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Cells change their sensitivity to an EGF morphogen gradient to control EGF-induced gene expression
Jeroen Sebastiaan van Zon1, Simone Kienle2, Guizela Huelsz-Prince2
11] Departments of Physics and Biology and Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [2] FOM Institute AMOLF, Science Park 104, 1098 XG Amsterdam, The Netherlands.
Nature Communications
|May 12, 2015
Summary
Cells interpret morphogen gradients by dynamically increasing sensitivity to signals like LIN-3/EGF. This study reveals a rapid switch in Notch ligand expression during Caenorhabditis elegans development, independent of the signal itself.
Area of Science:
- Developmental biology
- Molecular biology
- Systems biology
Background:
- Morphogen gradients provide quantitative positional information crucial for embryonic development.
- Understanding how cells interpret these gradients, particularly dynamic responses, remains a key challenge.
Purpose of the Study:
- To investigate the quantitative interpretation of morphogen gradients by cells.
- To elucidate the mechanism underlying dynamic gene expression changes in response to morphogen signals.
Main Methods:
- Utilized a novel integrative approach combining single-mRNA resolution gene expression measurements.
- Employed mathematical modeling to analyze the morphogen induction process.
- Focused on LIN-3/Epidermal Growth Factor (EGF) induced Notch ligand expression during Caenorhabditis elegans vulva development.
Main Results:
- Observed highly dynamic, abrupt transitions in LIN-3/EGF-induced Notch ligand expression.
- Confirmed similar dynamic expression patterns in divergent wild C. elegans isolates.
- Demonstrated that a dynamic increase in cell sensitivity to LIN-3/EGF drives the transition, independent of LIN-3/EGF presence.
Conclusions:
- Cellular interpretation of morphogen gradients involves dynamic sensitivity modulation.
- This dynamic sensitivity mechanism is conserved across C. elegans isolates.
- The integrative approach offers a framework for studying morphogen gradient interpretation in diverse biological systems.
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