Targeted Selection of Aptamer Complementary Elements toward Rapid Development of Aptamer Transducers.
Tim HachigianDrew LysneElton GraugnardJeunghoon LeePublished in: The journal of physical chemistry. B (2023)
Biosensing using aptamers has been a recent interest for their versatility in detecting many different analytes across a wide range of applications, including medical and environmental applications. In our last work, we introduced a customizable aptamer transducer (AT) that could successfully feed-forward many different output domains to target a variety of reporters and amplification reaction networks. In this paper, we explore the kinetic behavior and performance of novel ATs by modifying the aptamer complementary element (ACE) chosen based on a technique for exploring the ligand-binding landscape of duplexed aptamers. Using published data, we selected and constructed several modified ATs that contain ACEs with varying length, position of the start sites, and position of single mismatches, whose kinetic responses were tracked with a simple fluorescence reporter. A kinetic model for ATs was derived and used to extract the strand-displacement reaction constant k 1 and the effective aptamer dissociation constant K d,eff , allowing us to calculate a relative performance metric, k 1 / K d,eff . Comparing our results with the predictions based on the literature data, we provide useful insight into the dynamics of the adenosine AT's duplexed aptamer domain and suggest a high-throughput approach for future ATs to be developed with improved sensitivity. The performance of our ATs showed a moderate correlation to those predicted by the ACE scan method. Here, we find that predicted performance based on our ACE selection method was moderately correlated to our AT's performance.
Keyphrases
- gold nanoparticles
- label free
- sensitive detection
- magnetic nanoparticles
- high throughput
- angiotensin ii
- angiotensin converting enzyme
- healthcare
- crispr cas
- big data
- computed tomography
- systematic review
- single cell
- electronic health record
- machine learning
- randomized controlled trial
- wastewater treatment
- magnetic resonance
- single molecule
- data analysis
- contrast enhanced