Ud

Figure 5.1. EE exposure drives the expression of NGFI-A and Arc. NGFI-A immunoreactivity was increased in the retinas of EE rats (A), but not in HO or UD controls (C and E, respectively). EE retinas also underwent increases in immunoreactivity for the IEG Arc in both IPL and OPL (B). In contrast, HO and UD animals exhibited significantly reduced Arc immunoreactivity in these layers (D and F, respectively). NGFI-A immunolabeled neurons were distributed evenly throughout the INL and GCL of EE animals. Increased Arc labeling was found in putative dendrites located within the IPL and OPL; those also appeared to be evenly distributed across these layers. GCL, ganglion cell layer; INL, inner nuclear layer; ONL, outer nuclear layer; IPL, inner plexiform layer; OPL, outer plexiform layer. Scale bar = 50|im.

Figure 5.1. EE exposure drives the expression of NGFI-A and Arc. NGFI-A immunoreactivity was increased in the retinas of EE rats (A), but not in HO or UD controls (C and E, respectively). EE retinas also underwent increases in immunoreactivity for the IEG Arc in both IPL and OPL (B). In contrast, HO and UD animals exhibited significantly reduced Arc immunoreactivity in these layers (D and F, respectively). NGFI-A immunolabeled neurons were distributed evenly throughout the INL and GCL of EE animals. Increased Arc labeling was found in putative dendrites located within the IPL and OPL; those also appeared to be evenly distributed across these layers. GCL, ganglion cell layer; INL, inner nuclear layer; ONL, outer nuclear layer; IPL, inner plexiform layer; OPL, outer plexiform layer. Scale bar = 50|im.

that might have influenced visual responses and ultimately increased NGFI-A expression in the GCL of EE animals. Based on data collected from the cerebral cortex, noradrenergic influence is essential for NGFI-A expression (Cirelli et al., 1996; Pinaud et al., 2000). Should a similar situation apply in the retina, it is possible that adrenergic amacrine cells themselves might modulate NGFI-A expression as part of a putative neural plastic response.

Bipolar cells are believed to be the main class of NGFI-A expressing cells in response to the EE setting in the INL (Pinaud et al., 2002b). Should NGFI-A expression indicate sites of enhanced plasticity, it is possible that the complexity of information in the visual environment drives the expression of this activity-dependent gene that can ultimately alter cell structure and, subsequently, function. Although phenotypical changes of bipolar cells could be essential for the optimization of retinal function, a possibility also exits that horizontal and/or amacrine cells might also be undergoing plastic changes. Horizontal cells are believed to be involved in the regulation of information inflow through the OPL and into the second order retinal neurons, the bipolar cells (Dacey, 1999; Kamermans and Spekreijse, 1999; Lukasiewicz, 2005). More specifically, it has been proposed that horizontal cells play an important role in early spatial processing of visual input by developing the characteristic center-surround receptive fields of bipolar neurons. Given that NGFI-A immunoreactivity is localized to the nuclear compartment, it is not possible to differentiate the identity of these cells using strictly immunolabeling targeted at this protein. However, current efforts from our group are being directed at characterizing the neurochemical identity of NGFI-A-positive cells in the retinas of animals exposed to the EE setting. Detailing the cell types that exhibit NGFI-A induction will provide a better understanding of the key players involved in retinal rewiring that putatively occurs in response to exposure of animals to a complex visual environment.

Previous studies have indicated that the majority of amacrine cells use GABA as a neurotransmitter (Wu, 1992; Koulen et al., 1998). GABA's role in the OPL, at least where the terminals of horizontal cells oppose the bipolar cell process within the invaginated synapses of the cone system, may be to alter dynamically the center versus surround area as a means of preferentially funneling sensory information through the most biologically appropriate parts of retinal circuitry. Furthermore, it is possible that the molecular mechanisms that are sensitive to enhanced complexity of the environment were triggered in bipolar cells as a means of correcting for sub-optimal processing capabilities and, possibly, loss of environmental information that could potentially compromise the fidelity of visual information (Pinaud, 2004).

At present, there is currently only limited data concerning candidate plasticity gene expression in the retina of visual species. The great majority of data concerning retinal IEG expression is obtained in either rats or mice. We have, however, recently collected supporting evidence for a role of NGFI-A in the primate retina. More specifically, we have demonstrated that in a species of diurnal monkey, NGFI-A is expressed at high basal levels in undisturbed conditions (Pinaud et al., 2003). This was a surprising result given that UD rodents expressed NGFI-A at relatively low basal levels.

One possible explanation for this difference in basal expression between rodent and primate species is that primates rely more heavily on vision for normal behavior. Such a statement can be substantiated both by behavioral studies and by the proportion of cortex dedicated to visual processing. Thus, we have postulated that the expression of this gene, as well as other molecular machinery involved in retinal plasticity, might be primed in the adult monkey retina (Pinaud et al., 2003). Such mechanism could facilitate change in response to reorganizational pressures in these more visually-dependent animals (Pinaud et al., 2003; Pinaud, 2004).

Arc Expression in the Retina of EE animals

Arc immunoreactivity was enhanced strictly in EE animals for both the OPL and IPL (Pinaud et al., 2001) (Fig. 5.1). As stated above, the mRNA encoded by the IEG arc is rapidly delivered to dendrites upon cell stimulation and, therefore, it has been postulated that Arc protein is involved in activity-

dependent dendritic reconfiguration in the cerebral cortex and hippocampus (Lyford et al., 1995; Steward et al., 1998; Pinaud et al., 2001). We observed a significantly higher Arc expression in the OPL and IPL of EE animals, but not HO and UD controls (Fig. 5.1). These findings are in agreement with the proposed role for the protein encoded by this IEG. In the experiments conducted by us (Pinaud et al., 2001; Pinaud et al., 2002b) the hypothesis is that this protein may be expressed in response to enhanced levels of visual complexity and translated locally in dendrites as part of a process underlying circuitry restructuring (Pinaud et al., 2001). The relay of visual information in the OPL depends primarily upon synapses between photoreceptors and bipolar cells. It is possible that the exposure of animals to an EE increased the absolute number of transduced visual events, or some other measure of visual activity such that altered cell structure was required. Furthermore, it is plausible that this structural reorganization could involve a rearrangement of the synaptic contacts between photoreceptors, bipolar cells, and horizontal cells.

Increased Arc immunoreactivity was also observed in the IPL, the retinal layer that primarily primarily contains connections between bipolar and ganglion cells (Fig. 5.1). Although the encoding of information across different retinal layers is dissimilar, it is possible that a similar need for reorganizational plasticity, possibly involving the same molecular players, would be found in both IPL and OPL. This possibility, however, remains to be experimentally tested.

GAP-43 and Synapsin I Upregulation in the Retina

GAP-43 and Synapsin I expression were used by us, in the same set of experiments, to confirm enhanced plasticity in the retina, in response to EE exposure (Pinaud et al., 2002b). The expression of both of these late response genes (LGs) has been repeatedly used as reliable markers for plasticity in the CNS. For example, optic nerve transection induces these LGs in the lateral geniculate nucleus (Baekelandt et al., 1994). In addition, several studies have demonstrated the upregulation of these LGs in the cortex after alterations in sensory drive and, more recently, after LTP induction in the hippocampus (Levin and Dunn-Meynell, 1993; Schauwecker et al., 1995; Bendotti et al., 1997; Sato et al., 2000; Suemaru et al., 2000). As previously described by other authors, basal levels of Synapsin I and GAP-43 were observed in the IPL of both HO and UD animals (Haas et al., 1990; Mandell et al., 1990; Mcintosh and Blazynski, 1991; Mandell et al., 1992; Reh et al., 1993; LopezCosta et al., 2001). However, a modest but significant increase in Synapsin I and GAP-43 immunoreactivity was observed in the IPL of EE animals (Fig. 5.2). The most robust difference in the expression levels of these genes was, however, in the OPL, where HO and UD animals exhibited minimal GAP-43 and Synapsin I, while EE animals underwent a marked upregulation of the protein products of these LGs (Fig. 5.2).

Figure 5.2. GAP-43 and Synapsin I are differentially expressed in EE retinas, as compared to HO and UD retinas. In EE retinas, GAP-43 labeling of beaded dendrites could be detected in the OPL (A), but was not detected in HO and UD retinas (C and E, respectively). A significant increase was also detected for Synapsin I immunolabel-ing in the OPL of EE animals (B). In HO and UD retinas, the OPL was unlabeled for GAP-43 (C and E, respectively) and Synapsin I (D and F, respectively). Strong bands of GAP-43 immunoreactive puncta were visible in the IPL of all experimental groups, with significantly higher intensity in EE animals (A, C and E). Synapsin I immunola-beling in the IPL was also prominent in all animal groups, with higher density in EE animals (B) when compared to HO and UD controls (D and F, respectively). OPL, outer plexiform layer; INL, inner nuclear layer; IPL, inner plexiform layer; GCL ganglion cell layer. Scale bar = 50|im.

Figure 5.2. GAP-43 and Synapsin I are differentially expressed in EE retinas, as compared to HO and UD retinas. In EE retinas, GAP-43 labeling of beaded dendrites could be detected in the OPL (A), but was not detected in HO and UD retinas (C and E, respectively). A significant increase was also detected for Synapsin I immunolabel-ing in the OPL of EE animals (B). In HO and UD retinas, the OPL was unlabeled for GAP-43 (C and E, respectively) and Synapsin I (D and F, respectively). Strong bands of GAP-43 immunoreactive puncta were visible in the IPL of all experimental groups, with significantly higher intensity in EE animals (A, C and E). Synapsin I immunola-beling in the IPL was also prominent in all animal groups, with higher density in EE animals (B) when compared to HO and UD controls (D and F, respectively). OPL, outer plexiform layer; INL, inner nuclear layer; IPL, inner plexiform layer; GCL ganglion cell layer. Scale bar = 50|im.

The proteins encoded by LGs have been postulated to underlie more stable physical changes that ultimately alter function in CNS structures (Baekelandt et al., 1994; Han and Greengard, 1994; Melloni et al., 1994; Baekelandt et al., 1996; Yang et al., 1998; Aarts et al., 1999; Hilfiker et al., 1999). The upregu-lation of both classic plasticity markers discussed in this review lend further support to the hypothesis that retinal circuitry was altered in response to exposure to an EE setting.

Experience-Dependent Gene Expression Properties and Time Courses

The modifications in the expression levels for both IEGs and LGs detailed above were observed in the last experimental session (21st day), after the last exposure to the EE. As detailed above, we observed dramatic changes in the expression levels of NGFI-A, Arc, Synapsin I and GAP-43 in the retinas of animals exposed to this EE experience regimen for 1 hour per day. More recently, we have investigated in more detail the alterations in gene expression that result from EE exposure. In this new set of experiments, we investigated IEG and LG expression in animals that were exposed to the EE for 1 hour during 1 day, 2 days, 5 days, 1 week, 2 weeks, 3 weeks and animals that were exposed to the EE for 3 weeks and remained undisturbed for an additional month. All of these animals were sacrificed immediately after exposure to EE, however, in each timepoint, we also included animals that were sacrificed immediately prior to EE exposure. This experiment shed light into very important expression properties of these genes. We found, as expected, that both IEGs were rapidly and transiently induced in response to EE exposure. Both NGFI-A and Arc were induced by a single exposure to the EE. Interestingly, by the beginning of the subsequent session (day 2), the expression levels of both genes had returned to basal levels. These findings are not surprising taking into consideration the fact that the protein products of IEGs often exhibit a very short half-life (in a scale of minutes) (Hughes and Dragunow, 1995; Herdegen and Leah, 1998). However, exposure of animals to a second session (day 2) in the EE triggered a new wave of IEG expression in the retina. Irrespective of the number of exposures, expression of our genes of interest followed the same pattern as the one described previously in the original report (Pinaud et al., 2002b). Thus, daily 1 hour exposures of animals to the EE setting lead to daily upregulation of IEGs, followed by return to basal levels within a few hours after return of animals to lab home cages (Fig. 5.3).

Possibly the most interesting finding of this time-course study was revealed when investigating the expression profiles of the LGs GAP-43 and Synapsin I. We found that no alterations were found in the expression levels of these genes until the 5th session. After that point, a steady increase in the protein products for these LGs persisted until the 3rd week. Unlike IEG expression, LG expression was high prior to re-exposure of animals to the EE, suggesting that their protein expression is more long-lasting and stable than that of IEGs. Interestingly, animals that were studied a month after the last EE exposure still exhibited high LG expression (Fig. 5.3). Together, these findings suggest that although LG induction requires repeated exposures to the enriched visual environment, the modifications associated with these proteins are stable up until one month after the last session.

Immediate Early Genes as Detectors of Biological Repetition and Relevance?

It is clear for decades now that enhanced complexity of the sensory environment leads to reorganization of CNS circuitry (Rosenzweig et al., 1972; Volkmar and Greenough, 1972; Globus et al., 1973; van Praag et al., 2000). Although the most compelling evidence that support this claim has been col-

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