The Role of Dimensionality in Understanding Granuloma Formation.

Jennifer Linderman,Simeone Marino,Paul Wolberg,Caitlin Hult,Denise Kirschner

doi:10.3390/computation6040058

Jennifer Linderman, Simeone Marino + Show 3 more

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https://doi.org/10.3390/computation6040058

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Abstract

Within the first 2–3 months of a Mycobacterium tuberculosis (Mtb) infection, 2–4 mm spherical structures called granulomas develop in the lungs of the infected hosts. These are the hallmark of tuberculosis (TB) infection in humans and non-human primates. A cascade of immunological events occurs in the first 3 months of granuloma formation that likely shapes the outcome of the infection. Understanding the main mechanisms driving granuloma development and function is key to generating treatments and vaccines. In vitro, in vivo, and in silico studies have been performed in the past decades to address the complexity of granuloma dynamics. This study builds on our previous 2D spatio-temporal hybrid computational model of granuloma formation in TB (GranSim) and presents for the first time a more realistic 3D implementation. We use uncertainty and sensitivity analysis techniques to calibrate the new 3D resolution to non-human primate (NHP) experimental data on bacterial levels per granuloma during the first 100 days post infection. Due to the large computational cost associated with running a 3D agent-based model, our major goal is to assess to what extent 2D and 3D simulations differ in predictions for TB granulomas and what can be learned in the context of 3D that is missed in 2D. Our findings suggest that in terms of major mechanisms driving bacterial burden, 2D and 3D models return very similar results. For example, Mtb growth rates and molecular regulation mechanisms are very important both in 2D and 3D, as are cellular movement and modulation of cell recruitment. The main difference we found was that the 3D model is less affected by crowding when cellular recruitment and movement of cells are increased. Overall, we conclude that the use of a 2D resolution in GranSim is warranted when large scale pilot runs are to be performed and if the goal is to determine major mechanisms driving infection outcome (e.g., bacterial load). To comprehensively compare the roles of model dimensionality, further tests and experimental data will be needed to expand our conclusions to molecular scale dynamics and multi-scale resolutions.

Highlights

Tuberculosis (TB) is an ancient disease that has re-emerged as the number one cause of death due to infection in the world [1]
We show how the biology is transformed into computational and mathematical constructs that recapitulate those features and allow us to postulate on the mechanisms driving granuloma formation and development
We will highlight many 3D visualization tools and the insights they generate into granuloma formation and development

Summary

Introduction

Tuberculosis (TB) is an ancient disease that has re-emerged as the number one cause of death due to infection in the world [1]. The hallmark of infection with the bacterium that causes TB, Mycobacterium tuberculosis (Mtb), is the different disease outcomes—namely, clearance, clinical latency, and active disease—are not known. The hallmark of infection with the bacterium that causes TB, Mycobacterium tuberculosis (Mtb), is the bacteria, despite failing to fullythat clear it. Adding further complication that each contain human the suffers development often of lung granulomas serve to immunologically restrain andisphysically the development of multiple granulomas, and each granuloma has been shown to have a unique bacteria, despite often failing to fully clear it. As granulomas serve as the siteand of infection dynamics, successful of those the development of multiple granulomas, each granuloma has been shownidentification to have a unique factors that contribute to whether can or dynamics, cannot control infection is key to eventual trajectory [2]. As granulomas serveaasgranuloma the site of infection successful identification of those factors that contribute whether a granuloma can or cannot control infection is key to eventual elimination of this diseasetoworldwide

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