1. YS improves pulmonary function in COPD rats
Pulmonary function is an important index in evaluating COPD, including TV, MV and EF50, reflecting small airway obstruction. Studies[12] found that COPD patients showed decreased TV and MV. We found that EF50, TV and MV were significantly lower in COPD rats (P < 0.05), while EF50 (P < 0.05), TV and MV (P > 0.05) were higher after YS intervention (Fig. 1C-1E). COPD rats displayed hair withering, slow action, and shortness of breath. There were significant improvements in animal behaviors after the YS intervention. The body weights of COPD rats significantly decreased (P < 0.05). Weights in the YS+COPD group increased (P > 0.05) (Fig. 1B). These findings suggest that YS improves animal behaviors and pulmonary ventilatory function in COPD rats.
2. YS improved immune function in COPD rats
The spleen and thymus are critical immune organs, and their organ indexes reflect the strength of immune function to a certain extent [13]. Results show that thymus index and spleen index were decreased significantly in COPD rats (P > 0.05); after YS intervention, thymus index and spleen index were increased (P > 0.05) (Fig. 2A-2B). SIgA is a major effector molecule of the mucosal immune defense system against the colonization and adhesion of pathogenic microorganisms on mucosal surfaces[14]. The amount of SIgA in the sputum and alveolar lavage fluid of patients with COPD was significantly lower than in the control group. In the present study, we have found that SIgA was decreased in COPD rats (P > 0.05), while the SIgA of the COPD+YS group was significantly increased (P > 0.05) (Fig. 2C). All these suggested that YS could enhance the local mucosal immunity and improve immune function in COPD rats.
3.YS relieves inflammation in COPD rats
The inflammatory response of COPD primarily involves neutrophil infiltration. TNF-ɑ activates neutrophils, and IL-6 inhibits apoptosis [15]. HE staining showed that substantial amounts of neutrophil infiltration plugged the bronchi. The lumens were significantly narrowed, the alveolar walls become thinner and fused in COPD rats. There were fewer of these pathological changes in the YS intervention group (Fig. 3A). Levels of TNF-ɑ and IL-6 were significantly higher in the serum of COPD rats (P > 0.05) with YS intervention (Fig. 3C-3D). TGF-β1 is a powerful profibrotic cytokine that participates in inflammatory repair [16]. Masson staining showed that much collagen fiber deposition occurred around the trachea and pulmonary interstitium in COPD rats. Collagen deposition was less severe in YS rats (Fig. 3B). TGF-β1 protein expression was significantly elevated in lung tissue of COPD rats (P > 0.05). TGF-β1 levels in the COPD+YS group were significantly lower (P > 0.05) (Fig. 3F). These findings suggest that YS ameliorates lung tissue damage, attenuates inflammatory responses, and reduces collagen deposition in COPD rats.
4.YS reduces NLRP3/caspase-1/IL-1β signaling expression in COPD rats
NLRP3 promotes the release of downstream inflammatory cytokines, inducing acute and chronic inflammatory responses. When NLRP3 is overactivated, ASC acts as an adaptor protein to recruit the precursor caspase-1, promoting IL-1β and IL-18 secreted outside the cell, exerting proinflammatory effects[17]. Compared with Control, NLRP3 protein expression was significantly greater in lung tissues of COPD rats (P > 0.05). Caspase-1 and ASC were significantly increased in lung tissues (P > 0.05), and IL-1β and IL-18 levels were significantly higher in serum (P > 0.05). In the YS group, NLRP3 protein expression was significantly lower in lung tissue (P > 0.05), caspase-1 and ASC levels were significantly lower in lung tissue (P > 0.05), and serum IL-18 levels were significantly lower (P > 0.05). These findings suggest that YS inhibits the NLRP3/caspase-1/IL-1β signaling pathway (Fig. 4A-4E), alleviating the inflammatory response.
5. Effect of YS on lung microbiota in COPD rats
The lung microbiota is strongly associated with COPD. To explore the mechanisms, 16s rRNA high-throughput sequencing was employed to analyze the lung microbiota. The chao1 index reflects the relative abundance of flora, and the Shannon index reflects the diversity of flora. The results are represented in Figure 5A. Compared with the CT group, the relative abundance of flora in the COPD group decreased. After YS intervention, the relative abundance of the flora showed no significant change. Compared with the CT group, the diversity of the flora in the COPD group was significantly decreased (P > 0.05). The diversity of the flora was significantly greater after YS intervention (P > 0.05).
On the phylum level, the lung flora of rats in each group was dominated by Proteobacteria, Firmicutes, and Bacteroidota. Compared with the CT group, the COPD group showed an increased relative abundance of Proteobacteria and Firmicutes, with a decreased relative abundance of Bacteroidota; after YS intervention, the relative abundance of Bacteroidota increased those of Proteobacteria and Firmicutes decreased (Fig. 5B). At the genus level, the lung flora of rats in each group was dominated by Ralstonia, Mycoplasma, Halomonas, Lactobacillus, Dizetzia, and Bacteroides. Compared with the CT group, the COPD group showed an increased relative abundance of Ralstonia, Mycoplasma, Halomonas, and Dizetzia, while there was a decreased relative abundance of Lactobacillus and Bacteroides. The relative abundance of Halomonas, Lactobacillus, Dizetzia, and Bacteroides were increased, and there was a lower relative abundance of Ralstonia and Mycoplasma after YS intervention (Fig. 5C).
Linear discriminant analysis of effect size shows the iconic microorganisms in each group that contributed significantly to differences in microbial structure. As shown in Figure 5D, Mycoplasma was more abundant in the gut microbiota of the COPD group. Mycoplasma was significantly increased in COPD patients, while Halomonas, Dietzia, and Nesterenkonia were enriched after YS intervention. These results suggest that YS changes the relative abundance of specific bacteria and modulates the bacterial flora in COPD rats.
6. Environmental factor correlation analysis
Correlation heatmap plots were used to assess the top 20 species at the genus level and correlations with EF50, MV, TV, SIgA, TNF-α, IL-6, TGF-β1, NLRP3, caspase1, ASC, IL-1β, and IL-18.
As shown in the Figure 6, Mycoplasma positively correlated with IL-1β (P < 0.05) and TNF-α (P < 0.05), and negatively correlated with MV (P < 0.001), TV (P < 0.001) and EF50 (P < 0.001). Bacteroides positively correlated with EF50 (P < 0.001) and negatively correlated with TNF-α (P < 0.001), IL-6 (P < 0.001), TGF-β1 (P < 0.05), caspase1 (P < 0.001), ASC (P < 0.05) and IL-18 (P < 0.001). Halomonas positively correlated with SigA (P < 0.001), and negatively correlated with IL-6 (P < 0.05) and TGF-β1 (P < 0.001). Nesterenkonia positively correlated with IL-6 (P < 0.001), caspase 1 (P < 0.001), and ASC (P < 0.001) and negatively correlated with TV (P < 0.05). Parabacteroidesnegatively correlated with IL-6 (P < 0.001), caspase1 (P < 0.001), and ASC (P < 0.001). In summary, we presumed that inflammatory and immune indicators were the most closely related to this study.