Abstract
Purpose :
A wider appreciation for the importance of understanding the spatial biology of ocular tissues now exists. While significant focus is on transcriptomics, defining cells and processes at a protein level will be complementary and critical. Commercial approaches exist but are not designed for the distinct markers required for ocular tissues. In previous work, we developed the iterative bleaching extends multiplexity (IBEX) method which is open source and can be readily customized to achieve highly multiplexed immunohistochemistry on the same tissue section.
Methods :
The retina was dissected from three healthy post-mortem donors obtained via Moorfields Biobank (Ethics reference: 20/SW/0031-2022ETR84). Cryosections underwent cyclic immunohistochemistry, fluorescent confocal microscopy and bleaching using the IBEX technique. Following registration, image analysis and segmentation were performed using Imaris and Aivia software.
Results :
We demonstrate an optimized panel of antibodies widely available from common commercial sources and our approach for custom conjugation of ocular-specific antibodies that can be used as a resource for others in the field wanting to employ these approaches. We demonstrate using the retina that a 30-plex panel can be readily achieved (subset shown in Figure 1) on the same section. This outlines most key cellular populations and structures, including markers such as Vimentin, Iba1, HuC/D, Calbindin, Desmin, Chx10, CD44, PKCa, M/L-opsin, S-Opsin, B3-tubulin and IB4. Each antibody marker was morphologically validated for cell position and morphology before cell densities, and contact numbers were measured using Aivia software.
Conclusions :
Generating a high-content imaging dataset with IBEX allowed the imaging of almost all key cell types within human retina. While the size of the panel will not isolate every cellular subset identified by RNA sequencing, the open-source and optimized panel presented will facilitate wider access to many research groups in the field to enable a deeper assessment of a range of human retinal diseases than previously possible.
This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.