Jetse Scholma

Modeling Biological Pathway Dynamics With Timed Automata

Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

Biological networks 101: computational modeling for molecular biologists

Computational modeling of biological networks permits the comprehensive analysis of cells and tissues to define molecular phenotypes and novel hypotheses. Although a large number of software tools have been developed, the versatility of these tools is limited by mathematical complexities that prevent their broad adoption and effective use by molecular biologists. This study clarifies the basic aspects of molecular modeling, how to convert data into useful input, as well as the number of time points and molecular parameters that should be considered for molecular regulatory models with both explanatory and predictive potential. We illustrate the necessary experimental preconditions for converting data into a computational model of network dynamics. This model requires neither a thorough background in mathematics nor precise data on intracellular concentrations, binding affinities or reaction kinetics. Finally, we show how an interactive model of crosstalk between signal transduction pathways in primary human articular chondrocytes allows insight into processes that regulate gene expression.

Modelling biological pathway dynamics with Timed Automata

When analysing complex interaction networks occurring in biological cells, a biologist needs computational support in order to understand the effects of signalling molecules (e.g. growth factors, drugs). ANIMO (Analysis of Networks with Interactive MOdelling) is a tool that allows the user to create and explore executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analysed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signalling networks. This enforces precision and uniformity in the definition of signalling pathways, contributing to the integration of signalling event models into complex, crosstalk-driven networks. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic cell behaviour. A user friendly interface makes the use of Timed Automata completely transparent to the biologist, while keeping the expressive power intact. This allows to define relatively simple, yet faithful models of complex biological interactions. The resulting timed behaviour is displayed graphically, allowing for an intuitive and interactive modelling experience.

Modelling with ANIMO: between fuzzy logic and differential equations

BackgroundComputational support is essential in order to reason on the dynamics of biological systems. We have developed the software tool ANIMO (Analysis of Networks with Interactive MOdeling) to provide such computational support and allow insight into the complex networks of signaling events occurring in living cells. ANIMO makes use of timed automata as an underlying model, thereby enabling analysis techniques from computer science like model checking. Biology experts are able to use ANIMO via a user interface specifically tailored for biological applications. In this paper we compare the use of ANIMO with some established formalisms on two case studies.ResultsANIMO is a powerful and user-friendly tool that can compete with existing continuous and discrete paradigms. We show this by presenting ANIMO models for two case studies: Drosophila melanogaster circadian clock, and signal transduction events downstream of TNF α and EGF in HT-29 human colon carcinoma cells. The models were originally developed with ODEs and fuzzy logic, respectively.ConclusionsTwo biological case studies that have been modeled with respectively ODE and fuzzy logic models can be conveniently modeled using ANIMO. The ANIMO models require less parameters than ODEs and are more precise than fuzzy logic. For this reason we position the modelling paradigm of ANIMO between ODEs and fuzzy logic.

Improved intra-array and interarray normalization of peptide microarray phosphorylation for phosphorylome and kinome profiling by rational selection of relevant spots

Massive parallel analysis using array technology has become the mainstay for analysis of genomes and transcriptomes. Analogously, the predominance of phosphorylation as a regulator of cellular metabolism has fostered the development of peptide arrays of kinase consensus substrates that allow the charting of cellular phosphorylation events (often called kinome profiling). However, whereas the bioinformatical framework for expression array analysis is well-developed, no advanced analysis tools are yet available for kinome profiling. Especially intra-array and interarray normalization of peptide array phosphorylation remain problematic, due to the absence of “housekeeping” kinases and the obvious fallacy of the assumption that different experimental conditions should exhibit equal amounts of kinase activity. Here we describe the development of analysis tools that reliably quantify phosphorylation of peptide arrays and that allow normalization of the signals obtained. We provide a method for intraslide gradient correction and spot quality control. We describe a novel interarray normalization procedure, named repetitive signal enhancement, RSE, which provides a mathematical approach to limit the false negative results occuring with the use of other normalization procedures. Using in silico and biological experiments we show that employing such protocols yields superior insight into cellular physiology as compared to classical analysis tools for kinome profiling.

ECHO: the executable chondrocyte

Introduction: Decellularized engineered extracellular matrices (ECM) are used in a variety of regenerative medicine applications. Existing decellularization strategies rely on cell lysis and generally result in a variable but significant impairment of the ECM structure/composition. As an alternative, we aimed at activating the apoptotic pathway in order to decellularize engineered matrices while preserving their osteo-inductive properties [1]. Materials and methods: We generated a death-inducible, immortalized human Mesenchymal Stromal Cell (hMSC) line [2]. Cells were seeded on ceramic scaffolds and cultured for 4 weeks in osteogenic medium in a 3D perfusion bioreactor system (U-cup, Cellec). The ECM was decellularized by direct supply of the apoptotic inducer in the 3D culture system. Grafts were implanted in a rat cranial defect model to assess their regenerative potential after 12 weeks. Results: Cells were successfully seeded and differentiated, leading to deposition of a dense ECM during 3D culture. The apoptosis induction allowed for efficient decellularization while preserving the secreted matrix. These “apoptized” cell-free ECM coated constructs induced superior bone regeneration than control materials (Fig. 2). Areas of de novo bone formation not connected with surrounding bone suggest osteoinductive properties of the grafts.

Kinome Profiling of Regulatory T Cells: A Closer Look into a Complex Intracellular Network

Regulatory T cells (Treg) are essential for T cell homeostasis and maintenance of peripheral tolerance. They prevent activation of auto-reactive T effector cells (Teff) in the context of autoimmunity and allergy. Otherwise, Treg also inhibit effective immune responses against tumors. Besides a number of Treg-associated molecules such as Foxp3, CTLA-4 or GARP, known to play critical roles in Treg differentiation, activation and function, the involvement of additional regulatory elements is suggested. Herein, kinase activities seem to play an important role in Treg fine tuning. Nevertheless, our knowledge regarding the complex intracellular signaling pathways controlling phenotype and function of Treg is still limited and based on single kinase cascades so far. To gain a more comprehensive insight into the pathways determining Treg function we performed kinome profiling using a phosphorylation-based kinome array in human Treg at different activation stages compared to Teff. Here we have determined intriguing quantitative differences in both populations. Resting and activated Treg showed an altered pattern of CD28-dependent kinases as well as of those involved in cell cycle progression. Additionally, significant up-regulation of distinct kinases such as EGFR or CK2 in activated Treg but not in Teff not only resemble data we obtained in previous studies in the murine system but also suggest that those specific molecular activation patterns can be used for definition of the activation and functional state of human Treg. Taken together, detailed investigation of kinome profiles opens the possibility to identify novel molecular mechanisms for a better understanding of Treg biology but also for development of effective immunotherapies against unwanted T cell responses in allergy, autoimmunity and cancer.

ANIMO: a tool for modeling biological pathway dynamics

Introduction: Decellularized engineered extracellular matrices (ECM) are used in a variety of regenerative medicine applications. Existing decellularization strategies rely on cell lysis and generally result in a variable but significant impairment of the ECM structure/composition. As an alternative, we aimed at activating the apoptotic pathway in order to decellularize engineered matrices while preserving their osteo-inductive properties [1]. Materials and methods: We generated a death-inducible, immortalized human Mesenchymal Stromal Cell (hMSC) line [2]. Cells were seeded on ceramic scaffolds and cultured for 4 weeks in osteogenic medium in a 3D perfusion bioreactor system (U-cup, Cellec). The ECM was decellularized by direct supply of the apoptotic inducer in the 3D culture system. Grafts were implanted in a rat cranial defect model to assess their regenerative potential after 12 weeks. Results: Cells were successfully seeded and differentiated, leading to deposition of a dense ECM during 3D culture. The apoptosis induction allowed for efficient decellularization while preserving the secreted matrix. These “apoptized” cell-free ECM coated constructs induced superior bone regeneration than control materials (Fig. 2). Areas of de novo bone formation not connected with surrounding bone suggest osteoinductive properties of the grafts.