Peptidomic analysis of follicular fluid in patients with polycystic ovarian syndrome

Abstract

Objective: The aim of this study was to analyze and compare the differential expression of peptides within the follicular fluid of polycystic ovary syndrome (PCOS) patients versus normal women by using peptidomics techniques. The underlying mechanisms involved in PCOS pathogenesis will be explored, together with screening and identification of potential functional peptides via bioinformatics analysis. Materials and methods: A total of 12 patients who underwent in vitro fertilization and embryo transfer (IVF-ET) at the Reproductive Medicine Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from 1 September 2022 to 1 November 2022 were included in this study. The follicular fluid of PCOS patients (n = 6) and normal women (n = 6) were collected. The presence and concentration differences of various peptides were detected by the LC-MS/MS method. GO and KEGG analysis were performed on the precursor proteins of the differentially-expressed peptides, and protein network interaction analysis was carried out to identify functionally-relevant peptides among the various peptides. Results: A variety of peptides within the follicular fluid of PCOS versus normal patients were detected by peptidomics techniques. Altogether, 843 upregulated peptides and 236 downregulated peptides were detected (absolute fold change ≥2 and p < 0.05). Of these, 718 (718 = 488 + 230) peptides were only detected in the PCOS group, while 205 (205 = 174 + 31) were only detected in the control group. Gene Ontology enrichment and pathway analysis were performed to characterize peptides through their precursor proteins. We identified 18 peptides from 7 precursor proteins associated with PCOS, and 4 peptide sequences were located in the functional domains of their corresponding precursor proteins. Conclusion: In this study, differences in the follicular development of PCOS versus normal patients were revealed from the polypeptidomics of follicular development, which thus provided new insights for future studies on the pathological mechanisms of PCOS development.

Keywords: assisted reproduction; follicular fluid; in vitro fertilization; peptidomics analysis; polycystic ovarian syndrome.

FIGURE 1

Differentially-expressed peptides within the follicular fluid of PCOS versus normal patients. The quality scores of 3 k peptide (A) and 10 k peptide (B) segments were correlated with the quantity distribution of corresponding spectra. The more blue bars with more than 20 scores, the higher the proportion of the results of high-quality spectra. (C) Volcano plot of differentially-expressed 3 k peptides detected in the follicular fluid of women with PCOS (n = 6) versus normal women without PCOS (n = 6). (D) Volcano plot of differentially-expressed 10 k peptides detected in the follicular fluid of women with PCOS (n = 6) versus normal women without PCOS (n = 6). The volcano plot is a scatter plot with the log2 value of Fold Change as the horizontal axis and the -log10 change value of p-value as the vertical axis. Based on the threshold of significant change as the dividing line, the data are mainly divided into three categories: red dot is upregulated, blue dot is downregulated, and gray dot with no change (refer to the legend). The distribution of different peptides within each group can be seen (this analysis is based on quantified total peptides).

FIGURE 2

GO analysis of precursor proteins from peptides within the follicular fluid. (A) The top 20 categories of 3 k peptides with the smallest p-values in the GO classification chart. (B) The top 20 categories of 10 k peptides with the smallest p-values in the GO classification chart. The ordinate represents the number of proteins in each classification and its percentage of the total amount of differentially-expressed proteins, with the different colors representing different first-level classification, Biological Process (pink), Molecular Function (blue) and Cellular Component (green).

FIGURE 3

KOG function classification of the identified precursor proteins. (A) The function classification of the precursor proteins of 3 k peptides. (B) The function classification of the precursor proteins of 10 k peptides. Different colors in the bar charts indicate different KOG categories, and the Y-axis indicates the number of proteins belonging to each particular category. (C) Different KOG functional categories of upregulated/downregulated precursor proteins of 3 k peptides. (D) Different KOG functional categories of upregulated/downregulated precursor proteins of 10 k peptides. Upregulated proteins are depicted in red, downregulated proteins are depicted in black. The X-axis depicts various KOG categories, while the Y-axis represents the number of proteins that fall into these categories.

FIGURE 4

STRING network diagram. (A) PPI network diagram of 3 k peptides corresponding to precursor proteins. (B) PPI network diagram of 10 k peptides corresponding to precursor proteins.

FIGURE 5

Identification of hub genes for PCOS. (A) The top 30 DEGs of 3 k peptides. (B) The top 30 DEGs of 10 k peptides. The top 30 DEGs in the interrelationship network analysed by degree in cytoHubba, the higher the rank, the redder the color. (C) The significant module identified from the PPI network using the molecular complex detection method (MCODE) with a score of >4.0 and nodes >5, MCODE score = 26.87.