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

• 批准号: BB/F002807/1
• 负责人: Christopher Mitchell
• 金额: $ 37.23万
• 依托单位: University of Ulster
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2008
• 资助国家: 英国
• 起止时间: 2008 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FF002807%2F1
• 关键词: Guidance; cues; pattern; prediction; developing

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).

该项目的目的是使用最新的数学建模（MM）技术与最先进的3-D成像相结合，以发现小鼠视网膜血管丛（RVP）的最终模式如何在正常发育的小鼠和具有严重血管缺陷（VEGF转基因）的小鼠中进行调节;类似于观察到的导致人类婴儿终身失明的情况。随着视网膜的生长，其代谢需求由血管的3D网络支持，该血管网络形成连接其不同层中的小动脉和静脉的毛细血管网络的特征模式。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，这些因子以化学方式（趋化性）吸引细胞向视杯边缘移动。使用共聚焦和2-光子显微镜（允许收集和同化细胞，通路和趋化剂的3-D图像），我们将检查正常和新生小鼠血管畸形的不同发育阶段的视网膜，以发现哪些分子通路和趋化剂在确定RVP的模式和最终成熟中至关重要。这些图像是通过用特定的染料标记细胞（例如，内皮细胞用一种称为BSI-B4的同种凝集素; pericates，用一种针对平滑肌肌动蛋白的探针和具有特异性抗体的通路/趋化剂）来产生的，用激光激发组织，并用共聚焦显微镜捕获荧光染料的光。由于这些研究中收集的所有图像基本上都是RVP生长期间某个特定时间发生的快照，因此必须能够覆盖这些结果并发现细胞如何响应随时间（暂时）产生的途径和趋化剂的潜在表达模式。这就是MM的强大工具可以导致关于如何调节事件组合（在组织，细胞和分子水平）的新发现的地方。第一个提出的MM最初将依赖于在正常和VEGF转基因新生小鼠中进行的研究产生的数据。在收集、数字化和定量一系列参数（即血管长度、分支点、分形维数[在不同尺度下重复基本模式的频率]、细胞类型、位置和分子浓度）后，该信息用于通知MM，以便可以生成RVP的虚拟模型。然后，通过测试其在开发期间的后期阶段预测RVP图案的能力，验证和改进该MM。MM可以预测生物学数据（途径和趋化梯度）中的差距，然后将其用于通过提出新的研究来告知生物学实验，这些研究将进一步阐明RVP 3-D结构开发的细胞和分子机制。这是生物学家和数学家之间的一次独特合作，这两个学科在发现复杂的3D组织RVP如何在正常动物和具有严重眼部病理的动物中生长并有助于眼睛的最终结构方面都具有指导意义。该项目的最后部分将使用MM来预测治疗VEGF转基因小鼠的治疗方法，将防止眼部病理学的进展。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），眼睛如何正常生长以及更具体地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人失明的主要疾病）的基本生物学理解。

项目成果

Quantitation of microcomputed tomography-imaged ocular microvasculature.

微计算机断层扫描成像的眼部微血管系统的定量。

• DOI: 10.1111/j.1549-8719.2009.00009.x
• 发表时间: 2010
• 期刊: 1994)
• 作者: Atwood RC

Dynamics of angiogenesis during murine retinal development: a coupled in vivo and in silico study.

小鼠视网膜发育过程中血管生成的动态：体内和计算机耦合研究。

• DOI: 10.1098/rsif.2012.0067
• 发表时间: 2012
• 期刊: Journal of the Royal Society, Interface
• 作者: Watson MG