Fast-growing intracellular Mycobacterium tuberculosis populations evade antibiotic treatment

macrohet is a code repository designed to investigate Macrophage heterogeneity. It accompanies the aforementioned manuscript exploring single-cell heterogeneity in Mtb-infected macrophages using time-lapse microscopy, tracking, and single-cell growth rate analysis.

Interactive figures and plots for this project can be explored via GitHub Pages: nthndy.github.io/macrohet

Image description: A pseudocoloured timelapse image of Mtb, projected along the time axis visualise spatiotemporal evolution.

Contents

• notebooks/: Reproducible analysis notebooks for data loading, segmentation, tracking, and quantification
• macrohet/: Python module with core analysis functions
• data/: Subset of image data with associated segmentation and tracks
• models/: Bespoke segmentation model and btrack tracking parameters
• docs/: HTML manuscript and supporting content (hosted via GitHub Pages)
• environment.yml: Conda environment specification
• .pre-commit-config.yaml: Code formatting and linting hooks

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Installation and Reproducibility

The following instructions are configured for an Ubuntu workstation.

Clone the repository:

git clone https://github.com/nthndy/macrohet.git
cd macrohet

Create, install and activate the environment:

mamba env create -f environment.yml
conda activate macrohet

Parts of the image tiling and stitching pipeline were adapted from Volker Hilsenstein’s DaskFusion project, used under the MIT License. Details of the hardware and software used to generate the analyses in this repository are provided in reproducibility.md.

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Contact

For questions or access to underlying data/code, please contact:

Nathan J. Day
Host–Pathogen Interactions in Tuberculosis Laboratory
The Francis Crick Institute
nathan.day@crick.ac.uk
@nthndy.bsky.social
github.com/nthndy