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Publications in Biophysics by NOMIS researchers

BMP-dependent patterning of ectoderm tissue material properties modulates lateral mesendoderm cell migration during early zebrafish gastrulation

NOMIS Researcher(s)

Published in

March 8, 2025

Cell migration is a fundamental process during embryonic development. Most studies in vivo have focused on the migration of cells using the extracellular matrix (ECM) as their substrate for migration. In contrast, much less is known about how cells migrate on other cells, as found in early embryos when the ECM has not yet formed. Here, we show that lateral mesendoderm (LME) cells in the early zebrafish gastrula use the ectoderm as their substrate for migration. We show that the lateral ectoderm is permissive for the animal-pole-directed migration of LME cells, while the ectoderm at the animal pole halts it. These differences in permissiveness depend on the lateral ectoderm being more cohesive than the animal ectoderm, a property controlled by bone morphogenetic protein (BMP) signaling within the ectoderm. Collectively, these findings identify ectoderm tissue cohesion as one critical factor in regulating LME migration during zebrafish gastrulation.

Partnership(s)
,

Research field(s)
Molecular Biology, Biophysics

DOI
10.1016/j.celrep.2025.115387

AI-based approach to dissect the variability of mouse stem cell-derived embryo models

NOMIS Researcher(s)

Published in

February 19, 2025

Recent advances in stem cell-derived embryo models have transformed developmental biology, offering insights into embryogenesis without the constraints of natural embryos. However, variability in their development challenges research standardization. To address this, we use deep learning to enhance the reproducibility of selecting stem cell-derived embryo models. Through live imaging and AI-based models, we classify 900 mouse post-implantation stem cell-derived embryo-like structures (ETiX-embryos) into normal and abnormal categories. Our best-performing model achieves 88% accuracy at 90 h post-cell seeding and 65% accuracy at the initial cell-seeding stage, forecasting developmental trajectories. Our analysis reveals that normally developed ETiX-embryos have higher cell counts and distinct morphological features such as larger size and more compact shape. Perturbation experiments increasing initial cell numbers further supported this finding by improving normal development outcomes. This study demonstrates deep learning’s utility in improving embryo model selection and reveals critical features of ETiX-embryo self-organization, advancing consistency in this evolving field.

Research field(s)
Bioinformatics, Artificial Intelligence & Image Processing, Biophysics, Developmental Biology

DOI
10.1038/s41467-025-56908-5

Geometry-driven migration efficiency of autonomous epithelial cell clusters

NOMIS Researcher(s)

Published in

June 19, 2024

The directed migration of epithelial cell collectives through coordinated movements plays a crucial role in various physiological processes and is increasingly understood at the level of large confluent monolayers. However, numerous processes rely on the migration of small groups of polarized epithelial clusters in complex environments, and their responses to external geometries remain poorly understood. To address this, we cultivate primary epithelial keratocyte tissues on adhesive microstripes to create autonomous epithelial clusters with well-defined geometries. We show that their migration efficiency is strongly influenced by the contact geometry and the orientation of cell–cell contacts with respect to the direction of migration. A combination of velocity and polarity alignment with contact regulation of locomotion in an active matter model captures quantitatively the experimental data. Furthermore, we predict that this combination of rules enables efficient navigation in complex geometries, which we confirm experimentally. Altogether, our findings provide a conceptual framework for extracting the interaction rules of active systems from their interaction with physical boundaries, as well as design principles for collective navigation in complex microenvironments.

Research field(s)
Biophysics

DOI
10.1038/s41567-024-02532-x

Disentangling cadherin-mediated cell-cell interactions in collective cancer cell migration

NOMIS Researcher(s)

Published in

January 4, 2022

Cell dispersion from a confined area is fundamental in a number of biological processes, including cancer metastasis. To date, a quantitative understanding of the interplay of single-cell motility, cell proliferation, and intercellular contacts remains elusive. In particular, the role of E- and N-cadherin junctions, central components of intercellular contacts, is still controversial. Combining theoretical modeling with in vitro observations, we investigate the collective spreading behavior of colonies of human cancer cells (T24). The spreading of these colonies is driven by stochastic single-cell migration with frequent transient cell-cell contacts. We find that inhibition of E- and N-cadherin junctions decreases colony spreading and average spreading velocities, without affecting the strength of correlations in spreading velocities of neighboring cells. Based on a biophysical simulation model for cell migration, we show that the behavioral changes upon disruption of these junctions can be explained by reduced repulsive excluded volume interactions between cells. This suggests that in cancer cell migration, cadherin-based intercellular contacts sharpen cell boundaries leading to repulsive rather than cohesive interactions between cells, thereby promoting efficient cell spreading during collective migration.

Research field(s)
Health Sciences, Biomedical Research, Biophysics

DOI
10.1016/j.bpj.2021.12.006

Improved applicability and robustness of fast cryo-electron tomography data acquisition

NOMIS Researcher(s)

Published in

November 1, 2019

The power of cryo-electron tomography (cryoET) lies in its capability to characterize macromolecules in their cellular context. Structure determination by cryoET, however, is time-consuming compared to single particle approaches. A recent study reported significant acceleration of data acquisition by a fast-incremental single-exposure (FISE) tilt series scheme. Here we improved the method and evaluated its efficiency and performance. We show that (1) FISE combined with the latest generation of direct electron detectors speeds up collection considerably, (2) previous generation (pre-2017) double-tilt axis Titan Krios holders are also suitable for FISE data acquisition, (3) x, y and z-specimen shifts can be compensated for, and (4) FISE tilt series data can generate averages of sub-nanometer resolution. These advances will allow for a widespread adoption of cryoET for high-throughput in situ studies and high-resolution structure determination across different biological research disciplines.

Research field(s)
Health Sciences, Biomedical Research, Biophysics

DOI
10.1016/j.jsb.2019.08.006

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