Computational design and interpretation of single-RNA translation experiments

Bursting translation on single mRNAs in live cells

Stochasticity has emerged as a mechanism of gene regulation. Much of this so-called "noise" has been attributed to bursting transcription. Although bursting transcription has been studied extensively, the role of stochasticity in translation has not been fully investigated due to the lack of enabling imaging technology. In this study, we developed techniques to track single mRNAs and their translation in live cells for hours, allowing the measurement of previously uncharacterized translation dynamics. We applied genetic and pharmacological perturbations to control translation kinetics and found that, like transcription, translation is not a constitutive process but instead cycles between inactive and active states, or "bursts." However, unlike transcription, which is largely frequency-modulated, complex structures in the 5'-untranslated region alter burst amplitudes. Bursting frequency can be controlled through cap-proximal sequences and trans-acting factors such as eIF4F. We coupled single-molecule imaging with stochastic modeling to quantitatively determine the kinetic parameters of translational bursting.

Using mechanistic models and machine learning to design single-color multiplexed nascent chain tracking experiments

mRNA translation is the ubiquitous cellular process of reading messenger-RNA strands into functional proteins. Over the past decade, large strides in microscopy techniques have allowed observation of mRNA translation at a single-molecule resolution for self-consistent time-series measurements in live cells. Dubbed Nascent chain tracking (NCT), these methods have explored many temporal dynamics in mRNA translation uncaptured by other experimental methods such as ribosomal profiling, smFISH, pSILAC, BONCAT, or FUNCAT-PLA. However, NCT is currently restricted to the observation of one or two mRNA species at a time due to limits in the number of resolvable fluorescent tags. In this work, we propose a hybrid computational pipeline, where detailed mechanistic simulations produce realistic NCT videos, and machine learning is used to assess potential experimental designs for their ability to resolve multiple mRNA species using a single fluorescent color for all species. Our simulation results show that with careful application this hybrid design strategy could in principle be used to extend the number of mRNA species that could be watched simultaneously within the same cell. We present a simulated example NCT experiment with seven different mRNA species within the same simulated cell and use our ML labeling to identify these spots with 90% accuracy using only two distinct fluorescent tags. We conclude that the proposed extension to the NCT color palette should allow experimentalists to access a plethora of new experimental design possibilities, especially for cell Signaling applications requiring simultaneous study of multiple mRNAs.

Nucleotide and codon usage biases involved in the evolution of African swine fever virus: A comparative genomics analysis

Since African swine fever virus (ASFV) replication is closely related to its host's machinery, codon usage of viral genome can be subject to selection pressures. A better understanding of codon usage can give new insights into viral evolution. We implemented information entropy and revealed that the nucleotide usage pattern of ASFV is significantly associated with viral isolation factors (region and time), especially the usages of thymine and cytosine. Despite the domination of adenine and thymine in the viral genome, we found that mutation pressure alters the overall codon usage pattern of ASFV, followed by selective forces from natural selection. Moreover, the nucleotide skew index at the gene level indicates that nucleotide usages influencing synonymous codon bias of ASFV are significantly correlated with viral protein hydropathy. Finally, evolutionary plasticity is proved to contribute to the weakness in synonymous codons with A- or T-end serving as optimal codons of ASFV, suggesting that fine-tuning translation selection plays a role in synonymous codon usages of ASFV for adapting host. Taken together, ASFV is subject to evolutionary dynamics on nucleotide selections and synonymous codon usage, and our detailed analysis offers deeper insights into the genetic characteristics of this newly emerging virus around the world.

Using Mechanistic Models and Machine Learning to Design Single-Color Multiplexed Nascent Chain Tracking Experiments

mRNA translation is the ubiquitous cellular process of reading messenger-RNA strands into functional proteins. Over the past decade, large strides in microscopy techniques have allowed observation of mRNA translation at a single-molecule resolution for self-consistent time-series measurements in live cells. Dubbed Nascent chain tracking (NCT), these methods have explored many temporal dynamics in mRNA translation uncaptured by other experimental methods such as ribosomal profiling, smFISH, pSILAC, BONCAT, or FUNCAT-PLA. However, NCT is currently restricted to the observation of one or two mRNA species at a time due to limits in the number of resolvable fluorescent tags. In this work, we propose a hybrid computational pipeline, where detailed mechanistic simulations produce realistic NCT videos, and machine learning is used to assess potential experimental designs for their ability to resolve multiple mRNA species using a single fluorescent color for all species. Through simulation, we show that with careful application, this hybrid design strategy could in principle be used to extend the number of mRNA species that could be watched simultaneously within the same cell. We present a simulated example NCT experiment with seven different mRNA species within the same simulated cell and use our ML labeling to identify these spots with 90% accuracy using only two distinct fluorescent tags. The proposed extension to the NCT color palette should allow experimentalists to access a plethora of new experimental design possibilities, especially for cell signalling applications requiring simultaneous study of multiple mRNAs.

Imaging translational control by Argonaute with single-molecule resolution in live cells

A major challenge to our understanding of translational control has been deconvolving the individual impact specific regulatory factors have on the complex dynamics of mRNA translation. MicroRNAs (miRNAs), for example, guide Argonaute and associated proteins to target mRNAs, where they direct gene silencing in multiple ways that are not well understood. To better deconvolve these dynamics, we have developed technology to directly visualize and quantify the impact of human Argonaute2 (Ago2) on the translation and subcellular localization of individual reporter mRNAs in living cells. We show that our combined translation and Ago2 tethering sensor reflects endogenous miRNA-mediated gene silencing. Using the sensor, we find that Ago2 association leads to progressive silencing of translation at individual mRNA. Silencing was occasionally interrupted by brief bursts of translational activity and took 3–4 times longer than a single round of translation, consistent with a gradual increase in the inhibition of translation initiation. At later time points, Ago2-tethered mRNAs cluster and coalesce with P-bodies, where a translationally silent state is maintained. These results provide a framework for exploring miRNA-mediated gene regulation in live cells at the single-molecule level. Furthermore, our tethering-based, single-molecule reporter system will likely have wide-ranging application in studying RNA-protein interactions.

Guided by miRNA, Argonaute proteins silence mRNA in multiple ways that are not well understood. Here, the authors develop live-cell biosensors to image the impact tethered regulatory factors, such as Argonaute, have on single-mRNA translation dynamics.

Live-cell imaging reveals the spatiotemporal organization of endogenous RNA polymerase II phosphorylation at a single gene

The carboxyl-terminal domain of RNA polymerase II (RNAP2) is phosphorylated during transcription in eukaryotic cells. While residue-specific phosphorylation has been mapped with exquisite spatial resolution along the 1D genome in a population of fixed cells using immunoprecipitation-based assays, the timing, kinetics, and spatial organization of phosphorylation along a single-copy gene have not yet been measured in living cells. Here, we achieve this by combining multi-color, single-molecule microscopy with fluorescent antibody-based probes that specifically bind to different phosphorylated forms of endogenous RNAP2 in living cells. Applying this methodology to a single-copy HIV-1 reporter gene provides live-cell evidence for heterogeneity in the distribution of RNAP2 along the length of the gene as well as Serine 5 phosphorylated RNAP2 clusters that remain separated in both space and time from nascent mRNA synthesis. Computational models determine that 5 to 40 RNAP2 cluster around the promoter during a typical transcriptional burst, with most phosphorylated at Serine 5 within 6 seconds of arrival and roughly half escaping the promoter in ~1.5 minutes. Taken together, our data provide live-cell support for the notion of efficient transcription clusters that transiently form around promoters and contain high concentrations of RNAP2 phosphorylated at Serine 5.

What determines eukaryotic translation elongation: recent molecular and quantitative analyses of protein synthesis

Protein synthesis from mRNA is an energy-intensive and tightly controlled cellular process. Translation elongation is a well-coordinated, multifactorial step in translation that undergoes dynamic regulation owing to cellular state and environmental determinants. Recent studies involving genome-wide approaches have uncovered some crucial aspects of translation elongation including the mRNA itself and the nascent polypeptide chain. Additionally, these studies have fuelled quantitative and mathematical modelling of translation elongation. In this review, we provide a comprehensive overview of the key determinants of translation elongation. We discuss consequences of ribosome stalling or collision, and how the cells regulate translation in case of such events. Next, we review theoretical approaches and widely used mathematical models that have become an essential ingredient to interpret complex molecular datasets and study translation dynamics quantitatively. Finally, we review recent advances in live-cell reporter and related analysis techniques, to monitor the translation dynamics of single cells and single-mRNA molecules in real time.

Quantifying the dynamics of IRES and cap translation with single-molecule resolution in live cells

Viruses use internal ribosome entry sites (IRES) to hijack host ribosomes and promote cap-independent translation. Although they are well-studied in bulk, the dynamics of IRES-mediated translation remain unexplored at the single-molecule level. Here, we developed a bicistronic biosensor encoding distinct repeat epitopes in two open reading frames (ORFs), one translated from the 5' cap, and the other from the encephalomyocarditis virus IRES. When combined with a pair of complementary probes that bind the epitopes cotranslationally, the biosensor lights up in different colors depending on which ORF is translated. Using the sensor together with single-molecule tracking and computational modeling, we measured the kinetics of cap-dependent versus IRES-mediated translation in living human cells. We show that bursts of IRES translation are shorter and rarer than bursts of cap translation, although the situation reverses upon stress. Collectively, our data support a model for translational regulation primarily driven by transitions between translationally active and inactive RNA states.

Lighting up single-mRNA translation dynamics in living cells

Over the past five years, technological advances have made it possible to image the translation of single mRNA in the natural context of living cells. With these advances, researchers are beginning to shed light on when, where, and to what degree mRNA are translated with single-molecule precision. These works provide insight into the heterogeneity of translation amongst single transcripts, behavior that is averaged out in complementary bulk assays. In this review, we discuss the rapidly maturing field of live-cell, single-mRNA imaging of translation, beginning with a brief overview of recent technological advances. The remainder of the review focuses on the new biological insights gained from these technologies. We conclude with a discussion of the future of this technology.