Detailseite
Projekt Druckansicht

Die Entschlüsselung zellulärer Mechanismen in der Musterbildung embryonaler Stammzellen

Antragsteller Dr. Jakob Metzger
Fachliche Zuordnung Biophysik
Statistische Physik, Nichtlineare Dynamik, Komplexe Systeme, Weiche und fluide Materie, Biologische Physik
Förderung Förderung von 2015 bis 2017
Projektkennung Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 272597766
 
Erstellungsjahr 2018

Zusammenfassung der Projektergebnisse

Human embryonic stem cells are an invaluable tool for studying human aspects of embryonic development, for analyzing signaling pathways that determine differentiation and as disease models for human specific aspects of diseases. In my project, I worked on a combination of these aspects: 1. Pluripotent hESCs can be grown confined to circular micropatterns of 500µm diameter. When they are stimulated with BMP4, a ligand that in the embryo is thought to be secreted by the trophectoderm adjacent to the pluripotent epiblast, the cells self-organize into a circular arrangement of the three germ layer fates, thereby mimicking gastrulation. The mechanism of this was previously not understood. I therefore developed a model that includes a number of experimental results to predict the reaction and diffusion of inhibitors and activators of cell fate, successfully predicting the quantitative arrangement of the differentiated cell types. 2. Using hESCs as a model for Huntington’s disease, I uncovered phenotypes in genetically engineered cell lines that carry the Huntington mutation. In particular, these cells showed limited ability to self-organize into neural structures when differentiated towards neural precursors compared to the wild type cells. 3. In order to study differentiation of cells on a single cell level, I tracked live cells that carry a fluorescent reporter for a particular cell fate and analyzed the dynamics of the fate marker. I could show that endoderm fate acquisition is cell cycle dependent. 4. In order to analyze the size of neural rosettes on micropatterns that are hard to segment using conventional methods, I developed a framework that uses deep neural networks for segmentation. These networks reached human accuracy at segmenting rosettes, which is crucial for studying the effect of disease mutations on the self-organization potential of neural precursors. 5. In order to obtain a detailed comparison between in vivo and in vitro gastrulation, I collaborated with researchers that use mouse embryonic stem cells to mimic gastrulation on micropatterns as described above for hESCs, and then compare their results with the in vivo case. I developed image analysis software tailored to this problem that allowed accurate single-cell quantification of signaling and fate choices of the cells.

Projektbezogene Publikationen (Auswahl)

  • A balance between secreted inhibitors and edge-sensing controls gastruloid selforganization. Dev. Cell. 39, 302 (2016)
    Etoc F, Metzger JJ, Ruzo A, Kirst C, Yoney A, Ozair Z, Brivanlou AH, Siggia ED
    (Siehe online unter https://doi.org/10.1016/j.devcel.2016.09.016)
  • Self-organization of human embryonic stem cells on micropatterns. Nature Protocols, 11, 2223 (2016)
    Deglincerti A , Etoc F, Guerra M, Martyn I, Metzger JJ, Ruzo A, Simunovic M, Yoney A, Brivanlou AH, Siggia ED, Warmflash A
    (Siehe online unter https://doi.org/10.1038/nprot.2016.131)
  • Chromosomal instability during neurogenesis in Huntington's disease. Development 145, dev156844 (2018)
    Ruzo, A, Croft GF, Metzger JJ et al.
    (Siehe online unter https://doi.org/10.1242/dev.156844)
  • Micropattern differentiation of mouse pluripotent stem cells recapitulates embryo regionalized cell fate patterning. eLife 7, e32839 (2018)
    Morgani S, Metzger JJ, Nichols J, Siggia ED, Hadjantonakis AK
    (Siehe online unter https://doi.org/10.7554/eLife.32839)
 
 

Zusatzinformationen

Textvergrößerung und Kontrastanpassung