In this repository we analyze Cell Painting data generated from multiple cell line clones that were resistant or sensitive to bortezomib.
Kelley ME, Berman AY, Stirling DR, Cimini BA, Han Y, Singh S, Carpenter AE, Kapoor TM, Way GP. High-content microscopy reveals a morphological signature of bortezomib resistance. (2023) eLife; 12:e91362. DOI: https://doi.org/10.7554/eLife.91362.
We cultured a colon cancer cell line (HCT116), treated with a proteosome inhibitor (Bortezomib), and selected two resistant clones. We applied Cell Painting to these cell lines (in triplicate) under four conditions (DMSO, 0.7nm, 7nm, and 70nm Bortezomib).
The Cell Painting assay captures several cellular morphology features (described in more detail here). Our hypothesis was that morphological features could distinguish wildtype from resistant clones.
We processed the cell painting data using CellProfiler. We use CellProfiler to test quality control, segment images to extract nuclei, and measure features captured by cell painting.
This repository contains all image analysis pipelines and image-based profiling pipelines (see 0.generate-profiles
).
This repository ingests the processed Cell Painting data and performs several downstream analyses.
Using the triplicate measurements, and two batches, we perform the following pilot analyses:
- Obtain similarity matrices for each batch independently and combined; perform hierarchical clustering; visualize heatmaps.
- Apply UMAP to the batched data to observe large differences across variables
- Apply t-tests to determine cell morphology differences between conditions:
- We test for differences between resistant clones at two doses of Bortezomib (
0.7nm
and7nm
) - We also test for differences between wildtype and resistant clones at a low dose of Bortezomib (
0.7nm
)
- We test for differences between resistant clones at two doses of Bortezomib (
We use conda to manage package versions. After installing conda, obtain all required packages:
conda env create --force --file environment.yml
# Activate environment
conda activate resistance-mechansisms
Clone the github repository. First, generate and enable SSH Keys if you haven't already.
# Then clone and enter repo
git clone git@github.com:broadinstitute/profiling-resistance-mechanisms
cd profiling-resistance-mechanisms
All analyses are presented in analysis.sh
.
To reproduce, perform the following:
./analysis.sh
Please file an issue with any questions or bug reports.