Integrated ultrasensitive metabolomics and single-cell transcriptomics identify crucial regulators of sheep oocyte maturation and early embryo development in vitro

Abstract

Introduction: Developmental competence of oocytes matured in vitro is limited due to a lack of complete understanding of metabolism and metabolic gene expression during oocyte maturation and embryo development. Conventional metabolic analysis requires a large number of samples and is not efficiently applicable in oocytes and early embryos, thereby posing challenges in identifying key metabolites and regulating their in vitro culture system.

Objectives: To enhance the developmental competence of sheep oocytes, this study aimed to identify and supplement essential metabolites that were deficient in the culture systems.

Methods: The metabolic characteristics of oocytes and embryos were determined using ultrasensitive metabolomics analysis on trace samples and single-cell RNA-seq. By conducting integrated analyses of metabolites in cells (oocytes and embryos) and their developmental microenvironment (follicular fluid, oviductal fluid, and in vitro culture systems), we identified key missing metabolites in the in vitro culture systems. In order to assess the impact of these key missing metabolites on oocyte development competence, we performed in vitro culture experiments. Furthermore, omics analyses were employed to elucidate the underlying mechanisms.

Results: Our findings demonstrated that betaine, carnitine and creatine were the key missing metabolites in vitro culture systems and supplementation of betaine and L-carnitine significantly improved the blastocyst formation rate (67.48% and 48.61%). Through in vitro culture experiments and omics analyses, we have discovered that L-carnitine had the potential to promote fatty acid oxidation, reduce lipid content and lipid peroxidation level, and regulate spindle morphological grade through fatty acid degradation pathway. Additionally, betaine may participate in methylation modification and osmotic pressure regulation, thereby potentially improving oocyte maturation and early embryo development in sheep.

Conclusion: Together, these analyses identified key metabolites that promote ovine oocyte maturation and early embryo development, while also providing a new viewpoint to improve clinical applications such as oocyte maturation or embryo culture.

Keywords: Betaine; Early embryo; L-carnitine; Metabolomics; Sheep oocyte; Transcriptomics.

Graphical abstract

Fig. 1

Metabolic profile analysis for oocyte maturation and early embryo development. (A) Schematic overview of the workflow for metabolome profiling in oocytes and early embryos (created by biorender.com). (B-D) Volcano plot shows the number of upregulated metabolites (orange dots) or downregulated metabolites (blue dots). The black dotted line indicates that the P value is equal to 0.05. (E-F) Upregulated metabolic KEGG pathways in oocytes or early embryos based on the upregulated metabolites. (G-H) Downregulated metabolic KEGG pathways in oocytes or early embryos based on the downregulated metabolites. IVM, in vitro maturation; IVF, in vitro fertilization; IVC, in vitro culture; OO, oocyte; EM, embryo.

Fig. 2

KEGG pathway analysis of common metabolic pathways between oocyte and embryo development. (A) Venn diagram analysis of metabolic KEGG pathways between oocytes and embryos. (B) List of commonly enriched metabolic KEGG pathways between oocytes and embryos. Based on the common enrichment of metabolic KEGG pathways, significantly downregulated metabolites in oocytes or embryos were identified.

Fig. 3

Joint analysis of metabolic profiles among follicular fluid, oviductal fluid, oocytes, CCs and embryos. (A) Schematic diagram of the in vitro and in vivo development of the oocyte microenvironment (created by biorender.com). (B) Venn diagram analysis of metabolites among oocytes, cumulus cells and follicular fluid. (C) Venn diagram analysis of metabolites between follicular fluid and IVM medium. (D) Venn diagram analysis of metabolites between FF-OO-CC and Follicular fluid-IVM media. FF-OO-CC represented the common metabolites from follicular fluid, oocytes and cumulus cells. (E) List of 27 common metabolites between FF and IVM media. (F) List of 16 metabolites lacking in IVM medium. (G) Schematic diagram of the embryo development microenvironment in vitro and in vivo (created by biorender.com). (H) Venn diagram analysis of metabolites between embryos and oviductal fluid. (I) Venn diagram analysis of metabolites between oviductal fluid and IVC medium. (J) Venn diagram analysis of metabolites between oviductal fluid-embryo and oviductal fluid-IVC media. (K) List of 12 common metabolites between follicular fluid (OF) and IVM medium. (L) List of 34 metabolites lacking in IVM medium.

Fig. 4

Key lacking metabolites in culture media. (A) Venn diagram analysis of lacking metabolites in IVM medium and IVC medium. There were 10 missing metabolites found. (B) List of commonly lacking metabolites in IVM and IVC media. (C) Venn diagram analysis of metabolites between the missing metabolites and downregulated metabolites. (D) List of key lacking metabolites in IVM and IVC media. L-IVM medium, lacking metabolites in IVM medium；L-IVC medium, lacking metabolites in IVC medium.

Fig. 5

Functional analysis of betaine and L-carnitine. (A) Developmental competence analysis of oocytes when betaine, L-carnitine or both were added to in vitro maturation and in vitro culture systems. ^{a, b, c} Values with different superscripts are significantly different (P<0.05). (B) Effect of a glycine transporter 1 inhibitor (GlyT1 inhibitor) and GlyT1 inhibitor combined with betaine on blastocyst formation. “F”, cultured in normal IVC medium; “F+G”, cultured in IVC medium supplemented with GlyT1 inhibitor. “F+G+B”, cultured in IVC medium supplemented with GlyT1 inhibitor and betaine. Red arrows represent blastocyst formation. (C) Evaluation of spindle morphology of MⅡ oocyte.The spindle and DNA were labeled with α-Tubulin antibody and DAPI, respectively. (D) Effect of L-carnitine transport and synthesis inhibitors on lipid content in matured sheep oocytes. The lipid content was determined by BODIPY 493/503 labeling. (E) Effect of L-carnitine transport and synthesis inhibitors on lipid peroxidation in matured sheep oocytes. Lipid peroxidation was evaluated by BODIPY 581/591 C11. Lipids were oxidized and exhibited a green color. The lipid was in a reductive state with a red color. (F) Blastocyst rate corresponding to Fig. 5B. (G) Oocyte maturation rate after different treatments. (H) Effect of L-carnitine transport and synthesis inhibitors on the average grade of spindles of matured oocyte. (I) and (J) Lipid content and lipid peroxidation levels corresponding to Fig. 5D and Fig. 5E, respectively. COCs, cumulus-oocyte complexes; PA, parthenogenetic activation; F, fresh, without any treatment; B, betaine treatment; LC, L-carnitine treatment; FBL, fresh group with betaine and L-carnitine treatment; G, GlyT1 inhibitor; M, Mildronate, inhibitor of BBOX1 and OCTN2; E, Etomoxir, inhibitor of CPT-1A.

Fig. 6

Metabolic characteristic analysis of oocytes and embryos based on transcriptomics and metabolomics. (A) Heatmap of KEGG pathway analysis related to metabolism regulation from oocyte maturation to embryonic development. C1-C5 represented 5 different gene clusters. (B-D) KEGG enrichment analysis by combining transcriptomics and metabolomics.

Fig. 7

Energy metabolism and cysteine-methionine metabolism analysis based on transcriptomics and metabolomics. (A) Visualization analysis of fatty acid degradation based on joint transcriptomic and metabolomic analysis (created by biorender.com). (B) Visualization analysis of cysteine and methionine metabolism from 8-cell embryo to the blastocyst stage (created by biorender.com). The encoding genes of metabolic enzymes increased and decreased are marked as red and blue, respectively. The red and blue triangles denote the upregulated and downregulated metabolites, respectively. (C-E) Metabolic gene expression and relative fold change of metabolites. * indicates that the two groups were significantly different (P<0.05). THF, tetrahydrofolic acid; SAM, s-adenosylmethionine; SAH, S-adenosylhomocysteine; γ-GLC, γ-glutamylcysteine; O-GSH, Oxidated-GSH.