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. 2026 Jun 25;47:102685. doi: 10.1016/j.bbrep.2026.102685

Salidroside and mesenchymal stem cells alleviate hypobaric hypoxia-induced lung injury and are associated with alterations in the gut-lung axis

Dengqin Ma a,b,c,d, Bang Xin c,d, Meng Li a,e, Bingfang Xie b, Qun Li b, Enpen Zhu a,c,d, Jing Luo a,c,d, Xiaoqin Ha a,⁎
PMCID: PMC13318544  PMID: 42388232

Abstract

High-altitude pulmonary injury (HAPI) results from hypobaric hypoxia and is characterized by excessive inflammation, oxidative imbalance, and disrupted barrier integrity. Salidroside and mesenchymal stem cells (MSCs) have shown protective effects against HAPI. However, it remains unclear whether these effects are associated with alterations in the gut-lung axis and whether combined therapy provides synergistic advantages. A rat model of hypobaric hypoxia was established. Lung injury was assessed by histopathology analysis and determination of IL-6, TNF-α, glutathione (GSH), and catalase (CAT) levels in lung tissues. Gut microbial composition was characterized using 16S rRNA sequencing of cecal samples, and serum metabolomics was analyzed using untargeted LC-MS/MS. Correlation and network analyses were performed to evaluate associations among lung injury indicators, differential metabolites, and microbial taxa. Treatment with either salidroside or MSCs significantly decreased lung injury scores, reduced IL-6, TNF-α, and CAT levels, and increased GSH concentrations (all p < 0.05). The combined treatment reduced TNF-α levels and increased GSH concentrations (p < 0.05), but no additional protective effect on lung injury was observed. Both salidroside and MSCs independently altered serum metabolite profiles and gut microbial composition. Correlation analysis revealed significant associations among lung injury indicators, differential serum metabolites, and differential gut microbiota taxa, suggesting a potential involvement of the gut-lung axis in the observed protective effects. These findings provide insight into the associations among lung injury, gut microbiota, and serum metabolites under hypobaric hypoxia and support further investigation of salidroside and MSCs as potential interventions for HAPI.

Keywords: Hypobaric hypoxia, Lung injury, Salidroside, Mesenchymal stem cells, Gut-lung axis, Gut microbiota, Metabolomics

Highlights

  • •

    Salidroside and MSCs alleviated hypobaric hypoxia-induced lung injury.

  • •

    Combined therapy showed no clear synergistic protection in rats.

  • •

    Salidroside and MSCs reshaped gut microbiota and serum metabolites.

  • •

    Protective effects may involve regulation of the gut-lung axis.

1. Introduction

High-altitude pulmonary injury (HAPI) is a serious respiratory condition triggered by low-pressure hypoxic exposure at high-altitude environments [1]. It is clinically characterized by hypoxia-related lung damage, high-altitude pulmonary edema (HAPE), and high-altitude pulmonary hypertension (HAPH), all of which pose significant health risks. Some common underlying mechanisms include increased inflammation and oxidative stress, damage to the alveolar-vascular barrier leading to excessive permeability, and impaired gas exchange, all of which increase the chances of cardiopulmonary complications [2,3].

From a pathophysiological state, hypoxic pulmonary vasoconstriction acts as an adaptive mechanism in the early stages, redirecting blood flow to improve ventilation-perfusion balance [4,5]. During prolonged hypoxic conditions, this response becomes detrimental, leading to interstitial fluid accumulation, the recruitment of inflammatory cells, thickening of alveolar septa, and alveolar edema, which can ultimately result in HAPE [6,7]. Prolonged hypoxic exposure further causes vascular remodeling characterized by endothelial cell damage, smooth muscle proliferation, muscularization of small arteries, and adventitial fibrosis, which can progress to HAPH and right ventricular failure [8,9]. The pathogenesis of HAPI involves a network of interrelated biological processes, including immune dysregulation and inflammatory cascades [10], oxidative stress [11], disruption of the endothelial barrier [12], and gene polymorphisms [13], all of which have been widely documented. Currently, the methods available for preventing and managing HAPI remain limited, highlighting the urgent need for more effective treatments.

The concept of the gut-lung axis has provide a new interorgan perspective for understanding the pathogenesis of HAPI. Previous studies have suggested that at high altitudes, hypobaric hypoxia may disrupt intestinal barrier function and alter gut microbial composition, accompanied by reduced short-chain fatty acid synthesis and translocation of endotoxins, which are associated with systemic inflammation and pulmonary injury [[14], [15], [16]]. Therefore, targeting the gut microbiome and metabolome network could be an effective strategy for reducing HAPI.

Salidroside, the main bioactive compound of traditional Chinese medicine (TCM) Rhodiola rosea, shows antioxidant, anti-inflammatory, and immunomodulatory properties [17]. Mesenchymal stem cell (MSC) possess potent tissue repair and immunomodulatory capabilities and have shown therapeutic potential in various inflammatory disorders [[18], [19], [20]]. However, the mechanisms by which salidroside or MSC alleviate HAPI are not fully explored, particularly regarding their associations with alterations in the gut-lung axis, the possibility of synergistic effects from combined treatment, and the specific microbial taxa and metabolic pathways involved.

To investigate the effects of salidroside and human umbilical cord-derived MSCs, both individually and in combination, a rat model of hypobaric hypoxia was established. By combining 16S rRNA sequencing and untargeted serum metabolomics, a microbiota-metabolite-lung injury association framework was constructed to explore potential links among gut microbial alterations, metabolic changes, and lung injury, and to provide insights into the possible involvement of the gut-lung axis in HAPI.

2. Materials and methods

2.1. Isolation and expansion of MSCs

Written informed consent was obtained from all donors before starting this study. MSCs were cultured at the Key Laboratory of Stem Cells and Gene Drugs of Gansu Province, Lanzhou, China. All procedures followed the approved experimental protocol of the Animal Ethics Committee of the 940th Hospital of the Joint Logistics Support Force of PLA (approval number 2024KYLL314D). Briefly, umbilical cords and placentas from full-term newborns were collected from a tertiary care hospital and washed with saline to remove blood clots. The umbilical cords were washed under sterile conditions, with blood vessels removed, and cut into tissue pieces (1–2 mm3). These tissue pieces were evenly placed in cell culture dishes, and primary stem cell culture medium (89% α-MEM, 10% fetal bovine serum, and 1% penicillin/streptomycin) was added. The dishes were kept under static culture in a humidified incubator at 37°C with 5% CO2. The culture medium was replaced regularly, and once the cells reached 80–90% confluence, umbilical cord-derived MSCs were passaged. Second-generation (P2) MSCs were evaluated for their multipotent differentiation potential via osteogenic, chondrogenic, and adipogenic induction media. Third-generation (P3) cells were examined for surface antigen expression using flow cytometry. MSCs from 4th–6th passages (P4–P6) were then used for all experimental procedures.

2.2. Characterization of MSCs

For immunophenotypic characterization, 5 μL of each monoclonal antibody: APC-Cy7 conjugated anti-human CD34 (FCM/4H11, NuoHe Bio-Tech, China), PerCP-conjugated anti-human CD45 (FCM/HI30, NuoHe Bio-Tech, China), PE-conjugated anti-human CD73 (FCM/AD2, NuoHe Bio-Tech, China), FITC-conjugated anti-human CD90 (NuoHe Bio-Tech, China), and APC-conjugated anti-human CD105 (FCM/MEM-226, NuoHe Bio-Tech, China), was added separately to 250 μL of PBS containing stem cells (2.5 × 105 cells). The mixtures were incubated at ambient temperature for 30 min in the dark. After incubation, the cells were rinsed once with PBS to remove any unbound antibodies. Flow cytometric analysis was then conducted using a BD FACSCanto II system. The multilineage differentiation potential of P2 human umbilical cord-derived MSCs was evaluated using the Osteogenic Induction Kit (FY200006, Fuyuanbio, China), Adipogenic Induction Kit (FY200007, Fuyuanbio, China), and Chondrogenic Induction Kit (FY200008, Fuyuanbio, China).

2.3. Laboratory animal and model development

The hypobaric hypoxia rat model was developed using a previously described method [21], with slight modifications to the treatment protocol. Metabolomics profiling and statistical analyses were conducted as per the procedures outlined in a previous publication. Using a random number table generated before treatment allocation, a total of 40 male Sprague-Dawley rats, 8 weeks old, were randomly divided into five groups (n = 8/group): normal control (Control), hypobaric hypoxia chamber control (HC), MSC treatment (MSC), salidroside treatment (Sal), and combined salidroside + MSC treatment (SAM). The sample size (n = 8/group) was determined based on our previous study design [21] and preliminary experiments. Healthy rats showing no signs of illness during the acclimatization period were included in the study. No rats died during the experimental period, and no rats or samples were excluded from the final analyses.

Rats in the Control group were housed in Lanzhou (altitude 1588 m), while the experimental groups (HC, Sal, MSC, and SAM) were exposed to a hypobaric hypoxia chamber simulating an altitude of 6500 m for 14 consecutive days. In the MSC group, 2 × 106 MSCs were administered via tail vein injection 1 h before hypobaric hypoxia chamber exposure, with additional injections every 5 days for a total of three doses. The Sal group received oral salidroside (100 mg/kg/day) starting 5 days before exposure and continued throughout the study; controls received equal volumes of saline. The experimental workflow is shown in Fig. 1.

Fig. 1.

Fig. 1

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Experimental workflow of the study.

The study was conducted and reported in accordance with the ARRIVE guidelines. All animal handling and experimental procedures were approved by the Institutional Animal Care and Use Committee of the 940th Hospital of Joint Logistics Support Force of PLA (approval No. 2022KYLL168) and were conducted in accordance with institutional animal welfare regulations.

For sample collection, the colon was opened along the midline using sterile scissors, and the intestinal contents were transferred into sterile cryotubes. Fecal material was snap-frozen in liquid nitrogen and stored at −80°C. A 4 cm segment of colon adjacent to the lesion site was excised, washed with chilled physiological saline (0–4°C), and preserved in 4% neutral paraformaldehyde for 48 h before histological analysis.

2.4. Detection and analysis of gut microbiota

Genomic DNA was extracted from fecal samples using the DNeasy PowerSoil Kit (Mo Bio/QIAGEN). The variable region of the 16S rRNA gene was amplified via PCR with Pyrobest DNA Polymerase (TaKaRa, DR500A), followed by sequencing. The amplified products were purified through gel extraction (AxyPrep DNA Gel Extraction Kit, Axygen, AP-GX-500), and DNA concentrations were measured using a BioTek Flx800 microplate reader with the Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen, P7589). Sequencing libraries were prepared based on the Illumina TruSeq DNA Sample Preparation protocol.

Microbial community data were processed using QIIME2 (2019.4), ggplot2, and phyloseq in R, along with KronaTools (v2.7) and HUMAnN2. Alpha diversity indices, including Shannon, Simpson, and Chao1, were used to evaluate within-group diversity. Community structure visualization was performed using principal component analysis (PCA), principal coordinate analysis (PCoA), and metric multidimensional scaling (MDS). PCA was used for linear datasets, while PCoA and MDS were applied for distance-based ordination. Differentially abundant taxa were identified using LEfSe analysis, based on linear discriminant analysis (LDA) effect size, with significance defined as an LDA score >3 and p < 0.05. Data analyses and visualizations, such as bar graphs, heatmaps, scatter plots, and network diagrams, were generated using the online platform BioDeep (https://www.biodeep.cn/home).

2.5. Metabolomics analysis

Serum samples were subjected to non-targeted metabolomic profiling using a high-resolution mass spectrometry-based platform. Raw data processing, including peak extraction, alignment, normalization, and metabolite annotation, was performed according to the standard workflow. Metabolite annotation was conducted using HMDB, MassBank, LipidMaps, mzCloud, KEGG, and the proprietary standard compound library established by Nuomi Metabolomics. Metabolite identification followed the Metabolomics Standards Initiative (MSI) guidelines. Metabolites confirmed by authentic standards based on retention time, accurate mass, and MS/MS spectra were assigned as MSI level 1, whereas metabolites annotated through MS/MS spectral matching without authentic standard confirmation were assigned as MSI level 2. Only metabolites meeting MSI level 1 or level 2 criteria were included in this study.

2.6. Measurement of inflammatory and oxidative stress markers in lung tissue

Based on the manufacturers’ protocols, IL-6 and TNF-α levels in lung tissue were quantified using ELISA kits (Jiangsu Jingmei, China). The concentrations of reduced glutathione (GSH) and catalase (CAT) were determined with commercially available assay kits based on the visible-light method (Nanjing Jiancheng Bioengineering Institute, China).

2.7. Histopathological scoring of lung injury

Lung damage under hypobaric hypoxia was evaluated using a modified Smith scoring system. Paraffin-embedded lung sections (4 μm) were stained with hematoxylin and eosin and evaluated by two independent, blinded pathologists. The scoring parameters included pulmonary edema, compensatory bullae formation, inflammatory cell infiltration in the interstitium, and erythrocyte accumulation. Each parameter was graded on a semi-quantitative scale of 0–4, where 0 = no detectable lesion, 1 = involvement of ≤25% of the field, 2 = 25–50%, 3 = 50–75%, and 4 = > 75%. The overall lung injury score was the sum of the individual parameters. For each sample, ten high-power fields were examined, and the average score was calculated.

2.8. Statistical analysis

Data were statistically analyzed using GraphPad Prism 10 and SPSS 27. Data normality was assessed using the Shapiro-Wilk test. Normally distributed data were analyzed by one-way ANOVA followed by Dunnett's multiple-comparison test, with the HC group serving as the reference group for treatment comparisons. Non-normally distributed data were analyzed using the Kruskal-Wallis test. Statistical significance was set at p < 0.05. Associations among cytokines, oxidative stress parameters, microbial taxa, and metabolites were examined using Spearman's rank correlation analysis, and the results are presented as correlation coefficients (r) with corresponding p-values. Correlation networks were visualized using Cytoscape (version 3.9.1), while data plots and additional graphics were generated with GraphPad Prism and R software (version 4.2.2).

3. Results

3.1. Characterization of MSCs

Human umbilical cord-derived MSCs showed typical morphological features and multipotent differentiation ability. Under inductive conditions, MSCs successfully differentiated into osteoblasts, adipocytes, and chondrocytes, confirmed by Alizarin Red S, Oil Red O, and Alcian Blue staining, respectively (Fig. 2A–C). Flow cytometric profiling showed high surface expression of CD105 (98.4%), CD90 (98.2%), and CD73 (98.2%), with low expression of hematopoietic markers CD34 (0%) and CD45 (0.1%), consistent with the immunophenotypic profile of MSCs (Fig. 2D).

Fig. 2.

Fig. 2

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Characterization of human umbilical cord-derived mesenchymal stem cells. (A) Alizarin Red S staining confirmed osteogenic differentiation (100×), scale bar: 100 μm. (B) Oil Red O staining confirmed adipogenic differentiation (200×), scale bar: 100 μm. (C) Alcian Blue staining confirmed chondrogenic differentiation (50×), scale bar: 400 μm. (D) Flow cytometric analysis of MSC surface marker expression.

3.2. Effects of different interventions on lung injury after short-term hypobaric hypoxia

After 14 days of hypobaric hypoxia, lung tissues from the HC group showed significant pathological changes compared to the Control group. These included structural disruption, thickening of small arteriolar walls and alveolar septa, increased red blood cell accumulation, extensive infiltration of inflammatory cells, and perivascular and peribronchiolar lymphocytic infiltration, along with a higher occurrence of compensatory emphysema. Hypobaric hypoxia caused significant pathological effects in the colon, such as villus thickening, erythrocytosis, and extensive inflammatory infiltration. Treatment with salidroside or MSCs effectively reduced these histopathological lesions in both lung and colon tissues (Fig. 3A and B). Lung injury scores were significantly lower in the MSC and Sal groups compared to the HC group (Fig. 3C). Furthermore, in the HC group, lung tissue levels of IL-6, TNF-α, and CAT were significantly elevated. However, GSH levels were significantly lower compared to the Control group. Both salidroside and MSC treatments significantly reduced these inflammatory and oxidative stress markers (Fig. 3D–G, p < 0.05). These results suggest that either salidroside or MSCs alone can lessen lung and intestinal damage caused by hypobaric hypoxia.

Fig. 3.

Fig. 3

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Protective effects of salidroside or mesenchymal stem cells on hypobaric hypoxia-induced lung injury after 14 days. (A) Histological analysis of lung tissue, upper panel: 40×, scale bar: 625 μm; lower panel: 100×, scale bar: 200 μm. (B) Histological analysis of colon tissue, upper panel: 40×, scale bar: 625 μm; lower panel: 100×, scale bar: 200 μm. (C) Lung injury scores, (D) IL-6 levels, (E) TNF-α levels, (F) CAT levels, and (G) GSH levels in lung tissues. Data are presented as n = 8/group. Differences among groups were analyzed using one-way ANOVA followed by Dunnett's multiple-comparison test against the HC group. ns, p ≥ 0.05; *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001. Control, normal control group; HC hypobaric hypoxia chamber control group; MSC, mesenchymal stem cell-treated group; Sal, salidroside treated-group.

In the SAM group, which received combined treatment with salidroside and MSCs, inflammatory cell infiltration in both lung and colon tissues was slightly reduced compared to the HC group. Biochemically, TNF-α levels were significantly lower, and GSH levels were altered (p < 0.05), while IL-6 and CAT levels showed no significant differences (Fig. 4). No further analyses were performed for the combined treatment group.

Fig. 4.

Fig. 4

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Effects of combined salidroside and mesenchymal stem cells on hypobaric hypoxia-induced lung injury after 14 days. (A) Histological analysis of lung tissue, upper panel: 40×, scale bar: 625 μm; lower panel: 100×, scale bar: 200 μm. (B) Histological analysis of colon tissue, upper panel: 40×, scale bar: 625 μm; lower panel: 100×, scale bar: 200 μm. (C) Lung pathological score, (D) IL-6 levels, (E) TNF-α levels, (F) CAT levels, and (G) GSH levels in lung tissues. Data are presented as n = 8/group. Differences among groups were analyzed using one-way ANOVA followed by Dunnett's multiple-comparison test against the HC group. ns, p ≥ 0.05; *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001. GSH, glutathione; CAT, catalase; Control, normal control group; HC hypobaric hypoxia chamber control group; Sal, salidroside treated-group; SAM, combined salidroside and mesenchymal stem cell-treated group.

3.3. Effects of salidroside or MSCs on metabolite profiles in serum after short-term hypobaric hypoxia

The non-targeted metabolomic profiling of serum samples from the four groups (Control, HC, Sal, and MSC) revealed distinct metabolic profiles among groups. PCA analysis showed group separation in both positive and negative ionization modes (Fig. 5A and B). This separation was further confirmed by partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) (Fig. 5C–F). The stability of the OPLS-DA model was evaluated through a permutation test, which confirmed its statistical validity by verifying the goodness of fit (R2) and predictive ability (Q2) values. Moreover, the negative intercept of the Q2 regression line in cross-validation excluded overfitting, indicating strong predictive reliability of the model.

Fig. 5.

Fig. 5

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Effect of salidroside and mesenchymal stem cells on serum metabolite profile after short-term hypobaric hypoxia exposure. (A, B) PCA score plots for Control, HC, Sal, MSC, and Quality Control (QC) samples in both positive and negative ionization modes. (C, D) PLS-DA score plots of the four groups in positive and negative modes, including statistical validation. (E, F) OPLS-DA score plots of the four groups in both modes, with validation results. A three-line table presents model validation parameters, where indicates the number of principal components used in the model, R2X (cum) represents the total variance explained by the model, and R2Y (cum) indicates the cumulative Y variance explanation rate, i.e., the model's explanatory power for the response variable (Y). Q2 (cum) shows the cross-validation predictive power of the model. Control, normal control group; HC, hypobaric hypoxia chamber control group; Sal, salidroside-treated group, MSC, mesenchymal stem cell-treated group; PCA, principal component analysis; PLS-DA, partial least squares discriminant analysis, OPLS-DA, orthogonal partial least squares discriminant analysis.

Based on the selection criteria of VIP >1 and p < 0.05, a total of 472 metabolites were annotated, including carbohydrates and derivatives, amino acids and related compounds, bile acids, alcohol derivatives, fatty acids and conjugates, nucleotides, vitamins, and other metabolites. Comparison of HC versus Control groups showed 117 significantly altered metabolites, among them 84 were upregulated and 33 were downregulated under hypobaric hypoxia (p < 0.05, Fig. 6A). In the Sal group compared to HC, 90 altered metabolites were found, with 53 increased and 37 decreased (Fig. 6B). In the MSC group compared to HC, 59 differential metabolites were identified, with 35 upregulated and 24 downregulated (Fig. 6C).

Fig. 6.

Fig. 6

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Heatmaps and bar charts illustrating variations in annotated metabolites between HC and Control (A), Sal (B), and MSC (C). Control, normal control group; HC hypobaric hypoxia chamber control group; Sal, salidroside treated-group; MSC, mesenchymal stem cell-treated group.

The distribution of altered metabolites is visualized through a cluster heatmap (Fig. 7A). KEGG enrichment analysis of these metabolites (Fig. 7B) identified significant differences in multiple pathways, including lipolysis regulation in adipocytes, oleic acid metabolism, vascular smooth muscle contraction, longevity-regulating pathways, central carbon metabolism in cancer, cholesterol metabolism, alcohol metabolism, Hedgehog signaling, melanogenesis, cGMP-PKG signaling, cocaine addiction, amphetamine addiction, and prion disease (p < 0.05). These results indicated that short-term hypobaric hypoxia significantly disrupts these metabolic pathways, which were also affected after salidroside or MSC treatment. Differentially annotated metabolites mapped to these metabolic pathways included l-tyrosine, adenosine, cyclic AMP, corticosterone, 8,11,14-eicosatrienoic acid, 13-l-hydroxylinoleic acid, 9,10-epoxyoctadecenoic acid, 9(S)-HPODE, 20-HETE, 1,1-dimethylbiguanide, l-cystine, fumaric acid, l-asparagine, glycocholic acid, and taurocholic acid.

Fig. 7.

Fig. 7

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Heatmap and KEGG pathway analysis of differential annotated metabolites in four groups. (A) Heatmap showing the clustering of metabolites that differ among the Control, HC, Sal, and MSC groups. (B) Bar plot displaying KEGG pathway enrichment of differential metabolites. (C) Network diagram of differential metabolites and related biological pathways; blue nodes represent pathways, and colored nodes denote metabolites. The size of pathways reflects the number of connected metabolites, with larger nodes indicating higher connectivity. The intensity of metabolite node colors corresponds to log2(FC) values, where darker shades indicate greater fold changes. Control, normal control group; HC hypobaric hypoxia chamber control group; Sal, salidroside treated-group; MSC, mesenchymal stem cell-treated group.

Several annotated metabolites showed significant differences but were not included in the pathway enrichment results. These annotations included Perindopril, Enalaprilat, L-2-hydroxyglutaric acid, l-xylonate, l-ribulose, cis-aconitic acid, D-alanyl-d-alanine, aminosalicylic acid, 5-hydroxypentanoic acid, and others (Fig. 8).

Fig. 8.

Fig. 8

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Relative abundance of selected annotated metabolites in serum among the four groups. Differences among groups were analyzed using one-way ANOVA followed by Dunnett's multiple-comparison test against the HC group. Data are presented as n = 8/group. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Control, normal control group; HC hypobaric hypoxia chamber control group; Sal, salidroside treated-group; MSC, mesenchymal stem cell-treated group.

3.4. Effects of salidroside and MSCs on gut microbiota after short-term hypobaric hypoxia exposure

3.4.1. Alpha and beta diversity of gut microbiota

The richness and alpha diversity of gut microbiota were examined through the Chao1, Shannon, and Simpson indices. As shown in Fig. 9, these measures showed a decreasing trend in HC rats compared to the Control group; however, the reductions were not statistically significant. Similarly, no significant differences were observed between the HC group and the Sal or MSC groups (Fig. 9A–C). To further explore differences in microbial composition among groups, beta diversity was evaluated. Non-metric multidimensional scaling (NMDS) plots (Fig. 9D) revealed distinct separation patterns in microbial community structures across the four groups, indicating significant intergroup variation (p < 0.01 vs. HC group, assessed by PERMANOVA). The multidimensional scaling (MDS) analysis yielded a stress value of 0.171 (p < 0.2), suggesting a reliable representation of community structure differences. These results indicated that treatment with salidroside or MSCs significantly alters the gut microbiota architecture after hypobaric hypoxia. The Venn diagram analysis identified 394 shared operational taxonomic units (OTUs) among all groups, along with 4245 OTUs specific to the Control group, 3069 unique to the HC rats, 2804 exclusive to the salidroside-treated rats, and 2883 unique to the MSC-treated rats (Fig. 9E).

Fig. 9.

Fig. 9

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Impact of salidroside or mesenchymal stem cells on gut microbiota composition and structure following short-term hypobaric hypoxia exposure. (A–C) Assessment of gut microbiota α-diversity among different experimental groups. (D) β-diversity analysis using non-metric multidimensional scaling highlights differences in microbial community composition between groups. (E) Venn diagrams showing the count of unique and shared operational taxonomic units (OTUs) in all experimental groups. Data are presented as mean ± SD (n = 8/group). Differences among groups were analyzed using one-way ANOVA followed by Dunnett's multiple-comparison test against the HC group. ns, p ≥ 0.05. Control, normal control group; HC hypobaric hypoxia chamber control group; Sal, salidroside treated-group; MSC, mesenchymal stem cell-treated group.

3.4.2. Analysis of species composition of gut microbiota

At the phylum level, the main gut microbiota identified in the four rat groups consisted of Firmicutes, Actinobacteria, Proteobacteria, Bacteroidetes, Tenericutes, TM7, and Verrucomicrobia, collectively accounting for over 99% of the total microbial abundance (Fig. 10A). In the HC group, the proportions of Firmicutes and Tenericutes were higher, while Bacteroidetes and Actinobacteria were lower. Analysis of the top 20 most abundant genera showed significant compositional differences among the groups (Fig. 10B). At the genus level (Fig. 10C), the HC group had lower levels of Lactobacillus, Oscillospira, Corynebacterium, Coprococcus, Adlercreutzia, Psychobacter, Aerococcus, Clostridium, rc4-4, Jeotgalococcus, Akkermansia, Rothia, and Bacteroides compared to the Control group. The abundance of Ruminococcus, Allobaculum, Desulfovibrio, [Ruminococcus], Phascolarctobacterium, Blautia, Roseburia, Turicibacter, and SMB53 was higher. After treatment with salidroside or MSCs, differences in genus-level abundance were observed. Levels of Lactobacillus, Akkermansia, Bacteroides, [Prevotella], and Enterococcus increased, while Ruminococcus, [Ruminococcus], SMB53, and Turicibacter decreased. The abundance of Clostridiaceae_Clostridium increased significantly after MSC intervention but decreased after salidroside treatment.

Fig. 10.

Fig. 10

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Effect of salidroside or mesenchymal stem cells on gut microbial composition following short-term hypobaric hypoxia exposure. (A) Stacked bar chart showing species distribution and relative abundance at the phylum level. (B) Stacked bar chart illustrating species distribution and relative abundance at the genus level. (C) Bar plot presenting genus-level relative abundance across experimental groups. Data are presented as n = 8/group. Differences among groups were analyzed using one-way ANOVA followed by Dunnett's multiple-comparison test against the HC group. ns, p ≥ 0.05; *p < 0.05. Control, normal control group; HC hypobaric hypoxia chamber control group; Sal, salidroside treated-group; MSC, mesenchymal stem cell-treated group.

3.4.3. LEfSe analysis of gut microbiota

LEfSe analysis was used to identify biomarkers in each experimental group, with those showing LDA scores greater than 4.0 considered significant. In the Control group, the significantly enriched microbiota included o_Actinomycota, g_Corynebacterium, f_Corynebacteriaceae, c_Actinobacteria, p_Actinobacteria, g_Bacteroides, f_Bacteroidaceae, c_Betaproteobacteria, and o_Burkholderiales. In HC group, the enriched microbiota included p_Firmicutes, o_Clostridiales, c_Clostridia, f_Lachnospiraceae, g_[Ruminococcus], g_Helicobacter, c_Epsilonproteobacteria, o_Campylobacterales, and f_Helicobacteraceae. In the Sal group, significant enrichment was observed in c_Erysipelotrichi, f_Erysipelotrichaceae, o_Erysipelotrichales, f_Erysipelotrichaceae_g_Clostridium, f_Bifidobacteriaceae, o_Bifidobacteriales, g_Bifidobacterium, g_Blautia, g_[Eubacterium], and g_Streptococcus. The MSC group showed significant enrichment in f_Ruminococcaceae, g_Macrococcus, g_Lactococcus, f_Streptococcaceae, f_Clostridiaceae, f_Clostridiaceae_g_Clostridium, p_Bacteroidetes, c_Bacteroidia, and o_Bacteroidales (Fig. 11A). At the genus level, group-specific biomarkers are depicted in Fig. 11B. The Control group included g_Corynebacterium and g_Bacteroides. The HC group featured g_[Ruminococcus] and g_Helicobacter. The MSC group was characterized by g_Macrococcus, g_Lactococcus, and f_Clostridiaceae_g_Clostridium, while the Sal group included g_[Eubacterium] and f_ Erysipelotrichaceae_g_Clostridium.

Fig. 11.

Fig. 11

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LDA effect size histogram and cladogram illustrating intergroup taxonomic differences. (A) LEfSe analysis showing taxa with significant differential abundance among groups (LDA >3, p < 0.05). Y axis represents taxonomic units with substantial differences between groups, and X axis represents the logarithmic scores of LDA analysis for each taxonomic unit visually. (B) Cladogram illustrating the phylogenetic distribution of differentially abundant taxa. The rings, from inside to outside, represent the taxonomic hierarchy of phylum (p), class (c), order (o), family (f), and genus (g), in turn. Each node corresponds to a taxonomic unit, and node size reflects its relative abundance. LDA, linear discriminant analysis; Control, normal control; HC, hypobaric hypoxia chamber control; Sal, salidroside treatment; MSC, mesenchymal stem cell treatment.

3.5. Correlation analysis of gut microbiota, metabolites, and phenotypes

A heat map of correlations between lung injury, serum metabolites, and gut microbiota, as well as an integrated visualization network of lung injury indicators, metabolites, and microbiota, was constructed using Spearman correlation analysis (Fig. 12). Correlation analysis of four lung injury indicators, 15 serum metabolites, and 11 gut microbial taxa revealed that four of the 11 microbial taxa were significantly associated with lung injury indicators (p < 0.05). TNF-α was positively correlated with g_SMB53 (p = 0.025), IL-6 was positively correlated with g_[Ruminococcus] (p = 0.029), GSH was positively correlated with f_Lachnospiraceae_g_Clostridium (p = 0.037), and CAT was positively correlated with g_Turicibacter (p = 0.047). Among the 15 annotated metabolites, 7 were significantly correlated with the lung injury index and gut microbiota (p < 0.05), including perindopril, L-2-Hydroxyglutamic acid, l-xylonate, l-ribulose, D-alanyl-d-alanine, cis-aconitic acid, and aminosalicylic acid. GSH was negatively correlated with cis-aconic acid, L-2-hydroxyglutamic acid, l-ribulose, aminosalicylic acid, l-xylonate, and D-alanyl-d-alanine (p < 0.05). CAT was positively correlated with cis-aconic acid, l-Xylonate, perindopril, and L-2-hydroxyglutamic acid (p < 0.05), IL-6 was positively correlated with D-Alanyl-d-alanine and aminosalicylic acid (p < 0.05), and TNF-α was positively correlated with L-2-hydroxyglutamic acid (p < 0.05). Significant correlation analysis between gut microbiota and serum metabolites suggested that g_Turicibacter was positively correlated with L-2-hydroxyglutamic acid, perindopril, l-xylonate, and l-ribulose (p < 0.05). g_Enterococcus was negatively correlated with cis-aconitic acid (p < 0.05). g_[Ruminococcus] was positively correlated with perindopril, L-2-hydroxyglutamic acid (p < 0.05). g_SMB53 was positively correlated with D-Alanyl-d-alanine and aminosalicylic acid (p < 0.05). g_Ruminococcus was positively correlated with l-Xylonate, D-Alanyl-d-alanine (p < 0.05). f_Lachnospiraceae_g_Clostridium was positively correlated with perindopril, L-2-hydroxyglutamic acid, l-xylonate, l-ribulose (p < 0.05).

Fig. 12.

Fig. 12

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Correlation analysis of lung injury indicators, serum metabolites, and gut microbiota. (A) Heatmap illustrating pairwise correlations among lung injury indicators, differential serum metabolites, and gut microbial taxa, calculated using Spearman's rank correlation. Red and blue represent the positive and negative correlations, respectively. The p value and the depth of color indicate the degree of correlation. (B) Integrated correlation network linking lung injury indicators, metabolites, and gut microbiota. Nodes represent individual indicators, metabolites, or bacterial taxa, while edges denote significant correlations (p < 0.05, |r| > 0.3).

Salidroside or MSC intervention significantly reduced the levels of IL-6, TNF-α, and CAT, and increased the level of GSH in the lung after short-term hypobaric hypoxia exposure. These lung injury indicators were positively correlated with specific microbial taxa, including g_SMB53, g_Ruminococcus, g_Turicibacter, and f_Lachnospiraceae_g_Clostridium. Several annotated metabolite, including perindopril, L-2-hydroxyglutamic acid, l-Xylonate, l-Ribulose, D-Alanyl-d-alanine, cis-aconic acid, and aminosalicylic acid, were significantly associated with both lung injury and gut microbiota.

4. Discussion

HAPI is a significant medical concern for individuals exposed to high-altitude environments, highlighting the urgent need for effective acclimatization methods and treatment options. The development of HAPI is strongly associated with uncontrolled inflammation and oxidative stress [22]. Data from both clinical and experimental studies highlight a dual interaction between the lungs and the gut [23]. Hypobaric hypoxia, the main cause at high altitudes, disrupts the oxygen homeostasis in the intestines, resulting in epithelial damage, compromised barrier function, microbial translocation, and changes in gut microbial communities and metabolite dynamics [24]. These intestinal disturbances have been associated with the sympathetic nervous system, immune response, and metabolic regulation, which may contribute to pulmonary injury [25]. In this study, hypobaric hypoxia caused significant structural and functional damage to both lung and colonic tissues, along with increased inflammatory mediators and oxidative stress. Treatment with salidroside or MSCs significantly alleviated these pathological changes, accompanied by reduced inflammatory cytokine levels and improved oxidative stress status.

HAPI is a serious health concern for individuals exposed to high-altitude conditions, mainly caused by abnormal inflammation and oxidative stress [22]. Recently, the concept of the “gut-lung axis” has provided new insights for understanding the underlying mechanisms of HAPI [26]. Hypobaric hypoxia, the dominant pathogenic factor in high-altitude environments, initially disrupts the intestinal microenvironment. This disturbance, characterized by impaired barrier function, microbial dysbiosis, and metabolic changes, results in systemic inflammation and exacerbates lung damage. In this study, salidroside and MSCs showed protective effects against pulmonary injury, which were accompanied by improvements in gut microbial dysbiosis and alterations in serum metabolite profiles. Correlation analyses further revealed close associations among lung injury indicators, microbial taxa, and serum metabolites. These findings provide supportive evidence for a potential role of the gut-lung axis in hypobaric hypoxia-induced lung injury in this model and warrant further mechanistic studies to clarify its contribution to the protective effects of salidroside and MSCs.

Hypobaric hypoxia primarily affects the intestinal system, which is highly sensitive to changes in oxygen levels, leading to damage to the intestinal barrier and microbial dysbiosis, as shown in this model [24]. During hypoxia, there was a significant decrease in several genera that produce short-chain fatty acids and support the barrier, i.e., Oscillospira, Coprococcus, Bacteroides, Prevotella, and Akkermansia. Simultaneously, an increase in Desulfovibrio, a genus associated with pro-inflammatory activity and endotoxin release, was observed [[27], [28], [29], [30], [31]]. This shift in microbiota, characterized by the growth of pathogenic microbes and the loss of beneficial microbes, is a key event that increases intestinal permeability. These changes may facilitate the translocation of microbial metabolites and pathogen-associated molecular patterns into the circulation, potentially contributing to pulmonary inflammation [23,25]. Treatment with salidroside and MSCs was found to significantly reverse the dysbiosis changes. The relative abundance of beneficial genera, including Lactobacillus, Akkermansia, Bacteroides, Prevotella, and Enterococcus, was restored, while levels of Ruminococcus, SMB53, and Turicibacter decreased, indicating a microbial composition that favors intestinal barrier repair [27,[30], [31], [32], [33]]. These effects appear to arise through different but complementary mechanisms: salidroside, due to its antioxidant properties, may directly reduce hypoxia-induced stress in intestinal epithelial cells, supporting colonization by beneficial anaerobes [34,35]. In comparison, MSCs promote microbial homeostasis indirectly by reducing intestinal inflammation through strong immunomodulatory effects [36]. By improving gut microbial balance and intestinal homeostasis, both interventions may reduce the transmission of inflammatory signals associated with lung injury.

The metabolomic analysis provided further insights into potential microbiota-host metabolic interactions associated with hypobaric hypoxia-induced lung injury. Among the differential metabolites identified, annotations corresponding to perindopril and enalaprilat showed significant alterations following hypobaric hypoxia and subsequent treatment. Because these annotations were derived from non-targeted metabolomics and were not confirmed using authentic standards, they should be interpreted with caution. Nevertheless, the observed changes may suggest that pathways related to renin-angiotensin system (RAS) regulation could be involved in the response to hypobaric hypoxia and warrant further investigation. Previous studies have shown that certain Enterococcus strains can produce bioactive peptides with angiotensin-converting enzyme (ACE)-inhibitory properties [[37], [38], [39]], while ACE2 serves as an important regulator of the RAS and has also been implicated in gut microbial homeostasis [[40], [41], [42]]. Although the present study did not directly assess ACE or ACE2 activity, these observations raise the possibility that microbiota-related regulation of RAS signaling may be associated with the protective effects of salidroside and MSCs. Further targeted metabolomic and mechanistic studies are required to validate this hypothesis.

The metabolomic analysis further highlights that, in addition to the RAS, cellular oxidative stress and disrupted energy metabolism are key points linking intestinal dysregulation to lung injury. In this study, higher levels of L-2-hydroxyglutarate (L-2-HG), a metabolite closely associated with mitochondrial oxidative stress, were observed under hypoxic conditions, consistent with previous reports that identify L-2-HG as a pathogenic biomarker for lung injury [[43], [44], [45]]. Changes in l-xylonate and l-ribulose, both crucial to carbohydrate metabolism, also indicated disturbances in glucose consumption. However, treatment with either salidroside or MSCs significantly reversed these metabolic disturbances, suggesting that their protective effects are partly due to reducing oxidative stress and restoring cellular energy homeostasis. Consistent with the observed improvement in oxidative stress status, CAT activity was elevated in the HC group and reduced after salidroside or MSC treatment. Since CAT is an important antioxidant enzyme, increased CAT activity under hypobaric hypoxia may reflect an adaptive response to elevated oxidative stress [46]. The subsequent reduction in CAT activity following treatment may therefore be associated with a decreased demand for compensatory antioxidant responses, which is consistent with the concurrent restoration of GSH levels and the overall improvement in oxidative stress status observed in the treated groups. The restoration of cis-aconitate, a key intermediate of the tricarboxylic acid cycle, was particularly significant. This finding may reflect improved mitochondrial function and may also be related to the gut microbiota. Previous studies have reported that cis-aconitate can influence the activity of certain commensal organisms, including the immunomodulatory bacterium Flavonifractor plautii [47], suggesting a potential link among microbial activity, host metabolism, and immune regulation. Consistent with this, network analysis showed strong correlations among pulmonary inflammatory markers, microbial taxa such as Turicibacter, and metabolites including L-2-HG. These findings suggest that salidroside and MSCs could modulate gut microbial composition, which in turn affects host energy and redox pathways. Collectively, these observations indicate that alterations in microbial composition, metabolite profiles, and lung injury indicators occur concurrently following salidroside or MSC treatment.

In the 14-day hypobaric hypoxia model, it was observed that combining salidroside with MSCs did not yield the expected synergistic protective effects. Previous studies have demonstrated that short-term hypoxic exposure enhances the therapeutic potential of MSCs, particularly by promoting exosome secretion [[48], [49], [50]]. In TCM, MSC is associated with the “Kidney Essence” theory. According to the principle that “the Kidney governs bones and generates marrow,” Chinese herbal medicines have been postulated to affect the multipotency of stem cells or promote their osteogenic differentiation [51]. The current results suggest that under the complex in vivo environment of prolonged hypobaric hypoxia and combined treatments, the interaction between salidroside and MSCs does not act as a simple additive mechanism. Importantly, the absence of an additional protective effect does not necessarily diminish the therapeutic value of either intervention alone. Rather, it suggests that combining salidroside and MSCs may not provide greater benefit than monotherapy under the conditions tested in the present study. These findings highlight the importance of optimizing treatment schedules when developing combination approaches for hypobaric hypoxia-induced lung injury.

A deeper understanding may be based on the complex dual regulatory role of salidroside on the biological activity of MSCs. In vitro studies provide direct evidence of this dual action: while salidroside synergizes with hypoxia to promote proliferation, migration, and osteogenic differentiation of adipose-derived stem cells, it simultaneously antagonizes hypoxia-induced adipogenic differentiation [52]. These results show that the effects of salidroside on stem cell function are highly context-dependent and affected by the surrounding microenvironment. Therefore, the absence of synergy in this study possibly reflects this complex pharmacological interaction rather than insufficient dosing. This understanding highlights and suggests new directions for refining combination strategies that combine herbal compounds with stem cell-based therapies. Although this study provides a valuable understanding of the gut-lung axis under hypobaric hypoxia, its findings are mainly based on associative data. Therefore, a crucial next step is to establish causal relationships between specific microbial taxa and lung protection, which can be approached through functional methods such as fecal microbiota transplantation or experiments with germ-free models. Moreover, the current cross-sectional design, which is limited to a single dose and time point, restricts our understanding of dynamic regulatory patterns. Longitudinal studies are needed to investigate dose-response relationships and identify the precise signaling mediators, especially short-chain fatty acids, that promote communication along the gut-lung axis. Findings from such mechanistic research will be crucial for optimizing salidroside-MSC combination therapies and advancing this gut-lung axis strategy toward clinical application.

Based on the present findings, we propose a working model in which hypobaric hypoxia disrupts gut microbial homeostasis and alters host metabolic profiles, accompanied by increased inflammation and oxidative stress. Salidroside and MSC treatment partially restore microbial composition and metabolic balance, which is associated with improved redox status and reduced pulmonary injury. Correlation analyses revealed close associations among microbial taxa, metabolites, and lung injury indicators, suggesting that gut microbiota-metabolite interactions may contribute to the observed protective effects. However, further functional studies are required to determine whether these associations directly contribute to protection against hypobaric hypoxia-induced lung injury through the gut-lung axis.

Funding

This study was supported by the Gansu Provincial Science and Technology Major Program-Independent Research Project in the Field of Social Development. Project title: The Research of Human Umbilical Cord Mesenchymal Stem Cells on the Prevention and Treatment of Plateau Injury in Western China. Project number 25ZDFA007.

CRediT authorship contribution statement

Dengqin Ma: Conceptualization, Data curation, Formal analysis, Writing – original draft. Bang Xin: Conceptualization. Meng Li: Data curation. Bingfang Xie: Investigation, Validation. Qun Li: Methodology, Writing – review & editing. Enpen Zhu: Data curation, Software. Jing Luo: Project administration, Supervision. Xiaoqin Ha: Funding acquisition, Supervision.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

We sincerely thank Nomi Metabolism for their invaluable technical support, which enabled the successful progression of our research. We also recognize the contributions of other individuals and institutions who assisted in this study.

Data availability

The data that has been used is confidential.

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