Synthetic Biology
RADARS
Programmable eukaryotic protein synthesis with RNA sensors by harnessing ADAR
RADARS concept for programmable RNA sensing. The sensor RNA contains an optional marker protein (blue), a guide RNA region with a UAG stop (red octagon), and a downstream cargo protein (green). Sensor association with a target RNA (pink) forms a duplex with an A–C mismatch, which serves as a substrate for RNA editing by ADAR protein (brown). RNA editing converts the UAG stop codon to UIG (green triangle), allowing translation of the cargo (green protein).
Programmable approaches to sense and respond to the presence of specific RNAs in biological systems have broad applications in research, diagnostics, and therapeutics. Here we engineer a programmable RNA-sensing technology, reprogrammable ADAR sensors (RADARS), which harnesses RNA editing by adenosine deaminases acting on RNA (ADAR) to gate translation of a cargo protein by the presence of endogenous RNA transcripts. Introduction of a stop codon in a guide upstream of the cargo makes translation contingent on binding of an endogenous transcript to the guide, leading to ADAR editing of the stop codon and allowing translational readthrough. We show that RADARS are functional as either expressed DNA or synthetic mRNA and with either exogenous or endogenous ADAR. We apply RADARS in multiple contexts, including tracking transcriptional states, RNA-sensing-induced cell death, cell-type identification, and control of synthetic mRNA translation.
TRACE
Continuous and targeted mutagenesis in human cells
Schematic of TRACE. The recombinant fusion of cytidine deaminase and T7 RNAP recognizes a T7 promoter inserted upstream of a target gene. As the T7 RNAP transcribes DNA, the deaminase introduces point mutations (red star).
Methods for studying the dynamics of eukaryotic cells, such as directed evolution, lineage tracing, and molecular recording, depend on developing tools for targeted, continuous mutagenesis1. However, existing tools rely on non-physiological environments, rapidly saturate mutagenized sites, or have been adapted only to bacterial or yeast systems.
To enable continuous, targeted mutagenesis in eukaryotic cells, we developed TRACE, a system that combines the DNA processivity of bacteriophage DNA-dependent RNAPs with the somatic hypermutation capability of cytidine deaminases. By combining T7 RNAP with a cytidine deaminase, TRACE could continuously diversify DNA nucleotides downstream of a T7 promoter. We anticipate that TRACE is well suited to serve as a long-term cellular recorder owing to its continuity, its ability to be engineered, and its wide recording window.
RNA timestamps
Identifying the age of RNA molecules
Schematic of the timestamps approach, consisting of editing arrays of adenosines (blue dots) and several MS2 step loops in the 3′ UTR of an mRNA. In the presence of an MCP–ADAR fusion (MCP, blue ellipses; ADAR, yellow hexagon), timestamps are edited over time by catalytic conversion of adenosine to inosine (red dots).
Current approaches to single-cell RNA sequencing (RNA-seq) provide only limited information about the dynamics of gene expression. Here we present RNA timestamps, a method for inferring the age of individual RNAs in RNA-seq data by exploiting RNA editing.
To introduce timestamps, we tag RNA with a reporter motif consisting of multiple MS2 binding sites that recruit the adenosine deaminase ADAR2 fused to an MS2 capsid protein. ADAR2 binding to tagged RNA causes A-to-I edits to accumulate over time, allowing the age of the RNA to be inferred with hour-scale accuracy. By combining observations of multiple timestamped RNAs driven by the same promoter, we can determine when the promoter was active. We demonstrate that the system can infer the presence and timing of multiple past transcriptional events. Finally, we apply the method to cluster single cells according to the timing of past transcriptional activity. RNA timestamps will allow the incorporation of temporal information into RNA-seq workflows.