Dec 2, 2024
1:30pm - 2:00pm
Hynes, Level 1, Room 103
Valeria Milam1,Mary Catherine Adams1,Steven Ochoa1
Georgia Institute of Technology1
Valeria Milam1,Mary Catherine Adams1,Steven Ochoa1
Georgia Institute of Technology1
Single-stranded DNA ligands called aptamers are self-folded, single-stranded oligonucleotide sequences that act as a probe or ligand for a particular non-nucleotide target. While the nature of aptamer-target binding is largely unexplored, aptamers are often considered to be promising substitutes for antibodies which are more expensive and susceptible to irreversible denaturation. To find suitable aptamer candidates for our protein targets we developed a competition-based screening platform called CompELS or “Competition-Enhanced Ligand Screening” to circumvent complications arising from the conventional, yet laborious evolutionary aptamer screening approach called SELEX or "Systematic Evolution of Ligands by EXponential enrichment." To gain insight into the CompELS selection process itself, libraries were barcoded to mark the cycle number a particular aptamer candidate was selected. Following the completion of CompELS, the screening library, target-bound “winners” as well as nonbinding “losers” were evaluated using high throughput, next generation sequencing (NGS) analysis. Data analysis indicates a majority of the screening library emerge as losers, but the winners are numerous and surprisingly diverse in their sequence composition. Moreover, competition appears to play a role in selection since relatively smaller percentages of barcoded winners ultimately survive the first few selection rounds. Finally, the lack of overlap of winners with the screening library suggests that the barcoded sequence data itself is likely incomplete with many sequences lost either during sequence recovery steps or during multi-step, chip-based sequencing analysis. Thus, while NGS serves as an exciting tool for aptamer candidate analysis and future library design efforts, the possibility of an information gap – even in big data sets – is likely overlooked in many aptamer screening studies. Ongoing work includes additional one-pot competition experiments to rank aptamers as effective ligands and to characterize binding affinities of select winners.