Project B4

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

Project B4

B4 focuses on the analysis and modeling of image data acquired within the CRC/TR FungiNet. This is accomplished by an image-based systems biology approach consisting of three steps: (i) automated image processing, (ii) derivation of quantitative measures, and (iii) construction of mathematical models to perform predictive computer simulations. The main objective is to advance this approach to investigate the interaction between host immune cells and human-pathogenic fungi, ultimately contributing to the development of a virtual infection model.

In the first funding period, we followed three lines of research: (i) Development of a pipeline for the automated analysis of microscopic images from endpoint experiments to investigate phagocytosis assays for Aspergillus fumigatus (collaboration with A1) and invasion assays for Candida albicans (C1). (ii) Computer simulation of virtual infection models for epithelial invasion of C. albicans (C1) and host-pathogen interactions in human whole-blood (C3). (iii) Mathematical modeling of A. fumigatus infection in the human lung by evolutionary game theory on graphs (A1, B1, C5).

Building on our achievements, in the second funding period we will design new tools and workflows to investigate morphological, functional and dynamic aspects of host-pathogen interactions. For example, the automated analysis of endpoint images will be developed into a comprehensive processing framework of time-resolved image data generated by live cell microscopy. We will also apply advanced computer simulations towards three main goals: (i) the generation of synthetic data representing a well-defined ground truth that we can use to validate our new algorithms for automated image analysis, (ii) the support of the design of experimental assays in order to avoid ambiguities, and (iii) the ability to identify mechanisms that govern the immune response in virtual infection scenarios.

Furthermore, we want to combine Image-based systems biology with the bioinformatics analysis of omics data in order to arrive at a more comprehensive view of infection scenarios across various scales.

Principal Investigator
Prof. Dr. Marc Thilo Figge
Prof. Dr. Marc Thilo Figge

Research Group Applied Systems Biology

Leibniz Institute for Natural Product Research and Infection Biology – Hans Knöll Institute  

thilo.figge@leibniz-hki.de

Publications
Author Year Title Journal Links
Prauße MTE, Lehnert T, Timme S, Hünniger K, Leonhardt I, Kurzai O, Figge MT 2018 Predictive virtual infection modeling of fungal immune evasion in human whole blood. Front Immunol 9: 560 Frontiers
Timme S, Lehnert T, Prauße MTE, Hünniger K, Leonhardt I, Kurzai O, Figge M 2018 Quantitative simulations predict treatment strategies against fungal infections in virtual neutropenic patients. Front Immunol 9: 667 Frontiers
Meinel C, Spartà G, Dahse H-M, Hörhold F, König R, Westermann M, Cseresnyés Z, Coldewey SM, Figge MT, Hammerschmidt S, Skerka C, Zipfel PF 2018 Streptococcus pneumoniae from patients with hemolytic uremic syndrome binds human plasminogen via the surface protein PspC and uses plasmin to damage human endothelial cells. J Infect Dis 217: 358-70 PubMed
Cseresnyes Z, Kraibooj K, Figge MT 2018 Hessian-based quantitative image analysis of host-pathogen confrontation assays. Cytometry A 93: 346-56 PubMed
Svensson C-M, Medyukhina A, Belyaev I, Al-Zaben N, Figge MT 2018 Untangling cell tracks: Quantifying cell migration by time lapse image data analysis. Cytometry A 93: 357-70 PubMed
Schaarschmidt B, Vlaic S, Medyukhina A, Neugebauer S, Nietzsche S, Gonnert FA, Rödel J, Singer M, Kiehntopf M, Figge MT, Jacobsen ID, Bauer M, Press AT 2018 Molecular signatures of liver dysfunction are distinct in fungal and bacterial infections in mice. Theranostics 8: 3766-80  
Allert S*, Förster TM*, Svensson CM, Richardson JP, Pawlik T, Hebecker B, Rudolphi S, Juraschitz M, Schaller M, Blagojevic M, Morschhäuser J, Figge MT, Jacobsen ID, Naglik JR, Kasper L, Mogavero S, Hube B; *authors contributed equally 2018 Candida albicans-induced epithelial damage mediates translocation through intestinal barriers. mBio 9: e00915-18 PubMed
Dasari P, Shopova IA, Stroe M, Wartenberg D, Dahse HM, Beyersdorf N, Hortschansky P, Dietrich S, Cseresnyés Z, Figge MT, Westermann M, Skerka C, Brakhage AA, Zipfel PF 2018 Aspf2 from Aspergillus fumigatus recruits human immune regulators for immune evasion and cell damage. Front Immunol 9: 1635 Frontiers
Brandes S, Dietrich S, Hünniger K, Kurzai O, Figge MT 2017 Migration and interaction tracking for quantitative analysis of phagocyte-pathogen confrontation assays. Med Image Anal 356: 172-83 PubMed
Lehnert T, Figge MT 2017 Dimensionality of motion and binding valency govern receptor-ligand kinetics as revealed by agent-based modeling. Front Immunol 8: 1692 PubMed
Figge MT 2017 Systems Biology of Infection NOVA ACTA LEOPOLDINA (ed.) Crossing Boundaries in Science. Documentation of the Workshop of the German National Academy of Sciences Leopoldina, Weimar, 06/30/2016-07/02/2016, 419, pp. 45-51. Wissenschaftliche Verlagsgesellschaft Stuttgart, Halle (Saale). Leopoldina
Pollmächer J, Timme S, Schuster S, Brakhage AA, Zipfel PF, Figge MT 2016 Deciphering the counterplay of Aspergillus fumigatus infection and host inflammation by evolutionary games on graphs. Sci Rep 6: 27807 PubMed
Buhlmann D, Eberhardt HU, Medyukhina A, Prodinger WM, Figge MT, Zipfel PF, Skerka C 2016 Complement factor H related protein 3 (FHR3) blocks C3d-mediated co-activation of human B cells. J Immunol 197: 620-9 PubMed
Hünniger K, Bieber K, Martin R, Lehnert T, Figge MT, Löffler J, Guo RF, Riedemann NC, Kurzai O 2015 A second stimulus required for enhanced antifungal activity of human neutrophils in blood is provided by anaphylatoxin C5a. J Immunol 194: 1199-210 PubMed
Brandes S, Mokhtari Z, Essig F, Hünniger K, Kurzai O, Figge MT 2015 Automated segmentation and tracking of non-rigid objects in time-lapse microscopy videos of polymorphonuclear neutrophils. Med Image Anal 20: 34-51 PubMed
Duggan S, Essig F, Hünniger K, Mokhtari Z, Bauer L, Lehnert T, Brandes S, Häder A, Jacobsen ID, Martin R, Figge MT, Kurzai O 2015 Neutrophil activation by Candida glabrata but not Candida albicans promotes fungal uptake by monocytes. Cell Microbiol 17: 1259-76 PubMed
Lehnert T, Timme S, Pollmächer J, Hünniger K, Kurzai O, Figge MT 2015 Bottom-up modeling approach for the quantitative estimation of parameters in pathogen-host interactions. Front Microbiol 6: 608 PubMed
Medyukhina A, Timme S, Mokhtari Z, Figge MT 2015 Image-based systems biology of infection. Cytometry A 87: 462-70 PubMed
Kraibooj K, Schoeler H, Svensson CM, Brakhage AA, Figge MT 2015 Automated quantification of the phagocytosis of Aspergillus fumigatus conidia by a novel image analysis algorithm. Front Microbiol 6: 549 PubMed
Mattern DJ, Schoeler H, Weber J, Novohradská S, Kraibooj K, Dahse HM, Hillmann F, Valiante V, Figge MT, Brakhage AA 2015 Identification of the antiphagocytic trypacidin gene cluster in the human-pathogenic fungus Aspergillus fumigatus. Appl Microbiol Biotechnol 99: 10151-61 PubMed
Pollmächer J, Figge MT 2015 Deciphering chemokine properties by a hybrid agent-based model of Aspergillus fumigatus infection in human alveoli. Front Microbiol 6: 503 PubMed
Hünniger K, Lehnert T, Bieber K, Martin R, Figge MT, Kurzai O 2014 A virtual infection model quantifies innate effector mechanisms and Candida albicans immune escape in human blood. PLoS Comput Biol 10: e1003479 PubMed
Kraibooj K, Park HR, Dahse HM, Skerka C, Voigt K, Figge MT 2014 Virulent strain of Lichtheimia corymbifera shows increased phagocytosis by macrophages as revealed by automated microscopy image analysis. Mycoses 57 Suppl 3: 56-66 PubMed
Mech F, Wilson D, Lehnert T, Hube B, Figge MT 2014 Epithelial invasion outcompetes hypha development during Candida albicans infection as revealed by an image-based systems biology approach. Cytometry A 85: 126-39 PubMed