A Neural Network-Based Identification of Developmentally Competent or Incompetent Mouse Fully-Grown Oocytes
Summary
Here, we present a protocol for non-invasive assessment of oocyte developmental competence performed during their in vitro maturation from the germinal vesicle to the metaphase II stage. This method combines time-lapse imaging with particle image velocimetry (PIV) and neural network analyses.
Abstract
Infertility clinics would benefit from the ability to select developmentally competent vs. incompetent oocytes using non-invasive procedures, thus improving the overall pregnancy outcome. We recently developed a classification method based on microscopic live observations of mouse oocytes during their in vitro maturation from the germinal vesicle (GV) to the metaphase II stage, followed by the analysis of the cytoplasmic movements occurring during this time-lapse period. Here, we present detailed protocols of this procedure. Oocytes are isolated from fully-grown antral follicles and cultured for 15 h inside a microscope equipped for time-lapse analysis at 37 °C and 5% CO2. Pictures are taken at 8 min intervals. The images are analyzed using the Particle Image Velocimetry (PIV) method that calculates, for each oocyte, the profile of Cytoplasmic Movement Velocities (CMVs) occurring throughout the culture period. Finally, the CMVs of each single oocyte are fed through a mathematical classification tool (Feed-forward Artificial Neural Network, FANN), which predicts the probability of a gamete to be developmentally competent or incompetent with an accuracy of 91.03%. This protocol, set up for the mouse, could now be tested on oocytes of other species, including humans.
Introduction
Female infertility is a pathology that affects an increasing number of women. According to the World Health Organization, around 20% of couples are infertile, with a 40% due to female infertility. In addition, one third of women undergoing cancer treatments (300,000/year and 30,000/year in the USA or Italy, respectively) develop premature ovarian failure.
A strategy to prevent infertility in cancer patients is the isolation and cryopreservation of ovarian follicles before the oncological treatment, followed by in vitro maturation (IVM) of GV oocytes to the MII stage (GV-to-MII transition). The availability of non-invasive markers of oocyte developmental competence would improve the fertilization and developmental processes and the overall pregnancy success1,2.
Based on their chromatin configuration observed after staining with the supravital fluorochrome Hoechst 33342, mammalian fully-grown oocytes are classified either as a Surrounded Nucleolus (SN) or a Not Surrounded Nucleolus (NSN)3. Besides their different chromatin organization, these two types of oocytes display many morphological and functional differences3,4,5,6,7,8,9, including their meiotic and developmental competence. When isolated from the ovary and matured in vitro, both type of oocytes reach the MII stage, and after sperm insemination, develop to the 2-cell stage, but only those with an SN chromatin organization may develop to term9. Although good as a classification method for selecting competent vs. incompetent oocytes, the main drawback is the mutagenic effect that the fluorochrome itself and, above all, the UV light used for its detection might have on the cells.
For all these reasons, we searched for other non-invasive markers associated with the SN or NSN chromatin conformation that could substitute the use of Hoechst while maintaining the same high classification accuracy. The time-lapse observation of Cytoplasmic Movement Velocities (CMVs) is emerging as a feature distinctive of the cell status. For example, recent studies demonstrated the association between CMVs recorded at the time of fertilization and the capacity of mouse and human zygotes to complete preimplantation and full-term development10,11.
Based on these earlier studies, we describe here a platform for the recognition of developmentally competent or incompetent mouse fully-grown oocytes5,6,7,8. The platform is based on three main steps: 1) Oocytes isolated from antral follicles are first classified based on their chromatin configuration either as a surrounded nucleolus (SN) or a not-surrounded nucleolus (NSN); 2) Time-Lapse images of CMVs occurring during the GV-to-MII transition of each single oocyte are taken and analyzed with particle image velocimetry (PIV); and 3) the data obtained with PIV are analyzed with a Feed-forward Artificial Neural Network (FANN) for blind classification12,13. We give details of the most critical steps of the procedure designed for the mouse to make it ready available to be tested and used for other mammalian species (e.g., bovine, monkey and humans).
Protocol
Representative Results
Discussion
There are several critical steps one should take care of while performing this protocol with mouse oocytes as well as with those of other species. Once isolated from their follicles, oocytes should be immediately transferred into the recording drops, as the separation from the companion cumulus cells triggers the beginning of the GV-to-MII transition. A possible modification to the present protocol could be the addition of 3-isobutyl-1-methylxanthine (IBMX) to the M2 medium used for COCs isolation. IBMX prevents the imme…
Disclosures
The authors have nothing to disclose.
Acknowledgements
This work was made possible thanks to support by: University of Pavia FRG 2016; University of Parma FIL 2014, 2016; and Kinesis for supplying the plasticware necessary to carry out this study. We thank Dr. Shane Windsor (Faculty of Engineering, University of Bristol, UK) for providing the Cell_PIV software.
Materials
| Folligon | Intervet | A201A02 | Hormonal treatment |
| Hoechst 33342 | Sigma-Aldrich | B2261 | For oocyte heterochromatin staining |
| Cell culture Petri-dish 35 mm x 10 mm | Corning | 430165 | For COCs isolation |
| EmbryoMax M2 Medium (1X), Liquid, with phenol red | Merck-Millipore | MR-015-D | For COCs isolation |
| MEM Alpha medium (1X) + Glutamax | Sigma-Aldrich | M4526 | For oocyte in vitro maturation |
| Cell culture Petri-dish 35 mm glass-bottom | WillCo | GWSt-3522 | For imaging experiments |
| BioStation IM-LM | Nikon | MFA91001 | Live cell screening system |
| Pasteur pipette | Delchimica Scientific Glassware | 6709230 | For follicles manipulation |
| Mineral oil | Sigma-Aldrich | M8410 | To prevent contamination and medium evaporation |
| Penicillin / Streptomycin | Life Technologies | 15070063 | To prevent medium contamination |
| Fetal Bovine Serum (FBS) | Sigma-Aldrich | ML16141079 | For making up αMEM medium |
| L-Glutamine | Life Technologies | 25030 | For making up αMEM medium |
| Taurine | Sigma-Aldrich | T0625 | For making up αMEM medium |
| Bovine Serum Albumin (BSA) | Sigma-Aldrich | A3310 | For making up αMEM media |
| Sodium pyruvate | Sigma-Aldrich | P4562 | For making up αMEM media |
| Zoletil (Tiletamina and Zolazepan cloridrate) | Virbac Srl | QN01AX9 | For mice anesthesia |
| Cell_PIV sofware | Kindly provided by Dr. Shane Windsor, University of Bristol, UK | - | - |
| MATLAB | The MathWorks, Natick, MA | - | For multi-paradigm numerical computing |
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