# A semi-automated imaging and analysis pipeline for NET quantification and temporal-profiling of NETosis

## TL;DR

This paper introduces a new imaging pipeline to study and track NETosis, a type of cell death linked to immune responses and tissue damage.

## Contribution

A novel live-cell imaging and analysis pipeline for quantifying and classifying NETosis stages using machine learning.

## Key findings

- The pipeline enables large-scale tracking of NETosis progression in cultured cells.
- Validation was performed in HL-60-derived granulocyte-like cells and mouse primary neutrophils.
- The method supports dose- and stimulus-dependent analysis of NETosis modulators.

## Abstract

NETosis is a distinct form of neutrophil cell death involved in innate immunity and characterized by the release of DNA, that when dysregulated contributes to tissue damage and target-organ injury. As our understanding of the mechanisms governing this process continues to advance, there is a growing need for refined tools that can precisely characterize NETosis and enable efficient screening of its modulators. Here, we present a novel live-cell imaging and analysis pipeline for quantifying NETosis in cultured cells. We have generated a CellProfiler pipeline that enables in-depth analysis of cell and NET features, allowing for subsequent characterization and classification of NETosis stages using machine learning. Coupled with high throughput live cell imaging, this approach allows for large-scale and automated tracking of NETosis progression. The pipeline was validated in promyelocytic HL-60 cells differentiated into granulocyte-like cells, as well as primary neutrophils from the bone marrow of mice. We further confirmed dose and stimulus-dependent responses to common stimuli and pharmacological inhibitors of NETosis. As a flexible and scalable high-throughput imaging pipeline, our novel approach allows for the assessment of NETting dynamics and the screening of potential NETosis-modulating agents, which will be instrumental in developing therapies for NET-induced tissue injury.