Modeling complex cellular systems: from differential equations to constraint-based models

In the beginning of the 20th century, scientists realized the necessity of purifying enzymes to unravel their mechanistic nature. A century and tremendous progresses in the natural sciences later, molecular and systems biology became fundamental pillars of modern biology. Moreover, natural scientists developed an increasing interest in theoretical models. In the first part of my thesis, I present my contribution to the field of studying the dynamics of biological phenomena. I present fundamental issues arising, when neglecting substrate inhibition in kinetic modeling. Furthermore, I describe a model that considers experimental data to simulate the transition of normal proliferating into cellular senescent cells. Since large-scaled models are more comprehensive, they commonly prohibit a mechanistic modeling approach. In order to analyze such models, nevertheless, constraint-based methods proved to be suitable tools. In the second part of my thesis, I contribute three studies to constraint-based modeling. I describe the established concept of elementary flux modes, which resemble non-decomposable and theoretically feasible pathways of metabolic networks. Subsequently, I present the analysis of the nitrogen metabolism network of Chlamydomonas reinhardtii with respect to circadian regulation, which gives rise to about three million elementary flux modes. In the last study, I present a comprehensive work on metabolic costs of amino acid and protein production in Escherichia coli. These costs were manually calculated as well as based on a flux balance analysis of an E. coli genome-scale metabolic model. Both approaches, either dynamic or constraint-based modeling, proved to be suitable strategies to describe biological processes at different levels. Whereas dynamic modeling allowed for a precise description of the temporal behavior of biological species, constraint-based modeling enabled studies, where the complexity of the investigated phenomena prohibits kinetic modeling

Predicting the Physiological Role of Circadian Metabolic Regulation in the Green Alga Chlamydomonas reinhardtii

Although the number of reconstructed metabolic networks is steadily growing, experimental data integration into these networks is still challenging. Based on elementary flux mode analysis, we combine sequence information with metabolic pathway analysis and include, as a novel aspect, circadian regulation. While minimizing the need of assumptions, we are able to predict changes in the metabolic state and can hypothesise on the physiological role of circadian control in nitrogen metabolism of the green alga Chlamydomonas reinhardtii

In Silico Approaches and the Role of Ontologies in Aging Research

The 2013 Rostock Symposium on Systems Biology and Bioinformatics in Aging Research was again dedicated to dissecting the aging process using in silico means. A particular focus was on ontologies, as these are a key technology to systematically integrate heterogeneous information about the aging process. Related topics were databases and data integration. Other talks tackled modeling issues and applications, the latter including talks focussed on marker development and cellular stress as well as on diseases, in particular on diseases of kidney and skin

COVID-19 patients share common, corticosteroid-independent features of impaired host immunity to pathogenic molds

Patients suffering from coronavirus disease-2019 (COVID-19) are susceptible to deadly secondary fungal infections such as COVID-19-associated pulmonary aspergillosis and COVID-19-associated mucormycosis. Despite this clinical observation, direct experimental evidence for severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2)-driven alterations of antifungal immunity is scarce. Using an ex-vivo whole blood stimulation assay, we challenged blood from twelve COVID-19 patients with Aspergillus fumigatus and Rhizopus arrhizus antigens and studied the expression of activation, maturation, and exhaustion markers, as well as cytokine secretion. Compared to healthy controls, T-helper cells from COVID-19 patients displayed increased expression levels of the exhaustion marker PD-1 and weakened A. fumigatus - and R. arrhizus -induced activation. While baseline secretion of proinflammatory cytokines was massively elevated, whole blood from COVID-19 patients elicited diminished release of T-cellular (e.g., IFN-γ, IL-2) and innate immune cell-derived (e.g., CXCL9, CXCL10) cytokines in response to A. fumigatus and R. arrhizus antigens. Additionally, samples from COVID-19 patients showed deficient granulocyte activation by mold antigens and reduced fungal killing capacity of neutrophils. These features of weakened anti-mold immune responses were largely decoupled from COVID-19 severity, the time elapsed since diagnosis of COVID-19, and recent corticosteroid uptake, suggesting that impaired anti-mold defense is a common denominator of the underlying SARS-CoV-2 infection. Taken together, these results expand our understanding of the immune predisposition to post-viral mold infections and could inform future studies of immunotherapeutic strategies to prevent and treat fungal superinfections in COVID-19 patients

The PI3K and MAPK/p38 pathways control stress granule assembly in a hierarchical manner

All cells and organisms exhibit stress-coping mechanisms to ensure survival. Cytoplasmic protein-RNA assemblies termed stress granules are increasingly recognized to promote cellular survival under stress. Thus, they might represent tumor vulnerabilities that are currently poorly explored. The translation-inhibitory eIF2α kinases are established as main drivers of stress granule assembly. Using a systems approach, we identify the translation enhancers PI3K and MAPK/p38 as pro-stress-granule-kinases. They act through the metabolic master regulator mammalian target of rapamycin complex 1 (mTORC1) to promote stress granule assembly. When highly active, PI3K is the main driver of stress granules; however, the impact of p38 becomes apparent as PI3K activity declines. PI3K and p38 thus act in a hierarchical manner to drive mTORC1 activity and stress granule assembly. Of note, this signaling hierarchy is also present in human breast cancer tissue. Importantly, only the recognition of the PI3K-p38 hierarchy under stress enabled the discovery of p38’s role in stress granule formation. In summary, we assign a new pro-survival function to the key oncogenic kinases PI3K and p38, as they hierarchically promote stress granule formation

IL4I1 Is a Metabolic Immune Checkpoint that Activates the AHR and Promotes Tumor Progression

Immune checkpoint blockade therapy induces the AHR-activating enzyme IL4I1, which promotes tumor progression, through its effects on tumor cell motility and adaptive immunity

Quantitative model of cell cycle arrest and cellular senescence in primary human fibroblasts.

Primary human fibroblasts in tissue culture undergo a limited number of cell divisions before entering a non-replicative "senescent" state. At early population doublings (PD), fibroblasts are proliferation-competent displaying exponential growth. During further cell passaging, an increasing number of cells become cell cycle arrested and finally senescent. This transition from proliferating to senescent cells is driven by a number of endogenous and exogenous stress factors. Here, we have developed a new quantitative model for the stepwise transition from proliferating human fibroblasts (P) via reversibly cell cycle arrested (C) to irreversibly arrested senescent cells (S). In this model, the transition from P to C and to S is driven by a stress function γ and a cellular stress response function F which describes the time-delayed cellular response to experimentally induced irradiation stress. The application of this model based on senescence marker quantification at the single-cell level allowed to discriminate between the cellular states P, C, and S and delivers the transition rates between the P, C and S states for different human fibroblast cell types. Model-derived quantification unexpectedly revealed significant differences in the stress response of different fibroblast cell lines. Evaluating marker specificity, we found that SA-β-Gal is a good quantitative marker for cellular senescence in WI-38 and BJ cells, however much less so in MRC-5 cells. Furthermore we found that WI-38 cells are more sensitive to stress than BJ and MRC-5 cells. Thus, the explicit separation of stress induction from the cellular stress response, and the differentiation between three cellular states P, C and S allows for the first time to quantitatively assess the response of primary human fibroblasts towards endogenous and exogenous stress during cellular ageing

Additional file 7 of SBMLmod: a Python-based web application and web service for efficient data integration and model simulation

S7 — TCGA sample IDs. List of TCGA sample IDs used to calculate the results presented in Fig. 2 c and d. (TXT 76 kb