Quantifying Single mRNA Translation Kinetics in Living Cells

Morisaki, Tatsuya; Stasevich, Timothy J.

doi:10.1101/cshperspect.a032078

Cited by 43 publications

(48 citation statements)

References 79 publications

(171 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A multi-frame tag to monitor single RNA translation in two reading frames simultaneously We created a multi-frame (MF) tag to monitor, in living cells, the translation of single RNAs with overlapping open reading frames (ORFs). The tag builds off earlier technology to visualize translation using repeat FLAG or SunTag epitopes labeled by fluorescent Fab or scFv, respectively (Lyon and Stasevich, 2017;Morisaki and Stasevich, 2018). In the MF tag, FLAG epitopes in the 0 frame are separated from one another by SunTag epitopes in the -1 frame.…”

Section: Resultsmentioning

confidence: 99%

“…The loss of signal from the control translation site was fit to a single exponential decay and this decay was divided out from the FRAP recovery curves of the intentionally photobleached translation sites. The FRAP recovery curve can be thought of as the inverse of the harringtonine runoff curve (Morisaki and Stasevich, 2018). In this way, the FRAP recovery curve was fit to determine the average translation elongation rate (Fig.…”

Section: Ribosome Run-off Experiments and Fitsmentioning

confidence: 99%

See 1 more Smart Citation

Live-cell single RNA imaging reveals bursts of translational frameshifting

Lyon

Aguilera

Morisaki

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

Ribosomal frameshifting during the translation of RNA is implicated in both human disease and viral infection. While previous work has uncovered many mechanistic details about single RNA frameshifting kinetics in vitro, very 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 in living cells. Frameshifting RNA are preferentially in multi-RNA "translation factories," are translated at about the same All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. . https://doi.org/10.1101/478040 doi: bioRxiv preprint 2 rate as non-frameshifting RNA (~2 aa/sec), 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 novel insight into retroviral frameshifting and could lead to new strategies to perturb the process in living cells.All rights reserved. No reuse allowed without permission.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Ribosome Run-off Experiments and Fitsmentioning

confidence: 99%

Live-cell single RNA imaging reveals bursts of translational frameshifting

Lyon

Aguilera

Morisaki

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…While incredibly powerful, GFP-tagging has several limitations that have made it difficult to image the full lifecycles of proteins. First, long fluorophore maturation times prevent co-translational imaging of GFP-tagged nascent peptide chains 3,4 . By the time the GFP tag folds, matures and lights up, translation of the nascent peptide chain is long over.…”

Section: Introductionmentioning

confidence: 99%

A genetically encoded probe for imaging HA-tagged protein translation, localization, and dynamics in living cells and animals

Zhao

Kamijo

Fox

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

One-sentence summary:A genetically encodable intracellular single-chain variable fragment that selectively binds the HA epitope (YPYDVPDYA) with high affinity in living cells and organisms can be used to quantify HA-tagged protein translation, localization, and dynamics. ABSTRACTTo expand the toolbox of imaging in living cells, we have engineered a new single chain variable fragment (scFv) that binds the classic linear HA epitope with high affinity and specificity in vivo. The resulting probe, which we call the HA frankenbody, is capable of lighting up in multiple colors HA-tagged nuclear, cytoplasmic, and membrane proteins in diverse living cell types. The HA frankenbody also enables state-of-the-art singlemolecule experiments, which we demonstrate by tracking single mRNA translation dynamics in living U2OS cells and neurons. In combination with the SunTag, we track two mRNA species simultaneously to demonstrate comparative single-molecule studies of translation can now be done with genetically encoded tools alone. Finally, we use the HA frankenbody to precisely quantify the expression of HA tagged proteins in developing zebrafish embryos. The versatility of the HA frankenbody makes it a powerful new tool for imaging protein dynamics in vivo.

show abstract

“…Imaging translation in living cells at single-molecule resolution is a new experimental 506 technology that has been applied to only a few genes so far [6-10, 14, 15], but the 507 number of such studies is expected to grow considerably in the near future [12]. transcription dynamics for a multi-state promoter.…”

mentioning

confidence: 99%

“…With the full and reduced models in hand, it becomes possible to predict how well 538 three modern methodologies would estimate elongation rates from single-molecule 539 measurements: Fluorescence Correlation Spectroscopy (FCS) [12], Fluorescence 540 Recovery After Photobleaching (FRAP) [8,9,12], and Run-Off Assays (ROA) after 541 perturbation with inhibitory drugs [7,10]. Through simulations on 2,647 genes, we 542 demonstrated that estimating elongation rates for long genes (>1000 codons) could be 543 achieved with great accuracy using any of these methodologies, provided that a minimal 544 number of mRNA spots are considered and with an appropriate temporal resolution as 545 demonstrated in Fig 3. However, our results suggest that FCS would be the most likely 546 method to provide an accurate elongation rate estimate (Fig 3A), especially for small 547 and medium size genes.…”

mentioning

confidence: 99%

Computational design and interpretation of single-RNA translation experiments

Aguilera

Raymond²,

Fox³

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

Advances in fluorescence microscopy have introduced new assays to quantify live-cell translation dynamics at single-RNA resolution. We introduce a detailed, yet efficient sequence-based stochastic model that generates realistic synthetic data for several such assays, including Fluorescence Correlation Spectroscopy (FCS), ribosome Run-Off Assays (ROA) after Harringtonine application, and Fluorescence Recovery After Photobleaching (FRAP). We simulate these experiments under multiple imaging conditions and for thousands of human genes, and we evaluate through simulations which experiments are most likely to provide accurate estimates of elongation kinetics. Finding that FCS analyses are optimal for both short and long length genes, we integrate our model with experimental FCS data to capture the nascent protein statistics and temporal dynamics for three human genes: KDM5B, β-actin, and H2B. Finally, we introduce a new open-source software package, RNA Sequence to NAscent Protein Simulator (rSNAPsim), to easily simulate the single-molecule translation dynamics of any gene sequence for any of these assays and for different assumptions regarding synonymous codon usage, tRNA level modifications, or ribosome pauses. rSNAPsim is implemented in Python and is available at: https://github.com/MunskyGroup/rSNAPsim.git. Author summaryTranslation is an essential step in which ribosomes decipher mRNA sequences to 1 manufacture proteins. Recent advances in time-lapse fluorescence microscopy allow 2 live-cell quantification of translation dynamics at the resolution of single mRNA 3 molecules. Here, we develop a flexible computational framework to reproduce and 4interpret such experiments. We use this framework to explore how well different 5 single-mRNA translation experiment designs would perform to estimate key translation 6 parameters. We then integrate experimental data from the most flexible design with our 7 stochastic model framework to reproduce the statistics and temporal dynamics of 8 September 17, 2019 1/35 nascent protein elongation for three different human genes. Our validated 9 computational method is packaged with a simple graphical user interface that (1) starts 10 with mRNA sequences, (2) generates discrete, codon-dependent translation models, (3) 11 provides visualization of ribosome movement as trajectories or kymographs, and (4) 12 allows the user to estimate how optical single-mRNA translation experiments would be 13 affected by different genetic alterations (e.g., codon substitutions) or environmental 14 perturbations (e.g., tRNA titrations or drug treatments). 15Introduction 16 The central dogma of molecular biology (i.e., DNA codes are transcribed into messenger 17 RNA, which are then translated to build proteins) has been a foundation of biological 18 understanding since it was stated by Francis Crick in 1958. Despite their overwhelming 19 importance to biological and biomedical science, many of the fundamental steps in the 20 gene expression process are only now becoming observable in living cells throug...

show abstract

Quantifying Single mRNA Translation Kinetics in Living Cells

Cited by 43 publications

References 79 publications

Live-cell single RNA imaging reveals bursts of translational frameshifting

Live-cell single RNA imaging reveals bursts of translational frameshifting

A genetically encoded probe for imaging HA-tagged protein translation, localization, and dynamics in living cells and animals

Computational design and interpretation of single-RNA translation experiments

Contact Info

Product

Resources

About