Cell lines and clearing approaches: a single-cell level 3D light-sheet fluorescence microscopy dataset of...

Area of Science:

• Biomedical Imaging
• Cell Biology
• Cancer Research

Background:

• Three-dimensional (3D) cell cultures are crucial for biological research, particularly in cancer studies.
• Optical clearing methods are used to visualize cells within deep tissue layers of multicellular spheroids.
• A quantitative metric is lacking to determine the best clearing approach for diverse cell lines.

Purpose of the Study:

• To create and share a high-resolution 3D image dataset of human carcinoma spheroids.
• To evaluate and compare five different optical clearing protocols (ClearT, ClearT2, CUBIC, ScaleA2, Sucrose).
• To provide a resource for assessing image quality and light penetration in cleared 3D cancer models.

Main Methods:

• Generated a dataset of 90 multicellular cancer spheroids from three human carcinoma cell lines (T-47D, 5-8F, Huh-7D12).
• Applied five distinct optical clearing protocols to the spheroids.
• Imaged all samples using a Leica SP8 Digital Light-Sheet microscope after nuclear staining with DRAQ5.

Main Results:

• The dataset captures single-cell resolution 3D images of cleared spheroids under standardized conditions.
• Expert annotation allows for qualitative comparison of clearing protocol effectiveness across different cell lines.
• The dataset serves as a benchmark for quantitatively evaluating image analysis metrics for deep-layer imaging.

Conclusions:

• The shared dataset facilitates the selection of optimal optical clearing strategies for various cancer cell lines.
• This resource aids in advancing quantitative assessment of imaging techniques in 3D cell culture models.
• It supports improved visualization and analysis of cellular structures in deep spheroid layers for cancer research.