PDF(Pubmed)
Abstract：
BACKGROUND: The postsynaptic density is an elaborate protein network beneath the postsynaptic membrane involved in the molecular processes underlying learning and memory. The postsynaptic density is built up from the same major proteins but its exact composition and organization differs between synapses. Mutations perturbing protein: protein interactions generally occurring in this network might lead to effects specific for cell types or processes, the understanding of which can be especially challenging.
RESULTS: In this work we use systems biology-based modeling of protein complex distributions in a simplified set of major postsynaptic proteins to investigate the effect of a hypomorphic Shank mutation perturbing a single well-defined interaction. We use data sets with widely variable abundances of the constituent proteins. Our results suggest that the effect of the mutation is heavily dependent on the overall availability of all the protein components of the whole network and no trivial correspondence between the expression level of the directly affected proteins and overall complex distribution can be observed.
CONCLUSIONS: Our results stress the importance of context-dependent interpretation of mutations. Even the weakening of a generally occurring protein: protein interaction might have well-defined effects, and these can not easily be predicted based only on the abundance of the proteins directly affected. Our results provide insight on how cell-specific effects can be exerted by a mutation perturbing a generally occurring interaction even when the wider interaction network is largely similar.
RESULTS: In this work we use systems biology-based modeling of protein complex distributions in a simplified set of major postsynaptic proteins to investigate the effect of a hypomorphic Shank mutation perturbing a single well-defined interaction. We use data sets with widely variable abundances of the constituent proteins. Our results suggest that the effect of the mutation is heavily dependent on the overall availability of all the protein components of the whole network and no trivial correspondence between the expression level of the directly affected proteins and overall complex distribution can be observed.
CONCLUSIONS: Our results stress the importance of context-dependent interpretation of mutations. Even the weakening of a generally occurring protein: protein interaction might have well-defined effects, and these can not easily be predicted based only on the abundance of the proteins directly affected. Our results provide insight on how cell-specific effects can be exerted by a mutation perturbing a generally occurring interaction even when the wider interaction network is largely similar.
摘要：
背景：突触后密度是突触后膜下一个复杂的蛋白质网络，参与学习和记忆的分子过程。突触后密度由相同的主要蛋白质建立，但其确切的组成和组织在突触之间有所不同。突变干扰蛋白质：通常发生在该网络中的蛋白质相互作用可能导致特定于细胞类型或过程的效应，对其的理解可能特别具有挑战性。
结果：在这项工作中，我们在一组简化的主要突触后蛋白中使用基于系统生物学的蛋白质复合物分布建模来研究低态Shank突变扰乱单个明确定义的相互作用的影响。我们使用具有组成蛋白质的广泛可变丰度的数据集。我们的结果表明，突变的影响在很大程度上取决于整个网络的所有蛋白质成分的总体可用性，并且可以观察到直接受影响的蛋白质的表达水平与总体复合物分布之间的微小对应关系。
结论：我们的结果强调了对突变的语境依赖性解释的重要性。即使是通常发生的蛋白质的弱化：蛋白质相互作用也可能具有明确的影响，仅根据直接受影响的蛋白质的丰度，这些是不容易预测的。我们的结果提供了有关如何通过突变干扰通常发生的相互作用来发挥细胞特异性效应的见解，即使更广泛的相互作用网络在很大程度上相似。
结果：在这项工作中，我们在一组简化的主要突触后蛋白中使用基于系统生物学的蛋白质复合物分布建模来研究低态Shank突变扰乱单个明确定义的相互作用的影响。我们使用具有组成蛋白质的广泛可变丰度的数据集。我们的结果表明，突变的影响在很大程度上取决于整个网络的所有蛋白质成分的总体可用性，并且可以观察到直接受影响的蛋白质的表达水平与总体复合物分布之间的微小对应关系。
结论：我们的结果强调了对突变的语境依赖性解释的重要性。即使是通常发生的蛋白质的弱化：蛋白质相互作用也可能具有明确的影响，仅根据直接受影响的蛋白质的丰度，这些是不容易预测的。我们的结果提供了有关如何通过突变干扰通常发生的相互作用来发挥细胞特异性效应的见解，即使更广泛的相互作用网络在很大程度上相似。
