Publikationen

Tight junctions play an essential role in sealing tissues, by forming belts of adhesion strands around cellular perimeters. Recent work has shown that the condensation of ZO1 scaffold proteins is required for tight junction assembly. However, the mechanisms by which junctional condensates initiate at cell-cell contacts and elongate around cell perimeters remain unknown. Combining biochemical reconstitutions and live-cell imaging of MDCKII tissue, we found that tight junction belt formation is driven by adhesion receptor-mediated ZO1 surface condensation coupled to local actin polymerization. Adhesion receptor oligomerization provides the signal for surface binding and local condensation of ZO1 at the cell membrane. Condensation produces a molecular scaffold that selectively enriches junctional proteins. Finally, ZO1 condensates directly facilitate local actin polymerization and filament bundling, driving the elongation into a continuous tight junction belt. More broadly, our work identifies how cells couple surface condensation with cytoskeleton organization to assemble and structure adhesion complexes.

Autosomal dominant CDK13-related disease is characterized by congenital heart defects, dysmorphic facial features, and intellectual developmental disorder (CHDFIDD). Heterozygous pathogenic variants, particularly missense variants in the kinase domain, have previously been described as disease causing. Using the determination of a methylation pattern and comparison with an established episignature, we reveal the first hypomorphic variant in the kinase domain of CDK13, leading to a never before described autosomal recessive form of CHDFIDD in a boy with characteristic features. This highlights the utility of episignatures in variant interpretation, as well as a potential novel diagnostic approach in unsolved cases or for disease prognosis.

Anaphase is tightly controlled spatiotemporally to ensure proper separation of chromosomes.1,2,3 The mitotic spindle, the self-organized microtubule structure driving chromosome segregation, scales in size with the available cytoplasm.4,5,6,7 Yet, the relationship between spindle size and chromosome movement remains poorly understood. Here, we address this relationship during the cleavage divisions of the Drosophila blastoderm. We show that the speed of chromosome separation gradually decreases during the four nuclear divisions of the blastoderm. This reduction in speed is accompanied by a similar reduction in spindle length, ensuring that these two quantities are tightly linked. Using a combination of genetic and quantitative imaging approaches, we find that two processes contribute to controlling the speed at which chromosomes move in anaphase: the activity of molecular motors important for microtubule depolymerization and sliding and the cell cycle oscillator. Specifically, we found that the levels of multiple kinesin-like proteins important for microtubule depolymerization, as well as kinesin-5, contribute to setting the speed of chromosome separation. This observation is further supported by the scaling of poleward flux rate with the length of the spindle. Perturbations of the cell cycle oscillator using heterozygous mutants of mitotic kinases and phosphatases revealed that the duration of anaphase increases during the blastoderm cycles and is the major regulator of chromosome velocity. Thus, our work suggests a link between the biochemical rate of mitotic exit and the forces exerted by the spindle. Collectively, we propose that the cell cycle oscillator and spindle length set the speed of chromosome separation in anaphase.

Fluorescence correlation spectroscopy (FCS) enables the measurement of fluctuations at fast timescales (typically few nanoseconds) and with high spatial resolution (tens of nanometers). This single-molecule measurement has been used to characterize single-molecule transport and flexibility of polymers and biomolecules such as DNA and RNA. Here, we apply this technique as dual-color fluorescence cross-correlation spectroscopy (dcFCCS) to identify the motor function of the tethering protein EEA1 and the small GTPase Rab5 by probing the flexibility changes through end-monomer fluctuations.

Cholangiocarcinoma (CCA) is a very difficult-to-treat cancer. Chemotherapies are little effective and response to immune checkpoint inhibitors is limited. Therefore, new therapeutic strategies need to be identified.

Quality control procedures play a pivotal role in ensuring the reliability and consistency of data generated in mass spectrometry-based proteomics laboratories. However, the lack of standardized quality control practices across laboratories poses challenges for data comparability and reproducibility. In response, we conducted a harmonization study within proteomics laboratories of the Core for Life alliance with the aim of establishing a common quality control framework, which facilitates comprehensive quality assessment and identification of potential sources of performance drift. Through collaborative efforts, we developed a consensus quality control standard for longitudinal assessment and adopted common processing software. We generated a 4-year longitudinal data set from multiple instruments and laboratories, which enabled us to assess intra- and interlaboratory variability, to identify causes of performance drift, and to establish community reference values for several quality control parameters. Our study enhances data comparability and reliability and fosters a culture of collaboration and continuous improvement within the proteomics community to ensure the integrity of proteomics data.

We show that the resolution-dependent loss of bimolecular reactions in spatiotemporal Reaction-Diffusion Master Equations (RDMEs) is in agreement with the mean-field Collins-Kimball (C-K) theory of diffusion-limited reaction kinetics. The RDME is a spatial generalization of the chemical master equation, which enables studying stochastic reaction dynamics in spatially heterogeneous systems. It uses a regular Cartesian grid to partition space into locally well-mixed reaction compartments and treats diffusion as a jump reaction between neighboring grid cells. As the chance for reactants to be in the same grid cell decreases for smaller cell widths, the RDME loses bimolecular reactions in finer grids. We show that for a single homo-bimolecular reaction, the mesh spacing can be interpreted as the reaction radius of a well-mixed C-K rate. Then, the bimolecular reaction loss is consistent with diffusion-limited kinetics in the mean-field steady state. In this interpretation, the constant in a bimolecular reaction propensity is no longer the macroscopic reaction rate but the rate of the ballistic C-K step. For the same grid resolution, different diffusion models in RDME, such as those based on finite differences and Gaussian jumps, represent different reaction radii.

Fluorocarbon oils are uniquely suited for many biomedical applications due to their inert, bioorthogonal properties. In order to interface fluorocarbon oils with biological systems, non-ionic fluorosurfactants are necessary. However, there is a paucity of non-ionic fluorosurfactants with low interfacial tension (IFT) to stabilize fluorocarbon phases in aqueous environments (such as oil-in-water emulsions). We developed non-ionic fluorosurfactants composed of a polyethylene glycol (PEG) segment covalently bonded to a flexible perfluoropolyether (PFPE) segment that confer low IFTs between a fluorocarbon oil (HFE-7700) and water. The synthesis of a panel of surfactants spanning a molecular weight range of 0.64-66 kDa with various hydrophilic-lipophilic balances allowed for identification of minimal IFTs, ranging from 1.4 to 17.8 mN m-1. The majority of these custom fluorosurfactants display poor solubility in water, allowing their co-introduction with fluorocarbon oils and minimal leaching. We applied the PEG5PFPE1 surfactant for mechanical force measurements in zebrafish, enabling exceptional sensitivity.

We use a combination of unsupervised clustering and sparsity-promoting inference algorithms to learn locally dominant force balances that explain macroscopic pattern formation in self-organized active particle systems. The self-organized emergence of macroscopic patterns from microscopic interactions between self-propelled particles can be widely observed in nature. Although hydrodynamic theories help us better understand the physical basis of this phenomenon, identifying a sufficient set of local interactions that shape, regulate and sustain self-organized structures in active particle systems remains challenging. We investigate a classic hydrodynamic model of self-propelled particles that produces a wide variety of patterns, such as asters and moving density bands. Our data-driven analysis shows that propagating bands are formed by local alignment interactions driven by density gradients, while steady-state asters are shaped by a mechanism of splay-induced negative compressibility arising from strong particle interactions. Our method also reveals analogous physical principles of pattern formation in a system where the speed of the particle is influenced by the local density. This demonstrates the ability of our method to reveal physical commonalities across models. The physical mechanisms inferred from the data are in excellent agreement with analytical scaling arguments and experimental observations.