% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@PHDTHESIS{Helfrich:809222,
      author       = {Helfrich, Stefan},
      title        = {{H}igh-{T}hroughput {L}ive-{C}ell {I}maging for
                      {I}nvestigations of {C}ellular {H}eterogeneity in
                      {C}orynebacterium glutamicum},
      volume       = {130},
      school       = {RWTH Aachen},
      type         = {Dr.},
      address      = {Jülich},
      publisher    = {Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
      reportid     = {FZJ-2016-02512},
      isbn         = {978-3-95806-167-5},
      series       = {Schriften des Forschungszentrums Jülich. Reihe
                      Schlüsseltechnologien / Key Technologies},
      pages        = {XVI, 217 S.},
      year         = {2016},
      note         = {RWTH Aachen, Diss., 2016},
      abstract     = {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 $\textit{C.
                      glutamicum}$. Here, the applicability of growth
                      quantification methods from bulk experiments to single-cell
                      data are investigated. A second application transfers this
                      knowledge to a profiling study of $\textit{C. glutamicum}$
                      in which the influence of medium composition (i.e., carbon
                      sources) on growth and morphology parameters is analyzed.
                      Furthermore, an analysis of the microbial SOS response and
                      the induction of aprophage in C. glutamicum is presented. To
                      that end, a dual reporter strain (i.e.,reporters for SOS
                      response and prophage induction) is cultivated in
                      lab-on-a-chip devices and analyzed using fluorescence
                      microscopy. From the time-resolved reporter outputs, we have
                      established a cellular state model that is used for
                      comprehensive population modeling.},
      cin          = {IBG-1},
      cid          = {I:(DE-Juel1)IBG-1-20101118},
      pnm          = {581 - Biotechnology (POF3-581)},
      pid          = {G:(DE-HGF)POF3-581},
      typ          = {PUB:(DE-HGF)11},
      urn          = {urn:nbn:de:0001-2017040706},
      url          = {https://juser.fz-juelich.de/record/809222},
}