Axonopathy precedes cell death in ocular damage mediated by blast exposure

Visual Impairment in Pre-Clinical Models of Mild Traumatic Brain Injury

Impairment in visual function is common after traumatic brain injury (TBI) in the clinical setting, a phenomenon that translates to pre-clinical animal models as well. In Morris et al. (2021), we reported histological changes following weight-drop-induced TBI in a rodent model including retinal ganglion cell (RGC) loss, decreased electroretinogram (ERG) evoked potential, optic nerve diameter reduction, induced inflammation and gliosis, and loss of myelin accompanied by markedly impaired visual acuity. In this review, we will describe several pre-clinical TBI models that result in injuries to the visual system, indicating that visual function may be impaired following brain injury induced by a number of different injury modalities. This underscores the importance of understanding the role of the visual system and the potential detrimental sequelae to this sensory modality post-TBI. Given that most commonly employed behavioral tests such as the Elevated Plus Maze and Morris Water Maze rely on an intact visual system, interpretation of functional deficits in diffuse models may be confounded by off- target effects on the visual system.

Comparison of Brn3a and RBPMS Labeling to Assess Retinal Ganglion Cell Loss During Aging and in a Model of Optic Neuropathy

Purpose

Retinal ganglion cell (RGC) loss provides the basis for diagnosis and stage determination of many optic neuropathies, and quantification of RGC survival is a critical outcome measure in models of optic neuropathy. This study examines the accuracy of manual RGC counting using two selective markers, Brn3a and RBPMS.

Methods

Retinal flat mounts from 1- to 18-month-old C57BL/6 mice, and from mice after microbead (MB)-induced intraocular pressure (IOP) elevation, are immunostained with Brn3a and/or RBPMS antibodies. Four individuals masked to the experimental conditions manually counted labeled RGCs in three copies of five images, and inter- and intra-person reliability was evaluated by the intraclass correlation coefficient (ICC).

Results

A larger population (approximately 10% higher) of RGCs are labeled with RBPMS than Brn3a antibody up to 6 months of age, but differences decrease to approximately 1% at older ages. Both RGC-labeled populations significantly decrease with age. MB-induced IOP elevation is associated with a significant decrease of both Brn3a- and RBPMS-positive RGCs. Notably, RGC labeling with Brn3a provides more consistent cell counts than RBPMS in interpersonal (ICC = 0.87 to 0.11, respectively) and intra-personal reliability (ICC = 0.97 to 0.66, respectively).

Conclusions

Brn3a and RBPMS markers are independently capable of detecting significant decreases of RGC number with age and in response to IOP elevation despite RPBMS detecting a larger number of RGCs up to 6 months of age. Brn3a labeling is less prone to manual cell counting variability than RBPMS labeling. Overall, either marker can be used as a single marker to detect significant changes in RGC survival, each offering distinct advantages.

Model matters: Differential outcomes in traumatic optic neuropathy pathophysiology between blunt and blast-wave mediated head injuries

Over 3 million people in the United States live with long-term disability because of a traumatic brain injury (TBI). The purpose of this study was to characterize and compare two different animal models of TBI (blunt head trauma and blast TBI) to determine common and divergent characteristics of these models. With recent literature reviews noting the prevalence of visual system injury in animal models of TBI, coupled with clinical estimates of 50-75% of all TBI cases, we decided to assess commonalities, if they existed, through visual system injury. A unilateral (left directed) blast and repeat blast model injury with coup-contra-coup injury patterns were compared to a midline blunt injury. Injuries were induced in adult male mice to observe and quantify visual deficits. Retinal ganglion cell loss and axonal degeneration in the optic tract, superior colliculus, and lateral geniculate nuclei were examined to trace injury outcomes throughout major vision-associated areas. Optokinetic response, immunohistochemistry, and western blots were analyzed. Where a single blunt injury produces significant visual deficits a single blast injury appears to have less severe visual consequences. Visual deficits after repeat blasts are similar to a single blast. Single blast injury induces contralateral damage to the right optic chiasm and tract whereas bilateral injury follows a single blunt TBI. Repeat blast injuries are required to see degeneration patterns in downstream regions similar to the damage seen in a single blunt injury. This finding is further supported by amyloid precursor protein (APP) staining in injured cohorts. Blunt injured groups present with staining 1.2 mm ahead of the optic nerve, indicating axonal breakage closer to the optic chiasm. In blast groups, APP was identifiable in a bilateral pattern only in the geniculate nucleus. Evidence for unilateral neuronal degeneration in brain tissue with bilateral axonal ruptures are pivotal discoveries in this model differentiation. Analysis of the two injury models suggests that there is a significant difference in the histological outcomes dependent on injury type, though visual system injury is likely present in more cases than are currently diagnosed clinically.

Glaucoma-Associated CDR1 Peptide Promotes RGC Survival in Retinal Explants through Molecular Interaction with Acidic Leucine Rich Nuclear Phosphoprotein 32A (ANP32A)

Glaucoma is a complex, multifactorial optic neuropathy mainly characterized by the progressive loss of retinal ganglion cells (RGCs) and their axons, resulting in a decline of visual function. The pathogenic molecular mechanism of glaucoma is still not well understood, and therapeutic strategies specifically addressing the neurodegenerative component of this ocular disease are urgently needed. Novel immunotherapeutics might overcome this problem by targeting specific molecular structures in the retina and providing direct neuroprotection via different modes of action. Within the scope of this research, the present study showed for the first time beneficial effects of the synthetic CDR1 peptide SCTGTSSDVGGYNYVSWYQ on the viability of RGCs ex vivo in a concentration-dependent manner compared to untreated control explants (CTRL, 50 µg/mL: p < 0.05 and 100 µg/mL: p < 0.001). Thereby, this specific peptide was identified first as a potential biomarker candidate in the serum of glaucoma patients and was significantly lower expressed in systemic IgG molecules compared to healthy control subjects. Furthermore, MS-based co-immunoprecipitation experiments confirmed the specific interaction of synthetic CDR1 with retinal acidic leucine-rich nuclear phosphoprotein 32A (ANP32A; p < 0.001 and log2 fold change > 3), which is a highly expressed protein in neurological tissues with multifactorial biological functions. In silico binding prediction analysis revealed the N-terminal leucine-rich repeat (LRR) domain of ANP32A as a significant binding site for synthetic CDR1, which was previously reported as an important docking site for protein-protein interactions (PPI). In accordance with these findings, quantitative proteomic analysis of the retinae ± CDR1 treatment resulted in the identification of 25 protein markers, which were significantly differentially distributed between both experimental groups (CTRL and CDR1, p < 0.05). Particularly, acetyl-CoA biosynthesis I-related enzymes (e.g., DLAT and PDHA1), as well as cytoskeleton-regulating proteins (e.g., MSN), were highly expressed by synthetic CDR1 treatment in the retina; on the contrary, direct ANP32A-interacting proteins (e.g., NME1 and PPP2R4), as well as neurodegenerative-related markers (e.g., CEND1), were identified with significant lower abundancy in the CDR1-treated retinae compared to CTRL. Furthermore, retinal protein phosphorylation and histone acetylation were also affected by synthetic CDR1, which are both partially controlled by ANP32A. In conclusion, the synthetic CDR1 peptide provides a great translational potential for the treatment of glaucoma in the future by eliciting its neuroprotective mechanism via specific interaction with ANP32A's N terminal LRR domain.

AxoNet 2.0: A Deep Learning-Based Tool for Morphometric Analysis of Retinal Ganglion Cell Axons

Purpose

Assessment of glaucomatous damage in animal models is facilitated by rapid and accurate quantification of retinal ganglion cell (RGC) axonal loss and morphologic change. However, manual assessment is extremely time- and labor-intensive. Here, we developed AxoNet 2.0, an automated deep learning (DL) tool that (i) counts normal-appearing RGC axons and (ii) quantifies their morphometry from light micrographs.

Methods

A DL algorithm was trained to segment the axoplasm and myelin sheath of normal-appearing axons using manually-annotated rat optic nerve (ON) cross-sectional micrographs. Performance was quantified by various metrics (e.g., soft-Dice coefficient between predicted and ground-truth segmentations). We also quantified axon counts, axon density, and axon size distributions between hypertensive and control eyes and compared to literature reports.

Results

AxoNet 2.0 performed very well when compared to manual annotations of rat ON (R2 = 0.92 for automated vs. manual counts, soft-Dice coefficient = 0.81 ± 0.02, mean absolute percentage error in axonal morphometric outcomes < 15%). AxoNet 2.0 also showed promise for generalization, performing well on other animal models (R2 = 0.97 between automated versus manual counts for mice and 0.98 for non-human primates). As expected, the algorithm detected decreased in axon density in hypertensive rat eyes (P ≪ 0.001) with preferential loss of large axons (P < 0.001).

Conclusions

AxoNet 2.0 provides a fast and nonsubjective tool to quantify both RGC axon counts and morphological features, thus assisting with assessing axonal damage in animal models of glaucomatous optic neuropathy.

Translational Relevance

This deep learning approach will increase rigor of basic science studies designed to investigate RGC axon protection and regeneration.

Biological Correlations and Confounders for Quantification of Retinal Ganglion Cells by Optical Coherence Tomography Based on Studies of Outbred Mice

Purpose

Despite popularity of optical coherence tomography (OCT) in glaucoma studies, it's unclear how well OCT-derived metrics compare to traditional measures of retinal ganglion cell (RGC) abundance. Here, Diversity Outbred (J:DO) mice are used to directly compare ganglion cell complex (GCC) thickness measured by OCT to metrics of retinal anatomy measured ex vivo with retinal wholemounts and optic nerve histology.

Methods

J:DO mice (n = 48) underwent fundoscopic and OCT examinations, with automated segmentation of GCC thickness. RGC axons were quantified from para-phenylenediamine-stained optic nerve cross-sections and somas from BRN3A-immunolabeled retinal wholemounts, with total inner retinal cellularity assessed by TO-PRO and subsequent hematoxylin staining.

Results

J:DO tissues lacked overt disease. GCC thickness, RGC abundance, and total cell abundance varied broadly across individuals. GCC thickness correlated significantly to RGC somal density (r = 0.58) and axon number (r = 0.44), but not total cell density. Retinal area and nerve cross-sectional area varied widely. No metrics were significantly influenced by sex. In bilateral comparisons, GCC thickness (r = 0.95), axon (r = 0.72), and total cell density (r = 0.47) correlated significantly within individuals.

Conclusions

Amongst outbred mice, OCT-derived measurements of GCC thickness correlate significantly to RGC somal and axon abundance. Factors limiting correlation are likely both biological and methodological, including differences in retinal area that distort sampling-based estimates of RGC abundance.

Translational Relevance

There are significant-but imperfect-correlations between GCC thickness and RGC abundance across genetic contexts in mice, highlighting valid uses and ongoing challenges for meaningful use of OCT-derived metrics.

AxonDeep: Automated Optic Nerve Axon Segmentation in Mice With Deep Learning

Purpose

Optic nerve damage is the principal feature of glaucoma and contributes to vision loss in many diseases. In animal models, nerve health has traditionally been assessed by human experts that grade damage qualitatively or manually quantify axons from sampling limited areas from histologic cross sections of nerve. Both approaches are prone to variability and are time consuming. First-generation automated approaches have begun to emerge, but all have significant shortcomings. Here, we seek improvements through use of deep-learning approaches for segmenting and quantifying axons from cross-sections of mouse optic nerve.

Methods

Two deep-learning approaches were developed and evaluated: (1) a traditional supervised approach using a fully convolutional network trained with only labeled data and (2) a semisupervised approach trained with both labeled and unlabeled data using a generative-adversarial-network framework.

Results

From comparisons with an independent test set of images with manually marked axon centers and boundaries, both deep-learning approaches outperformed an existing baseline automated approach and similarly to two independent experts. Performance of the semisupervised approach was superior and implemented into AxonDeep.

Conclusions

AxonDeep performs automated quantification and segmentation of axons from healthy-appearing nerves and those with mild to moderate degrees of damage, similar to that of experts without the variability and constraints associated with manual performance.

Translational Relevance

Use of deep learning for axon quantification provides rapid, objective, and higher throughput analysis of optic nerve that would otherwise not be possible.

Chronic Histological Outcomes of Indirect Traumatic Optic Neuropathy in Adolescent Mice: Persistent Degeneration and Temporally Regulated Glial Responses

Injury to the optic nerve, termed, traumatic optic neuropathy (TON) is a known comorbidity of traumatic brain injury (TBI) and is now known to cause chronic and progressive retinal thinning up to 35 years after injury. Although animal models of TBI have described the presence of optic nerve degeneration and research exploring acute mechanisms is underway, few studies in humans or animals have examined chronic TON pathophysiology outside the retina. We used a closed-head weight-drop model of TBI/TON in 6-week-old male C57BL/6 mice. Mice were euthanized 7-, 14-, 30-, 90-, and 150-days post-injury (DPI) to assess histological changes in the visual system of the brain spanning a total of 12 regions. We show chronic elevation of FluoroJade-C, indicative of neurodegeneration, throughout the time course. Intriguingly, FJ-C staining revealed a bimodal distribution of mice indicating the possibility of subpopulations that may be more or less susceptible to injury outcomes. Additionally, we show that microglia and astrocytes react to optic nerve damage in both temporally and regionally different ways. Despite these differences, astrogliosis and microglial changes were alleviated between 14-30 DPI in all regions examined, perhaps indicating a potentially critical period for intervention/recovery that may determine chronic outcomes.