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How Many Parameters Does It Take to Describe Disease Tolerance?

Louie A, Song KH, Hotson A, Thomas Tate A, Schneider DS - PLoS Biol. (2016)

Bottom Line: Using a model experimental system in which we challenged Drosophila melanogaster with the pathogen Listeria monocytogenes, we tested this framework, finding that microbe growth, the immune response, and disease tolerance were all well represented by sigmoid models.Though either the pathogen or host immune response or both together could theoretically be the proximal cause of pathology that killed the flies, we found that the pathogen, but not the immune response, drove damage in this model.With this new understanding of the circuitry controlling disease tolerance, we can now propose better ways of choosing, combining, and developing treatments.

View Article: PubMed Central - PubMed

Affiliation: Department of Microbiology and Immunology, Stanford University, Stanford, California, United States of America.

ABSTRACT
The study of infectious disease has been aided by model organisms, which have helped to elucidate molecular mechanisms and contributed to the development of new treatments; however, the lack of a conceptual framework for unifying findings across models, combined with host variability, has impeded progress and translation. Here, we fill this gap with a simple graphical and mathematical framework to study disease tolerance, the dose response curve relating health to microbe load; this approach helped uncover parameters that were previously overlooked. Using a model experimental system in which we challenged Drosophila melanogaster with the pathogen Listeria monocytogenes, we tested this framework, finding that microbe growth, the immune response, and disease tolerance were all well represented by sigmoid models. As we altered the system by varying host or pathogen genetics, disease tolerance varied, as we would expect if it was indeed governed by parameters controlling the sensitivity of the system (the number of bacteria required to trigger a response) and maximal effect size according to a logistic equation. Though either the pathogen or host immune response or both together could theoretically be the proximal cause of pathology that killed the flies, we found that the pathogen, but not the immune response, drove damage in this model. With this new understanding of the circuitry controlling disease tolerance, we can now propose better ways of choosing, combining, and developing treatments.

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Related in: MedlinePlus

Visualizing infections in individuals, in pure lines and diverse populations.(A) A simple model in which microbes induce an immune response, which in turn limits microbe growth and kills the microbes. Both microbes and immune effectors can cause damage in this model.
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pbio.1002435.g001: Visualizing infections in individuals, in pure lines and diverse populations.(A) A simple model in which microbes induce an immune response, which in turn limits microbe growth and kills the microbes. Both microbes and immune effectors can cause damage in this model.

Mentions: We started by making a graphical model to explain four parameters: microbe load, the immune response, microbe-induced damage, and health (Fig 1). We modeled the immune response so that it could both limit microbe growth and kill microbes. We previously found that Mycobacterium marinum infected flies waste upon infection and predicted that the day they died they would have exhausted their glycogen and fat stores [18,19]. We also found that L. monocytogenes infected flies waste during infection [15]; to explain death, we used these empirical data to imagine that there was a store of “health” that could be depleted by the infection. In our model, both the immune response and the microbes can cause damage, which depletes health and increases the death rate. Immunopathology directly affects health, while microbes secrete damage effectors that impact health.


How Many Parameters Does It Take to Describe Disease Tolerance?

Louie A, Song KH, Hotson A, Thomas Tate A, Schneider DS - PLoS Biol. (2016)

Visualizing infections in individuals, in pure lines and diverse populations.(A) A simple model in which microbes induce an immune response, which in turn limits microbe growth and kills the microbes. Both microbes and immune effectors can cause damage in this model.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4835111&req=5

pbio.1002435.g001: Visualizing infections in individuals, in pure lines and diverse populations.(A) A simple model in which microbes induce an immune response, which in turn limits microbe growth and kills the microbes. Both microbes and immune effectors can cause damage in this model.
Mentions: We started by making a graphical model to explain four parameters: microbe load, the immune response, microbe-induced damage, and health (Fig 1). We modeled the immune response so that it could both limit microbe growth and kill microbes. We previously found that Mycobacterium marinum infected flies waste upon infection and predicted that the day they died they would have exhausted their glycogen and fat stores [18,19]. We also found that L. monocytogenes infected flies waste during infection [15]; to explain death, we used these empirical data to imagine that there was a store of “health” that could be depleted by the infection. In our model, both the immune response and the microbes can cause damage, which depletes health and increases the death rate. Immunopathology directly affects health, while microbes secrete damage effectors that impact health.

Bottom Line: Using a model experimental system in which we challenged Drosophila melanogaster with the pathogen Listeria monocytogenes, we tested this framework, finding that microbe growth, the immune response, and disease tolerance were all well represented by sigmoid models.Though either the pathogen or host immune response or both together could theoretically be the proximal cause of pathology that killed the flies, we found that the pathogen, but not the immune response, drove damage in this model.With this new understanding of the circuitry controlling disease tolerance, we can now propose better ways of choosing, combining, and developing treatments.

View Article: PubMed Central - PubMed

Affiliation: Department of Microbiology and Immunology, Stanford University, Stanford, California, United States of America.

ABSTRACT
The study of infectious disease has been aided by model organisms, which have helped to elucidate molecular mechanisms and contributed to the development of new treatments; however, the lack of a conceptual framework for unifying findings across models, combined with host variability, has impeded progress and translation. Here, we fill this gap with a simple graphical and mathematical framework to study disease tolerance, the dose response curve relating health to microbe load; this approach helped uncover parameters that were previously overlooked. Using a model experimental system in which we challenged Drosophila melanogaster with the pathogen Listeria monocytogenes, we tested this framework, finding that microbe growth, the immune response, and disease tolerance were all well represented by sigmoid models. As we altered the system by varying host or pathogen genetics, disease tolerance varied, as we would expect if it was indeed governed by parameters controlling the sensitivity of the system (the number of bacteria required to trigger a response) and maximal effect size according to a logistic equation. Though either the pathogen or host immune response or both together could theoretically be the proximal cause of pathology that killed the flies, we found that the pathogen, but not the immune response, drove damage in this model. With this new understanding of the circuitry controlling disease tolerance, we can now propose better ways of choosing, combining, and developing treatments.

Show MeSH
Related in: MedlinePlus