Published in:Jülich : Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag, Schriften des Forschungszentrums Jülich. Reihe Schlüsseltechnologien / Key Technologies 130, XVI, 217 S. (2016). = RWTH Aachen, Diss., 2016
Language:
English
ISBN:
978-3-95806-167-5
ISSN:
1866-1807
Origination:
Footnote:
Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
Description:
Significant cell-to-cell variation with respect to growth, stress resistance, and other cellular traits are observed in clonal microbial populations [1]. Advances in lab-on-a-chip research and time-lapse microscopy have recently extended the experimental capabilities to observe the development of individual cells with unprecedented spatial and temporal resolution. In combination with appropriate cultivation devices, e.g., custom microfluidic lab-on-a-chip devices [2], image sequences are acquired for hundreds of developing populations in parallel under controlled environmental conditions. With the possibility to generate such large-scale datasets, the role of image analysis has become a crucial step for the elicitation of quantitative, time-resolved information for direct interpretation as well as modeling purposes. We have developed an extensible image analysis pipeline for the evaluation of time-lapse videos of the industrially competitive amino-acid producer $\textit{Corynebacterium glutamicum}$. The pipeline has been optimized for the identification of cells in crowded environments, tracking of cells with large spatial displacements, and the extraction of a multitude of cellular characteristics, for instance, cell morphology and fluorescence reporter intensities. The presented pipeline is implemented as a plugin for the well established ImageJ(2) platform. The platform provides advanced data structures and allows for visual controls of workflow composition and parameters. The underlying service architecture promotes extensibility of modules and flexibility to use implementations in alternative contexts. The combination of microfluidic system, live-cell imaging setup, and image analysis techniques is capable to address challenges of population heterogeneity in microbial populations even at low temporal resolution. While the analysis platform has been applied for a variety of studies, applications from two fields are highlighted in this thesis. First, investigations of microbial growth and morphology of ...