Retinal degeneration and remodelling in experimental glaucoma

Glaucoma is an optic neuropathy characterised by the loss of retinal ganglion cells (RGC). Dendritic atrophy occurs early in the disease, prior to soma and axonal degeneration. RGCs exhibit reduced branching density and dendritic field size. This thesis seeks to further characterise dendritic atrophy in glaucoma in the context of two external factors that may contribute to the disease pathology – immune system effects mediated via complement and the influence of the perineuronal net (PNN), a specialised extracellular matrix that surrounds RGCs. RGC morphology was investigated in a rat bead model of experimental glaucoma using ballistic labelling techniques; morphological changes were related to synaptic loss and PNN composition using immunohistochemistry. A model was derived for the classification of diseased RGCs in order to prevent labelling bias in subsequent investigations. The immune system was modulated using a complement inhibitor (using a transgenic mouse and pharmacological agent in rats) and PNNs disrupted using the bacterial enzyme Chondroitinase ABC. Experimental glaucoma caused significant dendritic loss, with partial protection conferred by both complement inhibition and PNN digestion. Analysis of retinal sections also revealed partial protection of synapses. PNNs did not show any changes in their composition in the rat in experimental glaucoma but human glaucoma eyes showed increased glycosaminoglycan sulphation in the RGC layer which was correlated with visual deficit. Manipulation of the RGC external environment therefore proved successful in protecting from dendritic atrophy

Microbead models in glaucoma

The sustained and moderate elevation of intraocular pressure, which can be initiated at precise time points, remains the cornerstone of research into the mechanisms of glaucomatous retinal damage. We focus on the use of microbeads to block the outflow of aqueous following anterior chamber injection in a range of animals (mouse, rat and primate). We describe some of the most commonly used parameters and present guidance on injection technique and bead manipulation to facilitate the successful generation of experimental glaucoma

Ocular hypertension suppresses homeostatic gene expression in optic nerve head microglia of DBA/2 J mice.

Glaucoma is the leading cause of irreversible vision loss. Ocular hypertension is a major risk factor for glaucoma and recent work has demonstrated critical early neuroinflammatory insults occur in the optic nerve head following ocular hypertension. Microglia and infiltrating monocytes are likely candidates to drive these neuroinflammatory insults. However, the exact molecular identity / transcriptomic profile of microglia following ocular hypertensive insults is unknown. To elucidate the molecular identity of microglia after long-term exposure to ocular hypertension, we used a mouse model of glaucoma (DBA/2 J). We performed RNA-sequencing of microglia mRNA from the optic nerve head at a time point following ocular hypertensive insults, but preceding detectable neurodegeneration (with microglia identified as being CD4

Magnetic Field Evolution in Merging Clusters of Galaxies

We present initial results from the first 3-dimensional numerical magnetohydrodynamical (MHD) simulations of magnetic field evolution in merging clusters of galaxies. Within the framework of idealized initial conditions similar to our previous work, we look at the gasdynamics and the magnetic field evolution during a major merger event in order to examine the suggestion that shocks and turbulence generated during a cluster/subcluster merger can produce magnetic field amplification and relativistic particle acceleration and, as such, may play a role in the formation and evolution of cluster-wide radio halos. The ICM, as represented by the equations of ideal MHD, is evolved self-consistently within a changing gravitational potential defined largely by the collisionless dark matter component represented by an N-body particle distribution. The MHD equations are solved by the Eulerian, finite-difference code, ZEUS. The particles are evolved by a standard particle-mesh (PM) code. We find significant evolution of the magnetic field structure and strength during two distinct epochs of the merger evolution.Comment: 21 pages, 7 figures, Figure 2 is color postscript. Accepted for publication in Ap

Inhibition of the classical pathway of the complement cascade prevents early dendritic and synaptic degeneration in glaucoma

BACKGROUND: Glaucoma is a complex, multifactorial disease characterised by the loss of retinal ganglion cells and their axons leading to a decrease in visual function. The earliest events that damage retinal ganglion cells in glaucoma are currently unknown. Retinal ganglion cell death appears to be compartmentalised, with soma, dendrite and axon changes potentially occurring through different mechanisms. There is mounting evidence from other neurodegenerative diseases suggesting that neuronal dendrites undergo a prolonged period of atrophy, including the pruning of synapses, prior to cell loss. In addition, recent evidence has shown the role of the complement cascade in synaptic pruning in glaucoma and other diseases. RESULTS: Using a genetic (DBA/2J mouse) and an inducible (rat microbead) model of glaucoma we first demonstrate that there is loss of retinal ganglion cell synapses and dendrites at time points that precede axon or soma loss. We next determine the role of complement component 1 (C1) in early synaptic loss and dendritic atrophy during glaucoma. Using a genetic knockout of C1qa (D2.C1qa (-/-) mouse) or pharmacological inhibition of C1 (in the rat bead model) we show that inhibition of C1 is sufficient to preserve dendritic and synaptic architecture. CONCLUSIONS: This study further supports assessing the potential for complement-modulating therapeutics for the prevention of retinal ganglion cell degeneration in glaucoma. Mol Neurodegener 2016 Apr 6; 11(2):2

Glial metabolic alterations during glaucoma pathogenesis

Glaucoma is the leading cause of irreversible blindness. Current treatment options are limited and often only slow disease progression. Metabolic dysfunction has recently been recognized as a key early and persistent mechanism in glaucoma pathophysiology. Several intrinsic metabolic dysfunctions have been identified and treated in retinal ganglion cells to provide neuroprotection. Growing pre-clinical and clinical evidence has confirmed that metabolic alterations in glaucoma are widespread, occurring across visual system tissues, in ocular fluids, in blood/serum, and at the level of genomic and mitochondrial DNA. This suggests that metabolic dysfunction is not constrained to retinal ganglion cells and that metabolic alterations extrinsic to retinal ganglion cells may contribute to their metabolic compromise. Retinal ganglion cells are reliant on glial metabolic support under normal physiological conditions, but the implications of metabolic dysfunction in glia are underexplored. We highlight emerging evidence that has demonstrated metabolic alterations occurring within glia in glaucoma, and how this may affect neuro-glial metabolic coupling and the metabolic vulnerability of retinal ganglion cells. In other neurodegenerative diseases which share features with glaucoma, several other glial metabolic alterations have been identified, suggesting that similar mechanisms and therapeutic targets may exist in glaucoma

Digestion of the glycosaminoglycan extracellular matrix by chondroitinase ABC supports retinal ganglion cell dendritic preservation in a rodent model of experimental glaucoma

Retinal ganglion cell dendritic atrophy is an early feature of glaucoma, and the recovery of retinal ganglion cell dendrites is a viable option for vision improvement in glaucoma. Retinal ganglion cell neurites are surrounded by a specialised glycosaminoglycan extracellular matrix which inhibits dendritic plasticity. Since digestion of the extracellular matrix by chondroitinase ABC has been reported to have neuro-regenerative and neuro-plastic effects within the central nervous system, we explored its potential for dendritic recovery in a rat model of ocular hypertension. Chondroitinase ABC was administrated intravitreally 1 week after ocular hypertension (a time point where dendritic atrophy has already occurred). Retinal ganglion cell dendritic morphology was unaffected by chondroitinase ABC in normal retina. In ocular hypertensive eyes retinal ganglion cells showed significantly decreased dendritic length and area under the Sholl curve with atrophy confined to higher order dendrites. These changes were not observed in chondroitinase ABC injected eyes despite similar total retinal ganglion cell loss (i.e. dendritic protection of surviving retinal ganglion cells). These data suggest that glycosaminoglycan digestion could have a therapeutic role in mitigating the effects of elevated pressure on retinal ganglion cell dendritic structure in glaucoma

Sholl analysis: A quantitative comparison of semi-automated methods

Background: Sholl analysis remains one of the most commonly used methods to quantify neuronal dendritic complexity and is therefore a key analysis tool in neurobiology. While initially proposed when the quantification of neuronal structure was undertaken manually, the advent of software packages allowing automated analysis has resulted in the introduction of several semi and fully automated methods to quantify dendritic complexity. Unfortunately results from these methods have not in all cases been consistent. We therefore compared the results of five commonly used methods (Simple Neurite Tracer, manual, Fast Sholl, Bitmap, and Ghosh lab) using manual analysis as a ground truth. New method: Comparison of four semi-automated methods to the manual method using diolistically labelled mouse retinal ganglion cells. Results: We report consistency across a range of published techniques. While the majority perform well (Simple Neurite Tracer and Fast Sholl profiles have areas under the curve within 4.5% of the profile derived using the manual method), we highlight two areas in two of the methods (Bitmap and Ghosh lab methods) where errors may occur, namely undercounting (>20% relative to the manual profile) and a second peak. Comparison with existing methods: Our results support published validation of the Fast Sholl method. Conclusions: Our study highlights the importance of manual calibration of automated analysis software

A novel system for the classification of diseased retinal ganglion cells

Retinal ganglion cell (RGC) dendritic atrophy is an early feature of many forms of retinal degeneration, providing a challenge to RGC classification. The characterization of these changes is complicated by the possibility that selective labeling of any particular class can confound the estimation of dendritic remodeling. To address this issue we have developed a novel, robust, and quantitative RGC classification based on proximal dendritic features which are resistant to early degeneration. RGCs were labeled through the ballistic delivery of DiO and DiI coated tungsten particles to whole retinal explants of 20 adult Brown Norway rats. RGCs were grouped according to the Sun classification system. A comprehensive set of primary and secondary dendrite features were quantified and a new classification model derived using principal component (PCA) and discriminant analyses, to estimate the likelihood that a cell belonged to any given class. One-hundred and thirty one imaged RGCs were analyzed; according to the Sun classification, 24% (n = 31) were RGCA, 29% (n = 38) RGCB, 32% (n = 42) RGCC, and 15% (n = 20) RGCD. PCA gave a 3 component solution, separating RGCs based on descriptors of soma size and primary dendrite thickness, proximal dendritic field size and dendritic tree asymmetry. The new variables correctly classified 73.3% (n = 74) of RGCs from a training sample and 63.3% (n = 19) from a hold out sample indicating an effective model. Soma and proximal dendritic tree morphological features provide a useful surrogate measurement for the classification of RGCs in disease. While a definitive classification is not possible in every case, the technique provides a useful safeguard against sample bias where the normal criteria for cell classification may not be reliable

A novel system for the classification of diseased retinal ganglion cells

Retinal ganglion cell (RGC) dendritic atrophy is an early feature of many forms of retinal degeneration, providing a challenge to RGC classification. The characterization of these changes is complicated by the possibility that selective labeling of any particular class can confound the estimation of dendritic remodeling. To address this issue we have developed a novel, robust, and quantitative RGC classification based on proximal dendritic features which are resistant to early degeneration. RGCs were labeled through the ballistic delivery of DiO and DiI coated tungsten particles to whole retinal explants of 20 adult Brown Norway rats. RGCs were grouped according to the Sun classification system. A comprehensive set of primary and secondary dendrite features were quantified and a new classification model derived using principal component (PCA) and discriminant analyses, to estimate the likelihood that a cell belonged to any given class. One-hundred and thirty one imaged RGCs were analyzed; according to the Sun classification, 24% (n = 31) were RGCA, 29% (n = 38) RGCB, 32% (n = 42) RGCC, and 15% (n = 20) RGCD. PCA gave a 3 component solution, separating RGCs based on descriptors of soma size and primary dendrite thickness, proximal dendritic field size and dendritic tree asymmetry. The new variables correctly classified 73.3% (n = 74) of RGCs from a training sample and 63.3% (n = 19) from a hold out sample indicating an effective model. Soma and proximal dendritic tree morphological features provide a useful surrogate measurement for the classification of RGCs in disease. While a definitive classification is not possible in every case, the technique provides a useful safeguard against sample bias where the normal criteria for cell classification may not be reliable