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Mol Cell. 2019 Jun 3. pii: S1097-2765(19)30355-7. doi: 10.1016/j.molcel.2019.05.002. [Epub ahead of print]

Live-Cell Single RNA Imaging Reveals Bursts of Translational Frameshifting.

Author information

1
Department of Biochemistry and Molecular Biology, Institute of Genome Architecture and Function, Colorado State University, Fort Collins, CO 80523, USA.
2
Department of Chemical and Biological Engineering and School of Biomedical Engineering, Colorado State University, Fort Collins, CO 80523, USA.
3
Department of Chemical and Biological Engineering and School of Biomedical Engineering, Colorado State University, Fort Collins, CO 80523, USA. Electronic address: brian.munsky@colostate.edu.
4
Department of Biochemistry and Molecular Biology, Institute of Genome Architecture and Function, Colorado State University, Fort Collins, CO 80523, USA; World Research Hub Initiative, Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Kanagawa 226-8503, Japan. Electronic address: tim.stasevich@colostate.edu.

Abstract

Ribosomal frameshifting during the translation of RNA is implicated in human disease and viral infection. While previous work has uncovered many details about single RNA frameshifting kinetics in vitro, little is known about how single RNA frameshift in living systems. To confront this problem, we have developed technology to quantify live-cell single RNA translation dynamics in frameshifted open reading frames. Applying this technology to RNA encoding the HIV-1 frameshift sequence reveals a small subset (∼8%) of the translating pool robustly frameshift. Frameshifting RNA are translated at similar rates as non-frameshifting RNA (∼3 aa/s) and can continuously frameshift for more than four rounds of translation. Fits to a bursty model of frameshifting constrain frameshifting kinetic rates and demonstrate how ribosomal traffic jams contribute to the persistence of the frameshifting state. These data provide insight into retroviral frameshifting and could lead to alternative strategies to perturb the process in living cells.

KEYWORDS:

HIV-1; RNA translation; computational modeling; fluorescence microscopy; frameshifting; live-cell imaging; ribosomal traffic jams; single-molecule imaging; stochastic gene expression; translational heterogeneity

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