Investigation of the Mechanisms and Experimental Verification of Yulin Formula in the Treatment of Diminished Ovarian Reserve via Network Pharmacology

Abstract

Purpose: The aim of this study is to examine, using network pharmacology analysis and experimental validation, the pharmacological processes by which Yulin Formula (YLF) reduces cyclophosphamide-induced diminished ovarian reserve (DOR).

Methods: First, information about the active components, associated targets, and related genes of YLF and DOR was gathered from open-access databases. The primary targets and pathways of YLF to reduce DOR were predicted using studies of functional enrichment from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Protein-Protein Interaction (PPI) networks. Second, we built a cyclophosphamide-induced diminished ovarian reserve (DOR) rat model to verify the primary target proteins implicated in the predicted signaling pathway to explore the mechanism of improve ovarian function of YLF.

Results: 98 targets met the targets of the 82 active ingredients in YLF and DOR after searching the intersection of the active ingredient targets and DOR targets. Fourteen targets, including AKT and Caspase-3 among others, were hub targets, according to the PPI network study. The PI3K/AKT pathway was revealed to be enriched by numerous targets by the GO and KEGG enrichment studies, and it was used as a target for in vivo validation. Animal studies showed that YLF administration not only reduced the number of atretic follicles, the proportion of TUNEL-positive ovarian cells, the rate of apoptosis of granulosa cells (GCs) and the proportion of abnormal mitochondria in DOR rats, but also reversed the high expression of Caspase-3, Caspase-9, BAX, cytochrome C, PI3K and P-AKT, improving the ovarian reserve in cyclophosphamide (CTX)-induced DOR rats.

Conclusion: Our research results predicted the active ingredients and potential targets of YLF-interfering DOR by an integrated network pharmacology approach, and experimentally validated some key target proteins participated in the predicted signaling pathway. A more comprehensive understanding of the pharmacological mechanism of YLF for DOR treatment was obtained.

Keywords: PI3K/AKT; Yulin Formula; apoptosis; diminished ovarian reserve; network pharmacology; pharmacological mechanisms.

Figure 1

Comprehensive flow chart demonstrating the mechanism of YLF for DOR treatment, including potential target identification, protein–protein interaction (PPI) construction, enrichment analysis and experimental validation.

Figure 2

Study design of the project.

Figure 3

YLF increased ovarian size, ovarian weight, improved estrous cycle and follicle growth in DOR rats. (A,C) Ovarian anatomical maps and ovarian weight of the four groups. (B) Representative images of each stage of estrous cycle. Green triangle: leukocyte; red triangle: anucleated keratinized epithelia; blue triangle: nucleated epithelial cells. (D) Proportion of each stage of the estrous cycle. (E) Hematoxylin and eosin (H&E) staining of ovarian tissue in the group shown. (F) Number of primordial follicles. (G) Number of growing follicles. (H) Number of atretic follicles. (I) Number of corpus luteum. The data conformed to a normal distribution and were expressed as Mean ±SD, n = 10 animals per group for vaginal smear examination and weighing test, n = 6 animals per group for follicle counts at different growth stages. [^#p < 0.05, ^##p < 0.01, compared with control group; *p < 0.05, **p < 0.01, compared with DOR group].

Figure 4

Construction of the component-target-disease network. (A) Venn diagram summarizing the cross-targeting of YLF and DOR. (B) Ingredient-target-disease network. In this network, the peripheral ring represents the composition and the middle rectangle represents the target gene. (C) Cluster analysis of PPI network and disease targets.

Figure 5

Functional study using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. (A) Top 10 results of the GO enrichment study (BP represents biological progression of core targets. CC represents cellular components of core targets. MF represents molecular functions of core targets.) (B) KEGG analysis’s top 20 signaling pathways.

Figure 6

YLF reduces apoptosis in ovarian granulosa cells. (A) Representative images of mitochondria around each group of granulosa cells, M: mitochondria; white arrows: abnormal mitochondria; red arrows: vacuolated mitochondria. (B) Percentage of mitochondria with vague cristae and vacuolated mitochondria in all mitochondria. (C) Representative images of DAPI and TUNEL. Green staining indicates TUNEL-positive apoptotic cells (× 50, × 200 magnification). (D) Counting of TUNEL-positive cells and total granulosa cells in sinus follicles at random spots. The percentages of TUNEL-positive apoptotic cells in the 4 groups were compared. All data were conformed to a normal distribution and were expressed as Mean ±SD, n = 5 animals per group for electron microscopic observation, and n = 5 animals per group for TUNEL test. [^##p < 0.01, compared with control group; **p < 0.01, compared with DOR group].

Figure 7

YLF treatment down-regulates PI3K/AKT signaling and apoptosis-related protein expression in the ovary. (A–E) Caspase-3, Caspase-9, BAX and Cytochrome C protein expression levels were detected using Western blot and quantified; (F–H) AKT, PI3K and PTEN-related mRNA expression were detected using PCR; (I) Western blot was used to detect P-AKT and AKT protein expression and P-AKT/AKT were calculated. All data were conformed to a normal distribution and were expressed as Mean ±SD, n = 6 animals per group for protein expression analysis, and n = 6 animals per group for Real-time PCR test. [^#p < 0.05, ^##p < 0.01, compared to control group; *p < 0.05, **p < 0.01, compared to DOR group].