Image analysis workflows to reveal the spatial organization of cell nuclei and chromosomes.

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 plant AlcR-pAlcA ethanol-inducible system displays gross growth artefacts independently of downstream pAlcA-regulated inducible constructs.

The AlcR fungal protein responds to ethanol and binds to the fungal pAlcA promoter in its presence. This system was transferred to plants over twenty years ago and was claimed to function in the same manner in plants. However, never has the control experiment with plants containing the AlcR gene alone, with no downstream inducible construct, been made. In this paper, I conduct several experiments with this control, growing p35:AlcR plants in the presence or absence of ethanol. I found that when these plants were grown in the presence of ethanol, growth in several tissues and several stages of growth was retarded. This demonstrates that this system is not suitable for use in the plant sciences, and casts doubt on the conclusions of papers that have published phenotypes using this system.

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.

Light Sheet Fluorescence Microscopy Optimized for Long-Term Imaging of Arabidopsis Root Development.

Light sheet fluorescence microscopy (LSFM) allows sustained and repeated optical sectioning of living specimens at high spatial and temporal resolution, with minimal photodamage. Here, we describe in detail both the hardware and the software elements of a live imaging method based on LSFM and optimized for tracking and 3D scanning of Arabidopsis root tips grown vertically in physiological conditions. The system is relatively inexpensive and with minimal footprint; hence it is well suited for laboratories of any size.

Re-induction of the cell cycle in the Arabidopsis post-embryonic root meristem is ABA-insensitive, GA-dependent and repressed by KRP6.

Seeding establishment following seed germination requires activation of the root meristem for primary root growth. We investigated the hormonal and genetic regulation of root meristem activation during Arabidopsis seed germination. In optimal conditions, radicle cell divisions occur only after the completion of germination and require de novo GA synthesis. When the completion of germination is blocked by ABA, radicle elongation and cell divisions occurred in these non-germinating seeds. Conversely under GA-limiting conditions, ABA-insensitive mutants complete germination in the absence of radicle meristem activation and growth. Radicle meristem activation and extension can therefore occur independently of completion of the developmental transition of germination. The cell cycle regulator KRP6 partially represses GA-dependent activation of the cell cycle. Germination of krp6 mutant seeds occurs more rapidly, is slightly insensitive to ABA in dose-response assays, but also hypersensitive to the GA synthesis inhibitor PAC. These conflicting phenotypes suggest the cell cycle uncouples GA and ABA responses in germinating Arabidopsis seeds, and that KRP6 acts downstream of GA to inhibit mitotic cell cycle activation during germination.

AINTEGUMENTA and the D-type cyclin CYCD3;1 regulate root secondary growth and respond to cytokinins.

Higher plant vasculature is characterized by two distinct developmental phases. Initially, a well-defined radial primary pattern is established. In eudicots, this is followed by secondary growth, which involves development of the cambium and is required for efficient water and nutrient transport and wood formation. Regulation of secondary growth involves several phytohormones, and cytokinins have been implicated as key players, particularly in the activation of cell proliferation, but the molecular mechanisms mediating this hormonal control remain unknown. Here we show that the genes encoding the transcription factor AINTEGUMENTA (ANT) and the D-type cyclin CYCD3;1 are expressed in the vascular cambium of Arabidopsis roots, respond to cytokinins and are both required for proper root secondary thickening. Cytokinin regulation of ANT and CYCD3 also occurs during secondary thickening of poplar stems, suggesting this represents a conserved regulatory mechanism.

AINTEGUMENTA and the D-type cyclin CYCD3;1 independently contribute to petal size control in Arabidopsis: evidence for organ size compensation being an emergent rather than a determined property.

Plant lateral aerial organ (LAO) growth is determined by the number and size of cells comprising the organ. Genetic alteration of one parameter is often accompanied by changes in the other, such that the overall effect on final LAO size is minimized, suggested to be caused by an active organ level 'compensation mechanism'. For example, the aintegumenta (ant) mutant exhibits reduced cell number but increased cell size in LAOs. The ANT transcription factor regulates the duration of the cell division phase of LAO growth, and its ectopic expression is correlated with increased levels of the cell cycle regulator CYCD3;1. This has previously led to the suggestion that ANT regulates CYCD3;1. It is shown here that while ANT is required for normal cell proliferation in petals, CYCD3;1 is not, suggesting that ANT does not regulate CYCD3;1 during petal growth. Moreover CYCD3;1 expression was similar in wild-type and ant-9 flowers. In contrast to the compensatory changes between cell size and number in ant mutants, cycd3;1 mutants show increased petal cell size unaccompanied by changes in cell number, leading to larger organs. However, loss of CYCD3;1 in the ant-9 mutant background leads to a phenotype consistent with compensation mechanisms. These apparently arbitrary examples of compensation are reconciled through a model of LAO growth in which distinct phases of division and cell expansion occupy differing lengths of a defined overall growth window. This leads to the proposal that many observations of 'compensation mechanisms' might alternatively be more simply explained as emergent properties of LAO development.