STI-GMaS: an open-source environment for simulation of sexually-transmitted infections

Abstract

Background: Sexually-transmitted pathogens often have severe reproductive health implications if treatment is delayed or absent, especially in females. The complex processes of disease progression, namely replication and ascension of the infection through the genital tract, span both extracellular and intracellular physiological scales, and in females can vary over the distinct phases of the menstrual cycle. The complexity of these processes, coupled with the common impossibility of obtaining comprehensive and sequential clinical data from individual human patients, makes mathematical and computational modelling valuable tools in developing our understanding of the infection, with a view to identifying new interventions. While many within-host models of sexually-transmitted infections (STIs) are available in existing literature, these models are difficult to deploy in clinical/experimental settings since simulations often require complex computational approaches.

Results: We present STI-GMaS (Sexually-Transmitted Infections - Graphical Modelling and Simulation), an environment for simulation of STI models, with a view to stimulating the uptake of these models within the laboratory or clinic. The software currently focuses upon the representative case-study of Chlamydia trachomatis, the most common sexually-transmitted bacterial pathogen of humans. Here, we demonstrate the use of a hybrid PDE-cellular automata model for simulation of a hypothetical Chlamydia vaccination, demonstrating the effect of a vaccine-induced antibody in preventing the infection from ascending to above the cervix. This example illustrates the ease with which existing models can be adapted to describe new studies, and its careful parameterisation within STI-GMaS facilitates future tuning to experimental data as they arise.

Conclusions: STI-GMaS represents the first software designed explicitly for in-silico simulation of STI models by non-theoreticians, thus presenting a novel route to bridging the gap between computational and clinical/experimental disciplines. With the propensity for model reuse and extension, there is much scope within STI-GMaS to allow clinical and experimental studies to inform model inputs and drive future model development. Many of the modelling paradigms and software design principles deployed to date transfer readily to other STIs, both bacterial and viral; forthcoming releases of STI-GMaS will extend the software to incorporate a more diverse range of infections.

Figure 1

The C. trachomatis replication cycle. Initially a healthy epithelial cell is in the neighbourhood of extracellular chlamydiae. The cell becomes infected by a single EB, which adheres to the surface of the cell (illustrated at 0 hours). The EB is quickly engulfed by the cell and converts to the RB form within an inclusion (illustrated at 1–12 hours). RBs multiply approximately 500-fold by binary fission, and eventually convert back to the infectious EB form. The cell ultimately lyses (48–72 hours), releasing these infectious EBs.

Figure 2

The STI-GMaS workflow. A user-friendly graphical user interface (written in Java) enables easy model selection and parameterisation, and allows simulation of underlying models to be initiated using CHASTE. Results are passed to one of two visualisation tools, selected dependent upon whether the model contains spatial information.

Figure 3

A typical STI-GMaS model window. Each incorporated model is accessed through a control panel, which provides a citation and brief description of the model, and allows for setting of each of the model’s parameters prior to running of a new simulation. Parameter nomenclature is consistent with the model’s original publication; hovering over any parameter will display the meaning of that parameter as hover help.

Figure 4

Schema of the model of Mallet (2009). Illustrated are the infection and clearance events incorporated in the model of [2], showing parameterisation in the nomenclature of the model’s original publication. Cell infection occurs as a function of local extracellular particle number (C), while clearance events are governed by a local infection signal (I), computed as a historic measure of the number of neighbouring cells to have been infected. Each event occurs with likelihood given by (1), for parameters and inputs shown in red; associated delays are given in green. For a full list of parameter values, see [2].

Figure 5

Ascension of C. trachomatis in the cervix in the absence of vaccination. Results illustrated are the number of extracellular chlamydiae at each spatial location at (a) 0 hours, (b) 24 hours, (c) 48 hours, (d) 72 hours, (e) 96 hours, (f) 120 hours, (g) 144 hours, (h) 372 hours, (i) 384 hours and (j) 408 hours. The infection quickly spreads through the cervix and beyond, with reinfections occurring periodically in the lower cervix due to lysis of infected epithelial cells.

Figure 6

Progression of C. trachomatis infection through the cervix under a moderate vaccine-induced antibody level. Results illustrated are the number of extracellular chlamydiae at each spatial location at (a) 0 hours, (b) 24 hours, (c) 48 hours, (d) 72 hours and (e) 144 hours. While the majority of the extracellular chlamydiae are removed due to the antibody, some chlamydiae do ascend to above the cervix.

Figure 7

Evolution of C. trachomatis infection in the cervix under a high vaccine-induced antibody level. Results illustrated are the number of extracellular chlamydiae at each spatial location at (a) 0 hours, (b) 20 hours, (c) 40 hours and (d) 60 hours. The infection is quickly removed by the immune system, and does not ascend to above the cervix.