Quantitative 3D Analysis of Nuclear Morphology and Heterochromatin Organization from Whole-Mount Plant Tissue Using NucleusJ

2D morphometric analysis of Arabidopsis thaliana nuclei reveals characteristic profiles of different cell types and accessions

Functional changes of cells upon developmental switches and in response to environmental cues are often reflected in nuclear phenotypes, showing distinctive chromatin states corresponding to transcriptional changes. Such characteristic nuclear shapes have been microscopically monitored and can be quantified after differential staining of euchromatin and heterochromatin domains. Here, we examined several nuclear parameters (size, DNA content, DNA density, chromatin compaction, relative heterochromatin fraction (RHF), and number of chromocenters) in relation to spatial distribution of genes and transposon elements (TEs), using standard 2D fluorescence microscopy. We provide nuclear profiles for different cell types and different accessions of Arabidopsis thaliana. A variable, yet significant, fraction of TEs was found outside chromocenters in all cell types, except for guard cells. The latter cell type features nuclei with the highest level of chromatin compaction, while their chromocenters seem to contain gene-rich regions. The highest number of parameter correlations was found in the accession Cvi, whereas Ler showed only few correlations. This may point at differences in phenotype robustness between accessions. The significantly high association of NOR chromocenters in accessions Ws and Cvi corresponds to their low RHF level.

Automated 3D bio-imaging analysis of nuclear organization by NucleusJ 2.0

NucleusJ 1.0, an ImageJ plugin, is a useful tool to analyze nuclear morphology and chromatin organization in plant and animal cells. NucleusJ 2.0 is a new release of NucleusJ, in which image processing is achieved more quickly using a command-lineuser interface. Starting with large collection of 3D nuclei, segmentation can be performed by the previously developed Otsu-modified method or by a new 3D gift-wrapping method, taking better account of nuclear indentations and unstained nucleoli. These two complementary methods are compared for their accuracy by using three types of datasets available to the community at https://www.brookes.ac.uk/indepth/images/ . Finally, NucleusJ 2.0 was evaluated using original plant genetic material by assessing its efficiency on nuclei stained with DNA dyes or after 3D-DNA Fluorescence in situ hybridization. With these improvements, NucleusJ 2.0 permits the generation of large user-curated datasets that will be useful for software benchmarking or to train convolution neural networks.

Mathematical Modelling of Ground Truth Image for 3D Microscopic Objects Using Cascade of Convolutional Neural Networks Optimized with Parameters’ Combinations Generators

Mathematical modelling to compute ground truth from 3D images is an area of research that can strongly benefit from machine learning methods. Deep neural networks (DNNs) are state-of-the-art methods design for solving these kinds of difficulties. Convolutional neural networks (CNNs), as one class of DNNs, can overcome special requirements of quantitative analysis especially when image segmentation is needed. This article presents a system that uses a cascade of CNNs with symmetric blocks of layers in chain, dedicated to 3D image segmentation from microscopic images of 3D nuclei. The system is designed through eight experiments that differ in following aspects: number of training slices and 3D samples for training, usage of pre-trained CNNs and number of slices and 3D samples for validation. CNNs parameters are optimized using linear, brute force, and random combinatorics, followed by voter and median operations. Data augmentation techniques such as reflection, translation and rotation are used in order to produce sufficient training set for CNNs. Optimal CNN parameters are reached by defining 11 standard and two proposed metrics. Finally, benchmarking demonstrates that CNNs improve segmentation accuracy, reliability and increased annotation accuracy, confirming the relevance of CNNs to generate high-throughput mathematical ground truth 3D images.

Probing the 3D architecture of the plant nucleus with microscopy approaches: challenges and solutions

The eukaryotic cell nucleus is a central organelle whose architecture determines genome function at multiple levels. Deciphering nuclear organizing principles influencing cellular responses and identity is a timely challenge. Despite many similarities between plant and animal nuclei, plant nuclei present intriguing specificities. Complementary to molecular and biochemical approaches, 3D microscopy is indispensable for resolving nuclear architecture. However, novel solutions are required for capturing cell-specific, sub-nuclear and dynamic processes. We provide a pointer for utilising high-to-super-resolution microscopy and image processing to probe plant nuclear architecture in 3D at the best possible spatial and temporal resolution and at quantitative and cell-specific levels. High-end imaging and image-processing solutions allow the community now to transcend conventional practices and benefit from continuously improving approaches. These promise to deliver a comprehensive, 3D view of plant nuclear architecture and to capture spatial dynamics of the nuclear compartment in relation to cellular states and responses. Abbreviations: 3D and 4D: Three and Four dimensional; AI: Artificial Intelligence; ant: antipodal nuclei (ant); CLSM: Confocal Laser Scanning Microscopy; CTs: Chromosome Territories; DL: Deep Learning; DLIm: Dynamic Live Imaging; ecn: egg nucleus; FACS: Fluorescence-Activated Cell Sorting; FISH: Fluorescent In Situ Hybridization; FP: Fluorescent Proteins (GFP, RFP, CFP, YFP, mCherry); FRAP: Fluorescence Recovery After Photobleaching; GPU: Graphics Processing Unit; KEEs: KNOT Engaged Elements; INTACT: Isolation of Nuclei TAgged in specific Cell Types; LADs: Lamin-Associated Domains; ML: Machine Learning; NA: Numerical Aperture; NADs: Nucleolar Associated Domains; PALM: Photo-Activated Localization Microscopy; Pixel: Picture element; pn: polar nuclei; PSF: Point Spread Function; RHF: Relative Heterochromatin Fraction; SIM: Structured Illumination Microscopy; SLIm: Static Live Imaging; SMC: Spore Mother Cell; SNR: Signal to Noise Ratio; SRM: Super-Resolution Microscopy; STED: STimulated Emission Depletion; STORM: STochastic Optical Reconstruction Microscopy; syn: synergid nuclei; TADs: Topologically Associating Domains; Voxel: Volumetric pixel.

Replication-coupled histone H3.1 deposition determines nucleosome composition and heterochromatin dynamics during Arabidopsis seedling development

Developmental phase transitions are often characterized by changes in the chromatin landscape and heterochromatin reorganization. In Arabidopsis, clustering of repetitive heterochromatic loci into so-called chromocenters is an important determinant of chromosome organization in nuclear space. Here, we investigated the molecular mechanisms involved in chromocenter formation during the switch from a heterotrophic to a photosynthetically competent state during early seedling development. We characterized the spatial organization and chromatin features at centromeric and pericentromeric repeats and identified mutant contexts with impaired chromocenter formation. We find that clustering of repetitive DNA loci into chromocenters takes place in a precise temporal window and results in reinforced transcriptional repression. Although repetitive sequences are enriched in H3K9me2 and linker histone H1 before repeat clustering, chromocenter formation involves increasing enrichment in H3.1 as well as H2A.W histone variants, hallmarks of heterochromatin. These processes are severely affected in mutants impaired in replication-coupled histone assembly mediated by CHROMATIN ASSEMBLY FACTOR 1 (CAF-1). We further reveal that histone deposition by CAF-1 is required for efficient H3K9me2 enrichment at repetitive sequences during chromocenter formation. Taken together, we show that chromocenter assembly during post-germination development requires dynamic changes in nucleosome composition and histone post-translational modifications orchestrated by the replication-coupled H3.1 deposition machinery.

Technical Review: Microscopy and Image Processing Tools to Analyze Plant Chromatin: Practical Considerations

In situ nucleus and chromatin analyses rely on microscopy imaging that benefits from versatile, efficient fluorescent probes and proteins for static or live imaging. Yet the broad choice in imaging instruments offered to the user poses orientation problems. Which imaging instrument should be used for which purpose? What are the main caveats and what are the considerations to best exploit each instrument's ability to obtain informative and high-quality images? How to infer quantitative information on chromatin or nuclear organization from microscopy images? In this review, we present an overview of common, fluorescence-based microscopy systems and discuss recently developed super-resolution microscopy systems, which are able to bridge the resolution gap between common fluorescence microscopy and electron microscopy. We briefly present their basic principles and discuss their possible applications in the field, while providing experience-based recommendations to guide the user toward best-possible imaging. In addition to raw data acquisition methods, we discuss commercial and noncommercial processing tools required for optimal image presentation and signal evaluation in two and three dimensions.

A Compendium of Methods to Analyze the Spatial Organization of Plant Chromatin

The long linear chromosomes of eukaryotic organisms are tightly packed into the nucleus of the cell. Beyond a first organization into nucleosomes and higher-order chromatin fibers, the positioning of nuclear DNA within the three-dimensional space of the nucleus plays a critical role in genome function and gene expression. Different techniques have been developed to assess nanoscale chromatin organization, nuclear position of genomic regions or specific chromatin features and binding proteins as well as higher-order chromatin organization. Here, I present an overview of imaging and molecular techniques applied to study nuclear architecture in plants, with special attention to the related protocols published in the "Plant Chromatin Dynamics" edition from Methods in Molecular Biology.