Abstract
Pattern formation in developing tissues involves dynamic spatio-temporal changes in cellular organization and subsequent evolution of functional adult structures. Branching morphogenesis is a developmental mechanism by which patterns are generated in many developing organs, which is controlled by underlying molecular pathways. Understanding the relationship between molecular signaling, cellular behavior and resulting morphological change requires quantification and categorization of the cellular behavior. In this study, tissue-level and cellular changes in developing salivary gland in response to disruption of ROCK-mediated signaling by are modeled by building cell-graphs to compute mathematical features capturing structural properties at multiple scales. These features were used to generate multiscale cell-graph signatures of untreated and ROCK signaling disrupted salivary gland organ explants. From confocal images of mouse submandibular salivary gland organ explants in which epithelial and mesenchymal nuclei were marked, a multiscale feature set capturing global structural properties, local structural properties, spectral, and morphological properties of the tissues was derived. Six feature selection algorithms and multiway modeling of the data was performed to identify distinct subsets of cell graph features that can uniquely classify and differentiate between different cell populations. Multiscale cell-graph analysis was most effective in classification of the tissue state. Cellular and tissue organization, as defined by a multiscale subset of cell-graph features, are both quantitatively distinct in epithelial and mesenchymal cell types both in the presence and absence of ROCK inhibitors. Whereas tensor analysis demonstrate that epithelial tissue was affected the most by inhibition of ROCK signaling, significant multiscale changes in mesenchymal tissue organization were identified with this analysis that were not identified in previous biological studies. We here show how to define and calculate a multiscale feature set as an effective computational approach to identify and quantify changes at multiple biological scales and to distinguish between different states in developing tissues.
Highlights
Morphological and functional development of organs necessitates generation of multiple cell types and their coordinated spatiotemporal arrangement
We developed a cell-graph-based multiscale feature analysis capturing changes in cellular behavior and resulting organ shape upon treatment with Rho associated coiled-coil kinase 1 (ROCK1) inhibitor; providing insight into the cellular dynamics of submandibular gland (SMG) morphogenesis and the function of ROCK1mediated signaling in this process
Immunostaining and Image Acquisition We probed for quantitative changes in mouse embryonic submandibular gland (SMG) organ explants that were treated with the ROCK1/2 inhibitor, Y27632, using cell-graph methods
Summary
Morphological and functional development of organs necessitates generation of multiple cell types and their coordinated spatiotemporal arrangement. Important questions regarding the signals controlling branching, what patterns are followed by the organs, and how these movements are regulated at cellular and tissue level are just beginning to be explored. Recent studies in another organ that undergoes branching morphogenesis, the developing lung, identified a set of three stereotypical geometric subroutine patterns that when reiteratively combined result in an adult lung [2]. Since the branching pattern in salivary gland is different and the morphological patterns are less apparent at the tissue level than in the lung, we investigated whether a computational approach could be used to identify, quantify, and specify the cellular and tissue level organization of developing salivary glands as a first step in understanding the processes controlling organogenesis
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