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

Separierung mit FindLinks gecrawlter Texte nach Sprachen

In dieser Arbeit wird ein Programm zur Sprachidentifikation von Web-Dokumenten vorgestellt. Das Verfahren nutzt Worthäufigkeitslisten als Trainingsdaten, um anhand dieser Dokumentenklassifikation in Sprachen vorzunehmen. Somit gehört dieses Werkzeug zu den supervised-learning-Systemen. Die zu klassifizierenden Web-Dokumente wurden mittels des von der Abteilung fur Automatische Sprachverarbeitung entwickelten Tools 'FindLinks' heruntergeladen. Das Programm ist somit in die Nachverarbeitung bestehender Rohdaten einzuordnen.This BSc Thesis presents a program for automatic language identification of web-documents called LangSepa. The procedure uses training-data which is based on word-frequency-tables of over 350 natural languages. Thus this tool can be subsumed under supervised learning systems. The documents for the classification-task were crawled by an information-retrieval system called FindLinks, which is developed at the Natural Language Processing group at the University of Leipzig. Therefore the presented program will be employed for the postprocessing of existent raw data

Separierung mit FindLinks gecrawlter Texte nach Sprachen

In dieser Arbeit wird ein Programm zur Sprachidentifikation von Web-Dokumenten vorgestellt. Das Verfahren nutzt Worthäufigkeitslisten als Trainingsdaten, um anhand dieser Dokumentenklassifikation in Sprachen vorzunehmen. Somit gehört dieses Werkzeug zu den supervised-learning-Systemen. Die zu klassifizierenden Web-Dokumente wurden mittels des von der Abteilung fur Automatische Sprachverarbeitung entwickelten Tools 'FindLinks' heruntergeladen. Das Programm ist somit in die Nachverarbeitung bestehender Rohdaten einzuordnen.This BSc Thesis presents a program for automatic language identification of web-documents called LangSepa. The procedure uses training-data which is based on word-frequency-tables of over 350 natural languages. Thus this tool can be subsumed under supervised learning systems. The documents for the classification-task were crawled by an information-retrieval system called FindLinks, which is developed at the Natural Language Processing group at the University of Leipzig. Therefore the presented program will be employed for the postprocessing of existent raw data

Separierung mit FindLinks gecrawlter Texte nach Sprachen

In dieser Arbeit wird ein Programm zur Sprachidentifikation von Web-Dokumenten vorgestellt. Das Verfahren nutzt Worthäufigkeitslisten als Trainingsdaten, um anhand dieser Dokumentenklassifikation in Sprachen vorzunehmen. Somit gehört dieses Werkzeug zu den supervised-learning-Systemen. Die zu klassifizierenden Web-Dokumente wurden mittels des von der Abteilung fur Automatische Sprachverarbeitung entwickelten Tools 'FindLinks' heruntergeladen. Das Programm ist somit in die Nachverarbeitung bestehender Rohdaten einzuordnen.This BSc Thesis presents a program for automatic language identification of web-documents called LangSepa. The procedure uses training-data which is based on word-frequency-tables of over 350 natural languages. Thus this tool can be subsumed under supervised learning systems. The documents for the classification-task were crawled by an information-retrieval system called FindLinks, which is developed at the Natural Language Processing group at the University of Leipzig. Therefore the presented program will be employed for the postprocessing of existent raw data

Agent-Based Model of Human Alveoli Predicts Chemotactic Signaling by Epithelial Cells during Early <i>Aspergillus fumigatus</i> Infection

<div><p><i>Aspergillus fumigatus</i> is one of the most important human fungal pathogens, causing life-threatening diseases. Since humans inhale hundreds to thousands of fungal conidia every day, the lower respiratory tract is the primary site of infection. Current interaction networks of the innate immune response attribute fungal recognition and detection to alveolar macrophages, which are thought to be the first cells to get in contact with the fungus. At present, these networks are derived from <i>in vitro</i> or <i>in situ</i> assays, as the peculiar physiology of the human lung makes <i>in vivo</i> experiments, including imaging on the cell-level, hard to realize. We implemented a spatio-temporal agent-based model of a human alveolus in order to perform <i>in silico</i> experiments of a virtual infection scenario, for an alveolus infected with <i>A. fumigatus</i> under physiological conditions. The virtual analog captures the three-dimensional alveolar morphology consisting of the two major alveolar epithelial cell types and the pores of Kohn as well as the dynamic process of respiration. To the best of our knowledge this is the first agent-based model of a dynamic human alveolus in the presence of respiration. A key readout of our simulations is the first-passage-time of alveolar macrophages, which is the period of time that elapses until the first physical macrophage-conidium contact is established. We tested for random and chemotactic migration modes of alveolar macrophages and varied their corresponding parameter sets. The resulting first-passage-time distributions imply that randomly migrating macrophages fail to find the conidium before the start of germination, whereas guidance by chemotactic signals derived from the alveolar epithelial cell associated with the fungus enables a secure and successful discovery of the pathogen in time.</p></div

Typical measures of the first-passage-time density distribution used in this study.

<p>Here, we show an example-distribution for a persistent random walk scenario with the parameters and based on samples (the corresponding distribution for biased persistent random walk is shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0111630#pone.0111630.s002" target="_blank">Fig. S2</a>). One sample of these simulations can be viewed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0111630#pone.0111630.s008" target="_blank">Video S2</a>.</p

Geodesic distances and the retention time distribution of successful macrophages for different migration modes in the static case.

<p>(A) and (C) are based on and , whereas (B) and (D) are based on and .</p

Comparison of first-passage-time distribution measures with and without breathing for both migration modes.

<p>Subfigures (A)–(C) show the FPT measures mean, median and probabilities of FPT above six hours for persistent random walk migration mode. Subfigures (D)–(F) show these measures for biased persistent random walk. The two breathing scenarios, resting condition (dashed lines) and heavy exercise (dotted lines) are shown together with the static case (lines) of a constant deflated alveolus. The parameters for the static case and the breathing scenarios are summarized in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0111630#pone-0111630-t002" target="_blank">Table 2</a>.</p

Flowchart of the agent-based simulation procedure for first-passage-time measurements.

<p>Integration of the system dynamics over time with timestep by using an asynchronous random order updating scheme <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0111630#pone.0111630-Harvey1" target="_blank">[24]</a>. Here, the recording of one first-passage-time sample is shown. is the total number of cells in the system at time and denotes a uniform random permutation of <i>m</i> elements. See text for further details.</p

Model parameters for human alveolar macrophages.

<p>Model parameters for human alveolar macrophages.</p