ChemoTrack: A comprehensive dataset linking single-cell migration trajectories to precisely defined chemotactic signals

Abstract

Chemotaxis drives cell migration in processes ranging from wound healing to embryonic development and cancer metastasis, yet its quantitative understanding remains limited because responding cells change and degrade attractant gradients, and existing datasets are too small and imprecise to capture stochastic behaviour. We present ChemoTrack, a publicly accessible resource comprising 2 million measurements from 500,000 migration tracks, in which the chemoattractant gradient and concentration experienced by every cell at the time of observation are precisely determined. The dataset includes microscopy images and trajectories spanning a full range of biologically relevant chemotactic conditions. Analysis shows that cells steer according to absolute differences in active receptor number, not fractional receptor occupancy, and maximal chemotaxis is not predicted by half-maximal receptor occupancy. By combining scale, precision and accessibility, ChemoTrack shifts quantitative description of eukaryotic chemotaxis from experimental conditions to the instantaneous chemical signal experienced by individual cells, enabling future mathematical and mechanistic analyses.