ASPASIA: A toolkit for evaluating the effects of biological interventions on SBML model behaviour

Area of Science:

• Computational Biology
• Systems Biology
• Immunology

Background:

• Computational models are crucial for understanding complex systems, but calibrating them for post-intervention analysis is challenging.
• Existing software tools lack robust methods for assessing intervention impacts on Systems Biology Markup Language (SBML) models, especially when interventions occur after a defined time point.

Purpose of the Study:

• To introduce ASPASIA (Automated Simulation Parameter Alteration and SensItivity Analysis), an open-source Java toolkit designed to address deficiencies in analyzing intervention effects on SBML models.
• To enable the generation and modification of SBML models using solver output, allowing interventions at steady states and facilitating sensitivity analysis.

Main Methods:

• ASPASIA generates and modifies SBML models, using solver output as initial parameters for interventions at steady states.
• The toolkit employs local and global sensitivity analysis to perturb parameter values, creating multiple SBML models to reveal intervention sensitivity.
• ASPASIA was used with an SBML model of Th17-cell polarization to investigate T-cell plasticity.

Main Results:

• ASPASIA successfully generated novel hypotheses regarding Th17-cell plasticity control mechanisms.
• The analysis predicted that promoting T-bet is sufficient to drive Th17 cells towards an IFN-γ-producing phenotype, overriding RORγt inhibition.
• The study demonstrates the tool's capability to predict intervention effects on SBML-encoded models.

Conclusions:

• ASPASIA provides a valuable solution for analyzing intervention impacts in SBML models, particularly for time-dependent interventions.
• The tool facilitates hypothesis generation and mechanistic understanding, as exemplified by the Th17-cell plasticity study.
• ASPASIA is a versatile, open-source resource applicable to a wide range of SBML models for predicting intervention outcomes.