Department of Molecular Biology, Semmelweis University, Budapest, Hungary.
Division of Oncology, Department of Internal Medicine and Oncology, Semmelweis University, Budapest, Hungary.
Cell Mol Life Sci. 2024 Feb 19;81(1):97. doi: 10.1007/s00018-024-05112-7.
Recent findings show that single, non-neuronal cells are also able to learn signalling responses developing cellular memory. In cellular learning nodes of signalling networks strengthen their interactions e.g. by the conformational memory of intrinsically disordered proteins, protein translocation, miRNAs, lncRNAs, chromatin memory and signalling cascades. This can be described by a generalized, unicellular Hebbian learning process, where those signalling connections, which participate in learning, become stronger. Here we review those scenarios, where cellular signalling is not only repeated in a few times (when learning occurs), but becomes too frequent, too large, or too complex and overloads the cell. This leads to desensitisation of signalling networks by decoupling signalling components, receptor internalization, and consequent downregulation. These molecular processes are examples of anti-Hebbian learning and 'forgetting' of signalling networks. Stress can be perceived as signalling overload inducing the desensitisation of signalling pathways. Ageing occurs by the summative effects of cumulative stress downregulating signalling. We propose that cellular learning desensitisation, stress and ageing may be placed along the same axis of more and more intensive (prolonged or repeated) signalling. We discuss how cells might discriminate between repeated and unexpected signals, and highlight the Hebbian and anti-Hebbian mechanisms behind the fold-change detection in the NF-κB signalling pathway. We list drug design methods using Hebbian learning (such as chemically-induced proximity) and clinical treatment modalities inducing (cancer, drug allergies) desensitisation or avoiding drug-induced desensitisation. A better discrimination between cellular learning, desensitisation and stress may open novel directions in drug design, e.g. helping to overcome drug resistance.
最近的研究结果表明,单一的非神经元细胞也能够学习信号反应,从而形成细胞记忆。在细胞学习中,信号网络的节点通过固有无序蛋白的构象记忆、蛋白转位、miRNA、lncRNA、染色质记忆和信号级联等方式加强它们的相互作用。这可以用广义的、单细胞的海伯学习过程来描述,即那些参与学习的信号连接变得更强。在这里,我们回顾了那些信号不再只是重复几次(发生学习时),而是变得过于频繁、过于庞大或过于复杂而使细胞过载的情况。这导致信号网络的去敏化,通过分离信号成分、受体内化和随后的下调来实现。这些分子过程是反海伯学习和信号网络“遗忘”的例子。压力可以被视为诱导信号通路脱敏的信号过载。衰老的发生是由于累积的压力导致信号下调的累积效应。我们提出,细胞学习脱敏、压力和衰老可能沿着同一轴线进行,即信号越来越强烈(延长或重复)。我们讨论了细胞如何区分重复和意外的信号,并强调了 NF-κB 信号通路中折叠变化检测背后的海伯和反海伯机制。我们列出了使用海伯学习(如化学诱导接近)的药物设计方法和诱导脱敏(如癌症、药物过敏)或避免药物诱导脱敏的临床治疗方式。更好地区分细胞学习、脱敏和压力可能会为药物设计开辟新的方向,例如帮助克服药物耐药性。