Individual-based modeling and predictive simulation of fungal infection dynamics

The human-pathogenic fungus Aspergillus fumigatus causes life-threatening infections in immunocompromised patients and poses increasing challenges for the modern medicine. A. fumigatus is ubiquitously present and disseminates via small conidia over the air of the athmosphere. Each human inhales several hundreds to thousands of conidia every day. The small size of conidia allows them to pass into the alveoli of the lung, where primary infections with A. fumigatus are typically observed. In alveoli, the interaction between fungi and the innate immune system of the host takes place. This interaction is the core topic of this thesis and covered by mathematical modeling and computer simulations. Since in vivo laboratory studies of A. fumigatus infections under physiological conditions is hard to realize a modular software framework was developed and implemented, which allows for spatio-temporal agent-based modeling and simulation. A to-scale A. fumigatus infection model in a typical human alveolus was developed in order to simulate and analyze the infection scenario under physiological conditions. The process of conidial discovery by alveolar macrophages was modeled and simulated with different migration modes and different parameter configurations. It could be shown that chemotactic migration was required to find the pathogen before the onset of germination. A second model took advantage of evolutionary game theory on graphs. Here, the course of infection was modeled as a consecutive sequence of evolutionary games related to the complement system, alveolar macrophages and polymorphonuclear neutrophilic granulocytes. The results revealed a central immunoregulatory role of alveolar macrophages. In the case of high infectious doses it was found that the host required fully active phagocytes, but in particular a qualitative response of quantitatively sufficient polymorphonuclear neutrophilic granulocytes.Der human-pathogene Schimmelpilz Aspergillus fumigatus verursacht tödliche Infektionen und Erkrankungen vorrangig bei immunsupprimierten Patienten und stellt die moderne Medizin vor zunehmende Herausforderungen. A. fumigatus ist ubiquitär präsent und verbreitet sich über sehr kleine Konidien durch Luftströmungen in der Athmosphäre. Mehrere Hundert bis Tausende dieser Konidien werden täglich durch jeden Menschen eingeatmet. Die geringe Größe der infektiösen Konidien erlauben es dem Pilz bis in die Alveolen der Lunge des Wirtes vorzudringen,in denen eine Primärinfektionen mit A. fumigatus am häufigsten stattfindet. Die Alveolen sind der zentrale Schauplatz der Interaktion zwischen dem Pilz und dem angeborenen Immunsystem, welche Gegenstand dieser Arbeit ist. Diese Interaktion wird mit Hilfe von mathematischen Modellen und Computersimulationen nachgestellt und untersucht, da eine A. fumigatus Infektion im Nasslabor in vivo unter physiologischen Bedingungen nur sehr schwer realisiert werden kann. Als Grundlage für dieses Vorhaben wurde ein modulares Software-Paket entwickelt, welches agentenbasierte Modellierung und entsprechende Simulationen in Raum und Zeit ermöglicht. Ein maßstabsgetreues mathematisches Infektionsmodell in einer typischen menschlichen Alveole wurde entwickelt und die Suchstrategien von Alveolarmakrophagen unter der Berücksichtigung verschiedener Parameter wie Migrationsgeschwindigkeit, dem Vorhandensein von Chemokinen, dessen Diffusion und Chemotaxis untersucht. Es zeigte sich, dass Chemotaxis, notwendig ist, um die Konidie rechtzeitig finden zu können. In einem weiteren Modell, welches auf das Konzept evolutionärer Spieltheorie auf Graphen zurückgegriff, wurde der Infektionsverlauf als aufeinanderfolgende Serie evolutionärer Spiele mit dem Komplementsystem, Alveolarmakrophagen und Neutrophilen nachgestellt. Aus den Simulationsergebnissen konnte eine zentrale immunregulatorische Rolle von Alveolarmakrophagen entnommen werden

A proposed integrated approach for the preclinical evaluation of phage therapy in Pseudomonas infections

Bacteriophage therapy is currently resurging as a potential complement/alternative to antibiotic treatment. However, preclinical evaluation lacks streamlined approaches. We here focus on preclinical approaches which have been implemented to assess bacteriophage efficacy against Pseudomonas biofilms and infections. Laser interferometry and profilometry were applied to measure biofilm matrix permeability and surface geometry changes, respectively. These biophysical approaches were combined with an advanced Airway Surface Liquid infection model, which mimics in vitro the normal and CF lung environments, and an in vivo Galleria larvae model. These assays have been implemented to analyze KTN4 (279,593 bp dsDNA genome), a type-IV pili dependent, giant phage resembling phiKZ. Upon contact, KTN4 immediately disrupts the P. aeruginosa PAO1 biofilm and reduces pyocyanin and siderophore production. The gentamicin exclusion assay on NuLi-1 and CuFi-1 cell lines revealed the decrease of extracellular bacterial load between 4 and 7 logs and successfully prevents wild-type Pseudomonas internalization into CF epithelial cells. These properties and the significant rescue of Galleria larvae indicate that giant KTN4 phage is a suitable candidate for in vivo phage therapy evaluation for lung infection applications

Systems Biology of Fungal Infection

Elucidation of pathogenicity mechanisms of the most important human-pathogenic fungi, Aspergillus fumigatus and Candida albicans, has gained great interest in the light of the steadily increasing number of cases of invasive fungal infections. A key feature of these infections is the interaction of the different fungal morphotypes with epithelial and immune effector cells in the human host. Because of the high level of complexity, it is necessary to describe and understand invasive fungal infection by taking a systems biological approach, i.e., by a comprehensive quantitative analysis of the non-linear and selective interactions of a large number of functionally diverse, and frequently multifunctional, sets of elements, e.g., genes, proteins, metabolites, which produce coherent and emergent behaviors in time and space. The recent advances in systems biology will now make it possible to uncover the structure and dynamics of molecular and cellular cause-effect relationships within these pathogenic interactions. We review current efforts to integrate omics and image-based data of host-pathogen interactions into network and spatio-temporal models. The modeling will help to elucidate pathogenicity mechanisms and to identify diagnostic biomarkers and potential drug targets for therapy and could thus pave the way for novel intervention strategies based on novel antifungal drugs and cell therapy

METABOLIC MODELING OF MULTISPECIES MICROBIAL BIOFILMS

Biofilms are ubiquitous in medical, environmental, and engineered microbial systems. The majority of naturally occurring microbes grow as mixed species biofilms. These complicated biofilm consortia are comprised of many cell phenotypes with complex interactions and self-organized into three-dimensional structures. Approximately 2% of the US population suffers from non-healing chronic wounds infected by a combination of commensal and pathogenic bacteria whereas about 500,000 cases of Clostridium difficile infections (CDI) are reported annually. These polymicrobial infections are often resilient to antibiotic treatment due to the nutrient-rich environments and species interactions that promote community stability and robustness. This thesis focusses on developing metabolic modeling framework to study the interactions and the spatial/temporal organizations in the biofilms. The modeling framework is based on integrating genome scale metabolic reconstructions of considered species in this work, with the nutrient uptake kinetics to predict the species abundances, growth rates and byproduct secretions. The spatiotemporal modeling framework accounts for the nutrient concentration gradients in the biofilm system. Spatiotemporal biofilm metabolic models were formulated by combining genome scale metabolic reconstructions of considered species with uptake kinetics for available nutrients and reaction-diffusion type equations for species biomass, supplied substrates and synthesized metabolic byproducts. The resulting partial differential equations embedded with linear programs were discretized in the space and integrated using a dynamic flux balance method. This framework was used to calculate the spatial and temporal variations in the species, nutrient and byproduct concentrations in biofilms. This framework was used to study the species organization and dynamics in chronic wound infections, CDI and environmental biofilms. The chronic wound biofilm model was comprising of two most dominant species, Pseudomonas aeruginosa and Staphylococcus aureus. The CDI biofilm model was comprising of representative species from three most common phyla in gut Bacteroidetes thetaiotaomicron, Faecalibacterium prausnitzii, Escherichia coli and pathogen C. difficile. The simulation results were used to study the interspecies interactions, the spatial partitioning in the biofilms and important crossfeeding relationships within the community. These predictions would be useful in devising effective antibiotic treatment strategies to cure the biofilm infections associated with chronic wounds and C. difficile. The environmental biofilm model for cyanobacteria and heterotrophs was developed and validated with the experimental results, this model was used to evaluate the community dynamics under extreme environmental conditions The second modeling framework considered biofilm as a well-mixed homogenous system at steady state. Steady state in silico community models were formulated by combining genome scale metabolic reconstructions of the considered species. The community models were solved using SteadyCom method. This method uses community flux balance analysis to calculate the relative abundance of each species with an objective of maximizing the community growth rate. A 12 species chronic wound community metabolic model covering 74% of 16S rDNA pyrosequencing reads of dominant genera from 2,963 chronic wound patients was developed. The community model was used to predict species abundances averaged across this large patient population. The simulation results from this study were used to identify putative mutualistic interactions between bacteria that could be targeted to enhance treatment efficacy. The frameworks developed in this thesis would be useful in developing patient/disease specific therapeutic treatments

Marine infectious disease dynamics and outbreak thresholds: contact transmission, pandemic infection, and the potential role of filter feeders

Disease-causing organisms can have significant impacts on marine species and communities. However, the dynamics that underlie the emergence of disease outbreaks in marine ecosystems still lack the equivalent level of description, conceptual understanding, and modeling context routinely present in the terrestrial systems. Here, we propose a theoretical basis for modeling the transmission of marine infectious diseases (MIDs) developed from simple models of the spread of infectious disease. The models represent the dynamics of a variety of host–pathogen systems including those unique to marine systems where transmission of disease is by contact with waterborne pathogens both directly and through filter-feeding processes. Overall, the analysis of the epizootiological models focused on the most relevant processes that interact to drive the initiation and termination of epizootics. A priori, systems with multi-step disease infections (e.g., infection-death-particle release-filtration-transmission) reduced dependence on individual parameters resulting in inherently slower transmissions rates. This is demonstrably not the case; thus, these alternative transmission pathways must also considerably increase the rates of processes involved in transmission. Scavengers removing dead infected animals may inhibit disease spread in both contact-based and waterborne pathogen-based diseases. The capacity of highly infected animals, both alive and dead, to release a substantial number of infective elements into the water column, making them available to suspension feeders results in such diseases being highly infective with a very small “low-abundance refuge”. In these systems, the body burden of pathogens and the relative importance between the release and the removal rate of pathogens in the host tissue or water column becomes paramount. Two processes are of potential consequence inhibiting epizootics. First, large water volumes above the benthic susceptible populations can function as a sink for pathogens. Second, unlike contact-based disease models in which an increase in the number of susceptible individuals in the population increases the likelihood of transmission and epizootic development, large populations of filter feeders can reduce this likelihood through the overfiltration of infective particles.This investigation was funded by the NSF Evolution and Ecology of Infectious Diseases (EEID) Program Grant # OCE-1216220. We appreciate this support

Marine Infectious Disease Dynamics and Outbreak Thresholds: Contact Transmission, Pandemic Infection, and the Potential Role of Filter Feeders

Disease-causing organisms can have significant impacts on marine species and communities. However, the dynamics that underlie the emergence of disease outbreaks in marine ecosystems still lack the equivalent level of description, conceptual understanding, and modeling context routinely present in the terrestrial systems. Here, we propose a theoretical basis for modeling the transmission of marine infectious diseases (MIDs) developed from simple models of the spread of infectious disease. The models represent the dynamics of a variety of host-pathogen systems including those unique to marine systems where transmission of disease is by contact with waterborne pathogens both directly and through filter-feeding processes. Overall, the analysis of the epizootiological models focused on the most relevant processes that interact to drive the initiation and termination of epizootics. A priori, systems with multi-step disease infections (e.g., infection-death-particle release-filtration-transmission) reduced dependence on individual parameters resulting in inherently slower transmissions rates. This is demonstrably not the case; thus, these alternative transmission pathways must also considerably increase the rates of processes involved in transmission. Scavengers removing dead infected animals may inhibit disease spread in both contact-based and waterborne pathogen-based diseases. The capacity of highly infected animals, both alive and dead, to release a substantial number of infective elements into the water column, making them available to suspension feeders results in such diseases being highly infective with a very small low-abundance refuge . In these systems, the body burden of pathogens and the relative importance between the release and the removal rate of pathogens in the host tissue or water column becomes paramount. Two processes are of potential consequence inhibiting epizootics. First, large water volumes above the benthic susceptible populations can function as a sink for pathogens. Second, unlike contact-based disease models in which an increase in the number of susceptible individuals in the population increases the likelihood of transmission and epizootic development, large populations of filter feeders can reduce this likelihood through the overfiltration of infective particles

2015 Conference Abstracts: Annual Undergraduate Research Conference at the Interface of Biology and Mathematics

Schedule and abstract book for the Seventh Annual Undergraduate Research Conference at the Interface of Biology and Mathematics Date: November 21-22, 2015Plenary speaker: Robert Smith, University of OttawaFeatured speaker: Rachel Lenhart, University of Wisconsin, Madiso

Virtual infection modeling for Aspergillus fumigatus in human and murine alveoli

Der Der filamentöse pathogene Pilz Aspergillus fumigatus kann schwere Infektionen wie die invasive pulmonale Aspergillose in immungeschwächten Patienten verursachen. Verbunden mit einer hohen Mortalität und einer steigenden Inzidenz der letzten Jahrzehnte bezeugt dies die Notwendigkeit zur Erforschung seines opportunistischen Verhaltens sowie zur Entwicklung effizienter Behandlungsstrategien, um Menschenleben zu retten. Da die Lunge, als primäres Ziel von A. fumigatus Infektionen, nur begrenzt experimentell in vivo studiert werden kann, verfolgt diese Arbeit den Ansatz agenten-basierter Simulation. Die kumulative Dissertation basiert auf 4 veröffentlichten Manuskripten. Untersucht wurden dabei die Vergleichbarkeit von natürlichen Infektionen im Menschen und künstlichen Infektionen im etablierten Mausmodell. Eine zweite Veröffentlichung untersucht den Einfluss von Kohn'schen Poren auf die Dynamik der Immunabwehr gegen Aspergillus fumigatus. Eine dritte Veröffentlichung untersucht die Anwendbarkeit von dynamischen Kugeloberflächenfunktionen - Spherical Harmonics - als Werkzeug der Klassifikation und Beschreibung von beweglichen Zellen. Die vierte Veröffentlichung präsentiert erstmals einen Aspergillose Chip auf Mikrofluidikchips. Dies erlaubt es, die Pathogen-Wirt-Beziehungen unter realistischen Bedingungen zu untersuchen sowie das Wachstum der Pilzhyphen zu quantifizieren

Modelling the Composition and Structure of Campylobacter jejuni Biofilms

The goal of this research project was to study the effects of environmental and genetic factors on biofilm formation of Campylobacter jejuni with the use of mathematical modelling, experimental and bioinformatics techniques. Potential reasons for some puzzling observations regarding C. jejuni biofilm formation have been proposed as a result of this study, and a number of genes and SNPs have been identified, which may play a role in biofilm formation of this pathogen