.; Liang, Y.; Tu, X.; Zeng, X.; Wang, L.; Pan, D.; Zhang, T.; Wu, Z. Recombinant protein LPxT-GYLEQ attenuates cognitive impairment by ameliorating oxidative stress in D-galactose-induced aging mice model. Food Biosci. 2024, 62, 105079. [Google Scholar] [CrossRef]
  6. Chen, Z.-R.; Huang, J.-B.; Yang, S.-L.; Hong, F.-F. Role of Cholinergic Signaling in Alzheimer’s Disease. Molecules 2022, 27, 1816. [Google Scholar] [CrossRef] [PubMed]
  7. Stanciu, G.D.; Luca, A.; Rusu, R.N.; Bild, V.; Beschea Chiriac, S.I.; Solcan, C.; Bild, W.; Ababei, D.C. Alzheimer’s Disease Pharmacotherapy in Relation to Cholinergic System Involvement. Biomolecules 2020, 10, 40. [Google Scholar] [CrossRef]
  8. Bekdash, R.A. The Cholinergic System, the Adrenergic System and the Neuropathology of Alzheimer’s Disease. Int. J. Mol. Sci. 2021, 22, 1273. [Google Scholar] [CrossRef]
  9. Frinchi, M.; Scaduto, P.; Cappello, F.; Belluardo, N.; Mudò, G. Heat shock protein (Hsp) regulation by muscarinic acetylcholine receptor (mAChR) activation in the rat hippocampus. J. Cell. Physiol. 2018, 233, 6107–6116. [Google Scholar] [CrossRef]
  10. Blokland, A. Cholinergic models of memory impairment in animals and man: Scopolamine vs. biperiden. Behav. Pharmacol. 2022, 33, 231. [Google Scholar] [CrossRef]
  11. Xu, X.; Yang, J.; Lu, Z.; Ding, J.; Lin, S. Folic acid ameliorated the scopolamine-induced memory impairment in mice and the neuroprotective mechanisms. Food Biosci. 2024, 60, 104351. [Google Scholar] [CrossRef]
  12. Zeng, T.; Zhang, C.; Sun, L.; Xu, H. Water-Soluble Ginseng Oligosaccharides Prevent Scopolamine-Induced Cholinergic Dysfunction and Inflammatory Cytokine Overexpression. Cell Biochem. Biophys. 2025, 83, 2511–2518. [Google Scholar] [CrossRef] [PubMed]
  13. Yun, D.; Wang, Y.; Zhang, Y.; Jia, M.; Xie, T.; Zhao, Y.; Yang, C.; Chen, W.; Guo, R.; Liu, X.; et al. Sesamol Attenuates Scopolamine-Induced Cholinergic Disorders, Neuroinflammation, and Cognitive Deficits in Mice. J. Agric. Food Chem. 2022, 70, 13602–13614. [Google Scholar] [CrossRef] [PubMed]
  14. Wu, D.; Xu, X.; Sun, N.; Li, D.; Zhu, B.; Lin, S. AGLPM and QMDDQ peptides exert a synergistic action on memory improvement against scopolamine-induced amnesiac mice. Food Funct. 2020, 11, 10925–10935. [Google Scholar] [CrossRef]
  15. Munakarmi, S.; Gurau, Y.; Shrestha, J.; Risal, P.; Park, H.S.; Lee, G.-H.; Jeong, Y.J. Synergistic Effects of Vitis vinifera L. and Centella asiatica against CCl4-Induced Liver Injury in Mice. Int. J. Mol. Sci. 2023, 24, 11255. [Google Scholar] [CrossRef]
  16. Shen, K.; He, S.; Li, W.; Song, S.; Lin, Q.; Jin, H. Collagen peptide and taurine synergistically improve hypertensive kidney injury induced by high salt diet through gut-kidney axis. Food Biosci. 2024, 62, 105320. [Google Scholar] [CrossRef]
  17. Liu, J.; Zhang, Q.; Hao, H.; Bi, J.; Hou, H.; Zhang, G. Benzyl Isothiocyanate and Resveratrol Synergistically Alleviate Dextran Sulfate Sodium-Induced Colitis in Mice. Foods 2024, 13, 2078. [Google Scholar] [CrossRef]
  18. Sahay, A.; Kale, A.; Joshi, S. Role of neurotrophins in pregnancy and offspring brain development. Neuropeptides 2020, 83, 102075. [Google Scholar] [CrossRef]
  19. Lin, P.H.; Kuo, L.T.; Luh, H.T. The Roles of Neurotrophins in Traumatic Brain Injury. Life 2022, 12, 26. [Google Scholar] [CrossRef]
  20. Dalangin, R.; Kim, A.; Campbell, R.E. The role of amino acids in neurotransmission and fluorescent tools for their detection. Int. J. Mol. Sci. 2020, 21, 6197. [Google Scholar] [CrossRef]
  21. Lu, Z.; Yang, J.; Xu, X.; Liu, R.; Lin, S. Regulation mechanisms of sea cucumber peptides against scopolamine-induced memory disorder and novel memory-improving peptides identification. Eur. J. Pharmacol. 2024, 968, 176430. [Google Scholar] [CrossRef] [PubMed]
  22. Park, K.; Lee, W.H.; Cho, E.; Kong, C.H.; Min, H.S.; Kim, M.S.; Han, J.E.; Jung, S.Y.; Kim, D.H.; Ryu, J.H. The effects of Cheonwangbosim-dan, a traditional herbal medicine prescription, on scopolamine-induced cognitive dysfunction in mice. J. Ethnopharmacol. 2025, 343, 119500. [Google Scholar] [CrossRef] [PubMed]
  23. Madhu, L.N.; Kodali, M.; Attaluri, S.; Shuai, B.; Melissari, L.; Rao, X.; Shetty, A.K. Melatonin improves brain function in a model of chronic Gulf War Illness with modulation of oxidative stress, NLRP3 inflammasomes, and BDNF-ERK-CREB pathway in the hippocampus. Redox Biol. 2021, 43, 101973. [Google Scholar] [CrossRef] [PubMed]
  24. Yan, L.; Mao, J.; Shi, W.; Ren, L.; Li, J.; Geng, B.; Wang, H.; Zhang, J.; Tian, Y.; Zhang, B.; et al. Subchronic toxicity study of ferric oxide nanoparticles through intragastric administration: A 94-d, repeated dose study in Sprague Dawley rats. Regul. Toxicol. Pharmacol. 2023, 140, 105381. [Google Scholar] [CrossRef]
  25. Zhao, Y.; Lu, Z.; Xu, X.; Sun, N.; Lin, S. Sea Cucumber-Derived Peptide Attenuates Scopolamine-Induced Cognitive Impairment by Preventing Hippocampal Cholinergic Dysfunction and Neuronal Cell Death. J. Agric. Food Chem. 2022, 70, 567–576. [Google Scholar] [CrossRef]
  26. Luo, X.; Cheng, P.; Fang, Y.; Wang, F.; Mao, T.; Shan, Y.; Lu, Y.; Wei, Z. Yinzhihuang formula modulates the microbe-gut-liver axis and bile acid excretion to attenuate cholestatic liver injury. Phytomedicine 2025, 139, 156495. [Google Scholar] [CrossRef]
  27. Shen, Y.; Dang, Q.; Fang, L.; Wu, D.; Li, Y.; Zhao, F.; Liu, C.; Min, W. Walnut-Derived Peptides Ameliorate Scopolamine-Induced Memory Impairments in a Mouse Model via Activation of Peroxisome Proliferator-Activated Receptor γ-Mediated Excitotoxicity. J. Agric. Food Chem. 2024, 72, 12541–12554. [Google Scholar] [CrossRef]
  28. Xu, X.; Liang, R.; Li, D.; Jiang, C.; Lin, S. Evaluation of sea cucumber peptides-assisted memory activity and acetylation modification in hippocampus of test mice based on scopolamine-induced experimental animal model of memory disorder. J. Funct. Foods 2020, 68, 103909. [Google Scholar] [CrossRef]
  29. Xue, H.; Han, J.; Ma, J.; Song, H.; He, B.; Liu, X.; Yi, M.; Zhang, L. Identification of immune-active peptides in casein hydrolysates and its transport mechanism on a Caco-2 monolayer. Foods 2023, 12, 373. [Google Scholar] [CrossRef]
  30. Liu, D.; Chen, M.; Zhu, J.; Tian, W.; Guo, Y.; Ma, H. A two-stage enzymolysis method and its application in exerting antioxidant activity of walnut protein. Front. Nutr. 2022, 9, 889434. [Google Scholar] [CrossRef]
  31. Wu, D.; Zhang, S.; Sun, N.; Zhu, B.; Lin, S. Neuroprotective function of a novel hexapeptide QMDDQ from shrimp via activation of the PKA/CREB/BDNF signaling pathway and its structure-activity relationship. J. Agric. Food Chem. 2020, 68, 6759–6769. [Google Scholar] [CrossRef] [PubMed]
  32. Liu, R.; Ding, J.; Zhong, L.; Lin, S. Neuroprotective Effects of Shrimp Peptides by Improving Synaptic Plasticity through Adcy5/PKA/p-CREB Based on Proteomic Techniques. Food Sci. Hum. Wellness 2025, in press. [Google Scholar] [CrossRef]
  33. Liem-Moolenaar, M.; de Boer, P.; Timmers, M.; Schoemaker, R.C.; van Hasselt, J.G.C.; Schmidt, S.; van Gerven, J.M.A. Pharmacokinetic-pharmacodynamic relationships of central nervous system effects of scopolamine in healthy subjects. Br. J. Clin. Pharmacol. 2011, 71, 886–898. [Google Scholar] [CrossRef] [PubMed]
  34. EFSA Panel on Nutrition, Novel Foods and Food Allergens (NDA); Bohn, T.; Cámara, M.; Castenmiller, J.; de Henauw, S.; Hirsch-Ernst, K.I.; Jos, M.A.; Maciuk, A.; Mangelsdorf, I.; McNulty, B.; et al. Nutritional safety and suitability of a specific protein hydrolysate derived from sources of skimmed cow’s milk and whey protein concentrates and used in infant and follow-on formula manufactured from hydrolysed protein by Healthcare Reckitt BV. EFSA J. 2025, 23, e9278. [Google Scholar] [CrossRef]
  35. Yuan, Z.; Zhou, H.; Zhou, N.; Dong, D.; Chu, Y.; Shen, J.; Han, Y.; Chu, X.-P.; Zhu, K. Dynamic Evaluation Indices in Spatial Learning and Memory of Rat Vascular Dementia in the Morris Water Maze. Sci. Rep. 2019, 9, 7224. [Google Scholar] [CrossRef]
  36. Cazakoff, B.N.; Johnson, K.J.; Howland, J.G. Converging effects of acute stress on spatial and recognition memory in rodents: A review of recent behavioural and pharmacological findings. Prog. Neuropsychopharmacol. Biol. Psychiatry 2010, 34, 733–741. [Google Scholar] [CrossRef]
  37. Irisarri, A.; Corral, A.; Perez-Salvador, N.; Bellver-Sanchis, A.; Ribalta-Vilella, M.; Bentanachs, R.; Alegret, M.; Laguna, J.C.; Barroso, E.; Palomer, X.; et al. FTO inhibition mitigates high-fat diet-induced metabolic disturbances and cognitive decline in SAMP8 mice. Mol. Med. 2025, 31, 73. [Google Scholar] [CrossRef]
  38. Melgar-Locatelli, S.; Mañas-Padilla, M.C.; Castro-Zavala, A.; Rivera, P.; Razola-Díaz, M.C.; Monje, F.J.; Rodríguez-Pérez, C.; Castilla-Ortega, E. Diet enriched with high-phenolic cocoa potentiates hippocampal brain-derived neurotrophic factor expression and neurogenesis in healthy adult mice with subtle effects on memory. Food Funct. 2024, 15, 8310–8329. [Google Scholar] [CrossRef]
  39. Costa, J.F.; Dines, M.; Agarwal, K.; Lamprecht, R. Rac1 GTPase activation impairs fear conditioning-induced structural changes in basolateral amygdala neurons and long-term fear memory formation. Neuropsychopharmacology 2023, 48, 1338–1346. [Google Scholar] [CrossRef]
  40. Li, Y.; Shen, G.; Du, J.; Dai, W.; Su, Z. Neuroprotective Potential of Ethoxzolamide Targeting Oxidative Stress and Inflammation in Experimental Models of Intracerebral Hemorrhage. Front. Biosci. (Landmark Ed.) 2024, 29, 10356. [Google Scholar] [CrossRef]
  41. Weng, J.; Wang, Y.; Tan, Z.; Yuan, Y.; Huang, S.; Li, Z.; Li, Y.; Zhang, L.; Du, Z. Glabridin reduces neuroinflammation by modulating inflammatory signals in LPS-induced in vitro and in vivo models. Inflammopharmacology 2024, 32, 1159–1169. [Google Scholar] [CrossRef] [PubMed]
  42. Zhou, D.; Sun, Y.; Qian, Z.; Wang, Z.; Zhang, D.; Li, Z.; Zhao, J.; Dong, C.; Li, W.; Huang, G. Long-term dietary folic acid supplementation attenuated aging-induced hippocampus atrophy and promoted glucose uptake in 25-month-old rats with cognitive decline. J. Nutr. Biochem. 2023, 117, 109328. [Google Scholar] [CrossRef] [PubMed]
  43. Kljakic, O.; Al-Onaizi, M.; Janíčková, H.; Chen, K.S.; Guzman, M.S.; Prado, M.A.M.; Prado, V.F. Cholinergic transmission from the basal forebrain modulates social memory in male mice. Eur. J. Neurosci. 2021, 54, 6075–6092. [Google Scholar] [CrossRef] [PubMed]
  44. AlGhamdi, S.A.; Al-Abbasi, F.A.; Alghamdi, A.M.; Omer, A.B.; Afzal, O.; Altamimi, A.S.A.; Alamri, A.; Alzarea, S.I.; Almalki, W.H.; Kazmi, I. Barbigerone prevents scopolamine-induced memory impairment in rats by inhibiting oxidative stress and acetylcholinesterase levels. R. Soc. Open Sci. 2023, 10, 230013. [Google Scholar] [CrossRef]
  45. Liu, W.; Liu, J.; Gao, J.; Duan, X.; Zhang, L. Effects of Subchronic Aluminum Exposure on Learning, Memory, and Neurotrophic Factors in Rats. Neurotox. Res. 2022, 40, 2046–2060. [Google Scholar] [CrossRef]
  46. Sohn, E.; Lim, H.-S.; Kim, Y.J.; Kim, B.-Y.; Kim, J.-H.; Jeong, S.-J. Elaeagnus glabra f. Oxyphylla Attenuates Scopolamine-Induced Learning and Memory Impairments in Mice by Improving Cholinergic Transmission via Activation of CREB/NGF Signaling. Nutrients 2019, 11, 1205. [Google Scholar] [CrossRef]
  47. Niu, X.; Zheng, Y.; Wang, W.; Zhang, L.; Wang, S.; Lu, X.; Wang, J.; Yang, G.; Zhao, T.; Li, Q.; et al. Esketamine Provides Neuroprotection After Intracerebral Hemorrhage in Mice via the NTF3/PI3K/AKT Pathway. CNS Neurosci. Ther. 2024, 30, e70145. [Google Scholar] [CrossRef]
  48. Viennois, E.; Pujada, A.; Zen, J.; Merlin, D. Function, regulation, and pathophysiological relevance of the POT superfamily, specifically PepT1 in inflammatory bowel disease. Compr. Physiol. 2018, 8, 731–760. [Google Scholar] [CrossRef]
  49. Liang, J.; Takeuchi, H.; Jin, S.; Noda, M.; Li, H.; Doi, Y.; Kawanokuchi, J.; Sonobe, Y.; Mizuno, T.; Suzumura, A. Glutamate induces neurotrophic factor production from microglia via protein kinase C pathway. Brain Res. 2010, 1322, 8–23. [Google Scholar] [CrossRef]
  50. Pallag, G.; Nazarian, S.; Ravasz, D.; Bui, D.; Komlódi, T.; Doerrier, C.; Gnaiger, E.; Seyfried, T.N.; Chinopoulos, C. Proline oxidation supports mitochondrial ATP production when complex I is inhibited. Int. J. Mol. Sci. 2022, 23, 5111. [Google Scholar] [CrossRef]
  51. Shen, R.; Ardianto, C.; Celia, C.; Sidharta, V.M.; Sasmita, P.K.; Satriotomo, I.; Turana, Y. Interação do fator neurotrófico encefálico com o estresse oxidativo: Abordagem neuropatológica a um potencial biomarcador da doença de Alzheimer. Dement. Neuropsychol. 2023, 17, e20230012. [Google Scholar] [CrossRef]
  52. Yoshikawa, M.; Okubo, M.; Shirose, K.; Kan, T.; Kawaguchi, M. D-Serine increases release of acetylcholine in rat submandibular glands. Biology 2023, 12, 1227. [Google Scholar] [CrossRef]
  53. Yoshikawa, M.; Shinomiya, T.; Takayasu, N.; Tsukamoto, H.; Kawaguchi, M.; Kobayashi, H.; Oka, T.; Hashimoto, A. Long-term treatment with morphine increases the D-serine content in the rat brain by regulating the mRNA and protein expressions of serine racemase and D-amino acid oxidase. J. Pharmacol. Sci. 2008, 107, 270–276. [Google Scholar] [CrossRef]
  54. Kikuchi, H.; Yuan, B.; Yuhara, E.; Takagi, N.; Toyoda, H. Involvement of histone H3 phosphorylation through p38 MAPK pathway activation in casticin-induced cytocidal effects against the human promyelocytic cell line HL-60. Int. J. Oncol. 2013, 43, 2046–2056. [Google Scholar] [CrossRef]
  55. Heese, K.; Beck, K.F.; Behrens, M.H.; Plüss, K.; Fierlbeck, W.; Huwiler, A.; Mühl, H.; Geiger, H.; Otten, U.; Pfeilschifter, J. Effects of high glucose on cytokine-induced nerve growth factor (NGF) expression in rat renal mesangial cells. Biochem. Pharmacol. 2003, 65, 293–301. [Google Scholar] [CrossRef]
Figure 1. Effects of QMDDQ and AGLPM on general health and safety in scopolamine-treated mice. (A) Experimental schedule of animal treatments and behavioral tests. (B) Body weight changes over 41 days. (C) Body composition analysis on day 30. (D) Body composition analysis on day 40. (E) Lung coefficient. (F) Spleen coefficient. (G) Liver coefficient. (H) Kidney coefficient. (I) Heart coefficient. (J) H&E-stained sections of liver and small intestine tissues. All values are presented as mean ± SD; n.s. indicates no significant difference between groups (p > 0.05); p < 0.05 represents a statistically significant difference; n = 10. Individual data points are represented by different symbols for each group.
Figure 1. Effects of QMDDQ and AGLPM on general health and safety in scopolamine-treated mice. (A) Experimental schedule of animal treatments and behavioral tests. (B) Body weight changes over 41 days. (C) Body composition analysis on day 30. (D) Body composition analysis on day 40. (E) Lung coefficient. (F) Spleen coefficient. (G) Liver coefficient. (H) Kidney coefficient. (I) Heart coefficient. (J) H&E-stained sections of liver and small intestine tissues. All values are presented as mean ± SD; n.s. indicates no significant difference between groups (p > 0.05); p < 0.05 represents a statistically significant difference; n = 10. Individual data points are represented by different symbols for each group.
Foods 15 00827 g001
Figure 2. Effects of QMDDQ and AGLPM on the behavior tests in scopolamine-treated mice. (A) Schematic diagram of MWM and NORT. I, II, III, and IV represent the four quadrants. The green circle denotes the old object, while the red square and purple triangle denote the new objects. (B) Representative swimming trajectories of mice in the Morris water maze on day 28. Green and red dots indicate the start and end positions, respectively. (C) Platform crossing on day 28. (D) Time spent in the target quadrant on day 28. (E) Escape latency in the MWM on day 28. (F) Representative swimming trajectories of mice on day 38. (G) Platform crossing on day 38. (H) Time spent in the target quadrant on day 38. (I) Escape latency in the MWM on day 38. (J) Recognition index in the NORT on day 30. (K) Recognition index in the NORT on day 40. All values are presented as mean ± SD; n.s. indicates no significant difference between groups (p > 0.05); p < 0.05 represents a statistically significant difference; n = 10. Individual data points are represented by different symbols for each group.
Figure 2. Effects of QMDDQ and AGLPM on the behavior tests in scopolamine-treated mice. (A) Schematic diagram of MWM and NORT. I, II, III, and IV represent the four quadrants. The green circle denotes the old object, while the red square and purple triangle denote the new objects. (B) Representative swimming trajectories of mice in the Morris water maze on day 28. Green and red dots indicate the start and end positions, respectively. (C) Platform crossing on day 28. (D) Time spent in the target quadrant on day 28. (E) Escape latency in the MWM on day 28. (F) Representative swimming trajectories of mice on day 38. (G) Platform crossing on day 38. (H) Time spent in the target quadrant on day 38. (I) Escape latency in the MWM on day 38. (J) Recognition index in the NORT on day 30. (K) Recognition index in the NORT on day 40. All values are presented as mean ± SD; n.s. indicates no significant difference between groups (p > 0.05); p < 0.05 represents a statistically significant difference; n = 10. Individual data points are represented by different symbols for each group.
Foods 15 00827 g002
Figure 3. Effects of QMDDQ and AGLPM on hippocampal neuronal morphology and cholinergic markers in scopolamine-treated mice. (A) Nissl staining of hippocampal CA1 and CA3 regions. Red arrows indicate damaged neurons; yellow arrows indicate normal neurons. (B) Nissl body count in the CA1 region. (C) Nissl body count in the CA3 region. (D) ACh level in the hippocampus. (E) AChE activity in the hippocampus. (B,C): Each symbol = one microscopic field (6 fields per group, 2 sections from each of 3 mice); (D,E): ACh level and AChE activity: each symbol = one mouse (n = 3 per group). All values are presented as mean ± SD; p < 0.05 represents a statistically significant difference. Individual data points are represented by different symbols for each group.
Figure 3. Effects of QMDDQ and AGLPM on hippocampal neuronal morphology and cholinergic markers in scopolamine-treated mice. (A) Nissl staining of hippocampal CA1 and CA3 regions. Red arrows indicate damaged neurons; yellow arrows indicate normal neurons. (B) Nissl body count in the CA1 region. (C) Nissl body count in the CA3 region. (D) ACh level in the hippocampus. (E) AChE activity in the hippocampus. (B,C): Each symbol = one microscopic field (6 fields per group, 2 sections from each of 3 mice); (D,E): ACh level and AChE activity: each symbol = one mouse (n = 3 per group). All values are presented as mean ± SD; p < 0.05 represents a statistically significant difference. Individual data points are represented by different symbols for each group.
Foods 15 00827 g003
Figure 4. Effects of QMDDQ and AGLPM on neurotrophic factors in scopolamine-treated mice. (A) Western blot images of BDNF, NGF, NTF-3, and β-actin. (B) Relative expression of BDNF. (C) Relative expression of NGF. (D) Relative expression of NTF-3. Data were shown as mean ± SD. All values are presented as mean ± SD; p < 0.05 represents a statistically significant difference; n = 3. Individual data points are represented by different symbols for each group.
Figure 4. Effects of QMDDQ and AGLPM on neurotrophic factors in scopolamine-treated mice. (A) Western blot images of BDNF, NGF, NTF-3, and β-actin. (B) Relative expression of BDNF. (C) Relative expression of NGF. (D) Relative expression of NTF-3. Data were shown as mean ± SD. All values are presented as mean ± SD; p < 0.05 represents a statistically significant difference; n = 3. Individual data points are represented by different symbols for each group.
Foods 15 00827 g004
Figure 5. Effects of QMDDQ and AGLPM on peptide profiles in intestinal fluid of scopolamine-treated mice. (A) Venn diagram of identified peptides. (B) Clustering heatmap of representative peptides. (C) Z-score heatmap of representative peptides. (D) Peak area stacked bar chart of representative peptides. Data are from one pooled intestinal-fluid sample per group (n = 10 mice pooled); no statistical tests were performed.
Figure 5. Effects of QMDDQ and AGLPM on peptide profiles in intestinal fluid of scopolamine-treated mice. (A) Venn diagram of identified peptides. (B) Clustering heatmap of representative peptides. (C) Z-score heatmap of representative peptides. (D) Peak area stacked bar chart of representative peptides. Data are from one pooled intestinal-fluid sample per group (n = 10 mice pooled); no statistical tests were performed.
Foods 15 00827 g005
Figure 6. Effects of QMDDQ and AGLPM on amino acid profiles in the brain of mice. (A) Polar bar charts of amino acids, amino acids and metabolites in brain tissues were categorized into four functional modules, memory-related amino acids (green), peptide-derived amino acids (blue), negatively correlated metabolites (red), and other amino acids (gray). (B) Stacked bar chart of amino acids. Different colors represent different amino acids and NH3. (C) Clustering heatmap of amino acids, the color scale represents relative levels: red (high), white (intermediate), and blue (low), ranging from −2.00 to 2.00. Data are from one pooled brain sample per group (n = 3 mice pooled); no statistical tests were performed.
Figure 6. Effects of QMDDQ and AGLPM on amino acid profiles in the brain of mice. (A) Polar bar charts of amino acids, amino acids and metabolites in brain tissues were categorized into four functional modules, memory-related amino acids (green), peptide-derived amino acids (blue), negatively correlated metabolites (red), and other amino acids (gray). (B) Stacked bar chart of amino acids. Different colors represent different amino acids and NH3. (C) Clustering heatmap of amino acids, the color scale represents relative levels: red (high), white (intermediate), and blue (low), ranging from −2.00 to 2.00. Data are from one pooled brain sample per group (n = 3 mice pooled); no statistical tests were performed.
Foods 15 00827 g006
Figure 7. Correlation analysis between peptides and amino acids. (A) Network analysis of peptide-amino acid correlations. Pink nodes, brain amino acids and NH3; blue nodes, intestinal peptides (Pep1–Pep25); gray lines, correlations between peptides and amino acids. (B) Sankey diagram of metabolic flow from the intestine to the brain. Colors indicate peptide sources (red: QMDDQ; blue: AGLPM) and brain functional outcomes (green: NH3 detoxification; orange: Glu recovery; teal: Gly/Ala recovery; purple: Pro recovery; gray: general amino acid pool).
Figure 7. Correlation analysis between peptides and amino acids. (A) Network analysis of peptide-amino acid correlations. Pink nodes, brain amino acids and NH3; blue nodes, intestinal peptides (Pep1–Pep25); gray lines, correlations between peptides and amino acids. (B) Sankey diagram of metabolic flow from the intestine to the brain. Colors indicate peptide sources (red: QMDDQ; blue: AGLPM) and brain functional outcomes (green: NH3 detoxification; orange: Glu recovery; teal: Gly/Ala recovery; purple: Pro recovery; gray: general amino acid pool).
Foods 15 00827 g007
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Xu, X.; Liu, R.; Ma, E.; Zhong, L.; Lin, S. Gut–Brain Metabolic Remodeling Mediates the Neuroprotective Effects of Combined Shrimp and Corn Peptides in Scopolamine-Induced Cognitive Impairment. Foods 2026, 15, 827. https://doi.org/10.3390/foods15050827

AMA Style

Xu X, Liu R, Ma E, Zhong L, Lin S. Gut–Brain Metabolic Remodeling Mediates the Neuroprotective Effects of Combined Shrimp and Corn Peptides in Scopolamine-Induced Cognitive Impairment. Foods. 2026; 15(5):827. https://doi.org/10.3390/foods15050827

Chicago/Turabian Style

Xu, Xiaomeng, Ruowen Liu, Enhui Ma, Limin Zhong, and Songyi Lin. 2026. "Gut–Brain Metabolic Remodeling Mediates the Neuroprotective Effects of Combined Shrimp and Corn Peptides in Scopolamine-Induced Cognitive Impairment" Foods 15, no. 5: 827. https://doi.org/10.3390/foods15050827

APA Style

Xu, X., Liu, R., Ma, E., Zhong, L., & Lin, S. (2026). Gut–Brain Metabolic Remodeling Mediates the Neuroprotective Effects of Combined Shrimp and Corn Peptides in Scopolamine-Induced Cognitive Impairment. Foods, 15(5), 827. https://doi.org/10.3390/foods15050827

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop