From follicle to blastocyst: microRNA-34c from follicular fluid-derived extracellular vesicles modulates blastocyst quality.

Developmental competence Extracellular vesicles Maturation MicroRNA Oocyte miR-34c

Journal

Journal of animal science and biotechnology
ISSN: 1674-9782
Titre abrégé: J Anim Sci Biotechnol
Pays: England
ID NLM: 101581293

Informations de publication

Date de publication:
04 Aug 2024
Historique:
received: 15 03 2024
accepted: 04 06 2024
medline: 4 8 2024
pubmed: 4 8 2024
entrez: 3 8 2024
Statut: epublish

Résumé

Within the follicular fluid, extracellular vesicles (EVs) guide oocyte growth through their cargo microRNAs (miRNAs). Here, we investigated the role of EVs and their cargo miRNAs by linking the miRNAs found in EVs, derived from the fluid of an individual follicle, to the ability of its oocyte to become a blastocyst (competent) or not (non-competent). Bovine antral follicles were dissected, categorized as small (2-4 mm) or large (5-8 mm) and the corresponding oocytes were subjected to individual maturation, fertilization and embryo culture to the blastocyst stage. Follicular fluid was pooled in 4 groups (4 replicates) based on follicle size and competence of the corresponding oocyte to produce a blastocyst. Follicular fluid-derived EVs were isolated, characterized, and subjected to miRNA-sequencing (Illumina Miseq) to assess differential expression (DE) in the 4 groups. Functional validation of the effect of miR-34c on embryo development was performed by supplementation of mimics and inhibitors during in vitro maturation (IVM). We identified 16 DE miRNAs linked to oocyte competence when follicular size was not considered. Within the large and small follicles, 46 DE miRNAs were driving blastocyst formation in each group. Comparison of EVs from competent small and large follicles revealed 90 DE miRNAs. Cell regulation, cell differentiation, cell cycle, and metabolic process regulation were the most enriched pathways targeted by the DE miRNAs from competent oocytes. We identified bta-miR-34c as the most abundant in follicular fluid containing competent oocytes. Supplementation of miR-34c mimic and inhibitor during IVM did not affect embryo development. However, blastocyst quality, as evidenced by higher cell numbers, was significantly improved following oocyte IVM in the presence of miR-34c mimics, while miR-34c inhibitors resulted in the opposite effect. This study demonstrates the regulatory effect of miRNAs from follicular fluid-derived EVs on oocyte competence acquisition, providing a further basis for understanding the significance of miRNAs in oocyte maturation and embryonic development. Up-regulation of miR-34c in EVs from follicular fluid containing competent oocytes and the positive impact of miR-34c mimics added during IVM on the resulting blastocysts indicate its pivotal role in oocyte competence.

Sections du résumé

BACKGROUND BACKGROUND
Within the follicular fluid, extracellular vesicles (EVs) guide oocyte growth through their cargo microRNAs (miRNAs). Here, we investigated the role of EVs and their cargo miRNAs by linking the miRNAs found in EVs, derived from the fluid of an individual follicle, to the ability of its oocyte to become a blastocyst (competent) or not (non-competent).
METHODS METHODS
Bovine antral follicles were dissected, categorized as small (2-4 mm) or large (5-8 mm) and the corresponding oocytes were subjected to individual maturation, fertilization and embryo culture to the blastocyst stage. Follicular fluid was pooled in 4 groups (4 replicates) based on follicle size and competence of the corresponding oocyte to produce a blastocyst. Follicular fluid-derived EVs were isolated, characterized, and subjected to miRNA-sequencing (Illumina Miseq) to assess differential expression (DE) in the 4 groups. Functional validation of the effect of miR-34c on embryo development was performed by supplementation of mimics and inhibitors during in vitro maturation (IVM).
RESULTS RESULTS
We identified 16 DE miRNAs linked to oocyte competence when follicular size was not considered. Within the large and small follicles, 46 DE miRNAs were driving blastocyst formation in each group. Comparison of EVs from competent small and large follicles revealed 90 DE miRNAs. Cell regulation, cell differentiation, cell cycle, and metabolic process regulation were the most enriched pathways targeted by the DE miRNAs from competent oocytes. We identified bta-miR-34c as the most abundant in follicular fluid containing competent oocytes. Supplementation of miR-34c mimic and inhibitor during IVM did not affect embryo development. However, blastocyst quality, as evidenced by higher cell numbers, was significantly improved following oocyte IVM in the presence of miR-34c mimics, while miR-34c inhibitors resulted in the opposite effect.
CONCLUSION CONCLUSIONS
This study demonstrates the regulatory effect of miRNAs from follicular fluid-derived EVs on oocyte competence acquisition, providing a further basis for understanding the significance of miRNAs in oocyte maturation and embryonic development. Up-regulation of miR-34c in EVs from follicular fluid containing competent oocytes and the positive impact of miR-34c mimics added during IVM on the resulting blastocysts indicate its pivotal role in oocyte competence.

Identifiants

pubmed: 39097731
doi: 10.1186/s40104-024-01059-8
pii: 10.1186/s40104-024-01059-8
doi:

Types de publication

Journal Article

Langues

eng

Pagination

104

Informations de copyright

© 2024. The Author(s).

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Auteurs

Camilla Benedetti (C)

Department of Internal Medicine, Reproduction and Population Medicine, Faculty of Veterinary Medicine, Ghent University, 9820, Merelbeke, Belgium.

Krishna Chaitanya Pavani (KC)

Department of Internal Medicine, Reproduction and Population Medicine, Faculty of Veterinary Medicine, Ghent University, 9820, Merelbeke, Belgium.
Department for Reproductive Medicine, Ghent University Hospital, 9000, Ghent, Belgium.

Yannick Gansemans (Y)

Laboratory of Pharmaceutical Biotechnology, Faculty of Pharmaceutical Sciences, Ghent University, B-9000, Ghent, Belgium.

Nima Azari-Dolatabad (N)

Department of Animal Science, University of Tennessee, Knoxville, TN, USA.

Osvaldo Bogado Pascottini (OB)

Department of Internal Medicine, Reproduction and Population Medicine, Faculty of Veterinary Medicine, Ghent University, 9820, Merelbeke, Belgium.

Luc Peelman (L)

Department of Nutrition, Genetics and Ethology, Faculty of Veterinary Medicine, Ghent University, B-9000, Ghent, Belgium.

Rani Six (R)

Department of Nutrition, Genetics and Ethology, Faculty of Veterinary Medicine, Ghent University, B-9000, Ghent, Belgium.

Yuan Fan (Y)

Department of Nutrition, Genetics and Ethology, Faculty of Veterinary Medicine, Ghent University, B-9000, Ghent, Belgium.

Xuefeng Guan (X)

Department of Nutrition, Genetics and Ethology, Faculty of Veterinary Medicine, Ghent University, B-9000, Ghent, Belgium.

Koen Deserranno (K)

Laboratory of Pharmaceutical Biotechnology, Faculty of Pharmaceutical Sciences, Ghent University, B-9000, Ghent, Belgium.

Andrea Fernández-Montoro (A)

Department of Internal Medicine, Reproduction and Population Medicine, Faculty of Veterinary Medicine, Ghent University, 9820, Merelbeke, Belgium.

Joachim Hamacher (J)

Institute of Crop Science and Resource Conservation, Plant Pathology, Rheinische Friedrich-Wilhelms-University of Bonn, 53115, Bonn, Germany.

Filip Van Nieuwerburgh (F)

Laboratory of Pharmaceutical Biotechnology, Faculty of Pharmaceutical Sciences, Ghent University, B-9000, Ghent, Belgium.

Trudee Fair (T)

School of Agriculture and Food Science, University College Dublin, Belfield, Dublin, Ireland.

An Hendrix (A)

Laboratory of Experimental Cancer Research, Department of Human Structure and Repair, Ghent University, B-9000, Ghent, Belgium.

Katrien Smits (K)

Department of Internal Medicine, Reproduction and Population Medicine, Faculty of Veterinary Medicine, Ghent University, 9820, Merelbeke, Belgium. Katrien.Smits@UGent.be.

Ann Van Soom (A)

Department of Internal Medicine, Reproduction and Population Medicine, Faculty of Veterinary Medicine, Ghent University, 9820, Merelbeke, Belgium. Ann.VanSoom@UGent.be.

Classifications MeSH