Modeling Multivalent Ligand-Receptor Interactions with Steric Constraints on Configurations of Cell-Surface Receptor Aggregates

We use flow cytometry to characterize equilibrium binding of a fluorophore-labeled trivalent model antigen to bivalent IgE-FcεRI complexes on RBL cells. We find that flow cytometric measurements are consistent with an equilibrium model for ligand-receptor binding in which binding sites are assumed to be equivalent and ligand-induced receptor aggregates are assumed to be acyclic. However, this model predicts extensive receptor aggregation at antigen concentrations that yield strong cellular secretory responses, which is inconsistent with the expectation that large receptor aggregates should inhibit such responses. To investigate possible explanations for this discrepancy, we evaluate four rule-based models for interaction of a trivalent ligand with a bivalent cell-surface receptor that relax simplifying assumptions of the equilibrium model. These models are simulated using a rule-based kinetic Monte Carlo approach to investigate the kinetics of ligand-induced receptor aggregation and to study how the kinetics and equilibria of ligand-receptor interaction are affected by steric constraints on receptor aggregate configurations and by the formation of cyclic receptor aggregates. The results suggest that formation of linear chains of cyclic receptor dimers may be important for generating secretory signals. Steric effects that limit receptor aggregation and transient formation of small receptor aggregates may also be important.     

BioNetGen: software for rule-based modeling of signal transduction based on the interactions of molecular domains

BioNetGen allows a user to create a computational model that characterizes the dynamics of a signal transduction system, and that accounts comprehensively and precisely for specified enzymatic activities, potential post-translational modifications and interactions of the domains of signaling molecules. The output defines and parameterizes the network of molecular species that can arise during signaling and provides functions that relate model variables to experimental readouts of interest. Models that can be generated are relevant for rational drug discovery, analysis of proteomic data and mechanistic studies of signal transduction.     

Selected papers from the Fourth Annual q-bio Conference on Cellular Information Processing

This special issue consists of 11 original papers that elaborate on work presented at the Fourth Annual q-bio Conference on Cellular Information Processing, which was held on the campus of St John's College in Santa Fe, New Mexico, USA, 11-14 August 2010. Now in its fourth year, the q-bio conference has changed considerably over time. It is now well established and a major event in systems biology. The 2010 conference saw attendees from all continents (except Antarctica!) sharing novel results and participating in lively discussions at both the oral and poster sessions. The conference was oversubscribed and grew to 27 contributed talks, 16 poster spotlights and 137 contributed posters. We deliberately decreased the number of invited speakers to 21 to leave more space for contributed presentations, and the attendee feedback confirmed that the choice was a success. Although the q-bio conference has grown and matured, it has remained true to the original goal of being an intimate and dynamic event that brings together modeling, theory and quantitative experimentation for the study of cell regulation and information processing. Funded in part by a grant from NIGMS and by DOE funds through the Los Alamos National Laboratory Directed Research and Development program, the conference has continued to exhibit youth and vigor by attracting (and partially supporting) over 100 undergraduate, graduate and postdoctoral researchers. The associated q-bio summer school, which precedes the conference each year, further emphasizes the development of junior scientists and makes q-bio a singular event in its impact on the future of quantitative biology. In addition to an increased international presence, the conference has notably diversified its demographic representation within the USA, including increased participation from the southeastern corner of the country. One big change in the conference this year is our new publication partner, Physical Biology. Although we are very grateful to our previous partner, IET Systems Biology, for their help over the years in publicizing the work presented at the conference, we felt that the changing needs of our participants required that we find a new partner. We are thrilled that Physical Biology is publishing the q-bio proceedings this year. It has been a great collaboration, as evidenced by the high quality of this special issue. What's next for q-bio? We are happy to report that NIGMS has recently extended the q-bio conference grant for the next three years, ensuring strong support for junior researchers who need financial assistance to participate in the event. The conference will retain its emphasis on cellular information processing, but will also build connections to other areas of modern biology and biotechnology, focusing specifically on ecology and evolutionary biology next year. Indeed, to fully understand biological information processing systems, they must be studied in their ecological contexts. We will continue to honor distinguished contributors to the field in our opening banquets; the tradition started with Howard Berg, Bruce Alberts and Michael Savageau in previous years, and continues with Dennis Bray at the upcoming 2011 event. Starting in 2011, the conference will also venture into exploration of the social aspects of science. The future is bright for q-bio! We will see you at the Fifth Annual q-bio Conference on 10-13 August 2011, in Santa Fe, New Mexico, USA and at the Sixth Annual q-bio Conference in early August 2012.     

Dynamics of the nucleated polymerization model of prion replication

The disease process for transmissible spongiform encephalopathies (TSEs), in one way or another, involves the conversion of a predominantly alpha-helical normal host-coded prion protein (PrP(C)) to an abnormally folded (predominantly beta sheet) protease resistant isoform (PrP(Sc)). Several alternative mechanisms have been proposed for this auto-catalytic process. Here the dynamical behavior of one of these models, the nucleated polymerization model, is studied by Monte Carlo discrete-event simulation of the explicit conversion reactions. These simulations demonstrate the characteristic dynamical behavior of this model for prion replication. Using estimates for the reaction rates and concentrations, time courses are estimated for concentration of PrP(Sc), PrP(Sc) aggregates, and PrP(C) as well as size distributions for the aggregates. The implications of these dynamics on protein misfolding cyclic amplification (PMCA) is discussed.