Jarrett2015 - Modelling the interaction between immune response, bacterial dynamics and inflammatory damage

Model Identifier
BIOMD0000000920
Short description
Mathematical model of pro- and anti-inflammatory response, inflammation/damage and infection dynamics in BALB/c mouse with Staphylococcal aureus infection.
Format
SBML
(L2V4)
Related Publication
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Modelling the interaction between the host immune response, bacterial dynamics and inflammatory damage in comparison with immunomodulation and vaccination experiments.
- Jarrett AM, Cogan NG, Shirtliff ME
- Mathematical medicine and biology : a journal of the IMA , 9/ 2015 , Volume 32 , Issue 3 , pages: 285-306 , PubMed ID: 24814512
- Department of Mathematics, Florida State University, 1017 Academic Way, Tallahassee, FL 32306, USA ajarrett@math.fsu.edu.
- The immune system is a complex system of chemical and cellular interactions that responds quickly to queues that signal infection and then reverts to a basal level once the challenge is eliminated. Here, we present a general, four-component model of the immune system's response to a Staphylococcal aureus (S. aureus) infection, using ordinary differential equations. To incorporate both the infection and the immune system, we adopt the style of compartmenting the system to include bacterial dynamics, damage and inflammation to the host, and the host response. We incorporate interactions not previously represented including cross-talk between inflammation/damage and the infection and the suppression of the anti-inflammatory pathway in response to inflammation/damage. As a result, the most relevant equilibrium of the system, representing the health state, is an all-positive basal level. The model is able to capture eight different experimental outcomes for mice challenged with intratibial osteomyelitis due to S. aureus, primarily involving immunomodulation and vaccine therapies. For further validation and parameter exploration, we perform a parameter sensitivity analysis which suggests that the model is very stable with respect to variations in parameters, indicates potential immunomodulation strategies and provides a possible explanation for the difference in immune potential for different mouse strains.
Contributors
Submitter of the first revision: Matthew Roberts
Submitter of this revision: Ahmad Zyoud
Modellers: Matthew Roberts, Ahmad Zyoud
Submitter of this revision: Ahmad Zyoud
Modellers: Matthew Roberts, Ahmad Zyoud
Metadata information
is (3 statements)
isDescribedBy (1 statement)
hasTaxon (1 statement)
isVersionOf (1 statement)
hasProperty (3 statements)
BioModels Database
MODEL1803200002
BioModels Database BIOMD0000000920
BioModels Database MODEL1803200002
BioModels Database BIOMD0000000920
BioModels Database MODEL1803200002
isDescribedBy (1 statement)
hasTaxon (1 statement)
isVersionOf (1 statement)
hasProperty (3 statements)
Mathematical Modelling Ontology
Ordinary differential equation model
Experimental Factor Ontology Staphylococcus aureus infection
Experimental Factor Ontology BALB/c
Experimental Factor Ontology Staphylococcus aureus infection
Experimental Factor Ontology BALB/c
Curation status
Curated
Modelling approach(es)
Tags
Connected external resources
Name | Description | Size | Actions |
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Model files |
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Jarrett2015.xml | SBML L2V4 representation of Jarrett2015 - Modelling the interaction between immune response, bacterial dynamics and inflammatory damage_Curated | 49.44 KB | Preview | Download |
Additional files |
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Jarrett2015.cps | COPASI version 4.27 (Build 217) Modelling the interaction between immune response, bacterial dynamics and inflammatory damage_Curated | 80.76 KB | Preview | Download |
Jarrett2015.sedml | sed-ml L1V2_Modelling the interaction between immune response, bacterial dynamics and inflammatory damage_Curated | 3.66 KB | Preview | Download |
Jarrett2015_orignal.xml | SBML L2V4 representation of Jarrett2015 - Modelling the interaction between immune response, bacterial dynamics and inflammatory damage_orignal | 34.39 KB | Preview | Download |
figure.jpg | Curated figure 2. To improve the curated figures, Beta_2 was changed from 0.1 to 0.135_from the orignal | 22.44 KB | Preview | Download |
- Model originally submitted by : Matthew Roberts
- Submitted: May 21, 2018 3:47:53 PM
- Last Modified: Mar 11, 2020 10:16:58 AM
Revisions
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Version: 5
- Submitted on: Mar 11, 2020 10:16:58 AM
- Submitted by: Ahmad Zyoud
- With comment: Automatically added model identifier BIOMD0000000920
-
Version: 3
- Submitted on: May 21, 2018 3:47:53 PM
- Submitted by: Matthew Roberts
- With comment: Uploaded COPASI file and curated figure to facilitate the curation process in the future
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Legends
: Variable used inside SBML models
: Variable used inside SBML models
Species
Species | Initial Concentration/Amount |
---|---|
bacterial infection B Staphylococcus aureus infection |
1.0 item |
anti inflammatory A regulatory T-lymphocyte |
3.0 item |
pro inflammatory P inflammatory response ; Th17 cell ; Th1 cell |
1.0 item |
inflammation I Inflammation |
1.0 item |
Reactions
Reactions | Rate | Parameters |
---|---|---|
=> bacterial_infection__B; inflammation__I, pro_inflammatory__P | BALB_c_Mouse*(((g*(1-bacterial_infection__B/K_B)+alpha_4*inflammation__I)-beta_4*pro_inflammatory__P)*bacterial_infection__B+exp((-1)*gamma*time)) | K_B = 1.0; beta_4 = 5.0; g = 0.9; alpha_4 = 1.5; gamma = 0.01 |
=> anti_inflammatory__A; pro_inflammatory__P, inflammation__I, bacterial_infection__B | BALB_c_Mouse*(alpha_2*pro_inflammatory__P-(beta_2*inflammation__I+mu_2*(1-bacterial_infection__B/K_B))*anti_inflammatory__A) | mu_2 = 0.25; beta_2 = 0.135; K_B = 1.0; alpha_2 = 0.11 |
=> pro_inflammatory__P; inflammation__I, bacterial_infection__B, anti_inflammatory__A | BALB_c_Mouse*((alpha_1*inflammation__I+rho_1*bacterial_infection__B)*(1-pro_inflammatory__P)-(beta_1*anti_inflammatory__A+mu_1*(1-bacterial_infection__B/K_B))*pro_inflammatory__P) | mu_1 = 0.12; K_B = 1.0; alpha_1 = 0.27; beta_1 = 0.01; rho_1 = 0.2 |
=> inflammation__I; pro_inflammatory__P, bacterial_infection__B, anti_inflammatory__A | BALB_c_Mouse*((alpha_3*pro_inflammatory__P+rho_2*bacterial_infection__B)-(beta_3*anti_inflammatory__A+mu_3)*inflammation__I) | beta_3 = 2.0; rho_2 = 0.45; alpha_3 = 1.05; mu_3 = 0.0174 |
Curator's comment:
(added: 11 Mar 2020, 10:16:03, updated: 11 Mar 2020, 10:16:03)
(added: 11 Mar 2020, 10:16:03, updated: 11 Mar 2020, 10:16:03)
nothing has been changed regarding the parameters and the equations specified in the paper. Figure 2 has been reproduced exactly as it has been mentioned in the paper.