Algorithms & Techniques for Studying In Vitro Oral Biofilms

Oral Bioflms;Image Analysis;In Vitro Model System;Confocal Laser Scanning Microscope;Image Thresholding;Dentistry;Public Health;Health Sciences;Epidemiological Science

Luo, TingMarrs, Carl F ;

University of Michigan

关键词: Oral Bioflms;    Image Analysis;    In Vitro Model System;    Confocal Laser Scanning Microscope;    Image Thresholding;    Dentistry;    Public Health;    Health Sciences;    Epidemiological Science;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/145880/tingluo_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Dental caries and periodontal disease affect billions of people annually with a global prevalence estimated at 35% and 11%, respectively. Oral biofilms that develop on tooth surfaces and within gingival crevices are a major risk factor. Disease prevention efforts are focused on controlling the overgrowth of biofilms by removal (e.g., toothbrushing), antimicrobial-containing mouth rinses, and dentifrices. A number of laboratory (in vitro) models of biofilms are used to understand how biofilms develop and their response to mouth rinses and dentifrices.However, there are two major limitations to currently available in vitro biofilm model systems. First, there is no biofilm model system validated for the development of representative dental plaque biofilms. Second, there is no standard approach to analyze biofilm images. Current techniques rely on thresholding algorithms that are not designed for fluorescent images. Combined, these limitations can lead to differences in quantification of biofilm outcomes and thus raise questions regarding the relevance of the model system to the ;;real-world”. This dissertation seeks to bridge the gap between current laboratory techniques and software algorithms and provide investigators additional tools to conduct in vitro oral biofilm studies. First, a distillation of model systems relevant to modern in vitro oral biofilm research is provided. Second, we adapted one of these described model systems, the 24-well BiofluxTM to reproducibly grow multi-species dental biofilms. An objective imaging strategy was further developed to capture all biofilm architectural features. Before analyzing biofilm images, a novel thresholding algorithm, the biovolume elasticity method (BEM), was developed to threshold fluorescent signal. Finally, a software package called Biofilm Architecture Inference Tool (BAIT) was built and evaluated to measure core architectural features of biofilms. In summary, this dissertation describes the modification of a 24-well Bioflux system that facilitates the reproducible development of biofilms. For better visualization and quantification of in vitro biofilms, a novel thresholding algorithm was described. Finally, a software package integrating the BEM thresholding method was developed to measure architectural outcomes. The work presented here represents the outcome of a combinatorial approach to redefine techniques to study oral biofilms, and may also be relevant to the study of biofilms that exist outside the oral cavity.