Membrane blebbing‐dependent (blebby) amoeboid migration can be employed by lymphoid and cancer cells to invade 3D‐environments. Here, we reveal a mechanism by which the small GTPase RhoB controls membrane blebbing and blebby amoeboid migration. Interestingly, while all three Rho isoforms (RhoA, RhoB and RhoC) regulated amoeboid migration, each controlled motility in a distinct manner. In particular, RhoB depletion blocked membrane blebbing in ALL (acute lymphoblastic leukaemia), melanoma and lung cancer cells as well as ALL cell amoeboid migration in 3D‐collagen, while RhoB overexpression enhanced blebbing and 3D‐collagen migration in a manner dependent on its plasma membrane localization and down‐stream effectors ROCK and Myosin II. RhoB localization was controlled by endosomal trafficking, being internalized via Rab5 vesicles and then trafficked either to late endosomes/lysosomes or to Rab11‐positive recycling endosomes, as regulated by KIF13A. Importantly, KIF13A depletion not only inhibited RhoB plasma membrane localization, but also cell membrane blebbing and 3D‐migration of ALL cells. In conclusion, KIF13A‐mediated endosomal trafficking modulates RhoB plasma membrane localization to control membrane blebbing and blebby amoeboid migration.

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High-content image-based cell phenotyping provides fundamental insights in a broad variety of life science areas. Striving for accurate conclusions and meaningful impact demands high reproducibility standards, even more importantly with the advent of data sharing initiatives. However, the sources and degree of biological and technical variability, and thus the reproducibility and usefulness of meta-analysis of results from live-cell microscopy have not been systematically investigated. Here, using high content data describing features of cell migration and morphology, we determine the sources of variability across different scales, including between laboratories, persons, experiments, technical repeats, cells and time points. Significant technical variability occurred between laboratories, providing low value to direct meta-analysis on the data from different laboratories. However, batch effect removal markedly improved the possibility to combine image-based datasets of perturbation experiments. Thus, reproducible quantitative high-content cell image data and meta-analysis depend on standardized procedures and batch correction applied to studies of perturbation effects.

High‐content image‐based cell phenotyping provides fundamental insights into a broad variety of life science disciplines. Striving for accurate conclusions and meaningful impact demands high reproducibility standards, with particular relevance for high‐quality open‐access data sharing and meta‐analysis. However, the sources and degree of biological and technical variability, and thus the reproducibility and usefulness of meta‐analysis of results from live‐cell microscopy, have not been systematically investigated. Here, using high‐content data describing features of cell migration and morphology, we determine the sources of variability across different scales, including between laboratories, persons, experiments, technical repeats, cells, and time points. Significant technical variability occurred between laboratories and, to lesser extent, between persons, providing low value to direct meta‐analysis on the data from different laboratories. However, batch effect removal markedly improved the possibility to combine image‐based datasets of perturbation experiments. Thus, reproducible quantitative high‐content cell image analysis of perturbation effects and meta‐analysis depend on standardized procedures combined with batch correction.