Shayoni Ray

Multiscale feature analysis of salivary gland branching morphogenesis.

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.

Cell-Based Multi-Parametric Model of Cleft Progression during Submandibular Salivary Gland Branching Morphogenesis

Cleft formation during submandibular salivary gland branching morphogenesis is the critical step initiating the growth and development of the complex adult organ. Previous experimental studies indicated requirements for several epithelial cellular processes, such as proliferation, migration, cell-cell adhesion, cell-extracellular matrix (matrix) adhesion, and cellular contraction in cleft formation; however, the relative contribution of each of these processes is not fully understood since it is not possible to experimentally manipulate each factor independently. We present here a comprehensive analysis of several cellular parameters regulating cleft progression during branching morphogenesis in the epithelial tissue of an early embryonic salivary gland at a local scale using an on lattice Monte-Carlo simulation model, the Glazier-Graner-Hogeweg model. We utilized measurements from time-lapse images of mouse submandibular gland organ explants to construct a temporally and spatially relevant cell-based 2D model. Our model simulates the effect of cellular proliferation, actomyosin contractility, cell-cell and cell-matrix adhesions on cleft progression, and it was used to test specific hypotheses regarding the function of these parameters in branching morphogenesis. We use innovative features capturing several aspects of cleft morphology and quantitatively analyze clefts formed during functional modification of the cellular parameters. Our simulations predict that a low epithelial mitosis rate and moderate level of actomyosin contractility in the cleft cells promote cleft progression. Raising or lowering levels of contractility and mitosis rate resulted in non-progressive clefts. We also show that lowered cell-cell adhesion in the cleft region and increased cleft cell-matrix adhesions are required for cleft progression. Using a classifier-based analysis, the relative importance of these four contributing cellular factors for effective cleft progression was determined as follows: cleft cell contractility, cleft region cell-cell adhesion strength, epithelial cell mitosis rate, and cell-matrix adhesion strength.

LIM kinase regulation of cytoskeletal dynamics is required for salivary gland branching morphogenesis

LIMK regulation of actin and microtubule dynamics is required for epithelial regulation of early- and late-stage cleft stabilization and progression. LIMK stimulates focal adhesion assembly and integrin β1 activation in cleft regions, causing fibronectin fibrillogenesis and promoting cleft progression during salivary gland branching morphogenesis.

Genetic Modification and Recombination of Salivary Gland Organ Cultures

Branching morphogenesis occurs during the development of many organs, and the embryonic mouse submandibular gland (SMG) is a classical model for the study of branching morphogenesis. In the developing SMG, this process involves iterative steps of epithelial bud and duct formation, to ultimately give rise to a complex branched network of acini and ducts, which serve to produce and modify/transport the saliva, respectively, into the oral cavity. The epithelial-associated basement membrane and aspects of the mesenchymal compartment, including the mesenchyme cells, growth factors and the extracellular matrix, produced by these cells, are critical to the branching mechanism, although how the cellular and molecular events are coordinated remains poorly understood. The study of the molecular mechanisms driving epithelial morphogenesis advances our understanding of developmental mechanisms and provides insight into possible regenerative medicine approaches. Such studies have been hampered due to the lack of effective methods for genetic manipulation of the salivary epithelium. Currently, adenoviral transduction represents the most effective method for targeting epithelial cells in adult glands in vivo. However, in embryonic explants, dense mesenchyme and the basement membrane surrounding the epithelial cells impedes viral access to the epithelial cells. If the mesenchyme is removed, the epithelium can be transfected using adenoviruses, and epithelial rudiments can resume branching morphogenesis in the presence of Matrigel or laminin-111. Mesenchyme-free epithelial rudiment growth also requires additional supplementation with soluble growth factors and does not fully recapitulate branching morphogenesis as it occurs in intact glands. Here we describe a technique which facilitates adenoviral transduction of epithelial cells and culture of the transfected epithelium with associated mesenchyme. Following microdissection of the embryonic SMGs, removal of the mesenchyme, and viral infection of the epithelium with a GFP-containing adenovirus, we show that the epithelium spontaneously recombines with uninfected mesenchyme, recapitulating intact SMG glandular structure and branching morphogenesis. The genetically modified epithelial cell population can be easily monitored using standard fluorescence microscopy methods, if fluorescently-tagged adenoviral constructs are used. The tissue recombination method described here is currently the most effective and accessible method for transfection of epithelial cells with a wild-type or mutant vector within a complex 3D tissue construct that does not require generation of transgenic animals.

Prediction of Growth Factor-Dependent Cleft Formation During Branching Morphogenesis Using A Dynamic Graph-Based Growth Model

This study considers the problem of describing and predicting cleft formation during the early stages of branching morphogenesis in mouse submandibular salivary glands (SMG) under the influence of varied concentrations of epidermal growth factors (EGF). Given a time-lapse video of a growing SMG, first we build a descriptive model that captures the underlying biological process and quantifies the ground truth. Tissue-scale (global) and morphological features related to regions of interest (local features) are used to characterize the biological ground truth. Second, we devise a predictive growth model that simulates EGF-modulated branching morphogenesis using a dynamic graph algorithm, which is driven by biological parameters such as EGF concentration, mitosis rate, and cleft progression rate. Given the initial configuration of the SMG, the evolution of the dynamic graph predicts the cleft formation, while maintaining the local structural characteristics of the SMG. We determined that higher EGF concentrations cause the formation of higher number of buds and comparatively shallow cleft depths. Third, we compared the prediction accuracy of our model to the Glazier-Graner-Hogeweg (GGH) model, an on-lattice Monte-Carlo simulation model, under a specific energy function parameter set that allows new rounds of de novo cleft formation. The results demonstrate that the dynamic graph model yields comparable simulations of gland growth to that of the GGH model with a significantly lower computational complexity. Fourth, we enhanced this model to predict the SMG morphology for an EGF concentration without the assistance of a ground truth time-lapse biological video data; this is a substantial benefit of our model over other similar models that are guided and terminated by information regarding the final SMG morphology. Hence, our model is suitable for testing the impact of different biological parameters involved with the process of branching morphogenesis in silico, while reducing the requirement of in vivo experiments.

Cell-graph modeling of salivary gland morphology

Branching morphogenesis is a developmental process shared by many organs, including the submandibular salivary gland. During morphogenesis, cells within the gland undergo rearrangements to cause changes in the overall tissue morphology. This work presents a methodology based on cell-graphs to quantify these changes in cellular arrangements. Multiple confocal images of developing salivary gland organ cultures are captured. These cultures are immunostained with a nuclear marker and an epithelial marker to identify epithelial cells as separate from mesenchymal cells. Confocal images are stitched and segmented to identify epithelial and mesenchymal nuclei. Cell-graphs are constructed to model the structural organization of epithelial and mesenchymal cells. Cell-graph metrics are calculated to extract mathematical features that discriminate epithelial vs mesenchymal cells organizations and also distinguish between glands treated with pharmacological inhibitors vs vehicle control. The results indicate that cell-graph features can be used to both describe and predict the developing salivary gland to provide insights into cellular and physical processes driving morphogenesis.

A novel dynamic graph-based computational model for predicting salivary gland branching morphogenesis

In this paper, we introduce a biologically motivated dynamic graph-based growth model to describe and predict the stages of cleft formation during the process of branching morphogenesis in the submandibular mouse gland (SMG) from 3 hrs after embryonic day E12 to 8 hrs after embryonic day E12, which can be considered as E12.5. Branching morphogenesis is the process by which many mammalian exocrine and endocrine glands undergo significant morphological transformations, from a primary bud to an adult organ. Although many studies have investigated the cellular and molecular mechanisms driving branching morphogenesis, it is not clear how the shape changes that are inherent to establishing organ structure are produced. Using morphological features extracted from sequential images of SMG organ cultures we were able to develop a dynamic graph-based predictive model that is able to mimic the process of cleft formation and predict the final state. In addition, we compare our model to a state-of-the-art Glazier-Graner-Hogeweg (GGH) simulative tool, and demonstrate that the dynamic graph-based predictive model has comparable accuracy in modeling growth of clefts across SMG developmental stages, as well as faster convergence to the target SMG morphology.

A microRNA signature and TGF-β1 response were identified as the key master regulators for spaceflight response

Translating fundamental biological discoveries from NASA Space Biology program into health risk from space flights has been an ongoing challenge. We propose to use NASA GeneLab database to gain new knowledge on potential systemic responses to space. Unbiased systems biology analysis of transcriptomic data from seven different rodent datasets reveals for the first time the existence of potential “master regulators” coordinating a systemic response to microgravity and/or space radiation with TGF-β1 being the most common regulator. We hypothesized the space environment leads to the release of biomolecules circulating inside the blood stream. Through datamining we identified 13 candidate microRNAs (miRNA) which are common in all studies and directly interact with TGF-β1 that can be potential circulating factors impacting space biology. This study exemplifies the utility of the GeneLab data repository to aid in the process of performing novel hypothesis–based research.

The Viscoelastic Properties of Mouse Embryonic Salivary Glands

Normal organ development, function, and repair are coordinated by interactions between the epithelium and the surrounding stromal cell populations. Cellular function and homeostasis are controlled by an array of chemical and physical cues originating from the cells themselves and from the surrounding extracellular matrix (ECM). Both the endogenous cell population and ECM modulate and rely on the maintenance of basal level of tension within the tissue as a cue for growth and differentiation [1]. Furthermore, the loss of this tensional homeostasis is synonymous with many pathological conditions including; cancer, wound healing, and degenerative diseases [2].© 2013 ASME