Alexandra Adams

Aptamers are short, single stranded nucleic acids, which exhibit a unique ability to form complex tertiary structures and bind to molecules, much like antibodies. Using aptamers, we can solve challenges in biosensing and diagnostic applications by developing novel biorecognition elements.

Split aptamer biosensors offer exceptionally low background by assembling only in the presence of a target analyte; however, their performance is frequently limited by the lack of robust design rules for selecting effective split sites. Existing approaches largely rely on heuristic, structure-based assumptions that are poorly validated and often yield suboptimal signal. Using our massively parallel aptamer performance analyzer (MAPA) platform, we performed comprehensive mutant analysis of the binding region of the fluorogenic DNA aptamer Lettuce, informed by its three-dimensional structure. Dimensionality reduction and clustering of the resulting sequence–function landscape revealed mutation-tolerant elements within the binding domain that are suitable for splitting while preserving fluorophore activation. Sensors constructed using these non-intuitive split sites, exhibited a nearly four-fold improvement in fluorescence signal for SARS-CoV-2 RNA detection compared to a prior split-Lettuce design. The same split architecture also enabled robust detection of high-pathogenicity H5Nx avian influenza RNA. These results demonstrate that large-scale, data-driven interrogation of aptamer sequence–function relationships provide a generalizable pathway to rationally engineer split aptamer biosensors and overcome the limitations of trial-and-error design.