<em>In Vivo </em>Dynamics of Retinal Microglial Activation During Neurodegeneration: Confocal Ophthalmoscopic Imaging and Cell Morphometry in Mouse Glaucoma

Abstract

SHORT ABSTRACT Microglia activation and microgliosis are key responses to chronic neurodegeneration. Here, we present methods for in vivo, long-term visualization of retinal CX3CR1-GFP+ microglial cells by confocal ophthalmoscopy, and for threshold and morphometric analyses to identify and quantify their activation. We monitor microglial changes during early stages of age-related glaucoma. LONG ABSTRACT Microglia, which are CNS-resident neuroimmune cells, transform their morphology and size in response to CNS damage, switching to an activated state with distinct functions and gene expression profiles. The roles of microglial activation in health, injury and disease remain incompletely understood due to their dynamic and complex regulation in response to changes in their microenvironment. Thus, it is critical to non-invasively monitor and analyze changes in microglial activation over time in the intact organism. In vivo studies of microglial activation have been delayed by technical limitations to tracking microglial behavior without altering the CNS environment. This has been particularly challenging during chronic neurodegeneration, where long-term changes must be tracked. The retina, a CNS organ amenable to non-invasive live imaging, offers a powerful system to visualize and characterize the dynamics of microglia activation during chronic disorders. This protocol outlines methods for long-term, in vivo imaging of retinal microglia, using confocal ophthalmoscopy (cSLO) and CX3CR1-GFPGFP/+ reporter mice, to visualize microglia with cellular resolution. Also, we describe methods to quantify monthly changes in cell activation and density in large cell subsets (200–300 cells per retina). We confirm the use of somal area as a useful metric for live tracking of microglial activation in the retina by applying automated threshold-based morphometric analysis of in vivo images. We use these live image acquisition and analyses strategies to monitor the dynamic changes in microglial activation and microgliosis during early stages of retinal neurodegeneration in a mouse model of chronic glaucoma. This approach should be useful to investigate the contributions of microglia to neuronal and axonal decline in chronic CNS disorders that affect the retina and optic nerve.

Loss of Fractalkine Signaling Exacerbates Axon Transport Dysfunction in a Chronic Model of Glaucoma

“…RGC degeneration in the DBA/2J model is well characterized within the optic nerve to include a progressive loss of RGC axons and a subsequent replacement by glia and extracellular matrix (John et al, 1998; Libby et al, 2005a; Schlamp et al, 2006; Lye-Barthel et al, 2013; Bosco et al, 2015a,b, 2016; Cooper et al, 2016). To determine if the potential impact on axonal transport by loss of Cx3cr1 affected optic nerve degeneration, we estimated the relative coverage of non-axonal area using segmentation of glia and extracellular matrix in nerve cross-sections (Bosco et al, 2015a,b, 2016).…”

“…To determine if the potential impact on axonal transport by loss of Cx3cr1 affected optic nerve degeneration, we estimated the relative coverage of non-axonal area using segmentation of glia and extracellular matrix in nerve cross-sections (Bosco et al, 2015a,b, 2016). For both the DBA/2J and Cx3cr1 gfp/gfp DBA/2J genotypes at 10–11 months, we observed a similar distribution of nerves with non-axonal area ranging from 10 to above 95% in individual nerves (Figures 4A–E).…”

“…Sections were stained with PPD (Libby et al, 2005a) for 28 min using a modified protocol as previously described (Bosco et al, 2015a,b), and mounted under coverslips with Permount (Fisher).…”

“…The relative area devoid of axons or dystrophic axons in individual optic nerve cross-sections was measured by segmentation of glial cells and/or glial scar and extracellular matrix from 8-bit stitched RGB images of PPD stained nerves, as previously described (Bosco et al, 2015a,b, 2016). The green channel of the RGB image provided the greatest contrast to segment glial area from non-glial elements including axons and blood vessels.…”

Characterizing microglia activation: a spatial statistics approach to maximize information extraction

“…refs [13][14][15][16]. Furthermore, a growing interest in the detailed course of microglial reactivity in this experimental glaucoma model has been emerging [17][18][19][20][21] . Aiming to address this recent focus, we designed an automated analysis algorithm that, based on Iba-1 (ionized calcium-binding adapter molecule 1) immunostaining of the retinal microglia, quantifies five parameters: cell density, nearest neighbour distance (NND) and regularity index, to describe microglia numbers and distribution; and cell soma size and roundness, to assess cell morphology.…”