Khurana Sakshi, Schivo Stefano, Plass Jacqueline R M, Mersinis Nikolas, Scholma Jetse, Kerkhofs Johan, Zhong Leilei, van de Pol Jaco, Langerak Rom, Geris Liesbet, Karperien Marcel, Post Janine N
Technical Medicine Centre, Department of Developmental BioEngineering, University of Twente, Enschede, Netherlands.
Department of Formal Methods and Tools, CTIT Institute, University of Twente, Enschede, Netherlands.
Front Bioeng Biotechnol. 2021 Nov 15;9:732917. doi: 10.3389/fbioe.2021.732917. eCollection 2021.
A fundamental question in cartilage biology is: what determines the switch between permanent cartilage found in the articular joints and transient hypertrophic cartilage that functions as a template for bone? This switch is observed both in a subset of OA patients that develop osteophytes, as well as in cell-based tissue engineering strategies for joint repair. A thorough understanding of the mechanisms regulating cell fate provides opportunities for treatment of cartilage disease and tissue engineering strategies. The objective of this study was to understand the mechanisms that regulate the switch between permanent and transient cartilage using a computational model of chondrocytes, ECHO. To investigate large signaling networks that regulate cell fate decisions, we developed the software tool ANIMO, Analysis of Networks with interactive Modeling. In ANIMO, we generated an activity network integrating 7 signal transduction pathways resulting in a network containing over 50 proteins with 200 interactions. We called this model ECHO, for executable chondrocyte. Previously, we showed that ECHO could be used to characterize mechanisms of cell fate decisions. ECHO was first developed based on a Boolean model of growth plate. Here, we show how the growth plate Boolean model was translated to ANIMO and how we adapted the topology and parameters to generate an articular cartilage model. In ANIMO, many combinations of overactivation/knockout were tested that result in a switch between permanent cartilage (SOX9+) and transient, hypertrophic cartilage (RUNX2+). We used model checking to prioritize combination treatments for wet-lab validation. Three combinatorial treatments were chosen and tested on metatarsals from 1-day old rat pups that were treated for 6 days. We found that a combination of IGF1 with inhibition of ERK1/2 had a positive effect on cartilage formation and growth, whereas activation of DLX5 combined with inhibition of PKA had a negative effect on cartilage formation and growth and resulted in increased cartilage hypertrophy. We show that our model describes cartilage formation, and that model checking can aid in choosing and prioritizing combinatorial treatments that interfere with normal cartilage development. Here we show that combinatorial treatments induce changes in the zonal distribution of cartilage, indication possible switches in cell fate. This indicates that simulations in ECHO aid in describing pathologies in which switches between cell fates are observed, such as OA.
是什么决定了关节中发现的永久性软骨与作为骨模板的短暂性肥大软骨之间的转变?在一部分出现骨赘的骨关节炎(OA)患者以及基于细胞的关节修复组织工程策略中都观察到了这种转变。深入了解调节细胞命运的机制为软骨疾病的治疗和组织工程策略提供了机会。本研究的目的是使用软骨细胞计算模型ECHO来了解调节永久性和短暂性软骨之间转变的机制。为了研究调节细胞命运决定的大型信号网络,我们开发了软件工具ANIMO(交互式建模网络分析)。在ANIMO中,我们生成了一个整合7条信号转导途径的活性网络,得到一个包含50多种蛋白质和200个相互作用的网络。我们将这个模型称为ECHO,即可执行软骨细胞模型。此前,我们表明ECHO可用于表征细胞命运决定的机制。ECHO最初是基于生长板的布尔模型开发的。在此,我们展示了生长板布尔模型是如何转化为ANIMO的,以及我们如何调整拓扑结构和参数以生成关节软骨模型。在ANIMO中,测试了许多过度激活/敲除的组合,这些组合导致了永久性软骨(SOX9+)和短暂性肥大软骨(RUNX2+)之间的转变。我们使用模型检查来对组合治疗进行优先级排序,以便进行湿实验室验证。选择了三种组合治疗方法,并在1日龄大鼠幼崽的跖骨上进行了6天的测试。我们发现IGF1与ERK1/2抑制的组合对软骨形成和生长有积极影响,而DLX5激活与PKA抑制的组合对软骨形成和生长有负面影响,并导致软骨肥大增加。我们表明我们的模型描述了软骨形成,并且模型检查有助于选择和优先考虑干扰正常软骨发育的组合治疗。在此我们表明组合治疗会诱导软骨区域分布的变化,表明细胞命运可能发生转变。这表明ECHO中的模拟有助于描述观察到细胞命运转变的病理情况,如骨关节炎。