TP10: Identification of systems properties determining the dynamics of the hepatitis B virus infection cycle and cross-talk to host cell responses

The dynamics of the cross-talk of the HBV infection cycle with host cell responses is studied by quantitative mass spectrometry. Based on this data a mathematical model of the HBV infection cycle is calibrated and will be linked to a dynamic pathway model of interferon (IFN)α induced antiviral responses. The aim is to identify mechanisms responsible for the synergistic effects of Myrcludex B (MyrB) and pegylated IFNα (PEG-IFNα) that was observed in clinical trials and thereby provide means to identify patients that might particularly benefit from the co-treatment of MyrB and PEG-IFNα.

Prof. Dr. Ursula Klingmüller

Prof. Dr. Jens Timmer

D’Alessandro LA, Klingmüller U, Schilling M. (2022) Deciphering signal transduction networks in the liver by mechanistic mathematical modelling. Biochem J. 479 (12): 1361–1374. doi: https://doi.org/10.1042/BCJ20210548.

Robichon K, Maiwald T, Schilling M, Schneider A, Willemsen J, Salopiata F, Teusel M, Kreutz C, Ehlting C, Huang J, Chakraborty S, Huang X, Damm G, Seehofer D, Lang PA, Bode JG, Binder M, Bartenschlager R, Timmer J, Klingmüller U. Identification of Interleukin1β as an Amplifier of Interferon alpha-induced Antiviral Responses. PLoS Pathog. 2020 Oct 1;16(10):e1008461. doi: 10.1371/journal.ppat.1008461. (TP09, TP10, TP11)

Lampl S, Janas MK, Donakonda S, Brugger M, Lohr K, Schneider A, Manske K, Sperl LE, Kläger S, Küster B, Wettmarshausen J, Müller C, Laschinger M, Hartmann D, Hüser N, Perocchi F, Schmitt-Kopplin P, Hagn F, Zender L, Hornung V, Borner C, Pichlmair A, Kashkar H, Klingenspor M, Prinz M, Schreiner S, Conrad M, Jost PJ, Zischka H, Steiger K, Krönke M, Zehn D, Protzer U, Heikenwälder M, Knolle PA, Wohlleber D. Reduced mitochondrial resilience enables non-canonical induction of apoptosis after TNF receptor signaling in virus-infected hepatocytes. J Hepatol. 2020 Jun 26:S0168-8278(20)30398-6. doi: 10.1016/j.jhep.2020.06.026. (TP05, TP06, TP10, TP11, TP13, TP16, TP18)

Kok F, Rosenblatt M, Teusel M, Nizharadze T, Gonçalves Magalhães V, Dächert C, Maiwald T, Vlasov A, Wäsch M, Tyufekchieva S, Hoffmann K, Damm G, Seehofer D, Boettler T, Binder M, Timmer J, Schilling M, Klingmüller U. 2020. Disentangling molecular mechanisms regulating sensitization of interferon alpha signal transduction. Molecular Systems Biology 2020 Jul;16(7):e8955. doi: 10.15252/msb.20198955. (TP10)

Hass H, Loos C, Alvarez ER, Timmer J, Hasenauer J, Kreutz C. 2019. Benchmark Problems for Dynamic Modeling of Intracellular Processes. Bioinformatics. Bioinformatics 35: 3073-3082.

Kaschek D, Mader W, Fehling-Kaschek M, Rosenblatt M, Timmer J. 2019. Dynamic Modeling, Parame-ter Estimation, and Uncertainty Analysis in R. Journal of Statistical Software. 10: 1-32.

Lucarelli P, Schilling M, Kreutz C, Vlasov A, Boehm ME, Iwamoto N, Steiert B, Lattermann S, Wäsch M, Stepath M, Matter MS, Heikenwälder M, Hoffmann K, Deharde D, Damm G, Seehofer D, Muciek M, Gretz N, Lehmann WD, Timmer J, Klingmüller U. 2018. Resolving the Combinatorial Complexity of Smad Protein Complex Formation and Its Link to Gene Expression. Cell Syst. 6(1):75-89.

Oppelt A, Kaschek D, Huppelschoten S, Sison-Young R, Zhang F, Buck-Wiese M, Herrmann F, Malkusch S, Krüger CL, Meub M, Merkt B, Zimmermann L, Schofield A, Jones RP, Malik H, Schilling M, Heilemann M, van de Water B, Goldring CE, Park BK, Timmer J, Klingmüller U. 2018. Model-based identification of TNFα-induced IKKβ-mediated and IκBα-mediated regulation of NFκB signal transduc-tion as a tool to quantify the impact of drug-induced liver injury compounds. NPJ Syst Biol Appl. 4:23.

Sobotta S, Raue A, Huang X, Vanlier J, Jünger A, Bohl S, Albrecht U, Hahnel MJ, Wolf S, Mueller NS, D'Alessandro LA, Mueller-Bohl S, Boehm ME, Lucarelli P, Bonefas S, Damm G, Seehofer D, Lehmann WD, Rose-John S, van der Hoeven F, Gretz N, Theis FJ, Ehlting C, Bode JG, Timmer J, Schilling M, Klingmüller U. 2017. Model Based Targeting of IL-6-Induced Inflammatory Responses in Cultured Pri-mary Hepatocytes to Improve Application of the JAK Inhibitor Ruxolitinib. Front Physiol. 8:775

Rosenblatt M, Timmer J, Kaschek D. 2016. Customized Steady-State Constraints for Parameter Esti-mation in Non-Linear Ordinary Differential Equation Models. Front Cell Dev Biol. 4:41.

Maiwald T, Hass H, Steiert B, Vanlier J, Engesser R, Raue A, Kipkeew F, Bock HH, Kaschek D, Kreutz C, Timmer J. 2016. Driving the Model to Its Limit: Profile Likelihood Based Model Reduction. PLoS One. 11(9):e0162366.

D'Alessandro LA, Samaga R, Maiwald T, Rho SH, Bonefas S, Raue A, Iwamoto N, Kienast A, Waldow K, Meyer R, Schilling M, Timmer J, Klamt S, Klingmüller U. 2015. Disentangling the Complexity of HGF Signaling by Combining Qualitative and Quantitative Modeling. PLoS Comput Biol. 11(4):e1004192.

Mueller S, Huard J, Waldow K, Huang X, D'Alessandro LA, Bohl S, Börner K, Grimm D, Klamt S, Klingmüller U, Schilling M. 2015. T160-phosphorylated CDK2 defines threshold for HGF dependent proliferation in primary hepatocytes. Mol Syst Biol. 11(3):795.

Raue A, Steiert B, Schelker M, Kreutz C, Maiwald T, Hass H, Vanlier J, Tönsing C, Adlung L, Engesser R, Mader W, Heinemann T, Hasenauer J, Schilling M, Höfer T, Klipp E, Theis F, Klingmüller U, Schö-berl B, Timmer J. 2015. Data2Dynamics: a modeling environment tailored to parameter estimation in dynamical systems. Bioinformatics. 31(21):3558-60.

Project in detail +

Chronic hepatitis B virus (HBV) infections are a major health burden with around 240 million affected people worldwide. Currently recommended treatment options are PEGylated interferon alpha (PEG-IFNα) or nucle-os(t)ide analogues, but cure rates remain very low. In a recent clinical trial by Urban it was observed that co-treatment of HBV-infected patients superinfected with Hepatitis Delta virus (HDV) with the HBV entry inhibi-tor Myrcludex B (MyrB) and PEG-IFNα resulted in synergistic effects and, surprisingly, in some patients in an elimination of HBV. To elucidate molecular mechanisms that contribute to the clinically observed syner-gy, this project employs a systems biology approach that facilitates to disentangle complex interactions operating at different temporal and spatial scales. To mathematically describe events in HBV infected host cells, we established a targeted mass spectrometry approach that allows to accurately quantify the HBx protein – a key regulator of HBV gene expression – in infected hepatocytes. Together with Urban time- and dose-resolved data for HBx protein, HBV core protein, secretion of HBsAg and HBeAg as well as cccDNA production have been generated to develop an initial dynamic pathway model. With respect to activation of antiviral responses in a host cell, we showed that the extent of IFNα induced signal transduction is sensitive to pre-exposure to IFNα and dependent on the expression levels of the feedback regulators USP18 and STAT2, which are heterogeneously expressed in patients. Interestingly, our model-based approach revealed that interleukin (IL)-1β is capable to enhance antiviral responses triggered by IFNα. To quantitatively assess the modulation of IFNα induced antiviral responses by inflammatory factors, we established mechanistic models for transforming growth factor beta (TGFβ) signal transduction in hepatocytes showing the relation of Smad-complex formation to target gene expression (Lucarelli et al., 2018) and for IL-6 induced STAT3 activation (Sobotta et al., 2017). The focus of the next funding period will be to define the cross-talk of reactions of the HBV infection cycle with host cell responses and the impact of antiviral responses elicited by inflammatory factors such as IFNα, IL-1β IL-6 or TGFβ to elucidate molecular mechanisms that could contribute to synergistic effects and most importantly to HBV elimination. Specifically, we will (i) extend our targeted mass spectrometry approach to facilitate the simultaneous quantification of all viral proteins and determine HBV cccDNA production and RNA expression (with Urban) in time- and dose-resolved infection experiments, which will include the analysis of the dose-dependent impact of MyrB. Heterogeneity of the dynamics will be examined by single cell sequencing (with Z03N). This data will be used to calibrate a com-prehensive dynamic pathway model of the HBV infection cycle to identify key mechanisms determining the dynamics of HBV infection and to identify reactions in the HBV infection cycle that are most sensitive to perturbations and could be targeted to foster HBV elimination. We will (ii) examine the cross talk of HBV infection with host cell responses by analysing (with Binder/Pichlmair) dynamic changes in the host cell pro-teome with a particular emphasis on detecting alterations in signal transduction pathways involved in in-flammatory signalling such as IFNα, IL-1β, IL-6 and TGFβ. We will determine the impact of PEG-IFNα in-duced antiviral responses on reactions of the HBV infection cycle and elucidate (with Urban, Protzer, Schreiner) mechanisms that control the degradation of cccDNA. To test possibilities to enhance these re-sponses, we will examine the impact of co-stimulation of PEG-IFNα with IL-1β or TGFβ and thereby identify mechanisms that explain the elimination of HBV infection upon co-treatment with MyrB and PEG-IFN in patients with elevated inflammatory responses. To prepare a link from the cellular scale to the systemic level in patients, we will (iii) adapt our mathematical model on sensitization of IFNα signal transduction to PEG-IFNα, implement a more detailed receptor-ligand interaction model as an interphase to the systemic level and link the induction of antiviral responses to the impact on HBV cccDNA. Together with Boettler and Thimme we will explore the analysis of patient derived data such as serum IFNα levels and use the insights obtained in the project to develop strategies to a priori identify patients that particularly benefit from co-treatment with MyrB and PEG-IFNα and predict further options to prevent viral persistence and improve cure rate.

Milestones of the first funding period:
- Identification of rate limiting steps in the HBV infection cycle
- Impact of IFNα treatment on HBV infection
- Identification of strategies to enhance IFNα mediated antiviral effects