Explore the vast range of titles available.

This protocol describes how to use a computer program, DiPer, to analyze directional persistence of cell migration. The mechanism by which cells control directional persistence during migration is a major question. However, the common index measuring directional persistence, namely the ratio of displacement to trajectory length, is biased, particularly by cell speed. An unbiased method is to calculate direction autocorrelation as a function of time. This function depends only on the angles of the vectors tangent to the trajectory. This method has not been widely used, because it is more difficult to compute. Here we discuss biases of the classical index and introduce a custom-made open-source computer program, DiPer, which calculates direction autocorrelation. In addition, DiPer also plots and calculates other essential parameters to analyze cell migration in two dimensions: it displays cell trajectories individually and collectively, and it calculates average speed and mean square displacements (MSDs) to assess the area explored by cells over time. This user-friendly program is executable through Microsoft Excel, and it generates plots of publication-level quality. The protocol takes ∼15 min to complete. We have recently used DiPer to analyze cell migration of three different mammalian cell types in 2D cultures: the mammary carcinoma cell line MDA-MB-231, the motile amoeba Dictyostelium discoideum and fish-scale keratocytes. DiPer can potentially be used not only for random migration in 2D but also for directed migration and for migration in 3D (direction autocorrelation only). Moreover, it can be used for any types of tracked particles: cellular organelles, bacteria and whole organisms.

Cell migration plays a central role in tumor progression and metastasis, making it a critical parameter in both cancer biology and therapeutic evaluation. A range of in vitro migration assays are commonly used to assess treatment-induced effects on motility, each with distinct advantages and limitations that must be considered when interpreting results. In this study, we systematically compared four migration assay formats—scratch, zone-exclusion (Z-E), transwell, and single-cell tracking—across five melanoma cell lines treated with the multi-kinase inhibitor nintedanib. Migration inhibition was quantified for each assay, alongside machine learning-based classification to evaluate the discriminative power of assay-derived features in detecting treatment effects. All assays detected inhibitory effects of nintedanib, although response magnitude varied across formats. The transwell assay demonstrated clear inhibition in most lines but was sensitive to morphological changes. Gap closure assay-based migration rankings were influenced by cell size, underscoring the importance of size normalization. Scratch assays exhibited greater variability and potential confounding due to cell damage, while Z-E assays generated more uniform gaps without mechanical disruption. Single-cell tracking enabled high-resolution phenotypic profiling, including cell-specific features such as size and shape, resulting in consistently high classification accuracy. These findings highlight the importance of selecting appropriate assay formats to accurately evaluate migration behavior and the therapeutic efficacy of anti-migratory compounds.

The ability of cells to move and migrate is required during development, but also in the adult in processes such as wound healing and immune responses. In addition, cancer cells exploit the cells’ ability to migrate and invade to spread into nearby tissue and eventually metastasize. The majority of cancer deaths are caused by metastasis and the process of cell migration is therefore intensively studied. A common way to study cell migration is to observe cells through an optical microscope and record their movements over time. However, segmenting and tracking moving cells in phase contrast time-lapse video sequences is a challenging task. Several tools to track the velocity of migrating cells have been developed. Unfortunately, most of the automated tools are made for fluorescence images even though unlabelled cells are often preferred to avoid phototoxicity. Consequently, researchers are constrained with laborious manual tracking tools using ImageJ or similar software. We have therefore developed a freely available, user-friendly, automated tracking tool called CellTraxx . This software makes it easy to measure the velocity and directness of migrating cells in phase contrast images. Here, we demonstrate that our tool efficiently recognizes and tracks unlabelled cells of different morphologies and sizes (HeLa, RPE1, MDA-MB-231, HT1080, U2OS, PC-3) in several types of cell migration assays (random migration, wound healing and cells embedded in collagen). We also provide a detailed protocol and download instructions for CellTraxx.

Collective cell migration is crucial in various biological processes, including tumor progression and metastasis. The widely used scratch assay (wound healing assay) has limitations in throughput, reproducibility, and data analysis. To overcome these challenges, we previously developed the Transient Agarose Spot (TAS) assay, which enhanced assay precision and reproducibility. In this study, we present an improved microplate-based TAS assay. By using a microplate reader, we automated data acquisition, enabling the detection of cell migration in a 96-well plate format with greater throughput and accuracy. The new method applies Hoechst staining to label viable cells, providing a stable signal for kinetic analysis without compromising cell viability. We validated this approach with fluorophore-expressing cancer cells and demonstrated its ability to monitor dose-dependent effects of fetal bovine serum on cell migration. Additionally, we applied the microplate-based TAS assay to assess the anti-migratory effects of kinase inhibitors and mesenchymal stem cell-derived extracellular vesicles (EVs) on lung cancer cells. The assay accurately quantified migration inhibition and revealed the concentration-dependent effects of EVs, highlighting their potential as therapeutic agents. This microplate-based TAS assay provides a scalable, efficient, and cost-effective platform for high-throughput screening of cell migration and drug discovery, offering a robust alternative to traditional microscopy-based methods.

This is a protocol for studying several parameters of migration, including total and effective migration, velocity and cell polarization, in unharmed cells. Cell migration is a key feature of virtually every biological process, and it can be studied in a variety of ways. Here we outline a protocol for the in vitro study of cell migration using a ring barrier–based assay. A 'barrier' is inserted in the culture chamber, which prevents cells from entering a defined area. Cells of interest are seeded around this barrier, and after the formation of a peripheral monolayer the barrier is removed and migration into the cell-free area is monitored. This assay is highly reproducible and convenient to perform, and it allows the deduction of several parameters of migration, including total and effective migration, velocity and cell polarization. An advantage of this assay over the conventional scratch assay is that the cells move over an unaltered and virgin surface, and thus the effect of matrix components on cell migration can be studied. In addition, the cells are not harmed at the onset of the assay. Through computer automation, four individual barrier assays can be monitored at the same time. The procedure can be used in a 12-well standard plate allowing higher throughput, or it can be modified to perform invasion assays. The basic procedure takes 2–3 d to complete.

Quantitative imaging methods to analyze cell migration assays are not standardized. Here we present a suite of two-dimensional barrier assays describing the collective spreading of an initially-confined population of 3T3 fibroblast cells. To quantify the motility rate we apply two different automatic image detection methods to locate the position of the leading edge of the spreading population after 24, 48 and 72 hours. These results are compared with a manual edge detection method where we systematically vary the detection threshold. Our results indicate that the observed spreading rates are very sensitive to the choice of image analysis tools and we show that a standard measure of cell migration can vary by as much as 25% for the same experimental images depending on the details of the image analysis tools. Our results imply that it is very difficult, if not impossible, to meaningfully compare previously published measures of cell migration since previous results have been obtained using different image analysis techniques and the details of these techniques are not always reported. Using a mathematical model, we provide a physical interpretation of our edge detection results. The physical interpretation is important since edge detection algorithms alone do not specify any physical measure, or physical definition, of the leading edge of the spreading population. Our modeling indicates that variations in the image threshold parameter correspond to a consistent variation in the local cell density. This means that varying the threshold parameter is equivalent to varying the location of the leading edge in the range of approximately 1-5% of the maximum cell density.

Wound healing assay is a simple and cost-effective in vitro assay for assessing therapeutic impacts on cell migration. Its key limitation is the possible confoundment by other cellular phenotypes, causing misinterpretation of the experimental outcome. In this study, we attempted to address this problem by developing a simple analytical approach for scoring therapeutic influences on both cell migration and cell death, while normalizing the influence of cell growth using Mitomycin C pre-treatment. By carefully mapping the relationship between cell death and wound closure rate, contribution of cell death and cell migration on the observed wound closure delay can be quantitatively separated at all drug dosing. We showed that both intrinsic cell motility difference and extrinsic factors such as cell seeding density can significantly affect final interpretation of therapeutic impacts on cellular phenotypes. Such discrepancy can be rectified by using the actual wound closure time of each treatment condition for the calculation of phenotypic scores. Finally, we demonstrated a screen for strong pharmaceutical inhibitors of cell migration in cholangiocarcinoma cell lines. Our approach enables accurate scoring of both migrastatic and cytotoxic effects, and can be easily implemented for high-throughput drug screening.

To study the individual functions of hyaluronan interacting proteins in prostate cancer (PCa) motility through connective tissues, we developed a novel three-dimensional (3D) hyaluronic acid (HA) hydrogel assay that provides a flexible, quantifiable, and physiologically relevant alternative to current methods. Invasion in this system reflects the prevalence of HA in connective tissues and its role in the promotion of cancer cell motility and tissue invasion, making the system ideal to study invasion through bone marrow or other HA-rich connective tissues. The bio-compatible cross-linking process we used allows for direct encapsulation of cancer cells within the gel where they adopt a distinct, cluster-like morphology. Metastatic PCa cells in these hydrogels develop fingerlike structures, \"invadopodia\", consistent with their invasive properties. The number of invadopodia, as well as cluster size, shape, and convergence, can provide a quantifiable measure of invasive potential. Among candidate hyaluronan interacting proteins that could be responsible for the behavior we observed, we found that culture in the HA hydrogel triggers invasive PCa cells to differentially express and localize receptor for hyaluronan mediated motility (RHAMM)/CD168 which, in the absence of CD44, appears to contribute to PCa motility and invasion by interacting with the HA hydrogel components. PCa cell invasion through the HA hydrogel also was found to depend on the activity of hyaluronidases. Studies shown here reveal that while hyaluronidase activity is necessary for invadopodia and inter-connecting cluster formation, activity alone is not sufficient for acquisition of invasiveness to occur. We therefore suggest that development of invasive behavior in 3D HA-based systems requires development of additional cellular features, such as activation of motility associated pathways that regulate formation of invadopodia. Thus, we report development of a 3D system amenable to dissection of biological processes associated with cancer cell motility through HA-rich connective tissues.

Scratch assays are routinely used to study the collective spreading of cell populations. In general, the rate at which a population of cells spreads is driven by the combined effects of cell migration and proliferation. To examine the effects of cell migration separately from the effects of cell proliferation, scratch assays are often performed after treating the cells with a drug that inhibits proliferation. Mitomycin-C is a drug that is commonly used to suppress cell proliferation in this context. However, in addition to suppressing cell proliferation, mitomycin-C also causes cells to change size during the experiment, as each cell in the population approximately doubles in size as a result of treatment. Therefore, to describe a scratch assay that incorporates the effects of cell-to-cell crowding, cell-to-cell adhesion, and dynamic changes in cell size, we present a new stochastic model that incorporates these mechanisms. Our agent-based stochastic model takes the form of a system of Langevin equations that is the system of stochastic differential equations governing the evolution of the population of agents. We incorporate a time-dependent interaction force that is used to mimic the dynamic increase in size of the agents. To provide a mathematical description of the average behaviour of the stochastic model we present continuum limit descriptions using both a standard mean-field approximation and a more sophisticated moment dynamics approximation that accounts for the density of agents and density of pairs of agents in the stochastic model. Comparing the accuracy of the two continuum descriptions for a typical scratch assay geometry shows that the incorporation of agent growth in the system is associated with a decrease in accuracy of the standard mean-field description. In contrast, the moment dynamics description provides a more accurate prediction of the evolution of the scratch assay when the increase in size of individual agents is included in the model.

Microglial cells have important roles in maintaining brain homeostasis, and they are implicated in multiple brain diseases. There is currently interest in investigating microglial migration that results in cell accumulation at focal sites of injury. Here we describe a protocol for rapidly triggering and monitoring microglial migration by using a micropipette assay. This protocol is an adaptation of the axon turning assay using microglial cells. Chemoattractants released from the micropipette tip produce a chemotactic gradient that induces robust microglial migration. In combination with microscopic imaging, this assay allows simultaneous recording of cell movement and subcellular compartment trafficking, along with quantitative analysis. The actual handling time for the assay takes ∼2–3 h in total. The protocol is simple, inexpensive and convenient to set up, and it can be adopted to examine cell migration in multiple cell types, including cancer cells with a wide range of chemical signals.