June 2017
Volume 58, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2017
Automated Quantification of Subcellular Structures in the RPE: Lipid Droplets, Autophagic Vacuoles, and Lipofuscin
Author Affiliations & Notes
  • Feriel K. Presswalla
    Ophthalmology & Visual Science, University of Michigan Kellogg Eye Center, Ann Arbor, Michigan, United States
  • Qitao Zhang
    Ophthalmology & Visual Science, University of Michigan Kellogg Eye Center, Ann Arbor, Michigan, United States
  • David N Zacks
    Ophthalmology & Visual Science, University of Michigan Kellogg Eye Center, Ann Arbor, Michigan, United States
  • Debra A Thompson
    Ophthalmology & Visual Science, University of Michigan Kellogg Eye Center, Ann Arbor, Michigan, United States
  • Jason Miller
    Ophthalmology & Visual Science, University of Michigan Kellogg Eye Center, Ann Arbor, Michigan, United States
  • Footnotes
    Commercial Relationships   Feriel Presswalla, None; Qitao Zhang, None; David Zacks, None; Debra Thompson, None; Jason Miller, None
  • Footnotes
    Support  Research to Prevent Blindness Core Facility Grant, Kellogg Eye Center Pre-Residency Fellowship
Investigative Ophthalmology & Visual Science June 2017, Vol.58, 1041. doi:
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      Feriel K. Presswalla, Qitao Zhang, David N Zacks, Debra A Thompson, Jason Miller; Automated Quantification of Subcellular Structures in the RPE: Lipid Droplets, Autophagic Vacuoles, and Lipofuscin. Invest. Ophthalmol. Vis. Sci. 2017;58(8):1041.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : The abundance of subcellular structures changes in response to retinal pigment epithelial (RPE) phagocytosis of photoreceptor outer segments (OS). To quantify these structures in an unbiased way, we developed macros in the ImageJ/Fiji image analysis environment that distinguish and count 3 dissimilar structures: well-circumscribed adipocyte differentiation related protein (ADRP)-marked lipid droplets, indistinct LC3-marked autophagic puncta, and amorphous deposits of lipofuscin that coexist with other sources of spectrally-similar autofluorescence.

Methods : The code for ADRP puncta quantification is based on adjustments to the 3D Spot Segmentation plugin developed by Thomas Boudier. LC3 segmentation was approached with both difference of gaussian (DoG) blurring and Thorsten Wagner’s nanoparticle tracking analysis (NTA) background removal tool, which simultaneously reduces homogenous background while reinforcing areas of high-contrast, regardless of absolute local intensity. For lipofuscin, imaging with multiple emission windows enabled separation of lipofuscin from other sources of autofluorescence. Scripts were run on human fetal RPE immunofluorescence images and trends were evaluated against a manualized quantification method.

Results : Our Fiji-based macro quantification of ADRP, LC3, and lipofuscin proved reproducible and accurate compared to manual counts. Further, the total time needed to quantify each image was cut by at least half. Use of a modified LC3 immunofluorescence protocol combining two monoclonal antibodies with optimized permeabilization generated cleaner images and increased analysis accuracy. Separate NTA and DoG scripts each generated LC3 puncta counts, but averaging these counts and then normalizing to the total intensity for each individual image provided the most reproducible assessment of autophagy vacuole number. The accuracy of lipofuscin quantification was improved by masking the autofluoresence of OS adherent to the apical surface of the cultures using indirect immunofluorescence labeling of rhodopsin.

Conclusions : Our customizable ImageJ/Fiji macros can quantify lipid droplets, autophagic vacuoles, and lipofuscin, all important RPE downstream processes of OS phagocytosis, with a higher degree of efficiency and impartiality than can be achieved manually.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.

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