Dr. C. Schröter
The ordered differentiation of cells during the development of multicellular organisms is one of the most fascinating phenomena in biology. How do cells know which fate to adopt at the right time and place?
Now that most of the important genes and proteins involved in differentiation decisions have been identified, I believe the answer to this question lies in elucidating the functions of the interaction networks formed by these molecules. In particular, we need to understand how the dynamic activities of molecular networks guide cell fate choice. This requires quantitative, time-resolved and simultaneous measurements of the activity of network components in single cells. These data can then inform and constrain mathematical models to describe the behavior of these networks, and to formulate generic rules of the connection between network dynamics and fate decisions. Understanding the regulation of cell differentiation at this level is an attractive intellectual challenge in itself; furthermore, it will be crucial for the targeted differentiation of stem cells for regenerative approaches in vitro, and for the development of novel treatments in cases where cell fate choice fails, such as congenital diseases and cancer.
Differentiating mES cells expressing a fluorescently tagged transcription factor (red), a signaling reporter (green) and a nuclear marker for cell tracking (blue).
My lab tackles this task using mainly mouse embryonic stem (mES) cells as experimental system. Mouse ES cells can self-renew in the culture dish, and retain the remarkable ability to differentiate into all embryonic cell types in vitro and in vivo (Fig. 1). This makes them an ideal system to follow in individual live cells the molecular dynamics that underlie cell fate decisions of mammalian development. In the medium term we plan to extend our experimental toolkit to organoid systems (self-organising cellular aggregates) and the mouse embryo to test the dynamics of signaling networks in three-dimensional cell populations.
Modeling the fate decisions of mouse preimplantation development in ES cells shows that a transcription factor threshold determined by Fgf/MAPK signaling controls PrE differentiation by modulating a bistable genetic switch. See Schröter et al, bioRxiv 2015, for details.[weniger]
Modeling the fate decisions of mouse preimplantation development in ES cells shows that a transcription factor threshold determined by Fgf/MAPK signaling controls PrE differentiation by modulating a bistable genetic switch. See Schröter et al, bioRxiv 2015, for details.
I have used the fate decision between the epiblast (Epi) and the primitive endoderm (PrE) fate as a simple test case to study the integration of transcriptional and signaling inputs in cell-fate decision-making. This fate decision occurs between day 3.0 and day 4.5 of embryonic development in cells of the mouse preimplantation blastocyst (Fig. 1A). By recreating this decision in cultured mES cells (Fig. 1B), I could measure the activity of transcriptional regulators and signaling pathways involved in this decision in single cells by multi-color live imaging. I found that the transcriptional networks underlying the two fates form a mutual repression circuit that functions as a bistable switch. Furthermore, I could show that Fgf/MAPK signaling sets the switching threshold of this circuit and thereby controls the proportion of cells adopting the PrE fate. This is a novel principle for the role of signaling in cell-fate decisions, and may be of general relevance in contexts where the proportions of cells with specific fates have to be balanced.
A preprint of this work is available on the bioRxiv here.
Quantitative encoding and decoding of extracellular signals
Over the last decades we have learned a lot about the links between particular signaling molecules and specific cell fates in development. However, we still know very little about the features of extracellular signals that cells measure – do they simply detect the presence or absence of ligands, or do they read their concentration, their dynamic changes, or a combination of the two? And if signaling pathways can detect quantitative ligand information, how do they encode this information inside the cell?
One attractive hypothesis is that the dynamic activation pattern of signaling pathways stores information about extracellular ligand concentrations. We want to test this idea by investigating signaling dynamics in individual mES cells as they differentiate towards different lineages. We also want to find out how dynamic signaling patterns are turned into distinct stable gene expression programs. We will start to do this by focusing on the Fgf/MAPK signaling system, because of its importance for many cell fate decisions in the early embryo, and because an extensive toolkit of live cell reporters for this signaling pathway is available. In the future we will look at a range of extracellular ligands, and ask whether there exist generic principles for information encoding by intracellular signaling pathways.
Integration of signals during development
Multi-color reporter systems to interrogate the integration of diverse inputs driving fate decisions in individual ES cells.[weniger]
Multi-color reporter systems to interrogate the integration of diverse inputs driving fate decisions in individual ES cells.
Developmental cell fate decisions are usually controlled by a combination of signals. How do the cells integrate diverse cues and compute decisions? For the decision to adopt a primitive endoderm fate, we could show that the function of the extracellular FGF signal is to set the threshold of GATA transcription factor that cells need to experience in order to differentiate. Besides its role in primitive endoderm development, FGF/MAPK signaling controls several fate decision of early mammalian development in combination with a range of additional inputs. Is setting activity thresholds a generic mode of action for FGF/MAPK signaling? We will test this by performing multiplexed measurements of signaling dynamics for several pathways, and investigate how they relate to fate choice.
Spatial arrangement of signaling in cell populations
Extracellular signals have two main functions in developing and homeostatic tissues: They specify differentiation programs in individual cells, and they define coherent groups of cells that will adopt specific functions. We still now very little about how precisely do signaling molecules define three-dimensional domains of cells, how well defined the borders of signaling domains are, and how populations deal with potential signaling heterogeneities between individual cells. To address these questions, we will use novel organoid systems and the mouse embryo to investigate cell-signaling in three-dimensional cell populations, and apply 3D imaging techniques. This will provide insight into how signals function in cell populations, and how they organize and coordinate differentiation decisions in three dimensions.