An automated image analysis tool for quantitative studies of dynamic 3D-wound healing assays

用于动态 3D 伤口愈合测定定量研究的自动图像分析工具

• 批准号: 317276344
• 负责人: Dr. Sabrina Roßberger
• 金额: --
• 依托单位: Forschungsgruppe Biophysikalische Chemie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2016
• 资助国家: 德国
• 起止时间: 2015-12-31 至 2016-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/317276344?language=en
• 关键词: automated; image; analysis; tool; quantitative

An effective and fast wound healing process is essential for preserving the integrity of the skin and thus crucial for a functioning organism. Causes of skin damage are various including external physical force, surgery or diseases. Lately, 3-dimensional (3D) wound healing models have been successfully established. These are capable of revealing the complex interplay of different cell types during wound healing processes. However, visualization and analysis have only been performed on histological sections, which reveal only limited insights into the underlying dynamics.I will establish a 3D-in-vitro optical microscopy technique and a novel visualization workflow based on live-cell imaging and automated analysis routines to analyze the dynamic behavior of a whole in-vitro 3D-skin model. We will implement a recently for biological applications rediscovered imaging method - light sheet fluorescence microscopy (LSFM) - for time-lapse imaging. Thus, for the first time the fundamental underlying mechanism and dynamic aspects of wound healing demonstrated on an in-vitro 3D-skin model will be elucidated. Current 3D-tissue studies are lacking a common software tool for automated and comprehensive analysis of time resolved image data. Based on the expertise in our research group and of our collaboration partners we propose a software tool for automated and unbiased image analysis on a single cell level for whole in-vitro 3D-skin models and wound healing assays. Moreover, the developed algorithms are not limited to skin but can be easily adapted and applied to other tissue engineering experiments.Exploring the 3D-skin model the algorithm will allow for characterizing the healthy state of the skin in an unbiased manner based on well-defined extracted biophysical features. These features will be tracked over time and thus allow quantification of changes during the highly dynamical process of wound healing. Finally, we will establish the developed algorithms as an automated and unbiased benchmarking tool for high throughput screening (HTS) assays for testing the performance of various wound healing mediators and wound covers in in-vitro experiments.The proposed interdisciplinary project combines both biophysical studies on wound healing experiments and bioinformatics in order to develop a sophisticated and user-friendly bioinformatics tool for experimentalists.

有效和快速的伤口愈合过程对于保持皮肤的完整性至关重要，因此对于功能正常的生物体至关重要。皮肤损伤的原因是多种多样的，包括外部物理力量，手术或疾病。近年来，三维（3D）伤口愈合模型已成功建立。这些能够揭示伤口愈合过程中不同细胞类型的复杂相互作用。然而，可视化和分析只进行了组织切片，这揭示了只有有限的见解到潜在的dynamics.I将建立一个三维体外光学显微镜技术和一个新的可视化工作流程的基础上活细胞成像和自动分析例程来分析整个体外三维皮肤模型的动态行为。我们将实施一个最近的生物应用重新发现的成像方法-光片荧光显微镜（LSFM）-延时成像。因此，第一次在体外三维皮肤模型上展示的伤口愈合的基本机制和动态方面将得到阐明。目前的3D组织研究缺乏一个通用的软件工具，自动和全面的分析时间分辨图像数据。基于我们的研究团队和合作伙伴的专业知识，我们提出了一种软件工具，用于在单细胞水平上对整个体外3D皮肤模型和伤口愈合试验进行自动化和无偏见的图像分析。此外，开发的算法不仅限于皮肤，但可以很容易地适应和应用到其他组织工程experiments.Exploring的3D皮肤模型的算法将允许表征皮肤的健康状态，在一个公正的方式基于定义良好的提取的生物物理特征。这些特征将随时间进行跟踪，从而允许在伤口愈合的高度动态过程中量化变化。最后，我们将建立开发的算法作为一个自动化和公正的基准工具，高通量筛选（HTS）检测各种伤口愈合介质和伤口覆盖物的性能在体外experiments.The拟议的跨学科项目结合伤口愈合实验和生物信息学的生物物理研究，以开发一个复杂的和用户友好的生物信息学工具的实验。