Tag Archives: Rebecca Pfeiffer

Pathoconnectome Analysis of Müller Cells in Early Retinal Remodeling

Rebecca Pfeiffer, a post-doc in the laboratory presented her work on “Pathoconnectome Analysis of Müller Cells in Early Retinal Remodeling” as a platform presentation at the RD2018 meeting in Killarney, Ireland.

Authors: Rebecca Pfeiffer, James R. Anderson, Daniel P. Emrich, Jeebika Dahal, Crystal L Sigulinsky, Hope AB Morrison, Jia-Hui Yang, Carl B. Watt, Kevin D. Rapp, Mineo Kondo, Hiroko Terasaki, Jessica C Garcia, Robert E. Marc, and Bryan W. Jones.

Purpose: Glia play important roles in neural system function. These roles include, but are not limited to: amino acid recycling, ion homeostasis, glucose transport, and removal of waste. During retinal degeneration, Muller cells, the primary macroglia of the retina, are one of the first cells to show metabolic and morphological alterations in response to retinal stress. The metabolic alterations observed in Muller cells appear to manifest in regions of photoreceptor degeneration; however, the precise mechanisms that govern these alterations in response to neuronal stress, synapse maintenance, or glia-glia interactions is currently unknown.  This project aims to reconstruct Muller cells from a pathoconnectome of early retinal remodeling at 2nm/pixel with ultrastructural metabolic data to determine the relationship of structural and metabolic phenotypes between neighboring neurons and glia.

Methods:  Retinal pathoconnectome 1 (RPC1) is the first connectome to be assembled from pathologic neural tissue (a pathoconnectome). The tissue selected for RPC1 was collected post mortem from a 10 month transgenic P347L rabbit model of autosomal dominant retinitis pigmentosa, fixed in 1% formaldehyde, 2.5% glutaraldehyde, 3% sucrose, and 1mM MgSO4 in cacodylate buffer (pH 7.4). The tissue was subsequently osmicated, dehydrated, resin embedded, and sectioned at 70nm. Sections were placed on formvar grids, stained, and imaged at 2nm/pixel on a JEOL JEM-1400 TEM using SerialEM software. 1 section was reserved from every 30 sections for CMP, where it was placed on a slide and probed for small molecules: glutamate, glutamine, glycine, GABA, taurine, glutathione; or TEM compatible proteins GFAP and GS. The pathoconnectome volume was evaluated and annotated using the Viking software suite.

Results: RPC1 demonstrates hallmarks of early retinal degeneration and remodeling, including the glial phenotypes of hypertrophy and metabolic variation between neighboring Muller cells. Early evaluation of these glia demonstrates variations in osmication in Muller cells as well as apparent encroachment of glial end-feet on one another.  We are currently in the process of reconstructing multiple Muller cells within RPC1 and their neighboring neurons.  Once complete, we will assess the relationship between Muller cell phenotype and the phenotypes of contacted neuronal and glial neighbors.

Conclusions: How neural-glial relationships are affected by retinal remodeling may help us understand why remodeling and neurodegeneration follow photoreceptor degeneration. In addition, determining these relationships during remodeling will be crucial to developing therapeutics with long-term success. RPC1 provides a framework to analyze these relationships in early retinal remodeling through ultrastructural reconstructions of all neurons and glia in an intact retina. These reconstructions, informed by quantitative metabolite labeling, will allow us to evaluate these neural-glial interactions more comprehensively than other techniques have previously allowed.

Off to RD2018 and ISER 2018

The Marclab for Connectomics is off to RD2018 and ISER 2018 in Killarney, Ireland and Belfast, Northern Ireland.  I’ll be organizing sessions on retinal degeneration, and I’m tremendously proud of the work Dr. Crystal Sigulinsky will be presenting from her work on gap junctional connectivity in retinal degenerations and the work Dr. Rebecca Pfeiffer (@BeccaPfeiffer19) will be presenting on her work on the retinal pathoconnectome in two talks on bipolar cells and Müller cells.

A Pathoconnectome of Early Retinal Remodeling

This abstract was presented today, Monday, April 30th at the 2018 Association for Research in Vision and Opthalmology (ARVO) meetings in Honolulu, Hawaii by Rebecca Pfeiffer, Robert E. Marc, James R. Anderson, Daniel P. Emrich, Carl B. Watt, Jia-Hui Yang, Kevin D. Rapp, Jeebika Dahal, Mineo Kondo, Hiroko Terasaki, and Bryan W. Jones.

Purpose:
Retinal remodeling is a consequence of retinal degenerative disease, during which neurons sprout new neurites whose synaptic structures and partners are not yet defined. Simultaneously during remodeling, Müller cells (MCs) undergo structural and metabolic changes, whose impact on surrounding neurons is an active area of research. Retinal connectomes have elucidated and validated fundamental networks. These data provide further classification of neuronal types and subtypes and a precise framework for modeling of retinal function, based on ground truth networks. The creation of the first pathoconnectome (RPC1), a connectome from pathological retinal tissue, provides the opportunity to determine connectivites between neurons, while simultaneously evaluating glial remodeling. Computational Molecular Phenotyping (CMP) embedded within the ultrastructure provides metabolic factors of pathologies.

Methods:
RPC1 was collected post-mortem from a 10mo TgP347L rabbit model of adRP, fixed in 1% FA, 2.5% GA, 3% sucrose, and 1mM MgSO4 in cacodylate buffer (pH 7.4). The tissue was osmicated, dehydrated, resin embedded, and sectioned at 70nm. Sections were placed on formvar grids, stained, and imaged on a JEOL JEM-1400 TEM using SerialEM. 1 section was reserved from every 30 section for CMP, where it was probed for small molecules: glutamate, glutamine, glycine, GABA, taurine, glutathione; or proteins GFAP and GS. RPC1 was evaluated using the Viking software suite.

Results:
RPC1 was chosen based on early features of retinal degeneration/remodeling: degeneration of rod OS, MC hypertrophy, and neuronal sprouting. RPC1 consists of 948 serial sections spanning the ONL to the vitreous, with a diameter of 90µm. We find dendrites extending from rod bipolar cells to cone pedicles, originally described in light microscopy, and active synaptic contacts. We also see alterations of synaptic structure in the IPL, and MC morphological changes affecting surface to volume and neuron/glial relationships. Network motifs are being actively investigated.

Conclusions:
We observe many features of remodeling previously described using light microscopy, and confirm active synaptic contact. We also find synaptic structural features, not previously described. In addition, early evaluation of MC morphology demonstrates marked changes in MC shape and associations with nearby neurons and glia, which, combined with CMP, will be instrumental in understanding how MCs affect retinal remodeling.

Pattern Recognition Analysis Reveals Unique Contrast Sensitivity Isocontours Using Static Perimetry Thresholds Across The Visual Field

We have a new publication in IOVS, Pattern Recognition Analysis Reveals Unique Contrast Sensitivity Isocontours Using Static Perimetry Thresholds Across The Visual Field (Direct link here).  Authors are:  Jack Phu, Sieu Khuu, Lisa Nivison-Smith, Barbara Zangerl, Agnes Yiu, Jeung Choi, Bryan W. JonesRebecca Pfeiffer, Robert Marc, and Michael Kalloniatis.

Purpose
To determine the locus of test locations that exhibit statistically similar age-related decline in sensitivity to light increments and age-corrected contrast sensitivity isocontours (CSIs) across the central visual field (VF). We compared these CSIs with test point clusters used by the Glaucoma Hemifield Test (GHT).

Methods
Sixty healthy observers underwent testing on the Humphrey Field Analyzer 30-2 test grid using Goldmann (G) stimulus sizes I-V. Age-correction factors for GI-V were determined using linear regression analysis. Pattern recognition analysis was used to cluster test locations across the VF exhibiting equal age-related sensitivity decline (age-related CSIs), and points of equal age-corrected sensitivity (age-corrected CSIs) for GI-V.

Results
There was a small but significant test size–dependent sensitivity decline with age, with smaller stimuli declining more rapidly. Age-related decline in sensitivity was more rapid in the periphery. A greater number of unique age-related CSIs was revealed when using smaller stimuli, particularly in the mid-periphery. Cluster analysis of age-corrected sensitivity thresholds revealed unique CSIs for GI-V, with smaller stimuli having a greater number of unique clusters. Zones examined by the GHT consisted of test locations that did not necessarily belong to the same CSI, particularly in the periphery.

Conclusions
Cluster analysis reveals statistically significant groups of test locations within the 30-2 test grid exhibiting the same age-related decline. CSIs facilitate pooling of sensitivities to reduce the variability of individual test locations. These CSIs could guide future structure-function and alternate hemifield asymmetry analyses by comparing matched areas of similar sensitivity signatures.

Pattern Recognition Analysis of Age-Related Retinal Ganglion Cell Signatures In The Human Eye

We have a new publication in IOVS, Pattern Recognition Analysis of Age-Related Retinal Ganglion Cell Signatures In The Human Eye (Direct link here).  Authors are:  Nayuta Yoshioka, Barbara Zangerl, Lisa Nivison-Smith, Sieu Khuu, Bryan W. Jones, Rebecca Pfeiffer, Robert Marc, and Michael Kalloniatis.

Purpose: We recently used pattern recognition analysis to show macula areas can be classified into statistically distinct clusters in accordance to their age-related retinal ganglion cell layer (RGCL) thickness change in a normal population. The aim of this study was to perform a retrospective cross-sectional analysis utilizing a large cohort of patients to establish accuracy of this model and to develop a normative dataset using a 50-year-old equivalent cohort.

Methods: Data was collected from patients seen at the Centre for Eye Health for optic nerve assessment without posterior pole disease. The grid-wise RGCL thickness was obtained from a single eye of each patient via Spectralis OCT macular scan over an 8×8 measurement grid. Measurements for patients outside the 45-54 age range (training cohort) were converted to 50-year-old equivalent value utilizing pattern recognition derived regression model which, in brief, consists of 8×8 grid clustered into 8 distinct classes according to the pattern of RGCL thickness change with age. Accuracy of the predictions was assessed by comparing the training cohort’s measurements to the 45-54 year reference cohort using t-test and one-way ANOVA.

Results: Data were collected from a total 248 patients aged 20 to 78.1 years. 80 patients within this group were aged 45 – 54 and formed the reference cohort (average±SD 49.6±2.83) and the remaining 168 eyes formed the training cohort (average age±SD 50.7±17.34). Converted values for the training set matched those of the reference cohort (average disparity±SD 0.10±0.42µm, range -0.74-1.34µm) and were not significantly different (p > 0.9). Most variability was observed with patients above 70 years of age (average disparity±SD -0.09±1.73µm, range -3.67 to 6.16µm) and central grids corresponding to the fovea (average disparity±SD 0.47±0.72µm, range -0.22 to 1.34µm).

Conclusions: Our regression model for normal age-related RGCL change can accurately convert and/or predict RGCL thickness for individuals in comparison to 50-year-equivalent reference cohort and could allow for more accurate assessment of RGCL thickness and earlier detection of significant loss in the future. Caution may be needed when applying the model in the foveal area or for patients older than 70 years.

Predicting Age-related Changes with High Accuracy using a Pattern Recognition Derived Retinal Ganglion Cell Regression Model

This abstract was presented yesterday, May 7th at the 2017 Association for Research in Vision and Opthalmology (ARVO) meetings in Baltimore, Maryland by Nayuta Yoshioka, Barbara Zangerl, Lisa Nivison-Smith, Sieu Khuu, Bryan W. Jones, Rebecca Pfeiffer, Robert Marc, and Michael Kalloniatis.

Purpose: We recently used pattern recognition analysis to show macula areas can be classified into statistically distinct clusters in accordance to their age-related retinal ganglion cell layer (RGCL) thickness change in a normal population. The aim of this study was to perform a retrospective cross-sectional analysis utilizing a large cohort of patients to establish accuracy of this model and to develop a normative dataset using a 50-year-old equivalent cohort.

Methods: Data was collected from patients seen at the Centre for Eye Health for optic nerve assessment without posterior pole disease. The grid-wise RGCL thickness was obtained from a single eye of each patient via Spectralis OCT macular scan over an 8×8 measurement grid. Measurements for patients outside the 45-54 age range (training cohort) were converted to 50-year-old equivalent value utilizing pattern recognition derived regression model which, in brief, consists of 8×8 grid clustered into 8 distinct classes according to the pattern of RGCL thickness change with age. Accuracy of the predictions was assessed by comparing the training cohort’s measurements to the 45-54 year reference cohort using t-test and one-way ANOVA.

Results: Data were collected from a total 248 patients aged 20 to 78.1 years. 80 patients within this group were aged 45 – 54 and formed the reference cohort (average±SD 49.6±2.83) and the remaining 168 eyes formed the training cohort (average age±SD 50.7±17.34). Converted values for the training set matched those of the reference cohort (average disparity±SD 0.10±0.42µm, range -0.74-1.34µm) and were not significantly different (p > 0.9). Most variability was observed with patients above 70 years of age (average disparity±SD -0.09±1.73µm, range -3.67 to 6.16µm) and central grids corresponding to the fovea (average disparity±SD 0.47±0.72µm, range -0.22 to 1.34µm).

Conclusions: Our regression model for normal age-related RGCL change can accurately convert and/or predict RGCL thickness for individuals in comparison to 50-year-equivalent reference cohort and could allow for more accurate assessment of RGCL thickness and earlier detection of significant loss in the future. Caution may be needed when applying the model in the foveal area or for patients older than 70 years.

Müller Cell Metabolic Chaos During Retinal Degeneration

We have a new publication out (direct link, open access), Müller Cell Metabolic Chaos During Retinal Degeneration authored by Rebecca PfeifferRobert Marc, Mineo Kondo, Hiroko Terasaki and Bryan W. Jones.

Abstract:

Müller cells play a critical role in retinal metabolism and are among the first cells to demonstrate metabolic changes in retinal stress or disease. The timing, extent, regulation, and impacts of these changes are not yet known. We evaluated metabolic phenotypes of Müller cells in the degenerating retina.

Retinas harvested from wild-type (WT) and rhodopsin Tg P347L rabbits were fixed in mixed aldehydes and resin embedded for computational molecular phenotyping (CMP). CMP facilitates small molecule fingerprinting of every cell in the retina, allowing evaluation of metabolite levels in single cells.

CMP revealed signature variations in metabolite levels across Müller cells from TgP347L retina. In brief, neighboring Müller cells demonstrated variability in taurine, glutamate, glutamine, glutathione, glutamine synthetase (GS), and CRALBP. This variability showed no correlation across metabolites, implying the changes are functionally chaotic rather than simply heterogeneous. The inability of any clustering algorithm to classify Müller cell as a single class in the TgP347L retina is a formal proof of metabolic variability in the present in degenerating retina.

Although retinal degeneration is certainly the trigger, Müller cell metabolic alterations are not a coherent response to the microenvironment. And while GS is believed to be the primary enzyme responsible for the conversion of glutamate to glutamine in the retina, alternative pathways appear to be unmasked in degenerating retina. Somehow, long term remodeling involves loss of Müller cell coordination and identity, which has negative implications for therapeutic interventions that target neurons alone.

Retinal Remodeling in Human Retinitis Pigmentosa

We have a new publication out (Direct Link, Free Open Access), Retinal Remodeling in Human Retinitis Pigmentosa authored by Bryan W. Jones, Rebecca Pfeiffer, Drew Ferrell, Carl Watt, Michael Marmor and Robert Marc.

Abstract: Retinitis Pigmentosa (RP) in the human is a progressive, currently irreversible neural degenerative disease usually caused by gene defects that disrupt the function or architecture of the photoreceptors. While RP can initially be a disease of photoreceptors, there is increasing evidence that the inner retina becomes progressively disorganized as the outer retina degenerates. These alterations have been extensively described in animal models, but remodeling in humans has not been as well characterized. This study, using computational molecular phenotyping (CMP) seeks to advance our understanding of the retinal remodeling process in humans. We describe cone mediated preservation of overall topology, retinal reprogramming in the earliest stages of the disease in retinal bipolar cells, and alterations in both small molecule and protein signatures of neurons and glia. Furthermore, while Müller glia appear to be some of the last cells left in the degenerate retina, they are also one of the first cell classes in the neural retina to respond to stress which may reveal mechanisms related to remodeling and cell death in other retinal cell classes. Also fundamentally important is the finding that retinal network topologies are altered. Our results suggest interventions that presume substantial preservation of the neural retina will likely fail in late stages of the disease. Even early intervention offers no guarantee that the interventions will be immune to progressive remodeling. Fundamental work in the biology and mechanisms of disease progression are needed to support vision rescue strategies.