A Spatial Stochastic Model of AMPAR Trafficking and Subunit Dynamics

In excitatory neurons, the ability of a synaptic connection to strengthen or weaken is known as synaptic plasticity and is thought to be the cellular basis for learning and memory. Understanding the mechanism of synaptic plasticity is an important step towards understanding and developing treatment methods for learning and memory disorders. A key molecular process in synaptic plasticity for mammalian glutamatergic neurons is the exocytosis (delivery to the synapse) of AMPA-type glutamate receptors (AMPARs). While the protein signaling pathways responsible for exocytosis have long been investigated with experimental methods, it remains unreasonable to study the system in its full complexity via only in vitro and in vivo studies. A large number of protein interaction states are observed, creating a system both difficult to monitor and limited in spatiotemporal resolution in an experimental setting. Thus, a computational modeling approach could be employed to help elucidate the underlying protein interaction mechanisms. Here we develop a systematic model to investigate the spatiotemporal patterning of AMPARs. We replicate in silico two distinct mechanisms of AMPAR trafficking related to variation in AMPAR subunit functionality. This model is validated against current knowledge of AMPAR trafficking and used to explore spatial localization of AMPARs to specific synaptic sites, as well as to describe the differences in the spatiotemporal dynamics between the two interacting pathways. These findings help to explain how AMPAR trafficking occurs and can serve as a step towards understanding the role it plays in synaptic plasticity

A Multi-State Model of the CaMKII Dodecamer Suggests a Role for Calmodulin in Maintenance of Autophosphorylation

Ca²⁺/calmodulin-dependent protein kinase II (CaMKII) accounts for up to 2 percent of all brain protein and is essential to memory function. CaMKII activity is known to regulate dynamic shifts in the size and signaling strength of neuronal connections, a process known as synaptic plasticity. Increasingly, computational models are used to explore synaptic plasticity and the mechanisms regulating CaMKII activity. Conventional modeling approaches may exclude biophysical detail due to the impractical number of state combinations that arise when explicitly monitoring the conformational changes, ligand binding, and phosphorylation events that occur on each of the CaMKII holoenzyme’s subunits. To manage the combinatorial explosion without necessitating bias or loss in biological accuracy, we use a specialized syntax in the software MCell to create a rule-based model of a twelve-subunit CaMKII holoenzyme. Here we validate the rule-based model against previous experimental measures of CaMKII activity and investigate molecular mechanisms of CaMKII regulation. Specifically, we explore how Ca²⁺/CaM-binding may both stabilize CaMKII subunit activation and regulate maintenance of CaMKII autophosphorylation. Noting that Ca²⁺/CaM and protein phosphatases bind CaMKII at nearby or overlapping sites, we compare model scenarios in which Ca²⁺/CaM and protein phosphatase do or do not structurally exclude each other’s binding to CaMKII. Our results suggest a functional mechanism for the so-called “CaM trapping” phenomenon, wherein Ca²⁺/CaM may structurally exclude phosphatase binding and thereby prolong CaMKII autophosphorylation. We conclude that structural protection of autophosphorylated CaMKII by Ca²⁺/CaM may be an important mechanism for regulation of synaptic plasticity

New Perspectives on Glacial Geomorphology in Earth's Deep Time Record

International audienceThe deep time (pre-Quaternary) glacial record is an important means to understand the growth, development, and recession of the global cryosphere on very long timescales (10 6-10 8 Myr). Sedimentological description and interpretation of outcrops has traditionally played an important role. Whilst such data remain vital, new insights are now possible thanks to freely accessible aerial and satellite imagery, the widespread availability and affordability of Uncrewed Aerial Vehicles, and accessibility to 3D rendering software. In this paper, we showcase examples of glaciated landscapes from the Cryogenian, Ediacaran, Late Ordovician and Late Carboniferous where this approach is revolutionizing our understanding of deep time glaciation. Although some problems cannot be overcome (erosion or dissolution of the evidence), robust interpretations in terms of the evolving subglacial environment can be made. Citing examples from Australia (Cryogenian), China (Ediacaran), North and South Africa (Late Ordovician, Late Carboniferous), and Namibia (Late Carboniferous), we illustrate how the power of glacial geomorphology can be harnessed to interpret Earth's ancient glacial record

Bird’s-eye view of an Ediacaran subglacial landscape

Depositional evidence for glaciation (dropstones, diamictites) is common in Neoproterozoic strata, and often debated, but erosional evidence (e.g., unconformities cut directly by ice) is rare. Only two such unconformities are known to have been well preserved globally from the Ediacaran Period (in western Australia and central China). This paper provides the first full description of a spectacular subglacial landscape carved beneath ice masses in the Shimengou area of central China, with classical subglacial bed forms including general faceted forms, müschelbruche, cavetto, spindle forms, and striations that testify to an abundance of meltwater during subglacial erosion. These features were produced during the southward, somewhat sinuous, flow of a temperate to polythermal ice mass