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Guidance cues and pattern prediction in the developing retinal vasculature: A combined experimental and theoretical modelling approach

视网膜脉管系统发育中的指导线索和模式预测：实验和理论相结合的建模方法

基本信息

批准号：
BB/F002785/1
负责人：
S McDougall
金额：
$ 16.33万
依托单位：
Heriot-Watt University
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2010
资助国家：
英国
起止时间：
2010 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=BB%2FF002785%2F1
关键词：
Guidance cues pattern prediction developing

项目摘要

Summary The aim of this project is to use the latest mathematical modelling (MM) techniques coupled with state-of-the-art 3-D imaging to discover how the final patterning of the mouse retinal vasculature plexus (RVP) is regulated in both normally developing mice and mice with severe vascular defects (VEGF-transgenics); similar to those observed to cause a lifetime of blindness in human babies . As the retina grows, its metabolic needs are supported by a 3-D network of blood vessels that form a characteristic pattern of capillary networks linking the arterioles and veins in its different layers. The final structure of the RVP is determined by molecular pathways in the tissue, on which the endothelial cells (the main cell forming the blood vessels) and pericytes (cells which give structural/functional stability to the vessels) migrate. The direction of migration of these cells is dependent on the concentration gradients of both soluble and matrix-associated factors which chemically (chemotaxis) attract the cells towards the rim of the optic cup. Using confocal and 2-photon microscopy (allowing the collection and assimilation of 3-D images of cells, pathways and chemotactic agents) we will examine the retina from different developmental stages of normal and neonatal mice with vascular malformations to discover which molecular pathways and chemotactic agents are critical in determining the patterning and final maturation of the RVP. The images are generated by labelling cells with specific dyes (for instance endothelium with an isolectin called BSI-B4; perictes, with a probe against smooth muscle actin and pathways/chemotactic agents with specific antibodies) exciting the tissue with a laser and capturing the light from the fluorescing dyes with a confocal microscope. As all the images collected in these studies are essentially snapshots of what happens at one particular time during the growth of the RVP, it is essential to be able to overlay these results and discover how the cells respond to the underlying expression patterns of the pathways and chemotactic agents being produced over time (temporally). This is where the powerful tool of MM can lead to new discoveries about how the combination of events (at the tissue, cell and molecular level) are regulated. The first proposed MM will initially rely on data generated from studies performed in normal and VEGF-transgenic neonatal mice. After collecting, digitising and quantitating a series of parameters (i.e. vessel lengths, branch-points, fractal dimension [how often a basic pattern is repeated at different scales], cell-type, location and concentration of molecules) this information is used to inform the MM, so that a virtual model of the RVP can be generated. This MM is then verified and improved, by testing its ability to predict the RVP patterning at later stages during development. Gaps in the biological data (in both the pathways and the chemotactic gradients) can be anticipated by the MM that will then be used to inform biological experiments by proposing new studies which will further elucidate the cellular and molecular mechanisms underlying the development of the 3-D structure of the RVP. This is a unique collaboration between biologists and mathematicians, in which both disciplines are instructive in discovering how a complex 3-D tissue, the RVP, grows and contributes to the final structure of the eye in both normal animals and animals with a serious ocular pathology. The final portion of the project will employ the MM to predict which therapeutic approaches to treat the VEGF-transgenic mice, will prevent progression of ocular pathology. This research will benefit basic biological understanding of how blood vessels grow in 3-D (which determines the growth of all organs), how the eye grows normally and more specifically in ocular conditions characterised by inapprpriate blood vessel formation (all major diseases that cause blindness in neonates and adults).

这个项目的目的是使用最新的数学建模(MM)技术结合最先进的3-D成像来发现小鼠视网膜血管丛(RVP)的最终图案是如何在正常发育的小鼠和患有严重血管缺陷的小鼠(血管内皮生长因子转基因)中调节的；类似于观察到的导致人类婴儿终身失明的那些。随着视网膜的生长，它的新陈代谢需要得到一个3D血管网络的支持，这个网络形成了一个独特的毛细血管网络模式，将不同层的小动脉和静脉连接起来。RVP的最终结构由组织中的分子途径决定，内皮细胞(形成血管的主要细胞)和周细胞(为血管提供结构/功能稳定性的细胞)在其上迁移。这些细胞的迁移方向取决于可溶性和基质相关因子的浓度梯度，这些因子在化学上(趋化性)将细胞吸引到视杯边缘。使用共聚焦和双光子显微镜(允许收集和同化细胞、通路和化学趋向剂的3D图像)，我们将检查正常和新生血管畸形小鼠的不同发育阶段的视网膜，以发现哪些分子通路和化学趋向剂在决定RVP的模式和最终成熟方面至关重要。这些图像是通过用特定的染料标记细胞(例如，用名为BSI-B4的异凝素标记内皮；用针对平滑肌肌动蛋白的探针和带有特定抗体的通路/化学趋化剂)标记细胞来产生的，并用激光激发组织，并用共聚焦显微镜捕捉荧光染料的光。由于在这些研究中收集的所有图像基本上都是RVP生长过程中某个特定时间发生的快照，因此能够覆盖这些结果并发现细胞如何对随时间(时间)产生的通路和化学趋化剂的潜在表达模式做出反应是至关重要的。这就是MM这个强大的工具可以导致关于如何(在组织、细胞和分子水平上)调节事件组合的新发现。第一个提出的MM最初将依赖于在正常和血管内皮生长因子转基因新生小鼠中进行的研究产生的数据。在收集、数字化和量化一系列参数(即血管长度、分支点、分维[基本模式在不同尺度上重复的频率]、细胞类型、分子的位置和浓度)之后，这些信息被用来通知MM，从而可以生成RVP的虚拟模型。然后，通过测试其在开发过程中的后期阶段预测RVP图案的能力来验证和改进该MM。MM可以预见生物学数据中的差距(在通路和趋化梯度中)，然后将利用这些差距通过提出新的研究来为生物实验提供信息，这些研究将进一步阐明RVP三维结构发展的细胞和分子机制。这是生物学家和数学家之间的一次独特的合作，在这两个学科中，这两个学科都对发现复杂的3D组织RVP是如何生长并对眼睛的最终结构做出贡献的，无论是正常动物还是患有严重眼病的动物都是有指导意义的。该项目的最后部分将使用MM来预测哪些治疗方法可以治疗血管内皮生长因子转基因小鼠，以防止眼部病理的进展。这项研究将有助于对血管如何在3D中生长(决定所有器官的生长)的基本生物学理解，以及眼睛如何正常生长，更具体地说，在以不适当的血管形成为特征的眼部条件下(所有导致新生儿和成年人失明的主要疾病)。