Sea cucumber protein improves aging signs by affecting the brain and gut communication in older mice

SCP was pharmacologically grade and supplied by Dalian Shenlan Peptide Technology Research and Development Co., LTD (Dalian, China). Peptide sequences of SCP were characterized by liquid chromatography mass spectrometry (LC–MS) and subsequent bioinformatic alignment with the sea cucumber proteomic database was performed to identify predominant peptide constituents. A total of 308 protein groups were identified (Fig. 1 and Table 1). Using high-performance size exclusion chromatography, the molecular weight distribution profile of SCP was characterized. The chromatographic analysis was performed on a Waters 600 high performance liquid chromatography (HPLC) system equipped with a tosoh silica (TSK) gel column (2000 SWXL, 300 mm × 7.8 mm), and a 2487 ultraviolet (UV). The elution was carried out at 30℃ using a mobile phase consisting of water/acetonitrile/trifluoroacetic acid (85:15:0.05, v/v/v) delivered at a flow rate of 0.7 mL/min. Cytochrome c (12,500 Da), aprotinin (6512 Da), β-amyloid (4514 Da), vitamin B12 (1355 Da), MOG (2582 Da), GSH (307 Da), and glycine were among the standards used for calibration. The molecular weight calibration curve was established by plotting the relationship of logarithmic molecular weight(y) versus retention time(x), yielding the equation y = 0.0162x + 0.0197 with a correlation coefficient(R²) of 0.9992, demonstrating excellent linearity across the analytical range. The relative molecular weight distribution profile of the peptide constituents was subsequently determined by applying this equation, with quantitative analysis of each fraction achieved through normalized peak area integration (Table S1). Additionally, an automatic amino acid analyzer (Model 835–50, Hitachi, Tokyo, Japan) was quantitatively used to analyze the amino acid composition of the SCP (Table S2).

Following a one-week acclimation period under controlled vivarium conditions(24 ± 1 °C, 60 ± 5% relative humidity, 12:12 h light–dark cycle), six 8-week-old C57Bl/6 J mice and eighteen 20-month-old C57Bl/6 J mice were prepared for subsequent interventions. Throughout the acclimatization period, animals were provided unrestricted access to food and water. After 7 days of environmental adaptation, the mice were randomly allocated into four experimental groups(n = 6/group):

Upon completion of behavioral assessments, the mice were humanely euthanized, and their brains were immediately excised, frozen in liquid nitrogen, and kept at −80℃ until subsequent biochemical analyses. C57Bl/6 J mice were procured from Beijing Weitong Lihua Experimental Animal Technology Co., Ltd.(Beijing, China).

Throughout the experimental intervention period, mice body weights were measured biweekly, and any changes were meticulously documented. Post-euthanasia, the kidney, liver, heart, lungs, and brain of each mouse were precisely weighed to calculate their respective organ indexes, which were determined using the following formula: tissue index = (tissue weight/body weight) × 100%.

Each mouse was gently introduced into the center in an open field arena, consisting of a wooden box measuring 40 × 40 × 50 cm, allowing unrestricted exploration for a duration of 5 min. All behavioral sessions were digitally recorded using a camera. To quantitatively evaluate motor ability and anxiety, the total distance traveled, the distance covered within the center zone, and the number of entries into the center zone were calculated using the Smart Video Tracking Software(Panlab; Harvard Apparatus).

The Y-maze contraption consisted of three identical opaque polypropylene arms(35 × 20 × 10 cm; 120° angular separation) with matte white interior surfaces, constructed to minimize external visual cues and ensure standardized spatial navigation testing conditions. The floor was systematically decontaminated with 75%(v/v) ethanol solution to eliminate residual olfactory cues in between experiments. Throughout the test, consistent spatial visual cues were permanently affixed at the end of each maze arm. Through integration of distal spatial cues differentially perceived from each Y-maze arm, the mouse successfully discriminated between novelty and familiarity. The mice were permitted 3-min free exploration of two accessible maze arms, while the third arm remained obstructed by an opaque polycarbonate partition. Following a 120-min intertrial interval, the mice were reintroduced to the initial arm for the second experiment, with exploration behavior quantified during a 180-s epoch corresponding to each maze arm under unconstrained access conditions. For every mouse, the initial and novel arms were assigned randomly to control for positional bias across trials. When all four limbs entered the arm, the ingress was operationally defined as valid. Using Smart Video Tracking Software(Panlab; Harvard Apparatus), the animals'movements were tracked in order to assess their cognitive ability.

The Barnes maze apparatus was conducted on an elevated circular platform(100 cm diameter), featuring 20 equidistant holes(each 5 × 5 cm). One hole, randomly selected, served as the escape hole, allowing the mouse to descend into a dark box positioned beneath the platform. During the habituation phase(pre-test acclimation), the mouse was gently placed inside the dark box at the maze's center and allowed to remain there for 15 s. Following removal of the box, the mouse was permitted 180-s unrestricted exploration of the maze apparatus. During that time, the frequency of erroneous hole explorations and the escape latency were noted. The mouse was gently steered in the direction of the dark box if it failing to locate the target escape hole within the 180-s trial period. The mice underwent twice-daily training sessions for six consecutive days, and on the day 7, they were assessed. The maze apparatus was thoroughly cleaned with 75% ethanol between trials to eliminate residual olfactory cues. On day 7, the mice performed the task. The escape latency for the mouse to successful entry into the target box and the percentage of incorrect hole entries within the goal quadrant over a 3-min period were calculated. These metrics served to assess spatial reference learning and memory. All data were digitally acquired using a camera and analyzed objectively with an automated video tracking system(EthoVision 2.3 and XT 6.1.326, Noldus Information Technology, Wageningen, The Netherlands).

For fecal metabolomic profiling, the ultra-performance liquid chromatography coupled with quadrupole time of flight mass spectrometry(UPLC-QTOF-MS) technology was used based on its remarkable sensitivity, quick acquisition rates, and accuracy in mass data collection. Each 50 mg fecal sample was subjected to ultrasonic-assisted extraction to expedite the extraction procedure, followed by addition of 400 μl methanol containing 5 μg/ml of 2-chloro-L-phenylalanine as an internal standard for subsequently added. Following centrifugation(12,000 × g, 10 min, 4 °C), the resultant supernatant was moved to a glass container after centrifugation. An Agilent 1290 Infinity II ultra-high-performance liquid chromatography(UHPLC) system, an Agilent 6545 UHD, and an Accurate-Mass Q-TOF–MS(Agilent, Santa Clara, CA, USA) made up the liquid chromatography tandem mass spectrometry(LC–MS/MS) system. Raw MS data(.raw files) were processed using LECO Chroma TOF 4.3 × software(LECO Corporation),(then compared to the LECO-Fiehn Rtx5 database. Retention times and m/z data pairs were utilized to identify each peak, and only peaks having a matching probability of ≥ 60% were classified as confidently identified metabolites. The SIMCA14.1 software package was used to import the peaks, their numbers, sample names, and normalized peak areas. The Kyoto Encyclopedia of Genes and Genomes(KEGG) database was consulted in order to confirm the identified metabolites. All statistically significant metabolites were subjected to pathway topology analysis using MetaboAnalyst, with subsequent cross-referencing against canonical metabolic pathways in the KEGG database. To assess any associations between fecal metabolites and gut microbiota, Pearson's correlation coefficients was performed.

Microbiome sequencing and analysis were outsourced to Shanghai Majorbio Biopharm Technology Co., Ltd(Shanghai, China). The first step was to use a Qiagen Gel Extraction Kit(Qiagen, Germany) to extract genomic (DNA from the intestinal contents as directed by the manufacturer. Following that, bar-coded primers that specifically targeted the V3-V4 region of the 16S rRNA gene were used to amplify DNA fragments by polymerase chain reaction(PCR). Following electrophoretic verification of the PCR results, the Thermo Scientific GeneJET Glue Recovery Kit was used to recover and purify the appropriate bands. Qualified libraries were subsequently subjected to sequencing on the NovaSeq 6000(Beijing, China).

Total RNA was isolated from brain tissues using TRIZOL reagent(Takara, Shiga-ken, Japan) following the manufacturer's protocol., Subsequently, 1 μg of total RNA was reverse transcribed into cDNA for subsequent RT-qPCR analysis. Gene-specific primers were constructed applying Primer 6.0 software and synthesized by Sangon Biotech Co., Ltd.(Shanghai, China). RT-qPCR was performed in 20 μL reaction volumes using the following thermal cycling protocol: initial denaturation at 95 °C for 10 min; 45 cycles of denaturation at 95 °C for 10 s, annealing at 60 °C for 10 s, and extension at 72 °C for 10 s; with final fluorescence acquisition at 72 °C. In Stage III, melting curve analysis was performed with the following parameters: initial denaturation at 95 °C for 10 s, increasing gradually over 60 s to 65℃, followed by a final 1-s denaturation at 97 °C. The internal control for normalization was β-Actin. The 2^−ΔΔCt technique was used to examine the levels of messenger ribonucleic acid(mRNA) expression. The relevant primer sequences are listed in Table S3.

The kidney, liver, heart, lungs, spleen and brain tissues harvested from each animal were immersion-fixed in a 4% paraformaldehyde solution for a duration of 24 h. Following fixation, the tissues were processed through graded ethanol dehydration(70%−100%), cleared in xylene, embedded in paraffin, and sectioned to a thickness of 5 μm(Servicebio Biological Technology Co., Ltd.). H&E staining was carried out utilizing an H&E staining kit sourced(Solarbio, China), in strict adherence to the manufacturer's protocols. The histopathological evaluation within the tissues were examined under a light microscope.

Fresh whole blood samples were allowed to coagulate for 2 h at room temperature, followed by centrifugation at 3,000 × g for 15 min at 4 °C to obtain serum supernatant fractions. Following collection, all materials were kept at −80℃ for further scientific examination. The serum levels of alkaline phosphatase(ALP) and aspartate aminotransferase(AST) were quantitatively determined using standardized commercial assay kits. All biochemical analyses were performed strictly adhering to the manufacturer's recommendations on an automatic biochemical analyzer(Hitachi 7020, Japan).

Brain tissue samples from groups(n = 3 per group) were randomly selected and frozen for subsequent RNA extraction, and then the samples were isolated for their purity, quality, and integrity. mRNA was enriched using oligo(dT)25 magnetic beads, and cDNA and libraries were prepared by Major Bio-Tech Ltd(Shanghai, China). RNA sequencing libraries were prepared following the Illumina protocols to get the reads, and then these reads were quantified with read numbers mapped to each gene using HTSeq v0.6.1. Pathway scores were assessed utilizing the Gene Set Variation Analysis(GSVA), followed by ordinal regression analysis. Pathway enrichment scores were computed using GSVA by integrating the normalized protein expression profiles of all constituent proteins within the especial KEGG-defined pathway.

Serial 5-μm brain sections were mounted on slides after being floated in a 40 °C water bath. Following oven drying at 60 °C for 2 h, tissue sections underwent sequential deparaffinization in xylene(3 × 5 min) and rehydration through graded ethanol series(100%−70%). Then, staining was carried out using the Arixin Blue staining kit.

Serial 5-μm brain sections were mounted on slides after being floated in a 40 °C water bath. Following oven drying at 60 °C for 2 h, tissue sections underwent sequential deparaffinization in xylene(3 × 5 min) and rehydration through graded ethanol series(100%−70%). After that, sections were blocked with endogenous peroxidase, followed by antigen retrieval and nonspecific binding reduction. Tissue sections were incubated overnight at 4 °C with the following primary antibodies: anti COMT(1:100), anti UGT1A9(1:100), and anti HSD11B1(1:100). Following primary antibody incubation, the sections were incubated at room temperature with secondary antibody for 1 h and performed with staining agent. The expression of proteins was graded according to the staining intensity score(0, 1, 2 or 3) and positive rate score(0, 1, 2, 3 or 4). The composite score was calculated by multiplying the staining intensity score by the positive rate score.

Student's t-test and one-way ANOVA analysis were performed to examine all results with SPSS 21 software(IBM Inc., Armonk, NY, USA). p < 0.05 was considered statistically significant. The association between fecal metabolomic profiles and gut microbial taxa were assessed using Pearson correlation analysis. All experimental data are presented as mean ± standard deviation(SD) and were visualized using GraphPad Prism 9.1.0(GraphPad Software, USA).

To investigate the anti-aging effects of SCP, 20-month-old C57BL/6 J mice were randomly allocated into three groups and subjected to daily intragastric administration for 8 weeks: the aging-control group(physiological saline), a low dose of SCP(500 mg/kg/d)(aging-SCP low), or a high dose of SCP(1000 mg/kg/d)(aging-SCP high). Young mice administered with physiological saline were designated as the young-control group. Following the 8-week intervention period, the anti-aging efficacy of SCP were systematically evaluated through behavioral tests, metabolite analysis, and gut microbiota analysis. Body weight measurements were recorded and organ coefficients were determined for all experimental subjects. The results indicated that, compared with aging-control mice, the brain index of aging-SCP high mice increased (Table 2). Furthermore, biochemical analysis of hepatic function markers AST and ALP demonstrated significantly reduced in both aging-SCP low and aging-SCP high mice compared to aging-control mice (Figure S1). These findings suggest that SCP exhibits therapeutic potential in ameliorating age-related liver function decline. However, SCP showed negligible effects on attenuating the body weight reduction associated with aging (Figure S2). The H&E staining results showed that SCP did not show toxicity in the heart, liver, spleen, lung and kidney of mice, indicating that SCP was safe for mice (Fig. 2).

To evaluate the behavioral impacts of SCP on aging mice, we utilized the open field test to evaluate their spontaneous locomotor activity and exploratory tendencies. The total movement paths, traversal patterns within the central area, and number of entries into the central area were quantitatively recorded for each group of mice. The findings revealed that young mice, aging-SCP low, and aging-SCP high mice displayed longer movement paths and a broader range of movement within the given timeframe, showing a preference for exploring the central area. Conversely, aging-control mice reduced ambulatory distance and tended to stay near the periphery of the open field, indicating that SCP could enhance the spontaneous locomotor activity in aging mice (Fig. 3A). Moreover, the locomotor activity zones of mice can effectively indicate their anxiety levels. Statistical analysis showed that young mice, aging-SCP low, and aging-SCP high mice explored the central area more frequently and covered longer distances within, compared to aging-control mice (Fig. 3B-D). These findings imply that aging may trigger anxiety-like behavior in mice, whereas oral administration of SCP appears to mitigate aging-related anxiety phenotypes.

To further investigate the cognitive influence of SCP in aging mice, the Y-maze test was utilized to evaluate working memory. This behavioral test revealed that aging-control mice significantly reduced total movement distance and time spent in the testing area compared to young-control mice, indicative of a decline in age-associated working memory proficiency. Conversely, experimental analysis revealed that both aging-SCP low and aging-SCP high mice exhibited notably increased movement paths and durations in the testing area relative to aging-control mice, suggesting SCP’s potential in ameliorating age-related working memory deficits (Fig. 4).

Moreover, barnes maze outcomes revealed three distinct search strategies: random, serial, and spatial patterns for exploring holes (Fig. 5A). Over the initial six days of training, the time taken by all groups to locate the escape hole gradually decreased (Fig. 5B). Notably, during the testing phase, young mice demonstrated a diverse exploration strategy repertoire, while aging-control mice predominantly utilized random and serial strategies. In contrast, aging-SCP low and aging-SCP high mice favored serial and spatial strategies, with approximately 70% of aging-SCP high mice opting for the most efficient spatial strategy (Fig. 5C). Statistical analysis demonstrated that young-control, aging-SCP low, and aging-SCP high mice exhibited reduced exploration times and fewer errors compared to aging-control mice (Fig. 5D and E), indicative of superior spatial learning and memory abilities. These results demonstrate that SCP administration significantly attenuates age-related cognitive decline in learning and memory functions, supporting its potential as a cognitive-enhancing intervention for aging populations.

Hematoxylin and eosin(H&E) staining was utilized to systematically evaluate any pathological alterations in the brain tissue across four groups of mice. Compared to the young-control mice, a noticeable reduction in neuronal density was observed in aging-control mice. SCP treatment preserved neuronal density, with aging-SCP low and aging-SCP high mice exhibited a significantly higher number of neuronal cells than the aging-control group, indicating SCP's potential to attenuate age-associated neuronal loss (Fig. 6A). Furthermore, RT-qPCR analysis demonstrated significant upregulation of aging-associated genes APP and P53 in all other three groups as opposed to the aging-control mice, alongside reduced expression of the anti-aging gene SIRT1(Fig. 6B). These findings suggest that SCP could ameliorate age-related cerebral dysfunction by enhancing neuronal cell numbers and suppressing the expression of aging-related genes.

Aging, a progressive physiological deterioration in the body, has been strongly linked to alterations in gut microbiota [10]. In this study, AB staining and immunohistochemical staining of intestinal tissues were performed. The results revealed that, compared with the aging-control group, mice fed with SCP exhibited a significant increase in the number of goblet cells and enhanced secretion of acidic mucins in the intestinal tissue, suggesting that SCP may improve intestinal mucosal barrier function in aging mice (Fig. 7A). The intestinal mechanical barrier is composed of the basement membrane, epithelial cells, and the overlying mucus layer [11]. Among these components, epithelial cells maintain barrier integrity primarily through tight junctions. Zo-1 and Claudin-1 play crucial roles in the composition of tight junction proteins. Our study demonstrated that, compared with the aging-control group, both the aging-SCP low and aging-SCP high groups exhibited significantly increased protein expression levels of Zo-1 and Claudin-1 in intestinal tissues. These findings indicate that SCP supplementation effectively enhances intestinal barrier function in aging mice (Fig. 7A–C). We then systematically examined SCP's modulatory effects on the aging mice gut microbiome through high-throughput sequencing of the 16S rRNA gene V3-V4 hypervariable regions via Illumina NovaSeq for bacterial community structure analysis. Through species annotation, we identified and compared species at the phylum level across all groups and generated stacked bar charts depicting relative species abundances.

The results revealed notable differences in species composition at the phylum level among the experimental groups. Specifically, the aging-control group exhibited significant Firmicutes/Bacteroidetes(F/B) ratio dysregulation, characterized by a marked increase in Firmicutes abundance and a concurrent decrease in Bacteroidetes compared to the young-control group. Remarkably, SCP intervention significantly normalized the Firmicutes to Bacteroidetes ratio, aligning the gut microbiota structure toward youthful levels (Fig. 8A). The Firmicutes to Bacteroidetes ratio is a validated biomarker of the gut microbiota's equilibrium, suggesting that SCP possesses the capacity to counteract age-associated dysbiosis.

Furthermore, key diversity and richness indices including Shannon, Chao1, ACE, and Sobs exhibited a substantial increase in the gut microbiota of aging mice following SCP administration, as illustrated in Fig. 8B–E. To identify group-specific microbial biomarkers, we performed a Lefse analysis(LDA Score = 4). Differential abundance analysis identified significant taxonomic shifts in aging-SCP low and aging-SCP high groups in contrast to the aging-control group, notably marked by an upsurge in Clostridiales in the High SCP group and an increase in Oscillospirales in the Low SCP group (Fig. 8F and G). At the genus level, enrichment of g_Eubacterium_brachy_group and g_Prevotellaceae was evident in both the aging-SCP low and aging-SCP high groups, whereas g__Dubosiella did not exhibit a noticeable trend towards enrichment (Fig. 8H–J). Notably, literatures suggest that Eubacterium, Prevotellaceae, and Dubosiella are closely linked to the development and progression of neurodegenerative diseases such as Alzheimer's and Parkinson's disease [12–14]. Integrative analysis imply that SCP can restores age-disrupted gut microbial ecology, indicating gut-brain axis mediation of its geroprotective effects.

To systematically evaluate SCP's modulatory effects on age-related metabolic alterations, we conducted comprehensive fecal metabolomic profiling using metabolomics techniques. Fecal samples were collected from all mice prior to the conclusion of the experiment and subjected to LC–MS/MS analysis for metabolomics investigation. In order to assess the impact of SCP on aging mice, Principal Component Analysis(PCA) was employed to evaluate the metabolite expression profiles across the four experimental groups. The PCA results revealed a significant metabolic disparity between the young-control and aging-control groups in both positive and negative ion modes, indicating substantial differences in aging-related metabolite expression profiles. However, post-SCP intervention, a closer alignment in metabolite expression profiles was observed among the aging-SCP low, aging-SCP high, and young-control groups (Fig. 9A), suggesting SCP's potential in normalizing age-disrupted metabolic profiles. This finding was further supported by the Partial Least Squares Discriminant Analysis(PLS-DA) outcomes(Figure S3).

Differential analysis revealed significant variances in the metabolite expression profiles of the aging-SCP low group, aging-SCP high group, and young-control group compared to the aging-control group. A comprehensive screening for differential metabolites in these groups relative to the aging-control group was conducted (Fig. 9B). Integrative analysis identified 273 metabolites that were significantly upregulated in both SCP-treated groups and young-control group relative to age-control group (Fig. 9C). Through KEGG pathway annotation, these metabolites were notably enriched in the steroid hormone biosynthesis pathway (Fig. 9D). Furthermore, a correlation analysis was performed between gut microbiota and host metabolites following SCP intervention. The findings revealed a negative correlation of Dubosiella with Glycerophosphocholine, Laninamivir, and Alfaprostolum, among others, while showing a positive correlation with 6 β-Testosterone enanthate, Asitrilobin C, LysoPC(20:1(11Z)/0:0), and others (Fig. 10). These results highlight a strong correlation between the alteration in Dubosiella abundance within the intestine and the enhancement of metabolic patterns post-SCP intervention.

To further verify that SCP can activate the steroid hormone biosynthesis pathway, we employed RNA-seq to detected the gene expression profiles of brain tissues. GSVA analysis was used to calculate the steroid hormone biosynthesis score according to the genes set associated with this metabolic pathway. The results showed that the steroid hormone biosynthesis score appeared a low trend in the aging-control group, which showed the opposite trend in the young-control, aging-SCP low and aging-SCP high group (Fig. 11A). IHC analysis revealed significant upregulation of key proteins involved in steroid hormone biosynthesis COMT, UGT1A9 and HSD11B1 in both aging-SCP low and aging-SCP high group compared to aging-control group (Fig. 11B–C). Taken together, these observations suggest that SCP may delay brain tissue decline in aging mice by promoting steroid hormone biosynthesis.

All experiments and animal care in this study were approved by the ethics committee of the First Affiliated Hospital of Guangxi Medical University(2024-E380-01).

The manuscript is approved by all authors for publication.

Author Hongwei Guo is a Youth Editorial Board Member of Chinese Medicine, and has no other conflicts of interest to declare. Other authors declare that they have no competing interests.

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