Data-driven modeling of the dynamic competition between virus infection and the antiviral interferon response

The interferon system functions as a first line of defense against viral infections. The cellular recognition of viruses leads to the production of interferons (IFN) by the infected cells. Secreted IFN stimulates an antiviral response in an autocrine and paracrine manner: While autocrine IFN action inhibits virus production in infected cells, paracrine IFN signaling induces an antiviral protective state in naïve cells. Although central molecular components of the IFN system have been characterized, our quantitative understanding of its dynamics remains limited. In particular, it is not precisely known which molecular processes are decisive for the outcome of virus-host interactions. Together with our experimental cooperation partners, we have studied virus-induced IFN signaling at single-cell resolution in communicating cell populations after infection with a non-spreading and a spreading virus. On this basis, we established two complementary mathematical models. First, we developed a stochastic multi-scale model accounting for the intracellular dynamics in individual cells and the cell-to-cell communication via secreted IFN. Second, we constructed a delay differential equation model to analyze the competition between viral spread and IFN-induced antiviral defense in a cell population. Both models were parameterized on the basis of original experimental data and the numerical analyses of the models aimed at deriving testable predictions for new experiments. By live-cell imaging, we showed that key steps of the IFN pathway including virus-induced signaling, IFN expression, and induction of IFN-stimulated genes are stochastic events in individual cells. To relate the single-cell data after primary infection to antiviral protection at the cell-population level, we established a stochastic model which combines the heterogeneous IFN signaling in single cells with the intercellular communication through released IFN. The parameters describing the virus-induced activation of the transcription factors of the IFN gene were estimated from a distribution of observed single-cell activation times using as objective function Neyman’s chi-squares statistic. The minimization of this objective function by simulated annealing revealed that virus-induced signaling is cooperative. Moreover, fitting of the measured time delays between transcription factor activation and IFN gene induction in individual cells with a gamma distribution by applying the maximum-likelihood method implies that IFN gene induction downstream of transcription factor activation is a slow multi-step process. Notably, mathematical modeling and experimental validation indicate that reliable antiviral protection in the face of multi-layered cellular stochasticity can be achieved by paracrine propagation of the IFN signal. Therefore, a few IFN-producing cells are able to protect a large number of naïve cells (Rand, Rinas et al. 2012). To investigate the competition between viral spread and IFN-induced antiviral defense, we examined virus-host interactions after infection with spreading Dengue virus. For this purpose, our experimental partners generated data showing the antiviral response dynamics of fluorescent reporter cells after infection with a fluorescently labeled Dengue virus. Based on these kinetic data, we established a delay differential equation model with time delays for virus replication, virus production and IFN secretion. Using data-driven least-squares fitting and profile likelihood analysis, we identified the model parameters within narrow confidence bounds and found that the timing of virus production and IFN secretion after infection are almost identical. This direct competition together with the highly heterogeneous IFN response in single cells fosters the coexistence of IFN-induced protection of naïve cells and viral spread in non-protected cells. To analyze which components of the antiviral IFN system have the greatest influence on viral spread, we compared the infection dynamics of the wild-type Dengue virus with the attenuated spread of the vaccine candidate Dengue virus E217A mutant. We quantified the differences between wild-type and mutant Dengue virus infections using data-driven parameter optimization constrained by the determined wild-type virus related parameter values. In this way, we identified two mutant virus specific parameters, which explain the attenuation of the mutant through a reduced virus production rate and an accelerated IFN secretion taking place much earlier than virus production. By mathematical modeling and validation experiments, we predict that rapid IFN action curbing virus production in infected cells is critical for the attenuation of the Dengue virus E217A mutant. Thus, a fast acting autocrine IFN signal could limit viral spread in such a way that accelerated paracrine IFN response has only a minor impact on the spread of Dengue virus (Schmid, Rinas et al. submitted). In conclusion, our work demonstrates that mathematical modeling is an essential tool to integrate data and mechanisms from the molecular to the cell-population level. The research on understanding which molecular mechanisms shape virus-host interactions might inform the development of new antiviral therapies and vaccines

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

Live-cell imaging and mathematical modelling of the type-I interferon response to viral infection reveal that multiple layers of the cellular response are stochastic events in individual cells, while paracrine propagation of the IFN signal results in reliable antiviral protection

HPV Genotypes in High Grade Cervical Lesions and Invasive Cervical Carcinoma as Detected by Two Commercial DNA Assays, North Carolina, 2001–2006

HPV typing using formalin fixed paraffin embedded (FFPE) cervical tissue is used to evaluate HPV vaccine impact, but DNA yield and quality in FFPE specimens can negatively affect test results. This study aimed to evaluate 2 commercial assays for HPV detection and typing using FFPE cervical specimens.Four large North Carolina pathology laboratories provided FFPE specimens from 299 women ages18 and older diagnosed with cervical disease from 2001 to 2006. For each woman, one diagnostic block was selected and unstained serial sections were prepared for DNA typing. Extracts from samples with residual lesion were used to detect and type HPV using parallel and serial testing algorithms with the Linear Array and LiPA HPV genotyping assays.LA and LiPA concordance was 0.61 for detecting any high-risk (HR) and 0.20 for detecting any low-risk (LR) types, with significant differences in marginal proportions for HPV16, 51, 52, and any HR types. Discordant results were most often LiPA-positive, LA-negative. The parallel algorithm yielded the highest prevalence of any HPV type (95.7%). HR type prevalence was similar using parallel (93.1%) and serial (92.1%) approaches. HPV16, 33, and 52 prevalence was slightly lower using the serial algorithm, but the median number of HR types per woman (1) did not differ by algorithm. Using the serial algorithm, HPV DNA was detected in >85% of invasive and >95% of pre-invasive lesions. The most common type was HPV16, followed by 52, 18, 31, 33, and 35; HPV16/18 was detected in 56.5% of specimens. Multiple HPV types were more common in lower grade lesions.We developed an efficient algorithm for testing and reporting results of two commercial assays for HPV detection and typing in FFPE specimens, and describe HPV type distribution in pre-invasive and invasive cervical lesions in a state-based sample prior to HPV vaccine introduction

MAPK pathway and B cells overactivation in multiple sclerosis revealed by phosphoproteomics and genomic analysis

Dysregulation of signaling pathways in multiple sclerosis (MS) can be analyzed by phosphoproteomics in peripheral blood mononuclear cells (PBMCs). We performed in vitro kinetic assays on PBMCs in 195 MS patients and 60 matched controls and quantified the phosphorylation of 17 kinases using xMAP assays. Phosphoprotein levels were tested for association with genetic susceptibility by typing 112 single-nucleotide polymorphisms (SNPs) associated with MS susceptibility. We found increased phosphorylation of MP2K1 in MS patients relative to the controls. Moreover, we identified one SNP located in the PHDGH gene and another on IRF8 gene that were associated with MP2K1 phosphorylation levels, providing a first clue on how this MS risk gene may act. The analyses in patients treated with disease-modifying drugs identified the phosphorylation of each receptor’s downstream kinases. Finally, using flow cytometry, we detected in MS patients increased STAT1, STAT3, TF65, and HSPB1 phosphorylation in CD19+ cells. These findings indicate the activation of cell survival and proliferation (MAPK), and proinflammatory (STAT) pathways in the immune cells of MS patients, primarily in B cells. The changes in the activation of these kinases suggest that these pathways may represent therapeutic targets for modulation by kinase inhibitors

Intertwining Self-efficacy, Basic Psychological Need Satisfaction, and Emotions in Higher Education Teaching

Previous research on school teachers has successfully explained individual differences by use of motivational constructs established in other populations, particularly self-efficacy, basic psychological needs (BPNS), and emotions. However, these constructs have primarily been examined independently without considering their interplay, and few studies have investigated their role for higher education teachers. The aim of the current paper was therefore to transfer these findings to the context of higher education teaching at universities, and simultaneously, to investigate the connections between these motivational constructs. For this purpose, we propose and test hypotheses of the interplay of self-efficacy, BPNS, and emotions. We conducted a micro-longitudinal study where 103 university teachers from Germany (49 female; average age: 41.4 years, SD=11.0) completed 1090 session-specific assessments of these constructs. Results of structural equation modeling revealed positive associations between self-efficacy and BPNS. Moreover, self-efficacy and BPNS emerged as being positively related to positive emotions and vice versa—however, not all emotions had significant associations with all basic psychological needs

Opposing roles of Akt and STAT3 in the protection of the maternal heart from peripartum stress

Background Peripartum cardiomyopathy ( PPCM) is a pregnancy-associated cardiomyopathy in previously healthy women. Mice with a cardiomyocyte-restricted deletion of signal transducer and activator of transcription-3 ( STAT3, CKO) develop PPCM. PI3K-Akt signalling is thought to promote cardiac hypertrophy and protection during pregnancy. We evaluated the role of activated Akt signalling in the maternal heart postpartum. Methods and results CKOmice were bred to mice harbouring an Akt transgene, specifically expressed in cardiomyocytes ( CAkt(tg)) generating CKO; CAkt(tg), CAkttg, CKO, and wild-type sibling mice. CAkt(tg) and CKO; CAkttg female mice developed PPCM with systolic dysfunction. Both genotypes displayed cardiac hypertrophy and lower capillary density, showed increased phosphorylation of p66 Src homology 2 domain containing protein and FoxO3A, and reduced expression of manganese superoxide dismutase as well as increased cathepsin D activity and increased miR-146a levels [ indicative for generation of the anti-angiogenic 16 kDa prolactin ( PRL)]. Cardiac inflammation and fibrosis was accelerated in CKO; CAkt(tg) and associated with high postpartum mortality. The PRL blocker, bromocriptine ( BR), prevented heart failure and the decrease in capillary density in CKO; CAkt(tg) and CAkt(tg) mice. BR attenuated high mortality, up-regulation of CCL2, and cardiac inflammation as well as fibrosis in CKO; CAkt(tg). PRL infusion induced cardiac inflammation in CKO; CAkt(tg) independent of pregnancy. In neonatal rat cardiomyocytes, PRL and interferon g ( IFN gamma) induced the expression of CCL2 via activation of Akt. Conclusion Postpartum Akt activation is detrimental for the peripartum heart as it lowers anti-oxidative defence and in combination with low STAT3 conditions, accelerate cardiac inflammation and fibrosis. PRL and its cleaved 16 kDa form are central for Akt-induced PPCM as indicated by the protection from the disease by PRL blockade

Prediction of combination therapies based on topological modeling of the immune signaling network in multiple sclerosis

Background: Multiple sclerosis (MS) is a major health problem, leading to a significant disability and patient suffering. Although chronic activation of the immune system is a hallmark of the disease, its pathogenesis is poorly understood, while current treatments only ameliorate the disease and may produce severe side effects. Methods: Here, we applied a network-based modeling approach based on phosphoproteomic data to uncover the differential activation in signaling wiring between healthy donors, untreated patients, and those under different treatments. Based in the patient-specific networks, we aimed to create a new approach to identify drug combinations that revert signaling to a healthy-like state. We performed ex vivo multiplexed phosphoproteomic assays upon perturbations with multiple drugs and ligands in primary immune cells from 169 subjects (MS patients, n=129 and matched healthy controls, n=40). Patients were either untreated or treated with fingolimod, natalizumab, interferon-β, glatiramer acetate, or the experimental therapy epigallocatechin gallate (EGCG). We generated for each donor a dynamic logic model by fitting a bespoke literature-derived network of MS-related pathways to the perturbation data. Last, we developed an approach based on network topology to identify deregulated interactions whose activity could be reverted to a "healthy-like" status by combination therapy. The experimental autoimmune encephalomyelitis (EAE) mouse model of MS was used to validate the prediction of combination therapies. Results: Analysis of the models uncovered features of healthy-, disease-, and drug-specific signaling networks. We predicted several combinations with approved MS drugs that could revert signaling to a healthy-like state. Specifically, TGF-β activated kinase 1 (TAK1) kinase, involved in Transforming growth factor β-1 proprotein (TGF-β), Toll-like receptor, B cell receptor, and response to inflammation pathways, was found to be highly deregulated and co-druggable with all MS drugs studied. One of these predicted combinations, fingolimod with a TAK1 inhibitor, was validated in an animal model of MS. Conclusions: Our approach based on donor-specific signaling networks enables prediction of targets for combination therapy for MS and other complex diseases. Keywords: Combination therapy; Immunotherapy; Kinases; Logic modeling; Multiple sclerosis; Network modeling; Pathways; Personalized medicine; Phosphoproteomics; Signaling networks; Treatment; xMAP assay

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

<div><p>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.</p></div