An Introduction to Rule-based Modeling of Immune Receptor Signaling

Cells process external and internal signals through chemical interactions. Cells that constitute the immune system (e.g., antigen presenting cell, T-cell, B-cell, mast cell) can have different functions (e.g., adaptive memory, inflammatory response) depending on the type and number of receptor molecules on the cell surface and the specific intracellular signaling pathways activated by those receptors. Explicitly modeling and simulating kinetic interactions between molecules allows us to pose questions about the dynamics of a signaling network under various conditions. However, the application of chemical kinetics to biochemical signaling systems has been limited by the complexity of the systems under consideration. Rule-based modeling (BioNetGen, Kappa, Simmune, PySB) is an approach to address this complexity. In this chapter, by application to the Fc$\varepsilon$RI receptor system, we will explore the origins of complexity in macromolecular interactions, show how rule-based modeling can be used to address complexity, and demonstrate how to build a model in the BioNetGen framework. Open source BioNetGen software and documentation are available at http://bionetgen.org.Comment: 5 figure

Simplicity of Completion Time Distributions for Common Complex Biochemical Processes

Biochemical processes typically involve huge numbers of individual reversible steps, each with its own dynamical rate constants. For example, kinetic proofreading processes rely upon numerous sequential reactions in order to guarantee the precise construction of specific macromolecules. In this work, we study the transient properties of such systems and fully characterize their first passage (completion) time distributions. In particular, we provide explicit expressions for the mean and the variance of the completion time for a kinetic proofreading process and computational analyses for more complicated biochemical systems. We find that, for a wide range of parameters, as the system size grows, the completion time behavior simplifies: it becomes either deterministic or exponentially distributed, with a very narrow transition between the two regimes. In both regimes, the dynamical complexity of the full system is trivial compared to its apparent structural complexity. Similar simplicity is likely to arise in the dynamics of many complex multi-step biochemical processes. In particular, these findings suggest not only that one may not be able to understand individual elementary reactions from macroscopic observations, but also that such understanding may be unnecessary

A rule-based kinetic model of RNA polymerase II C-terminal domain phosphorylation

The complexity ofmany RNA processing pathways is such that a conventional systemsmodelling approach is inadequate to represent all themolecular species involved. We demonstrate that rule-based modelling permits a detailed model of a complex RNA signalling pathway to be defined. Phosphorylation of the RNApolymerase II (RNAPII)C-terminal domain (CTD; a flexible tail-like extension of the largest subunit) couples pre-messenger RNA capping, splicing and 30 end maturation to transcriptional elongation and termination, and plays a central role in integrating these processes. The phosphorylation states of the serine residues of many heptapeptide repeats of the CTD alter along the coding region of genes as a function of distance from the promoter. From a mechanistic perspective, both the changes in phosphorylation and the location atwhich they take place on the genes are a function of the time spent byRNAPII in elongation as this interval provides the opportunity for the kinases and phosphatases to interactwith theCTD.On this basis,we synthesize the available data to create a kinetic model of the action of the known kinases and phosphatases to resolve the phosphorylation pathways and their kinetics.</p

Memory of Germinant Stimuli in Bacterial Spores

Bacterial spores, despite being metabolically dormant, possess the remarkable capacity to detect nutrients and other molecules in their environment through a biochemical sensory apparatus that can trigger spore germination, allowing the return to vegetative growth within minutes of exposure of germinants. We demonstrate here that bacterial spores of multiple species retain memory of transient exposures to germinant stimuli that can result in altered responses to subsequent exposure. The magnitude and decay of these memory effects depend on the pulse duration as well as on the separation time, incubation temperature, and pH values between the pulses. Spores of Bacillus species germinate in response to nutrients that interact with germinant receptors (GRs) in the spore’s inner membrane, with different nutrient types acting on different receptors. In our experiments, B. subtilis spores display memory when the first and second germinant pulses target different receptors, suggesting that some components of spore memory are downstream of GRs. Furthermore, nonnutrient germinants, which do not require GRs, exhibit memory either alone or in combination with nutrient germinants, and memory of nonnutrient stimulation is found to be more persistent than that induced by GR-dependent stimuli. Spores of B. cereus and Clostridium difficile also exhibit germination memory, suggesting that memory may be a general property of bacterial spores. These observations along with experiments involving strains with mutations in various germination proteins suggest a model in which memory is stored primarily in the metastable states of SpoVA proteins, which comprise a channel for release of dipicolinic acid, a major early event in spore germination