Role of cell-to-cell variability in activating a positive feedback antiviral response in human dendritic cells

The Regulation of Flavivirus Infection by Hijacking Exosome-Mediated Cell-Cell Communication: New Insights on Virus-Host Interactions

The arthropod-borne flaviviruses are important human pathogens, and a deeper understanding of the virus-host cell interaction is required to identify cellular targets that can be used as therapeutic candidates. It is well reported that the flaviviruses hijack several cellular functions, such as exosome-mediated cell communication during infection, which is modulated by the delivery of the exosomal cargo of pro- or antiviral molecules to the receiving host cells. Therefore, to study the role of exosomes during flavivirus infections is essential, not only to understand its relevance in virus-host interaction, but also to identify molecular factors that may contribute to the development of new strategies to block these viral infections. This review explores the implications of exosomes in flavivirus dissemination and transmission from the vector to human host cells, as well as their involvement in the host immune response. The hypothesis about exosomes as a transplacental infection route of ZIKV and the paradox effect or the dual role of exosomes released during flavivirus infection are also discussed here. Although several studies have been performed in order to identify and characterize cellular and viral molecules released in exosomes, it is not clear how all of these components participate in viral pathogenesis. Further studies will determine the balance between protective and harmful exosomes secreted by flavivirus infected cells, the characteristics and components that distinguish them both, and how they could be a factor that determines the infection outcome.

Small Heterodimer Partner Controls the Virus-Mediated Antiviral Immune Response by Targeting CREB-Binding Protein in the Nucleus

Small heterodimer partner (SHP) is an orphan nuclear receptor that acts as a transcriptional co-repressor by interacting with nuclear receptors and transcription factors. Although SHP plays a negative regulatory function in various signaling pathways, its role in virus infection has not been studied. Here, we report that SHP is a potent negative regulator of the virus-mediated type I IFN signaling that maintains homeostasis within the antiviral innate immune system. Upon virus infection, SHP interacts specifically with CREB-binding protein (CBP) in the nucleus, thereby obstructing CBP/β-catenin interaction competitively. Consequently, SHP-deficient cells enhance antiviral responses, including transcription of the type I IFN gene, upon virus infection. Furthermore, SHP-deficient mice show higher levels of IFN production and are more resistant to influenza A virus infection. Our results suggest that SHP is a nuclear regulator that blocks transcription of the type I IFN gene to inhibit excessive innate immune responses.

Regulation of interferon stimulated gene expression levels at homeostasis

Interferon stimulated genes (ISGs), a collection of genes important in the early innate immune response, are upregulated in response to stimulation by extracellular type I interferons. The regulation of ISGs has been extensively studied in cells exposed to significant interferon stimulation, but less is known about ISG regulation in homeostatic regimes in which extracellular interferon levels are low. Using a collection of pre-existing, publicly available microarray datasets, we investigated ISG regulation at homeostasis in CD4, pulmonary epithelial, fibroblast and macrophage cells. We used a linear regression model to predict ISG expression levels from regulator expression levels. Our results suggest significant regulation of ISG expression at homeostasis, both through the ISGF3 molecule and through IRF7 and IRF8 associated pathways. We find that roughly 50% of ISGs have expression levels significantly correlated with ISGF3 expression levels at homeostasis, supporting previous results suggesting that homeostatic IFN levels have broad functional consequences. We find that ISG expression levels varied in their correlation with ISGF3, with epithelial and macrophage cells showing more correlation than CD4 and fibroblast cells. Our analysis provides a novel approach for decomposing and quantifying ISG regulation.

West Nile Virus-Inclusive Single-Cell RNA Sequencing Reveals Heterogeneity in the Type I Interferon Response within Single Cells

West Nile virus (WNV) is a neurotropic mosquito-borne flavivirus of global importance. Neuroinvasive WNV infection results in encephalitis and can lead to prolonged neurological impairment or death. Type I interferon (IFN-I) is crucial for promoting antiviral defenses through the induction of antiviral effectors, which function to restrict viral replication and spread. However, our understanding of the antiviral response to WNV infection is mostly derived from analysis of bulk cell populations. It is becoming increasingly apparent that substantial heterogeneity in cellular processes exists among individual cells, even within a seemingly homogenous cell population. Here, we present WNV-inclusive single-cell RNA sequencing (scRNA-seq), an approach to examine the transcriptional variation and viral RNA burden across single cells. We observed that only a few cells within the bulk population displayed robust transcription of IFN-β mRNA, and this did not appear to depend on viral RNA abundance within the same cell. Furthermore, we observed considerable transcriptional heterogeneity in the IFN-I response, with genes displaying high unimodal and bimodal expression patterns. Broadly, IFN-stimulated genes negatively correlated with viral RNA abundance, corresponding with a precipitous decline in expression in cells with high viral RNA levels. Altogether, we demonstrated the feasibility and utility of WNV-inclusive scRNA-seq as a high-throughput technique for single-cell transcriptomics and WNV RNA detection. This approach can be implemented in other models to provide insights into the cellular features of protective immunity and identify novel therapeutic targets.IMPORTANCE West Nile virus (WNV) is a clinically relevant pathogen responsible for recurrent epidemics of neuroinvasive disease. Type I interferon is essential for promoting an antiviral response against WNV infection; however, it is unclear how heterogeneity in the antiviral response at the single-cell level impacts viral control. Specifically, conventional approaches lack the ability to distinguish differences across cells with varying viral abundance. The significance of our research is to demonstrate a new technique for studying WNV infection at the single-cell level. We discovered extensive variation in antiviral gene expression and viral abundance across cells. This protocol can be applied to primary cells or in vivo models to better understand the underlying cellular heterogeneity following WNV infection for the development of targeted therapeutic strategies.

Investigating Functional Roles for Positive Feedback and Cellular Heterogeneity in the Type I Interferon Response to Viral Infection

Secretion of type I interferons (IFN) by infected cells mediates protection against many viruses, but prolonged or excessive type I IFN secretion can lead to immune pathology. A proper type I IFN response must therefore maintain a balance between protection and excessive IFN secretion. It has been widely noted that the type I IFN response is driven by positive feedback and is heterogeneous, with only a fraction of infected cells upregulating IFN expression even in clonal cell lines, but the functional roles of feedback and heterogeneity in balancing protection and excessive IFN secretion are not clear. To investigate the functional roles for feedback and heterogeneity, we constructed a mathematical model coupling IFN and viral dynamics that extends existing mathematical models by accounting for feedback and heterogeneity. We fit our model to five existing datasets, reflecting different experimental systems. Fitting across datasets allowed us to compare the IFN response across the systems and suggested different signatures of feedback and heterogeneity in the different systems. Further, through numerical experiments, we generated hypotheses of functional roles for IFN feedback and heterogeneity consistent with our mathematical model. We hypothesize an inherent tradeoff in the IFN response: a positive feedback loop prevents excessive IFN secretion, but also makes the IFN response vulnerable to viral antagonism. We hypothesize that cellular heterogeneity of the IFN response functions to protect the feedback loop from viral antagonism. Verification of our hypotheses will require further experimental studies. Our work provides a basis for analyzing the type I IFN response across systems.

Single-cell analysis reveals that stochasticity and paracrine signaling control interferon-alpha production by plasmacytoid dendritic cells

Type I interferon (IFN) is a key driver of immunity to infections and cancer. Plasmacytoid dendritic cells (pDCs) are uniquely equipped to produce large quantities of type I IFN but the mechanisms that control this process are poorly understood. Here we report on a droplet-based microfluidic platform to investigate type I IFN production in human pDCs at the single-cell level. We show that type I IFN but not TNFα production is limited to a small subpopulation of individually stimulated pDCs and controlled by stochastic gene regulation. Combining single-cell cytokine analysis with single-cell RNA-seq profiling reveals no evidence for a pre-existing subset of type I IFN-producing pDCs. By modulating the droplet microenvironment, we demonstrate that vigorous pDC population responses are driven by a type I IFN amplification loop. Our study highlights the significance of stochastic gene regulation and suggests strategies to dissect the characteristics of immune responses at the single-cell level.

Plasmacytoid dendritic cells (pDC) are a pivotal component of the immune system. Here, the authors utilize single-cell microfluidics to interrogate the human pDC compartment and reveal a subset of type I IFN secreting pDCs that is regulated by stochastic gene expression and amplified by microenvironmental cues.

Kinetic Modeling of Virus Growth in Cells

When a virus infects a host cell, it hijacks the biosynthetic capacity of the cell to produce virus progeny, a process that may take less than an hour or more than a week. The overall time required for a virus to reproduce depends collectively on the rates of multiple steps in the infection process, including initial binding of the virus particle to the surface of the cell, virus internalization and release of the viral genome within the cell, decoding of the genome to make viral proteins, replication of the genome, assembly of progeny virus particles, and release of these particles into the extracellular environment. For a large number of virus types, much has been learned about the molecular mechanisms and rates of the various steps. However, in only relatively few cases during the last 50 years has an attempt been made-using mathematical modeling-to account for how the different steps contribute to the overall timing and productivity of the infection cycle in a cell. Here we review the initial case studies, which include studies of the one-step growth behavior of viruses that infect bacteria (Qβ, T7, and M13), human immunodeficiency virus, influenza A virus, poliovirus, vesicular stomatitis virus, baculovirus, hepatitis B and C viruses, and herpes simplex virus. Further, we consider how such models enable one to explore how cellular resources are utilized and how antiviral strategies might be designed to resist escape. Finally, we highlight challenges and opportunities at the frontiers of cell-level modeling of virus infections.

Cell fate in antiviral response arises in the crosstalk of IRF, NF-κB and JAK/STAT pathways

The innate immune system processes pathogen-induced signals into cell fate decisions. How information is turned to decision remains unknown. By combining stochastic mathematical modelling and experimentation, we demonstrate that feedback interactions between the IRF3, NF-κB and STAT pathways lead to switch-like responses to a viral analogue, poly(I:C), in contrast to pulse-like responses to bacterial LPS. Poly(I:C) activates both IRF3 and NF-κB, a requirement for induction of IFNβ expression. Autocrine IFNβ initiates a JAK/STAT-mediated positive-feedback stabilising nuclear IRF3 and NF-κB in first responder cells. Paracrine IFNβ, in turn, sensitises second responder cells through a JAK/STAT-mediated positive feedforward pathway that upregulates the positive-feedback components: RIG-I, PKR and OAS1A. In these sensitised cells, the 'live-or-die' decision phase following poly(I:C) exposure is shorter-they rapidly produce antiviral responses and commit to apoptosis. The interlinked positive feedback and feedforward signalling is key for coordinating cell fate decisions in cellular populations restricting pathogen spread.

Single-cell analysis of early antiviral gene expression reveals a determinant of stochastic IFNB1 expression

RIG-I-like receptors (RLRs) are cytoplasmic sensors of viral RNA that trigger the signaling cascade that leads to type I interferon (IFN) production. Transcriptional induction of RLRs by IFN is believed to play the role of positive feedback to further amplify viral sensing. We found that RLRs and several other IFN-stimulated genes (ISGs) are induced early in viral infection independent of IFN. Expression of these early ISGs requires IRF3/IRF7 and is highly correlated amongst them. Simultaneous detection of mRNA of IFNB1, viral replicase, and ISGs revealed distinct populations of IFNB1 expressing and non-expressing cells which are highly correlated with the levels of early ISGs but are uncorrelated with IFN-dependent ISGs and viral gene expression. Individual expression of RLRs made IFNB1 expression more robust and earlier, suggesting a causal relation between levels of RLR and induction of IFN.

Replication defective viral genomes exploit a cellular pro-survival mechanism to establish paramyxovirus persistence

Replication defective viral genomes (DVGs) generated during virus replication are the primary triggers of antiviral immunity in many RNA virus infections. However, DVGs can also facilitate viral persistence. Why and how these two opposing functions of DVGs are achieved remain unknown. Here we report that during Sendai and respiratory syncytial virus infections DVGs selectively protect a subpopulation of cells from death, thereby promoting the establishment of persistent infections. We find that during Sendai virus infection this phenotype results from DVGs stimulating a mitochondrial antiviral-signaling (MAVS)-mediated TNF response that drives apoptosis of highly infected cells while extending the survival of cells enriched in DVGs. The pro-survival effect of TNF depends on the activity of the TNFR2/TRAF1 pathway that is regulated by MAVS signaling. These results identify TNF as a pivotal factor in determining cell fate during a viral infection and delineate a MAVS/TNFR2-mediated mechanism that drives the persistence of otherwise acute viruses.

Replication defective viral genomes (DVGs) can facilitate persistence of paramyxoviruses, but the underlying mechanisms are unclear. Using FISH, Xu et al. here analyze the cellular response to DVGs on a single cell level and show that a MAVS-mediated TNF response specifically extends survival of cells enriched in DVGs.

Gene Expression Correlates with the Number of Herpes Viral Genomes Initiating Infection in Single Cells

Viral gene expression varies significantly among genetically identical cells. The sources of these variations are not well understood and have been suggested to involve both deterministic host differences and stochastic viral host interactions. For herpesviruses, only a limited number of incoming viral genomes initiate expression and replication in each infected cell. To elucidate the effect of this limited number of productively infecting genomes on viral gene expression in single cells, we constructed a set of fluorescence-expressing genetically tagged herpes recombinants. The number of different barcodes originating from a single cell is a good representative of the number of incoming viral genomes replicating (NOIVGR) in that cell. We identified a positive correlation between the NOIVGR and viral gene expression, as measured by the fluorescent protein expressed from the viral genome. This correlation was identified in three distinct cell-types, although the average NOIVGR per cell differed among these cell-types. Among clonal single cells, high housekeeping gene expression levels are not supportive of high viral gene expression, suggesting specific host determinants effecting viral infection. We developed a model to predict NOIVGR from cellular parameters, which supports the notion that viral gene expression is tightly linked to the NOIVGR in single-cells. Our results support the hypothesis that the stochastic nature of viral infection and host cell determinants contribute together to the variability observed among infected cells.

Single cell variation is of major interest in understanding key biological processes, like cancer, development and host pathogen interaction. During viral infection, these cell to cell variations can change the outcome of the whole organism infection. We suggested that differences in the number of parental viral genomes that initiate the replication process alter the outcome of infection among single cells. In this work we present a method based on genetically barcoded herpesvirus recombinants to identify the number of viral genomes initiating replication in individual cells. Our results indicate that viral gene expression is tightly linked to the number of viral genomes replicating per cell. Remarkably, we found that high cellular gene expression was an indicator for a lower viral gene expression in a given cell. We suggest that variations among single cells result from preexisting differences among cells, as well as from random viral host interactions.

High-Throughput Single-Cell Kinetics of Virus Infections in the Presence of Defective Interfering Particles

Defective interfering particles (DIPs) are virus mutants that lack essential genes for growth. In coinfections with helper virus, the diversion of viral proteins to the replication and packaging of DIP genomes can interfere with virus production. Mounting cases of DIPs and DIP-like genomes in clinical and natural isolates, as well as growing interest in DIP-based therapies, underscore a need to better elucidate how DIPs work. DIP activity is primarily measured by its inhibition of virus infection yield, an endpoint that masks the dynamic and potentially diverse individual cell behaviors. Using vesicular stomatitis virus (VSV) as a model, we coinfected BHK cells with VSV DIPs and recombinant helper virus carrying a gene encoding a red fluorescent protein (RFP) whose expression correlates with the timing and level of virus release. For single cells within a monolayer, 10 DIPs per cell suppressed the reporter expression in only 1.2% of the cells. In most cells, it slowed and reduced viral gene expression, manifested as a shift in mean latent time from 4 to 6 h and reduced virus yields by 10-fold. For single cells isolated in microwells, DIP effects were more pronounced, reducing virus yields by 100-fold and extending latent times to 12 h, including individual instances above 20 h. Together, these results suggest that direct or indirect cell-cell interactions prevent most coinfected cells from being completely suppressed by DIPs. Finally, a gamma distribution model captures well how the infection kinetics quantitatively depends on the DIP dose. Such models will be useful for advancing a predictive biology of DIP-associated virus growth and infection spread.

IMPORTANCE

During the last century, basic studies in virology have focused on developing a molecular mechanistic understanding of how infectious viruses reproduce in their living host cells. However, over the last 10 years, the advent of deep sequencing and other powerful technologies has revealed in natural and patient infections that viruses do not act alone. Instead, viruses are often accompanied by defective virus-like particles that carry large deletions in their genomes and fail to replicate on their own. Coinfections of viable and defective viruses behave in unpredictable ways, but they often interfere with normal virus growth, potentially enabling infections to evade host immune surveillance. In the current study, controlled levels of defective viruses are coinfected with viable viruses that have been engineered to express a fluorescent reporter protein during infection. Unique profiles of reporter expression acquired from thousands of coinfected cells reveal how interference acts at multiple stages of infection.

Live Cell Analysis and Mathematical Modeling Identify Determinants of Attenuation of Dengue Virus 2'-O-Methylation Mutant

Dengue virus (DENV) is the most common mosquito-transmitted virus infecting ~390 million people worldwide. In spite of this high medical relevance, neither a vaccine nor antiviral therapy is currently available. DENV elicits a strong interferon (IFN) response in infected cells, but at the same time actively counteracts IFN production and signaling. Although the kinetics of activation of this innate antiviral defense and the timing of viral counteraction critically determine the magnitude of infection and thus disease, quantitative and kinetic analyses are lacking and it remains poorly understood how DENV spreads in IFN-competent cell systems. To dissect the dynamics of replication versus antiviral defense at the single cell level, we generated a fully viable reporter DENV and host cells with authentic reporters for IFN-stimulated antiviral genes. We find that IFN controls DENV infection in a kinetically determined manner that at the single cell level is highly heterogeneous and stochastic. Even at high-dose, IFN does not fully protect all cells in the culture and, therefore, viral spread occurs even in the face of antiviral protection of naïve cells by IFN. By contrast, a vaccine candidate DENV mutant, which lacks 2’-O-methylation of viral RNA is profoundly attenuated in IFN-competent cells. Through mathematical modeling of time-resolved data and validation experiments we show that the primary determinant for attenuation is the accelerated kinetics of IFN production. This rapid induction triggered by mutant DENV precedes establishment of IFN-resistance in infected cells, thus causing a massive reduction of virus production rate. In contrast, accelerated protection of naïve cells by paracrine IFN action has negligible impact. In conclusion, these results show that attenuation of the 2’-O-methylation DENV mutant is primarily determined by kinetics of autocrine IFN action on infected cells.

Dengue virus (DENV) infection is a global health problem for which no selective therapy or vaccine exists. The magnitude of infection critically depends on the induction kinetics of the interferon (IFN) response and the kinetics of viral countermeasures. Here we established a novel live cell imaging system to dissect the dynamics of this interplay. We find that IFN controls DENV infection in a kinetically determined manner. At the single cell level, the IFN response is highly heterogeneous and stochastic, likely accounting for viral spread in the presence of IFN. Mathematical modeling and validation experiments show that the kinetics of activation of the IFN response critically determines control of virus replication and spread. A vaccine candidate DENV mutant lacking 2’-O-methylation of viral RNA is profoundly attenuated in IFN-competent cells. This attenuation is primarily due to accelerated kinetics of IFN production acting on infected cells in an autocrine manner. In contrast, accelerated protection of naïve cells by paracrine IFN action has negligible impact. Thus, attenuation of the 2’-O-methylation DENV mutant is primarily determined by kinetics of autocrine IFN action on infected cells.

Human Dendritic Cell Response Signatures Distinguish 1918, Pandemic, and Seasonal H1N1 Influenza Viruses

Influenza viruses continue to present global threats to human health. Antigenic drift and shift, genetic reassortment, and cross-species transmission generate new strains with differences in epidemiology and clinical severity. We compared the temporal transcriptional responses of human dendritic cells (DC) to infection with two pandemic (A/Brevig Mission/1/1918, A/California/4/2009) and two seasonal (A/New Caledonia/20/1999, A/Texas/36/1991) H1N1 influenza viruses. Strain-specific response differences included stronger activation of NF-κB following infection with A/New Caledonia/20/1999 and a unique cluster of genes expressed following infection with A/Brevig Mission/1/1918. A common antiviral program showing strain-specific timing was identified in the early DC response and found to correspond with reported transcript changes in blood during symptomatic human influenza virus infection. Comparison of the global responses to the seasonal and pandemic strains showed that a dramatic divergence occurred after 4 h, with only the seasonal strains inducing widespread mRNA loss.

IMPORTANCE

Continuously evolving influenza viruses present a global threat to human health; however, these host responses display strain-dependent differences that are incompletely understood. Thus, we conducted a detailed comparative study assessing the immune responses of human DC to infection with two pandemic and two seasonal H1N1 influenza strains. We identified in the immune response to viral infection both common and strain-specific features. Among the stain-specific elements were a time shift of the interferon-stimulated gene response, selective induction of NF-κB signaling by one of the seasonal strains, and massive RNA degradation as early as 4 h postinfection by the seasonal, but not the pandemic, viruses. These findings illuminate new aspects of the distinct differences in the immune responses to pandemic and seasonal influenza viruses.

Fluorescence-Activated Cell Sorting-Based Analysis Reveals an Asymmetric Induction of Interferon-Stimulated Genes in Response to Seasonal Influenza A Virus

Influenza A virus (IAV) infection provokes an antiviral response involving the expression of type I and III interferons (IFN) and IFN-stimulated genes (ISGs) in infected cell cultures. However, the spatiotemporal dynamics of the IFN reaction are incompletely understood, as previous studies investigated mainly the population responses of virus-infected cultures, although substantial cell-to-cell variability has been documented. We devised a fluorescence-activated cell sorting-based assay to simultaneously quantify expression of viral antigens and ISGs, such as ISG15, MxA, and IFIT1, in IAV-infected cell cultures at the single-cell level. This approach revealed that seasonal IAV triggers an unexpected asymmetric response, as the major cell populations expressed either viral antigen or ISG, but rarely both. Further investigations identified a role of the viral NS1 protein in blocking ISG expression in infected cells, which surprisingly did not reduce paracrine IFN signaling to noninfected cells. Interestingly, viral ISG control was impaired in cultures infected with avian-origin IAV, including the H7N9 virus from eastern China. This phenotype was traced back to polymorphic NS1 amino acids known to be important for stable binding of the polyadenylation factor CPSF30 and concomitant suppression of host cell gene expression. Most significantly, mutation of two amino acids within the CPSF30 attachment site of NS1 from seasonal IAV diminished the strict control of ISG expression in infected cells and substantially attenuated virus replication. In conclusion, our approach revealed an asymmetric, NS1-dependent ISG induction in cultures infected with seasonal IAV, which appears to be essential for efficient virus propagation.

IMPORTANCE

Interferons are expressed by infected cells in response to IAV infection and play important roles in the antiviral immune response by inducing hundreds of interferon-stimulated genes (ISGs). Unlike many previous studies, we investigated the ISG response at the single-cell level, enabling novel insights into this virus-host interaction. Hence, cell cultures infected with seasonal IAV displayed an asymmetric ISG induction that was confined almost exclusively to noninfected cells. In comparison, ISG expression was observed in larger cell populations infected with avian-origin IAV, suggesting a more resolute antiviral response to these strains. Strict control of ISG expression by seasonal IAV was explained by the binding of the viral NS1 protein to the polyadenylation factor CPSF30, which reduces host cell gene expression. Mutational disruption of CPSF30 binding within NS1 concomitantly attenuated ISG control and replication of seasonal IAV, illustrating the importance of maintaining an asymmetric ISG response for efficient virus propagation.

Negative feedback contributes to the stochastic expression of the interferon-β gene in virus-triggered type I interferon signaling pathways

Type I interferon (IFN) signaling pathways play an essential role in the defense against early viral infections; however, the diverse and intricate molecular mechanisms of virus-triggered type I IFN responses are still poorly understood. In this study, we analyzed and compared two classes of models i.e., deterministic ordinary differential equations (ODEs) and stochastic models to elucidate the dynamics and stochasticity of type I IFN signaling pathways. Bifurcation analysis based on an ODE model reveals that the system exhibits a bistable switch and a one-way switch at high or low levels when the strengths of the negative and positive feedbacks are tuned. Furthermore, we compared the stochastic simulation results under the Master and Langevin equations. Both of the stochastic equations generate the bistable switch phenomenon, and the distance between two stable states are smaller than normal under the simulation of the Langevin equation. The quantitative computations also show that a moderate ratio between positive and negative feedback strengths is required to ensure a reliable switch between the different IFN concentrations that regulate the immune response. Moreover, we propose a multi-state stochastic model based on the above deterministic model to describe the multi-cellular system coupled with the diffusion of IFNs. The perturbation and inhibition analysis showed that the positive feedback, as well as noises, has little effect on the stochastic expression of IFNs, but the negative feedback of ISG56 on the activation of IRF7 has a great influence on IFN stochastic expression. Together, these results reveal that positive feedback stabilizes IFN gene expression, and negative feedback may be the main contribution to the stochastic expression of the IFN gene in the virus-triggered type I IFN response. These findings will provide new insight into the molecular mechanisms of virus-triggered type I IFN signaling pathways.

Single-cell analysis shows that paracrine signaling by first responder cells shapes the interferon-β response to viral infection

Immune responses to viral infection are stochastic processes, which initiate in a limited number of cells that then propagate the response. A key component of the response to viral infection entails the synthesis and secretion of type I interferons (IFNs), including the early induction of the gene encoding IFN-β (Ifnb1). With single-cell analysis and mathematical modeling, we investigated the mechanisms underlying how increases in the amount of Ifnb1 mRNA per cell and in the numbers of cells expressing Ifnb1 calibrate the response to viral infection. We used single-cell, single-molecule assays to quantify the early induction of Ifnb1 expression (the Ifnb1 response) in human monocyte-derived dendritic cells infected with Newcastle disease virus, thus retaining the physiological stoichiometry of transcriptional regulators to both alleles of the Ifnb1 gene. We applied computational methods to extract the stochastic features that underlie the cell-to-cell variations in gene expression over time. Integration of simulations and experiments identified the role of paracrine signaling in increasing the number of cells that express Ifnb1 over time and in calibrating the immune response to viral infection.

Heterogeneity in immune responses: from populations to single cells

The mammalian immune system is tasked with protecting the host against a broad range of threats. Understanding how immune populations leverage cellular diversity to achieve this breadth and flexibility, particularly during dynamic processes such as differentiation and antigenic response, is a core challenge that is well suited for single cell analysis. Recent years have witnessed transformative and intersecting advances in nanofabrication and genomics that enable deep profiling of individual cells, affording exciting opportunities to study heterogeneity in the immune response at an unprecedented scope. In light of these advances, here we review recent work exploring how immune populations generate and leverage cellular heterogeneity at multiple molecular and phenotypic levels. Additionally, we highlight opportunities for single cell technologies to shed light on the causes and consequences of heterogeneity in the immune system.

Noise propagation through extracellular signaling leads to fluctuations in gene expression

BACKGROUND

Cell-to-cell variability in mRNA and proteins has been observed in many biological systems, including the human innate immune response to viral infection. Most of these studies have focused on variability that arises from (a) intrinsic stochastic fluctuations in gene expression and (b) extrinsic sources (e.g. fluctuations in transcription factors). The main focus of our study is the effect of extracellular signaling on enhancing intrinsic stochastic fluctuations. As a new source of noise, the communication between cells with fluctuating numbers of components has received little attention. We use agent-based modeling to study this contribution to noise in a system of human dendritic cells responding to viral infection.

RESULTS

Our results, validated by single-cell experiments, show that in the transient state cell-to-cell variability in an interferon-stimulated gene (DDX58) arises from the interplay between the spatial randomness of the cellular sources of the interferon and the temporal stochasticity of its own production. The numerical simulations give insight into the time scales on which autocrine and paracrine signaling act in a heterogeneous population of dendritic cells upon viral infection. We study the effect of different factors that influence the magnitude of the cell-to-cell-variability of the induced gene, including the cell density, multiplicity of infection, and the time scale over which the cellular sources begin producing the cytokine.

CONCLUSIONS

We propose a mechanism of noise propagation through extracellular communication and establish conditions under which the mechanism is operative. The cellular stochasticity of gene induction, which we investigate, is not limited to the specific interferon-induced gene we have studied; a broad distribution of copy numbers across cells is to be expected for other interferon-stimulated genes. This can lead to functional consequences for the system-level response to a viral challenge.

Evidence of expression variation and allelic imbalance in Crohn's disease susceptibility genes NOD2 and ATG16L1 in human dendritic cells

Human dendritic cells (DCs) play an important role in induction and progression of Crohn's disease (CD). Accumulating evidence suggests that viral infection is required to trigger CD pathogenesis in genetically predisposed individuals. NOD2 and ATG16L1 are among the major CD susceptibility genes implicated in impaired immune response to bacterial infection. In this study, we investigated gene expression and allelic imbalance (AI) of NOD2 and ATG16L1 using common variants in human monocyte-derived DCs. Significant AI was observed in ~40% and ~70% of NOD2 and ATG16L1 heterozygotes, respectively (p<0.05). AI of NOD2 was inversely associated with its expression level (p=0.015). No correlation was detected between gene expression and AI for ATG16L1. When infected with Newcastle Disease Virus (NDV), NOD2 expression in DCs was induced about four-fold (p<0.001), whereas ATG16L1 expression was not affected (p=0.88). In addition, NDV infection tended to lower the variance in AI among DC populations for the NOD2 gene (p=0.05), but not the ATG16L1 gene (p=0.32). Findings of a simulation study, aimed to verify whether the observed variation in gene expression and AI is a result of sample-to-sample variability or experimental measurement error, suggested that NOD2 AI is likely to result from a deterministic event at a single cell level. Overall, our results present initial evidence that AI of the NOD2 and ATG16L1 genes exists in populations of human DCs. In addition, our findings suggest that viral infection may regulate NOD2 expression.

Computational approaches to understanding dendritic cell responses to influenza virus infection

The evolution of immunology research from measurements of single entities to large-scale data-intensive assays necessitates the integration of experimental work with bioinformatics and computational approaches. The introduction of physics into immunology has led to the study of new phenomena, such as cellular noise, which is likely to prove increasingly important to understand immune system responses. The fusion of "hard science" and biology is also leading to a re-examination of data acquisition, analysis, and statistical validation and is resulting in the development of easy-to-access tools for immunology research. Here, we review some of our models, computational tools, and results related to studies of the innate immune response of human dendritic cells to viral infection. Our project functions on an open model across institutions with electronic record keeping and public sharing of data. Our tools, models, and data can be accessed at http://tsb.mssm.edu/primeportal/ .

Biphasic RLR-IFN-β response controls the balance between antiviral immunity and cell damage

In RNA virus-infected cells, retinoic acid-inducible gene-I-like receptors (RLRs) sense foreign RNAs and activate signaling cascades to produce IFN-α/β. However, not every infected cell produces IFN-α/β that exhibits cellular heterogeneity in antiviral immune responses. Using the IFN-β-GFP reporter system, we observed bimodal IFN-β production in the uniformly stimulated cell population with intracellular dsRNA. Mathematical simulation proposed the strength of autocrine loop via RLR as one of the contributing factor for biphasic IFN-β expression. Bimodal IFN-β production with intracellular dsRNA was disturbed by blockage of IFN-α/β secretion or by silencing of the IFN-α/β receptor. Amplification of RLRs was critical in the generation of bimodality of IFN-β production, because IFN-β(high) population expressed more RLRs than IFN-β(low) population. In addition, bimodality in IFN-β production results in biphasic cellular response against infection, because IFN-β(high) population was more prone to apoptosis than IFN-β(low) population. These results suggest that RLR-mediated biphasic cellular response may act to restrict the number of cells expressing IFN-β and undergoing apoptosis in the infected population.

Activation and regulation of interferon-β in immune responses

Interferons (IFNs) were discovered more than half a century ago, and extensive research has since identified multifarious roles for type I IFN in human immune responses. Here, we review the functions of IFN-β in innate and adaptive immunity. We also discuss the activation and influence of IFN-β on myeloid cell types, including monocytes and dendritic cells, as well as address the effects of IFN-β on T cells and B cells. Findings from our own laboratory, which explores the molecular mechanisms of IFN-β activation by LPS and viruses, as well as from other groups investigating the regulation of IFN-β by viral proteins and endogenous factors are described. The effects of post-translational modifications of the interferon regulatory factor (IRF)-3 on IFN-β induction are also highlighted. Many unanswered questions remain concerning the regulation of the type I IFN response in inflammation, especially the role of transcription factors in the modulation of inflammatory gene expression, and these questions will form the basis for exciting avenues of future research.

Understanding immunology via engineering design: the role of mathematical prototyping

A major challenge in immunology is how to translate data into knowledge given the inherent complexity and dynamics of human physiology. Both the physiology and engineering communities have rich histories in applying computational approaches to translate data obtained from complex systems into knowledge of system behavior. However, there are some differences in how disciplines approach problems. By referring to mathematical models as mathematical prototypes, we aim to highlight aspects related to the process (i.e., prototyping) rather than the product (i.e., the model). The objective of this paper is to review how two related engineering concepts, specifically prototyping and "fitness for use," can be applied to overcome the pressing challenge in translating data into improved knowledge of basic immunology that can be used to improve therapies for disease. These concepts are illustrated using two immunology-related examples. The prototypes presented focus on the beta cell mass at the onset of type 1 diabetes and the dynamics of dendritic cells in the lung. This paper is intended to illustrate some of the nuances associated with applying mathematical modeling to improve understanding of the dynamics of disease progression in humans.

Multi-layered stochasticity and paracrine signal propagation shape the type-I interferon response

The cellular recognition of viruses evokes the secretion of type-I interferons (IFNs) that induce an antiviral protective state. By live-cell imaging, we show that key steps of virus-induced signal transduction, IFN-β expression, and induction of IFN-stimulated genes (ISGs) are stochastic events in individual cells. The heterogeneity in IFN production is of cellular-and not viral-origin, and temporal unpredictability of IFN-β expression is largely due to cell-intrinsic noise generated both upstream and downstream of the activation of nuclear factor-κB and IFN regulatory factor transcription factors. Subsequent ISG induction occurs as a stochastic all-or-nothing switch, where the responding cells are protected against virus replication. Mathematical modelling and experimental validation show that reliable antiviral protection in the face of multi-layered cellular stochasticity is achieved by paracrine response amplification. Achieving coherent responses through intercellular communication is likely to be a more widely used strategy by mammalian cells to cope with pervasive stochasticity in signalling and gene expression.

Kinetics of virus production from single cells

The production of virus by infected cells is an essential process for the spread and persistence of viral diseases, the effectiveness of live-viral vaccines, and the manufacture of viruses for diverse applications. Yet despite its importance, methods to precisely measure virus production from cells are lacking. Most methods test infected-cell populations, masking how individual cells behave. Here we measured the kinetics of virus production from single cells. We combined simple steps of liquid-phase infection, serial dilution, centrifugation, and harvesting, without specialized equipment, to track the production of virus particles from BHK cells infected with vesicular stomatitis virus. Remarkably, cell-to-cell differences in latent times to virus release were within a factor of two, while production rates and virus yields spanned over 300-fold, highlighting an extreme diversity in virus production for cells from the same population. These findings have fundamental and technological implications for health and disease.

Multi-scale stochastic simulation of diffusion-coupled agents and its application to cell culture simulation

Many biological systems consist of multiple cells that interact by secretion and binding of diffusing molecules, thus coordinating responses across cells. Techniques for simulating systems coupling extracellular and intracellular processes are very limited. Here we present an efficient method to stochastically simulate diffusion processes, which at the same time allows synchronization between internal and external cellular conditions through a modification of Gillespie's chemical reaction algorithm. Individual cells are simulated as independent agents, and each cell accurately reacts to changes in its local environment affected by diffusing molecules. Such a simulation provides time-scale separation between the intra-cellular and extra-cellular processes. We use our methodology to study how human monocyte-derived dendritic cells alert neighboring cells about viral infection using diffusing interferon molecules. A subpopulation of the infected cells reacts early to the infection and secretes interferon into the extra-cellular medium, which helps activate other cells. Findings predicted by our simulation and confirmed by experimental results suggest that the early activation is largely independent of the fraction of infected cells and is thus both sensitive and robust. The concordance with the experimental results supports the value of our method for overcoming the challenges of accurately simulating multiscale biological signaling systems.