IAV_intracellular_model

Matlab scripts for the stochastic simulation of intracellular replication and population level modeling.

IAV Stochastic Simulation Pipeline – Overview

This pipeline simulates the intracellular replication dynamics of Influenza A Virus (IAV) using a stochastic modeling framework based on the Gillespie algorithm with the tau-leaping approximation.

The pipeline is organized into two main MATLAB scripts:

• Central_IAVGillespie_single.m: Runs a single stochastic simulation for a specified MOI and initial condition.
• Central_IAVGillespie_multiple.m: Performs multiple replicate simulations for a range of MOI values or parameters, storing the aggregated outputs for downstream analysis or plotting.

These scripts call a core simulation module (mode_IAV_GillespieTauLeaping.m) that implements the tau-leaping method to efficiently simulate reaction dynamics in a stochastic setting.

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The model structure (reaction network, parameters, and initial conditions) is provided externally via an Excel file (Param_mat.xlsx) with the following required sheets:

1. Stoichiometric matrix: Defines how species counts change per reaction.
2. Reactants matrix: Indicates which species are reactants in each reaction.
3. Rate constants matrix: Contains numeric rate parameters associated with each reaction.
4. Parameter list: Maps parameter names to values for interpretability and use in the simulation.
5. QSSA-eliminated reactions: Lists reactions removed under the Quasi-Steady-State Approximation (QSSA).
6. Virion composition: Specifies the stoichiometry of viral proteins in mature virions.

Note:

• Species-specific degradation reactions are automatically generated internally, but degradation rates must be defined in the parameter list.

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On execution, the scripts prompt the user (or accept input variables) for two key parameters:

• MOI: Multiplicity of Infection – the number of distinct viral variants infecting the cell.
• IniV: Initial number of virions per variant.

The total number of infecting particles is given by MOI × IniV.

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This framework enables the simulation of viral diversity, replication kinetics, and stochastic effects within infected cells under varying initial conditions and parameter settings.

For example applications, see:

• Central_IAVGillespie_single.m → used to generate data for Figure 2B and Figure S1 in Segredo-Otero & Gresham (2025)

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We've uploaded to the OSF proect https://osf.io/f9e6v/ the simulated data that generates the script Central_IAVGillespie_multiple.m, Rangig MOIs from 1 to 20, and 1000 replicates per MOI (simulating 1000 cellulas infections). These simulated data are used by the population level model.