Model Based Targeting of IL-6-Induced Inflammatory Responses in Cultured Primary Hepatocytes to Improve Application of the JAK Inhibitor Ruxolitinib

Hepatocyte-specific disruption of soluble epoxide hydrolase attenuates abdominal aortic aneurysm formation: novel role of the liver in aneurysm pathogenesis

Introduction

Inflammation is a key pathogenic feature of abdominal aortic aneurysm (AAA). Soluble epoxide hydrolase (sEH) is a pro-inflammatory enzyme that converts cytochrome P450-derived epoxides of fatty acids to the corresponding diols, and pharmacological inhibition of sEH prevented AAA formation. Both cytochrome P450 enzymes and sEH are highly expressed in the liver. Here, we investigated the role of hepatic sEH in AAA using a selective pharmacological inhibitor of sEH and hepatocyte-specific Ephx2 (which encodes sEH gene) knockout (KO) mice in two models of AAA [angiotensin II (AngII) infusion and calcium chloride (CaCl 2 ) application].

Methods and results

sEH expression and activity were strikingly higher in mouse liver compared with aorta and further increased the context of AAA, in conjunction with elevated expression of the transcription factor Sp1 and the epigenetic regulator Jarid1b, which have been reported to positively regulate sEH expression. Pharmacological sEH inhibition, or liver-specific sEH disruption, achieved by crossing sEH floxed mice with albumin-cre mice, prevented AAA formation in both models, concomitant with reduced expression of hepatic sEH as well as complement factor 3 (C3) and serum amyloid A (SAA), liver-derived factors linked to AAA formation. Moreover, sEH antagonism markedly reduced C3 and SAA protein accumulation in the aortic wall. Co-incubation of liver ex vivo with aneurysm-prone aorta resulted in induction of sEH in the liver, concomitant with upregulation of Sp1, Jarid1b, C3 and SAA gene expression, suggesting that the aneurysm-prone aorta secretes factors that activate sEH and downstream inflammatory signaling in the liver. Using an unbiased proteomic approach, we identified a number of dysregulated proteins [ e.g., plastin-2, galectin-3 (gal-3), cathepsin S] released by aneurysm-prone aorta as potential candidate mediators of hepatic sEH induction.

Conclusion

We provide the first direct evidence of the liver's role in orchestrating AAA via the enzyme sEH. These findings not only provide novel insight into AAA pathogenesis, but they have potentially important implications with regard to developing effective medical therapies for AAA.

Dynamic modelling predicts lactate and IL-1β as interventional targets in metabolic-inflammation-clock regulatory loop in glioma

In an attempt to understand the role of dysregulated circadian rhythm in glioma, our recent findings highlighted the existence of a feed-forward loop between tumour metabolite lactate, pro-inflammatory cytokine IL-1β and circadian CLOCK. To further elucidate the implication of this complex interplay, we developed a mathematical model that quantitatively describes this lactate dehydrogenase A (LDHA)-IL-1β-CLOCK/BMAL1 circuit and predicts potential therapeutic targets. The model was calibrated on quantitative western blotting data in two glioma cell lines in response to either lactate inhibition or IL-1β stimulation. The calibrated model described the experimental data well and most of the parameters were identifiable, thus the model was predictive. Sensitivity analysis identified IL-1β and LDHA as potential intervention points. Mathematical models described here can be useful to understand the complex interrelationship between metabolism, inflammation and circadian rhythm, and in designing effective therapeutic strategies. Our findings underscore the importance of including the circadian clock when developing pharmacological approaches that target aberrant tumour metabolism and inflammation. Insight box  The complex interplay of metabolism-inflammation-circadian rhythm in tumours is not well understood. Our recent findings provided evidence of a feed-forward loop between tumour metabolite lactate, pro-inflammatory cytokine IL-1β and circadian CLOCK/BMAL1 in glioma. To elucidate the implication of this complex interplay, we developed a mathematical model that quantitatively describes this LDHA-IL-1β-CLOCK/BMAL1 circuit and integrates experimental data to predict potential therapeutic targets. The study employed a multi-start optimization strategy and profile likelihood estimations for parameter estimation and assessing identifiability. The simulations are in reasonable agreement with the experimental data. Sensitivity analysis found LDHA and IL-1β as potential therapeutic points. Mathematical models described here can provide insights to understand the complex interrelationship between metabolism, inflammation and circadian rhythm, and in identifying effective therapeutic targets.

Realistic simulation of time-course measurements in systems biology

In systems biology, the analysis of complex nonlinear systems faces many methodological challenges. For the evaluation and comparison of the performances of novel and competing computational methods, one major bottleneck is the availability of realistic test problems. We present an approach for performing realistic simulation studies for analyses of time course data as they are typically measured in systems biology. Since the design of experiments in practice depends on the process of interest, our approach considers the size and the dynamics of the mathematical model which is intended to be used for the simulation study. To this end, we used 19 published systems biology models with experimental data and evaluated the relationship between model features (e.g., the size and the dynamics) and features of the measurements such as the number and type of observed quantities, the number and the selection of measurement times, and the magnitude of measurement errors. Based on these typical relationships, our novel approach enables suggestions of realistic simulation study designs in the systems biology context and the realistic generation of simulated data for any dynamic model. The approach is demonstrated on three models in detail and its performance is validated on nine models by comparing ODE integration, parameter optimization, and parameter identifiability. The presented approach enables more realistic and less biased benchmark studies and thereby constitutes an important tool for the development of novel methods for dynamic modeling.

Protein phosphatases regulate the liver microenvironment in the development of hepatocellular carcinoma

The liver is a complicated heterogeneous organ composed of different cells. Parenchymal cells called hepatocytes and various nonparenchymal cells, including immune cells and stromal cells, are distributed in liver lobules with hepatic architecture. They interact with each other to compose the liver microenvironment and determine its characteristics. Although the liver microenvironment maintains liver homeostasis and function under healthy conditions, it also shows proinflammatory and profibrogenic characteristics that can induce the progression of hepatitis and hepatic fibrosis, eventually changing to a protumoral microenvironment that contributes to the development of hepatocellular carcinoma (HCC). According to recent studies, phosphatases are involved in liver diseases and HCC development by regulating protein phosphorylation in intracellular signaling pathways and changing the activities and characteristics of liver cells. Therefore, this review aims to highlight the importance of protein phosphatases in HCC development and in the regulation of the cellular components in the liver microenvironment and to show their significance as therapeutic targets.

Multi-Level Computational Modeling of Anti-Cancer Dendritic Cell Vaccination Utilized to Select Molecular Targets for Therapy Optimization

Dendritic cells (DCs) can be used for therapeutic vaccination against cancer. The success of this therapy depends on efficient tumor-antigen presentation to cytotoxic T lymphocytes (CTLs) and the induction of durable CTL responses by the DCs. Therefore, simulation of such a biological system by computational modeling is appealing because it can improve our understanding of the molecular mechanisms underlying CTL induction by DCs and help identify new strategies to improve therapeutic DC vaccination for cancer. Here, we developed a multi-level model accounting for the life cycle of DCs during anti-cancer immunotherapy. Specifically, the model is composed of three parts representing different stages of DC immunotherapy – the spreading and bio-distribution of intravenously injected DCs in human organs, the biochemical reactions regulating the DCs’ maturation and activation, and DC-mediated activation of CTLs. We calibrated the model using quantitative experimental data that account for the activation of key molecular circuits within DCs, the bio-distribution of DCs in the body, and the interaction between DCs and T cells. We showed how such a data-driven model can be exploited in combination with sensitivity analysis and model simulations to identify targets for enhancing anti-cancer DC vaccination. Since other previous works show how modeling improves therapy schedules and DC dosage, we here focused on the molecular optimization of the therapy. In line with this, we simulated the effect in DC vaccination of the concerted modulation of combined intracellular regulatory processes and proposed several possibilities that can enhance DC-mediated immunogenicity. Taken together, we present a comprehensive time-resolved multi-level model for studying DC vaccination in melanoma. Although the model is not intended for personalized patient therapy, it could be used as a tool for identifying molecular targets for optimizing DC-based therapy for cancer, which ultimately should be tested in in vitro and in vivo experiments.

Visualization and modeling of inhibition of IL-1β and TNF-α mRNA transcription at the single-cell level

IL-1β and TNF-α are canonical immune response mediators that play key regulatory roles in a wide range of inflammatory responses to both chronic and acute conditions. Here we employ an automated microscopy platform for the analysis of messenger RNA (mRNA) expression of IL-1β and TNF-α at the single-cell level. The amount of IL-1β and TNF-α mRNA expressed in a human monocytic leukemia cell line (THP-1) is visualized and counted using single-molecule fluorescent in-situ hybridization (smFISH) following exposure of the cells to lipopolysaccharide (LPS), an outer-membrane component of Gram-negative bacteria. We show that the small molecule inhibitors MG132 (a 26S proteasome inhibitor used to block NF-κB signaling) and U0126 (a MAPK Kinase inhibitor used to block CCAAT-enhancer-binding proteins C/EBP) successfully block IL-1β and TNF-α mRNA expression. Based upon this single-cell mRNA expression data, we screened 36 different mathematical models of gene expression, and found two similar models that capture the effects by which the drugs U0126 and MG132 affect the rates at which the genes transition into highly activated states. When their parameters were informed by the action of each drug independently, both models were able to predict the effects of the combined drug treatment. From our data and models, we postulate that IL-1β is activated by both NF-κB and C/EBP, while TNF-α is predominantly activated by NF-κB. Our combined single-cell experimental and modeling efforts show the interconnection between these two genes and demonstrates how the single-cell responses, including the distribution shapes, mean expression, and kinetics of gene expression, change with inhibition.

Hypoxia Routes Tryptophan Homeostasis Towards Increased Tryptamine Production

The liver is the central hub for processing and maintaining homeostatic levels of dietary nutrients especially essential amino acids such as tryptophan (Trp). Trp is required not only to sustain protein synthesis but also as a precursor for the production of NAD, neurotransmitters and immunosuppressive metabolites. In light of these roles of Trp and its metabolic products, maintaining homeostatic levels of Trp is essential for health and well-being. The liver regulates global Trp supply by the immunosuppressive enzyme tryptophan-2,3-dioxygenase (TDO2), which degrades Trp down the kynurenine pathway (KP). In the current study, we show that isolated primary hepatocytes when exposed to hypoxic environments, extensively rewire their Trp metabolism by reducing constitutive Tdo2 expression and differentially regulating other Trp pathway enzymes and transporters. Mathematical modelling of Trp metabolism in liver cells under hypoxia predicted decreased flux through the KP while metabolic flux through the tryptamine branch significantly increased. In line, the model also revealed an increased accumulation of tryptamines under hypoxia, at the expense of kynurenines. Metabolic measurements in hypoxic hepatocytes confirmed the predicted reduction in KP metabolites as well as accumulation of tryptamine. Tdo2 expression in cultured primary hepatocytes was reduced upon hypoxia inducible factor (HIF) stabilisation by dimethyloxalylglycine (DMOG), demonstrating that HIFs are involved in the hypoxic downregulation of hepatic Tdo2. DMOG abrogated hepatic luciferase signals in Tdo2 reporter mice, indicating that HIF stability also recapitulates hypoxic rewiring of Trp metabolism in vivo. Also in WT mice HIF stabilization drove homeostatic Trp metabolism away from the KP towards enhanced tryptamine production, leading to enhanced levels of tryptamine in liver, serum and brain. As tryptamines are the most potent hallucinogens known, the observed upregulation of tryptamine in response to hypoxic exposure of hepatocytes may be involved in the generation of hallucinations occurring at high altitude. KP metabolites are known to activate the aryl hydrocarbon receptor (AHR). The AHR-activating properties of tryptamines may explain why immunosuppressive AHR activity is maintained under hypoxia despite downregulation of the KP. In summary our results identify hypoxia as an important factor controlling Trp metabolism in the liver with possible implications for immunosuppressive AHR activation and mental disturbances.

Identification of Interleukin1β as an Amplifier of Interferon alpha-induced Antiviral Responses

The induction of an interferon-mediated response is the first line of defense against pathogens such as viruses. Yet, the dynamics and extent of interferon alpha (IFNα)-induced antiviral genes vary remarkably and comprise three expression clusters: early, intermediate and late. By mathematical modeling based on time-resolved quantitative data, we identified mRNA stability as well as a negative regulatory loop as key mechanisms endogenously controlling the expression dynamics of IFNα-induced antiviral genes in hepatocytes. Guided by the mathematical model, we uncovered that this regulatory loop is mediated by the transcription factor IRF2 and showed that knock-down of IRF2 results in enhanced expression of early, intermediate and late IFNα-induced antiviral genes. Co-stimulation experiments with different pro-inflammatory cytokines revealed that this amplified expression dynamics of the early, intermediate and late IFNα-induced antiviral genes can also be achieved by co-application of IFNα and interleukin1 beta (IL1β). Consistently, we found that IL1β enhances IFNα-mediated repression of viral replication. Conversely, we observed that in IL1β receptor knock-out mice replication of viruses sensitive to IFNα is increased. Thus, IL1β is capable to potentiate IFNα-induced antiviral responses and could be exploited to improve antiviral therapies.

Innate immune responses contribute to the control of viral infections and the induction of interferon alpha (IFNα)-mediated antiviral responses is an important component. However, IFNα induces a multitude of antiviral response genes and the expression dynamics of these genes can be classified as early, intermediate and late. Here we show, based on a mathematical modeling approach, that mRNA stability as well as the negative regulator IRF2 control the expression dynamics of IFNα-induced antiviral genes. Knock-down of IRF2 resulted in the amplified IFNα-mediated induction of the antiviral genes and this amplified expression of antiviral genes could be functionally mimicked by co-stimulation with IFNα and IL1β. We observed that co-stimulation with IFNα and IL1β enhanced the repression of virus replication and that knock-out of the IL1 receptor in mice resulted in increased replication of a virus sensitive to IFNα. In sum, our studies identified IL1β as an important amplifier of IFNα-induced antiviral responses.

Benchmark problems for dynamic modeling of intracellular processes

Motivation

Dynamic models are used in systems biology to study and understand cellular processes like gene regulation or signal transduction. Frequently, ordinary differential equation (ODE) models are used to model the time and dose dependency of the abundances of molecular compounds as well as interactions and translocations. A multitude of computational approaches, e.g. for parameter estimation or uncertainty analysis have been developed within recent years. However, many of these approaches lack proper testing in application settings because a comprehensive set of benchmark problems is yet missing.

Results

We present a collection of 20 benchmark problems in order to evaluate new and existing methodologies, where an ODE model with corresponding experimental data is referred to as problem. In addition to the equations of the dynamical system, the benchmark collection provides observation functions as well as assumptions about measurement noise distributions and parameters. The presented benchmark models comprise problems of different size, complexity and numerical demands. Important characteristics of the models and methodological requirements are summarized, estimated parameters are provided, and some example studies were performed for illustrating the capabilities of the presented benchmark collection.

Availability and implementation

The models are provided in several standardized formats, including an easy-to-use human readable form and machine-readable SBML files. The data is provided as Excel sheets. All files are available at https://github.com/Benchmarking-Initiative/Benchmark-Models, including step-by-step explanations and MATLAB code to process and simulate the models.

Supplementary information

Supplementary data are available at Bioinformatics online.

Response to IL-6 trans- and IL-6 classic signalling is determined by the ratio of the IL-6 receptor α to gp130 expression: fusing experimental insights and dynamic modelling

BACKGROUND

Interleukin-6 is a pleiotropic cytokine with high clinical relevance and an important mediator of cellular communication, orchestrating both pro- and anti-inflammatory processes. Interleukin-6-induced signalling is initiated by binding of IL-6 to the IL-6 receptor α and subsequent binding to the signal transducing receptor subunit gp130. This active receptor complex initiates signalling through the Janus kinase/signal transducer and activator of transcription pathway. Of note, IL-6 receptor α exists in a soluble and a transmembrane form. Binding of IL-6 to membrane-bound IL-6 receptor α induces anti-inflammatory classic signalling, whereas binding of IL-6 to soluble IL-6 receptor α induces pro-inflammatory trans-signalling. Trans-signalling has been described to be markedly stronger than classic signalling. Understanding the molecular mechanisms that drive differences between trans- and classic signalling is important for the design of trans-signalling-specific therapies. These differences will be addressed here using a combination of dynamic mathematical modelling and molecular biology.

METHODS

We apply an iterative systems biology approach using set-based modelling and validation approaches combined with quantitative biochemical and cell biological analyses.

RESULTS

The combination of experimental analyses and dynamic modelling allows to relate the observed differences between IL-6-induced trans- and classic signalling to cell-type specific differences in the expression and ratios of the individual subunits of the IL-6 receptor complex. Canonical intracellular Jak/STAT signalling is indifferent in IL-6-induced trans- and classic signalling.

CONCLUSION

This study contributes to the understanding of molecular mechanisms of IL-6 signal transduction and underlines the power of combined dynamical modelling, model-based validation and biological experiments. The opposing pro- and anti-inflammatory responses initiated by IL-6 trans- and classic signalling depend solely on the expression ratios of the subunits of the entire receptor complex. By pointing out the importance of the receptor expression ratio for the strength of IL-6 signalling this study lays a foundation for future precision medicine approaches that aim to selectively block pro-inflammatory trans-signalling. Furthermore, the derived models can be used for future therapy design.

Modulation of the IL-6-Signaling Pathway in Liver Cells by miRNAs Targeting gp130, JAK1, and/or STAT3

Interleukin-6 (IL-6)-type cytokines share the common receptor glycoprotein 130 (gp130), which activates a signaling cascade involving Janus kinases (JAKs) and signal transducer and activator of transcription (STAT) transcription factors. IL-6 and/or its signaling pathway is often deregulated in diseases, such as chronic liver diseases and cancer. Thus, the identification of compounds inhibiting this pathway is of interest for future targeted therapies. We established novel cellular screening systems based on a STAT-responsive reporter gene (Cypridina luciferase). Of a library containing 538 microRNA (miRNA) mimics, several miRNAs affected hyper-IL-6-induced luciferase activities. When focusing on candidate miRNAs specifically targeting 3′ UTRs of signaling molecules of this pathway, we identified, e.g., miR-3677-5p as a novel miRNA affecting protein expression of both STAT3 and JAK1, whereas miR-16-1-3p, miR-4473, and miR-520f-3p reduced gp130 surface expression. Interestingly, combination treatment with 2 or 3 miRNAs targeting gp130 or different signaling molecules of the pathway did not increase the inhibitory effects on phospho-STAT3 levels and STAT3 target gene expression compared to treatment with single mimics. Taken together, we identified a set of miRNAs of potential therapeutic value for cancer and inflammatory diseases, which directly target the expression of molecules within the IL-6-signaling pathway and can dampen inflammatory signal transduction.

Signals from the Niche: Insights into the Role of IGF-1 and IL-6 in Modulating Skeletal Muscle Fibrosis

Muscle regeneration, characterized by the activation and proliferation of satellite cells and other precursors, is accompanied by an inflammatory response and the remodeling of the extracellular matrix (ECM), necessary to remove cellular debris and to mechanically support newly generated myofibers and activated satellite cells. Muscle repair can be considered concluded when the tissue architecture, vascularization, and innervation have been restored. Alterations in these connected mechanisms can impair muscle regeneration, leading to the replacement of functional muscle tissue with a fibrotic scar. In the present review, we will discuss the cellular mediators of fibrosis and how the altered expression and secretion of soluble mediators, such as IL-6 and IGF-1, can modulate regulatory networks involved in the altered regeneration and fibrosis during aging and diseases.

Robustness and Information Transfer within IL-6-induced JAK/STAT Signalling

Cellular communication via intracellular signalling pathways is crucial. Expression and activation of signalling proteins is heterogenous between isogenic cells of the same cell-type. However, mechanisms evolved to enable sufficient communication and to ensure cellular functions. We use information theory to clarify mechanisms facilitating IL-6-induced JAK/STAT signalling despite cell-to-cell variability. We show that different mechanisms enabling robustness against variability complement each other. Early STAT3 activation is robust as long as cytokine concentrations are low. Robustness at high cytokine concentrations is ensured by high STAT3 expression or serine phosphorylation. Later the feedback-inhibitor SOCS3 increases robustness. Channel Capacity of JAK/STAT signalling is limited by cell-to-cell variability in STAT3 expression and is affected by the same mechanisms governing robustness. Increasing STAT3 amount increases Channel Capacity and robustness, whereas increasing STAT3 tyrosine phosphorylation reduces robustness but increases Channel Capacity. In summary, we elucidate mechanisms preventing dysregulated signalling by enabling reliable JAK/STAT signalling despite cell-to-cell heterogeneity.