Sindbis Macrodomain Poly-ADP-Ribose Hydrolase Activity Is Important for Viral RNA Synthesis.

ADP-ribosylation is a highly dynamic posttranslational modification frequently studied in stress response pathways with recent attention given to its role in response to viral infection. Notably, the alphaviruses encode catalytically active macrodomains capable of ADP-ribosylhydrolase (ARH) activities, implying a role in remodeling the cellular ADP-ribosylome. This report decouples mono- and poly-ARH contributions to macrodomain function using a newly engineered Sindbis virus (SINV) mutant with attenuated poly-ARH activity. Our findings indicate that viral poly-ARH activity is uniquely required for high titer replication in mammalian systems. Despite translating incoming genomic RNA as efficiently as WT virus, mutant viruses have a reduced capacity to establish productive infection, offering a more complete understanding of the kinetics and role of the alphavirus macrodomain with important implications for broader ADP-ribosyltransferase biology. IMPORTANCE Viral macrodomains have drawn attention in recent years due to their high degree of conservation in several virus families (e.g., coronaviruses and alphaviruses) and their potential druggability. These domains erase mono- or poly-ADP-ribose, posttranslational modifications written by host poly-ADP-ribose polymerase (PARP) proteins, from undetermined host or viral proteins to enhance replication. Prior work determined that efficient alphavirus replication requires catalytically active macrodomains; however, which form of the modification requires removal and from which protein(s) had not been determined. Here, we present evidence for the specific requirement of poly-ARH activity to ensure efficient productive infection and virus replication.

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. Experimental systems that do not rely on viruses capable of spread are needed for potential use in lower-containment settings. In this work, we use a yeast-based reverse genetics system to develop spike-deleted SARS-CoV-2 self-replicating RNAs. These noninfectious self-replicating RNAs, or replicons, can be trans-complemented with viral glycoproteins to generate replicon delivery particles 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 viral variant characterization.

Inborn errors of type I IFN immunity in patients with life-threatening COVID-19.

Clinical outcome upon infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ranges from silent infection to lethal coronavirus disease 2019 (COVID-19). We have found an enrichment in rare variants predicted to be loss-of-function (LOF) at the 13 human loci known to govern Toll-like receptor 3 (TLR3)- and interferon regulatory factor 7 (IRF7)-dependent type I interferon (IFN) immunity to influenza virus in 659 patients with life-threatening COVID-19 pneumonia relative to 534 subjects with asymptomatic or benign infection. By testing these and other rare variants at these 13 loci, we experimentally defined LOF variants underlying autosomal-recessive or autosomal-dominant deficiencies in 23 patients (3.5%) 17 to 77 years of age. We show that human fibroblasts with mutations affecting this circuit are vulnerable to SARS-CoV-2. Inborn errors of TLR3- and IRF7-dependent type I IFN immunity can underlie life-threatening COVID-19 pneumonia in patients with no prior severe infection.

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.

A Post-Transcriptional Feedback Mechanism for Noise Suppression and Fate Stabilization.

Diverse biological systems utilize fluctuations ("noise") in gene expression to drive lineage-commitment decisions. However, once a commitment is made, noise becomes detrimental to reliable function, and the mechanisms enabling post-commitment noise suppression are unclear. Here, we find that architectural constraints on noise suppression are overcome to stabilize fate commitment. Using single-molecule and time-lapse imaging, we find that-after a noise-driven event-human immunodeficiency virus (HIV) strongly attenuates expression noise through a non-transcriptional negative-feedback circuit. Feedback is established through a serial cascade of post-transcriptional splicing, whereby proteins generated from spliced mRNAs auto-deplete their own precursor unspliced mRNAs. Strikingly, this auto-depletion circuitry minimizes noise to stabilize HIV's commitment decision, and a noise-suppression molecule promotes stabilization. This feedback mechanism for noise suppression suggests a functional role for delayed splicing in other systems and may represent a generalizable architecture of diverse homeostatic signaling circuits.

Nonlatching positive feedback enables robust bimodality by decoupling expression noise from the mean.

Fundamental to biological decision-making is the ability to generate bimodal expression patterns where 2 alternate expression states simultaneously exist. Here, we use a combination of single-cell analysis and mathematical modeling to examine the sources of bimodality in the transcriptional program controlling HIV's fate decision between active replication and viral latency. We find that the HIV transactivator of transcription (Tat) protein manipulates the intrinsic toggling of HIV's promoter, the long terminal repeat (LTR), to generate bimodal ON-OFF expression and that transcriptional positive feedback from Tat shifts and expands the regime of LTR bimodality. This result holds for both minimal synthetic viral circuits and full-length virus. Strikingly, computational analysis indicates that the Tat circuit's noncooperative "nonlatching" feedback architecture is optimized to slow the promoter's toggling and generate bimodality by stochastic extinction of Tat. In contrast to the standard Poisson model, theory and experiment show that nonlatching positive feedback substantially dampens the inverse noise-mean relationship to maintain stochastic bimodality despite increasing mean expression levels. Given the rapid evolution of HIV, the presence of a circuit optimized to robustly generate bimodal expression appears consistent with the hypothesis that HIV's decision between active replication and latency provides a viral fitness advantage. More broadly, the results suggest that positive-feedback circuits may have evolved not only for signal amplification but also for robustly generating bimodality by decoupling expression fluctuations (noise) from mean expression levels.

Viral Infection Identifies Micropeptides Differentially Regulated in smORF-Containing lncRNAs.

Viral infection leads to a robust cellular response whereby the infected cell produces hundreds of molecular regulators to combat infection. Currently, non-canonical components, e.g., long noncoding RNAs (lncRNAs) have been added to the repertoire of immune regulators involved in the antiviral program. Interestingly, studies utilizing next-generation sequencing technologies show that a subset of the >10,000 lncRNAs in the mammalian genome contain small open reading frames (smORFs) associated with active translation, i.e., many lncRNAs are not noncoding. Here, we use genome-wide high-throughput methods to identify potential micropeptides in smORF-containing lncRNAs involved in the immune response. Using influenza as a viral infection model, we performed RNA-seq and ribosome profiling to track expression and translation of putative lncRNAs that may encode for peptides and identify tens of potential candidates. Interestingly, many of these peptides are highly conserved at the protein level, strongly suggesting biological relevance and activity. By perusing publicly available data sets, four potential peptides of interest seem common to stress induction and/or are highly conserved; potential peptides from the MMP24-AS1, ZFAS1, RP11-622K12.1, and MIR22HG genes. Interestingly, using an antibody against the potential peptide encoded by MIR22HG RNA, we show that the peptide is stably expressed in the absence of infection, and upregulated in response to infection, corroborating the prediction of the ribosome profiling results. These data show the utility of perturbation approaches in identifying potentially relevant novel molecules encoded in the genome.

Resource Sharing Controls Gene Expression Bursting.

Episodic gene expression, with periods of high expression separated by periods of no expression, is a pervasive biological phenomenon. This bursty pattern of expression draws from a finite reservoir of expression machinery in a highly time variant way, i.e., requiring no resources most of the time but drawing heavily on them during short intense bursts, that intimately links expression bursting and resource sharing. Yet, most recent investigations have focused on specific molecular mechanisms intrinsic to the bursty behavior of individual genes, while little is known about the interplay between resource sharing and global expression bursting behavior. Here, we confine Escherichia coli cell extract in both cell-sized microfluidic chambers and lipid-based vesicles to explore how resource sharing influences expression bursting. Interestingly, expression burst size, but not burst frequency, is highly sensitive to the size of the shared transcription and translation resource pools. The intriguing implication of these results is that expression bursts are more readily amplified than initiated, suggesting that burst formation occurs through positive feedback or cooperativity. When extrapolated to prokaryotic cells, these results suggest that large translational bursts may be correlated with large transcriptional bursts. This correlation is supported by recently reported transcription and translation bursting studies in E. coli. The results reported here demonstrate a strong intimate link between global expression burst patterns and resource sharing, and they suggest that bursting plays an important role in optimizing the use of limited, shared expression resources.

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

Recent 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-to-cell expression variability (noise) and mean are uncorrelated, a significant deviation 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-size manifolds. 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.

The Low Noise Limit in Gene Expression.

Protein noise measurements are increasingly used to elucidate biophysical parameters. Unfortunately noise analyses are often at odds with directly measured parameters. Here we show that these inconsistencies arise from two problematic analytical choices: (i) the assumption that protein translation rate is invariant for different proteins of different abundances, which has inadvertently led to (ii) the assumption that a large constitutive extrinsic noise sets the low noise limit in gene expression. While growing evidence suggests that transcriptional bursting may set the low noise limit, variability in translational bursting has been largely ignored. We show that genome-wide systematic variation in translational efficiency can-and in the case of E. coli does-control the low noise limit in gene expression. Therefore constitutive extrinsic noise is small and only plays a role in the absence of a systematic variation in translational efficiency. These results show the existence of two distinct expression noise patterns: (1) a global noise floor uniformly imposed on all genes by expression bursting; and (2) high noise distributed to only a select group of genes.

A hardwired HIV latency program.

Biological circuits can be controlled by two general schemes: environmental sensing or autonomous programs. For viruses such as HIV, the prevailing hypothesis is that latent infection is controlled by cellular state (i.e., environment), with latency simply an epiphenomenon of infected cells transitioning from an activated to resting state. However, we find that HIV expression persists despite the activated-to-resting cellular transition. Mathematical modeling indicates that HIV's Tat positive-feedback circuitry enables this persistence and strongly controls latency. To overcome the inherent crosstalk between viral circuitry and cellular activation and to directly test this hypothesis, we synthetically decouple viral dependence on cellular environment from viral transcription. These circuits enable control of viral transcription without cellular activation and show that Tat feedback is sufficient to regulate latency independent of cellular activation. Overall, synthetic reconstruction demonstrates that a largely autonomous, viral-encoded program underlies HIV latency­potentially explaining why cell-targeted latency-reversing agents exhibit incomplete penetrance.

Transcriptional burst frequency and burst size are equally modulated across the human genome.

Gene expression occurs either as an episodic process, characterized by pulsatile bursts, or as a constitutive process, characterized by a Poisson-like accumulation of gene products. It is not clear which mode of gene expression (constitutive versus bursty) predominates across a genome or how transcriptional dynamics are influenced by genomic position and promoter sequence. Here, we use time-lapse fluorescence microscopy to analyze 8,000 individual human genomic loci and find that at virtually all loci, episodic bursting--as opposed to constitutive expression--is the predominant mode of expression. Quantitative analysis of the expression dynamics at these 8,000 loci indicates that both the frequency and size of the transcriptional bursts varies equally across the human genome, independent of promoter sequence. Strikingly, weaker expression loci modulate burst frequency to increase activity, whereas stronger expression loci modulate burst size to increase activity. Transcriptional activators such as trichostatin A (TSA) and tumor necrosis factor α (TNF) only modulate burst size and frequency along a constrained trend line governed by the promoter. In summary, transcriptional bursting dominates across the human genome, both burst frequency and burst size vary by chromosomal location, and transcriptional activators alter burst frequency and burst size, depending on the expression level of the locus.

Microwell devices with finger-like channels for long-term imaging of HIV-1 expression kinetics in primary human lymphocytes.

A major obstacle in the treatment of human immunodeficiency virus type 1 (HIV-1) is a sub-population of latently infected CD4(+) T lymphocytes. The cellular and viral mechanisms regulating HIV-1 latency are not completely understood, and a promising technique for probing the regulation of HIV-1 latency is single-cell time-lapse microscopy. Unfortunately, CD4(+) T lymphocytes rapidly migrate on substrates and spontaneously detach, making them exceedingly difficult to track, hampering single-cell level studies. To overcome these problems, we built microdevices with a three-level architecture. The devices contain arrays of finger-like microchannels to "corral" T-lymphocyte migration, round wells that are accessible to pipetting, and microwells connecting the microchannels with the round wells. T lymphocytes that are loaded into a well first settle into the microwells and then to microchannels by gravity. Within the microchannels, T lymphocytes are in favorable culture conditions because they are in physical contact with each other, under no mechanical stress, and fed from a large reservoir of fresh medium. Most importantly, T lymphocytes in the microchannels are not exposed to any flow and their random migration is restricted to a nearly one-dimensional region, greatly facilitating long-term tracking of multiple cells in time-lapse microscopy. The devices have up to nine separate round wells, making it possible to test up to nine different cell lines or medium conditions in a single experiment. Activated primary CD4(+) T lymphocytes, resting primary CD4(+) T lymphocytes, and THP-1 monocytic leukemia cells loaded into the devices maintained viability over multiple days. The devices were used to track the fluorescence level of individual primary CD4(+) T lymphocytes expressing green fluorescent protein (GFP) for up to 60 hours (h) and to quantify single-cell gene-expression kinetics of four different HIV-1 variants. The kinetics of GFP expression from the lentiviruses in the primary CD4(+) T lymphocytes agree with previous measurements of these lentiviral vectors in the immortalized Jurkat T lymphocyte cell line. The proposed devices offer a simple, robust approach to long-term single-cell studies of environmentally sensitive primary lymphocytes.

Dynamics of protein noise can distinguish between alternate sources of gene-expression variability.

Within individual cells, two molecular processes have been implicated as sources of noise in gene expression: (i) Poisson fluctuations in mRNA abundance arising from random birth and death of individual mRNA transcripts or (ii) promoter fluctuations arising from stochastic promoter transitions between different transcriptional states. Steady-state measurements of variance in protein levels are insufficient to discriminate between these two mechanisms, and mRNA single-molecule fluorescence in situ hybridization (smFISH) is challenging when cellular mRNA concentrations are high. Here, we present a perturbation method that discriminates mRNA birth/death fluctuations from promoter fluctuations by measuring transient changes in protein variance and that can operate in the regime of high molecular numbers. Conceptually, the method exploits the fact that transcriptional blockage results in more rapid increases in protein variability when mRNA birth/death fluctuations dominate over promoter fluctuations. We experimentally demonstrate the utility of this perturbation approach in the HIV-1 model system. Our results support promoter fluctuations as the primary noise source in HIV-1 expression. This study illustrates a relatively simple method that complements mRNA smFISH hybridization and can be used with existing GFP-tagged libraries to include or exclude alternate sources of noise in gene expression.

Mapping the architecture of the HIV-1 Tat circuit: A decision-making circuit that lacks bistability and exploits stochastic noise.

Upon infection of a CD4(+) T cell, HIV-1 appears to 'choose' between two alternate fates: active replication or a long-lived dormant state termed proviral latency. A transcriptional positive-feedback loop generated by the HIV-1 Tat protein appears sufficient to mediate this decision. Here, we describe a coupled wet-lab and computational approach that uses mathematical modeling and live-cell time-lapse microscopy to map the architecture of the HIV-1 Tat transcriptional regulatory circuit and generate predictive models of HIV-1 latency. This approach provided the first characterization of a 'decision-making' circuit that lacks bistability and instead exploits stochastic fluctuations in cellular molecules (i.e. noise) to generate a decision between an on or off transcriptional state.