# FAST – filamentous actin segmentation tool for quantifying cytoskeletal organization

## TL;DR

FAST is a deep learning tool that segments and quantifies actin structures in microscopy images, aiding research on cell motility and disease.

## Contribution

FAST introduces a novel deep learning-based method for segmenting actin structures without requiring specific antibodies.

## Key findings

- FAST accurately segments and quantifies actin structures in confocal microscopy images.
- The tool works across different cell lines and dynamic changes in actin organization.
- FAST reduces the need for antibody-based labeling, streamlining actin structure analysis.

## Abstract

Studying how actin filaments are assembled into different subcellular structures can provide insights into both physiological processes and the mechanisms of disease. However, quantifying the size, abundance and organization of different classes of actin structure from optical microscopy data remains a challenge. To address this, we developed a deep learning-based tool called the ‘filamentous actin segmentation tool’ (FAST) to accurately and efficiently segment and quantify different classes of actin structure from phalloidin stained confocal microscopy images. We evaluated the performance of this tool to segment and quantify the abundance of different classes of actin structure in different cell lines and with dynamic changes in actin organization using LifeAct–GFP during drug treatments. FAST enables quantification of different classes of actin structure from actin images alone, without the need for specific antibodies against proteins in different actin structures and hence can be a useful tool for researchers studying actin-related pathways involved in cell motility, cancer metastasis and drug development.

Highlighted Article:
Development of the ‘filamentous actin segmentation tool’ (FAST), which leverages deep learning and antibody assisted labeling to segment and quantify actin structures from optical microscopy images.