Cells don’t divide forever. When they are damaged or under stress, many of them enter a state called senescence: they stay alive but permanently stop dividing. Senescence protects the body because it stops damaged cells from multiplying, and it is therefore one of the natural barriers against cancer. At the same time, senescent cells that build up in tissue can promote inflammation, aging and, in some cases, tumour growth. Being able to reliably tell senescent cells apart from healthy ones is therefore important for cancer research.

One telltale sign of a cell in trouble is the presence of micronuclei. These are tiny, separate packages of genetic material found next to the cell’s main nucleus. They form when chromosomes or fragments of chromosomes are lost during cell division, and they indicate that the cell’s genome has become unstable.

In this project we are developing software that automatically finds and outlines individual cells, nuclei and micronuclei in fluorescence microscopy images. In these images, specific cell structures are stained with glowing dyes and photographed at very high magnification, in several layers through the depth of the sample. From the features of each cell, including its micronuclei, the software is designed to predict biological properties such as whether the cell is senescent. Doing this by eye is slow and subjective. An automated analysis can evaluate thousands of cells consistently and in a fraction of the time.

The program reads common microscopy image formats, including files directly from ZEISS microscopes. It also comes with a built-in image viewer, so researchers can open their recordings, inspect them and run the analysis without any programming.

Status: The project is under active development. The software will be released on our GitHub page once it has been sufficiently tested.