(175ac) High-Accuracy Nanopore Sequencing of 6-Letter DNA for Synthetic Biology Applications

Synthetic biology has long aimed at expanding the DNA alphabet from four letters (ATGC) to six letters (ATGCXY). Several sets of synthetic nucleotides that base pair orthogonally to A:T/G:C pairs have been developed and have been shown to be tolerated (to various extents) by biological systems. These synthetic nucleotides, known as unnatural base pairing xeno-nucleic acids (ubp XNAs), are being explored for various applications, with genetic code expansion as a conspicuous example. Although implementing ubp XNAs into synthetic biology could be transformative, challenges in reading (sequencing) and amplification (PCR) of sequences containing these ubp XNAs have limited their impact. Here, we present machine learning models for high-accuracy XNA sequencing (>98%) on commercially available devices. Next, we apply these robust single-molecule sequencing methods to study the replication fidelity of XNAs in vitro. We show high-throughput screening of various conditions to improve XNA retention during PCR. Finally, we present strain engineering efforts to pursue applications of expanded genetic alphabets in vivo. By modernizing the synthetic biology toolkit available for XNAs, we look to improve access and application of XNAs to therapeutic, synthetic biology, and chemical biology research.