Combining Selenocystine Based Fluorescence Assay with Structural Prediction for Enhanced Detection and Analysis of Cystine Stone Pathology

BackgroundCystine stones, a rare but recurrent type of kidney stones, primarily result from cystinuria, an inherited disorder caused by mutations in the genes SLC3A1 and SLC7A9, which encode renal cystine transporters. These mutations impair cystine reabsorption, resulting in elevated urinary cystine concentrations and stone formation. Current diagnostic methods are limited, particularly for detecting molecular-level dysfunctions. We aimed to develop a nonradioactive method for functional assessment of cystine transporters and mutation-specific pathologies. MethodsWe designed an innovative diagnostic approach combining a selenocystine-based fluorescence assay with structural predictions using AlphaFold to rapidly and accurately assess cystine transporter function and the molecular impacts of genetic mutations. ResultsOur assay demonstrated comparable transport efficiencies of cystine and selenocystine by the SLC3A1/SLC7A9 complex, and effectively differentiated mild, moderate, and severe functional impairments associated with known clinical mutations, including A354T and P482L. Structural modeling further provided mechanistic insights into mutation-induced dysfunctions. ConclusionThis integrated approach--combining a sensitive selenocystine fluorescence assay with AI-powered structural analysis--enables rapid, precise diagnosis of cystinuria variants and delivers mechanistic insights for personalized therapeutic strategies.