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epimechfc.bsky.social
epithelial mechanics fan club
@epimechfc.bsky.social
📚 We're your source for papers on various #EpithelialMechanics topics 🔍 & platform to share your research and passion 🧫🔬

Like to write a thread? Please DM us!
💬 @onenimesa.bsky.social & @juliaeckert.bsky.social

👉 https://epithelialmechanics.github.io
In many developmental systems, cells don’t read out pre-established gradients, but interact to self-organize shapes. How can we quantify the information in self-organized patterns? We recently proposed how to measure the total information in a pattern.

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November 15, 2025 at 8:00 AM
Beyond the fly, many other systems are controlled by morphogens. The patterning of the vertebrate neural tube is controlled by two opposing gradients, which together provide high spatial precision for cell decisions.

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November 15, 2025 at 8:00 AM
For a comprehensive review on the history, concept, and mathematics of PI, check out “The many bits of positional information” by Gasper Tkacik and @thomasgregor.bsky.social.

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November 15, 2025 at 8:00 AM
Could one measure the information in such gradients? Combining imaging and information theory, @thomasgregor.bsky.social, William Bialek & Co. measured 4.2 bits of PI in the early fly gap genes (downstream of Bicoid) – enough for each cell to infer its position.

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November 15, 2025 at 8:00 AM
20 years later, the first morphogen molecule was discovered: Driever & Nüsslein-Volhard discovered that Bicoid mRNA placed by the mother fly at the anterior of the embryo establishes a gradient and controls cell fate.

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November 15, 2025 at 8:00 AM
During development, stem cells decide their fate based on input chemicals, called morphogens. In 1967, Lewis Wolpert proposed that gradients of such chemicals could tell cells where they are in the tissue, and thus carry positional information (PI).

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November 15, 2025 at 8:00 AM
Hi, I’m David Brückner @davidbrueckner.bsky.social.

I’ll take you through how cells in a tissue can use information distributed by biochemical gradients to make decisions, and how we can measure such positional information.

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November 15, 2025 at 8:00 AM
Dubuis, J. O., Tkačik, G., Wieschaus, E. F., Gregor, T., & Bialek, W. (2013). Positional information, in bits. Proceedings of the National Academy of Sciences, doi.org/10.1073/pnas... #EpithelialMechanics
November 14, 2025 at 8:01 AM
Petkova, M. D., Tkačik, G., Bialek, W., Wieschaus, E. F., & Gregor, T. (2019). Optimal decoding of cellular identities in a genetic network. Cell, #EpithelialMechanics doi.org/10.1016/j.ce...
November 13, 2025 at 11:00 AM
Tkačik, G., & Gregor, T. (2021). The many bits of positional information. Development, 148(2), dev176065. #EpithelialMechanicsReviews doi.org/10.1242/dev....
November 13, 2025 at 8:01 AM
Zagorski, M., Tabata, Y., Brandenberg, N., Lutolf, M. P., Tkačik, G., Bollenbach, T., ... & Kicheva, A. (2017). Decoding of position in the developing neural tube from antiparallel morphogen gradients. Science, #EpithelialMechanics doi.org/10.1126/scie...
November 11, 2025 at 8:00 AM
Brückner, D. B., & Tkačik, G. (2024). Information content and optimization of self-organized developmental systems. Proceedings of the National Academy of Sciences, #EpithelialMechanics www.pnas.org/doi/10.1073/...
November 10, 2025 at 8:00 AM
Beussman, K. M., Mollica, M. Y., Leonard, A., Miles, J., Hocter, J., ..., Thomas, W. E., & Sniadecki, N. J. (2023). Black dots: High-yield traction force microscopy reveals structural factors contributing to platelet forces. Acta biomaterialia, 163, 302–311. #EpithelialMechanics
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November 7, 2025 at 8:01 AM
Yousafzai, M. S., & Hammer, J. A. (2023). Using Biosensors to Study Organoids, Spheroids and Organs-on-a-Chip: A Mechanobiology Perspective. Biosensors, 13(10), 905. #EpithelialMechanicsReview
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November 6, 2025 at 8:01 AM
Marelli, M., Gadhari, N., Boero, G., Chiquet, M., & Brugger, J. (2014). Cell force measurements in 3D microfabricated environments based on compliant cantilevers. Lab Chip, 14(2), 286-293. #EpithelialMechanics
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November 5, 2025 at 8:01 AM
Wang, Y., Gunasekara, D. B., Reed, M. I., ..., Magness, S. T., & Allbritton, N. L. (2017). A microengineered collagen scaffold for generating a polarized crypt-villus architecture of human small intestinal epithelium. Biomaterials, 128, 44–55. #EpithelialMechanics
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November 4, 2025 at 8:01 AM
And if you’re interested in how dynamical systems have helped to elucidate the robustness and plasticity of fate and form in development from data, check out our other recent review.

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November 2, 2025 at 9:02 AM
There’s so much more to the #EpithelialMechanics of gastrulation than any simple model can capture. How might other cell behaviors factor into modeling the multi-scale mechanics of vertebrate gastrulation? Check out our recent review with Kees Weijer.

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November 2, 2025 at 9:02 AM
Chick is great for modelling and analysis because its nearly flat, but what about curved epithelial tissues? @sreejithsanthosh.bsky.social developed open-source code to extract DMs from arbitrary curved and dynamic surfaces.

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November 2, 2025 at 9:02 AM
Morphogenesis also affects which cells can communicate. Recasting morphogen advection-diffusion equations in cells’ moving frames, we found that DMs identify where flows most strongly affect diffusive fluxes, reshaping cells’ morphogen signaling ranges.

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November 2, 2025 at 9:02 AM
Model/experiment perturbations can also reshape the Attractor (primitive streak) into a ring, point, or thicker line, resembling other vertebrate gastrulation modes! (Note: Attractors aren’t actively attracting cells; they show where cells converged)

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November 2, 2025 at 9:02 AM
Comparing DMs is a great way to validate a model. By perturbing initial and boundary conditions in both model and experiment, we found that modular mechanisms generate the two Repellers. These mechanisms contribute independently to the embryo’s size and shape!
November 2, 2025 at 9:02 AM
To figure out how these structures emerge from >60k cells, we built a continuum mechanochemical model coupling velocities to dynamic myosin cables and contractility. The model predicts the flows, and the embryo’s transition from circular to pear-shaped.

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November 2, 2025 at 9:02 AM
Dynamical systems theory gives us tools to extract robust, frame-invariant kinematic features—coherent structures—from velocity or trajectory data. In #DevBio, the relevant ones are attractors and repellers, constituting the Dynamic Morphoskeleton (DM).

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November 2, 2025 at 9:02 AM
Which features of tissue flows are most robust and how do they emerge from #EpithelialMechanics?

I’m @alex-plum.bsky.social (@mattiaserra.bsky.social group) and I’ll be sharing some papers on characterizing and controlling avian gastrulation flows.
November 2, 2025 at 9:02 AM