Research Collection. Statistical analysis and modeling of endocytic vesicle pattern formation. Doctoral Thesis. ETH Library
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1 Research Collection Doctoral Thesis Statistical analysis and modeling of endocytic vesicle pattern formation Author(s): Birbaumer, Mirko Publication Date: 2010 Permanent Link: Rights / License: In Copyright - Non-Commercial Use Permitted This page was generated automatically upon download from the ETH Zurich Research Collection. For more information please consult the Terms of use. ETH Library
2 Diss. ETH No Statistical Analysis and Modeling of Endocytic Vesicle Pattern Formation A dissertation submitted to ETH Zurich for the degree of Doctor of Sciences presented by Mirko Birbaumer Dipl. Phys. ETH born June 5, 1979 citizen of Ufhusen (LU) accepted on the recommendation of Prof. Dr. Lucas Pelkmans, examiner Prof. Dr. Dr. Frank Schweitzer, coexaminer Prof. Dr. Ivo Sbalzarini, coexaminer Prof. Dr. Uwe Sauer, coexaminer 2010
3 Summary Image-based screens in standard tissue culture cells have revealed a wide variety of single-cell phenotypes in endocytosis. These not only include a change in the net uptake of endocytic cargo in an individual cell, but also in the size distribution of vesicles, variety of vesicle shapes, the number of vesicles, their sub-cellular localization, and their degree of clustering. Because these cellular properties vary greatly within a population of genetically identical cells, a comprehensive and quantitative understanding of cellular phenotypes in mammalian tissue culture cells faces the problem of quantifying variability at (at least) two levels. First, at the level of a population of cells, in which different cellular states may have different vesicle patterns, and second at the level of vesicle populations within a single cell, which may consist of multiple specific subpopulations of vesicles that differently react to perturbations. In both cases, the variability itself leads to the characteristic patterns cell biologists are familiar with, namely phenotypic patterns in a cell population, and vesicle patterns in a single cell. For the analysis of image-based high-throughput screens, we have developed an automated image analysis pipeline to detect vesicular structures and to extract primary single-vesicle features describing different measures of each vesicles intensity, its area, its cargo contents, its shape, the number of vesicles per cell area, and the degree of overall as well as local vesicle
4 vi clustering in a single cell. We also implemented a Support Vector Machinebased filter to exclude out-of-focus, mitotic and apoptotic cells from our analysis. Although various algorithm packages can nowadays faithfully quantify a number of features of individual vesicles within single cells, these measurements are usually averaged over all vesicular objects detected in a single cell and a whole cell population. Although averaging simplifies analysis, it leads to a loss of information that obscures interesting observations. We therefore developed and applied an approach to avoid vesicle averaging when analyzing large numbers of images. We identified discrete vesicle subpopulations within single cells using multiple single vesicle features. It is shown that vesicle subpopulation modeling provides a quantitative, robust and correct description of vesicle patterns. This is necessary to accurately group single cells with similar vesicle patterns together and finally to achieve a quantitative description of the heterogeneity of cellular phenotypes within a population of (perturbed) cells in terms of discrete vesicle patterns. We applied our approach to identify changes in the abundance of vesicle subpopulations in the time course of cargo uptake and transport and to group kinases together according to their function to regulate vesicle patterns. Clustering can help to find groups of genes with similar phenotypic profiles, but the regulatory structure and hierarchy in the observed perturbation effects may be missed. To reveal regulatory mechanisms within a subsystem that may represent a potential signaling pathway, we applied Nested Effects Modeling (NEM) on the one hand to 50 Kinases that have shown very strong perturbation effects, on the other hand we have applied NEM to genes within modules that were found by clustering of the protein-protein interaction database String. Spatial organization and compartmentalization of intracellular vesicles is a signature of complex (nonlinear) interactions among many motors, organelles, and cytoskeletal filaments which are globally regulated by elaborate biochemical networks. To provide a firm theoretical ground for classification of our experimentally found vesicle patterns and to understand how they are regulated by the cell we set up a general agent-based model of intracellular transport of vesicles which are controlled by cytoskeleton-
5 vii based movements powered by molecular motors and by fusion. This model enables us to characterize the (often poorly known) function of genes by relating a vesicle pattern experimentally found upon depletion of single genes to the (functionally interpretable) parameter values of the corresponding simulated pattern. Zürich, September 2010 Mirko Birbaumer
6 Zusammenfassung Bild-basierte Screens in standardmässigen Gewebekulturzellen haben eine Vielzahl von zellulären Phänotypen im Zusammenhang von Endocytose zum Vorschein gebracht. Dazu zählen nicht nur Veränderungen in der Netto-Aufnahme von endozytischer Cargo in einer einzelnen Zelle, sondern auch die Grössenverteilung der Vesikel, verschiedene Vesikel Formen, die Zahl der Vesikel, die subzelluläre Lokalisation und der Grad der Clusterbildung. Da diese zellulären Eigenschaften innerhalb einer Population von genetisch identischen Zellen sehr unterschiedlich ausfallen, steht ein umfassendes und quantitatives Verständnis der zellulären Phänotypen in menschlichen Gewebekulturzellen vor dem Problem der Quantifizierung der Variabilität auf (mindestens) zwei Ebenen. Erstens auf der Ebene einer Population von Zellen, in denen die zellulären Zustände verschiedene Vesikel Muster aufweisen können, und zweitens auf der Ebene der Vesikel Populationen innerhalb einer einzelnen Zelle, die aus mehreren spezifischen Subpopulationen von Vesikeln bestehen können, die verschieden auf Störungen reagieren. In beiden Fällen führt die Variabilität auf das charakteristische Muster, mit welchem Zellbiologen vertraut sind, nämlich phänotypische Muster in einer Zellpopulation und verschiedene Muster von Vesikeln in einer einzelnen Zelle. Für die Analyse von bild-basierten High-Throughput-Screens haben wir eine automatisierte Bildanalyse-Pipeline zur Erkennung von vesikulären
7 x Strukturen entwickelt, die die primären Merkmale von einzelnen Vesikeln misst, insbesondere verschiedene Intensitätsmasse von Vesikeln, Vesikel Fläche, Cargo Gehalt, Vesikel Gestalt, Anzahl von Vesikeln pro Zelle, und Grad der allgemeinen als auch lokalen Clusterbildung von Vesikeln in einzelnen Zellen. Wir haben auch einen Support Vector Machine basierten Filter implementiert, um entweder unscharfe, mitotische oder apoptotische Zellen aus unserer Analyse auszuschliessen. Obwohl verschiedene Programme heute zuverlässig eine Reihe von Vesikel Merkmalen innerhalb einzelner Zellen quantifizieren können, werden diese Messungen dann in der Regel über alle detektierten vesikulären Objekte in einer einzelnen Zelle und über die ganze Zellpopulation gemittelt. Obwohl Mittelung die Analyse vereinfacht, führt dies zu einem Verlust an Informationen, die interessante Beobachtungen verunmöglicht. Deshalb haben wir einen Ansatz entwickelt und angewandt, um Mittelung über Vesikel Merkmale bei der Analyse grosser Anzahl von Bildern zu vermeiden. Wir haben diskrete Subpopulationen von Vesikeln innerhalb einzelner Zellen anhand einzelner Vesikel Merkmalen identifiziert. Es wird gezeigt, dass Modellierung aufgrund von Vesikel Subpopulationen eine quantitative, robuste und korrekte Beschreibung von Vesikel Mustern ermöglicht. Dies ist notwendig, um einzelne Zellen mit ähnlichen Mustern in Gruppen zusammenzufassen und schliesslich eine quantitative Beschreibung der Heterogenität von zellulären Phänotypen innerhalb einer Population von (gestörten) Zellen in Form von diskreten Vesikel Mustern zu erreichen. Wir haben unseren Ansatz angewandt, um Veränderungen bezüglich des Anteils an Vesikel Subpopulationen während des zeitlichen Verlaufs der Cargo Aufnahme und des Transports zu verfolgen und um Kinasen gemäss ihrer Funktion, Vesikel Muster zu regulieren, in Gruppen zusammenzufassen. Clustering is hilfreich, um Gene mit ähnlichem phänotypischem Profil in Gruppen zusammenzufassen, allerdings dürfte die regulatorische Struktur und die Hierarchie innerhalb der beobachteten Störungen dabei unbeachtet bleiben. Damit Regulierungsmechanismen innerhalb eines Subsystems enthüllt werden können, das einen möglichen Signalübertragungsweg darstellen könnte, haben wir Nested-Effects-Modeling (NEM) angewandt, einerseits für 50 Kinasen, die besonders starke Störeffekte gezeigt haben, andererseits haben wir NEM für Subsysteme von Genen benützt, die aufgrund der Protein-Protein Interaktionsdatenbank String gefunden
8 xi worden sind. Räumliche Organisation und Kompartimentierung von intrazellulären Vesikeln ist ein Merkmal von komplexen (nichtlinearen) Wechselwirkungen vieler Motorproteine, Organellen, Zytoskelett, die wiederum umfassend von raffinierten biochemischen Netzwerken reguliert werden. Um eine solide theoretische Grundlage für die Klassifizierung unserer experimentell gefundenen Vesikel Mustern aufzustellen und um zu verstehen, wie diese Muster von der Zelle reguliert werden, haben wir ein allgemeines agentenbasiertes Modell für intrazellulären Transport von Vesikeln aufgestellt. Der Transport von Vesikeln wird gesteuert einerseits durch Zytoskelett gebundene und von molekularen Motoren angetriebene Bewegung, andererseits durch Fusionsprozesse. Dieses Modell ermöglicht es uns, die (oft schlecht bekannte) Funktion von Genen zu charakterisieren, indem man versucht, die experimentell gefundenen Vesikel Muster, die infolge vom Knock-down von Genen zustande kamen, in Zusammenhang mit den (funktionell interpretierbaren) Parameterwerten der entsprechenden simulierten Muster zu bringen. Zürich, im September 2010 Mirko Birbaumer
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