Enzyme-Assisted High Throughput Sequencing of an Expanded Genetic Alphabet at Single Base Resolution

Abstract Many efforts have sought to apply laboratory in vitro evolution (LIVE) to natural nucleic acid (NA) scaffolds to directly evolve functional molecules. However, synthetic biology can move beyond natural NA scaffolds to create molecular systems whose libraries are far richer reservoirs of functionality than natural NAs. For example, "artificially expanded genetic information systems" (AEGIS) add up to eight nucleotides to the four found in standard NA. Even in its simplest 6-letter versions, AEGIS adds functional groups, information density, and folding motifs that natural NA libraries lack. To complete this vision, however, tools are needed to sequence molecules that are created by AEGIS LIVE. Previous sequencing approaches, including approaches from our laboratories, exhibited limited performance and lost many sequences in diverse library mixtures. Here, we present a new approach that enzymatically transforms the target AEGIS DNA. With higher transliteration efficiency and fidelity, this Enzyme-Assisted Sequencing of Expanded Genetic Alphabet (ESEGA) approach produces substantially better sequences of 6-letter (AGCTZP) DNA than previous transliteration approaches. Therefore, ESEGA facilitates precise analysis of libraries, allowing 'next-generation deep sequencing' to accurately quantify the sequences of 6-letter DNA molecules at single base resolution. We then applied ESEGA to three tasks: (a) defining optimal conditions to perform 6-nucleotide PCR (b) evaluating the fidelity of 6-nucleotide PCR with various DNA polymerases, and (c) extending that evaluation to AEGIS components functionalized with alkynyl and aromatic groups. No other approach at present has this scope, allowing this work to be the next step towards exploiting the potential of expanded DNA alphabets in biotechnology.