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Biology subjects

Luethi, J.

Publications and source records attributed to Luethi, J..

3 recordsLinked to original sources

Multiplexed embryo profiling links cellular state to zygotic genome activation in single cells

Multicellular self-organization relies on complex interactions across multiple length scales, shaping the transcriptional activity and molecular phenotype of individual cells. Despite advances in spatial omics technologies, mapping protein state composition at high spatial resolution to capture the molecular phenotype across whole-mount structures has remained challenging. Here, we introduce high-throughput 3D iterative indirect immunofluorescence imaging (3D-4i) for the simultaneous detection of multiple proteins and protein states across the entire embryo, and a 3D-dedicated computer vision pipeline for quantifying morphological and molecular properties across subcellular, single-cell, and whole-embryo scales in hundreds of samples. Applying this pipeline to early zebrafish embryos undergoing mid-blastula transition, we determine the cell cycle phase for each cell across the embryo, allowing us to uncover the spatiotemporal dynamics by which global meta-synchronous mitotic waves transition to cell cycle desynchronization. Using statistical analysis, we find that cell cycle phase is the major source of variability in transcription within a division cycle, and combining this with analysis of key transcription factors and chromatin modifier state enables accurate prediction of transcriptional output during zygotic genome activation in individual cells. Collectively, our results demonstrate the strength of 3D-4i in quantifying multimodal effects across spatiotemporal scales and show how it can be utilized to unravel the complex contribution of causal factors that collectively drive multicellular self-organization.

systems biology↗

Multiscale chromatin dynamics and high entropy in plant iPSC cultures

Plant protoplasts constitute the starting material to induce pluripotent cell masses in vitro competent for tissue regeneration. Dedifferentiation is associated with large-scale chromatin reorganisation and massive transcriptome reprogramming, characterized by stochastic gene expression. How this cellular variability reflects on chromatin organisation in individual cells and what are the factors influencing chromatin transitions during culturing is largely unknown. High-throughput imaging and a custom, supervised image analysis protocol extracting over 100 chromatin features unravelled a rapid, multiscale dynamics of chromatin patterns which trajectory strongly depends on nutrients availability. Decreased abundance in H1 (linker histones) is hallmark of chromatin transitions. We measured a high heterogeneity of chromatin patterns indicating an intrinsic entropy as hallmark of the initial cultures. We further measured an entropy decline over time, and an antagonistic influence by external and intrinsic factors, such as phytohormones and epigenetic modifiers, respectively. Collectively, our study benchmarks an approach to understand the variability and evolution of chromatin patterns underlying plant cell reprogramming in vitro.

molecular biology↗

OME-Zarr: a cloud-optimized bioimaging file format with international community support

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself - OME-Zarr - along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain -- the file format that underlies so many personal, institutional, and global data management and analysis tasks.

bioinformatics↗