Paradoxical signaling regulates structural plasticity in dendritic spines

Abstract

<p id="d10497734e203">The basis for learning and memory formation is in tiny <span class="inline-formula"> <math id="i1" overflow="scroll"> <mrow> <mrow> <mo>(</mo> <mrow> <mn>1</mn> <mo>−</mo> <mn>2</mn> </mrow> </mrow> </mrow> </math> </span> μm) membranous protrusions along short branched extensions (dendrites) of nerve cells (neurons) called dendritic spines. Recently, common themes have begun to emerge in identifying the cellular basis of many conditions associated with learning and memory, mainly through the observation of dynamic changes to the dendritic spine. The ability of the dendritic spine to grow, shrink, and change shape has long been associated with synaptic plasticity, learning, and memory. We develop a mathematical model that couples the biochemical signaling machinery and the actin remodeling events to provide insight into the dynamics of the dendritic spine. </p><p class="first" id="d10497734e222">Transient spine enlargement (3- to 5-min timescale) is an important event associated with the structural plasticity of dendritic spines. Many of the molecular mechanisms associated with transient spine enlargement have been identified experimentally. Here, we use a systems biology approach to construct a mathematical model of biochemical signaling and actin-mediated transient spine expansion in response to calcium influx caused by NMDA receptor activation. We have identified that a key feature of this signaling network is the paradoxical signaling loop. Paradoxical components act bifunctionally in signaling networks, and their role is to control both the activation and the inhibition of a desired response function (protein activity or spine volume). Using ordinary differential equation (ODE)-based modeling, we show that the dynamics of different regulators of transient spine expansion, including calmodulin-dependent protein kinase II (CaMKII), RhoA, and Cdc42, and the spine volume can be described using paradoxical signaling loops. Our model is able to capture the experimentally observed dynamics of transient spine volume. Furthermore, we show that actin remodeling events provide a robustness to spine volume dynamics. We also generate experimentally testable predictions about the role of different components and parameters of the network on spine dynamics. </p>