SPARK-seq: a high-throughput platform for aptamer discovery and kinetic profiling

Cell-based SELEX is a versatile technique for discovering large anount of aptamers capable of distinguishing specific cell types and identifying cell type-specific biomarkers without prior molecular knowledge. However, systematically mapping large-scale aptamer-protein interactions remains a major challenge. Here, we report the development of Single-cell Perturbation-driven Aptamer Recognition and Kinetics Sequencing (SPARK-seq), a high-throughput platform that integrates single-cell mRNA and aptamer sequencing with CRISPR-based surface protein perturbation. SPARK-seq leverages the sequence-readability of aptamers to identify thousands of aptamer-protein interactions in a single experiment, far surpassing traditional methods that typically yield only one or two such interactions per experiment. By directly quantifying the aptamer-target kinetic property of dissociation rate (Koff), SPARK-seq increases the sensitivity of aptamer discovery for low-abundance targets and prioritizes aptamers with slow off-rate. Building on this, we further developed Single-cell Perturbation-Aptamer Recognition and Targeted Aptamer-generation algorithm (SPARTA), a hybrid framework that integrates statistical methods and deep learning to accelerate aptamer identification and de novo generation, while providing detailed kinetic insights. Together, SPARK-seq and SPARTA establish a robust platform for high-efficiency aptamer discovery, advancing precision therapeutics and diagnostic development.