Comparative assessment of immune evasion mechanisms in human whole-blood infection assays by a systems biology approach.

Autor: Lehnert T; Applied Systems Biology, Leibniz Institute for Natural Product Research Infection Biology, Hans Knöll Institute (HKI), Jena, Germany.; Center for Sepsis Control and Care (CSCC), Jena University Hospital, Jena, Germany., Prauße MTE; Applied Systems Biology, Leibniz Institute for Natural Product Research Infection Biology, Hans Knöll Institute (HKI), Jena, Germany.; Institute of Microbiology, Faculty of Biological Sciences, Friedrich Schiller University Jena, Jena, Germany., Hünniger K; Fungal Septomics, Leibniz Institute for Natural Product Research Infection Biology, Hans Knöll Institute (HKI), Jena, Germany.; Institute of Hygiene and Microbiology, University of Würzburg, Würzburg, Germany., Praetorius JP; Applied Systems Biology, Leibniz Institute for Natural Product Research Infection Biology, Hans Knöll Institute (HKI), Jena, Germany.; Institute of Microbiology, Faculty of Biological Sciences, Friedrich Schiller University Jena, Jena, Germany., Kurzai O; Center for Sepsis Control and Care (CSCC), Jena University Hospital, Jena, Germany.; Fungal Septomics, Leibniz Institute for Natural Product Research Infection Biology, Hans Knöll Institute (HKI), Jena, Germany.; Institute of Hygiene and Microbiology, University of Würzburg, Würzburg, Germany., Figge MT; Applied Systems Biology, Leibniz Institute for Natural Product Research Infection Biology, Hans Knöll Institute (HKI), Jena, Germany.; Center for Sepsis Control and Care (CSCC), Jena University Hospital, Jena, Germany.; Institute of Microbiology, Faculty of Biological Sciences, Friedrich Schiller University Jena, Jena, Germany.
Jazyk: angličtina
Zdroj: PloS one [PLoS One] 2021 Apr 01; Vol. 16 (4), pp. e0249372. Date of Electronic Publication: 2021 Apr 01 (Print Publication: 2021).
DOI: 10.1371/journal.pone.0249372
Abstrakt: Computer simulations of mathematical models open up the possibility of assessing hypotheses generated by experiments on pathogen immune evasion in human whole-blood infection assays. We apply an interdisciplinary systems biology approach in which virtual infection models implemented for the dissection of specific immune mechanisms are combined with experimental studies to validate or falsify the respective hypotheses. Focusing on the assessment of mechanisms that enable pathogens to evade the immune response in the early time course of a whole-blood infection, the least-square error (LSE) as a measure for the quantitative agreement between the theoretical and experimental kinetics is combined with the Akaike information criterion (AIC) as a measure for the model quality depending on its complexity. In particular, we compare mathematical models with three different types of pathogen immune evasion as well as all their combinations: (i) spontaneous immune evasion, (ii) evasion mediated by immune cells, and (iii) pre-existence of an immune-evasive pathogen subpopulation. For example, by testing theoretical predictions in subsequent imaging experiments, we demonstrate that the simple hypothesis of having a subpopulation of pre-existing immune-evasive pathogens can be ruled out. Furthermore, in this study we extend our previous whole-blood infection assays for the two fungal pathogens Candida albicans and C. glabrata by the bacterial pathogen Staphylococcus aureus and calibrated the model predictions to the time-resolved experimental data for each pathogen. Our quantitative assessment generally reveals that models with a lower number of parameters are not only scored with better AIC values, but also exhibit lower values for the LSE. Furthermore, we describe in detail model-specific and pathogen-specific patterns in the kinetics of cell populations that may be measured in future experiments to distinguish and pinpoint the underlying immune mechanisms.
Competing Interests: The authors have declared that no competing interests exist.
Databáze: MEDLINE
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