Multi-omics reveals Dengzhan Shengmai formulation ameliorates cognitive impairments in D-galactose-induced aging mouse model by regulating CXCL12/CXCR4 and gut microbiota

Abstract

Dengzhan Shengmai (DZSM), a traditional Chinese medicine formulation, has been administered extensively to elderly individuals with cognitive impairment (CI). However, the underlying mechanisms by which Dengzhan Shengmai improves cognitive impairment remains unknown. This study aimed to elucidate the underlying mechanism of the effect of Dengzhan Shengmai on aging-associated cognitive impairment via a comprehensive combination of transcriptomics and microbiota assessment. Dengzhan Shengmai was orally administered to a D-galactose-induced aging mouse model, and evaluation with an open field task (OFT), Morris water maze (MWM), and histopathological staining was performed. Transcriptomics and 16S rDNA sequencing were applied to elucidate the mechanism of Dengzhan Shengmai in alleviating cognitive deficits, and enzyme-linked immunosorbent assay (ELISA), quantitative real-time polymerase chain reaction (PCR), and immunofluorescence were employed to verify the results. The results first confirmed the therapeutic effects of Dengzhan Shengmai against cognitive defects; specifically, Dengzhan Shengmai improved learning and impairment, suppressed neuro loss, and increased Nissl body morphology repair. Comprehensive integrated transcriptomics and microbiota analysis indicated that chemokine CXC motif receptor 4 (CXCR4) and its ligand CXC chemokine ligand 12 (CXCL12) were targets for improving cognitive impairments with Dengzhan Shengmai and also indirectly suppressed the intestinal flora composition. Furthermore, in vivo results confirmed that Dengzhan Shengmai suppressed the expression of CXC motif receptor 4, CXC chemokine ligand 12, and inflammatory cytokines. This suggested that Dengzhan Shengmai inhibited CXC chemokine ligand 12/CXC motif receptor 4 expression and modulated intestinal microbiome composition by influencing inflammatory factors. Thus, Dengzhan Shengmai improves aging-related cognitive impairment effects via decreased CXC chemokine ligand 12/CXC motif receptor 4 and inflammatory factor modulation to improve gut microbiota composition.

Keywords: CXCL12; CXCR4; Dengzhan Shengmai (DZSM); aging; cognitive impairment (CI).

FIGURE 1

Experimental design and behavioral analysis. (A) Experimental design for medication treatment in C57BL/6 mice and behavioral analysis; (B) Open field task: a. total movement distance, b. activity time; (C) Morris water maze: a. latency to platform in the 5-day training phase, b. movement tracking in the positioning navigation phase, c. movement distance in target quadrant, d. number of platform crossings. (Compared with the Nor group: ^# p < 0.05, ^## p < 0.01; compared with the Aging group: ^* p < 0.05, ^** p < 0.01, n = 8).

FIGURE 2

Histopathological changes in the brain tissue. (A) H&E staining; (B) Nissl staining (n = 3). Bar length: 1 mm, 100 μm.

FIGURE 3

Transcriptomics analysis. (A) Volcano map of the DEGs in the Aging vs. Normal (Nor) groups and the DZSM vs. Aging groups; (B) Heatmap of the DEGs in the Nor, Aging, and DZSM groups; (C) Venn diagram of the DEGs in the Nor, Aging, and DZSM groups; (D) GO enrichment analysis of DEGs (red terms represent MF, green terms represent CC, and blue terms represent BP). (E) KEGG pathway analysis of DEGs.

FIGURE 4

Network analysis of reverse DEGs. (A) The network of DEGs in the Aging and DZSM groups. Upregulated/downregulated DEGs are indicated by the blue/pink nodes whose size reflects the degree. (B) GO terms for the network of reverse DEGs. (C) The expression levels of CXCR4 in RNA-seq (compared with the Nor group: ^# p < 0.05, ^## p < 0.01; compared with the Aging group: ^* p < 0.05, ^** p < 0.01).

FIGURE 5

DZSM downregulated CXCR4 and CXCR12 expression and inhibited inflammatory cytokine production. (A) RT-PCR, ELISA, and IF analysis of CXCR4 (Bar length: 50 μm); (B) RT-PCR, ELISA, and IF analysis of CXCL12 (Bar length: 50 μm); (C) Analysis of IL-1β, IL-6, TNF-α, and IL-18 levels by ELISA. (D) RT-PCR analysis of IL-1β, IL-6, TNF-α, and IL-18 (compared with the Nor group: ^# p < 0.05, ^## p < 0.01; compared with the Aging group: ^* p < 0.05, ^** p < 0.01).

FIGURE 6

The intestinal microbiome determined by 16S rDNA. (A) Rarefaction curve of the chao1 index; (B) Unweighted UniFrac PCoA in which each dot represents the gut microbiota of a mouse; (C) Unweighted pair group method with arithmetic mean (UPGMA) sample clustering tree; (D) Venn diagram of three groups indicates shared and special OTUs of Nor, Aging, and DZSM groups; (E,F) Intestinal microbial taxonomic composition of DZSM at the class and phylum levels.

FIGURE 7

Different species abundance on linear discriminant analysis (LDA) effect size (LefSe). (A) Cladogram of Aging vs. Nor groups; (B) LDA scores of Aging vs. Nor groups; (C) Cladogram of DZSM vs. Aging groups; (D) LDA scores of DZSM vs. Aging groups.

FIGURE 8

Relationship between the relative abundance of gut microbiota and key targets and pro-inflammatory cytokines. (A) Redundancy analysis (RDA) between microbes of the genus and key targets and pro-inflammatory cytokines; (B) Correlations between the microbes of the main genus and the key targets and pro-inflammatory cytokines; (C) Redundancy analysis (RDA) between the microbes of the family and key targets and pro-inflammatory cytokines; (D) Correlations between the microbes of the main family and the key targets and pro-inflammatory cytokines.

FIGURE 9

Overview of the cognitive impairment-ameliorating mechanism of DZSM via CXCL12/CXCR4 regulation and microbial improvement.