RNA Sequence and Structure Determinants of Pol III Transcriptional Termination in Human Cells.

The precise mechanism of transcription termination of the eukaryotic RNA polymerase III (Pol III) has been a subject of considerable debate. Although previous studies have clearly shown that multiple uracils at the end of RNA transcripts are required for Pol III termination, the effects of upstream RNA secondary structure in the nascent transcript on transcriptional termination is still unclear. To address this, we developed an in cellulo Pol III transcription termination assay using the recently developed Tornado-Corn RNA aptamer system to create a Pol III-transcribed RNA that produces a detectable fluorescent signal when transcribed in human cells. To study the effects of RNA sequence and structure on Pol III termination, we systematically varied the sequence context upstream of the aptamer and identified sequence characteristics that enhance or diminish termination. For transcription from Pol III type 3 promoters, we found that only poly-U tracts longer than the average length found in the human genome efficiently terminate Pol III transcription without RNA secondary structure elements. We observed that RNA secondary structure elements placed in proximity to shorter poly-U tracts induced termination, and RNA secondary structure by itself was not sufficient to induce termination. For Pol III type 2 promoters, we found that the shorter poly-U tract lengths of 4 uracils were sufficient to induce termination. These findings demonstrate a key role for sequence and structural elements within Pol III-transcribed nascent RNA for efficient transcription termination, and demonstrate a generalizable assay for characterizing Pol III transcription in human cells.

Computation-guided optimization of split protein systems.

Splitting bioactive proteins into conditionally reconstituting fragments is a powerful strategy for building tools to study and control biological systems. However, split proteins often exhibit a high propensity to reconstitute, even without the conditional trigger, limiting their utility. Current approaches for tuning reconstitution propensity are laborious, context-specific or often ineffective. Here, we report a computational design strategy grounded in fundamental protein biophysics to guide experimental evaluation of a sparse set of mutants to identify an optimal functional window. We hypothesized that testing a limited set of mutants would direct subsequent mutagenesis efforts by predicting desirable mutant combinations from a vast mutational landscape. This strategy varies the degree of interfacial destabilization while preserving stability and catalytic activity. We validate our method by solving two distinct split protein design challenges, generating both design and mechanistic insights. This new technology will streamline the generation and use of split protein systems for diverse applications.