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# 3D imaging-based analysis of the germline in teleost

Marlène Davilma¹, Stéphanie Gay¹, Manon Thomas¹, Laurence Dubreil², Frédérique Clément³, Violette Thermes¹

## Context

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* In mammals, the stock of oocytes is predetermined at birth, whereas in teleosts, the oocyte reserve is renewed throughout life

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* Use of the reserve in adults to produce mature oocytes and reconstitution of the reserve from germline stem cells

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* Germline stem cells organized in germline cradles surrounded by somatic cells expressing sox9 (1)

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**How do germline stem cells contribute to the renewal of the oocyte reserve and what are the regulatory mechanisms involved in this renewal?**

## Objectives

To explore the oogenesis renewal process and its regulation, we have chosen the medaka as a model organism and developed a **3D imaging strategy for the whole ovary**. This approach aims to provide us with **quantitative data to study the cellular dynamics of germinal cradles**.

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* Study oocyte reserve formation and renewal

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* Identify the molecular regulators of oocyte reserve

## Imaging and image analysis

In order to image the germinal cradles and follicles, we have developed a whole ovary immunolabeling protocol combined with the C-ECi clearing protocol (2). Once the protocol is completed, we must transfer our samples to agarose for **3D imaging using Light Sheet Blaze imaging** (APEX platform, ONIRIS, Nantes). Without this agarose mounting, the screw used during acquisition was visible and distracting, and the pressure exerted by the screw could damage the sample.

Without agarose :

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Visible screw

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With agarose :

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* Denoising and segmentation of images using the N2V module and Cellpose to study follicle distribution, followed by error correction and diameter measurement with AMIRA software (3).

* Adaptation of these analysis steps for the quantitative study of the germinal cradles.

## Emergence of several difficulties with Light Sheet acquisitions

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* 1st difficulty

* Cellpose segmentation detecting many false positives in agarose.

* Development of a custom Cellpose model to segment the whole ovary and create an ovarian mask, avoiding false-positive labels in agarose.

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* 2nd difficulty

* Very large Light Sheet microscopy images, over 100GB each after stitching.

* Pre-processed images between 800KB and 2.5GB, causing challenges in opening and segmenting them with Cellpose (potential use of CellposeDask extension).

## Prospects and difficulties for image analysis

### 1- Study the distribution and number of cradles in medaka ovaries

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* Denoising with N2V

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* Segmentation of vasa-positive germline stem cell clusters surrounded by somatic cells expressing sox9 with Cellpose_Napari

### 2- Study the composition of germinal cradles

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* Difficulty : vasa-labelling is cytoplasmic so these cells are difficult to segment individually

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* We want to use MG core labelling to separate vasa-positive cells individually with Cellpose Napari

## References

1- Nakamura, Shuhei, et al. "Identification of germline stem cells in the ovary of the teleost medaka." *Science* 328.5985 (2010): 1561-1563.

2- Lesage, Manon, et al. "C-ECi: a CUBIC-ECi combined clearing method for three-dimensional follicular content analysis in the fish ovary." *Biology of Reproduction* 103.5 (2020): 1099-1109.