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Modeling the immune rheostat of macrophages in the lung in response to infection
Judy Day1, Avner Friedman, Larry S Schlesinger
1Mathematical Biosciences Institute, Ohio State University, Columbus, OH 43210, USA.
Abstract:
In the lung, alternatively activated macrophages (AAM) form the first line of defense against microbial infection. Due to the highly regulated nature of AAM, the lung can be considered as an immunosuppressive organ for respiratory pathogens. However, as infection progresses in the lung, another population of macrophages, known as classically activated macrophages (CAM) enters; these cells are typically activated by IFN-gamma. CAM are far more effective than AAM in clearing the microbial load, producing proinflammatory cytokines and antimicrobial defense mechanisms necessary to mount an adequate immune response. Here, we are concerned with determining the first time when the population of CAM becomes more dominant than the population of AAM. This proposed "switching time" is explored in the context of Mycobacterium tuberculosis (MTb) infection. We have developed a mathematical model that describes the interactions among cells, bacteria, and cytokines involved in the activation of both AAM and CAM. The model, based on a system of differential equations, represents a useful tool to analyze strategies for reducing the switching time, and to generate hypotheses for experimental testing.
Insights
This study models macrophage dynamics during Mycobacterium tuberculosis infection. It identifies a "switching time" when classically activated macrophages (CAM) dominate over alternatively activated macrophages (AAM) for effective pathogen clearance.
Area of Science:
- Immunology
- Infectious Disease
- Mathematical Biology
Background:
- Alternatively activated macrophages (AAM) are the primary defense in the lung, creating an immunosuppressive environment for pathogens.
- Classically activated macrophages (CAM), induced by IFN-gamma, are crucial for controlling microbial infections by producing proinflammatory cytokines.
- The transition point where CAM populations exceed AAM populations is critical for effective immune response during lung infections.
Purpose of the Study:
- To determine the "switching time" when CAM populations become dominant over AAM during Mycobacterium tuberculosis (MTB) infection.
- To develop a mathematical model simulating the interactions between macrophages, bacteria, and cytokines in the lung.
- To provide a framework for analyzing strategies to shorten this critical switching time.
Main Methods:
- Development of a mathematical model using a system of differential equations.
- Modeling the interactions among immune cells (AAM, CAM), Mycobacterium tuberculosis (MTB), and cytokines.
- Analysis of the model to predict the timing of macrophage population shifts.
Main Results:
- The study establishes a framework to quantify the "switching time" in MTB infection.
- The mathematical model provides insights into the dynamics of AAM and CAM populations.
- Identified potential for the model to guide experimental testing and therapeutic strategies.
Conclusions:
- The timing of macrophage population shifts is a key factor in controlling Mycobacterium tuberculosis infection.
- Mathematical modeling offers a valuable approach to understanding complex immune responses in the lung.
- Further research can utilize this model to explore interventions aimed at optimizing the immune response to respiratory pathogens.
