Background

The migration of cells within our body is an essential process and driven by complex underlying cellular functions. It plays an important role in many physiological processes, including development, immune responses, and tissue regeneration (Kunwar et al., 2006; Friedl and Weigelin, 2008; Reig et al., 2014). In addition, certain pathological situations such as tumor invasion and metastasis rely on cell motility (Thiery, 2002). Consequently, cell migration has become a major field of study in the context of both fundamental and translational research. Although in the last decade we have witnessed enormous advances in the understanding of the mechanisms underlying the highly plastic process of cell migration, many questions remain open. Especially, the complex regulation of migration is still unclear within differently composed microenvironments that are crowded by cells and extracellular matrix (Petrie et al., 2009; Friedl and Wolf, 2010).

To analyze cell migration, several in vitro and in vivo cell migration assays have been developed over the years. Thein vivo cell migration assays most closely mimic the real physiological situation and observe cells within their natural environment with its complexities of variable extracellular matrix (ECM) composition, geometry, topography and pore size. However, performing such experiments is labor- and cost-intensive, time-consuming, tough to control and requires advanced imaging techniques and animal experiments. Due to such practical challenges, cell migration has traditionally been studied on two-dimensional (2D) surfaces (Dang and Gautreau, 2018), e.g., in the context of wound-healing assays (Molinie and Gautreau, 2018). While this works to some extent for adherent cells such as breast epithelial carcinoma cells, 2D migration assays have little physiological relevance and thus little predictive value. Moreover, the striking difference between the 2D and the 3D settings becomes understandable in the light of recent studies of cell motility (Lämmermann et al., 2009; Friedl et al., 2012; Petrie and Yamada, 2016). These recent studies demonstrate that cell migration is a very plastic process and the cells embedded in 3D matrices composed of collagens or matrigel employ a very different locomotory machinery than cells on 2D surfaces. Therefore, studying the migration of cells embedded within a physiological-like 3D environment could lead to the results that have more significance and better predictive value.

Apart from being easier to perform than true in vivo migration experiments, 3D migration assays with their simpler matrix composition offer the advantage of a controlled, easily manipulable environment. Thus, it facilitates easy dissection of molecular mechanisms and the interpretation of experimental results. The 3D migration studies are usually done with the help of Boyden chambers (e.g., transwell assays [Visweshwaran et al., 2018]). However, these assays typically provide only an endpoint readout of cell migration efficiency, thereby not much information derived for an in-depth analysis. In contrast, real-time microscopy-based 3D assays allow one to observe and track individual cells, and thus the analysis of various parameters such as cell morphology during migration, cell speed, and directionality.

To our knowledge, there are not many optimal methods available for 3D cell migration analysis. All existing methods have their limitations. They either allow the experimenter to use a set-up where the embedded cells in the collagen gel are prone to migrate randomly in all directions including Z-axis, which render them hard to track and quantify migration parameters, or compel the experimenter to use complex, hard-to-handle and often costly setups (Rommerswinkel et al., 2014; Biswenger et al., 2018) to perform 3D migration assays. To overcome these limitations, we have developed a set-up where cells are sandwiched in a single plane between two collagen-fibronectin gels. This procedure facilitates the analysis of cell tracks, which are for the most part 2D, at least in the beginning, but in a 3D environment. In essence, here we describe an easy method for performing and analyzing 3D migration assays based on a home-made set-up and an easy analysis pipeline.