Networks of neurons, networks of genes: an integrated view of memory consolidation

Abstract

Investigations into the mechanisms of memory formation have abided by the central tenet of the consolidation theory-that memory formation occurs in stages which differ in their requirement for protein synthesis. The current most widely accepted hypothesis posits that new memories are encoded as neural activity-induced changes in synaptic efficacy, and stabilization of these changes requires de novo protein synthesis. However, the basic assumptions of this view have been challenged by concerns regarding the specificity of the effects of the protein synthesis inhibitors used to support the claim. Studies on immediate-early genes (IEGs), in particular Arc, provide a distinct and independent perspective on the issue of the requirement of new protein synthesis in synaptic plasticity and memory consolidation. The IEG Arc and its protein are dynamically induced in response to neuronal activity, and are directly involved in synaptic plasticity and memory consolidation. Although we provide extensive data on Arc's properties to address the requirement of genomic and proteomic responses in memory formation, Arc is merely one element in a network of genes that interact in a coordinated fashion to serve memory consolidation. From gene expression and other studies, we propose the view that the stabilization of a memory trace is a continuous and ongoing process, which does not have a discrete endpoint and cannot be reduced to a single deterministic "molecular cascade". Rather, memory traces are maintained within metastable networks, which must integrate and update past traces with new ones. Such an updating process may well recruit and use many of the plasticity mechanisms necessary for the initial encoding of memory.

Figure 1. A dynamic model of the molecular, cellular, and systems interactions involved in the establishment and maintenance of memory

Neuronal activation driven by external inputs (e.g, sensory experience) and intrinsic brain network activity (information of the internal state of the organism) activate second messenger systems in brain neurons which modify the protein-interaction network (“interactome”). These changes occur via rapid post-translational modification (PTM) of pre-existing proteins and through alterations in gene expression (via regulated transcription and translation). Modifications of the protein interactome alter functional properties of neurons within an ensemble to entrain them into a representation encoding a discrete experience. While necessary for initially establishing memory, these initial changes are likely not sufficient for lasting memory. Rather, repeated intrinsic network activity may continue to reinforce a memory trace, using many of the same molecular mechanisms that were required initially. In this model, memories may never become fully “consolidated”, but remain dynamic for as long as they persist.

Figure 2. Robust induction of Arc mRNA expression in hippocampus and neocortex by behavioral experience

Fluorescence in situ hybridization to Arc mRNA in 20 micron brain sections of rats sacrificed directly from the home cage (upper panel; “caged control”) or 25 min after a 5 min exposure to a novel environment (lower panel; “exploration”). Cell nuclei are shown in blue and Arc mRNA is shown in yellow. The left panels show low magnification images (2x objective) of ventral hippocampus and surrounding neocortex, and the right panels show higher magnification images (20x objective) of the CA1 region of hippocampus from the same field. Note the extremely low levels of Arc mRNA in the caged control and the dramatic increase throughout the neocortex and each subregion of the hippocampus.

Figure 3. “Digital” expression of Arc protein in hippocampal neurons

Rats were given 4 sessions (of 5 min each) of training on a rectangular track over a 90 min period, and then sacrificed. Ten minutes before the start of the behavioral procedure, the rats were given an i.p. injection of vehicle (left panels) or the protein synthesis inhibitor anisomycin (right panels; 210 mg / kg). As seen with Arc mRNA (Fig. 2), immunofluorescent detection of Arc protein (green) shows discrete labeling in a subset of the total population of cells (DAPI, here shown in red) in CA1, CA3, and DG regions of the hippocampus of vehicle treated rats (left panels). By contrast, the virtually absent staining in the sections from the anisomycin treated rats (right panels) is even lower than seen in caged controls (not shown), providing further evidence of the short half-life of Arc protein (see also Ramirez-Amaya et al., 2005). The lower grayscale panel is a crop of Arc protein staining for the DG of a vehicle treated rat. Please note the digital nature of Arc protein expression and its punctuate labeling within the dendritic arbors of specific granule cells.

Figure 4. Distinct hippocampal gene expression profiles are associated with distinct stages of learning & memory

(Panel 4.1) Behavioral performance in the spatial water maze task. Different groups of rats were trained in the spatial water maze task, as described in the text. N = 6 rats per group. Panel A: The rats given multiple days of training learned the task well and showed an asymptotic performance achieved by end of day 3. Panel B: The behavioral performance of each group in the last training session before being sacrificed is shown. Note, that the Day 5 reversal rats were required to extinguish their response to the old platform location, in order to locate the new platform location. Accordingly, the behavioral performance of the Day 5 Reversal rats is similar to that of the Day 1 rats. (Panel 4.2) Pattern template matching of microarray expression data reveals gene expression profiles associated with distinct stages of learning. RNA was isolated from the dorsal hippocampi of 6 rats from each behavioral group, and RNA from 3 rats each was used to generate replicate pools for each behavioral condition. Genome-wide gene expression analysis was done using Affymetrix® GeneChip® Rat230_2 arrays for each replicate pool. The Affymetrix PLIER algorithm was used to generate normalized gene expression values. TIGR MeV was used to define a set of ~400 significant genes with an ANOVA value of <0.05 and a fold change of < 1.5 or >1.5 relative to the caged control value. The gene expression profiles shown here were generated using a pattern template matching clustering algorithm. Gene expression levels are normalized to caged controls (CC), and the group labels are listed at the bottom of the panel (CC, D1, D5, and D5R). The data for each replicate chip is shown as a single data point, resulting in the “mountains” (panels B, C, and D) or “valleys” (panels F, G, and H) for genes differentially expressed in only one behavioral condition. Panels A & E show several genes that are induced (A) and repressed (E) in all behavior groups at 30m post-behavior. Panels B–D and F–H show distinct clusters of genes that are regulated only by initial learning (B &F), overtraining (reference memory retrieval; C &G), or reversal learning (reference memory extinction, coincident with new information acquisition; D &H). Notably, although the behavioral performance of D1 and D5R rats were similar, the gene expression profiles are distinct. Additionally, several genes in the D5 30m expression profile are associated with axonal outgrowth and new synapse formation, suggesting that overtraining might recruit additional plasticity mechanisms which play a role in the long-term stability of highly learned information (Reckart et al., 2007). (Panel 4.3) Complex network analysis of gene expression networks regulated by distinct stages of learning & memory. Network of gene expression regulated by behavior in the spatial water maze task at D1 30m (purple square), D1 3h (purple octagon), D5 30m (green square), D5R 30m (green rounded-square). The lines connect behavior groups with the genes (blue circle nodes) that are differentially regulated by that behavior. Red & Green edges indicate up- and down- regulation of gene expression, respectively. Note that the several nodes in the center of the network represent genes that are regulated across multiple stages of learning and memory. This is also demonstrated by the high connectivity of these nodes in the network. Of these “core” genes several common IEGs are indicated as orange circle nodes and Arc is shown as a larger yellow circle node. In contrast, low connectivity genes, represented by blue circles connected to only one behavior group, are regulated only by a single behavior (i.e., in a distinct state of learning and memory). The degree of similarity or difference of the gene expression networks between any two of the behavior groups (stages of learning and memory) can be culled from the number of shared and distinct regulated genes. For example, D1 30m and D5R 30m exclusively share 9 up-regulated and 1 down regulated genes (left side of figure).

Figure 5. Modification of the Plasticity Interactome by IEG Expression

A simplified model of a protein interaction network containing 4 distinct subnetworks (dark blue circles, red squares, green triangles, and aqua rounded-squares). Solid lines between protein nodes represent constitutive interactions and dotted lines represent conditional interactions. Directionality of interactions is noted with arrowheads. Prior to patterned synaptic input, the two IEGs (IEG1 and IEG2, yellow diamonds) are absent and the protein in the red subnetwork is not phosphorylated. Under these basal conditions, the green and blue subnetworks function in isolation, and the red and aqua subnetworks interact. Following patterned synaptic activity, IEGs 1 and 2 are induced and the protein in the red network is phosphorylated (indicated by “PO4”), activating the conditional interactions. With these conditional interactions now active, the dialog between the subnetworks changes dramatically. IEG1 couples the blue and red subnetworks, and IEG2 functions as a dominant negative gene to block the interaction between red and aqua subnetworks. The phosphorylation in the red subnetwork now enables interaction with the green subnetwork. These 3 changes (induction of the two IEGs and the phosphorylation in the red subnetwork) markedly change the behavior of the entire network, with now a directed interaction between blue, red, and green networks, which did not occur in the basal state. Please note the powerful capacity of IEGs to modify the dialog of the plasticity interactome, and by regulation of a relatively limited number of IEGs.