|since 2012||Ph. D. student, Bioinformatics|
Buchmann Institute for Molecular Life Sciences
Johann-Wolfgang-Goethe-Universität Frankfurt am Main (Goethe University Frankfurt am Main, Germany)
Fluorescence microscopy, such as light-sheet-based fluorescence microscopy (LSFM) allows to acquire three dimensional biological specimens with high spatio-temporal resolution. However, the image data amount and complexity drastically increases demanding for automated methods to the extract meaningful quantitative information. With a background in bioinformatics, I develop tools intended to extract quantitative data from LSFM image data for large scale pattern analysis. I focus on the development and application of task-dependent image segmentation and algorithms for object identification, tracking and lineaging. I am particularly involved and active in the projects outlined below.
Development of Arabidopsis thaliana’s root system
We employ LSFM to study the dynamics of root system development in Arabidopsis thaliana. The plant is imaged under close-to-natural growth conditions which is essential for long-term observations of several days. In collaboration with Daniel von Wangenheim, a plant imaging and data processing pipeline has been successfully established to track the movement and lineage of all cells involved in lateral root development of Arabidopsis thaliana. The resulting data is analyzed for spatial and temporal patterns of cell dvisions (Wangenheim et. al., 2016).
Developmental biology with Tribolium castaneum
The red flour beetle, Tribolium castaneum, is taken as a model organism for developmental biology in our group. We established non-invasive long-time fluorescence live imaging for Tribolium embryos using LSFM (Strobl & Stelzer, 2014). A new mounting technique allows multi-view observation of the complete Tribolium embryogenesis for up to 120 hours (Strobl, Schmitz & Stelzer, 2015). Major embryogenic events such as gastrulation, germ band elongation, germ band retraction and dorsal closure are observed and analyzed in the same specimen. The embryo survives the imaging process, develops into an adult and produces fertile progeny. Together with Frederic Strobl, patterns of key developmental processes at cellular resolution are studied by following the movement and lineage of individiual cells in Troblium castaneum embryos.
Three dimensional multicellular spheroids have become an important model in 3D cell biology. Most cellular systems such as tissues have a three-dimensional organization. In our group, aspects of the development of tissue, living organisms or tumor growth is studied in these systems. Since spheroids closely resemble the situation in real tumors in the living organism they are investigated for drug and toxicity screening assays where different drug candidates are evaluated in terms of their therapeutic efficacy. We employ fluorescence microscopy, biochemical and molecular biology-based assays. In collaboration with Nariman Ansari, my particular contribution is to apply three-dimensional segmentation and tracking approaches in order to quantitatively evaluate drug effects on tumor spheroids of T47D human breast cancer cells.
- von Wangenheim D., Fangerau J., Schmitz, A., Smith, R. S., Leitte, H., Stelzer, E. H.K., & Maizel, A. (2016) Rules and self-organizing properties of post-embryonic plant organ cell division patterns. Current Biology, 26(4):157-159. doi:10.1016/j.cub.2015.12.047 Current Biology
- Strobl, F., Schmitz, A., & Stelzer, E. H.K. (2015) Live imaging of Tribolium castaneum embryonic development using light-sheet–based fluorescence microscopy. Nature Protocols, 10:1486-1507. doi:10.1038/nprot.2015.093 PubMed
- Mathew, B., Schmitz, A., Muñoz-Descalzo, S., Ansari, N., Pampaloni, F., Stelzer, E. H.K., & Fischer, S. C. (2015) Robust and automated three-dimensional segmentation of densely packed cell nuclei in different biological specimens with Lines-of-Sight decomposition. BMC Bioinformatics, 16(1):187. doi: 10.1186/s12859-015-0617-x PubMed
- Schäfer, T., Schäfer, H. & Schmitz, A. (2013) Image database analysis of Hodgkin lymphoma. Comput. Biol. Chem. 46:1–7. PubMed
- Schmitz, A., Schäfer, T., Schäfer, H., Döring, C., Ackermann, J., Dichter, N., Hartmann, S., Hansmann, M.-L., Koch, I. (2012) Automated Image Analysis of Hodgkin lymphoma. Dagstuhl Seminar 12291 "Structure Discovery in Biology: Motifs, Networks & Phylogenies" arXiv.org