We are known for running projects that tackle different aspects of organismal biology. We look at a range of live systems from a mechanistic point of view, trying to reverse engineer different aspects of multicellular life. Tracing the incremental advancements in development of multicellular organisms from a single cell perspective allows better understanding of the complexity of the entire organism or organ system in a final phase. That is why our main strength is developmental biology. The knowledge gained from developmental biology research is widely applied in regenerative medicine. Thus, we hope to improve human health via discovering new fundamental ideas about how development, stem cells, and regeneration work.
Our laboratory advances a broad spectrum of projects related to developmental biology, stem cells, EvoDevo and regenerative medicine. The methodology includes classical developmental biology approaches blended with single cell transcriptomics, 2D sequencing and 3D-reconstructions of tissues and organs based on optical or X-ray methods (micro-CT, synchrotron).
The neural crest stem cells is our primary model system, where we address general principles of cell fate choice, transcriptional and epigenetic control of a lineage progression, morphogenesis, and tissue shaping.
Lineage tracing
Cell type ablation
Cell selection via FACS
RNAscope
MERFISH (coming soon)
Slide-seq (coming soon)
Dataset clustering and integration
Trajectory analysis
Non-model organism exploration
Neural crest cells are embryonic progenitors that generate numerous cell types in vertebrates. With single-cell analysis, we show that mouse trunk neural crest cells become biased toward neuronal lineages when they delaminate from the neural tube, whereas cranial neural crest cells acquire ectomesenchyme potential dependent on activation of the transcription factor Twist1. The choices that neural crest cells make to become sensory, glial, autonomic, or mesenchymal cells can be formalized as a series of sequential binary decisions. Each branch of the decision tree involves initial coactivation of bipotential properties followed by gradual shifts toward commitment. Competing fate programs are coactivated before cells acquire fate-specific phenotypic traits. Determination of a specific fate is achieved by increased synchronization of relevant programs and concurrent repression of competing fate programs.