A Metapopulation Model Of Granuloma Formation In The Lung During Infection With Mycobacterium Tuberculosis

Ganguli, Suman; Gammack, David; Kirschner, Denise E.

doi:10.3934/mbe.2005.2.535

Cited by 21 publications

(8 citation statements)

References 31 publications

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“…The models predict that disease reactivation occurs when the granulomas no longer effectively control extracellular bacterial growth; when intracellular management predominates, local tissue damage and bacterial dissemination are reduced. The models also predict that the signalling that occurs between host cells and their intracellular bacteria facilitate granuloma maintenance, and that the slow mycobacterial growth rate favours latency 85,[88][89][90][91]93 . Thus, M. tuberculosis has evolved slow growth rates and the ability to survive inside macrophages, while hosts who minimize tissue damage from potentially over-zealous immune responses have been selected 75,83,85 .…”

Section: A General Model Of Microbial Persistence In Hostsmentioning

confidence: 97%

“…In this environment, host cells and mycobacteria can interact for the host's lifetime 85 , with bacterial replication 86,87 but controlled growth. Mathematical models [88][89][90][91][92][93] of the conditions favouring latency have defined two bacterial subpopulations (intracellular and extracellular) with distinctive growth rates and signals to host cells, and different macrophage-response states and T-cell and cytokine contributions 92 . An equilibrium maintains low bacterial levels and controls tissue damage, based on macrophage activation and control 83,84,93 .…”

Section: A General Model Of Microbial Persistence In Hostsmentioning

confidence: 99%

See 1 more Smart Citation

The equilibria that allow bacterial persistence in human hosts

Blaser

Kirschner

2007

Nature

207

172

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We propose that microbes that have developed persistent relationships with human hosts have evolved cross-signalling mechanisms that permit homeostasis that conforms to Nash equilibria and, more specifically, to evolutionarily stable strategies. This implies that a group of highly diverse organisms has evolved within the changing contexts of variation in effective human population size and lifespan, shaping the equilibria achieved, and creating relationships resembling climax communities. We propose that such ecosystems contain nested communities in which equilibrium at one level contributes to homeostasis at another. The model can aid prediction of equilibrium states in the context of further change: widespread immunodeficiency, changing population densities, or extinctions.

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Section: A General Model Of Microbial Persistence In Hostsmentioning

confidence: 97%

Section: A General Model Of Microbial Persistence In Hostsmentioning

confidence: 99%

The equilibria that allow bacterial persistence in human hosts

Blaser

Kirschner

2007

Nature

207

172

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show abstract

“…For example, the model by Segovia-Juarez et al showed that a slower bacterial growth rate within infected cells is worse for the host [141]. Bacterial replication and decay rates as well as other model components identified distinct pathological states including early clearance, granuloma formation, and persistent infection [68,140,150,152,160,165,166,172,179,188].…”

Section: General Results and Conclusion From Modeling Tuberculosis And Anthraxmentioning

confidence: 99%

Review of Mathematical Modeling of the Inflammatory Response in Lung Infections and Injuries

Minucci

Heise

Reynolds

2020

Front. Appl. Math. Stat.

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Lung inflammation may occur due to viral and bacterial infections, structural damage, or inhalation of dangerous particles. These injuries may be quickly resolved by the immune system, treated effectively through various interventions, become chronic problems, or lead to death. Mathematical modeling has been used to understand immune system dynamics during a number of pulmonary infections and injuries, identify key mechanisms, and provide important insights into new treatments. In this review, we present long-accepted modeling techniques and novel strategies for simulating various lung injuries to highlight the usefulness of mathematical modeling in addressing these life-threatening conditions. Advances in computational power have allowed for a diverse collection of models ranging from those using only Boolean operatorsto complex hybrid multi-scale models, each specifically designed to address relevant biological questions. To illustrate the findings from these mathematical approaches, we present detailed examples, summarize results, and consider future directions from modeling influenza, pneumonia, COVID-19, tuberculosis, anthrax, and other non-infectious injuries.

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“…The first spatial model of granulomas developed was an agent-based model (ABM) (64, 69); formation of the granuloma was an emergent behavior in the model. PDE models (58, 68, 71) and other formulations such as meta-population models (70) were also used and compared (146). One model examined early events in mice, including neutrophils and the role they play in granuloma formation (66), while others examined the role of the bacterial burst size on granulomas (67).…”

Section: Overview Of In-host Computational Modelsmentioning

confidence: 99%

A review of computational and mathematical modeling contributions to our understanding of Mycobacterium tuberculosis within-host infection and treatment

Kirschner

Pienaar

Marino

et al. 2017

Current Opinion in Systems Biology

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Tuberculosis (TB) is an ancient and deadly disease characterized by complex host-pathogen dynamics playing out over multiple time and length scales and physiological compartments. Computational modeling can be used to integrate various types of experimental data and suggest new hypotheses, mechanisms, and therapeutic approaches to TB. Here, we offer a first-time comprehensive review of work on within-host TB models that describe the immune response of the host to infection, including the formation of lung granulomas. The models include systems of ordinary and partial differential equations and agent-based models as well as hybrid and multi-scale models that are combinations of these. Many aspects of M. tuberculosis infection, including host dynamics in the lung (typical site of infection for TB), granuloma formation, roles of cytokine and chemokine dynamics, and bacterial nutrient availability have been explored. Finally, we survey applications of these within-host models to TB therapy and prevention and suggest future directions to impact this global disease.

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A Metapopulation Model Of Granuloma Formation In The Lung During Infection With Mycobacterium Tuberculosis

Cited by 21 publications

References 31 publications

The equilibria that allow bacterial persistence in human hosts

The equilibria that allow bacterial persistence in human hosts

Review of Mathematical Modeling of the Inflammatory Response in Lung Infections and Injuries

A review of computational and mathematical modeling contributions to our understanding of Mycobacterium tuberculosis within-host infection and treatment

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