For the science, see our Tweetorial 🧵: bsky.app/profile/iber...

Kudos to the @ethz.ch Animal Facility for championing transparency! 🙏

#3Rs #AnimalWelfare #LungDevelopment #COPD

We're fully committed to 3Rs:
♻️ Replace – comp models & simulations go beyond what animal data alone could reveal
📉 Reduce – just 7 pregnant females (severity degree 0) & reuse of 20-year-old datasets instead of new experiments
🔬 Refine – SkelePlex & our pipeline extract max insight from min data

From the fractal structure of the lungs to diagnosing COPD Dagmar Iber and her team at the Department of Biosystems Science and Engineering in Basel aim to understand how the lungs develop in the foetus so they are fully functional by the time the baby is bor...

📖 @ethz.ch feature: ethz.ch/en/research/... 🧵(2/4)

The @ethz.ch Animal Facility featured our work on how the lung gets its energy-efficient shape and how it remodels in disease like COPD 🐭🫁 — as part of their spotlight on responsible animal research. 🧵(1/4)

Many processes influence boundary sharpness and placement: gene regulatory interactions, spatial averaging, cell sorting to name a few.

Our analysis shows that cellular readout noise is the main determinant of boundary sharpness, i.e. #TZW.

Preprint: doi.org/10.64898/202...

🧵 6/6

By matching simulations with measurement of #TZW & #positional #error, we inferred kinetic and readout noise levels - and found them in the reported range.

This further supports that reliable long-range morphogen patterning is feasible with physiological noise levels:
x.com/DagmarIber/s...

🧵 5/6

We uncover a trade-off regarding cell size:
• Larger cells yield sharper boundaries (smaller #TZW)
• Smaller cells reduce variability in boundary position between embryos (lower positional error)

The measured cell size in the neural tube perfectly balances boundary sharpness and precision.

🧵 4/6

Our theoretical & computational analysis shows that #TZW is primarily set by #noise in the #cellular #readout process, not by fluctuations in the morphogen gradient itself.

For exponential gradients, a noisy readout threshold naturally yields a position-independent TZW.

🧵 3/6

According to prevailing theory, transition zones should widen exponentially with distance from the morphogen source, due to stochastic effects at low morphogen copy numbers.

#Contrary, we find that #TZW remains about #constant, independent of readout position and developmental timepoint.

🧵 2/6

What determines the sharpness of cell fate boundaries in gradient-based patterning?

We quantified #transition #zone #widths (TZW) across seven progenitor domain boundaries spanning the entire dorsal-ventral axis of the developing #mouse #neural #tube.

Preprint: doi.org/10.64898/202...

🧵 1/6

Many processes influence boundary sharpness and placement: gene regulatory interactions, spatial averaging, cell sorting to name a few.

Our analysis shows that cellular readout noise is the main determinant of boundary sharpness, i.e. #TZW.

Preprint: doi.org/10.64898/202...

🧵 6/6

By matching simulations with measurement of #TZW & #positional #error, we inferred kinetic and readout noise levels - and found them in the reported range.

This further supports that reliable long-range morphogen patterning is feasible with physiological noise levels:
x.com/DagmarIber/s...

🧵 5/6

Paper & poster are available on the COMSOL conference website: www.comsol.com/paper/direct...

"Within the competition to bring this field to a new level, SimuCell3D is remarkable and will mark a clear evolution of the topic."
🥁That’s what the committee said about this #SIBRemarkableOutputs 2024
👉Discover the output: tinyurl.com/53arz2rz
@iberd.bsky.social

The goal: make it easier for others to reproduce and extend these models within COMSOL.

We hope this serves as a generalizable reference for simulating collective cell behavior and pattern formation.

arxiv.org/pdf/2509.08930

This complements our earlier work introducing the DCM model 👉 bsky.app/profile/iber...

That previous paper focused on the biological questions and mathematical framework.

Here, we focus on the practical COMSOL #PIDE implementation: setup, BCs, 1D–3D, and Lagrangian reformulation for growth.

Out now: Simulating Organogenesis in #COMSOL: Tissue Patterning with Directed Cell Migration

We provide a detailed walkthrough of how to implement #DCM partial integro-differential equation models - enabling accessible simulations of tissue patterning and morphogenesis.

arxiv.org/pdf/2509.08930

Morphogen gradients can convey position and time in growing tissues Morphogen gradients are known to guide spatial patterning, but can they also encode time? Vetter and Iber propose that a co-expanding morphogen source generates transient signals, allowing cells to measure time without additional molecular clocks. The Sonic Hedgehog gradient in the mouse neural tube is used to show how this mechanism can act as a timer. Opposing gradients synchronize differentiation across the tissue, providing a simple, widely applicable strategy for coordinating space and time during development.

Online now: Morphogen gradients can convey position and time in growing tissues #newton #physics

Morphogen gradients can convey position and time in growing tissues Morphogen gradients are known to guide spatial patterning, but can they also encode time? Vetter and Iber propose that a co-expanding morphogen source generates transient signals, allowing cells to me...

Paper: doi.org/10.1016/j.ne...

Tweetorial: x.com/DagmarIber/s...

Our paper "Morphogen gradients can convey position and time in growing tissues" is now out in Newton ‪@cp-newton.bsky.social‬

Quite fitting to see this novel idea that morphogen gradients not only encode position, but can also time & synchronise development over long distances out in a new journal.

Directed cell migration is a versatile mechanism for rapid developmental pattern formation The evolution of multicellular organisms hinges on self-organization mechanisms that generate tissues with diverse functions. A central process is the breaking of symmetry to form spatial patterns fro...

📄 Read the full study here: doi.org/10.1101/2025...

🎯 Useful for: developmental biology, tissue engineering, pattern formation, and computational modeling

#DevBio #PatternFormation #CellMigration #Morphogenesis #ComputationalBiology

📌 Summary:

• #DCM is a rapid, robust mechanism for developmental pattern formation
• COMSOL FEM implementation makes DCM models numerically accessible
• #DCM patterning parameter ranges and timeframes
• Pattern Orientation via attraction anisotropy or directed tissue growth

👇Thread 🧵(10/11)

2. Dynamic #attraction #zones

Spatially varying cell attraction that changes with tissue growth can guide migrating cells, leading to precise large-scale patterning.

This mimics how tissues form rings, bands, or layered structures in vivo.

👇Thread 🧵(9/11)

We identify two mechanisms for guiding pattern orientation:

1. #Anisotropic #attraction
Cells pulling or migrating more strongly in one direction form aligned stripe-like patterns—e.g., during directional tissue growth.

👇Thread 🧵(8/11)

#DCM naturally leads to unoriented patterns—spots, labyrinths—similar to Turing-like systems.

But biological tissues often require oriented patterns to fulfill specific functions.

Can DCM produce stripes, too?

👇Thread 🧵(7/11)

Three key parameters drive the emergence and morphology of patterns:

• Initial density of motile cells
• Intercellular attraction strength
• Cell sensing radius

👇Thread 🧵(6/11)

Simulations and linear stability analysis allowed us to find #critical #conditions for pattern formation and predict #patterning #speed.

We show under which conditions #DCM can realistically pattern tissues in development.

👇Thread 🧵(5/11)

We developed a mathematical framework that represents a wide range of #DCM cues, e.g., chemotaxis, durotaxis, haptotaxis & a general Finite Element Method #FEM:

👉 1D, 2D, 3D
👉 arbitrary geometries & boundary conditions
👉 isotropic & anisotropic interactions
👉 fast, large-scale simulations

🧵(4/11)

To study #DCM, both discrete and continuum models have been used.

But:
👉 Discrete models are computationally expensive.

👉 Continuum models have required custom Finite Volume Method #FVM implementations—until now.

👇Thread 🧵(3/11)

During embryonic development, cellular tissues transition from uniform starting conditions into robust spatial patterns.

#DCM offers a particularly fast and versatile route to spontaneously symmetry breaks and pattern formation without tissue buckling.

🧵(2/11)