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Zika virus (ZIKV) infection can cause developmental and neurological defects and represents a threat for human health. Type I/III interferon responses control ZIKV infection and pathological processes, yet the virus has evolved various mechanisms to defeat these host responses. Here, we established a pipeline to delineate at high-resolution the genetic evolution of ZIKV in a controlled host cell environment. We uncovered that serially passaged ZIKV acquired increased infectivity, defined as the probability for one virus to initiate infection, and simultaneously developed a resistance to TLR3-induced restriction. We built a mathematical model that suggests that the increased infectivity is due to a reduced time-lag between infection and viral replication. We found that this adaptation is cell-type specific, suggesting that different cell environments may drive viral evolution along different routes. Deep-sequencing of ZIKV quasi-species pinpointed mutations whose increased frequencies temporally coincide with the acquisition of the adapted phenotype. We functionally validated a point-mutation in ZIKV envelope (E) protein recapitulating the adapted phenotype. Its positioning on the E structure suggests a putative function in protein refolding/stability. Altogether, our results uncovered ZIKV adaptations to the cell environment leading to an accelerated replication onset coupled with resistance to TLR3-induced antiviral response. Our work provides insights into viral escape mechanisms and interactions with host cell and can serve as a framework to study other viruses.

Uncovering vulnerable steps in the life cycle of viruses supports the rational design of antiviral treatments. However, information on viral replication dynamics obtained from traditional bulk assays with host cell populations is inherently limited as the data represent averages over a multitude of unsynchronized replication cycles. Here, we use time-lapse imaging of virus replication in thousands of single cells, combined with computational inference, to identify rate-limiting steps for dengue virus (DENV), a widespread human pathogen. Comparing wild-type DENV with a vaccine candidate mutant, we show that the viral spread in the mutant is greatly attenuated by delayed onset of productive replication, whereas wild-type and mutant virus have identical replication rates. Single-cell analysis done after applying the broad-spectrum antiviral drug, ribavirin, at clinically relevant concentrations revealed the same mechanism of attenuating viral spread. We conclude that the initial steps of infection, rather than the rate of established replication, are quantitatively limiting DENV spread.

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.

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., Author summary The human intestinal tract plays two important roles in the body: first it is responsible for nutrient absorption and second it is the primary barrier which protects the human body from the outside environment. This complex tissue is constantly exposed to commensal bacteria and is often exposed to both bacterial and viral pathogens. To protect itself, the gut produces, among others, secreted agents called interferons which help to fight against pathogen attacks. There are several varieties (type I, II, and III) of interferons and our work aims at understanding how type I and III interferon act to protect human intestinal epithelial cells (hIECs) during viral infection. In this study, we confirmed that both interferons can protect hIECs against viral infection but with different kinetics. We determined that type I confer an antiviral state to hIECs faster than type III interferons. We uncovered that these differences were intrinsic to each pathway and not the result of differential abundance of the respective interferon receptors. The results of this study suggest that type III interferon may provide a different antiviral environment to the epithelium target cells which is likely critical for maintaining gut homeostasis. Our findings will also help us to design therapies to aid in controlling and eliminating viral infections of the gut.

Mathematical modelling has been instrumental to understand kinetics of radiation-induced DNA damage repair and associated secondary cancer risk. The widely accepted two-lesion kinetic (TLK) model assumes two kinds of double strand breaks, simple and complex ones, with different repair rates. Recently, persistent DNA damage associated with telomeres was reported as a new kind of DNA damage. We therefore extended existing versions of the TLK model by new categories of DNA damage and re-evaluated those models using extensive data. We subjected different versions of the TLK model to a rigorous model discrimination approach. This enabled us to robustly select a best approximating parsimonious model that can both recapitulate and predict transient and persistent DNA damage after ionizing radiation. Models and data argue for i) nonlinear dose-damage relationships and ii) negligible saturation of repair kinetics even for high doses. Additionally, we show that simulated radiation-induced persistent telomere-associated DNA damage foci (TAF) can be used to predict excess relative risk (ERR) of developing secondary leukemia after fractionated radiotherapy. We suggest that TAF may serve as an additional measure to predict cancer risk after radiotherapy using high dose rates. This may improve predicting risk-dose dependency of ionizing radiation especially for long-term therapies.