Abstract
Purpose :
Partial optic nerve transection (pONT) in the rodent is a useful model to assess RGC secondary degeneration which is thought to play a role in diseases such as glaucoma. Previous studies segregated primary and secondary degeneration in this model spatially, with primary degeneration suggested to occur exclusively in the superior retina and secondary degeneration in the inferior retina. The present study describes a novel algorithm for the automatic spatial segmentation of Brn3a labelled RGCs into retinal segments to enable the percentage contribution of primary and secondary degeneration.
Methods :
A previously described Brn3a automatic counting algorithm (Cell Death & Disease 2014 e1460) was adapted to automatically divide RGC counts into pre-defined sectors from which RGC density (RGC/mm2) were determined. This algorithm was applied to 42 Dark Agouti rat retinal whole mounts at 0 (control), 3, 7, 21 and 56 days post pONT induction. The rate of RGC loss in each sector was determined by fitting RGC density to exponential decay equations from which the percentage of primary and secondary degeneration in each non-overlapping segment could be determined.
Results :
Mean Brn3a-positive RGC count (82,592 ± 681) and RGC density (1,695 ± 23.3 RGC/mm2) in control eyes were comparable with previous studies (PLoS ONE, 2012 e49830). A significant reduction in RGC density was observed from 3 days of pONT model induction (one-way ANOVA, p <0.001), declining by an average of 70% by day 56. On further spatial segmentation, significantly greater loss in RGC density was observed in the superior versus inferior retinal quadrants at 21 and 56 days post pONT induction (paired two tailed T-tests, p < 0.001). While the majority of primary degeneration was observed in the superior and central retinal sectors, secondary degeneration was also observed in these sectors.
Conclusions :
A novel algorithm to automatically segment Brn3a retinal wholemounts into non-overlapping segments is described, which has been succesfully used to delineate primary and secondary degeneration in pONT models. The interesting finding of heterogeneity in the spatial distribution of retinal degeneration in this model highlights the importance of accurate assessment of these processes. We recommend that similar analyses of RGC loss is applied to any model where it is being used as an endpoint.
This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.