Our cells are experts at navigating inherently noisy and complicated environments.
EMBL researchers are using theoretical physics approaches to uncover fundamental principles behind how cells use complex information to self-organise.
www.embl.org/news/science...
Posts by Jenna Elliott
Figure 1 from the preprint
Check out our preprint! With new molecular mechanisms, 140 subtomogram averages, and ~600 annotated cells under different conditions, we @embl.org were able to describe bacterial populations with in-cell #cryoET. And there’s a surprise at the end 🕵️
www.biorxiv.org/content/10.1...
#teamtomo
Congratulations, Michael Dorrity and Anna Erzberger!
The two EMBL Heidelberg group leaders have received ERC Starting Grants that will enable ambitious projects related to developmental timing and tissue self-organisation, respectively.
Learn more: www.embl.org/news/awards-...
Want to acquire #ExM images like this and help us understand the true extent of cytoskeletal diversity across the tree of life? This position might be for you!
embl.wd103.myworkdayjobs.com/en-US/EMBL/j...
With @dudinlab.bsky.social
@embl.org @biology-unige.bsky.social @moorefound.bsky.social
Thanks for sharing! I think scale-hierarchical “zones” offer an interesting lens on sub-cellular information flow. I’d be curious how compression, selection, or computation at each scale could be approached analytically, especially with physical and emergent properties shaping the flow.
11/ We're excited about the implications for membrane organisation, cellular decision-making, and how physical interactions can encode computational logic in biology. 📝 Check out the full paper here: arxiv.org/abs/2506.14739 We would love to hear your thoughts! 👇
10/ Huge thanks to my incredible coauthors Hiral Shah (@hiralshah.bsky.social), Roman Belousov, Gautam Dey (@gautamdey.bsky.social), and Anna Erzberger -- this project was a true collaboration, combining theory, modelling, and experimental validation. So grateful for your brilliance and support!
Expansion microscopy image, and accompanying sketch, of S. arctica nucleus with labelled microtubules and nuclear pore complexes.
9/ The observed patterns matched our model, and their parameters place these systems near the predicted optimal filtering regime -- These NPCs may act as efficient spatial thresholding filters! #Microscopy #QuantBio #Microtubules #UExM
8/ To test our predictions, we used expansion microscopy to examine distributions of nuclear pore complexes in Sphaeroforma arctica.
Plot of the mutual information between input energy profiles and output density profiles as a function of parameter ratio, for various input dimensions.
7/ Surprisingly (and excitingly!), when we analysed real biological systems from the literature, their particle parameters often fell within these optimal regions, suggesting that cells might indeed be taking advantage of this mechanism! #EvoDevo #Biophysics
6/ We identified an optimal phase space region where this classification works best. Interestingly, this region depends on the dimensionality of the input signal.
5/ Cells could perform a binary classification of spatial cues based on particle organisation -- transmitting only “relevant” information across compartment interfaces (like membranes). It’s a simple yet energy-efficient and powerful way for cells to decide what signals to pass on. #CellSignaling
4/ The particle distribution therefore acts like a spatial thresholding filter, providing a new way to think about how membrane-bound structures manage information flow. #MembraneBiology #InformationProcessing
Plot of equilibrium particle density dependence on environment interaction energy, which takes the form of a sigmoid when there are particle repulsions, and is exponential if not.
3/ We found that when surface-associated particles (e.g., proteins) repel each other and interact with nearby structures, their density exhibits a nonlinear, sigmoidal response to spatial features in the environment.
2/ Living systems use chemical signals to communicate, but physical properties like repulsion between particles also shape how information flows. We propose a physics-based mechanism by which cells could interpret spatial cues. #CellBiology #Biophysics #Physics
Sketch of membrane-enclosed compartment with particles on its surface, which interact with an adjacent structure
🧵 🧪 1/ Hi! I’m excited to share our latest work, now on arXiv:
Repulsive particle interactions at cellular interfaces enable selective information processing (arxiv.org/abs/2506.14739)
Where we explore how the physical properties of living systems can help cells process spatial information.