ZAP's stress granule localization is correlated with its antiviral activity and induced by virus replication.

Cellular antiviral programs encode molecules capable of targeting multiple steps in the virus lifecycle. Zinc-finger antiviral protein (ZAP) is a central and general regulator of antiviral activity that targets pathogen mRNA stability and translation. ZAP is diffusely cytoplasmic, but upon infection ZAP is targeted to particular cytoplasmic structures, termed stress granules (SGs). However, it remains unclear if ZAP's antiviral activity correlates with SG localization, and what molecular cues are required to induce this localization event. Here, we use Sindbis virus (SINV) as a model infection and find that ZAP's localization to SGs can be transient. Sometimes no apparent viral infection follows ZAP SG localization but ZAP SG localization always precedes accumulation of SINV non-structural protein, suggesting virus replication processes trigger SG formation and ZAP recruitment. Data from single-molecule RNA FISH corroborates this finding as the majority of cells with ZAP localization in SGs contain low levels of viral RNA. Furthermore, ZAP recruitment to SGs occurred in ZAP-expressing cells when co-cultured with cells replicating full-length SINV, but not when co-cultured with cells replicating a SINV replicon. ZAP recruitment to SGs is functionally important as a panel of alanine ZAP mutants indicate that the anti-SINV activity is correlated with ZAP's ability to localize to SGs. As ZAP is a central component of the cellular antiviral programs, these data provide further evidence that SGs are an important cytoplasmic antiviral hub. These findings provide insight into how antiviral components are regulated upon virus infection to inhibit virus spread

Replication and single-cycle delivery of SARS-CoV-2 replicons

Molecular virology tools are critical for basic studies of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and for developing new therapeutics. There remains a need for experimental systems that do not rely on viruses capable of spread that could potentially be used in lower containment settings. Here, we develop spike-deleted SARS-CoV-2 self-replicating RNAs using a yeast-based reverse genetics system. These non-infectious self-replicating RNAs, or replicons, can be trans-complemented with viral glycoproteins to generate Replicon Delivery Particles (RDPs) for single-cycle delivery into a range of cell types. This SARS-CoV-2 replicon system represents a convenient and versatile platform for antiviral drug screening, neutralization assays, host factor validation, and characterizing viral variants

Transcriptional Bursting Explains the Noise-Versus-Mean Relationship in mRNA and Protein Levels

Publisher's PDFRecent analysis demonstrates that the HIV-1 Long Terminal Repeat (HIV LTR) promoter exhibits a range of possible transcriptional burst sizes and frequencies for any mean-expression level. However, these results have also been interpreted as demonstrating that cell-tocell expression variability (noise) and mean are uncorrelated, a significant Developmentiation from previous results. Here, we re-examine the available mRNA and protein abundance data for the HIV LTR and find that noise in mRNA and protein expression scales inversely with the mean along analytically predicted transcriptional burst-sizemanifolds. We then experimentally perturb transcriptional activity to test a prediction of the multiple burst-size model: that increasing burst frequency will cause mRNA noise to decrease along given burst-size lines as mRNA levels increase. The data show that mRNA and protein noise decrease as mean expression increases, supporting the canonical inverse correlation between noise and mean.University of Delaware, Department of Electrical and Computer Engineerin

Yeast shows less burstiness and no noise floor compared to <i>E</i>. <i>coli</i>.

<p><b>(A)</b> Reported noise magnitude measurements for 1467 genes of <i>S</i>. <i>cerevisiae</i> plotted along with genome-wide <i>E</i>. <i>coli</i> noise measurements from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140969#pone.0140969.g003" target="_blank">Fig 3D</a>. <b>(B)</b> Using calculated values for translational burst size [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140969#pone.0140969.ref001" target="_blank">1</a>] based off of four separate databases [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140969#pone.0140969.ref047" target="_blank">47</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140969#pone.0140969.ref050" target="_blank">50</a>], in contrast to <i>E</i>. <i>coli</i>, the translational burst size are invariant to protein abundance. A moving average of 20 genes was applied to the trend.</p

ZAP's stress granule localization is correlated with its antiviral activity and induced by virus replication.

Cellular antiviral programs encode molecules capable of targeting multiple steps in the virus lifecycle. Zinc-finger antiviral protein (ZAP) is a central and general regulator of antiviral activity that targets pathogen mRNA stability and translation. ZAP is diffusely cytoplasmic, but upon infection ZAP is targeted to particular cytoplasmic structures, termed stress granules (SGs). However, it remains unclear if ZAP's antiviral activity correlates with SG localization, and what molecular cues are required to induce this localization event. Here, we use Sindbis virus (SINV) as a model infection and find that ZAP's localization to SGs can be transient. Sometimes no apparent viral infection follows ZAP SG localization but ZAP SG localization always precedes accumulation of SINV non-structural protein, suggesting virus replication processes trigger SG formation and ZAP recruitment. Data from single-molecule RNA FISH corroborates this finding as the majority of cells with ZAP localization in SGs contain low levels of viral RNA. Furthermore, ZAP recruitment to SGs occurred in ZAP-expressing cells when co-cultured with cells replicating full-length SINV, but not when co-cultured with cells replicating a SINV replicon. ZAP recruitment to SGs is functionally important as a panel of alanine ZAP mutants indicate that the anti-SINV activity is correlated with ZAP's ability to localize to SGs. As ZAP is a central component of the cellular antiviral programs, these data provide further evidence that SGs are an important cytoplasmic antiviral hub. These findings provide insight into how antiviral components are regulated upon virus infection to inhibit virus spread

Evidence of the noise floor at high abundance in mammalian cells.

<p>Polyclonal populations of T cells infected with a viral HIV-LTR and housekeeping promoters, UbC and Ef1A, show an increase of noise at higher abundances. Time-lapse microscopy and signal processing of limited duration experiments filters extrinsic noise (High-frequency or HF-CV², [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140969#pone.0140969.ref006" target="_blank">6</a>]) suggesting that burstiness drives the noise increase from a simple model line that is inversely proportional to mean GFP. Data adapted from Dar <i>et al</i>., 2012, [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140969#pone.0140969.ref006" target="_blank">6</a>].</p

The noise floor is not determined by extrinsic noise acting alone; rather noise from bursty gene expression dominates.

<p><b>(A)</b> Illustration of noise floors resulting from various levels of extrinsic noise. <b>(B)</b> Relative likelihood of gene expression noise models with various levels of extrinsic noise as evaluated by the Akaike information criteria [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140969#pone.0140969.ref045" target="_blank">45</a>]. The model with extrinsic noise E = 0 has the highest likelihood; models with E = 0.07 and E = 0.1 have extremely low likelihood. <b>(C)</b> Transcriptional burst size (B) corresponding to different levels of assumed extrinsic noise. Burst size corresponding to larger noise floors are incompatible with values calculated from the experimentally based model of So <i>et al</i>. (2011).</p