Quantitative image analysis to determine the function of selected microglia-expressed genes in retinal development and regeneration

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PROJECT SUMMARY This Idaho INBRE Administrative Supplement will establish a collaboration between an INBRE-Developmental Research Program Investigator, S Long, and an IDeA co-funded R01 principle investigator, D Mitchell. Dr. Long is a computer scientist with expertise in machine learning and computer-assisted image analyses. Dr. Mitchell is a cell biologist/immunologist with expertise in retinal development/regeneration. The project is titled, ‘Quantitative image analysis to determine the function of selected microglia-expressed genes in retinal development and regeneration’. There are three Specific Aims: Specific Aim 1. Develop a collaboration between the two investigators to enhance both projects and increase undergraduate student research opportunities. Specific Aim 2: Determine the requirement for selected microglia-expressed genes in retinal development and regeneration. Specific Aim 3: Develop an image analysis pipeline to support zebrafish retinal analyses. Microglia are the resident phagocytes in the central nervous system and engulf and degrade pathogens, apoptotic cells, and debris. In addition, these cells may be involved in retinal degenerative disease, injury, homeostasis, development, regeneration, and/or crosstalk with Müller glia. The Mitchell laboratory did transcriptome analysis of microglia/macrophage populations isolated from regenerating zebrafish retinas. From this, a shortlist of five microglia-expressed genes of interest are identified. Zebrafish mutant lines are, or will be, established for each gene. Real-time live confocal imaging will be done on wild-type, heterozygous, and homozygous zebrafish lines to record microglial dynamics in developing or regenerating retinas. The Long laboratory will develop an image analysis pipeline to automate the interpretation of the large datasets from these experiments. The analyses will quantify microglia numbers and morphology, cell death, Müller glial proliferation, hypertrophy, migration of daughter cells, and expression of neural progenitor markers. The machine learning techniques developed by the Long laboratory will relieve the bottleneck and potential biases in analysis of large image datasets from the Mitchell laboratory and allow rapid testing of microglia gene function. Strong preliminary data and investigator expertise indicate that this team will complete the proposed work. The Long-Mitchell collaboration will provide a continuum of research opportunities for students by delivering broadened student research experiences. Dr. Long has the expertise and the environment to propel students into Data Science, a needed complement for modern biological research. Undergraduate students will be supported in both the Long laboratory at the primarily undergraduate institution, Lewis-Clark State College, and the Mitchell laboratory at the research-intensive, University of Idaho.