Poster presented at CellBio 2025 in Philadelphia, PA. December 2025Abstract:Adenosine deaminase (ADA) deficiency causes severe combined immunodeficiency, and current treatments include enzyme replacement therapy with immunogenic bovine proteins. To develop improved therapeutic variants, robust model systems are needed for testing rationally designed enzymes in vivo. We used Zoogle (zoogle.arcadiascience.com), a computational dataset that selects model organisms based on conserved protein characteristics rather than sequence similarity, to identify Chlamydomonas reinhardtii as an optimal system for studying human ADA1 function. This approach can identify effective models that traditional phylogenetic methods might overlook. We characterized Chlamydomonas ADA1 mutants and found clear phenotypic defects in motility and cellular metabolism, particularly altered starch accumulation under nutrient stress. We established quantitative phenotyping approaches, including high-throughput motility tracking, metabolic profiling via Raman spectroscopy, and biochemical staining to assess cellular function. These multi-modal readouts provided robust, reproducible measures of ADA1 activity in living cells. We're validating this system using wild-type human ADA1 and candidate variants designed through machine learning approaches to enhance stability and improve therapeutic properties. Initial results demonstrate that the algal system can detect functional differences in ADA1 variants, establishing a platform for screening computationally designed proteins. This approach enables systematic evaluation of engineered enzymes in a physiologically relevant cellular context. Our work establishes Chlamydomonas as an effective model for human metabolic enzymes and demonstrates the power of protein characteristic-based organism selection over traditional phylogenetic approaches. This validation platform enables rapid, cost-effective screening of designed therapeutic proteins before advancing to mammalian studies, potentially accelerating the development of next-generation enzyme replacement therapies for genetic diseases.