• In-silico insights on the prognostic potential of immune cell infiltration patterns in the breast lobular epithelium.

      Alfonso, J C L; Schaadt, N S; Schönmeyer, R; Brieu, N; Forestier, G; Wemmert, C; Feuerhake, F; Hatzikirou, H; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany. (2016-10-12)
      Scattered inflammatory cells are commonly observed in mammary gland tissue, most likely in response to normal cell turnover by proliferation and apoptosis, or as part of immunosurveillance. In contrast, lymphocytic lobulitis (LLO) is a recurrent inflammation pattern, characterized by lymphoid cells infiltrating lobular structures, that has been associated with increased familial breast cancer risk and immune responses to clinically manifest cancer. The mechanisms and pathogenic implications related to the inflammatory microenvironment in breast tissue are still poorly understood. Currently, the definition of inflammation is mainly descriptive, not allowing a clear distinction of LLO from physiological immunological responses and its role in oncogenesis remains unclear. To gain insights into the prognostic potential of inflammation, we developed an agent-based model of immune and epithelial cell interactions in breast lobular epithelium. Physiological parameters were calibrated from breast tissue samples of women who underwent reduction mammoplasty due to orthopedic or cosmetic reasons. The model allowed to investigate the impact of menstrual cycle length and hormone status on inflammatory responses to cell turnover in the breast tissue. Our findings suggested that the immunological context, defined by the immune cell density, functional orientation and spatial distribution, contains prognostic information previously not captured by conventional diagnostic approaches.
    • Influenza A virus-induced thymus atrophy differentially affects dynamics of conventional and regulatory T-cell development in mice.

      Elfaki, Yassin; Robert, Philippe A; Binz, Christoph; Falk, Christine S; Bruder, Dunja; Prinz, Immo; Floess, Stefan; Meyer-Hermann, Michael; Huehn, Jochen; HZI,Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7,38124 Braunschweig, Germany.; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany. (Wiley-VCH, 2021-02-26)
      Foxp3+ Treg cells, which are crucial for maintenance of self-tolerance, mainly develop within the thymus, where they arise from CD25+ Foxp3- or CD25- Foxp3+ Treg cell precursors. Although it is known that infections can cause transient thymic involution, the impact of infection-induced thymus atrophy on thymic Treg (tTreg) cell development is unknown. Here, we infected mice with influenza A virus (IAV) and studied thymocyte population dynamics post infection. IAV infection caused a massive, but transient thymic involution, dominated by a loss of CD4+ CD8+ double-positive (DP) thymocytes, which was accompanied by a significant increase in the frequency of CD25+ Foxp3+ tTreg cells. Differential apoptosis susceptibility could be experimentally excluded as a reason for the relative tTreg cell increase, and mathematical modeling suggested that enhanced tTreg cell generation cannot explain the increased frequency of tTreg cells. Yet, an increased death of DP thymocytes and augmented exit of single-positive (SP) thymocytes was suggested to be causative. Interestingly, IAV-induced thymus atrophy resulted in a significantly reduced T-cell receptor (TCR) repertoire diversity of newly produced tTreg cells. Taken together, IAV-induced thymus atrophy is substantially altering the dynamics of major thymocyte populations, finally resulting in a relative increase of tTreg cells with an altered TCR repertoire.
    • Influenza epidemic surveillance and prediction based on electronic health record data from an out-of-hours general practitioner cooperative: model development and validation on 2003-2015 data.

      Michiels, Barbara; Nguyen, Van Kinh; Coenen, Samuel; Ryckebosch, Philippe; Bossuyt, Nathalie; Hens, Niel; BRICS - Braunschweig Integrated Centre of Systems Biology, Rebenring 56. 38106 Braunschweig, Germany. (2017-01-18)
      Annual influenza epidemics significantly burden health care. Anticipating them allows for timely preparation. The Scientific Institute of Public Health in Belgium (WIV-ISP) monitors the incidence of influenza and influenza-like illnesses (ILIs) and reports on a weekly basis. General practitioners working in out-of-hour cooperatives (OOH GPCs) register diagnoses of ILIs in an instantly accessible electronic health record (EHR) system. This article has two objectives: to explore the possibility of modelling seasonal influenza epidemics using EHR ILI data from the OOH GPC Deurne-Borgerhout, Belgium, and to attempt to develop a model accurately predicting new epidemics to complement the national influenza surveillance by WIV-ISP.
    • Injection of Antibodies against Immunodominant Epitopes Tunes Germinal Centers to Generate Broadly Neutralizing Antibodies.

      Meyer-Hermann, Michael; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany. (Elsevier, 2019-10-29)
      Broadly neutralizing antibodies are crucial for the control of many life-threatening viral infections like HIV, influenza, or hepatitis. Their induction is a prime goal in vaccine research. Using computer simulations, we identify strategies to promote the generation of broadly neutralizing antibodies in natural germinal center (GC) reactions. The simulations predict a feedback loop based on antibodies and memory B cells from previous GC reactions that promotes GCs to focus on new epitopes. Memory-derived or injected antibodies specific for immunodominant epitopes control epitope availability, suppress the participation of memory B cells in the GC reaction, and allow for the evolution of other B cells to affinity mature for hidden or rare epitopes. This defines a natural selection mechanism for GC B cells to concentrate on new epitopes rather than refine affinity to already-covered epitopes. This principle can be used for the design and testing of future therapies and vaccination protocols.
    • Inoculation density and nutrient level determine the formation of mushroom-shaped structures in Pseudomonas aeruginosa biofilms.

      Ghanbari, Azadeh; Dehghany, Jaber; Schwebs, Timo; Müsken, Mathias; Häussler, Susanne; Meyer-Hermann, Michael; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany. (2016-09-09)
      Pseudomonas aeruginosa often colonises immunocompromised patients and the lungs of cystic fibrosis patients. It exhibits resistance to many antibiotics by forming biofilms, which makes it hard to eliminate. P. aeruginosa biofilms form mushroom-shaped structures under certain circumstances. Bacterial motility and the environment affect the eventual mushroom morphology. This study provides an agent-based model for the bacterial dynamics and interactions influencing bacterial biofilm shape. Cell motility in the model relies on recently published experimental data. Our simulations show colony formation by immotile cells. Motile cells escape from a single colony by nutrient chemotaxis and hence no mushroom shape develops. A high number density of non-motile colonies leads to migration of motile cells onto the top of the colonies and formation of mushroom-shaped structures. This model proposes that the formation of mushroom-shaped structures can be predicted by parameters at the time of bacteria inoculation. Depending on nutrient levels and the initial number density of stalks, mushroom-shaped structures only form in a restricted regime. This opens the possibility of early manipulation of spatial pattern formation in bacterial colonies, using environmental factors.
    • Integrating Mathematical Modeling into the Roadmap for Personalized Adaptive Radiation Therapy

      Enderling, Heiko; Alfonso, Juan Carlos López; Moros, Eduardo; Caudell, Jimmy J.; Harrison, Louis B.; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany. (Elsevier(Cell Press), 2019-08-01)
      In current radiation oncology practice, treatment protocols are prescribed based on the average outcomes of large clinical trials, with limited personalization and without adaptations of dose or dose fractionation to individual patients based on their individual clinical responses. Predicting tumor responses to radiation and comparing predictions against observed responses offers an opportunity for novel treatment evaluation. These analyses can lead to protocol adaptation aimed at the improvement of patient outcomes with better therapeutic ratios. We foresee the integration of mathematical models into radiation oncology to simulate individual patient tumor growth and predict treatment response as dynamic biomarkers for personalized adaptive radiation therapy (RT).
    • Investigating the Physical Effects in Bacterial Therapies for Avascular Tumors.

      Mascheroni, Pietro; Meyer-Hermann, Michael; Hatzikirou, Haralampos (Frontiers, 2020-06-04)
      Tumor-targeting bacteria elicit anticancer effects by infiltrating hypoxic regions, releasing toxic agents and inducing immune responses. Although current research has largely focused on the influence of chemical and immunological aspects on the mechanisms of bacterial therapy, the impact of physical effects is still elusive. Here, we propose a mathematical model for the anti-tumor activity of bacteria in avascular tumors that takes into account the relevant chemo-mechanical effects. We consider a time-dependent administration of bacteria and analyze the impact of bacterial chemotaxis and killing rate. We show that active bacterial migration toward tumor hypoxic regions provides optimal infiltration and that high killing rates combined with high chemotactic values provide the smallest tumor volumes at the end of the treatment.We highlight the emergence of steady states in which a small population of bacteria is able to constrain tumor growth. Finally, we show that bacteria treatment works best in the case of tumors with high cellular proliferation and low oxygen consumption.
    • In Vivo Killing Capacity of Cytotoxic T Cells Is Limited and Involves Dynamic Interactions and T Cell Cooperativity.

      Halle, Stephan; Keyser, Kirsten Anja; Stahl, Felix Rolf; Busche, Andreas; Marquardt, Anja; Zheng, Xiang; Galla, Melanie; Heissmeyer, Vigo; Heller, Katrin; Boelter, Jasmin; et al. (2016-02-16)
      According to in vitro assays, T cells are thought to kill rapidly and efficiently, but the efficacy and dynamics of cytotoxic T lymphocyte (CTL)-mediated killing of virus-infected cells in vivo remains elusive. We used two-photon microscopy to quantify CTL-mediated killing in mice infected with herpesviruses or poxviruses. On average, one CTL killed 2-16 virus-infected cells per day as determined by real-time imaging and by mathematical modeling. In contrast, upon virus-induced MHC class I downmodulation, CTLs failed to destroy their targets. During killing, CTLs remained migratory and formed motile kinapses rather than static synapses with targets. Viruses encoding the calcium sensor GCaMP6s revealed strong heterogeneity in individual CTL functional capacity. Furthermore, the probability of death of infected cells increased for those contacted by more than two CTLs, indicative of CTL cooperation. Thus, direct visualization of CTLs during killing of virus-infected cells reveals crucial parameters of CD8(+) T cell immunity.
    • A least microenvironmental uncertainty principle (LEUP) as a generative model of collective cell migration mechanisms.

      Barua, Arnab; Nava-Sedeño, Josue M; Meyer-Hermann, Michael; Hatzikirou, Haralampos; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany. (Nature research, 2020-12-22)
      Collective migration is commonly observed in groups of migrating cells, in the form of swarms or aggregates. Mechanistic models have proven very useful in understanding collective cell migration. Such models, either explicitly consider the forces involved in the interaction and movement of individuals or phenomenologically define rules which mimic the observed behavior of cells. However, mechanisms leading to collective migration are varied and specific to the type of cells involved. Additionally, the precise and complete dynamics of many important chemomechanical factors influencing cell movement, from signalling pathways to substrate sensing, are typically either too complex or largely unknown. The question is how to make quantitative/qualitative predictions of collective behavior without exact mechanistic knowledge. Here we propose the least microenvironmental uncertainty principle (LEUP) that may serve as a generative model of collective migration without precise incorporation of full mechanistic details. Using statistical physics tools, we show that the famous Vicsek model is a special case of LEUP. Finally, to test the biological applicability of our theory, we apply LEUP to construct a model of the collective behavior of spherical Serratia marcescens bacteria, where the underlying migration mechanisms remain elusive.
    • A mathematical model of immune activation with a unified self-nonself concept.

      Khailaie, Sahamoddin; Bahrami, Fariba; Janahmadi, Mahyar; Milanez-Almeida, Pedro; Huehn, Jochen; Meyer-Hermann, Michael (2013)
      The adaptive immune system reacts against pathogenic nonself, whereas it normally remains tolerant to self. The initiation of an immune response requires a critical antigen(Ag)-stimulation and a critical number of Ag-specific T cells. Autoreactive T cells are not completely deleted by thymic selection and partially present in the periphery of healthy individuals that respond in certain physiological conditions. A number of experimental and theoretical models are based on the concept that structural differences discriminate self from nonself. In this article, we establish a mathematical model for immune activation in which self and nonself are not distinguished. The model considers the dynamic interplay of conventional T cells, regulatory T cells (Tregs), and IL-2 molecules and shows that the renewal rate ratio of resting Tregs to naïve T cells as well as the proliferation rate of activated T cells determine the probability of immune stimulation. The actual initiation of an immune response, however, relies on the absolute renewal rate of naïve T cells. This result suggests that thymic selection reduces the probability of autoimmunity by increasing the Ag-stimulation threshold of self reaction which is established by selection of a low number of low-avidity autoreactive T cells balanced with a proper number of Tregs. The stability analysis of the ordinary differential equation model reveals three different possible immune reactions depending on critical levels of Ag-stimulation: a subcritical stimulation, a threshold stimulation inducing a proper immune response, and an overcritical stimulation leading to chronic co-existence of Ag and immune activity. The model exhibits oscillatory solutions in the case of persistent but moderate Ag-stimulation, while the system returns to the homeostatic state upon Ag clearance. In this unifying concept, self and nonself appear as a result of shifted Ag-stimulation thresholds which delineate these three regimes of immune activation.
    • A mathematical model of T lymphocyte calcium dynamics derived from single transmembrane protein properties.

      Schmeitz, Christine; Hernandez-Vargas, Esteban Abelardo; Fliegert, Ralf; Guse, Andreas H; Meyer-Hermann, Michael; Department of Systems Immunology, Helmholtz Centre for Infection Research , Braunschweig , Germany. (2013)
      Fate decision processes of T lymphocytes are crucial for health and disease. Whether a T lymphocyte is activated, divides, gets anergic, or initiates apoptosis depends on extracellular triggers and intracellular signaling. Free cytosolic calcium dynamics plays an important role in this context. The relative contributions of store-derived calcium entry and calcium entry from extracellular space to T lymphocyte activation are still a matter of debate. Here we develop a quantitative mathematical model of T lymphocyte calcium dynamics in order to establish a tool which allows to disentangle cause-effect relationships between ion fluxes and observed calcium time courses. The model is based on single transmembrane protein characteristics which have been determined in independent experiments. This reduces the number of unknown parameters in the model to a minimum and ensures the predictive power of the model. Simulation results are subsequently used for an analysis of whole cell calcium dynamics measured under various experimental conditions. The model accounts for a variety of these conditions, which supports the suitability of the modeling approach. The simulation results suggest a model in which calcium dynamics dominantly relies on the opening of channels in calcium stores while calcium entry through calcium-release activated channels (CRAC) is more associated with the maintenance of the T lymphocyte calcium levels and prevents the cell from calcium depletion. Our findings indicate that CRAC guarantees a long-term stable calcium level which is required for cell survival and sustained calcium enhancement.
    • A mathematical model of the impact of insulin secretion dynamics on selective hepatic insulin resistance.

      Zhao, Gang; Wirth, Dagmar; Schmitz, Ingo; Meyer-Hermann, Michael; Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106, Germany. (2017-11-08)
      Physiological insulin secretion exhibits various temporal patterns, the dysregulation of which is involved in diabetes development. We analyzed the impact of first-phase and pulsatile insulin release on glucose and lipid control with various hepatic insulin signaling networks. The mathematical model suggests that atypical protein kinase C (aPKC) undergoes a bistable switch-on and switch-off, under the control of insulin receptor substrate 2 (IRS2). The activation of IRS1 and IRS2 is temporally separated due to the inhibition of IRS1 by aPKC. The model further shows that the timing of aPKC switch-off is delayed by reduced first-phase insulin and reduced amplitude of insulin pulses. Based on these findings, we propose a sequential model of postprandial hepatic control of glucose and lipid by insulin, according to which delayed aPKC switch-off contributes to selective hepatic insulin resistance, which is a long-standing paradox in the field.
    • Mathematical Model Shows How Sleep May Affect Amyloid-β Fibrillization.

      Hoore, Masoud; Khailaie, Sahamoddin; Montaseri, Ghazal; Mitra, Tanmay; Meyer-Hermann, Michael; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany; HZI,Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7,38124 Braunschweig, Germany. (Elsevier (CellPress), 2020-07-22)
      Deposition of amyloid-β (Aβ) fibers in the extracellular matrix of the brain is a ubiquitous feature associated with several neurodegenerative disorders, especially Alzheimer's disease (AD). Although many of the biological aspects that contribute to the formation of Aβ plaques are well addressed at the intra- and intercellular levels in short timescales, an understanding of how Aβ fibrillization usually starts to dominate at a longer timescale despite the presence of mechanisms dedicated to Aβ clearance is still lacking. Furthermore, no existing mathematical model integrates the impact of diurnal neural activity as emanated from circadian regulation to predict disease progression due to a disruption in the sleep-wake cycle. In this study, we develop a minimal model of Aβ fibrillization to investigate the onset of AD over a long timescale. Our results suggest that the diseased state is a manifestation of a phase change of the system from soluble Aβ (sAβ) to fibrillar Aβ (fAβ) domination upon surpassing a threshold in the production rate of sAβ. By incorporating the circadian rhythm into our model, we reveal that fAβ accumulation is crucially dependent on the regulation of the sleep-wake cycle, thereby indicating the importance of good sleep hygiene in averting AD onset. We also discuss potential intervention schemes to reduce fAβ accumulation in the brain by modification of the critical sAβ production rate.
    • Mechanical Control of Cell Proliferation Increases Resistance to Chemotherapeutic Agents.

      Rizzuti, Ilaria Francesca; Mascheroni, Pietro; Arcucci, Silvia; Ben-Mériem, Zacchari; Prunet, Audrey; Barentin, Catherine; Rivière, Charlotte; Delanoë-Ayari, Hélène; Hatzikirou, Haralampos; Guillermet-Guibert, Julie; et al. (American Physical Society, 2020-09-18)
      While many cellular mechanisms leading to chemotherapeutic resistance have been identified, there is an increasing realization that tumor-stroma interactions also play an important role. In particular, mechanical alterations are inherent to solid cancer progression and profoundly impact cell physiology. Here, we explore the influence of compressive stress on the efficacy of chemotherapeutics in pancreatic cancer spheroids. We find that increased compressive stress leads to decreased drug efficacy. Theoretical modeling and experiments suggest that mechanical stress decreases cell proliferation which in turn reduces the efficacy of chemotherapeutics that target proliferating cells. Our work highlights a mechanical form of drug resistance and suggests new strategies for therapy.
    • MicroRNA-155 controls affinity-based selection by protecting c-MYC+ B cells from apoptosis.

      Nakagawa, Rinako; Leyland, Rebecca; Müller, A; Lu, Dong; Turner, Martin; Arbore, Giuseppina; Phan, Tri Giang; Brink, Robert; Vigorito, Elena; Helmholtz Centre for infection research, Inhoffenstr. 7, 38124 Braunschweig, Germany. (2016-01-04)
      The production of high-affinity antibodies by B cells is essential for pathogen clearance. Antibody affinity for antigen is increased through the affinity maturation in germinal centers (GCs). This is an iterative process in which B cells cycle between proliferation coupled with the acquisition of mutations and antigen-based positive selection, resulting in retention of the highest-affinity B cell clones. The posttranscriptional regulator microRNA-155 (miR-155) is critical for efficient affinity maturation and the maintenance of the GCs; however, the cellular and molecular mechanism by which miR-155 regulates GC responses is not well understood. Here, we utilized a miR-155 reporter mouse strain and showed that miR-155 is coexpressed with the proto-oncogene encoding c-MYC in positively selected B cells. Functionally, miR-155 protected positively selected c-MYC+ B cells from apoptosis, allowing clonal expansion of this population, providing an explanation as to why Mir155 deletion impairs affinity maturation and promotes the premature collapse of GCs. We determined that miR-155 directly inhibits the Jumonji family member JARID2, which enhances B cell apoptosis when overexpressed, and thereby promotes GC B cell survival. Our findings also suggest that there is cooperation between c-MYC and miR-155 during the normal GC response, a cooperation that may explain how c-MYC and miR-155 can collaboratively function as oncogenes.
    • A minimal modeling framework of radiation and immune system synergy to assist radiotherapy planning.

      Montaseri, Ghazal; Alfonso, Juan Carlos López; Hatzikirou, Haralampos; Meyer-Hermann, Michael (Elsevier, 2020-02-07)
    • Modeling Influenza Virus Infection: A Roadmap for Influenza Research.

      Boianelli, Alessandro; Nguyen, Van Kinh; Ebensen, Thomas; Schulze, Kai; Wilk, Esther; Sharma, Niharika; Stegemann-Koniszewski, Sabine; Bruder, Dunja; Toapanta, Franklin R; Guzmán, Carlos A; et al. (2015-10)
      Influenza A virus (IAV) infection represents a global threat causing seasonal outbreaks and pandemics. Additionally, secondary bacterial infections, caused mainly by Streptococcus pneumoniae, are one of the main complications and responsible for the enhanced morbidity and mortality associated with IAV infections. In spite of the significant advances in our knowledge of IAV infections, holistic comprehension of the interplay between IAV and the host immune response (IR) remains largely fragmented. During the last decade, mathematical modeling has been instrumental to explain and quantify IAV dynamics. In this paper, we review not only the state of the art of mathematical models of IAV infection but also the methodologies exploited for parameter estimation. We focus on the adaptive IR control of IAV infection and the possible mechanisms that could promote a secondary bacterial coinfection. To exemplify IAV dynamics and identifiability issues, a mathematical model to explain the interactions between adaptive IR and IAV infection is considered. Furthermore, in this paper we propose a roadmap for future influenza research. The development of a mathematical modeling framework with a secondary bacterial coinfection, immunosenescence, host genetic factors and responsiveness to vaccination will be pivotal to advance IAV infection understanding and treatment optimization.
    • Modeling the effect of intratumoral heterogeneity of radiosensitivity on tumor response over the course of fractionated radiation therapy.

      Alfonso, J C L; Berk, L; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany. (BioMed Central (BMC), 2019-05-30)
      Standard radiobiology theory of radiation response assumes a uniform innate radiosensitivity of tumors. However, experimental data show that there is significant intratumoral heterogeneity of radiosensitivity. Therefore, a model with heterogeneity was developed and tested using existing experimental data to show the potential effects from the presence of an intratumoral distribution of radiosensitivity on radiation therapy response over a protracted radiation therapy treatment course.
    • Modeling the three stages in HIV infection.

      Hernandez-Vargas, Esteban A; Middleton, Richard H; SIMM, Helmholtz Zentrum für Infektionsforschung, Inhoffenstraße 7, D-38124 Braunschweig, Germany. (2013-03-07)
      A typical HIV infection response consists of three stages: an initial acute infection, a long asymptomatic period and a final increase in viral load with simultaneous collapse in healthy CD4+T cell counts. The majority of existing mathematical models give a good representation of either the first two stages or the last stage of the infection. Using macrophages as a long-term active reservoir, a deterministic model is proposed to explain the three stages of the infection including the progression to AIDS. Simulation results illustrate how chronic infected macrophages can explain the progression to AIDS provoking viral explosion. Further simulation studies suggest that the proposed model retains its key properties even under moderately large parameter variations. This model provides important insights on how macrophages might play a crucial role in the long term behavior of HIV infection.
    • Modelling collective cell motion: are on- and off-lattice models equivalent?

      Nava-Sedeño, Josué Manik; Voß-Böhme, Anja; Hatzikirou, Haralampos; Deutsch, Andreas; Peruani, Fernando (2020-07-27)