Güven Emine, Wester Michael J, Edwards Jeremy S, Halász Ádám M
Department of Biomedical Engineering, Düzce University, Düzce, Turkey.
Department of Mathematics and Statistics, University of New Mexico, Albuquerque, NM, USA.
Bioinform Biol Insights. 2022 Mar 25;16:11779322221085078. doi: 10.1177/11779322221085078. eCollection 2022.
We previously developed a method of defining receptor clusters in the membrane based on mutual distance and applied it to a set of transmission microscopy images of vascular endothelial growth factor receptors. An optimal length parameter was identified, resulting in cluster identification and a procedure that assigned a geometric shape to each cluster. We showed that the observed particle distribution results were consistent with the random placement of receptors within the clusters and, to a lesser extent, the random placement of the clusters on the cell membrane. Here, we develop and validate a stochastic model of clustering, based on a hypothesis of preexisting domains that have a high affinity for receptors. The proximate objective is to clarify the mechanism behind cluster formation and to estimate the effect on signaling. Receptor-enriched domains may significantly impact signaling pathways that rely on ligand-induced dimerization of receptors. We define a simple statistical model, based on the preexisting domain hypothesis, to predict the probability distribution of cluster sizes. The process yielded sets of parameter values that can readily be used in dynamical calculations as the estimates of the quantitative characteristics of the clustering domains.
我们之前开发了一种基于相互距离来定义膜中受体簇的方法，并将其应用于一组血管内皮生长因子受体的透射显微镜图像。确定了一个最佳长度参数，从而实现了簇的识别以及为每个簇赋予几何形状的程序。我们表明，观察到的粒子分布结果与受体在簇内的随机分布一致，并且在较小程度上与簇在细胞膜上的随机分布一致。在此，我们基于对受体具有高亲和力的预先存在结构域的假设，开发并验证了一种簇形成的随机模型。近期目标是阐明簇形成背后的机制，并估计其对信号传导的影响。富含受体的结构域可能会显著影响依赖配体诱导受体二聚化的信号通路。我们基于预先存在结构域假设定义了一个简单的统计模型，以预测簇大小的概率分布。该过程产生了可轻易用于动力学计算的参数值集，作为簇结构域定量特征的估计值。
