Organotypic Culture of Physiologically Functional Adult Mammalian Retinas

BACKGROUND: The adult mammalian retina is an important model in research on the central nervous system. Many experiments require the combined use of genetic manipulation, imaging, and electrophysiological recording, which make it desirable to use an in vitro preparation. Unfortunately, the tissue culture of the adult mammalian retina is difficult, mainly because of the high energy consumption of photoreceptors. METHODS AND FINDINGS: We describe an interphase culture system for adult mammalian retina that allows for the expression of genes delivered to retinal neurons by particle-mediated transfer. The retinas retain their morphology and function for up to six days— long enough for the expression of many genes of interest—so that effects upon responses to light and receptive fields could be measured by patch recording or multielectrode array recording. We show that a variety of genes encoding pre- and post-synaptic marker proteins are localized correctly in ganglion and amacrine cells. CONCLUSIONS: In this system the effects on neuronal function of one or several introduced exogenous genes can be studied within intact neural circuitry of adult mammalian retina. This system is flexible enough to be compatible with genetic manipulation, imaging, cell transfection, pharmacological assay, and electrophysiological recordings

Expression of SPIG1 Reveals Development of a Retinal Ganglion Cell Subtype Projecting to the Medial Terminal Nucleus in the Mouse

Visual information is transmitted to the brain by roughly a dozen distinct types of retinal ganglion cells (RGCs) defined by a characteristic morphology, physiology, and central projections. However, our understanding about how these parallel pathways develop is still in its infancy, because few molecular markers corresponding to individual RGC types are available. Previously, we reported a secretory protein, SPIG1 (clone name; D/Bsp120I #1), preferentially expressed in the dorsal region in the developing chick retina. Here, we generated knock-in mice to visualize SPIG1-expressing cells with green fluorescent protein. We found that the mouse retina is subdivided into two distinct domains for SPIG1 expression and SPIG1 effectively marks a unique subtype of the retinal ganglion cells during the neonatal period. SPIG1-positive RGCs in the dorsotemporal domain project to the dorsal lateral geniculate nucleus (dLGN), superior colliculus, and accessory optic system (AOS). In contrast, in the remaining region, here named the pan-ventronasal domain, SPIG1-positive cells form a regular mosaic and project exclusively to the medial terminal nucleus (MTN) of the AOS that mediates the optokinetic nystagmus as early as P1. Their dendrites costratify with ON cholinergic amacrine strata in the inner plexiform layer as early as P3. These findings suggest that these SPIG1-positive cells are the ON direction selective ganglion cells (DSGCs). Moreover, the MTN-projecting cells in the pan-ventronasal domain are apparently composed of two distinct but interdependent regular mosaics depending on the presence or absence of SPIG1, indicating that they comprise two functionally distinct subtypes of the ON DSGCs. The formation of the regular mosaic appears to be commenced at the end of the prenatal stage and completed through the peak period of the cell death at P6. SPIG1 will thus serve as a useful molecular marker for future studies on the development and function of ON DSGCs

Genetically-Directed, Cell Type-Specific Sparse Labeling for the Analysis of Neuronal Morphology

Background: In mammals, genetically-directed cell labeling technologies have not yet been applied to the morphologic analysis of neurons with very large and complex arbors, an application that requires extremely sparse labeling and that is only rendered practical by limiting the labeled population to one or a few predetermined neuronal subtypes. Methods and Findings: In the present study we have addressed this application by using CreER technology to noninvasively label very small numbers of neurons so that their morphologies can be fully visualized. Four lines of IRES-CreER knock-in mice were constructed to permit labeling selectively in cholinergic or catecholaminergic neurons [choline acetyltransferase (ChAT)-IRES-CreER or tyrosine hydroxylase (TH)-IRES-CreER], predominantly in projection neurons [neurofilament light chain (NFL)-IRES-CreER], or broadly in neurons and some glia [vesicle-associated membrane protein2 (VAMP2)-IRES-CreER]. When crossed to the Z/AP reporter and exposed to 4-hydroxytamoxifen in the early postnatal period, the number of neurons expressing the human placental alkaline phosphatase reporter can be reproducibly lowered to fewer than 50 per brain. Sparse Cre-mediated recombination in ChAT-IRES-CreER;Z/AP mice shows the full axonal and dendritic arbors of individual forebrain cholinergic neurons, the first time that the complete morphologies of these very large neurons have been revealed in any species. Conclusions: Sparse genetically-directed, cell type-specific neuronal labeling with IRES-creER lines should prove useful fo

Non-Centered Spike-Triggered Covariance Analysis Reveals Neurotrophin-3 as a Developmental Regulator of Receptive Field Properties of ON-OFF Retinal Ganglion Cells

The functional separation of ON and OFF pathways, one of the fundamental features of the visual system, starts in the retina. During postnatal development, some retinal ganglion cells (RGCs) whose dendrites arborize in both ON and OFF sublaminae of the inner plexiform layer transform into RGCs with dendrites that monostratify in either the ON or OFF sublamina, acquiring final dendritic morphology in a subtype-dependent manner. Little is known about how the receptive field (RF) properties of ON, OFF, and ON-OFF RGCs mature during this time because of the lack of a reliable and efficient method to classify RGCs into these subtypes. To address this deficiency, we developed an innovative variant of Spike Triggered Covariance (STC) analysis, which we term Spike Triggered Covariance – Non-Centered (STC-NC) analysis. Using a multi-electrode array (MEA), we recorded the responses of a large population of mouse RGCs to a Gaussian white noise stimulus. As expected, the Spike-Triggered Average (STA) fails to identify responses driven by symmetric static nonlinearities such as those that underlie ON-OFF center RGC behavior. The STC-NC technique, in contrast, provides an efficient means to identify ON-OFF responses and quantify their RF center sizes accurately. Using this new tool, we find that RGCs gradually develop sensitivity to focal stimulation after eye opening, that the percentage of ON-OFF center cells decreases with age, and that RF centers of ON and ON-OFF cells become smaller. Importantly, we demonstrate for the first time that neurotrophin-3 (NT-3) regulates the development of physiological properties of ON-OFF center RGCs. Overexpression of NT-3 leads to the precocious maturation of RGC responsiveness and accelerates the developmental decrease of RF center size in ON-OFF cells. In summary, our study introduces STC-NC analysis which successfully identifies subtype RGCs and demonstrates how RF development relates to a neurotrophic driver in the retina

Long-Term Gene Therapy Causes Transgene-Specific Changes in the Morphology of Regenerating Retinal Ganglion Cells

Recombinant adeno-associated viral (rAAV) vectors can be used to introduce neurotrophic genes into injured CNS neurons, promoting survival and axonal regeneration. Gene therapy holds much promise for the treatment of neurotrauma and neurodegenerative diseases; however, neurotrophic factors are known to alter dendritic architecture, and thus we set out to determine whether such transgenes also change the morphology of transduced neurons. We compared changes in dendritic morphology of regenerating adult rat retinal ganglion cells (RGCs) after long-term transduction with rAAV2 encoding: (i) green fluorescent protein (GFP), or (ii) bi-cistronic vectors encoding GFP and ciliary neurotrophic factor (CNTF), brain-derived neurotrophic factor (BDNF) or growth-associated protein-43 (GAP43). To enhance regeneration, rats received an autologous peripheral nerve graft onto the cut optic nerve of each rAAV2 injected eye. After 5–8 months, RGCs with regenerated axons were retrogradely labeled with fluorogold (FG). Live retinal wholemounts were prepared and GFP positive (transduced) or GFP negative (non-transduced) RGCs injected iontophoretically with 2% lucifer yellow. Dendritic morphology was analyzed using Neurolucida software. Significant changes in dendritic architecture were found, in both transduced and non-transduced populations. Multivariate analysis revealed that transgenic BDNF increased dendritic field area whereas GAP43 increased dendritic complexity. CNTF decreased complexity but only in a subset of RGCs. Sholl analysis showed changes in dendritic branching in rAAV2-BDNF-GFP and rAAV2-CNTF-GFP groups and the proportion of FG positive RGCs with aberrant morphology tripled in these groups compared to controls. RGCs in all transgene groups displayed abnormal stratification. Thus in addition to promoting cell survival and axonal regeneration, vector-mediated expression of neurotrophic factors has measurable, gene-specific effects on the morphology of injured adult neurons. Such changes will likely alter the functional properties of neurons and may need to be considered when designing vector-based protocols for the treatment of neurotrauma and neurodegeneration

Using Non-oscillatory Dynamics to Disambiguate Pattern Mixtures

This chapter describes a model which takes advantage of the time domain through feedback iterations that improve recognition and help disambiguate pattern mixtures. This model belongs to a class of models called generative models. It is based on the hypothesis that recognition centers of the brain reconstruct an internal copy of inputs using knowledge the brain has previously accumulated. Subsequently, it minimizes the error between the internal copy and the input from the environment. This model is distinguished from other generative models which are unsupervised and represent early visual processing. This approach utilizes generative reconstruction in a supervised paradigm, implementing later sensory recognition processing. This chapter shows how this paradigm takes advantage of the time domain, provides a convenient way to store recognition information, and avoids some of the difficulties associated with traditional feedforward classification models. To survive animals must interpret mixtures of patterns (scenes) quickly, for example