FIGL1 and its novel partner FLIP form a conserved complex that regulates homologous recombination.

Homologous recombination is central to repair DNA double-strand breaks, either accidently arising in mitotic cells or in a programed manner at meiosis. Crossovers resulting from the repair of meiotic breaks are essential for proper chromosome segregation and increase genetic diversity of the progeny. However, mechanisms regulating crossover formation remain elusive. Here, we identified through genetic and protein-protein interaction screens FIDGETIN-LIKE-1 INTERACTING PROTEIN (FLIP) as a new partner of the previously characterized anti-crossover factor FIDGETIN-LIKE-1 (FIGL1) in Arabidopsis thaliana. We showed that FLIP limits meiotic crossover together with FIGL1. Further, FLIP and FIGL1 form a protein complex conserved from Arabidopsis to human. FIGL1 interacts with the recombinases RAD51 and DMC1, the enzymes that catalyze the DNA strand exchange step of homologous recombination. Arabidopsis flip mutants recapitulate the figl1 phenotype, with enhanced meiotic recombination associated with change in counts of DMC1 and RAD51 foci. Our data thus suggests that FLIP and FIGL1 form a conserved complex that regulates the crucial step of strand invasion in homologous recombination.

Cell geometry determines symmetric and asymmetric division plane selection in Arabidopsis early embryos.

Plant tissue architecture and organ morphogenesis rely on the proper orientation of cell divisions. Previous attempts to predict division planes from cell geometry in plants mostly focused on 2D symmetric divisions. Using the stereotyped division patterns of Arabidopsis thaliana early embryogenesis, we investigated geometrical principles underlying plane selection in symmetric and in asymmetric divisions within complex 3D cell shapes. Introducing a 3D computational model of cell division, we show that area minimization constrained on passing through the cell centroid predicts observed divisions. Our results suggest that the positioning of division planes ensues from cell geometry and gives rise to spatially organized cell types with stereotyped shapes, thus underlining the role of self-organization in the developing architecture of the embryo. Our data further suggested the rule could be interpreted as surface minimization constrained by the nucleus position, which was validated using live imaging of cell divisions in the stomatal cell lineage.

On the presence and functional significance of sympathetic premotor neurons with collateralized spinal axons in the rat.

KEY POINTS: Spinally-projecting neurons of the rostral ventrolateral medulla (RVLM) determine sympathetic outflow to different territories of the body. Previous studies suggest the existence of RVLM neurons with distinct functional classes, such as neurons that target sympathetic nerves bound for functionally-similar tissue types (e.g. muscle vasculature). The existence of RVLM neurons with more general actions had not been critically tested. Using viral tracing, we show that a significant minority of RVLM neurons send axon collaterals to disparate spinal segments (T2 and T10 ). Furthermore, optogenetic activation of sympathetic premotor neurons projecting to lumbar spinal segments also produced activation of sympathetic nerves from rostral spinal segments that innervate functionally diverse tissues (heart and forelimb muscle). These findings suggest the existence of individual RVLM neurons for which the axons branch to drive sympathetic preganglionic neurons of more than one functional class and may be able to produce global changes in sympathetic activity. ABSTRACT: We investigate the extent of spinal axon collateralization of rat rostral ventrolateral medulla (RVLM) sympathetic premotor neurons and its functional consequences. In anatomical tracing experiments, two recombinant herpes viral vectors with retrograde tropism and expressing different fluorophores were injected into the intermediolateral column at upper thoracic and lower thoracic levels. Histological analysis revealed that ∼21% of RVLM bulbospinal neurons were retrogradely labelled by both vectors, indicating substantial axonal collateralization to disparate spinal segments. In functional experiments, another virus with retrograde tropism, a canine adenovirus expressing Cre recombinase, was injected into the left intermediolateral horn around the thoracolumbar junction, whereas a Cre-dependent viral vector encoding Channelrhodopsin2 under LoxP control was injected into the ipsilateral RVLM. In subsequent terminal experiments, blue laser light (473 nm × 20 ms pulses at 10 mW) was used to activate RVLM neurons that had been transduced by both vectors. Stimulus-locked activation, at appropriate latencies, was recorded in the following pairs of sympathetic nerves: forelimb and hindlimb muscle sympathetic fibres, as well as cardiac and either hindlimb muscle or lumbar sympathetic nerves. The latter result demonstrates that axon collaterals of lumbar-projecting RVLM neurons project to, and excite, both functionally similar (forelimb and hindlimb muscle) and functionally dissimilar (lumbar and cardiac) preganglionic neurons. Taken together, these findings show that the axons of a significant proportion of RVLM neurons collateralise widely within the spinal cord, and that they may excite preganglionic neurons of more than one functional class.

Multiscale quantification of morphodynamics: MorphoLeaf software for 2D shape analysis.

A major challenge in morphometrics is to analyse complex biological shapes formed by structures at different scales. Leaves exemplify this challenge as they combine differences in their overall shape with smaller shape variations at their margin, leading to lobes or teeth. Current methods based on contour or on landmark analysis are successful in quantifying either overall leaf shape or leaf margin dissection, but fail in combining the two. Here, we present a comprehensive strategy and its associated freely available platform for the quantitative, multiscale analysis of the morphology of leaves with different architectures. For this, biologically relevant landmarks are automatically extracted and hierarchised, and used to guide the reconstruction of accurate average contours that properly represent both global and local features. Using this method, we establish a quantitative framework of the developmental trajectory of Arabidopsis leaves of different ranks and retrace the origin of leaf heteroblasty. When applied to different mutant forms, our method can contribute to a better understanding of gene function, as we show here for the role of CUC2 during Arabidopsis leaf serration. Finally, we illustrate the wider applicability of our tool by analysing hand morphometrics.

The Arabidopsis hnRNP-Q Protein LIF2 and the PRC1 Subunit LHP1 Function in Concert to Regulate the Transcription of Stress-Responsive Genes.

LHP1-INTERACTING FACTOR2 (LIF2), a heterogeneous nuclear ribonucleoprotein involved in Arabidopsis thaliana cell fate and stress responses, interacts with LIKE HETEROCHROMATIN PROTEIN1 (LHP1), a Polycomb Repressive Complex1 subunit. To investigate LIF2-LHP1 functional interplay, we mapped their genome-wide distributions in wild-type, lif2, and lhp1 backgrounds, under standard and stress conditions. Interestingly, LHP1-targeted regions form local clusters, suggesting an underlying functional organization of the plant genome. Regions targeted by both LIF2 and LHP1 were enriched in stress-responsive genes, the H2A.Z histone variant, and antagonistic histone marks. We identified specific motifs within the targeted regions, including a G-box-like motif, a GAGA motif, and a telo-box. LIF2 and LHP1 can operate both antagonistically and synergistically. In response to methyl jasmonate treatment, LIF2 was rapidly recruited to chromatin, where it mediated transcriptional gene activation. Thus, LIF2 and LHP1 participate in transcriptional switches in stress-response pathways.

Human spinal ejaculation generator.

OBJECTIVE: A spinal ejaculation generator (SEG) has been identified in the rat with lumbar galaninergic interneurons playing a pivotal role (Science 2002;297:1566-1569). The aim was to evidence a SEG in humans. METHODS: Spatial distribution of galaninergic neurons was studied in postmortem spinal cord segments of 6 men and compared with that of 6 women for evidencing sexual dimorphism. Based on the identified segmental distribution of galaninergic neurons, the ability for penile vibratory stimulation (PVS) to elicit ejaculation when the concerned spinal segments were injured was studied in 384 patients with clinically complete spinal cord injury (SCI) and consequent anejaculation. Such patients represent a unique model to investigate the role of defined spinal segments in the control of ejaculation. RESULTS: Galaninergic neurons were mostly located between L2 and L5 segments in medial lamina VII, with a maximal density within L4. Three-dimensional 3D reconstruction showed that these neurons were grouped into single columns bilaterally to the central canal. In addition, galaninergic neuron density was found higher in L3 and L4 segments in men as compared to women supporting sexual dimorphism. In the patients' cohort, injury of L3-L5 segments was the sole independent predictor for failure of PVS to induce ejaculation. Although evidence from clinical observations was indirect, there is close correspondence to neuroanatomical data. INTERPRETATION: Organization and sexual dimorphism of human spinal galaninergic neurons were similar to the rat's SEG. Neurohistological data, together with clinical results, corroborate the existence of an SEG in humans in L3-L5 segments. Such a generator could be targeted to treat neurogenic and non-neurogenic ejaculatory disorders. ANN NEUROL 2017;81:35-45.

Strategy and software for the statistical spatial analysis of 3D intracellular distributions.

The localization of proteins in specific domains or compartments in the 3D cellular space is essential for many fundamental processes in eukaryotic cells. Deciphering spatial organization principles within cells is a challenging task, in particular because of the large morphological variations between individual cells. We present here an approach for normalizing variations in cell morphology and for statistically analyzing spatial distributions of intracellular compartments from collections of 3D images. The method relies on the processing and analysis of 3D geometrical models that are generated from image stacks and that are used to build representations at progressively increasing levels of integration, ultimately revealing statistical significant traits of spatial distributions. To make this methodology widely available to end-users, we implemented our algorithmic pipeline into a user-friendly, multi-platform, and freely available software. To validate our approach, we generated 3D statistical maps of endomembrane compartments at subcellular resolution within an average epidermal root cell from collections of image stacks. This revealed unsuspected polar distribution patterns of organelles that were not detectable in individual images. By reversing the classical 'measure-then-average' paradigm, one major benefit of the proposed strategy is the production and display of statistical 3D representations of spatial organizations, thus fully preserving the spatial dimension of image data and at the same time allowing their integration over individual observations. The approach and software are generic and should be of general interest for experimental and modeling studies of spatial organizations at multiple scales (subcellular, cellular, tissular) in biological systems.

MorphoLibJ: integrated library and plugins for mathematical morphology with ImageJ.

MOTIVATION: Mathematical morphology (MM) provides many powerful operators for processing 2D and 3D images. However, most MM plugins currently implemented for the popular ImageJ/Fiji platform are limited to the processing of 2D images. RESULTS: The MorphoLibJ library proposes a large collection of generic tools based on MM to process binary and grey-level 2D and 3D images, integrated into user-friendly plugins. We illustrate how MorphoLibJ can facilitate the exploitation of 3D images of plant tissues. AVAILABILITY AND IMPLEMENTATION: MorphoLibJ is freely available at http://imagej.net/MorphoLibJ CONTACT: david.legland@nantes.inra.frSupplementary information: Supplementary data are available at Bioinformatics online.

NucleusJ: an ImageJ plugin for quantifying 3D images of interphase nuclei.

UNLABELLED: NucleusJ is a simple and user-friendly ImageJ plugin dedicated to the characterization of nuclear morphology and chromatin organization in 3D. Starting from image stacks, the nuclear boundary is delimited by combining the Otsu segmentation method with optimization of nuclear sphericity. Chromatin domains are segmented by partitioning the nucleus using a 3D watershed algorithm and by thresholding a contrast measure over the resulting regions. As output, NucleusJ quantifies 15 parameters including shape and size of nuclei as well as intra-nuclear objects and their position within the nucleus. A step-by-step documentation is available for self-training, together with data sets of nuclei with different nuclear organization. AVAILABILITY AND IMPLEMENTATION: Dataset of nuclei is available at https://www.gred-clermont.fr/media/WorkDirectory.zip. NucleusJ is available at http://imagejdocu.tudor.lu/doku.php?id=plugin:stacks:nuclear_analysis_plugin:start. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A generic classification-based method for segmentation of nuclei in 3D images of early embryos.

BACKGROUND: Studying how individual cells spatially and temporally organize within the embryo is a fundamental issue in modern developmental biology to better understand the first stages of embryogenesis. In order to perform high-throughput analyses in three-dimensional microscopic images, it is essential to be able to automatically segment, classify and track cell nuclei. Many 3D/4D segmentation and tracking algorithms have been reported in the literature. Most of them are specific to particular models or acquisition systems and often require the fine tuning of parameters. RESULTS: We present a new automatic algorithm to segment and simultaneously classify cell nuclei in 3D/4D images. Segmentation relies on training samples that are interactively provided by the user and on an iterative thresholding process. This algorithm can correctly segment nuclei even when they are touching, and remains effective under temporal and spatial intensity variations. The segmentation is coupled to a classification of nuclei according to cell cycle phases, allowing biologists to quantify the effect of genetic perturbations and drug treatments. Robust 3D geometrical shape descriptors are used as training features for classification. Segmentation and classification results of three complete datasets are presented. In our working dataset of the Caenorhabditis elegans embryo, only 21 nuclei out of 3,585 were not detected, the overall F-score for segmentation reached 0.99, and more than 95% of the nuclei were classified in the correct cell cycle phase. No merging of nuclei was found. CONCLUSION: We developed a novel generic algorithm for segmentation and classification in 3D images. The method, referred to as Adaptive Generic Iterative Thresholding Algorithm (AGITA), is freely available as an ImageJ plug-in.

Nuclear architecture and chromatin dynamics in interphase nuclei of Arabidopsis thaliana.

The interphase cell nucleus is extraordinarily complex, ordered, and dynamic. In the last decade, remarkable progress has been made in deciphering the functional organisation of the cell nucleus, and intricate relationships between genome functions (transcription, DNA repair, or replication) and various nuclear compartments have been revealed. In this review, we describe the architecture of the Arabidopsis thaliana interphase cell nucleus and discuss the dynamic nature of its organisation. We underline the need for further developments in quantitative and modelling approaches to nuclear organization.

Multiple binding of repressed mRNAs by the P-body protein Rck/p54.

Translational repression is achieved by protein complexes that typically bind 3' UTR mRNA motifs and interfere with the formation of the cap-dependent initiation complex, resulting in mRNPs with a closed-loop conformation. We demonstrate here that the human DEAD-box protein Rck/p54, which is a component of such complexes and central to P-body assembly, is in considerable molecular excess with respect to cellular mRNAs and enriched to a concentration of 0.5 mM in P-bodies, where it is organized in clusters. Accordingly, multiple binding of p54 proteins along mRNA molecules was detected in vivo. Consistently, the purified protein bound RNA with no sequence specificity and high nanomolar affinity. Moreover, bound RNA molecules had a relaxed conformation. While RNA binding was ATP independent, relaxing of bound RNA was dependent on ATP, though not on its hydrolysis. We propose that Rck/p54 recruitment by sequence-specific translational repressors leads to further binding of Rck/p54 along mRNA molecules, resulting in their masking, unwinding, and ultimately recruitment to P-bodies. Rck/p54 proteins located at the 5' extremity of mRNA can then recruit the decapping complex, thus coupling translational repression and mRNA degradation.

Non-random spatial organization of telomeres varies during the cell cycle and requires LAP2 and BAF.

Spatial genome organization within the nucleus influences major biological processes and is impacted by the configuration of linear chromosomes. Here, we applied 3D spatial statistics and modeling on high-resolution telomere and centromere 3D-structured illumination microscopy images in cancer cells. We found a multi-scale organization of telomeres that dynamically evolved from a mixed clustered-and-regular distribution in early G1 to a purely regular distribution as cells progressed through the cell cycle. In parallel, our analysis revealed two pools of peripheral and internal telomeres, the proportions of which were inverted during the cell cycle. We then conducted a targeted screen using MadID to identify the molecular pathways driving or maintaining telomere anchoring to the nuclear envelope observed in early G1. Lamina-associated polypeptide (LAP) proteins were found transiently localized to telomeres in anaphase, a stage where LAP2α initiates the reformation of the nuclear envelope, and impacted telomere redistribution in the next interphase together with their partner barrier-to-autointegration factor (BAF).

TreeJ: an ImageJ plugin for interactive cell lineage reconstruction from static images.

BACKGROUND: With the emergence of deep-learning methods, tools are needed to capture and standardize image annotations made by experimentalists. In developmental biology, cell lineages are generally reconstructed from time-lapse data. However, some tissues need to be fixed to be accessible or to improve the staining. In this case, classical software do not offer the possibility of generating any lineage. Because of their rigid cell walls, plants present the advantage of keeping traces of the cell division history over successive generations in the cell patterns. To record this information despite having only a static image, dedicated tools are required. RESULTS: We developed an interface to assist users in the building and editing of a lineage tree from a 3D labeled image. Each cell within the tree can be tagged. From the created tree, cells of a sub-tree or cells sharing the same tag can be extracted. The tree can be exported in a format compatible with dedicated software for advanced graph visualization and manipulation. CONCLUSIONS: The TreeJ plugin for ImageJ/Fiji allows the user to generate and manipulate a lineage tree structure. The tree is compatible with other software to analyze the tree organization at the graphical level and at the cell pattern level. The code source is available at https://github.com/L-EL/TreeJ .

Model-based reconstruction of whole organ growth dynamics reveals invariant patterns in leaf morphogenesis.

Plant organ morphogenesis spans several orders of magnitude in time and space. Because of limitations in live-imaging, analysing whole organ growth from initiation to mature stages typically rely on static data sampled from different timepoints and individuals. We introduce a new model-based strategy for dating organs and for reconstructing morphogenetic trajectories over unlimited time windows based on static data. Using this approach, we show that Arabidopsis thaliana leaves are initiated at regular 1-day intervals. Despite contrasted adult morphologies, leaves of different ranks exhibited shared growth dynamics, with linear gradations of growth parameters according to leaf rank. At the sub-organ scale, successive serrations from same or different leaves also followed shared growth dynamics, suggesting that global and local leaf growth patterns are decoupled. Analysing mutants leaves with altered morphology highlighted the decorrelation between adult shapes and morphogenetic trajectories, thus stressing the benefits of our approach in identifying determinants and critical timepoints during organ morphogenesis.

Large-scale analysis and computer modeling reveal hidden regularities behind variability of cell division patterns in Arabidopsis thaliana embryogenesis.

Noise plays a major role in cellular processes and in the development of tissues and organs. Several studies have examined the origin, the integration or the accommodation of noise in gene expression, cell growth and elaboration of organ shape. By contrast, much less is known about variability in cell division plane positioning, its origin and links with cell geometry, and its impact on tissue organization. Taking advantage of the first-stereotyped-then-variable division patterns in the embryo of the model plant Arabidopsis thaliana, we combined 3D imaging and quantitative cell shape and cell lineage analysis together with mathematical and computer modeling to perform a large-scale, systematic analysis of variability in division plane orientation. Our results reveal that, paradoxically, variability in cell division patterns of Arabidopsis embryos is accompanied by a progressive reduction of heterogeneity in cell shape topology. The paradox is solved by showing that variability operates within a reduced repertoire of possible division plane orientations that is related to cell geometry. We show that in several domains of the embryo, a recently proposed geometrical division rule recapitulates observed variable patterns, suggesting that variable patterns emerge from deterministic principles operating in a variable geometrical context. Our work highlights the importance of emerging patterns in the plant embryo under iterated division principles, but also reveal domains where deviations between rule predictions and experimental observations point to additional regulatory mechanisms.

Dopamine Modulates the Processing of Food Odour in the Ventral Striatum.

Food odour is a potent stimulus of food intake. Odour coding in the brain occurs in synergy or competition with other sensory information and internal signals. For eliciting feeding behaviour, food odour coding has to gain signification through enrichment with additional labelling in the brain. Since the ventral striatum, at the crossroads of olfactory and reward pathways, receives a rich dopaminergic innervation, we hypothesized that dopamine plays a role in food odour information processing in the ventral striatum. Using single neurones recordings in anesthetised rats, we show that some ventral striatum neurones respond to food odour. This neuronal network displays a variety of responses (excitation, inhibition, rhythmic activity in phase with respiration). The localization of recorded neurones in a 3-dimensional brain model suggests the spatial segregation of this food-odour responsive population. Using local field potentials recordings, we found that the neural population response to food odour was characterized by an increase of power in the beta-band frequency. This response was modulated by dopamine, as evidenced by its depression following administration of the dopaminergic D1 and D2 antagonists SCH23390 and raclopride. Our results suggest that dopamine improves food odour processing in the ventral striatum.

Statistical analysis of 3D images detects regular spatial distributions of centromeres and chromocenters in animal and plant nuclei.

In eukaryotes, the interphase nucleus is organized in morphologically and/or functionally distinct nuclear "compartments". Numerous studies highlight functional relationships between the spatial organization of the nucleus and gene regulation. This raises the question of whether nuclear organization principles exist and, if so, whether they are identical in the animal and plant kingdoms. We addressed this issue through the investigation of the three-dimensional distribution of the centromeres and chromocenters. We investigated five very diverse populations of interphase nuclei at different differentiation stages in their physiological environment, belonging to rabbit embryos at the 8-cell and blastocyst stages, differentiated rabbit mammary epithelial cells during lactation, and differentiated cells of Arabidopsis thaliana plantlets. We developed new tools based on the processing of confocal images and a new statistical approach based on G- and F- distance functions used in spatial statistics. Our original computational scheme takes into account both size and shape variability by comparing, for each nucleus, the observed distribution against a reference distribution estimated by Monte-Carlo sampling over the same nucleus. This implicit normalization allowed similar data processing and extraction of rules in the five differentiated nuclei populations of the three studied biological systems, despite differences in chromosome number, genome organization and heterochromatin content. We showed that centromeres/chromocenters form significantly more regularly spaced patterns than expected under a completely random situation, suggesting that repulsive constraints or spatial inhomogeneities underlay the spatial organization of heterochromatic compartments. The proposed technique should be useful for identifying further spatial features in a wide range of cell types.

Spatial modeling of biological patterns shows multiscale organization of Arabidopsis thaliana heterochromatin.

The spatial organization in the cell nucleus is tightly linked to genome functions such as gene regulation. Similarly, specific spatial arrangements of biological components such as macromolecular complexes, organelles and cells are involved in many biological functions. Spatial interactions among elementary components of biological systems define their relative positioning and are key determinants of spatial patterns. However, biological variability and the lack of appropriate spatial statistical methods and models limit our current ability to analyze these interactions. Here, we developed a framework to dissect spatial interactions and organization principles by combining unbiased statistical tests, multiple spatial descriptors and new spatial models. We used plant constitutive heterochromatin as a model system to demonstrate the potential of our framework. Our results challenge the common view of a peripheral organization of chromocenters, showing that chromocenters are arranged along both radial and lateral directions in the nuclear space and obey a multiscale organization with scale-dependent antagonistic effects. The proposed generic framework will be useful to identify determinants of spatial organizations and to question their interplay with biological functions.

A Method for Testing Random Spatial Models on Nuclear Object Distributions.

The cell nucleus is a structurally complex and dynamic organelle ensuring key biological functions. Complex relationships between nuclear structure and functions require a better understanding of the three-dimensional organization of the genome and of the subnuclear compartments. Quantitative image analysis coupled with spatial statistics and modeling is a relevant approach to address these questions. In this chapter, we describe a step-by-step procedure to process images and to test a spatial random model for the distribution of nuclear objects using chromocenters as an example. More elaborate models can be designed on the basis of the random model by introducing additional and more complex constraints to better fit observations and to question determinants of these spatial organizations.