Publikationen

Organ injury triggers nonneuronal electric currents essential for regeneration. However, the mechanisms by which electrical signals are generated, sensed, and transmitted upon damage to promote organ growth remain unclear. Here, we uncover that organ repair relies on dynamic electrochemical coupling between membrane potential depolarization and intracellular signaling, essential to activate cell proliferation. By subsecond live imaging of locally injured zebrafish larval fins, we identify events across time and space: a millisecond, long-range, membrane depolarization gradient, followed by second-persistent intracellular calcium responses. In the subsequent hour, voltage sensing phosphatase senses the injury-driven membrane potential change and autonomously translates the electric signal intracellularly, promoting tissue-wide cell proliferation. Connecting these dynamics with an electrodiffusive model showed that ionic fluxes and electric potential become coupled in the fin's interstitial space, enabling organ-wide signal spreading. Our work reveals the coupling between fast electrical signals and slower intracellular signaling, ensuring complete organ recovery.

Electrochemical gradients are essential to the functioning of cells and form across membranes using active transporters. Here we show in contrast that condensed biomolecular systems-often termed condensates-sustain pH gradients without any external energy input. By studying individual condensates on the micrometre scale using a microdroplet platform, we reveal dense-phase pH shifts towards conditions of minimal electrostatic repulsion. We demonstrate that protein condensates can drive substantial alkaline and acidic gradients, which are compositionally tunable and can extend to complex architectures sustaining multiple unique pH conditions simultaneously. Through in silico characterization of human proteomic condensate networks, we further highlight potential wide-ranging electrochemical properties emerging from condensation in nature, while correlating intracellular condensate pH gradients with complex biomolecular composition. Together, the emergent nature of condensation shapes distinct pH microenvironments, thereby creating a regulatory mechanism to modulate biochemical activity in living and artificial systems.

Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning (ML) are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap encompasses key aspects of how ML is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities. We aim to give the reader an overview of the key developments and an understanding of possibilities and limitations of ML for microscopy. It will be of interest to a wide cross-disciplinary audience in the physical sciences and life sciences.

Early development across vertebrates and insects critically relies on robustly reorganizing the cytoplasm of fertilized eggs into individualized cells1,2. This intricate process is orchestrated by large microtubule structures that traverse the embryo, partitioning the cytoplasm into physically distinct and stable compartments3,4. Here, despite the robustness of embryonic development, we uncover an intrinsic instability in cytoplasmic partitioning driven by the microtubule cytoskeleton. By combining experiments in cytoplasmic extract and in vivo, we reveal that embryos circumvent this instability through two distinct mechanisms: either by matching the cell-cycle duration to the time needed for the instability to unfold or by limiting microtubule nucleation. These regulatory mechanisms give rise to two possible strategies to fill the cytoplasm, which we experimentally demonstrate in zebrafish and Drosophila embryos, respectively. In zebrafish embryos, unstable microtubule waves fill the geometry of the entire embryo from the first division. Conversely, in Drosophila embryos, stable microtubule asters resulting from reduced microtubule nucleation gradually fill the cytoplasm throughout multiple divisions. Our results indicate that the temporal control of microtubule dynamics could have driven the evolutionary emergence of species-specific mechanisms for effective cytoplasmic organization. Furthermore, our study unveils a fundamental synergy between physical instabilities and biological clocks, uncovering universal strategies for rapid, robust and efficient spatial ordering in biological systems.

Human liver ductal epithelium is morphologically, functionally, and transcriptionally heterogeneous. Under- standing the impact of this heterogeneity has been challenging due to the absence of systems that recapit- ulate this heterogeneity in vitro. Here, we found that human liver cholangiocyte organoids do not retain the complex cellular heterogeneity of the native ductal epithelium. Inspired by the knowledge of the cellular niche, we refined our previous organoid medium to fully capture the in vivo cellular heterogeneity. We em- ployed this refined system to analyze the relationships between human biliary epithelial cell states. In our refined model, cholangiocytes transition toward hepatocyte-like states through a bipotent state. Additionally, inhibiting WNT signaling enhances the differentiation capacity of the cells toward hepatocyte-like states. By capturing the in vivo cholangiocyte heterogeneity, our improved organoid model represents a platform to investigate the impact of the different liver ductal cell states in cell plasticity, regeneration, and disease.

Metabolic dysfunction-associated steatotic liver disease (MASLD) encompasses liver steatosis and metabolic dysfunction-associated steatohepatitis (MASH), which can result in fibrosis and/or cirrhosis and increase the risk of hepatocellular carcinoma (HCC). The latest Clinical Practice Guidelines acknowledge the importance of systemic metabolic dysfunction as a driver of hepatic lipid accumulation and disease progression. To ensure translational relevance of preclinical models, they need to faithfully replicate the key human pathophysiological characteristics of MASLD and its progression to fibrosis and HCC. This Review discusses the strengths and weaknesses of prevalent MASLD and MASH-HCC preclinical models, expanding the discussion to the latest advances in vivo (for example, genetically altered, humanized and large animals) and in vitro (for example, organoids or spheroids, 3D-bioprinted livers, precision-cut liver slices, organs-on-a-chip and decellularized scaffolds). Evidence will be critically re-assessed according to the new MASLD definition, paving a consensus in the field for nomenclature, expected limitations and how to conduct a systematic validation of new models against human-relevant disease outcomes. We also propose a standardized pipeline for preclinical studies in MASLD and MASH-HCC. This Review aims to help researchers make informed decisions when choosing an experimental design that best aligns with the specific requirements of their projects, whilst meaningfully replicating human disease.

Organoids derived from pluripotent stem cells have emerged as powerful models to study human development. To investigate signaling pathways regulating human pancreas differentiation and morphogenesis, we developed a high-content, image-based screen and quantitative multivariate analysis pipelines robust to heterogeneity to extract single-cell and organoid features using pancreatic progenitor organoids. Here, we identified 54 compounds affecting cell identity and/or morphological landscape. Focusing on one family of compounds, we found that glycogen synthase kinase 3α/β (GSK3A/B) inhibition via wingless/int-1 (WNT) signaling has a reversible effect on cell identity, repressing pancreatic progenitor markers and inducing a poised state in progenitors transitioning to acinar cells. We show that additional fibroblast growth factor (FGF) repression enables further differentiation of acinar cells, recapitulating pancreatic acinar morphogenesis and function. The ability to produce acinar cells is valuable for future studies on pancreatic exocrine function and cancer initiation in humans, as acinar cells are thought to be an important cell of origin for pancreatic adenocarcinoma.

The identification of cancer drivers is a cornerstone to delivery of precision oncology. So far sequencing of renal cell cancer (RCC) has largely been confined to the clear cell subtype of RCC. In contrast, sequencing analyses of the less common forms of RCC, papillary RCC (pRCC) and chromophobe RCC (ChRCC), have so far been limited. We analysed whole genome sequencing data on 164 tumour-normal pairs from the Genomics England 100,000 Genomes Project, providing a comprehensive, high-resolution map of copy number alterations, structural variation, and key global genomic features, including mutational signatures, intra-tumour heterogeneity and analysis of extrachromosomal DNA formation. Our research establishes correlations between genomic alterations and histological diversification and the extent to which genetically-mediated immune escape contributes to the development of these RCC subtypes. Implications: We demonstrate the distinctive genetics which characterises pRCC and ChRCC and how this information has the potential to inform patient treatment and clinical trials.

Rhodamine dyes conjugated to targeting ligands can yield exceptionally bright fluorescent probes for live-cell imaging. However, the limited permeability of such rhodamine derivatives restricts their broader applications, particularly in vivo. Here, we present Rho-tag and SiR-tag, engineered protein tags derived from bacterial multidrug-resistant proteins that bind unsubstituted (silicon) rhodamines with nanomolar affinity. Unsubstituted (silicon) rhodamines readily cross membranes and enable rapid, reversible, and fluorogenic labeling of the tags in mammalian cells within seconds. The labeling of Rho-tag and SiR-tag is compatible with various super-resolution imaging methods and allows their use alongside self-labeling tags, such as HaloTag7 and SNAP-tag. The high affinity and specificity of both tags, combined with the permeability and outstanding spectroscopic properties of rhodamines, make them particularly attractive for in vivo bioimaging, as demonstrated by efficient fluorescent labeling inC. elegansembryos and zebrafish larvae.

DNA-based Point Accumulation for Imaging in Nanoscale Topography (DNA-PAINT) is a powerful variant of single-molecule localization microscopy (SMLM) that overcomes the limitations of photobleaching, offers flexible fluorophore selection, and enables fine control of imaging parameters through tunable on- and off-binding kinetics. Its most distinctive feature is its capacity for multiplexing, typically implemented through sequential imaging of targets using an Exchange-PAINT. This technique involves assigning orthogonal DNA strands to different targets within a sample and then sequentially adding and removing complementary imager strands that are specific to only one target at a time. However, manual Exchange-PAINT workflows are often inefficient, prone to drift and variability, and lack reproducibility. Here, we introduce a custom compressed-air-driven microfluidics system specifically designed for multiplexed SMLM. Featuring a stackable and modular design that is, in principle, not limited by the number of channels, the system ensures robust, reproducible, and material-efficient buffer exchange with minimal dead volume. It operates in both manual and automated modes and can be readily adapted to a wide range of commercial and custom microscopes, including wide-field, confocal, STED, MINFLUX and other platforms. We demonstrate robust 5-plex Exchange-PAINT imaging in cancerous U2OS cells, and importantly, we establish multiplexed nanoscale imaging in fragile primary cardiomyocytes. These applications demonstrate that the platform enables reliable super-resolution multiplexing in physiologically relevant systems and supports detailed nanoscale analysis in complex primary cells.