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Retinal pigment epithelial integrity is compromised in the developing albino mouse retina.

The Journal of comparative neurology | 2016

In the developing murine eye, melanin synthesis in the retinal pigment epithelium (RPE) coincides with neurogenesis of retinal ganglion cells (RGCs). Disruption of pigmentation in the albino RPE is associated with delayed neurogenesis in the ventrotemporal retina, the source of ipsilateral RGCs, and a reduced ipsilateral RGC projection. To begin to unravel how melanogenesis and the RPE regulate RGC neurogenesis and cell subpopulation specification, we compared the features of albino and pigmented mouse RPE cells during the period of RGC neurogenesis (embryonic day, E, 12.5 to 18.5) when the RPE is closely apposed to developing RGC precursors. At E12.5 and E15.5, although albino and pigmented RPE cells express RPE markers Otx2 and Mitf similarly, albino RPE cells are irregularly shaped and have fewer melanosomes compared with pigmented RPE cells. The adherens junction protein P-cadherin appears loosely distributed within the albino RPE cells rather than tightly localized on the cell membrane, as in pigmented RPE. Connexin 43 (gap junction protein) is expressed in pigmented and albino RPE cells at E13.5 but at E15.5 albino RPE cells have fewer small connexin 43 puncta, and a larger fraction of phosphorylated connexin 43 at serine 368. These results suggest that the lack of pigment in the RPE results in impaired RPE cell integrity and communication via gap junctions between RPE and neural retina during RGC neurogenesis. Our findings should pave the way for further investigation of the role of RPE in regulating RGC development toward achieving proper RGC axon decussation. J. Comp. Neurol. 524:3696-3716, 2016. © 2016 Wiley Periodicals, Inc.

Pubmed ID: 27097562 RIS Download

Research resources used in this publication

Additional research tools detected in this publication

None found

Associated grants

  • Agency: NEI NIH HHS, United States
    Id: R01 EY015290
  • Agency: NEI NIH HHS, United States
    Id: R01 EY012736
  • Agency: NCI NIH HHS, United States
    Id: P30 CA013696
  • Agency: NEI NIH HHS, United States
    Id: P30 EY019007
  • Agency: NEI NIH HHS, United States
    Id: R21 EY023714

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This is a list of tools and resources that we have found mentioned in this publication.


connexin 43 (C-20) (antibody)

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ZO-1 Polyclonal Antibody (antibody)

RRID:AB_2533456

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B6(Cg)-Tyrc-2J/J (organism)

RRID:IMSR_JAX:000058

Mus musculus with name B6(Cg)-Tyrc-2J/J from IMSR.

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ZIC2 (antibody)

RRID:AB_2315623

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connexin 43 (C-20) (antibody)

RRID:AB_638639

This polyclonal targets connexin 43 (C-20)

View all literature mentions

Na+/K+-ATPase alpha (H-300) (antibody)

RRID:AB_2290063

This polyclonal targets ATP1A3, ATP1A1, ATP1A2

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Monoclonal Anti-Vinculin antibody produced in mouse (antibody)

RRID:AB_477629

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Human Otx2 Affinity Purified Polyclonal Ab (antibody)

RRID:AB_2157172

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View all literature mentions

ImageJ (software resource)

RRID:SCR_003070

Open source Java based image processing software program designed for scientific multidimensional images. ImageJ has been transformed to ImageJ2 application to improve data engine to be sufficient to analyze modern datasets.

View all literature mentions

Neurolucida (software resource)

RRID:SCR_001775

Neurolucida is advanced scientific software for brain mapping, neuron reconstruction, anatomical mapping, and morphometry. Since its debut more than 20 years ago, Neurolucida has continued to evolve and has become the worldwide gold-standard for neuron reconstruction and 3D mapping. Neurolucida has the flexibility to handle data in many formats: using live images from digital or video cameras; stored image sets from confocal microscopes, electron microscopes, and scanning tomographic sources, or through the microscope oculars using the patented LucividTM. Neurolucida controls a motorized XYZ stage for integrated navigation through tissue sections, allowing for sophisticated analysis from many fields-of-view. Neurolucidas Serial Section Manager integrates unlimited sections into a single data file, maintaining each section in aligned 3D space for full quantitative analysis. Neurolucidas neuron tracing capabilities include 3D measurement and reconstruction of branching processes. Neurolucida also features sophisticated tools for mapping delineate and map anatomical regions for detailed morphometric analyses. Neurolucida uses advanced computer-controlled microscopy techniques to obtain accurate results and speed your work. Plug-in modules are available for confocal and MRI analysis, 3D solid modeling, and virtual slide creation. The user-friendly interface gives you rapid results, allowing you to acquire data and capture the full 3D extent of neurons and brain regions. You can reconstruct neurons or create 3D serial reconstructions directly from slides or acquired images, and Neurolucida offers full microscope control for brightfield, fluorescent, and confocal microscopes. Its added compatibility with 64-bit Microsoft Vista enables reconstructions with even larger images, image stacks, and virtual slides. Adding the Solid Modeling Module allows you to rotate and view your reconstructions in real time. Neurolucida is available in two separate versions Standard and Workstation. The Standard version enables control of microscope hardware, whereas the Workstation version is used for offline analysis away from the microscope. Neurolucida provides quantitative analysis with results presented in graphical or spreadsheet format exportable to Microsoft Excel. Overall, features include: - Tracing Neurons - Anatomical Mapping - Image Processing and Analysis Features - Editing - Morphometric Analysis - Hardware Integration - Cell Analysis - Visualization Features Sponsors: Neurolucida is supported by MBF Bioscience.

View all literature mentions

CellProfiler Image Analysis Software (data processing software)

RRID:SCR_007358

Software tool to enable biologists without training in computer vision or programming to quantitatively measure phenotypes from thousands of images automatically. It counts cells and also measures the size, shape, intensity and texture of every cell (and every labeled subcellular compartment) in every image. It was designed for high throughput screening but can perform automated image analysis for images from time-lapse movies and low-throughput experiments. CellProfiler has an increasing number of algorithms to identify and measure properties of neuronal cell types.

View all literature mentions