Vitolo, M. I. | Search bioRxiv

bioRxiv2021

Label-free Cell Tracking Enables Collective Motion Phenotyping in Epithelial Monolayers

Collective cell migration is an umbrella term for a rich variety of cell behaviors, whose distinct character is essential for biological function, notably for cancer metastasis. One essential feature of collective behavior is the motion of cells relative to their immediate neighbors. We introduce an AI-based pipeline to segment and track cell nuclei from phase contrast images. Nuclei segmentation is based on a U-Net convolutional neural network trained on images with nucleus staining. Tracking, based on the Crocker-Grier algorithm, quantifies nuclei movement and allows for robust downstream analysis of collective motion. Since the AI algorithm required no new training data, our approach promises to be applicable to and yield new insights for vast libraries of existing collective motion images. In a systematic analysis of a cell line panel with oncogenic mutations, we find that the collective rearrangement metric, D2min, which reflects non-affine motion, shows promise as an indicator of metastatic potential. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=67 SRC="FIGDIR/small/472148v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@82a35corg.highwire.dtl.DTLVardef@b31442org.highwire.dtl.DTLVardef@f703aborg.highwire.dtl.DTLVardef@1120d98_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIVersatile AI-based algorithm can robustly identify individual cells and track their motion from phase contrast images. C_LIO_LIAnalysis of motion of cells relative to nearby neighbors distinguishes weakly tumorigenic (KRas) and metastatic (KRas/PTEN-/-) cell lines. C_LI

biophysics↗

bioRxiv2020

Distinct Roles of Tumor-Associated Mutations in Collective Cell Migration

Recent evidence suggests that groups of cells are more likely to form clinically dangerous metastatic tumors, emphasizing the importance of understanding mechanisms underlying collective behavior. The emergent collective behavior of migrating cell sheets in vitro has been shown to be disrupted in tumorigenic cells but the connection between this behavior and in vivo tumorigenicity is unclear. Here we use particle image velocimetry to measure a multi-dimensional collective migration phenotype for genetically defined cell lines that range in their in vivo behavior from non-tumorigenic to aggressively metastatic. By using cells with controlled mutations, we show that PTEN deletion enhances collective migration, while Ras activation suppresses it, even when combined with PTEN deletion. These opposing effects on collective migration phenotype of two mutations that are frequently found in patient tumors could be exploited in clinical assessments of metastatic potential or in the development of novel treatments for metastatic disease.

biophysics↗