Purpose: To compare the timing and efficiency of the development of non-human primate (NHP) derived retinal organoids in comparison to those derived from human embryonic stem cells. Methods: Human embryonic stem cells (hESCs) and induced-pluripotent stem cells (rhiPSCs) derived from non-human primates (Macaca mulatta) were differentiated into retinal organoids by using an established differentiation protocol. Briefly, embryoid bodies were formed from pluripotent stem cells and induced into a neural lineage with neural induction media with the addition of BMP4. Thereafter, self-formation of optic vesicles was allowed to form in a 2D culture in retinal differentiation media (RDM). Optic vesicles were then manually harvested and cultured in suspension in 3D-RDM media until analysis. Differences in the timing of differentiation and efficiency of retinal organoid development were assessed by light microscopy, electron microscopy, immunocytochemistry, and single-cell transcriptomics. Results: Generation of retinal organoids was achieved from both human and several NHP pluripotent stem cells lines. All rhiPSC lines resulted in retinal differentiation with the formation of optic vesicle-like structures similar to what has been observed in hESC retinal organoids. NHP retinal organoids had laminated structure and were composed of mature retinal cell types including cone and rod photoreceptors. Single cell RNA sequencing was conducted at two time points, which allowed identification of cell types and characterization of developmental trajectory in the developing organoid. Important differences between rhesus and human cells were measured regarding the timing and efficiency of retinal organoid differentiation. While the culture of NHP-derived iPSCs is relatively difficult compared to human stem cells, the generation of retinal organoids is feasible and may be less time consuming due to an intrinsically faster timing of retinal differentiation. Conclusions: Retinal organoids produced from iPSCs derived from Rhesus monkey using established protocols differentiate through the stages of organoid development faster than those derived from human stem cells. The production of NHP retinal organoids may be advantageous to reduce experimental time and cost for basic biology studies in retinogenesis as well as for preclinical trials in NHPs studying retinal allograft transplantation.

Motivation: There are current programs and plugins that automatically count the number of cells in a given image. However, many of these processes are not entirely automatic, as they require user input to specify a region of interest and are also frequently inaccurate. Results: This project presents laocoön , a Python package specifically designed to automatically and efficiently count the number of fluorescently-labelled cells in images. This package not only allows for reliable cell counting, but returns the proportion of cells in each cell cycle relative to all the cells in the DAPI channel, which is currently used for research purposes, but could ultimately be utilized for clinical purposes. Availability and Implementation: This package, its corresponding execution instructions, and further information about the underlying algorithms, are currently available in the GitHub repository https://github.com/edukait/laocoon under the MIT license and can be run on the command terminal of any operating system. Alternatively, laocoön is available in the Python Package Index (PyPi), so the user can use the pip command to immediately download the package. Contact: kaitlin.y.