surfinFBA

surfinFBA accelerates dynamic flux balance analysis (dFBA) of microbial communities by selecting bases for internal flux spaces to permit forward simulation via linear systems and reduce the frequency of full linear constrained optimization solves.

Key Features:

• Basis selection for internal fluxes: Selects a basis for the space of internal fluxes for each microbe to enable forward simulation by solving linear equations instead of re-solving the full optimization at most time steps.
• Feasibility and degeneracy management: Monitors feasibility within the original optimization constraints and detects degenerate feasible states, invoking a related optimization to select an appropriate basis when required.
• Efficiency gains: Replaces most optimization solves with inexpensive linear solves, yielding reported speed-ups of approximately 85% per organism in an eight-species community benchmark.
• Mathematical foundation: Represents the system as an ordinary differential equation (ODE) over intervals where a chosen basis remains valid, with solutions remaining valid until a re-optimization condition arises.

Scientific Applications:

• Dynamic metabolic modeling: Enables efficient dFBA simulations of interacting microbial species over time.
• Systems biology: Facilitates system-level studies of metabolic dynamics and interspecies interactions.
• Synthetic biology: Supports design and analysis of engineered microbial communities and metabolic interventions.
• Ecological modeling: Allows simulation of community-scale ecological interactions mediated by metabolism.
• Large-scale community simulations: Makes feasible exploration of larger and more intricate community models that are computationally prohibitive with standard dFBA.

Methodology:

Selects a basis for each microbe's internal flux space, advances the simulation by solving linear systems (treating dynamics as ODEs over basis-valid intervals), monitors feasibility and degeneracy against the original linear constrained optimization, and solves related optimization problems to update bases when necessary.