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

Early signaling pathways in virus-infected cells

Virus infection activates specific pattern recognition receptors and immune signal transduction, resulting in pro-inflammatory cytokine production and activation of innate immunity. We describe here the molecular organization of early signaling pathways downstream of viral recognition, including conformational changes, post-translational modifications, formation of oligomers, and generation of small-molecule second messengers. Such molecular organization allows tight regulation of immune signal transduction, characterized by swift but transient responses, nonlinearity, and signal amplification. Pathologies of early immune signaling caused by genomic mutations illustrate the fine regulation of the immune transduction cascade.

Co-imaging of RelA and c-Rel reveals features of NF-κB signaling for ligand discrimination

Individual cell sensing of external cues has evolved through the temporal patterns in signaling. Since nuclear factor κB (NF-κB) signaling dynamics have been examined using a single subunit, RelA, it remains unclear whether more information might be transmitted via other subunits. Using NF-κB double-knockin reporter mice, we monitored both canonical NF-κB subunits, RelA and c-Rel, simultaneously in single macrophages by quantitative live-cell imaging. We show that signaling features of RelA and c-Rel convey more information about the stimuli than those of either subunit alone. Machine learning is used to predict the ligand identity accurately based on RelA and c-Rel signaling features without considering the co-activated factors. Ligand discrimination is achieved through selective non-redundancy of RelA and c-Rel signaling dynamics, as well as their temporal coordination. These results suggest a potential role of c-Rel in fine-tuning immune responses and highlight the need for approaches that will elucidate the mechanisms regulating NF-κB subunit specificity.

Personalizing Oncolytic Immunovirotherapy Approaches

Development of successful cancer therapeutics requires exploration of the differences in genetics, metabolism, and interactions with the immune system among malignant and normal cells. The clinical observation of spontaneous tumor regression following natural infection with microorganism has created the premise of their use as cancer therapeutics. Oncolytic viruses (OVs) originate from viruses with attenuated virulence in humans, well-characterized vaccine strains of known human pathogens, or engineered replication-deficient viral vectors. Their selectivity is based on receptor expression level and post entry restriction factors that favor replication in the tumor, while keeping the normal cells unharmed. Clinical trials have demonstrated a wide range of patient responses to virotherapy, with subgroups of patients significantly benefiting from OV administration. Tumor-specific gene signatures, including antiviral interferon-stimulated gene (ISG) expression profile, have demonstrated a strong correlation with tumor permissiveness to infection. Furthermore, the combination of OVs with immunotherapeutics, including anticancer vaccines and immune checkpoint inhibitors [ICIs, such as anti-PD-1/PD-L1 or anti-CTLA-4 and chimeric antigen receptor (CAR)-T or CAR-NK cells], could synergistically improve the therapeutic outcome. Creating response prediction algorithms represents an important step for the transition to individualized immunovirotherapy approaches in the clinic. Integrative predictors could include tumor mutational burden (TMB), inflammatory gene signature, phenotype of tumor-infiltrating lymphocytes, tumor microenvironment (TME), and immune checkpoint receptor expression on both immune and target cells. Additionally, the gut microbiota has recently been recognized as a systemic immunomodulatory factor and could further be used in the optimization of individualized immunovirotherapy algorithms.

The population context is a driver of the heterogeneous response of epithelial cells to interferons

Isogenic cells respond in a heterogeneous manner to interferon. Using a micropatterning approach combined with high-content imaging and spatial analyses, we characterized how the population context (position of a cell with respect to neighboring cells) of epithelial cells affects their response to interferons. We identified that cells at the edge of cellular colonies are more responsive than cells embedded within colonies. We determined that this spatial heterogeneity in interferon response resulted from the polarized basolateral interferon receptor distribution, making cells located in the center of cellular colonies less responsive to ectopic interferon stimulation. This was conserved across cell lines and primary cells originating from epithelial tissues. Importantly, cells embedded within cellular colonies were not protected from viral infection by apical interferon treatment, demonstrating that the population context-driven heterogeneous response to interferon influences the outcome of viral infection. Our data highlights that the behavior of isolated cells does not directly translate to their behavior in a population, placing the population context as one important factor influencing heterogeneity during interferon response in epithelial cells.

ISG15/USP18/STAT2 is a molecular hub regulating IFN I-mediated control of Dengue and Zika virus replication

The establishment of a virus infection is the result of the pathogen's ability to replicate in a hostile environment generated by the host's immune system. Here, we found that ISG15 restricts Dengue and Zika viruses' replication through the stabilization of its binding partner USP18. ISG15 expression was necessary to control DV replication driven by both autocrine and paracrine type one interferon (IFN-I) signaling. Moreover, USP18 competes with NS5-mediated STAT2 degradation, a major mechanism for establishment of flavivirus infection. Strikingly, reconstitution of USP18 in ISG15-deficient cells was sufficient to restore the STAT2's stability and restrict virus growth, suggesting that the IFNAR-mediated ISG15 activity is also antiviral. Our results add a novel layer of complexity in the virus/host interaction interface and suggest that NS5 has a narrow window of opportunity to degrade STAT2, therefore suppressing host's IFN-I mediated response and promoting virus replication.

Nonself RNA rewires IFN-β signaling: A mathematical model of the innate immune response

Type I interferons (IFNs) are key coordinators of the innate immune response to viral infection, which, through activation of the transcriptional regulators STAT1 and STAT2 (STAT1/2) in bystander cells, induce the expression of IFN-stimulated genes (ISGs). Here, we showed that in cells transfected with poly(I:C), an analog of viral RNA, the transcriptional activity of STAT1/2 was terminated because of depletion of the interferon-β (IFN-β) receptor, IFNAR. Activation of RNase L and PKR, products of two ISGs, not only hindered the replenishment of IFNAR but also suppressed negative regulators of IRF3 and NF-κB, consequently promoting IFNB transcription. We incorporated these findings into a mathematical model of innate immunity. By coupling signaling through the IRF3-NF-κB and STAT1/2 pathways with the activities of RNase L and PKR, the model explains how poly(I:C) switches the transcriptional program from being STAT1/2 induced to being IRF3 and NF-κB induced, which converts IFN-β-responding cells to IFN-β-secreting cells.

Antiviral responses are shaped by heterogeneity in viral replication dynamics

Antiviral signalling, which can be activated in host cells upon virus infection, restricts virus replication and communicates infection status to neighbouring cells. The antiviral response is heterogeneous, both quantitatively (efficiency of response activation) and qualitatively (transcribed antiviral gene set). To investigate the basis of this heterogeneity, we combined Virus Infection Real-time IMaging (VIRIM), a live-cell single-molecule imaging method, with real-time readouts of the dsRNA sensing pathway to analyse the response of human cells to encephalomyocarditis virus (EMCV) infection. We find that cell-to-cell heterogeneity in viral replication rates early in infection affect the efficiency of antiviral response activation, with lower replication rates leading to more antiviral response activation. Furthermore, we show that qualitatively distinct antiviral responses can be linked to the strength of the antiviral signalling pathway. Our analyses identify variation in early viral replication rates as an important parameter contributing to heterogeneity in antiviral response activation.

High-resolution kinetic characterization of the RIG-I-signaling pathway and the antiviral response

RIG-I recognizes viral dsRNA and activates a cell-autonomous antiviral response. Upon stimulation, it triggers a signaling cascade leading to the production of type I and III IFNs. IFNs are secreted and signal to elicit the expression of IFN-stimulated genes, establishing an antiviral state of the cell. The topology of this pathway has been studied intensively, however, its exact dynamics are less understood. Here, we employed electroporation to synchronously activate RIG-I, enabling us to characterize cell-intrinsic innate immune signaling at a high temporal resolution. Employing IFNAR1/IFNLR-deficient cells, we could differentiate primary RIG-I signaling from secondary signaling downstream of the IFN receptors. Based on these data, we developed a comprehensive mathematical model capable of simulating signaling downstream of dsRNA recognition by RIG-I and the feedback and signal amplification by IFN. We further investigated the impact of viral antagonists on signaling dynamics. Our work provides a comprehensive insight into the signaling events that occur early upon virus infection and opens new avenues to study and disentangle the complexity of the host-virus interface.

Antagonism between viral infection and innate immunity at the single-cell level

When infected with a virus, cells may secrete interferons (IFNs) that prompt nearby cells to prepare for upcoming infection. Reciprocally, viral proteins often interfere with IFN synthesis and IFN-induced signaling. We modeled the crosstalk between the propagating virus and the innate immune response using an agent-based stochastic approach. By analyzing immunofluorescence microscopy images we observed that the mutual antagonism between the respiratory syncytial virus (RSV) and infected A549 cells leads to dichotomous responses at the single-cell level and complex spatial patterns of cell signaling states. Our analysis indicates that RSV blocks innate responses at three levels: by inhibition of IRF3 activation, inhibition of IFN synthesis, and inhibition of STAT1/2 activation. In turn, proteins coded by IFN-stimulated (STAT1/2-activated) genes inhibit the synthesis of viral RNA and viral proteins. The striking consequence of these inhibitions is a lack of coincidence of viral proteins and IFN expression within single cells. The model enables investigation of the impact of immunostimulatory defective viral particles and signaling network perturbations that could potentially facilitate containment or clearance of the viral infection.

Transiently heritable fates and quorum sensing drive early IFN-I response dynamics

Type I interferon (IFN-I)-mediated antiviral responses are central to host defense against viral infections. Crucial is the tight and well-orchestrated control of cellular decision-making leading to the production of IFN-Is. Innovative single-cell approaches revealed that the initiation of IFN-I production is limited to only fractions of 1-3% of the total population, both found in vitro, in vivo, and across cell types, which were thought to be stochastically regulated. To challenge this dogma, we addressed the influence of various stochastic and deterministic host-intrinsic factors on dictating early IFN-I responses, using a murine fibroblast reporter model. Epigenetic drugs influenced the percentage of responding cells. Next, with the classical Luria-Delbrück fluctuation test, we provided evidence for transient heritability driving responder fates, which was verified with mathematical modeling. Finally, while studying varying cell densities, we substantiated an important role for cell density in dictating responsiveness, similar to the phenomenon of quorum sensing. Together, this systems immunology approach opens up new avenues to progress the fundamental understanding on cellular decision-making during early IFN-I responses, which can be translated to other (immune) signaling systems.

Modeling Cellular Signaling Variability Based on Single-Cell Data: The TGFβ-SMAD Signaling Pathway

Nongenetic heterogeneity is key to cellular decisions, as even genetically identical cells respond in very different ways to the same external stimulus, e.g., during cell differentiation or therapeutic treatment of disease. Strong heterogeneity is typically already observed at the level of signaling pathways that are the first sensors of external inputs and transmit information to the nucleus where decisions are made. Since heterogeneity arises from random fluctuations of cellular components, mathematical models are required to fully describe the phenomenon and to understand the dynamics of heterogeneous cell populations. Here, we review the experimental and theoretical literature on cellular signaling heterogeneity, with special focus on the TGFβ/SMAD signaling pathway.

Single-cell analysis reveals TLR-induced macrophage heterogeneity and quorum sensing dictate population wide anti-inflammatory feedback in response to LPS

The role of macrophages in controlling tissue inflammation is indispensable to ensure a context-appropriate response to pathogens whilst preventing excessive tissue damage. Their initial response is largely characterized by high production of tumor necrosis factor alpha (TNFα) which primes and attracts other immune cells, thereafter, followed by production of interleukin 10 (IL-10) which inhibits cell activation and steers towards resolving of inflammation. This delicate balance is understood at a population level but how it is initiated at a single-cell level remains elusive. Here, we utilize our previously developed droplet approach to probe single-cell macrophage activation in response to toll-like receptor 4 (TLR4) stimulation, and how single-cell heterogeneity and cellular communication affect macrophage-mediated inflammatory homeostasis. We show that only a fraction of macrophages can produce IL-10 in addition to TNFα upon LPS-induced activation, and that these cells are not phenotypically different from IL-10 non-producers nor exhibit a distinct transcriptional pathway. Finally, we demonstrate that the dynamics of TNFα and IL-10 are heavily controlled by macrophage density as evidenced by 3D hydrogel cultures suggesting a potential role for quorum sensing. These exploratory results emphasize the relevance of understanding the complex communication between macrophages and other immune cells and how these amount to population-wide responses.

Caspase-Mediated Regulation and Cellular Heterogeneity of the cGAS/STING Pathway in Kaposi's Sarcoma-Associated Herpesvirus Infection

As a result of the ongoing virus-host arms race, viruses have evolved numerous immune subversion strategies, many of which are aimed at suppressing the production of type I interferons (IFNs). Apoptotic caspases have recently emerged as important regulators of type I IFN signaling both in noninfectious contexts and during viral infection. Despite being widely considered antiviral factors since they can trigger cell death, several apoptotic caspases promote viral replication by suppressing innate immune response. Indeed, we previously discovered that the AIDS-associated oncogenic gammaherpesvirus Kaposi's sarcoma-associated herpesvirus (KSHV) exploits caspase activity to suppress the antiviral type I IFN response and promote viral replication. However, the mechanism of this novel viral immune evasion strategy is poorly understood, particularly with regard to how caspases antagonize IFN signaling during KSHV infection. Here, we show that caspase activity inhibits the DNA sensor cGAS during KSHV lytic replication to block type I IFN induction. Furthermore, we used single-cell RNA sequencing to reveal that the potent antiviral state conferred by caspase inhibition is mediated by an exceptionally small percentage of IFN-β-producing cells, thus uncovering further complexity of IFN regulation during viral infection. Collectively, these results provide insight into multiple levels of cellular type I IFN regulation that viruses co-opt for immune evasion. Unraveling these mechanisms can inform targeted therapeutic strategies for viral infections and reveal cellular mechanisms of regulating interferon signaling in the context of cancer and chronic inflammatory diseases. IMPORTANCE Type I interferons are key factors that dictate the outcome of infectious and inflammatory diseases. Thus, intricate cellular regulatory mechanisms are in place to control IFN responses. While viruses encode their own immune-regulatory proteins, they can also usurp existing cellular interferon regulatory functions. We found that caspase activity during lytic infection with the AIDS-associated oncogenic gammaherpesvirus Kaposi's sarcoma-associated herpesvirus inhibits the DNA sensor cGAS to block the antiviral type I IFN response. Moreover, single-cell RNA sequencing analyses unexpectedly revealed that an exceptionally small subset of infected cells (<5%) produce IFN, yet this is sufficient to confer a potent antiviral state. These findings reveal new aspects of type I IFN regulation and highlight caspases as a druggable target to modulate cGAS activity.

Type I Interferon Signaling Controls Gammaherpesvirus Latency In Vivo

Gammaherpesviruses, such as Epstein-Barr virus and Kaposi's sarcoma-associated herpesvirus, are important human pathogens involved in lymphoproliferative disorders and tumorigenesis. Herpesvirus infections are characterized by a biphasic cycle comprised of an acute phase with lytic replication and a latent state. Murine gammaherpesvirus 68 (MHV-68) is a well-established model for the study of lytic and latent life cycles in the mouse. We investigated the interplay between the type I interferon (IFN)-mediated innate immune response and MHV-68 latency using sensitive bioluminescent reporter mice. Adoptive transfer of latently infected splenocytes into type I IFN receptor-deficient mice led to a loss of latency control. This was revealed by robust viral propagation and dissemination of MHV-68, which coincided with type I IFN reporter induction. Despite MHV-68 latency control by IFN, the continuous low-level cell-to-cell transmission of MHV-68 was detected in the presence of IFN signaling, indicating that IFN cannot fully prevent viral dissemination during latency. Moreover, impaired type I IFN signaling in latently infected splenocytes increased the risk of virus reactivation, demonstrating that IFN directly controls MHV-68 latency in infected cells. Overall, our data show that locally constrained type I IFN responses control the cellular reservoir of latency, as well as the distribution of latent infection to potential new target cells.

Deficiency for SAMHD1 activates MDA5 in a cGAS/STING-dependent manner

Defects in nucleic acid metabolizing enzymes can lead to spontaneous but selective activation of either cGAS/STING or RIG-like receptor (RLR) signaling, causing type I interferon-driven inflammatory diseases. In these pathophysiological conditions, activation of the DNA sensor cGAS and IFN production are linked to spontaneous DNA damage. Physiological, or tonic, IFN signaling on the other hand is essential to functionally prime nucleic acid sensing pathways. Here, we show that low-level chronic DNA damage in mice lacking the Aicardi-Goutières syndrome gene SAMHD1 reduced tumor-free survival when crossed to a p53-deficient, but not to a DNA mismatch repair-deficient background. Increased DNA damage did not result in higher levels of type I interferon. Instead, we found that the chronic interferon response in SAMHD1-deficient mice was driven by the MDA5/MAVS pathway but required functional priming through the cGAS/STING pathway. Our work positions cGAS/STING upstream of tonic IFN signaling in Samhd1-deficient mice and highlights an important role of the pathway in physiological and pathophysiological innate immune priming.

Stochastic dynamics of Type-I interferon responses

Interferon (IFN) activates the transcription of several hundred of IFN stimulated genes (ISGs) that constitute a highly effective antiviral defense program. Cell-to-cell variability in the induction of ISGs is well documented, but its source and effects are not completely understood. The molecular mechanisms behind this heterogeneity have been related to randomness in molecular events taking place during the JAK-STAT signaling pathway. Here, we study the sources of variability in the induction of the IFN-alpha response by using MxA and IFIT1 activation as read-out. To this end, we integrate time-resolved flow cytometry data and stochastic modeling of the JAK-STAT signaling pathway. The complexity of the IFN response was matched by fitting probability distributions to time-course flow cytometry snapshots. Both, experimental data and simulations confirmed that the MxA and IFIT1 induction circuits generate graded responses rather than all-or-none responses. Subsequently, we quantify the size of the intrinsic variability at different steps in the pathway. We found that stochastic effects are transiently strong during the ligand-receptor activation steps and the formation of the ISGF3 complex, but negligible for the final induction of the studied ISGs. We conclude that the JAK-STAT signaling pathway is a robust biological circuit that efficiently transmits information under stochastic environments.

We investigate the impact of intrinsic and extrinsic noise on the reliability of interferon signaling. Information must be transduced robustly despite existing biochemical variability and at the same time the system has to allow for cellular variability to tune it against changing environments. Getting insights into stochasticity in signaling networks is crucial to understand cellular dynamics and decision-making processes. To this end, we developed a detailed stochastic computational model based on single cell data. We are able to show that reliability is achieved despite high noise at the receptor level.

Dissection of the macrophage response towards infection by the Leishmania-viral endosymbiont duo and dynamics of the type I interferon response

Leishmania RNA virus 1 (LRV1) is a double-stranded RNA virus found in some strains of the human protozoan parasite Leishmania, the causative agent of leishmaniasis, a neglected tropical disease. Interestingly, the presence of LRV1 inside Leishmania constitutes an important virulence factor that worsens the leishmaniasis outcome in a type I interferon (IFN)–dependent manner and contributes to treatment failure. Understanding how macrophages respond toward Leishmania alone or in combination with LRV1 as well as the role that type I IFNs may play during infection is fundamental to oversee new therapeutic strategies. To dissect the macrophage response toward infection, RNA sequencing was performed on murine wild-type and Ifnar-deficient bone marrow–derived macrophages infected with Leishmania guyanensis (Lgy) devoid or not of LRV1. Additionally, macrophages were treated with poly I:C (mimetic virus) or with type I IFNs. By implementing a weighted gene correlation network analysis, the groups of genes (modules) with similar expression patterns, for example, functionally related, coregulated, or the members of the same functional pathway, were identified. These modules followed patterns dependent on Leishmania, LRV1, or Leishmania exacerbated by the presence of LRV1. Not only the visualization of how individual genes were embedded to form modules but also how different modules were related to each other were observed. Thus, in the context of the observed hyperinflammatory phenotype associated to the presence of LRV1, it was noted that the biomarkers tumor-necrosis factor α (TNF-α) and the interleukin 6 (IL-6) belonged to different modules and that their regulating specific Src-family kinases were segregated oppositely. In addition, this network approach revealed the strong and sustained effect of LRV1 on the macrophage response and genes that had an early, late, or sustained impact during infection, uncovering the dynamics of the IFN response. Overall, this study contributed to shed light and dissect the intricate macrophage response toward infection by the Leishmania-LRV1 duo and revealed the crosstalk between modules made of coregulated genes and provided a new resource that can be further explored to study the impact of Leishmania on the macrophage response.

Microfluidic chip for precise trapping of single cells and temporal analysis of signaling dynamics

Microfluidic designs are versatile examples of technology miniaturisation that find their applications in various cell biology research, especially to investigate the influence of environmental signals on cellular response dynamics. Multicellular systems operate in intricate cellular microenvironments where environmental signals govern well-orchestrated and robust responses, the understanding of which can be realized with integrated microfluidic systems. In this study, we present a fully automated and integrated microfluidic chip that can deliver input signals to single and isolated suspension or adherent cells in a precisely controlled manner. In respective analyses of different single cell types, we observe, in real-time, the temporal dynamics of caspase 3 activation during DMSO-induced apoptosis in single cancer cells (K562) and the translocation of STAT-1 triggered by interferon γ (IFNγ) in single fibroblasts (NIH3T3). Our investigations establish the employment of our versatile microfluidic system in probing temporal single cell signaling networks where alternations in outputs uncover signal processing mechanisms.

Nidhi Sinha, Haowen Yang and colleagues report a microfluidic large-scale integration chip to probe temporal single-cell signalling networks via the delivery of patterns of input signalling molecules. The researchers use their device to investigate drug-induced cancer cell apoptosis and single cell transcription (STAT-1) protein signalling dynamics.

Quantification of Type I Interferon Inhibition by Viral Proteins: Ebola Virus as a Case Study

Type I interferons (IFNs) are cytokines with both antiviral properties and protective roles in innate immune responses to viral infection. They induce an antiviral cellular state and link innate and adaptive immune responses. Yet, viruses have evolved different strategies to inhibit such host responses. One of them is the existence of viral proteins which subvert type I IFN responses to allow quick and successful viral replication, thus, sustaining the infection within a host. We propose mathematical models to characterise the intra-cellular mechanisms involved in viral protein antagonism of type I IFN responses, and compare three different molecular inhibition strategies. We study the Ebola viral protein, VP35, with this mathematical approach. Approximate Bayesian computation sequential Monte Carlo, together with experimental data and the mathematical models proposed, are used to perform model calibration, as well as model selection of the different hypotheses considered. Finally, we assess if model parameters are identifiable and discuss how such identifiability can be improved with new experimental data.

Single-cell secretion analysis reveals a dual role for IL-10 in restraining and resolving the TLR4-induced inflammatory response

Following Toll-like receptor 4 (TLR4) stimulation of macrophages, negative feedback mediated by the anti-inflammatory cytokine interleukin-10 (IL-10) limits the inflammatory response. However, extensive cell-to-cell variability in TLR4-stimulated cytokine secretion raises questions about how negative feedback is robustly implemented. To explore this, we characterize the TLR4-stimulated secretion program in primary murine macrophages using a single-cell microwell assay that enables evaluation of functional autocrine IL-10 signaling. High-dimensional analysis of single-cell data reveals three tiers of TLR4-induced proinflammatory activation based on levels of cytokine secretion. Surprisingly, while IL-10 inhibits TLR4-induced activation in the highest tier, it also contributes to the TLR4-induced activation threshold by regulating which cells transition from non-secreting to secreting states. This role for IL-10 in restraining TLR4 inflammatory activation is largely mediated by intermediate interferon (IFN)-β signaling, while TNF likely mediates response resolution by IL-10. Thus, cell-to-cell variability in cytokine regulatory motifs provides a means to tailor the TLR4-induced inflammatory response.

Decoding the dynamics of multilayered stochastic antiviral IFN-I responses

Type I Interferon (IFN-I) responses were first recognized for their role in antiviral immunity, but it is now widely appreciated that IFN-Is have many immunomodulatory functions, influencing antitumor responses, autoimmune manifestations, and antimicrobial defenses. Given these pivotal roles, it may be surprising that multilayered stochastic events create highly heterogeneous, but tightly regulated, all-or-nothing cellular decisions. Recently, mathematical models have provided crucial insights into the stochastic nature of antiviral IFN-I responses, which we critically evaluate in this review. In this context, we emphasize the need for innovative single-cell technologies combined with mathematical models to further reveal, understand, and predict the complexity of the IFN-I system in physiological and pathological conditions that may be relevant to a plethora of diseases.

Physics of the Nuclear Pore Complex: Theory, Modeling and Experiment

The hallmark of eukaryotic cells is the nucleus that contains the genome, enclosed by a physical barrier known as the nuclear envelope (NE). On the one hand, this compartmentalization endows the eukaryotic cells with high regulatory complexity and flexibility. On the other hand, it poses a tremendous logistic and energetic problem of transporting millions of molecules per second across the nuclear envelope, to facilitate their biological function in all compartments of the cell. Therefore, eukaryotes have evolved a molecular "nanomachine" known as the Nuclear Pore Complex (NPC). Embedded in the nuclear envelope, NPCs control and regulate all the bi-directional transport between the cell nucleus and the cytoplasm. NPCs combine high molecular specificity of transport with high throughput and speed, and are highly robust with respect to molecular noise and structural perturbations. Remarkably, the functional mechanisms of NPC transport are highly conserved among eukaryotes, from yeast to humans, despite significant differences in the molecular components among various species. The NPC is the largest macromolecular complex in the cell. Yet, despite its significant complexity, it has become clear that its principles of operation can be largely understood based on fundamental physical concepts, as have emerged from a combination of experimental methods of molecular cell biology, biophysics, nanoscience and theoretical and computational modeling. Indeed, many aspects of NPC function can be recapitulated in artificial mimics with a drastically reduced complexity compared to biological pores. We review the current physical understanding of the NPC architecture and function, with the focus on the critical analysis of experimental studies in cells and artificial NPC mimics through the lens of theoretical and computational models. We also discuss the connections between the emerging concepts of NPC operation and other areas of biophysics and bionanotechnology.

Agent-based modeling reveals benefits of heterogeneous and stochastic cell populations during cGAS-mediated IFNβ production

MOTIVATION

The cGAS pathway is a component of the innate immune system responsible for the detection of pathogenic DNA and upregulation of interferon beta (IFNβ). Experimental evidence shows that IFNβ signaling occurs in highly heterogeneous cells and is stochastic in nature; however, the benefits of these attributes remain unclear. To investigate how stochasticity and heterogeneity affect IFNβ production, an agent-based model is developed to simulate both DNA transfection and viral infection.

RESULTS

We show that heterogeneity can enhance IFNβ responses during infection. Furthermore, by varying the degree of IFNβ stochasticity, we find that only a percentage of cells (20-30%) need to respond during infection. Going beyond this range provides no additional protection against cell death or reduction of viral load. Overall, these simulations suggest that heterogeneity and stochasticity are important for moderating immune potency while minimizing cell death during infection.

AVAILABILITY AND IMPLEMENTATION

Model repository is available at: https://github.com/ImmuSystems-Lab/AgentBasedModel-cGASPathway.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The Causes and Consequences of Spatial Organization of the Genome in Regulation of Gene Expression

Regulation of gene expression in time, space and quantity is orchestrated by the functional interplay of cis-acting elements and trans-acting factors. Our current view postulates that transcription factors recognize enhancer DNA and read the transcriptional regulatory code by cooperative DNA binding to specific DNA motifs, thus instructing the recruitment of transcriptional regulatory complexes forming a plethora of higher-ordered multi-protein-DNA and protein-protein complexes. Here, we reviewed the formation of multi-dimensional chromatin assemblies implicated in gene expression with emphasis on the regulatory role of enhancer hubs as coordinators of stochastic gene expression. Enhancer hubs contain many interacting regulatory elements and represent a remarkably dynamic and heterogeneous network of multivalent interactions. A functional consequence of such complex interaction networks could be that individual enhancers function synergistically to ensure coordination, tight control and robustness in regulation of expression of spatially connected genes. In this review, we discuss fundamental paradigms of such inter- and intra- chromosomal associations both in the context of immune-related genes and beyond.

Autocrine and paracrine interferon signalling as 'ring vaccination' and 'contact tracing' strategies to suppress virus infection in a host

The innate immune response, particularly the interferon response, represents a first line of defence against viral infections. The interferon molecules produced from infected cells act through autocrine and paracrine signalling to turn host cells into an antiviral state. Although the molecular mechanisms of IFN signalling have been well characterized, how the interferon response collectively contribute to the regulation of host cells to stop or suppress viral infection during early infection remain unclear. Here, we use mathematical models to delineate the roles of the autocrine and the paracrine signalling, and show that their impacts on viral spread are dependent on how infection proceeds. In particular, we found that when infection is well-mixed, the paracrine signalling is not as effective; by contrast, when infection spreads in a spatial manner, a likely scenario during initial infection in tissue, the paracrine signalling can impede the spread of infection by decreasing the number of susceptible cells close to the site of infection. Furthermore, we argue that the interferon response can be seen as a parallel to population-level epidemic prevention strategies such as ‘contact tracing’ or ‘ring vaccination’. Thus, our results here may have implications for the outbreak control at the population scale more broadly.

COVID-19 and the human innate immune system

The introduction of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into the human population represents a tremendous medical and economic crisis. Innate immunity—as the first line of defense of our immune system—plays a central role in combating this novel virus. Here, we provide a conceptual framework for the interaction of the human innate immune system with SARS-CoV-2 to link the clinical observations with experimental findings that have been made during the first year of the pandemic. We review evidence that variability in innate immune system components among humans is a main contributor to the heterogeneous disease courses observed for coronavirus disease 2019 (COVID-19), the disease spectrum induced by SARS-CoV-2. A better understanding of the pathophysiological mechanisms observed for cells and soluble mediators involved in innate immunity is a prerequisite for the development of diagnostic markers and therapeutic strategies targeting COVID-19. However, this will also require additional studies addressing causality of events, which so far are lagging behind.

Rational Design of Single Copy Expression Cassettes in Defined Chromosomal Sites Overcomes Intraclonal Cell-to-Cell Expression Heterogeneity and Ensures Robust Antibody Production

The expression of endogenous genes as well as transgenes depends on regulatory elements within and surrounding genes as well as their epigenetic modifications. Members of a cloned cell population often show pronounced cell-to-cell heterogeneity with respect to the expression of a certain gene. To investigate the heterogeneity of recombinant protein expression we targeted cassettes into two preselected chromosomal hot-spots in Chinese hamster ovary (CHO) cells. Depending on the gene of interest and the design of the expression cassette, we found strong expression variability that could be reduced by epigenetic modifiers, but not by site-specific recruitment of the modulator dCas9-VPR. In particular, the implementation of ubiquitous chromatin opening elements (UCOEs) reduced cell-to-cell heterogeneity and concomitantly increased expression. The application of this method to recombinant antibody expression confirmed that rational design of cell lines for production of transgenes with predictable and high titers is a promising approach.

Importance of Type I and III Interferons at Respiratory and Intestinal Barrier Surfaces

Interferons (IFNs) constitute the first line of defense against microbial infections particularly against viruses. They provide antiviral properties to cells by inducing the expression of hundreds of genes known as interferon-stimulated genes (ISGs). The two most important IFNs that can be produced by virtually all cells in the body during intrinsic innate immune response belong to two distinct families: the type I and type III IFNs. The type I IFN receptor is ubiquitously expressed whereas the type III IFN receptor's expression is limited to epithelial cells and a subset of immune cells. While originally considered to be redundant, type III IFNs have now been shown to play a unique role in protecting mucosal surfaces against pathogen challenges. The mucosal specific functions of type III IFN do not solely rely on the restricted epithelial expression of its receptor but also on the distinct means by which type III IFN mediates its anti-pathogen functions compared to the type I IFN. In this review we first provide a general overview on IFNs and present the similarities and differences in the signal transduction pathways leading to the expression of either type I or type III IFNs. By highlighting the current state-of-knowledge of the two archetypical mucosal surfaces (e.g. the respiratory and intestinal epitheliums), we present the differences in the signaling cascades used by type I and type III IFNs to uniquely induce the expression of ISGs. We then discuss in detail the role of each IFN in controlling pathogen infections in intestinal and respiratory epithelial cells. Finally, we provide our perspective on novel concepts in the field of IFN (stochasticity, response heterogeneity, cellular polarization/differentiation and tissue microenvironment) that we believe have implications in driving the differences between type I and III IFNs and could explain the preferences for type III IFNs at mucosal surfaces.

Virus-Intrinsic Differences and Heterogeneous IRF3 Activation Influence IFN-Independent Antiviral Protection

Type 1 interferon (IFN) plays a critical role in early antiviral defense and priming of adaptive immunity by signaling upregulation of host antiviral IFN-stimulated genes (ISGs). Certain stimuli trigger strong activation of IFN regulatory factor 3 (IRF3) and direct upregulation of ISGs in addition to IFN. It remains unclear why some stimuli are stronger activators of IRF3 and how this leads to IFN-independent antiviral protection. We found that UV-inactivated human cytomegalovirus (HCMV) particles triggered an IFN-independent ISG signature that was absent in cells infected with UV-inactivated Sendai virus particles. HCMV particles triggered mostly uniform activation of IRF3 and low-level IFN-β production within the population while SeV particles triggered a small fraction of cells producing abundant IFN-β. These findings suggest that population-level activation of IRF3 and antiviral protection emerges from a diversity of responses occurring simultaneously in single cells. Moreover, this occurs in the absence of virus replication.

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The antiviral response to virus particles requires low levels of interferon

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Cells respond differently to HCMV or SeV particles

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Heterogeneous IRF3 activation influences the response to virus

Synthetic rewiring and boosting type I interferon responses for visualization and counteracting viral infections

Mammalian first line of defense against viruses is accomplished by the interferon (IFN) system. Viruses have evolved numerous mechanisms to reduce the IFN action allowing them to invade the host and/or to establish latency. We generated an IFN responsive intracellular hub by integrating the synthetic transactivator tTA into the chromosomal Mx2 locus for IFN-based activation of tTA dependent expression modules. The additional implementation of a synthetic amplifier module with positive feedback even allowed for monitoring and reacting to infections of viruses that can antagonize the IFN system. Low and transient IFN amounts are sufficient to trigger these amplifier cells. This gives rise to higher and sustained—but optionally de-activatable—expression even when the initial stimulus has faded out. Amplification of the IFN response induced by IFN suppressing viruses is sufficient to protect cells from infection. Together, this interfaced sensor/actuator system provides a toolbox for robust sensing and counteracting viral infections.

Cell-cycle-gated feedback control mediates desensitization to interferon stimulation

Cells use molecular circuits to interpret and respond to extracellular cues, such as hormones and cytokines, which are often released in a temporally varying fashion. In this study, we combine microfluidics, time-lapse microscopy, and computational modeling to investigate how the type I interferon (IFN)-responsive regulatory network operates in single human cells to process repetitive IFN stimulation. We found that IFN-α pretreatments lead to opposite effects, priming versus desensitization, depending on input durations. These effects are governed by a regulatory network composed of a fast-acting positive feedback loop and a delayed negative feedback loop, mediated by upregulation of ubiquitin-specific peptidase 18 (USP18). We further revealed that USP18 upregulation can only be initiated at the G1/early S phases of cell cycle upon the treatment onset, resulting in heterogeneous and delayed induction kinetics in single cells. This cell cycle gating provides a temporal compartmentalization of feedback loops, enabling duration-dependent desensitization to repetitive stimulations.

Systems-Level Properties of EGFR-RAS-ERK Signaling Amplify Local Signals to Generate Dynamic Gene Expression Heterogeneity

Intratumoral heterogeneity is associated with aggressive tumor behavior, therapy resistance, and poor patient outcomes. Such heterogeneity is thought to be dynamic, shifting over periods of minutes to hours in response to signaling inputs from the tumor microenvironment. However, models of this process have been inferred from indirect or post-hoc measurements of cell state, leaving the temporal details of signaling-driven heterogeneity undefined. Here, we developed a live-cell model system in which microenvironment-driven signaling dynamics can be directly observed and linked to variation in gene expression. Our analysis reveals that paracrine signaling between two cell types is sufficient to drive continual diversification of gene expression programs. This diversification emerges from systems-level properties of the EGFR-RAS-ERK signaling cascade, including intracellular amplification of amphiregulin-mediated paracrine signals and differential kinetic filtering by target genes including Fra-1, c-Myc, and Egr1. Our data enable more precise modeling of paracrine-driven transcriptional variation as a generator of gene expression heterogeneity. A record of this paper's transparent peer review process is included in the Supplemental Information.

Interplay between SARS-CoV-2 and the type I interferon response

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is responsible for the current COVID-19 pandemic. An unbalanced immune response, characterized by a weak production of type I interferons (IFN-Is) and an exacerbated release of proinflammatory cytokines, contributes to the severe forms of the disease. SARS-CoV-2 is genetically related to SARS-CoV and Middle East respiratory syndrome-related coronavirus (MERS-CoV), which caused outbreaks in 2003 and 2013, respectively. Although IFN treatment gave some encouraging results against SARS-CoV and MERS-CoV in animal models, its potential as a therapeutic against COVID-19 awaits validation. Here, we describe our current knowledge of the complex interplay between SARS-CoV-2 infection and the IFN system, highlighting some of the gaps that need to be filled for a better understanding of the underlying molecular mechanisms. In addition to the conserved IFN evasion strategies that are likely shared with SARS-CoV and MERS-CoV, novel counteraction mechanisms are being discovered in SARS-CoV-2-infected cells. Since the last coronavirus epidemic, we have made considerable progress in understanding the IFN-I response, including its spatiotemporal regulation and the prominent role of plasmacytoid dendritic cells (pDCs), which are the main IFN-I-producing cells. While awaiting the results of the many clinical trials that are evaluating the efficacy of IFN-I alone or in combination with antiviral molecules, we discuss the potential benefits of a well-timed IFN-I treatment and propose strategies to boost pDC-mediated IFN responses during the early stages of viral infection.

A Coupled Mathematical Model of the Intracellular Replication of Dengue Virus and the Host Cell Immune Response to Infection

Dengue virus (DV) is a positive-strand RNA virus of the Flavivirus genus. It is one of the most prevalent mosquito-borne viruses, infecting globally 390 million individuals per year. The clinical spectrum of DV infection ranges from an asymptomatic course to severe complications such as dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS), the latter because of severe plasma leakage. Given that the outcome of infection is likely determined by the kinetics of viral replication and the antiviral host cell immune response (HIR) it is of importance to understand the interaction between these two parameters. In this study, we use mathematical modeling to characterize and understand the complex interplay between intracellular DV replication and the host cells' defense mechanisms. We first measured viral RNA, viral protein, and virus particle production in Huh7 cells, which exhibit a notoriously weak intrinsic antiviral response. Based on these measurements, we developed a detailed intracellular DV replication model. We then measured replication in IFN competent A549 cells and used this data to couple the replication model with a model describing IFN activation and production of IFN stimulated genes (ISGs), as well as their interplay with DV replication. By comparing the cell line specific DV replication, we found that host factors involved in replication complex formation and virus particle production are crucial for replication efficiency. Regarding possible modes of action of the HIR, our model fits suggest that the HIR mainly affects DV RNA translation initiation, cytosolic DV RNA degradation, and naïve cell infection. We further analyzed the potential of direct acting antiviral drugs targeting different processes of the DV lifecycle in silico and found that targeting RNA synthesis and virus assembly and release are the most promising anti-DV drug targets.

Integrative analysis suggests cell type-specific decoding of NF-κB dynamics

The complex signaling dynamics of transcription factors can encode both qualitative and quantitative information about the extracellular environment, which increases the information transfer capacity and potentially supports accurate cellular decision-making. An important question is how these signaling dynamics patterns are translated into functionally appropriate gene regulation programs. To address this question for transcription factors of the nuclear factor κB (NF-κB) family, we profiled the single-cell dynamics of two major NF-κB subunits, RelA and c-Rel, induced by a panel of pathogen-derived stimuli in immune and nonimmune cellular contexts. Diverse NF-κB-activating ligands produced different patterns of RelA and c-Rel signaling dynamic features, such as variations in duration or time-integrated activity. Analysis of nascent transcripts delineated putative direct targets of NF-κB as compared to genes controlled by other transcriptional and posttranscriptional mechanisms and showed that the transcription of more than half of the induced genes was tightly linked to specific dynamic features of NF-κB signaling. Fibroblast and macrophage cell lines shared a cluster of such "NF-κB dynamics-decoding" genes, as well as cell type-specific decoding genes. Dissecting the subunit specificity of dynamics-decoding genes suggested that target genes were most often linked to both RelA and c-Rel or to RelA alone. Thus, our analysis reveals the cell type-specific interpretation of pathogenic information through the signaling dynamics of NF-κB.

Order by chance: origins and benefits of stochasticity in immune cell fate control

To protect against diverse challenges, the immune system must continuously generate an arsenal of specialized cell types, each of which can mount a myriad of effector responses upon detection of potential threats. To do so, it must generate multiple differentiated cell populations with defined sizes and proportions, often from rare starting precursor cells. Here, we discuss the emerging view that inherently probabilistic mechanisms, involving rare, rate-limiting regulatory events in single cells, control fate decisions and population sizes and fractions during immune development and function. We first review growing evidence that key fate control points are gated by stochastic signaling and gene regulatory events that occur infrequently over decision-making timescales, such that initially homogeneous cells can adopt variable outcomes in response to uniform signals. We next discuss how such stochastic control can provide functional capabilities that are harder to achieve with deterministic control strategies, and may be central to robust immune system function.

Principles of Effective and Robust Innate Immune Response to Viral Infections: A Multiplex Network Analysis

The human innate immune response, particularly the type-I interferon (IFN) response, is highly robust and effective first line of defense against virus invasion. IFN molecules are produced and secreted from infected cells upon virus infection and recognition. They then act as signaling/communication molecules to activate an antiviral response in neighboring cells so that those cells become refractory to infection. Previous experimental studies have identified the detailed molecular mechanisms for the IFN signaling and response. However, the principles underlying how host cells use IFN to communicate with each other to collectively and robustly halt an infection is not understood. Here we take a multiplex network modeling approach to provide a theoretical framework to identify key factors that determine the effectiveness of the IFN response against virus infection of a host. In this approach, we consider the virus spread among host cells and the interferon signaling to protect host cells as a competition process on a two-layer multiplex network. We focused on two types of network topology, i.e., the Erdős-Rényi (ER) network and the Geometric Random (GR) network, which represent the scenarios when infection of cells is mostly well mixed (e.g., in the blood) and when infection is spatially segregated (e.g., in tissues), respectively. We show that in general, the IFN response works effectively to stop viral infection when virus infection spreads spatially (a most likely scenario for initial virus infection of a host at the peripheral tissue). Importantly, we show that the effectiveness of the IFN response is robust against large variations in the distance of IFN diffusion as long as IFNs diffuse faster than viruses and they can effectively induce antiviral responses in susceptible host cells. This suggests that the effectiveness of the IFN response is insensitive to the specific arrangement of host cells in peripheral tissues. Thus, our work provides a quantitative explanation of why the IFN response can serve an effective and robust response in different tissue types to a wide range of viral infections of a host.

Interferon at the cellular, individual, and population level in hepatitis C virus infection: Its role in the interferon-free treatment era

The advent of powerful direct-acting antiviral agents (DAAs) has revolutionized the treatment of hepatitis C. DAAs cure nearly all patients with short duration, oral treatments. Significant efforts are now underway to optimize DAA-based treatments. We discuss the potential role of interferon in this optimization. Clinical studies present compelling evidence that DAAs perform better in treatment-naive individuals than in individuals who previously failed treatment with interferon, a surprising correlation because interferon and DAAs are thought to act independently. Recent mathematical models explore a mechanistic hypothesis underlying this correlation. The hypothesis invokes the action of interferon at the cellular, individual, and population levels. Strong interferon responses prevent the productive infection of cells, reduce viral replication, and impede the development of resistance to DAAs in infected individuals and improve cure rates elicited by DAAs in treated populations. The models develop descriptions of these processes, integrate them into a comprehensive framework, and capture clinical data quantitatively, providing a successful test of the hypothesis. Individuals with strong endogenous interferon responses thus present a promising subpopulation for reducing DAA treatment durations. This review discusses the conceptual advances made by the models, highlights the new insights they unravel, and examines their applicability to optimize DAA-based treatments.

Antiviral interferon response at single-cell resolution

Experimental studies of the innate immune response of mammalian cells to viruses reveal pervasive heterogeneity at the level of single cells. Interferons are induced only in a fraction of virus-infected cells; subsequently a fraction of cells exposed to interferons upregulate interferon-stimulated genes. Nevertheless, quantitative experiments and linked mathematical models show that the interferon response can be effective in curbing viral spread through two distinct mechanisms. First, paracrine interferon signals from scattered source cells can protect many uninfected cells, and the self-amplification of interferon production might serve to calibrate response amplitude to strength of viral infection. Second, models of the tug-of-war between viral replication and the innate interferon response imply a pivotal role of interferon action on already infected cells in curbing viral spread, through effectively lowering virus replication rate. This finding is in line with the observation that several pathogenic viruses selectively abrogate interferon action on infected cells. Thus, interferons may delay viral spread in acute infections by acting as sentinels, warning uninfected cells of imminent danger, or as negative feedback regulators of virus replication in infected cells. The timing of the interferon response relative to the onset of viral replication is critical for its effectiveness in curbing viral spread.

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.

Quantitative systems pharmacology of interferon alpha administration: A multi-scale approach

The therapeutic effect of a drug is governed by its pharmacokinetics which determine the downstream pharmacodynamic response within the cellular network. A complete understanding of the drug-effect relationship therefore requires multi-scale models which integrate the properties of the different physiological scales. Computational modelling of these individual scales has been successfully established in the past. However, coupling of the scales remains challenging, although it will provide a unique possibility of mechanistic and holistic analyses of therapeutic outcomes for varied treatment scenarios. We present a methodology to combine whole-body physiologically-based pharmacokinetic (PBPK) models with mechanistic intracellular models of signal transduction in the liver for therapeutic proteins. To this end, we developed a whole-body distribution model of IFN-α in human and a detailed intracellular model of the JAK/STAT signalling cascade in hepatocytes and coupled them at the liver of the whole-body human model. This integrated model infers the time-resolved concentration of IFN-α arriving at the liver after intravenous injection while simultaneously estimates the effect of this dose on the intracellular signalling behaviour in the liver. In our multi-scale physiologically-based pharmacokinetic/pharmacodynamic (PBPK/PD) model, receptor saturation is seen at low doses, thus giving mechanistic insights into the pharmacodynamic (PD) response. This model suggests a fourfold lower intracellular response after administration of a typical IFN-α dose to an individual as compared to the experimentally observed responses in in vitro setups. In conclusion, this work highlights clear differences between the observed in vitro and in vivo drug effects and provides important suggestions for future model-based study design.

An information-theoretic framework for deciphering pleiotropic and noisy biochemical signaling

Many components of signaling pathways are functionally pleiotropic, and signaling responses are marked with substantial cell-to-cell heterogeneity. Therefore, biochemical descriptions of signaling require quantitative support to explain how complex stimuli (inputs) are encoded in distinct activities of pathways effectors (outputs). A unique perspective of information theory cannot be fully utilized due to lack of modeling tools that account for the complexity of biochemical signaling, specifically for multiple inputs and outputs. Here, we develop a modeling framework of information theory that allows for efficient analysis of models with multiple inputs and outputs; accounts for temporal dynamics of signaling; enables analysis of how signals flow through shared network components; and is not restricted by limited variability of responses. The framework allows us to explain how identity and quantity of type I and type III interferon variants could be recognized by cells despite activating the same signaling effectors.

Differential induction of interferon stimulated genes between type I and type III interferons is independent of interferon receptor abundance

It is currently believed that type I and III interferons (IFNs) have redundant functions. However, the preferential distribution of type III IFN receptor on epithelial cells suggests functional differences at epithelial surfaces. Here, using human intestinal epithelial cells we could show that although both type I and type III IFNs confer an antiviral state to the cells, they do so with distinct kinetics. Type I IFN signaling is characterized by an acute strong induction of interferon stimulated genes (ISGs) and confers fast antiviral protection. On the contrary, the slow acting type III IFN mediated antiviral protection is characterized by a weaker induction of ISGs in a delayed manner compared to type I IFN. Moreover, while transcript profiling revealed that both IFNs induced a similar set of ISGs, their temporal expression strictly depended on the IFNs, thereby leading to unique antiviral environments. Using a combination of data-driven mathematical modeling and experimental validation, we addressed the molecular reason for this differential kinetic of ISG expression. We could demonstrate that these kinetic differences are intrinsic to each signaling pathway and not due to different expression levels of the corresponding IFN receptors. We report that type III IFN is specifically tailored to act in specific cell types not only due to the restriction of its receptor but also by providing target cells with a distinct antiviral environment compared to type I IFN. We propose that this specific environment is key at surfaces that are often challenged with the extracellular environment.

Mathematical modeling identifies Lck as a potential mediator for PD-1 induced inhibition of early TCR signaling

Programmed cell death-1 (PD-1) is an inhibitory immune checkpoint receptor that negatively regulates the functioning of T cell. Although the direct targets of PD-1 were not identified, its inhibitory action on the TCR signaling pathway was known much earlier. Recent experiments suggest that the PD-1 inhibits the TCR and CD28 signaling pathways at a very early stage ─ at the level of phosphorylation of the cytoplasmic domain of TCR and CD28 receptors. Here, we develop a mathematical model to investigate the influence of inhibitory effect of PD-1 on the activation of early TCR and CD28 signaling molecules. Proposed model recaptures several quantitative experimental observations of PD-1 mediated inhibition. Model simulations show that PD-1 imposes a net inhibitory effect on the Lck kinase. Further, the inhibitory effect of PD-1 on the activation of TCR signaling molecules such as Zap70 and SLP76 is significantly enhanced by the PD-1 mediated inhibition of Lck. These results suggest a critical role for Lck as a mediator for PD-1 induced inhibition of TCR signaling network. Multi parametric sensitivity analysis explores the effect of parameter uncertainty on model simulations.

Gene expression variability across cells and species shapes innate immunity

As the first line of defence against pathogens, cells mount an innate immune response, which varies widely from cell to cell. The response must be potent but carefully controlled to avoid self-damage. How these constraints have shaped the evolution of innate immunity remains poorly understood. Here we characterize the innate immune response's transcriptional divergence between species and variability in expression among cells. Using bulk and single-cell transcriptomics in fibroblasts and mononuclear phagocytes from different species, challenged with immune stimuli, we map the architecture of the innate immune response. Transcriptionally diverging genes, including those that encode cytokines and chemokines, vary across cells and have distinct promoter structures. Conversely, genes that are involved in the regulation of this response, such as those that encode transcription factors and kinases, are conserved between species and display low cell-to-cell variability in expression. We suggest that this expression pattern, which is observed across species and conditions, has evolved as a mechanism for fine-tuned regulation to achieve an effective but balanced response.

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.

Challenges of Decoding Transcription Factor Dynamics in Terms of Gene Regulation

Technological advances are continually improving our ability to obtain more accurate views about the inner workings of biological systems. One such rapidly evolving area is single cell biology, and in particular gene expression and its regulation by transcription factors in response to intrinsic and extrinsic factors. Regarding the study of transcription factors, we discuss some of the promises and pitfalls associated with investigating how individual cells regulate gene expression through modulation of transcription factor activities. Specifically, we discuss four leading experimental approaches, the data that can be obtained from each, and important considerations that investigators should be aware of when drawing conclusions from such data.

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.