Design approaches to expand the toolkit for building cotranscriptionally encoded RNA strand displacement circuits

Abstract

Cotranscriptionally encoded RNA strand displacement (ctRSD) circuits are an emerging tool for programmable molecular computation with potential applications spanning in vitro diagnostics to continuous computation inside living cells. In ctRSD circuits, RNA strand displacement components are continuously produced together via transcription. These RNA components can be rationally programmed through base pairing interactions to execute logic and signaling cascades. However, the small number of ctRSD components characterized to date limits circuit size and capabilities. Here, we characterize 220 ctRSD gate sequences, exploring different input, output, and toehold sequences and changes to other design parameters, including domain lengths, ribozyme sequences, and the order in which gate strands are transcribed. This characterization provides a library of sequence domains for engineering ctRSD components, i.e., a toolkit, enabling circuits with up to four-fold more inputs than previously possible. We also identify specific failure modes and systematically develop design approaches that reduce the likelihood of failure across different gate sequences. Lastly, we show ctRSD gate design is robust to changes in transcriptional encoding, opening a broad design space for applications in more complex environments. Together, these results deliver an expanded toolkit and design approaches for building ctRSD circuits that will dramatically extend capabilities and potential applications.

Engineering a cell-free biosensor signal amplification circuit with polymerase strand recycling

“…We believe the PSR circuit can be interfaced with other molecular computation circuits to expand capabilities of cell-free systems. For example, PSR could serve as an amplified output for logic gates [3, 28, 47], genelets [48, 49], co-transcriptionally activated RNA gates [50, 51], or other signal processing circuits to control complex computations in cell-free systems [52]. We also envision using PSR to amplify RNA transcriptional signals from other polymerases that are less efficient than T7 RNAP, such as E. coli RNAP, to enable robust signal generation.…”