Published December 16, 2024 | Version v3

Mammary epithelial intravital imaging data and MaSCOT-AI Cellpose model for analysis of in vivo cell shape dynamics

Authors/Creators

Description

The data and deep learning segmentation model deposited here are derived from 3D multicoloured intravital microscopy of mammary epithelial cells during development. We aimed to study in vivo cell shape dynamics in real-time in an unbiased way. This robust and deep analysis revealed that hormone-responsive breast cells are unexpectedly elongated and motile at a high frequency during duct growth. The data is associated with our publication Dawson, Milevskiy et al, Cell Reports 2024, Hormone-responsive progenitors have a unique identity and exhibit high motility during mammary morphogenesis. https://doi.org/10.1016/j.celrep.2024.115073

Deposited data
- Single channel intravital movie maximum projections (File:MaSCOT-AI Max projections). These are up to 5 hours long, with timepoints every 10 minutes.
- Extracted 5th time points from each movie that we used for model training (File:MaSCOT-AI t5 training)
- Segmentation files generated by Cellpose 2.2.2 (File: MaSCOT-AI t5 segmentation files)

Analysis scripts:
The Trackmate-Cellpose python script, R data processing scripts and example excel data sheet are on github at https://github.com/cadaws/MaSCOT-AI

Example analysis and data export:
A small set of example data and resulting trackmate-Cellpose output will be uploaded at a later date.

Methods
27 4D movies were acquired every 10 minutes by multiphoton microscopy of anaesthetised cell-type-specific confetti mice at different stages of development. 350 single channel, single-cell thick layers (10-30 µm sections) were isolated by 3D cropping, then flattened by max projection. The 5th time point from all movies was taken for model training in Cellpose 2.2.2, which was achieved after manual correction of segmentation for 150 images (MaSCOT-AI model).

The MaSCOT-AI model was used in a high throughput Trackmate-Cellpose script in ImageJ to track mammary cell shape over time.

Software versions:
Cellpose 2.2.2 GUI with GPU was installed according to https://pypi.org/project/cellpose/ (March 2024).
Trackmate v7.11.1

File name structure
Date_mouse-model_developmental-stage_fluorescent-protein_z-span

Mouse models:
K5: K5-rtTA/tetoCre/Confetti
Elf5: Elf5-rtTA/tetoCre/Confetti
Pr: PR-Cre/Confetti

Developmental stage:
no label = Terminal end bud at 5 weeks
duct/notpreg = duct at 6 or 9 weeks
6dPreg/6dplug = 6 days pregnancy
6d MPA = 6 days MPA treatment
MPAveh = 6 days MPA vehicle treatment

 

Files

MaSCOT-AI Max projections.zip

Files (943.4 MB)

Name Size
md5:9a88afd51dd8d517fadcdea3e4cc007d
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md5:b4771b7840bed51616e56854f400c9b0
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md5:190df7e1b8c0a2e9debb6a1fdc8d7596
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md5:d2f52352e47798597b2cddc2c34a17c5
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md5:80f1cbbf36eaf9a8f2aaeaad26b56615
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md5:d08ae8fa65f69ed0dc41664b07194928
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Additional details

Related works

Is published in
Publication: 10.1016/j.celrep.2024.115073 (DOI)

Funding

National Health and Medical Research Council
Investigator Grant 2018105

Software

Repository URL
https://github.com/cadaws/MaSCOT-AI
Programming language
Python
Development Status
Active