Trends in mathematical modeling of host–pathogen interactions

Pathogenic microorganisms entail enormous problems for humans, livestock, and crop plants. A better understanding of the different infection strategies of the pathogens enables us to derive optimal treatments to mitigate infectious diseases or develop vaccinations preventing the occurrence of infect...

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Vydáno v:Cellular and molecular life sciences : CMLS Ročník 77; číslo 3; s. 467 - 480
Hlavní autoři: Ewald, Jan, Sieber, Patricia, Garde, Ravindra, Lang, Stefan N., Schuster, Stefan, Ibrahim, Bashar
Médium: Journal Article
Jazyk:angličtina
Vydáno: Cham Springer International Publishing 01.02.2020
Springer Nature B.V
Témata:
Animals
Biochemistry
Biomedical and Life Sciences
Biomedicine
Cell Biology
Computer applications
Computer Simulation
Crypsis
Game theory
Host-pathogen interactions
Host-Pathogen Interactions - physiology
Humans
Infectious diseases
Life Sciences
Livestock
Mathematical analysis
Mathematical models
Microorganisms
Mimicry
Modelling
Models, Theoretical
molecular mimicry
Optimization
Pathogens
Review
Systems Biology - methods
Trends
Vaccination
Crypsis
Host–pathogen interactions
Agent-based modeling
Equation-based modeling
Game theory
Dynamic optimization
ISSN:1420-682X, 1420-9071, 1420-9071
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Abstract Pathogenic microorganisms entail enormous problems for humans, livestock, and crop plants. A better understanding of the different infection strategies of the pathogens enables us to derive optimal treatments to mitigate infectious diseases or develop vaccinations preventing the occurrence of infections altogether. In this review, we highlight the current trends in mathematical modeling approaches and related methods used for understanding host–pathogen interactions. Since these interactions can be described on vastly different temporal and spatial scales as well as abstraction levels, a variety of computational and mathematical approaches are presented. Particular emphasis is placed on dynamic optimization, game theory, and spatial modeling, as they are attracting more and more interest in systems biology. Furthermore, these approaches are often combined to illuminate the complexities of the interactions between pathogens and their host. We also discuss the phenomena of molecular mimicry and crypsis as well as the interplay between defense and counter defense. As a conclusion, we provide an overview of method characteristics to assist non-experts in their decision for modeling approaches and interdisciplinary understanding.
AbstractList Pathogenic microorganisms entail enormous problems for humans, livestock, and crop plants. A better understanding of the different infection strategies of the pathogens enables us to derive optimal treatments to mitigate infectious diseases or develop vaccinations preventing the occurrence of infections altogether. In this review, we highlight the current trends in mathematical modeling approaches and related methods used for understanding host-pathogen interactions. Since these interactions can be described on vastly different temporal and spatial scales as well as abstraction levels, a variety of computational and mathematical approaches are presented. Particular emphasis is placed on dynamic optimization, game theory, and spatial modeling, as they are attracting more and more interest in systems biology. Furthermore, these approaches are often combined to illuminate the complexities of the interactions between pathogens and their host. We also discuss the phenomena of molecular mimicry and crypsis as well as the interplay between defense and counter defense. As a conclusion, we provide an overview of method characteristics to assist non-experts in their decision for modeling approaches and interdisciplinary understanding.Pathogenic microorganisms entail enormous problems for humans, livestock, and crop plants. A better understanding of the different infection strategies of the pathogens enables us to derive optimal treatments to mitigate infectious diseases or develop vaccinations preventing the occurrence of infections altogether. In this review, we highlight the current trends in mathematical modeling approaches and related methods used for understanding host-pathogen interactions. Since these interactions can be described on vastly different temporal and spatial scales as well as abstraction levels, a variety of computational and mathematical approaches are presented. Particular emphasis is placed on dynamic optimization, game theory, and spatial modeling, as they are attracting more and more interest in systems biology. Furthermore, these approaches are often combined to illuminate the complexities of the interactions between pathogens and their host. We also discuss the phenomena of molecular mimicry and crypsis as well as the interplay between defense and counter defense. As a conclusion, we provide an overview of method characteristics to assist non-experts in their decision for modeling approaches and interdisciplinary understanding.
Pathogenic microorganisms entail enormous problems for humans, livestock, and crop plants. A better understanding of the different infection strategies of the pathogens enables us to derive optimal treatments to mitigate infectious diseases or develop vaccinations preventing the occurrence of infections altogether. In this review, we highlight the current trends in mathematical modeling approaches and related methods used for understanding host-pathogen interactions. Since these interactions can be described on vastly different temporal and spatial scales as well as abstraction levels, a variety of computational and mathematical approaches are presented. Particular emphasis is placed on dynamic optimization, game theory, and spatial modeling, as they are attracting more and more interest in systems biology. Furthermore, these approaches are often combined to illuminate the complexities of the interactions between pathogens and their host. We also discuss the phenomena of molecular mimicry and crypsis as well as the interplay between defense and counter defense. As a conclusion, we provide an overview of method characteristics to assist non-experts in their decision for modeling approaches and interdisciplinary understanding.
Author Garde, Ravindra
Ibrahim, Bashar
Ewald, Jan
Lang, Stefan N.
Sieber, Patricia
Schuster, Stefan
Author_xml – sequence: 1
  givenname: Jan
  orcidid: 0000-0002-9415-2317
  surname: Ewald
  fullname: Ewald, Jan
  organization: Matthias Schleiden Institute, Bioinformatics, Friedrich Schiller University Jena
– sequence: 2
  givenname: Patricia
  orcidid: 0000-0001-9631-1126
  surname: Sieber
  fullname: Sieber, Patricia
  organization: Matthias Schleiden Institute, Bioinformatics, Friedrich Schiller University Jena
– sequence: 3
  givenname: Ravindra
  surname: Garde
  fullname: Garde, Ravindra
  organization: Matthias Schleiden Institute, Bioinformatics, Friedrich Schiller University Jena, Max Planck Institute for Chemical Ecology
– sequence: 4
  givenname: Stefan N.
  surname: Lang
  fullname: Lang, Stefan N.
  organization: Matthias Schleiden Institute, Bioinformatics, Friedrich Schiller University Jena
– sequence: 5
  givenname: Stefan
  orcidid: 0000-0003-2828-9355
  surname: Schuster
  fullname: Schuster, Stefan
  email: stefan.schu@uni-jena.de
  organization: Matthias Schleiden Institute, Bioinformatics, Friedrich Schiller University Jena
– sequence: 6
  givenname: Bashar
  orcidid: 0000-0001-7773-0122
  surname: Ibrahim
  fullname: Ibrahim, Bashar
  email: bashar.ibrahim@uni-jena.de
  organization: Matthias Schleiden Institute, Bioinformatics, Friedrich Schiller University Jena, Centre for Applied Mathematics and Bioinformatics, Gulf University for Science and Technology
BackLink https://www.ncbi.nlm.nih.gov/pubmed/31776589$$D View this record in MEDLINE/PubMed
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Cellular and Molecular Life Sciences is a copyright of Springer, (2019). All Rights Reserved. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Copyright Springer Nature B.V. Feb 2020
Copyright_xml – notice: The Author(s) 2019
– notice: Cellular and Molecular Life Sciences is a copyright of Springer, (2019). All Rights Reserved. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
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Issue 3
Keywords Crypsis
Host–pathogen interactions
Agent-based modeling
Equation-based modeling
Game theory
Dynamic optimization
Language English
License Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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SubjectTerms Animals
Biochemistry
Biomedical and Life Sciences
Biomedicine
Cell Biology
Computer applications
Computer Simulation
Crypsis
Game theory
Host-pathogen interactions
Host-Pathogen Interactions - physiology
Humans
Infectious diseases
Life Sciences
Livestock
Mathematical analysis
Mathematical models
Microorganisms
Mimicry
Modelling
Models, Theoretical
molecular mimicry
Optimization
Pathogens
Review
Systems Biology - methods
Trends
Vaccination
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