Deep generative design of RNA aptamers using structural predictions.

RNAs represent a class of programmable biomolecules capable of performing diverse biological functions. Recent studies have developed accurate RNA three-dimensional structure prediction methods, which may enable new RNAs to be designed in a structure-guided manner. Here, we develop a structure-to-sequence deep learning platform for the de novo generative design of RNA aptamers.

Synthetic genetic circuits to uncover the OCT4 trajectories of successful reprogramming of human fibroblasts.

Reprogramming human fibroblasts to induced pluripotent stem cells (iPSCs) is inefficient, with heterogeneity among transcription factor (TF) trajectories driving divergent cell states. Nevertheless, the impact of TF dynamics on reprogramming efficiency remains uncharted. We develop a system that accurately reports OCT4 protein levels in live cells and use it to reveal the trajectories of OCT4 in successful reprogramming.

Autocatalytic base editing for RNA-responsive translational control.

Genetic circuits that control transgene expression in response to pre-defined transcriptional cues would enable the development of smart therapeutics. To this end, here we engineer programmable single-transcript RNA sensors in which adenosine deaminases acting on RNA (ADARs) autocatalytically convert target hybridization into a translational output. Dubbed DART VADAR (Detection and Amplification of RNA Triggers via ADAR), our system amplifies the signal from editing by endogenous ADAR through a positive feedback loop.

Synthetic genetic circuits to uncover and enforce the OCT4 trajectories of successful reprogramming of human fibroblasts.

Reprogramming human fibroblasts to induced pluripotent stem cells (iPSCs) is inefficient, with heterogeneity among transcription factor (TF) trajectories driving divergent cell states. Nevertheless, the impact of TF dynamics on reprogramming efficiency remains uncharted. Here, we identify the successful reprogramming trajectories of the core pluripotency TF, OCT4, and design a genetic controller that enforces such trajectories with high precision.

Robust and tunable signal processing in mammalian cells via engineered covalent modification cycles.

Engineered signaling networks can impart cells with new functionalities useful for directing differentiation and actuating cellular therapies. For such applications, the engineered networks must be tunable, precisely regulate target gene expression, and be robust to perturbations within the complex context of mammalian cells. Here, we use bacterial two-component signaling proteins to develop synthetic phosphoregulation devices that exhibit these properties in mammalian cells.