Automated Layer Analysis (ALAn): An Image Analysis Tool for the Unbiased Characterization of Mammalian Epithelial Architecture in Culture

Background

We developed a tool for the unbiased analysis of layer architecture (Automated Layer Analysis or ALAn) for two reasons. Firstly, cultured epithelial architecture can vary drastically between experiments, and we found this can be the case even across a single 1 mm² culture well [1]. Secondly, epithelial tissues are commonly considered to be pseudo–two dimensional, meaning that architecture is primarily considered with respect to the tissue plane/surface. We found that this perspective is not always predictive of architecture with respect to tissue depth (the apical-basal axis) [1]. We are interested in the mechanical and biological parameters that contribute to epithelial layer architecture and we developed this tool to quantify architecture development over time and test the effect of plating density, culture time, and presence of cadherin-mediated adhesion on architecture. Due to the variability in the shape of layers and the complexity of attempting to perform 3D analysis manually, it was important to us to develop an unbiased and automated tool that requires as little user input as possible. As a consequence of developing ALAn, we identified a developmental series of layer architectures that progress through the process of epithelialization, whereby individual cells form a tissue layer [1,2]. Our quantifications of cell height, cell density, and circularity show distinct morphological regimes for each architecture.

Several tools exist for the analysis of epithelial topology in the plane of the tissue [3–6]. As far as we are aware, ALAn is the first to characterize and quantify the apical-basal topology of cultured layers. To do so, the tool makes use of two pieces of spatial information: 1) a projection of actin signal intensity and 2) the positions of cell nuclei in the apical-basal dimension. Using this information, ALAn outputs layer density and layer height and assigns each layer to one of four organized categories representing a developmental series (Immature, Intermediate A, Intermediate B, and Mature) or a fifth category of exclusion (Disorganized) [1,2]. ALAn also utilizes existing Python libraries to output in-plane quantifications of cell shape.

Confluent epithelial tissues in culture transition between distinct developmental architectures as they proliferate and therefore densify [1,2]. ALAn makes architectural classifications based on plots of the average spatial distributions of nuclei and actin across the apical-basal depth of a 3D-imaged region. At sparse densities, cultured epithelial cell layers have a squamous morphology and are characterized by a lack of defined lateral surfaces; these are classified as Immature. The spatial plots of Immature layers have the peak of nuclear distribution located at, or occasionally above, the peak actin intensity (Figure 1A). At intermediate densities, layers develop lateral cell–cell borders and rounded cell apices; these are classified as Intermediate. The Intermediate category is split into two. The first of these, called Intermediate A (IntA), are layers where cells exhibit an asymmetric actin intensity profile with a single peak closer to the apical surface than the nuclear profile (Figure 1B). If the plot of actin exhibits a shoulder (corresponding to distinct lateral and apical pools of actin), then layers are classified as Intermediate B (IntB) or Mature (Figure 1C–1D) [2]. ALAn uses the derivative of the actin intensity plot to detect this shoulder. If the derivative is two-peaked, the ratio of the right peak to the left peak is used. A ratio of less than 1 defines IntB layers, and a ratio of greater than 1 is classified as a Mature layer. The Disorganized architectural category of epithelial cell culture is characterized by a failure to achieve a regular monolayered architecture in the apical-basal axis and therefore is characterized by broad nuclear and actin profiles (Figure 1E). Disorganization occurs when the underlying cell culture substrate area is insufficient to accommodate the number of cells seeded onto the plate [1].

Figure 1. Epithelial architecture categories and the distinctive spatial distribution profiles of nuclei and actin positions in the apical-basal (z) axis that Automated Layer Analysis (ALAn) uses to categorize them