C-Eci: A Cubic-Eci Combined Clearing Method For 3D Follicular Content Analysis In The Fish Ovary

Abstract

15A modified ethyl-cinnamate-based clearing method allows solving fish ovary-16 specific challenges for 3D imaging, including high lipid-contents, and analyzing the 17 ovarian follicular content in medaka and trout. ABSTRACT 1Deciphering mechanisms of oocyte development in female fishes still remains 2 challenging and a comprehensive overview of this process at the level of the organ is 3 still needed. The recent development optical tissue clearing methods have 4 tremendously boosted the 3D imaging of large size biological samples that are 5 naturally opaque. However, no attempt of clearing on fish ovary that accumulates 6 extremely high concentration of lipids within oocytes has been reported to date. To 7 face with this ovarian-specific challenge, we combined two existing clearing 8 methods, the non-toxic solvent-based Eci method for efficient clearing and the 9 CUBIC method to enhance lipid removal and reduce non-specific staining. The 10 methyl green fluorescent dye was used to stain nuclei and delineate follicles. Using 11 this procedure (named C-Eci), ovaries of both medaka and trout could be imaged in 12 3D and all follicles analyzed. To our knowledge this is the first procedure elaborated 13 for clearing and imaging fish ovary in 3D. The C-Eci methods thus provides an 14 interesting tool for getting precise quantitative data on follicular content in fish 15 ovary and promises to be useful for further morphological studies. 16 17

An end-to-end pipeline based on open source deep learning tools for reliable analysis of complex 3D images of Medaka ovaries

“…In situ follicular size measurements by our 3D imaging and DL-based segmentation approaches allowed producing size distribution profiles for both larvae and adult ovaries. Our results are consistent with those obtained previously from dissociated follicles measured manually for the larvae ovary (Iwamatsu, 2015) or semi-automatically from 3D images by classical watershed segmentation approaches for the adult ovary as shown in our previous study (Lesage et al, 2020). However, greater confidence can be attributed to the present study, particularly for the pre- and post-vitellogenic stages in the adult ovary for which we achieved fewer segmentation errors.…”

“…Finally, stained larvae ovaries were embedded in low-melting agarose 1% before proceeding to clearing. Adult ovary samples were stained and cleared according to the C-ECi method with few modifications (Lesage et al, 2020). For staining, adult ovaries were incubated with the Methyl Green dye (MG) (40 μg/mL, 323829, Sigma-Aldrich) in PBS/0.1% Triton X-100 at 37°C for 2.5 days.…”

“…Finally, stained larvae ovaries were embedded in low-melting agarose 1% before proceeding to clearing. Adult ovary samples were stained and cleared according to the C-ECi method with few modifications (Lesage et al, 2020).…”

“…It is thus now possible to generate 3D image data, generally of very large size, that ideally allows direct and comprehensive access to all structures and to achieve a precise 3D image reconstruction of the whole ovary. However, tools for 3D image analyses are still too inaccurate and tedious, especially for image segmentation, partly because of an irregular contrast signal in depth and the presence of oocytes of heterogenous sizes, as reported previously for the adult Medaka ovary (Lesage et al, 2020). Ovarian 3D imaging therefore has a promising future, but its widespread use still relies on the availability of more efficient and easier-to-use computerized analytical tools.…”

“…Some studies have also focused on the development of complex stereological approaches to limit the biases induced by 2D approaches (Charleston et al, 2007). Recently, the emergence of optical tissue clearing methods and powerful microscopes have opened new perspectives with the possibility of imaging whole ovaries in three dimensions (3D), notably for mice and fishes (Fiorentino et al, 2021; Lesage et al, 2020; Soygur and Laird, 2021). It is thus now possible to generate 3D image data, generally of very large size, that ideally allows direct and comprehensive access to all structures and to achieve a precise 3D image reconstruction of the whole ovary.…”