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Predictive Virtual Infection Modeling of Fungal Immune Evasion in Human Whole Blood

Bloodstream infections by the human-pathogenic fungi Candida albicans and Candida glabrata increasingly occur in hospitalized patients and are associated with high mortality rates. The early immune response against these fungi in human blood comprises a concerted action of humoral and cellular compo...

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Autores principales: Prauße, Maria T. E., Lehnert, Teresa, Timme, Sandra, Hünniger, Kerstin, Leonhardt, Ines, Kurzai, Oliver, Figge, Marc Thilo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5871695/
https://www.ncbi.nlm.nih.gov/pubmed/29619027
http://dx.doi.org/10.3389/fimmu.2018.00560
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author Prauße, Maria T. E.
Lehnert, Teresa
Timme, Sandra
Hünniger, Kerstin
Leonhardt, Ines
Kurzai, Oliver
Figge, Marc Thilo
author_facet Prauße, Maria T. E.
Lehnert, Teresa
Timme, Sandra
Hünniger, Kerstin
Leonhardt, Ines
Kurzai, Oliver
Figge, Marc Thilo
author_sort Prauße, Maria T. E.
collection PubMed
description Bloodstream infections by the human-pathogenic fungi Candida albicans and Candida glabrata increasingly occur in hospitalized patients and are associated with high mortality rates. The early immune response against these fungi in human blood comprises a concerted action of humoral and cellular components of the innate immune system. Upon entering the blood, the majority of fungal cells will be eliminated by innate immune cells, i.e., neutrophils and monocytes. However, recent studies identified a population of fungal cells that can evade the immune response and thereby may disseminate and cause organ dissemination, which is frequently observed during candidemia. In this study, we investigate the so far unresolved mechanism of fungal immune evasion in human whole blood by testing hypotheses with the help of mathematical modeling. We use a previously established state-based virtual infection model for whole-blood infection with C. albicans to quantify the immune response and identified the fungal immune-evasion mechanism. While this process was assumed to be spontaneous in the previous model, we now hypothesize that the immune-evasion process is mediated by host factors and incorporate such a mechanism in the model. In particular, we propose, based on previous studies that the fungal immune-evasion mechanism could possibly arise through modification of the fungal surface by as of yet unknown proteins that are assumed to be secreted by activated neutrophils. To validate or reject any of the immune-evasion mechanisms, we compared the simulation of both immune-evasion models for different infection scenarios, i.e., infection of whole blood with either C. albicans or C. glabrata under non-neutropenic and neutropenic conditions. We found that under non-neutropenic conditions, both immune-evasion models fit the experimental data from whole-blood infection with C. albicans and C. glabrata. However, differences between the immune-evasion models could be observed for the infection outcome under neutropenic conditions with respect to the distribution of fungal cells across the immune cells. Based on these predictions, we suggested specific experimental studies that might allow for the validation or rejection of the proposed immune-evasion mechanism.
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spelling pubmed-58716952018-04-04 Predictive Virtual Infection Modeling of Fungal Immune Evasion in Human Whole Blood Prauße, Maria T. E. Lehnert, Teresa Timme, Sandra Hünniger, Kerstin Leonhardt, Ines Kurzai, Oliver Figge, Marc Thilo Front Immunol Immunology Bloodstream infections by the human-pathogenic fungi Candida albicans and Candida glabrata increasingly occur in hospitalized patients and are associated with high mortality rates. The early immune response against these fungi in human blood comprises a concerted action of humoral and cellular components of the innate immune system. Upon entering the blood, the majority of fungal cells will be eliminated by innate immune cells, i.e., neutrophils and monocytes. However, recent studies identified a population of fungal cells that can evade the immune response and thereby may disseminate and cause organ dissemination, which is frequently observed during candidemia. In this study, we investigate the so far unresolved mechanism of fungal immune evasion in human whole blood by testing hypotheses with the help of mathematical modeling. We use a previously established state-based virtual infection model for whole-blood infection with C. albicans to quantify the immune response and identified the fungal immune-evasion mechanism. While this process was assumed to be spontaneous in the previous model, we now hypothesize that the immune-evasion process is mediated by host factors and incorporate such a mechanism in the model. In particular, we propose, based on previous studies that the fungal immune-evasion mechanism could possibly arise through modification of the fungal surface by as of yet unknown proteins that are assumed to be secreted by activated neutrophils. To validate or reject any of the immune-evasion mechanisms, we compared the simulation of both immune-evasion models for different infection scenarios, i.e., infection of whole blood with either C. albicans or C. glabrata under non-neutropenic and neutropenic conditions. We found that under non-neutropenic conditions, both immune-evasion models fit the experimental data from whole-blood infection with C. albicans and C. glabrata. However, differences between the immune-evasion models could be observed for the infection outcome under neutropenic conditions with respect to the distribution of fungal cells across the immune cells. Based on these predictions, we suggested specific experimental studies that might allow for the validation or rejection of the proposed immune-evasion mechanism. Frontiers Media S.A. 2018-03-21 /pmc/articles/PMC5871695/ /pubmed/29619027 http://dx.doi.org/10.3389/fimmu.2018.00560 Text en Copyright © 2018 Prauße, Lehnert, Timme, Hünniger, Leonhardt, Kurzai and Figge. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Prauße, Maria T. E.
Lehnert, Teresa
Timme, Sandra
Hünniger, Kerstin
Leonhardt, Ines
Kurzai, Oliver
Figge, Marc Thilo
Predictive Virtual Infection Modeling of Fungal Immune Evasion in Human Whole Blood
title Predictive Virtual Infection Modeling of Fungal Immune Evasion in Human Whole Blood
title_full Predictive Virtual Infection Modeling of Fungal Immune Evasion in Human Whole Blood
title_fullStr Predictive Virtual Infection Modeling of Fungal Immune Evasion in Human Whole Blood
title_full_unstemmed Predictive Virtual Infection Modeling of Fungal Immune Evasion in Human Whole Blood
title_short Predictive Virtual Infection Modeling of Fungal Immune Evasion in Human Whole Blood
title_sort predictive virtual infection modeling of fungal immune evasion in human whole blood
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5871695/
https://www.ncbi.nlm.nih.gov/pubmed/29619027
http://dx.doi.org/10.3389/fimmu.2018.00560
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