Sandra Timme

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About Sandra Timme:

No description specified

SEEK ID: https://funginet.hki-jena.de/people/69

Location: Germany

ORCID: Not specified

Joined: 4th Mar 2016

Expertise: Not specified

Tools: Not specified

Their tags

agent-based model alveolar epithelial cells alveolar macrophages alveolus antibody-antigen binding Aspergillus fumigatus B cell Candida albicans chemotaxis complement regulator factor H Complement system computational biology differential equations Evolutionary game theory Game Theory hybrid differential equation approach Immune evasion lung modelling monocytes mouse neutrophils non-self recognition ODE Ordinary differential equations Partial differential equations Partial-differential equations receptor-ligand interaction self-tolerance state-based model Systems Biology virtual infection model whole-blood assay whole-blood infection assay

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Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

The yeast Candida albicans and the filamentous fungus Aspergillus fumigatus are by far the most important causes of life-threatening invasive mycoses in Europe. Despite the increasing incidence of these infections, the current diagnosis is still difficult and often too late, and options for therapies are limited. Moreover, A. fumigatus and C. albicans have developed multiple sophisticated, specific and unique pathogenicity mechanisms. Many of these mechanisms are not well understood. Research on ...

Projects: FungiNet total, FungiNet A - Aspergillus projects, FungiNet B - Bioinformatics projects, FungiNet C - Candida projects, INF, A1, A2, A3, A4 (E), A5, B1, B2, B3 (E), B4, C1, C2, C3, C4 (E), C5, C6 (E), Z2, Z1, B5, A6, A7, A8, C7

Web page: http://www.funginet.de/home.html

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FungiNet total

No description specified

Programme: Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

Public web page: http://www.funginet.de/home.html

Organisms: Aspergillus fumigatus, Candida albicans

Image data analysis and agent-based modelling of the spatio-temporal interaction between immune cells and human-pathogenic fungi

Programme: Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

Public web page: http://www.funginet.de/project-b4.html

Organisms: Aspergillus fumigatus, Candida albicans

FungiNet C - Candida projects

No description specified

Programme: Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

Public web page: http://www.funginet.de/project-area-c.html

Organisms: Candida albicans

FungiNet A - Aspergillus projects

No description specified

Programme: Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

Public web page: http://www.funginet.de/project-area-a.html

Organisms: Aspergillus fumigatus

FungiNet B - Bioinformatics projects

No description specified

Programme: Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

Public web page: http://www.funginet.de/project-area-b.html

Organisms: Aspergillus fumigatus, Candida albicans

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Leibniz-Institute for Natural Product Research and Infection Biology Hans Knöll Institute (HKI)

Country: Germany

City: 07745 Jena

Web page: http://www.hki-jena.de

Showing 5 out of a possible 6 Models Advanced Models list for this Person with search and filtering

State-based model of whole-blood infection assay with PMN-mediated immune evasion mechanism

This model is a variant of the previously developed SBM of whole-blood infection assay. While in the previous model a spontaneous immune evasion mechanism (A) was implemented in this model immune evasion was caused by PMN molecule secretion (B).

Creators: Teresa Lehnert, Maria T. E. Prauße

Submitter: Sandra Timme

Model type: Not specified

Model format: Not specified

Environment: Not specified

Organism: Candida albicans

Investigations: No Investigations

Studies: No Studies

Assays: No Assays

Created: 18th Feb 2021 at 09:28

State-based model of whole-blood infection assays with Candida albicans

The state-based model (SBM) allow to simulate the interplay between innate immune cells, such as monocytes and PMN, and Candida albicans and to quantify immune reaction rates like phagocytosis and killing rates. It is implemented in C++.

Creator: Teresa Lehnert

Submitter: Sandra Timme

Model type: Not specified

Model format: Not specified

Environment: Not specified

Organism: Candida albicans

Investigations: No Investigations

Studies: No Studies

Assays: No Assays

Created: 18th Feb 2021 at 09:23, Last updated: 18th Feb 2021 at 09:23

DynaCoSys

DynaCoSys models the complement system by using a combination of Ordinary and Partial Differential Equations.

Creators: Teresa Lehnert, Alexander Tille

Submitter: Sandra Timme

Model type: Partial differential equations (PDE)

Model format: Not specified

Environment: Not specified

Organism: Candida albicans

Investigations: No Investigations

Studies: No Studies

Assays: No Assays

Created: 16th Feb 2021 at 16:25, Last updated: 18th Feb 2021 at 09:00

Virtual infection model of Aspergillus fumigatus in a murine alveolus

Adaptation of the previously developed virtual infection model of Aspergillus fumigatus in a human alveolus. This model comprises a hybrid agent-based model of a single murine alveolus. The alveolus is represented in a realistic to-scale representation and contains the cell types of alveolar epithelial cells (AEC) of type 1 and 2 as well as the pores of Kohn (PoK). Furthermore, in this model, depending on the infection dose multiple A. fumigatus conidium are inserted into the alveolus and the ...

Creators: Sandra Timme, Marco Blickensdorf

Submitter: Sandra Timme

Model type: Agent based modelling

Model format: Not specified

Environment: Not specified

Organism: Aspergillus fumigatus

Investigations: No Investigations

Studies: No Studies

Assays: No Assays

Created: 18th Feb 2021 at 08:57, Last updated: 18th Feb 2021 at 08:57

Virtual infection model of Aspergillus fumigatus in a human alveolus

This model comprises a hybrid agent-based model of a single human alveolus. The alveolus is represented in a realistic to-scale representation and contains the cell types of alveolar epithelial cells (AEC) of type 1 and 2 as well as the pores of Kohn (PoK). A single A. fumigatus conidium in inserted into the alveolus and the AEC, where the conidium is located secretes chemokines. Chemokine secretion is modelled using the partial differential equation of the diffusion equation and numerically ...

Creator: Johannes Pollmächer

Submitter: Sandra Timme

Model type: Agent based modelling

Model format: Not specified

Environment: Not specified

Organism: Aspergillus fumigatus

Investigations: No Investigations

Studies: No Studies

Assays: No Assays

Created: 18th Feb 2021 at 08:39, Last updated: 18th Feb 2021 at 08:39

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Showing 5 out of a possible 10 Publications Advanced Publications list for this Person with search and filtering

Quantification of Factor H Mediated Self vs. Non-self Discrimination by Mathematical Modeling.

FungiNet C - Candida projects, B4

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Abstract (Expand)

The complement system is part of the innate immune system and plays an important role in the host defense against infectious pathogens. One of the main effects is the opsonization of foreign invaders … and subsequent uptake by phagocytosis. Due to the continuous default basal level of active complement molecules, a tight regulation is required to protect the body's own cells (self cells) from opsonization and from complement damage. A major complement regulator is Factor H, which is recruited from the fluid phase and attaches to cell surfaces where it effectively controls complement activation. Besides self cells, pathogens also have the ability to bind Factor H; they can thus escape opsonization and phagocytosis causing severe infections. In order to advance our understanding of the opsonization process at a quantitative level, we developed a mathematical model for the dynamics of the complement system-termed DynaCoSys model-that is based on ordinary differential equations for cell surface-bound molecules and on partial differential equations for concentration profiles of the fluid phase molecules in the environment of cells. This hybrid differential equation approach allows to model the complement cascade focusing on the role of active C3b in the fluid phase and on the cell surface as well as on its inactivation on the cell surface. The DynaCoSys model enables us to quantitatively predict the conditions under which Factor H mediated complement evasion occurs. Furthermore, investigating the quantitative impact of model parameters by a sensitivity analysis, we identify the driving processes of complement activation and regulation in both the self and non-self regime. The two regimes are defined by a critical Factor H concentration on the cell surface and we use the model to investigate the differential impact of complement model parameters on this threshold value. The dynamic modeling on the surface of pathogens are further relevant to understand pathophysiological situations where Factor H mutants and defective Factor H binding to target surfaces results in pathophysiology such as renal and retinal disease. In the future, this DynaCoSys model will be extended to also enable evaluating treatment strategies of complement-related diseases.

Authors: A. Tille, T. Lehnert, P. F. Zipfel, M. T. Figge

Date Published: 5th Oct 2020

Publication Type: Not specified

PubMed ID: 33013842

Citation: Front Immunol. 2020 Sep 2;11:1911. doi: 10.3389/fimmu.2020.01911. eCollection 2020.

Created: 16th Feb 2021 at 16:08, Last updated: 17th Jan 2024 at 10:24

Hybrid Agent-Based Modeling of Aspergillus fumigatus Infection to Quantitatively Investigate the Role of Pores of Kohn in Human Alveoli.

Abstract (Expand)

The healthy state of an organism is constantly threatened by external cues. Due to the daily inhalation of hundreds of particles and pathogens, the immune system needs to constantly accomplish the task …

Authors: M. Blickensdorf, S. Timme, M. T. Figge

Date Published: 9th Sep 2020

Publication Type: Not specified

PubMed ID: 32903715

Citation: Front Microbiol. 2020 Aug 12;11:1951. doi: 10.3389/fmicb.2020.01951. eCollection 2020.

Created: 11th Feb 2021 at 16:07, Last updated: 17th Jan 2024 at 10:24

Comparative Assessment of Aspergillosis by Virtual Infection Modeling in Murine and Human Lung.

Abstract (Expand)

Aspergillus fumigatus is a ubiquitous opportunistic fungal pathogen that can cause severe infections in immunocompromised patients. Conidia that reach the lower respiratory tract are confronted with …

Authors: M. Blickensdorf, S. Timme, M. T. Figge

Date Published: 27th Feb 2019

Publication Type: Not specified

PubMed ID: 30804941

Citation: Front Immunol. 2019 Feb 5;10:142. doi: 10.3389/fimmu.2019.00142. eCollection 2019.

Created: 11th Feb 2021 at 16:15, Last updated: 17th Jan 2024 at 10:24

Quantitative Simulations Predict Treatment Strategies Against Fungal Infections in Virtual Neutropenic Patients.

FungiNet C - Candida projects, B4

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Abstract (Expand)

The condition of neutropenia, i.e., a reduced absolute neutrophil count in blood, constitutes a major risk factor for severe infections in the affected patients. Candida albicans and Candida glabrata …

Authors: S. Timme, T. Lehnert, M. T. E. Prausse, K. Hunniger, I. Leonhardt, O. Kurzai, M. T. Figge

Date Published: 20th Apr 2018

Publication Type: Not specified

PubMed ID: 29670632

Citation: Front Immunol. 2018 Apr 4;9:667. doi: 10.3389/fimmu.2018.00667. eCollection 2018.

Created: 11th Feb 2021 at 15:43, Last updated: 17th Jan 2024 at 10:24

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

FungiNet C - Candida projects, B4

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Abstract (Expand)

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.

Authors: M. T. E. Prausse, T. Lehnert, S. Timme, K. Hunniger, I. Leonhardt, O. Kurzai, M. T. Figge

Date Published: 6th Apr 2018

Publication Type: Not specified

PubMed ID: 29619027

Citation: Front Immunol. 2018 Mar 21;9:560. doi: 10.3389/fimmu.2018.00560. eCollection 2018.

Created: 11th Feb 2021 at 15:53, Last updated: 17th Jan 2024 at 10:24

View all 10 Publications

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