Esmraldi: efficient methods for the fusion of mass spectrometry and magnetic resonance images.

BACKGROUND: Mass spectrometry imaging (MSI) is a family of acquisition techniques producing images of the distribution of molecules in a sample, without any prior tagging of the molecules. This makes it a very interesting technique for exploratory research. However, the images are difficult to analyze because the enclosed data has high dimensionality, and their content does not necessarily reflect the shape of the object of interest. Conversely, magnetic resonance imaging (MRI) scans reflect the anatomy of the tissue. MRI also provides complementary information to MSI, such as the content and distribution of water. RESULTS: We propose a new workflow to merge the information from 2D MALDI-MSI and MRI images. Our workflow can be applied to large MSI datasets in a limited amount of time. Moreover, the workflow is fully automated and based on deterministic methods which ensures the reproducibility of the results. Our methods were evaluated and compared with state-of-the-art methods. Results show that the images are combined precisely and in a time-efficient manner. CONCLUSION: Our workflow reveals molecules which co-localize with water in biological images. It can be applied on any MSI and MRI datasets which satisfy a few conditions: same regions of the shape enclosed in the images and similar intensity distributions.

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.

Quantitative dissection of variations in root growth rate: a matter of cell proliferation or of cell expansion?

Plant organ growth results from cell production and cell expansion. Deciphering the contribution of each of these processes to growth rate is an important issue in developmental biology. Here, we investigated the cellular processes governing root elongation rate, considering two sources of variation: genotype and disturbance by chemicals (NaCl, polyethylene glycol, H2O2, abscisic acid). Exploiting the adventitious rooting capacity of the Populus genus, and using time-lapse imaging under infrared-light, particle image velocimetry, histological analysis, and kinematics, we quantified the cellular processes involved in root growth variation, and analysed the covariation patterns between growth parameters. The rate of cell production by the root apical meristem and the number of dividing cells were estimated in vivo without destructive measurement. We found that the rate of cell division contributed more to the variation in cell production rate than the number of dividing cells. Regardless of the source of variation, the length of the elongation zone was the best proxy for growth rate, summarizing rates of cell production and cell elongation into a single parameter. Our results demonstrate that cell production rate is the main driver of growth rate, whereas elemental elongation rate is a key driver of short-term growth adjustments.

KymoRod: a method for automated kinematic analysis of rod-shaped plant organs.

A major challenge in plant systems biology is the development of robust, predictive multiscale models for organ growth. In this context it is important to bridge the gap between the, rather well-documented molecular scale and the organ scale by providing quantitative methods to study within-organ growth patterns. Here, we describe a simple method for the analysis of the evolution of growth patterns within rod-shaped organs that does not require adding markers at the organ surface. The method allows for the simultaneous analysis of root and hypocotyl growth, provides spatio-temporal information on curvature, growth anisotropy and relative elemental growth rate and can cope with complex organ movements. We demonstrate the performance of the method by documenting previously unsuspected complex growth patterns within the growing hypocotyl of the model species Arabidopsis thaliana during normal growth, after treatment with a growth-inhibiting drug or in a mechano-sensing mutant. The method is freely available as an intuitive and user-friendly Matlab application called KymoRod.

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.

New Growth-Related Features of Wheat Grain Pericarp Revealed by Synchrotron-Based X-ray Micro-Tomography and 3D Reconstruction.

Wheat (Triticum aestivum L.) is one of the most important crops as it provides 20% of calories and proteins to the human population. To overcome the increasing demand in wheat grain production, there is a need for a higher grain yield, and this can be achieved in particular through an increase in the grain weight. Moreover, grain shape is an important trait regarding the milling performance. Both the final grain weight and shape would benefit from a comprehensive knowledge of the morphological and anatomical determinism of wheat grain growth. Synchrotron-based phase-contrast X-ray microtomography (X-ray µCT) was used to study the 3D anatomy of the growing wheat grain during the first developmental stages. Coupled with 3D reconstruction, this method revealed changes in the grain shape and new cellular features. The study focused on a particular tissue, the pericarp, which has been hypothesized to be involved in the control of grain development. We showed considerable spatio-temporal diversity in cell shape and orientations, and in tissue porosity associated with stomata detection. These results highlight the growth-related features rarely studied in cereal grains, which may contribute significantly to the final grain weight and shape.

Quantification of Cell Division Angles in the Arabidopsis Root.

In many plant tissues, division plane orientation within cell files is highly predictable since all cells divide almost perpendicular to the cell file axis. Many mutations can affect division plane orientation, and the quantification of the deviation from the expected transverse orientation in various genetic backgrounds is thus an important issue.While several software tools have been proposed for the quantification of cellular morphology in plant tissues, none of them allowed investigating division plane orientation. We propose here a complete method for measuring orientation of division planes in 2D, using an open-source ImageJ plugin named "Cell File Angles." The method comprises the staining of cell wall within whole mount roots with the calcofluor dye, the acquisition of 3D Z-stacks of the stained roots, and the measurement of cell wall orientation using image processing algorithms and semi-automated analysis.

Spatial correlation of water distribution and fine structure of arabinoxylans in the developing wheat grain.

This study was to investigate the distribution of water and arabinoxylan structures in growing wheat grain using two complementary imaging techniques, magnetic resonance microimaging (µMRI) and mass spectrometry imaging (MSI). µMRI showed an inhomogeneous water distribution, particularly at early stages. This heterogeneity revealed histological differences that corresponded, within the limits of resolution of µMRI, to tissues with specific physiological functions, including the vascular bundles, the cavity and the endosperm periphery. All of these tissues had a higher water content than the central endosperm. MSI revealed distinct xylan structures in these regions with high levels of Araf substitution around the cavity and acetylated xylans concentrated at the endosperm periphery. For the first time, acetylation and Araf substitution of arabinoxylans were found by image processing to spatially correlate with water distribution in planta. Acetylation and Araf substitution of xylans, which alter chain-chain interactions and increase wall porosity, decreased as the grain matured.

A Hitchhiker's guide through the bio-image analysis software universe.

Modern research in the life sciences is unthinkable without computational methods for extracting, quantifying and visualising information derived from microscopy imaging data of biological samples. In the past decade, we observed a dramatic increase in available software packages for these purposes. As it is increasingly difficult to keep track of the number of available image analysis platforms, tool collections, components and emerging technologies, we provide a conservative overview of software that we use in daily routine and give insights into emerging new tools. We give guidance on which aspects to consider when choosing the platform that best suits the user's needs, including aspects such as image data type, skills of the team, infrastructure and community at the institute and availability of time and budget.

Brain virtual histology with X-ray phase-contrast tomography Part II:3D morphologies of amyloid-ß plaques in Alzheimer's disease models.

While numerous transgenic mouse strains have been produced to model the formation of amyloid-ß (Aß) plaques in the brain, efficient methods for whole-brain 3D analysis of Aß deposits have to be validated and standardized. Moreover, routine immunohistochemistry performed on brain slices precludes any shape analysis of Aß plaques, or require complex procedures for serial acquisition and reconstruction. The present study shows how in-line (propagation-based) X-ray phase-contrast tomography (XPCT) combined with ethanol-induced brain sample dehydration enables hippocampus-wide detection and morphometric analysis of Aß plaques. Performed in three distinct Alzheimer mouse strains, the proposed workflow identified differences in signal intensity and 3D shape parameters: 3xTg displayed a different type of Aß plaques, with a larger volume and area, greater elongation, flatness and mean breadth, and more intense average signal than J20 and APP/PS1. As a label-free non-destructive technique, XPCT can be combined with standard immunohistochemistry. XPCT virtual histology could thus become instrumental in quantifying the 3D spreading and the morphological impact of seeding when studying prion-like properties of Aß aggregates in animal models of Alzheimer's disease. This is Part II of a series of two articles reporting the value of in-line XPCT for virtual histology of the brain; Part I shows how in-line XPCT enables 3D myelin mapping in the whole rodent brain and in human autopsy brain tissue.

Darkfield and Fluorescence Macrovision of a Series of Large Images to Assess Anatomical and Chemical Tissue Variability in Whole Cross-Sections of Maize Stems.

The proportion and composition of plant tissues in maize stems vary with genotype and agroclimatic factors and may impact the final biomass use. In this manuscript, we propose a quantitative histology approach without any section labelling to estimate the proportion of different tissues in maize stem sections as well as their chemical characteristics. Macroscopic imaging was chosen to observe the entire section of a stem. Darkfield illumination was retained to visualise the whole stem cellular structure. Multispectral autofluorescence images were acquired to detect cell wall phenolic compounds after UV and visible excitations. Image analysis was implemented to extract morphological features and autofluorescence pseudospectra. By assimilating the internode to a cylinder, the relative proportions of tissues in the internode were estimated from their relative areas in the sections. The approach was applied to study a series of 14 maize inbred lines. Considerable variability was revealed among the 14 inbred lines for both anatomical and chemical traits. The most discriminant morphological descriptors were the relative amount of rind and parenchyma tissues together with the density and size of the individual bundles, the area of stem and the parenchyma cell diameter. The rind, as the most lignified tissue, showed strong visible-induced fluorescence which was line-dependant. The relative amount of para-coumaric acid was associated with the UV-induced fluorescence intensity in the rind and in the parenchyma near the rind, while ferulic acid amount was significantly correlated mainly with the parenchyma near the rind. The correlation between lignin and the tissue pseudospectra showed that a global higher amount of lignin resulted in a higher level of lignin fluorescence whatever the tissues. We demonstrated here the potential of darkfield and autofluorescence imaging coupled with image analysis to quantify histology of maize stem and highlight variability between different lines.

Stereological estimation of cell wall density of DR12 tomato mutant using three-dimensional confocal imaging.

BACKGROUND AND AIMS: The cellular structure of fleshy fruits is of interest to study fruit shape, size, mechanical behaviour or sensory texture. The cellular structure is usually not observed in the whole fruit but, instead, in a sample of limited size and volume. It is therefore difficult to extend measurements to the whole fruit and/or to a specific genotype, or to describe the cellular structure heterogeneity within the fruit. METHODS: An integrated method is presented to describe the cellular structure of the whole fruit from partial three-dimensional (3D) observations, involving the following steps: (1) fruit sampling, (2) 3D image acquisition and processing and (3) measurement and estimation of relevant 3D morphological parameters. This method was applied to characterize DR12 mutant and wild-type tomatoes (Solanum lycopersicum). KEY RESULTS: The cellular structure was described using the total volume of the pericarp, the surface area of the cell walls and the ratio of cell-wall surface area to pericarp volume, referred to as the cell-wall surface density. The heterogeneity of cellular structure within the fruit was investigated by estimating variations in the cell-wall surface density with distance to the epidermis. CONCLUSIONS: The DR12 mutant presents a greater pericarp volume and an increase of cell-wall surface density under the epidermis.

Parametric mapping of cellular morphology in plant tissue sections by gray level granulometry.

BACKGROUND: The cellular morphology of plant organs is strongly related to other physical properties such as shape, size, growth, mechanical properties or chemical composition. Cell morphology often vary depending on the type of tissue, or on the distance to a specific tissue. A common challenge in quantitative plant histology is to quantify not only the cellular morphology, but also its variations within the image or the organ. Image texture analysis is a fundamental tool in many areas of image analysis, that was proven efficient for plant histology, but at the scale of the whole image. RESULTS: This work presents a method that generates a parametric mapping of cellular morphology within images of plant tissues. It is based on gray level granulometry from mathematical morphology for extracting image texture features, and on Centroidal Voronoi Diagram for generating a partition of the image. Resulting granulometric curves can be interpreted either through multivariate data analysis or by using summary features corresponding to the local average cell size. The resulting parametric maps describe the variations of cellular morphology within the organ. CONCLUSIONS: We propose a methodology for the quantification of cellular morphology and of its variations within images of tissue sections. The results should help understanding how the cellular morphology is related to genotypic and / or environmental variations, and clarify the relationships between cellular morphology and chemical composition of cell walls.

Use of X-ray micro computed tomography imaging to analyze the morphology of wheat grain through its development.

BACKGROUND: Wheat is one of the most important staple source in the world for human consumption, animal feed and industrial raw materials. To deal with the global and increasing population demand, enhancing crop yield by increasing the final weight of individual grain is considered as a feasible solution. Morphometric analysis of wheat grain plays an important role in tracking and understanding developmental processes by assessing potential impacts on grains properties, size and shape that are major determinants of final grain weight. X-ray micro computed tomography (µCT) is a very powerful non-invasive imaging tool that is able to acquire 3D images of an individual grain, enabling to assess the morphology of wheat grain and of its different compartments. Our objective is to quantify changes of morphology during growth stages of wheat grain from 3D µCT images. METHODS: 3D µCT images of wheat grains were acquired at various development stages ranging from 60 to 310 degree days after anthesis. We developed robust methods for the identification of outer and inner tissues within the grains, and the extraction of morphometric features using 3D µCT images. We also developed a specific workflow for the quantification of the shape of the grain crease. RESULTS: The different compartments of the grain could be semi-automatically segmented. Variations of volumes of the compartments adequately describe the different stages of grain developments. The evolution of voids within wheat grain reflects lysis of outer tissues and growth of inner tissues. The crease shape could be quantified for each grain and averaged for each stage of development, helping us understand the genesis of the grain shape. CONCLUSION: This work shows that µCT acquisitions and image processing methodologies are powerful tools to extract morphometric parameters of developing wheat grain. The results of quantitative analysis revealed remarkable features of wheat grain growth. Further work will focus on building a computational model of wheat grain growth based on real 3D imaging data.

Changes in cell walls lignification, feruloylation and p-coumaroylation throughout maize internode development.

Plant cell walls development is an integrated process during which several components are deposited successively. In the cell walls in grass, the accessibility of structural polysaccharides is limited by the cell walls structure and composition mainly as a result of phenolic compounds. Here, we studied the patterns of cell walls establishment in the internode supporting the ear in three distinct maize genotypes. The developmental patterns observed in the internode cell walls in terms of its composition are reported with an emphasis on lignification, p-coumaroylation and feruloylation. We combined biochemical and histological approaches and revealed that internode cell walls development in maize before flowering is characterized by the rapid deposition of secondary cell walls components and robust lignification in both the pith and the rind. After flowering and until silage maturity, the slow deposition of secondary walls components occurs in the cortical region, and the deposited lignins are rich in ß-O-4 bonds and are highly p-coumaroylated. We conclude the paper by proposing a revised spatiotemporal model based on that proposed by Terashima et al. (1993) for cell walls development in grass.

Impact of Two-Dimensional Particle Size Distribution on Estimation of Water Vapor Diffusivity in Micrometric Size Cellulose Particles.

This work aims at assessing the impact of two-dimensional particle size distribution (2D-PSD) on the identification of water vapor diffusivity in micrometric size cellulose particles displaying a size aspect ratio lower than 2 and a cylindrical shape. First, different methodologies to obtain the two-dimensional (2D) particle size distribution (diameter versus length) were compared, based on image analysis. Then, experimental sorption kinetics were obtained by using a quartz crystal microbalance (QCM) coupled with a water vapor adsorption system. Diffusivity values were estimated when considering either the 2D-PSD or global descriptors, such as the mean or median diameter and length of particles. Results revealed that the use of an analytical approach when considering the 2D mean-PSD or the median-PSD was the most accurate way to get diffusivity values at the scale of particles in a polydisperse sample of cellulose particles. Following this approach, a water vapor apparent diffusivity of 3.1 × 10-12 ± 2.3 × 10-12 m²·s-1 was found for the considered cellulose sample. Neglecting PSD in diffusivity estimation led to an underestimation of a factor of 2. This procedure could be extended for all the polydisperse samples in order to have an accurate estimation of water vapor diffusivity at the scale of single particles.

Histological quantification of maize stem sections from FASGA-stained images.

BACKGROUND: Crop species are of increasing interest both for cattle feeding and for bioethanol production. The degradability of the plant material largely depends on the lignification of the tissues, but it also depends on histological features such as the cellular morphology or the relative amount of each tissue fraction. There is therefore a need for high-throughput phenotyping systems that quantify the histology of plant sections. RESULTS: We developed custom image processing and an analysis procedure for quantifying the histology of maize stem sections coloured with FASGA staining and digitalised with whole microscopy slide scanners. The procedure results in an automated segmentation of the input images into distinct tissue regions. The size and the fraction area of each tissue region can be quantified, as well as the average coloration within each region. The measured features can discriminate contrasted genotypes and identify changes in histology induced by environmental factors such as water deficit. CONCLUSIONS: The simplicity and the availability of the software will facilitate the elucidation of the relationships between the chemical composition of the tissues and changes in plant histology. The tool is expected to be useful for the study of large genetic populations, and to better understand the impact of environmental factors on plant histology.

The preprophase band of microtubules controls the robustness of division orientation in plants.

Controlling cell division plane orientation is essential for morphogenesis in multicellular organisms. In plant cells, the future cortical division plane is marked before mitotic entry by the preprophase band (PPB). Here, we characterized an Arabidopsis trm (TON1 Recruiting Motif) mutant that impairs PPB formation but does not affect interphase microtubules. Unexpectedly, PPB disruption neither abolished the capacity of root cells to define a cortical division zone nor induced aberrant cell division patterns but rather caused a loss of precision in cell division orientation. Our results advocate for a reassessment of PPB function and division plane determination in plants and show that a main output of this microtubule array is to limit spindle rotations in order to increase the robustness of cell division.