Aptamer Sequence Deconvolution through Microarray Technology

Aptamer, which is generated by systematic evolution of ligands by exponential enrichment (SELEX), can recognize a specific target protein with high affinity. It is selected from a single-stranded DNA or RNA library, and the typical length is between 60 to 200 nucleotides, which may consist of some redundant regions not responsible for protein targeting. Therefore, how to determine the major protein-targeting motif of a selected aptamer is one of the most essential post-SELEX tasks to improve aptamer's affinity. Yet this sequence-mining process is tedious and costly. Here, we demonstrate a high-throughput, microarray-based method to identify the major protein-targeting motif of an aptamer. An aptamer microarray with 12,000 features was created to deconvolute the sequence information of six anti-prothrombin aptamers. All the features comprised truncated probes with 23 to 35 nucleotides, which represented sub-motifs of six anti-prothrombin aptamers. These were designed by a “base-by-base shift” strategy and in situ synthesized on the microarray. The major protein-targeting motifs and the optimal lengths for the aptamers were accordingly determined through this microarray platform. Also, the structural and functional characteristics between the optimized aptamers and their parent sequences were compared in support of the microarray approach. In addition, we used the microarray and in silico docking approaches to investigate the targeting motif of an aptamer recognizing influenza hemagglutinin. The optimized motif obtained from the microarray approach correlated closely with the in silico model. This study indicates that the proposed microarray methodology can accelerate the aptamer sequence mining for post-SELEX optimization.