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Lin F, Lin ST, Wang J, Geisert EE. Optimizing retinal ganglion cell nuclear staining for automated cell counting. Exp Eye Res 2024; 242:109881. [PMID: 38554800 PMCID: PMC11055661 DOI: 10.1016/j.exer.2024.109881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Revised: 03/25/2024] [Accepted: 03/27/2024] [Indexed: 04/02/2024]
Abstract
The retinal ganglion cells (RGCs) serve as the critical pathway for transmitting visual information from the retina to the brain, yet they can be dramatically impacted by diseases such as glaucoma. When investigating disease processes affecting RGCs in mouse models, accurately quantifying affected cells becomes essential. However, the use of pan RGC markers like RBPMS or THY1 presents challenges in accurate total cell counting. While Brn3a serves as a reliable RGC nuclear marker for automated counting, it fails to encompass all RGC subtypes in mice. To address this limitation and enable precise automated counting, our research endeavors to develop a method for labeling nuclei in all RGC subtypes. Investigating RGC subtypes labeled with the nuclear marker POU6F2 revealed that numerous RGCs unlabeled by Brn3a were, in fact, labeled with POU6F2. We hypothesize that using antibodies against both Brn3a and POU6F2 would label virtually all RGC nuclei in the mouse retina. Our experiments confirmed that staining retinas with both markers resulted in the labeling of all RGCs. Additionally, when using the cell body marker RBPMS known to label all mouse RGCs, all RBPMS-labeled cells also exhibited Brn3a or POU6F2 labeling. This combination of Brn3a and POU6F2 antibodies provides a pan-RGC nuclear stain, facilitating accurate automated counting by labeling cell nuclei in the retina.
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Affiliation(s)
- Fangyu Lin
- Department of Ophthalmology, Emory University, 1365B Clifton Road NE, Atlanta, GA, 30322, USA
| | - Su-Ting Lin
- Department of Ophthalmology, Emory University, 1365B Clifton Road NE, Atlanta, GA, 30322, USA
| | - Jiaxing Wang
- Department of Ophthalmology, Emory University, 1365B Clifton Road NE, Atlanta, GA, 30322, USA
| | - Eldon E Geisert
- Department of Ophthalmology, Emory University, 1365B Clifton Road NE, Atlanta, GA, 30322, USA.
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Hedberg-Buenz A, Meyer KJ, van der Heide CJ, Deng W, Lee K, Soukup DA, Kettelson M, Pellack D, Mercer H, Wang K, Garvin MK, Abramoff MD, Anderson MG. Biological Correlations and Confounders for Quantification of Retinal Ganglion Cells by Optical Coherence Tomography Based on Studies of Outbred Mice. Transl Vis Sci Technol 2022; 11:17. [PMID: 36135979 PMCID: PMC9513741 DOI: 10.1167/tvst.11.9.17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 08/02/2022] [Indexed: 01/28/2023] Open
Abstract
Purpose Despite popularity of optical coherence tomography (OCT) in glaucoma studies, it's unclear how well OCT-derived metrics compare to traditional measures of retinal ganglion cell (RGC) abundance. Here, Diversity Outbred (J:DO) mice are used to directly compare ganglion cell complex (GCC) thickness measured by OCT to metrics of retinal anatomy measured ex vivo with retinal wholemounts and optic nerve histology. Methods J:DO mice (n = 48) underwent fundoscopic and OCT examinations, with automated segmentation of GCC thickness. RGC axons were quantified from para-phenylenediamine-stained optic nerve cross-sections and somas from BRN3A-immunolabeled retinal wholemounts, with total inner retinal cellularity assessed by TO-PRO and subsequent hematoxylin staining. Results J:DO tissues lacked overt disease. GCC thickness, RGC abundance, and total cell abundance varied broadly across individuals. GCC thickness correlated significantly to RGC somal density (r = 0.58) and axon number (r = 0.44), but not total cell density. Retinal area and nerve cross-sectional area varied widely. No metrics were significantly influenced by sex. In bilateral comparisons, GCC thickness (r = 0.95), axon (r = 0.72), and total cell density (r = 0.47) correlated significantly within individuals. Conclusions Amongst outbred mice, OCT-derived measurements of GCC thickness correlate significantly to RGC somal and axon abundance. Factors limiting correlation are likely both biological and methodological, including differences in retinal area that distort sampling-based estimates of RGC abundance. Translational Relevance There are significant-but imperfect-correlations between GCC thickness and RGC abundance across genetic contexts in mice, highlighting valid uses and ongoing challenges for meaningful use of OCT-derived metrics.
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Affiliation(s)
- Adam Hedberg-Buenz
- VA Center for the Prevention and Treatment of Visual Loss, Iowa City VA Health Care System, Iowa City, IA, USA
- Department of Molecular Physiology and Biophysics, University of Iowa, Iowa City, IA, USA
| | - Kacie J. Meyer
- Department of Molecular Physiology and Biophysics, University of Iowa, Iowa City, IA, USA
| | - Carly J. van der Heide
- Department of Molecular Physiology and Biophysics, University of Iowa, Iowa City, IA, USA
| | - Wenxiang Deng
- VA Center for the Prevention and Treatment of Visual Loss, Iowa City VA Health Care System, Iowa City, IA, USA
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA
| | - Kyungmoo Lee
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA
| | - Dana A. Soukup
- Department of Molecular Physiology and Biophysics, University of Iowa, Iowa City, IA, USA
| | - Monica Kettelson
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
| | - Danielle Pellack
- Department of Molecular Physiology and Biophysics, University of Iowa, Iowa City, IA, USA
| | - Hannah Mercer
- Department of Molecular Physiology and Biophysics, University of Iowa, Iowa City, IA, USA
| | - Kai Wang
- Department of Biostatistics, University of Iowa, Iowa City, IA, USA
| | - Mona K. Garvin
- VA Center for the Prevention and Treatment of Visual Loss, Iowa City VA Health Care System, Iowa City, IA, USA
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA
| | - Michael D. Abramoff
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA
- Department of Ophthalmology and Visual Sciences, University of Iowa, Iowa City, IA, USA
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
| | - Michael G. Anderson
- VA Center for the Prevention and Treatment of Visual Loss, Iowa City VA Health Care System, Iowa City, IA, USA
- Department of Molecular Physiology and Biophysics, University of Iowa, Iowa City, IA, USA
- Department of Ophthalmology and Visual Sciences, University of Iowa, Iowa City, IA, USA
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