AFT-tracks is a tool to analyze the interplay between cell migration and the extracellular matrix

Abstract

Cell migration underlies key processes in living organisms, such as morphogenesis, immune response, wound repair, and tissue homeostasis. In different processes, cells can use various migration modes that define the mechanism of cell migration. Despite the variability of migration mechanisms, analysis of migration behavior is based on quantitative migration metrics. Calculation of these metrics relies on specialized tools that can reveal the cell migration features, such as velocity, directionality, and displacement. In addition to the cell migration behavior description, another crucial factor regulating cell migration is the ECM. ECM acts as the substrate that migrating cells follow and interact with. Importantly, physical parameters such as ECM orientation and morphology directly affect cell migration behavior. Despite this clear connection between cell migration and ECM features, there is a lack of an open-source tool to reveal the interplay between ECM properties and migrating cells. Here, we introduce the open-source AFT-tracks tool, which combines cell track analysis with assessment of ECM orientation and morphology. Cell track feature calculations are integrated with CellTracksCollab, while ECM orientation is determined using the Alignment by Fourier Transform (AFT) tool. The ECM morphology is calculated using the Multiscale Ridge-Detection algorithm, which provides structural features describing ECM complexity, density, porosity, and branching. In AFT-tracks, we propose AFT-AI metrics that define a coefficient of alignment between tracks and ECM orientation. We present AFT-tracks as a user-friendly, open-source tool for studying the interplay between migrating cells and ECM, enabling new insights into these interactions.