Mineral Structure and Composition in Amelogenesis Models

Cooley, Victoria Mae

doi:https://doi.org/10.21985/n2-4jey-6356

Work

Mineral Structure and Composition in Amelogenesis Models

Public

Download PDF

Dental enamel is a complex bio-composite with compositional and structural features across a wide range of length scales. Defects in these features can compromise enamel’s ability to protect the tooth, resulting in adverse health outcomes. Acquired defects like tooth decay are familiar to most people and are the subject of numerous public health campaigns. However, developmental defects can also occur before the tooth has erupted into the mouth, which could require a lifetime of costly treatment. These congenital defects are diverse in their pathology, etiology, and prevalence, such that designing universal diagnosis and treatment protocols is challenging. Much is still not understood about the cellular and molecular mechanisms during enamel formation and how they determine properties of the final mineral; less is known about these mechanisms when they are impacted by genetic mutations or childhood illness. Clinical strategies, therefore, benefit from fundamental research of amelogenesis, the developmental process that gives rise to enamel. This thesis seeks to establish a connection between cellular processes, including those disrupted by genetic mutations, to resulting enamel structure and composition. To achieve this, a multi-scale, comprehensive combination of techniques was used to characterize mineralized dental tissues in genetically modified mouse models and in vitro organoid culture. As an integral part of this effort, a deep learning tool to process large volumes of data, which are necessary to draw conclusions about inherently varying biological systems, was developed. The presentation of topics in this thesis is as follows: First, convolutional neural networks for rapid, automatic labeling of dental tissues in μCT images of amelogenesis models are described. A demonstration of the success and limitations of semantic segmentation follows, along with a proof-of-concept analysis pipeline for extracting quantitative measurements from the labeled datasets. This tool is then used in combination with electron microscopy, vibrational spectroscopy, synchrotron μXRD mapping, histology, and immunofluorescence imaging to characterize two mouse lines modeling disruption of protein self-assembly during amelogenesis. The results indicate that mutations to different regions of protein can result in dramatically different phenotypes characterized by hypoplastic, ectopic, or hypomineralized enamel. Characterization techniques are then further applied to two efforts to expand the genetic and cellular tools available to enamel researchers. The first of these efforts is the development of novel mouse lines that allow for temporal and spatial control over genetic modifications in adult mice. The second is an in vitro model of amelogenesis generated from adult dental epithelial stem cells, which were shown to generate crystallites similar in size and composition to those in dental tissues.

Creator