MOSAIC: a multiscale model of osteogenesis and sprouting angiogenesis with lateral inhibition of endothelial cells.
MOSAIC: a multiscale model of osteogenesis and sprouting angiogenesis with lateral inhibition of endothelial cells.
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DOI：
10.1371/journal.pcbi.1002724
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发表时间：
2012
影响因子：
4.3
通讯作者：
Van Oosterwyck H
中科院分区：
文献类型：
--
作者：
Carlier A;Geris L;Bentley K;Carmeliet G;Carmeliet P;Van Oosterwyck H
骨折的愈合在很大程度上取决于骨痂中新血管网络(血管生成)的发展。在血管生成过程中，TIP细胞响应细胞外信号而引导发芽发育，其中血管内皮生长因子(VEGF)起着至关重要的作用。为了确保维管系统的正确发育，必须严格控制茎和顶端细胞表型之间的平衡，这主要是通过Dll4-Notch1信号通路实现的。本研究提出了一种新的多尺度成骨和萌发血管生成模型，通过DLL4-Notch1信号对血管内皮细胞的侧向抑制(进一步表示为马赛克模型)，并将其应用于骨折愈合。马赛克模型正确地预测了骨再生过程，并概括了实验观察到的TIP细胞选择的许多方面：细胞命运的盐和胡椒模式，由于DLL4丢失而导致的TIP细胞密度增加，以及在高血管内皮生长因子环境中TIP细胞的过量数量。当进一步增加血管内皮生长因子浓度时，马赛克模型预测缺乏血管网络和骨折愈合，从而导致骨不连，这是相邻细胞通过DLL4-Notch1信号相互抑制的直接结果。这一结果不适用于只考虑TIP细胞迁移的细胞外信号的现象学模型，这说明了实施实际信号通路而不是现象学规则的重要性。最后，马赛克模型证明了选择TIP细胞的适当标准的重要性，以及进一步探索这一点的实验数据的必要性。综上所述，这项研究表明，马赛克模型增强了以更机械的方式跨不同时间和空间尺度研究分子机制对血管生成的影响及其与骨形成的关系的能力。骨折的愈合在很大程度上取决于一种新的血管网络(血管生成)的发展，这可以用数学模型来研究和模拟。然而，目前的骨折愈合过程中血管生成的数学模型并没有严格地在多尺度框架内实现所有相关的生物尺度(例如，组织、细胞和细胞内水平)。这项研究建立了一个新的骨折愈合过程中血管生成的多尺度平台(称为马赛克)，使我们能够跨不同的生物尺度研究几个影响因素的相互作用。我们重点研究了TIP细胞选择的生物学过程，在这个过程中，血管中的一个特定细胞，即TIP细胞，被选择来从原始血管中迁移出来，并领导新的分支。在证明马赛克模型能够正确地预测骨再生过程以及实验观察到的尖端细胞选择的许多方面之后，我们使用该模型来研究刺激信号对血管系统发育和愈合进程的影响。这些结果提出了一个关于TIP细胞选择标准的重要生物学问题。这项研究展示了多尺度建模有助于理解血管生成等生物过程的潜力。
The healing of a fracture depends largely on the development of a new blood vessel network (angiogenesis) in the callus. During angiogenesis tip cells lead the developing sprout in response to extracellular signals, amongst which vascular endothelial growth factor (VEGF) is critical. In order to ensure a correct development of the vasculature, the balance between stalk and tip cell phenotypes must be tightly controlled, which is primarily achieved by the Dll4-Notch1 signaling pathway. This study presents a novel multiscale model of osteogenesis and sprouting angiogenesis, incorporating lateral inhibition of endothelial cells (further denoted MOSAIC model) through Dll4-Notch1 signaling, and applies it to fracture healing. The MOSAIC model correctly predicted the bone regeneration process and recapitulated many experimentally observed aspects of tip cell selection: the salt and pepper pattern seen for cell fates, an increased tip cell density due to the loss of Dll4 and an excessive number of tip cells in high VEGF environments. When VEGF concentration was even further increased, the MOSAIC model predicted the absence of a vascular network and fracture healing, thereby leading to a non-union, which is a direct consequence of the mutual inhibition of neighboring cells through Dll4-Notch1 signaling. This result was not retrieved for a more phenomenological model that only considers extracellular signals for tip cell migration, which illustrates the importance of implementing the actual signaling pathway rather than phenomenological rules. Finally, the MOSAIC model demonstrated the importance of a proper criterion for tip cell selection and the need for experimental data to further explore this. In conclusion, this study demonstrates that the MOSAIC model creates enhanced capabilities for investigating the influence of molecular mechanisms on angiogenesis and its relation to bone formation in a more mechanistic way and across different time and spatial scales. The healing of a fracture largely depends on the development of a new blood vessel network (angiogenesis), which can be investigated and simulated with mathematical models. The current mathematical models of angiogenesis during fracture healing do not, however, implement all relevant biological scales (e.g. a tissue, cellular and intracellular level) rigorously in a multiscale framework. This study established a novel multiscale platform of angiogenesis during fracture healing (called MOSAIC) which allowed us to investigate the interactions of several influential factors across the different biological scales. We focused on the biological process of tip cell selection, during which a specific cell of a blood vessel, the “tip cell”, is selected to migrate away from the original vessel and lead the new branch. After showing that the MOSAIC model is able to correctly predict the bone regeneration process as well as many experimentally observed aspects of tip cell selection, we have used the model to investigate the influence of stimulating signals on the development of the vasculature and the progression of healing. These results raised an important biological question concerning the criterion for tip cell selection. This study demonstrates the potential of multiscale modeling to contribute to the understanding of biological processes like angiogenesis.
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影响因子：
4.6
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