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Purification of post-transcriptionally modified tRNAs for enhanced cell-free translation systems

Kalb, E.; Alejo, J.; Dias-Fields, L.; Knudson, I.; Davisson, J.; Maldonado, E.; Chattrakun, K.; Lin, S.; Schepartz, A.; Zhang, S.; Blanchard, S.; Engelhart, A. E.; Adamala, K. P.

2025-06-10 biochemistry
10.1101/2025.06.10.658963 bioRxiv
Show abstract

Transfer RNAs (tRNAs) are utilized by the ribosome to decode the nucleic acid alphabet. tRNA structure, stability, aminoacylation efficiency, and decoding efficacy are governed by their extensive post-transcriptional modifications. In most studies, individual tRNAs are generated using in vitro transcription, which produces tRNAs devoid of these critical site-specific modifications, negatively affecting translation yields and fidelity. To address this, we have developed a purification method which couples tRNA overexpression to DNA hybridization-based purification. Using this approach, we produced native tRNAs from E. coli in high yield and purity while retaining their complement of native post-transcriptional modifications and translational activity. We extend this technique to the purification of [Formula] and [Formula], tRNAs of critical importance for genetic code expansion. We confirmed that both [Formula] and [Formula] contain native E. coli post-transcriptional modifications and provide the first complete modification profiles of each. Moreover, we found that in vivo-generated [Formula] significantly outperforms its in vitro-generated counterpart in amber codon suppression in cell-free translation reactions. Finally, we purified an engineered variant of E. coli [Formula], extending our studies to synthetic tRNAs. We present a flexible method which generates modified tRNAs in high yield and purity, addressing a critical and persistent challenge in RNA biochemistry. This toolkit enables future structural and cell-free studies through scalable access to native and engineered tRNAs, advancing the broader field of translation and synthetic biology.

Published in Nucleic Acids Research (predicted rank #3) · training set

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