Sophie Desset

The transition from seed to seedling involves major changes in nuclear organization and gene expression, yet the extent to which this developmental transition requires chromatin reprogramming remains largely unexplored. Here, we report that Arabidopsis dry seed embryos accumulate the histone variant H2B.8, which contributes to higher-order chromatin organization by forming spatial clusters that structure the 3D nuclear space. H2B.8 predominantly assembles into heterotypic nucleosomes, is enriched at euchromatic transposons and lowly expressed genes and, during imbibition, modulates the transcriptional activation of a subset of these genes. Water uptake triggers a decrease in H2B.8 transcripts and the eviction of the H2B.8 variant from chromatin, in a process that operates independently of DNA replication but requires de novo transcription. Histone eviction is not restricted to H2B.8, as imbibition also induces turnover of the H3.3 histone variant and therefore initiates a replication-independent chromatin reprogramming process. These findings highlight a fundamental mechanism of epigenetic regulation during early plant development.

The transition from seed to seedling involves major changes in nuclear organization and gene expression, yet the extent to which this developmental transition requires chromatin reprogramming remains largely unexplored. Here, we report that Arabidopsis dry seed embryos accumulate the histone variant H2B.8, which contributes to higher-order chromatin organization by forming spatial clusters that structure the 3D nuclear space. H2B.8 forms heterotypic nucleosomes at euchromatic transposons and lowly expressed genes and, during imbibition, modulates the transcriptional activation of a subset of these genes. Imbibition triggers a decrease in H2B.8 transcripts and the eviction of H2B.8 proteins in a process that operates independently of DNA replication but requires protein translation and de novo transcription. Histone eviction is not limited to H2B.8 as imbibition also induces the turnover of the H3.3 histone variant, thereby initiating a broad, replication-independent chromatin reprogramming process. These findings highlight a fundamental mechanism of epigenetic regulation during early plant development.

The “CSMA: An ImageJ Plugin for the Analysis of Wound Healing Assays” preprint proposes a new image analysis tool called CSMA for monitoring the repair of a cell mat wound in culture. CSMA is programmed in Python with Java scripts for use as an Image...

The antagonistic POLYCOMB (PcG) REPRESSIVE COMPLEX 2 (PRC2) and trithorax (trxG) chromatin machineries play a major role in orchestrating gene expression during the development of multicellular eukaryotes. These complexes are well known for depositing and maintaining the repressive H3K27me3 and activating H3K4me3 marks, respectively. However, the mechanisms that govern the switch between these functions remains elusive, especially in plants, whose lifelong, flexible development relies heavily on this process. Here we demonstrate that the plant specific ULTRAPETALA1 (ULT1) protein, previously reported as a trxG factor that antagonizes the PRC2 enzymatic subunit CURLY LEAF (CLF), also exhibits a repressive function, increasing H3K27me3 levels at over a thousand genes. We discovered a physical interaction between ULT1 and PRC2 components, particularly the SWINGER (SWN) enzymatic subunit. We further show that in vitro ULT1 significantly enhances the enzymatic activity of PRC2 ^SWN , and to a lesser extent also that of PRC2 ^CLF , corroborating our epigenomic and developmental genetic data that reveal different ULT1 activity depending on the catalytic subunit of the PRC2 complex. This study provides new insights into the relative activities of CLF and SWN and introduces a novel mechanistic framework for a chromatin switch mediated by a bivalent trxG/PcG factor. Key message: ULTRAPETALA1 counteracts or promotes PRC2 activity at hundreds of developmental genes in Arabidopsis thaliana , and activates the deposition of the repressive H3K27me3 chromatin mark via direct interaction with PRC2. This is the first instance of a bivalent factor which functions as a cofactor of PRC2 HMTs.

U-Net is a convolutional neural network model developed in 2015 and has proven to be one of the most inspiring deep-learning models for image segmentation. Numerous U-Net-based applications have since emerged, constituting a heterogeneous set of tools that illustrate the current reproducibility crisis in the deep-learning field and that remain slow to spread in application fields such as 3D bioimaging. Here we propose a solution named Biom3d, a modular deep learning framework facilitating the integration and development of novel models, metrics, or training schemes for 3D image segmentation. The development philosophy of Biom3d provides an improved code sustainability and reproducibility in line with the FAIR principles and is available as a graphical user interface and an open-source deep-learning framework to target a large community of users, from end users to deep learning developers.

Nucleus, chromatin, and chromosome organization studies heavily rely on fluorescence microscopy imaging to elucidate the distribution and abundance of structural and regulatory components. Three-dimensional (3D) image stacks are a source of quantitative data on signal intensity level and distribution and on the type and shape of distribution patterns in space. Their analysis can lead to novel insights that are otherwise missed in qualitative-only analyses. Quantitative image analysis requires specific software and workflows for image rendering, processing, segmentation, setting measurement points and reference frames and exporting target data before further numerical processing and plotting. These tasks often call for the development of customized computational scripts and require an expertise that is not broadly available to the community of experimental biologists. Yet, the increasing accessibility of high- and super-resolution imaging methods fuels the demand for user-friendly image analysis workflows. Here, we provide a compendium of strategies developed by participants of a training school from the COST action INDEPTH to analyze the spatial distribution of nuclear and chromosomal signals from 3D image stacks, acquired by diffraction-limited confocal microscopy and super-resolution microscopy methods (SIM and STED). While the examples make use of one specific commercial software package, the workflows can easily be adapted to concurrent commercial and open-source software. The aim is to encourage biologists lacking custom-script-based expertise to venture into quantitative image analysis and to better exploit the discovery potential of their images. Abbreviations: 3D FISH: three-dimensional fluorescence in situ hybridization; 3D: three-dimensional; ASY1: ASYNAPTIC 1; CC: chromocenters; CO: Crossover; DAPI: 4',6-diamidino-2-phenylindole; DMC1: DNA MEIOTIC RECOMBINASE 1; DSB: Double-Strand Break; FISH: fluorescence in situ hybridization; GFP: GREEN FLUORESCENT PROTEIN; HEI10: HUMAN ENHANCER OF INVASION 10; NCO: Non-Crossover; NE: Nuclear Envelope; Oligo-FISH: oligonucleotide fluorescence in situ hybridization; RNPII: RNA Polymerase II; SC: Synaptonemal Complex; SIM: structured illumination microscopy; ZMM (ZIP: MSH4: MSH5 and MER3 proteins); ZYP1: ZIPPER-LIKE PROTEIN 1.

The Open Microscopy Environment Remote Objects (OMERO) is an open-source image manager used by many biologists to store, organize, view, and share microscopy images, while the open-source software ImageJ/Fiji is a very popular program used to analyse them. However, there is a lack of an easy-to-use generic tool to run a workflow on a batch of images without having to download them to local computers, and to automatically organize the results in OMERO. To offer this functionality, we have built (i) a library in Java: “Simple OMERO Client”, to communicate with an OMERO database from Java software, (ii) an ImageJ/Fiji plugin to run a macro-program on a batch of images from OMERO and (iii) a new set of Macro Functions, “OMERO Macro extensions“, dedicated to interact with OMERO in macro-programming. The latter is intended for developers, with additional possibilities using tag criteria, while the “Batch OMERO plugin” is more geared towards non-IT scientists and has a very easy to use interface. Each tool is illustrated with a use case.

Background: The three-dimensional nuclear arrangement of chromatin impacts many cellular processes operating at the DNA level in animal and plant systems. Chromatin organization is a dynamic process that can be affected by biotic and abiotic stresses. Three-dimensional imaging technology allows to follow these dynamic changes, but only a few semi-automated processing methods currently exist for quantitative analysis of the 3D chromatin organization. Results: We present an automated method, Nuclear Object DetectionJ (NODeJ), developed as an imageJ plugin. This program segments and analyzes high intensity domains in nuclei from 3D images. NODeJ performs a Laplacian convolution on the mask of a nucleus to enhance the contrast of intra-nuclear objects and allow their detection. We reanalyzed public datasets and determined that NODeJ is able to accurately identify heterochromatin domains from a diverse set of Arabidopsis thaliana nuclei stained with DAPI or Hoechst. NODeJ is also able to detect signals in nuclei from DNA FISH experiments, allowing for the analysis of specific targets of interest. Conclusion and availability: NODeJ allows for efficient automated analysis of subnuclear structures by avoiding the semi-automated steps, resulting in reduced processing time and analytical bias. NODeJ is written in Java and provided as an ImageJ plugin with a command line option to perform more high-throughput analyses. NODeJ can be downloaded from https://gitlab.com/axpoulet/image2danalysis/-/releases with source code, documentation and further information avaliable at https://gitlab.com/axpoulet/image2danalysis. The images used in this study are publicly available at https://www.brookes.ac.uk/indepth/images/ and https://doi.org/10.15454/1HSOIE.