Aguilera, L. | bioRxiv Science

bioRxiv2020

Quantifying the spatiotemporal dynamics of IRES versus Cap translation with single-molecule resolution in living cells

Viruses use IRES sequences within their RNA to hijack translation machinery and thereby rapidly replicate in host cells. While this process has been extensively studied in bulk assays, the dynamics of hijacking at the single-molecule level remain unexplored in living cells. To achieve this, we developed a bicistronic biosensor encoding complementary repeat epitopes in two ORFs, one translated in a Cap-dependent manner and the other translated in an IRES-mediated manner. Using a pair of complementary probes that bind the epitopes co-translationally, our biosensor lights up in different colors depending on which ORF is being translated. In combination with single-molecule tracking and computational modeling, we measured the relative kinetics of Cap versus IRES translation and show: (1) Two non-overlapping ORFs can be simultaneously translated within a single mRNA; (2) EMCV IRES-mediated translation sites recruit ribosomes less efficiently than Cap-dependent translation sites but are otherwise nearly indistinguishable, having similar mobilities, sizes, spatial distributions, and ribosomal initiation and elongation rates; (3) Both Cap-dependent and IRES-mediated ribosomes tend to stretch out translation sites; (4) Although the IRES recruits two to three times fewer ribosomes than the Cap in normal conditions, the balance shifts dramatically in favor of the IRES during oxidative and ER stresses that mimic viral infection; and (5) Translation of the IRES is enhanced by translation of the Cap, demonstrating upstream translation can positively impact the downstream translation of a non-overlapping ORF. With the ability to simultaneously quantify two distinct translation mechanisms in physiologically relevant live-cell environments, we anticipate bicistronic biosensors like the one we developed here will become powerful new tools to dissect both canonical and non-canonical translation dynamics with single-molecule precision. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=177 HEIGHT=200 SRC="FIGDIR/small/900829v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@a44259org.highwire.dtl.DTLVardef@651org.highwire.dtl.DTLVardef@19ebc26org.highwire.dtl.DTLVardef@527822_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2019

Computational design and interpretation of live-cell, single-RNA translation experiments

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, {beta}-actin, and H2B. Finally, we introduce a new open-source software package, RNA Sequence to NAscent Protein Simulator (O_SCPCAPRC_SCPCAPSNAPO_SCPCAPSIMC_SCPCAP), 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. O_SCPCAPRC_SCPCAPSNAPO_SCPCAPSIMC_SCPCAP is implemented in Python and is available at: https://github.com/MunskyGroup/rSNAPsim.git.\n\nAuthor summaryTranslation is an essential step in which ribosomes decipher mRNA sequences to manufacture proteins. Recent advances in time-lapse fluorescence microscopy allow live-cell quantification of translation dynamics at the resolution of single mRNA molecules. Here, we develop a flexible computational framework to reproduce and interpret such experiments. We use this framework to explore how well different single-mRNA translation experiment designs would perform to estimate key translation parameters. We then integrate experimental data from the most flexible design with our stochastic model framework to reproduce the statistics and temporal dynamics of nascent protein elongation for three different human genes. Our validated computational method is packaged with a simple graphical user interface that (1) starts with mRNA sequences, (2) generates discrete, codon-dependent translation models, (3) provides visualization of ribosome movement as trajectories or kymographs, and (4) allows the user to estimate how optical single-mRNA translation experiments would be affected by different genetic alterations (e.g., codon substitutions) or environmental perturbations (e.g., tRNA titrations or drug treatments).

systems biology↗