@phdthesis{Breuer2016, author = {Breuer, David}, title = {The plant cytoskeleton as a transportation network}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-93583}, school = {Universit{\"a}t Potsdam}, pages = {164}, year = {2016}, abstract = {The cytoskeleton is an essential component of living cells. It is composed of different types of protein filaments that form complex, dynamically rearranging, and interconnected networks. The cytoskeleton serves a multitude of cellular functions which further depend on the cell context. In animal cells, the cytoskeleton prominently shapes the cell's mechanical properties and movement. In plant cells, in contrast, the presence of a rigid cell wall as well as their larger sizes highlight the role of the cytoskeleton in long-distance intracellular transport. As it provides the basis for cell growth and biomass production, cytoskeletal transport in plant cells is of direct environmental and economical relevance. However, while knowledge about the molecular details of the cytoskeletal transport is growing rapidly, the organizational principles that shape these processes on a whole-cell level remain elusive. This thesis is devoted to the following question: How does the complex architecture of the plant cytoskeleton relate to its transport functionality? The answer requires a systems level perspective of plant cytoskeletal structure and transport. To this end, I combined state-of-the-art confocal microscopy, quantitative digital image analysis, and mathematically powerful, intuitively accessible graph-theoretical approaches. This thesis summarizes five of my publications that shed light on the plant cytoskeleton as a transportation network: (1) I developed network-based frameworks for accurate, automated quantification of cytoskeletal structures, applicable in, e.g., genetic or chemical screens; (2) I showed that the actin cytoskeleton displays properties of efficient transport networks, hinting at its biological design principles; (3) Using multi-objective optimization, I demonstrated that different plant cell types sustain cytoskeletal networks with cell-type specific and near-optimal organization; (4) By investigating actual transport of organelles through the cell, I showed that properties of the actin cytoskeleton are predictive of organelle flow and provided quantitative evidence for a coordination of transport at a cellular level; (5) I devised a robust, optimization-based method to identify individual cytoskeletal filaments from a given network representation, allowing the investigation of single filament properties in the network context. The developed methods were made publicly available as open-source software tools. Altogether, my findings and proposed frameworks provide quantitative, system-level insights into intracellular transport in living cells. Despite my focus on the plant cytoskeleton, the established combination of experimental and theoretical approaches is readily applicable to different organisms. Despite the necessity of detailed molecular studies, only a complementary, systemic perspective, as presented here, enables both understanding of cytoskeletal function in its evolutionary context as well as its future technological control and utilization.}, language = {en} } @phdthesis{Sin2016, author = {Sin, Celine}, title = {Post-transcriptional control of gene expression}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-102469}, school = {Universit{\"a}t Potsdam}, pages = {xxv, 238}, year = {2016}, abstract = {Gene expression describes the process of making functional gene products (e.g. proteins or special RNAs) from instructions encoded in the genetic information (e.g. DNA). This process is heavily regulated, allowing cells to produce the appropriate gene products necessary for cell survival, adapting production as necessary for different cell environments. Gene expression is subject to regulation at several levels, including transcription, mRNA degradation, translation and protein degradation. When intact, this system maintains cell homeostasis, keeping the cell alive and adaptable to different environments. Malfunction in the system can result in disease states and cell death. In this dissertation, we explore several aspects of gene expression control by analyzing data from biological experiments. Most of the work following uses a common mathematical model framework based on Markov chain models to test hypotheses, predict system dynamics or elucidate network topology. Our work lies in the intersection between mathematics and biology and showcases the power of statistical data analysis and math modeling for validation and discovery of biological phenomena.}, language = {en} }