Metabolomic and microbiome analysis of cervicovaginal mucus in in vitro fertilization-embryo transfer: Toward predicting pregnancy success

Abstract

Purpose: In the context of in vitro fertilization-embryo transfer (IVF-ET), factors other than egg quality may be key determinants of treatment success, in particular, maternal factors related to uterine endometrial receptivity and unidentified factors. We therefore aimed to analyze the metabolome and microbiome in IVF-ET patients who did and did not achieve pregnancy.

Methods: Cervicovaginal mucus was collected from patients undergoing IVF-ET. Metabolite analysis was conducted by liquid chromatography-mass spectrometry and the microbiota were determined by the polymerase chain reaction using universal 16S-rRNA gene bacterial primers by MiSeq sequencing. Patients were classified as pregnant (N = 10) or nonpregnant (N = 13). Metabolic pathways were examined by MetaboAnalyst.

Results: Three metabolic pathways, including alanine-aspartate-glutamate metabolism, arginine biosynthesis, and cysteine-methionine metabolism, were commonly decreased at the time of embryo transfer irrespective pregnant outcomes. Notably, pyruvate was decreased in the pregnant group. Amino acid metabolites showed inverse correlations with the presence of anaerobic microbiota in the nonpregnant group.

Conclusions: Metabolism decreased during embryo transplantation, with a notable decrease in pyruvate metabolism, particularly in patients who became pregnant. The behavior of metabolites in the pregnant and nonpregnant groups suggests that metabolome analysis in the cervicovaginal mucus may be a diagnostic marker for predicting pregnancy.

Keywords: in vitro fertilization–embryo transfer; metabolome; microbiome; mucus; pyruvate.

FIGURE 1

Details of sample collections. (A) Cervicovaginal mucus samples were collected twice from the same patient, at the time of oocyte retrieval and at the time of embryo transfer, from pregnant (N = 10) and nonpregnant (N = 13) patients. *Metabolome analysis was carried out in 12 patients in the nonpregnant group because of improper sampling in one patient. (B) Information on age at time of sample collection and number of days between oocyte retrieval and transplantation.

FIGURE 2

Volcano plot showing differential metabolites in patients undergoing IVF. (A) At oocyte retrieval in nonpregnant group versus pregnant group; (B) at embryo transfer in nonpregnant group vs. pregnant group; (C) at embryo transfer vs. oocyte retrieval in pregnant group; (D) at embryo transfer vs. oocyte retrieval in nonpregnant group. Up or down in the pregnant group relative to the nonpregnant group (A, B) and at the time of embryo transfer relative to the time of oocyte retrieval (C, D). Results were plotted with a p‐value < 0.05 and a fold change > 2. Significantly increased metabolites are shown in red and significantly decreased metabolites are shown in blue. FC, fold change.

FIGURE 3

Pathway analysis by MetaboAnalyst. (A) Plots depicting several metabolic pathways that were reduced at the time of embryo transfer relative to the time of oocyte retrieval. Pathways represented as circles according to their pathway impact values from pathway topology analysis (x‐axis) and log p‐value obtained from pathway enrichment analysis (y‐axis). Each dot represents a metabolic pathway, and label corresponds to pathway number in (B). (B) Overlapping results with MetaboAnalyst analysis in (A) identified five pathways (bold) that were more strongly reduced in the pregnant group (false discovery rate p < 0.05, pathway impact >0.40). These included three pathways with large differences (highlighted orange) in impact values (C–E). Metabolites that were commonly decreased in the pregnant and nonpregnant groups at the time of embryo transfer are shown in blue, metabolites that were significantly lower in the pregnant group only are shown in red, and metabolites that were significantly lower in the nonpregnant group only are shown in green. (C) Alanine, aspartate, and glutamate metabolism; (D) arginine biosynthesis; (E) cysteine and methionine metabolism. S‐Adenosylhomocysteine was decreased in the nonpregnant group.

FIGURE 4

Heatmap of relative abundance of representative microbiota. Cervicovaginal microbiota were collected from 23 patients undergoing oocyte retrieval and embryo transfer. A total of 46 samples were identified by 16S rRNA V3/4 sequencing. Color gradient indicates relative abundance of microbial groups (scale indicated at bottom). Number of microbial species qualified by observed species richness indicated as α‐diversity in each sample.

FIGURE 5

Spearman's correlation coefficients between Lactobacillus species or other microbes and metabolites at the time of oocyte retrieval. Heatmap showing Spearman's correlation coefficients between (A) Lactobacillus species and metabolites other than amino acids and nucleic acids, and (B) Lactobacillus species or other microbes and amino acids and nucleic acids. Microbiota present in three or more patients were selected. Color corresponds to Spearman's correlation coefficient distribution: dark yellow indicates strong positive correlation (correlation coefficient 0.6–1.0); pale yellow indicates weak positive correlation (correlation coefficient 0.2–0.6); pale blue indicates weak negative correlation (correlation coefficient −0.2 to −0.6); and dark blue indicates strong negative correlation (correlation coefficient −0.6 to −1.0). *p < 0.05.