Cyclone: open-source package for simulation and analysis of finite dynamical systems.

MOTIVATION: While there are software packages that analyze Boolean, ternary, or other multi-state models, none compute the complete state space of function-based models over any finite set. Results: We propose Cyclone, a simple light-weight software package which simulates the complete state space for a finite dynamical system over any finite set. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at https://github.com/discretedynamics/cyclone under the Apache-2.0 license.

SteadyCellPhenotype: a web-based tool for the modeling of biological networks with ternary logic.

SUMMARY: We introduce SteadyCellPhenotype, a browser-based interface for the analysis of ternary biological networks. It includes tools for deterministically finding all steady states of a network, as well as the simulation and visualization of trajectories with publication quality graphics. Simulations allow us to approximate the size of the basin for attractors and deterministic simulations of trajectories nearby specified points allow us to explore the behavior of the system in that neighborhood. AVAILABILITY AND IMPLEMENTATION: https://github.com/knappa/steadycellphenotype MIT License.

Computational Modeling of Macrophage Iron Sequestration during Host Defense against Aspergillus.

Iron is essential to the virulence of Aspergillus species, and restricting iron availability is a critical mechanism of antimicrobial host defense. Macrophages recruited to the site of infection are at the crux of this process, employing multiple intersecting mechanisms to orchestrate iron sequestration from pathogens. To gain an integrated understanding of how this is achieved in aspergillosis, we generated a transcriptomic time series of the response of human monocyte-derived macrophages to Aspergillus and used this and the available literature to construct a mechanistic computational model of iron handling of macrophages during this infection. We found an overwhelming macrophage response beginning 2 to 4 h after exposure to the fungus, which included upregulated transcription of iron import proteins transferrin receptor-1, divalent metal transporter-1, and ZIP family transporters, and downregulated transcription of the iron exporter ferroportin. The computational model, based on a discrete dynamical systems framework, consisted of 21 3-state nodes, and was validated with additional experimental data that were not used in model generation. The model accurately captures the steady state and the trajectories of most of the quantitatively measured nodes. In the experimental data, we surprisingly found that transferrin receptor-1 upregulation preceded the induction of inflammatory cytokines, a feature that deviated from model predictions. Model simulations suggested that direct induction of transferrin receptor-1 (TfR1) after fungal recognition, independent of the iron regulatory protein-labile iron pool (IRP-LIP) system, explains this finding. We anticipate that this model will contribute to a quantitative understanding of iron regulation as a fundamental host defense mechanism during aspergillosis. IMPORTANCE Invasive pulmonary aspergillosis is a major cause of death among immunosuppressed individuals despite the best available therapy. Depriving the pathogen of iron is an essential component of host defense in this infection, but the mechanisms by which the host achieves this are complex. To understand how recruited macrophages mediate iron deprivation during the infection, we developed and validated a mechanistic computational model that integrates the available information in the field. The insights provided by this approach can help in designing iron modulation therapies as anti-fungal treatments.