Sprecher
Beschreibung
The design of optimal nucleic acid oligomers capable of rapid and specific isothermal binding to long single-stranded DNA or RNA sequences often exceeding a thousand bases in length (e.g., genomes, mRNA, or lncRNA), remains a significant challenge. This endeavor holds substantial implications not only for DNA nanotechnology but also for understanding fundamental biological processes and developing novel analytical systems or therapies. We addressed this challenge by studying the binding of long sequence models, such as M13mp18, to a large panel (> 50) of DNA oligomers immobilized on a label-free biosensor microarray. Our observations revealed that fewer than 10% of the oligomers complementary to the long sequence exhibited substantial binding capability. These findings unveil an unexpected hierarchy of factors influencing binding: the primary parameters are the multiplicity of partial pairing with above-average strength and the polymorphic binding of degenerate sequences, while the secondary structure of the strands plays a relevant, but secondary, role [1]. To further validate this concept, we selected a new panel of oligomer probes designed to provide specific response patterns in the presence of different genome strands. Biosensor experiments confirmed the expected behavior. Computational selection, based on both the multiplicity of binding and the strength of transient secondary structures, enabled the identification of a small fraction of optimal probes (less than 1% of complementary probes) that provided excellent discrimination capabilities. This fraction of optimal probes is further reduced when detection oligomer probes providing an amplification signal (e.g., single-nanoparticle detection) are used in addition to surface-immobilized capture oligomers. We found that, in such cases, cross-interactions between probes, mediated by polymorphic binding, must also be considered. Overall, the results of this study provide a key to cracking the code for optimal sequences in capturing and detecting low concentrations of various genomic sequences, down to single-molecule counting.
[1] Nava, G., Carzaniga, T., Casiraghi et al. (2024). Nucleic Acids Research Vol. 52, Issue 15, pp. 8661–8674.
