Quantifying morphological features of actin cytoskeletal filaments in plant cells based on mathematical morphology

Grading the Severity of Damage to the Perijunctional Actomyosin Ring and Zonula Occludens-1 of the Corneal Endothelium by Ensemble Learning Methods

Purpose: In many epithelia, including the corneal endothelium, intracellular/extracellular stresses break down the perijunctional actomyosin ring (PAMR) and zonula occludens-1 (ZO-1) at the apical junctions. This study aims to grade the severity of damage to PAMR and ZO-1 through machine learning. Methods: Immunocytochemical images of PAMR and ZO-1 were drawn from recent studies on the corneal endothelium subjected to hypothermia and oxidative stress. The images were analyzed for their morphological (e.g., Hu moments) and textural features (based on gray-level co-occurrence matrix [GLCM] and Gabor filters). The extracted features were ranked by SHapley analysis and analysis of variance. Then top features were used to grade the severity of damage using a suite of ensemble classifiers, including random forest, bagging classifier (BC), AdaBoost, extreme gradient boosting, and stacking classifier. Results: A partial set of features from GLCM, along with Hu moments and the number of hexagons, enabled the classification of damage to PAMR into Control, Mild, Moderate, and Severe with the area under the receiver operating characteristics curve (AUC) = 0.92 and F1 score = 0.77 with BC. In contrast, a bank of Gabor filters provided a partial set of features that could be combined with Hu moments, branch length, and sharpness for the classification of ZO-1 images into four levels with AUC = 0.95 and F1 score of 0.8 with BC. Conclusions: We have developed a workflow that enables the stratification of damage to PAMR and ZO-1. The approach can be applied to similar data during drug discovery or pathophysiological studies of epithelia.

Pexophagy suppresses ROS-induced damage in leaf cells under high-intensity light

Although light is essential for photosynthesis, it has the potential to elevate intracellular levels of reactive oxygen species (ROS). Since high ROS levels are cytotoxic, plants must alleviate such damage. However, the cellular mechanism underlying ROS-induced leaf damage alleviation in peroxisomes was not fully explored. Here, we show that autophagy plays a pivotal role in the selective removal of ROS-generating peroxisomes, which protects plants from oxidative damage during photosynthesis. We present evidence that autophagy-deficient mutants show light intensity-dependent leaf damage and excess aggregation of ROS-accumulating peroxisomes. The peroxisome aggregates are specifically engulfed by pre-autophagosomal structures and vacuolar membranes in both leaf cells and isolated vacuoles, but they are not degraded in mutants. ATG18a-GFP and GFP-2×FYVE, which bind to phosphatidylinositol 3-phosphate, preferentially target the peroxisomal membranes and pre-autophagosomal structures near peroxisomes in ROS-accumulating cells under high-intensity light. Our findings provide deeper insights into the plant stress response caused by light irradiation.

Coefficient of variation as an image-intensity metric for cytoskeleton bundling

The evaluation of cytoskeletal bundling is a fundamental experimental method in the field of cell biology. Although the skewness of the pixel intensity distribution derived from fluorescently-labeled cytoskeletons has been widely used as a metric to evaluate the degree of bundling in digital microscopy images, its versatility has not been fully validated. Here, we applied the coefficient of variation (CV) of intensity values as an alternative metric, and compared its performance with skewness. In synthetic images representing extremely bundled conditions, the CV successfully detected degrees of bundling that could not be distinguished by skewness. On actual microscopy images, CV was better than skewness, especially on variable-angle epifluorescence microscopic images or stimulated emission depletion and confocal microscopy images of very small areas of around 1 μm2. When blur or noise was added to synthetic images, CV was found to be robust to blur but deleteriously affected by noise, whereas skewness was robust to noise but deleteriously affected by blur. For confocal images, CV and skewness showed similar sensitivity to noise, possibly because optical blurring is often present in microscopy images. Therefore, in practical use with actual microscopy images, CV may be more appropriate than skewness, unless the image is extremely noisy.

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.

A Method for Evaluating Three-Dimensional Morphological Features: A Case Study Using Marchantia polymorpha

The description and evaluation of morphological features are essential to many biological studies. Bioimaging and quantification methods have been developed to analyze the morphological features of plants. However, efficient three-dimensional (3D) imaging and its quantification are still under development, particularly for studies of plant morphology, due to complex organ structure with great flexibility among individuals with the same genotype. In this study, we propose a new approach that combines a 3D imaging technique using micro-computed tomography and a mathematical image-processing method to describe 3D morphological features. As an example, we applied this method to Marchantia polymorpha, a new model plant used for the evolutional study of land plants, and we evaluated a mutant individual with an abnormal 3D shape. Using this new method, we quantitatively described the thallus morphology of M. polymorpha and distinguished the wild type from a mutant with different morphological features. Our newly established method can be applied to various tissues or bodies with irregular 3D morphology.

An Image Recognition-Based Approach to Actin Cytoskeleton Quantification

Quantification of the actin cytoskeleton is of prime importance to unveil the cellular force sensing and transduction mechanism. Although fluorescence imaging provides a convenient tool for observing the morphology of the actin cytoskeleton, due to the lack of approaches to accurate actin cytoskeleton quantification, the dynamics of mechanotransduction is still poorly understood. Currently, the existing image-based actin cytoskeleton analysis tools are either incapable of quantifying both the orientation and the quantity of the actin cytoskeleton simultaneously or the quantified results are subject to analysis artifacts. In this study, we propose an image recognition-based actin cytoskeleton quantification (IRAQ) approach, which quantifies both the actin cytoskeleton orientation and quantity by using edge, line, and brightness detection algorithms. The actin cytoskeleton is quantified through three parameters: the partial actin-cytoskeletal deviation (PAD), the total actin-cytoskeletal deviation (TAD), and the average actin-cytoskeletal intensity (AAI). First, Canny and Sobel edge detectors are applied to skeletonize the actin cytoskeleton images, then PAD and TAD are quantified using the line directions detected by Hough transform, and AAI is calculated through the summational brightness over the detected cell area. To verify the quantification accuracy, the proposed IRAQ was applied to six artificially-generated actin cytoskeleton mesh work models. The average error for both the quantified PAD and TAD was less than 1.22 ∘ . Then, IRAQ was implemented to quantify the actin cytoskeleton of NIH/3T3 cells treated with an F-actin inhibitor (latrunculin B). The quantification results suggest that the local and total actin-cytoskeletal organization became more disordered with the increase of latrunculin B dosage, and the quantity of the actin cytoskeleton showed a monotonically decreasing relation with latrunculin B dosage.

Heterogeneous distribution of doublecortin-expressing cells surrounding the rostral migratory stream in the juvenile mouse

In the postnatal mammalian brain, neural stem cells of the ventricular-subventricular zone continue to generate doublecortin (Dcx)-expressing immature neurons. Throughout life, these immature neurons migrate to the olfactory bulb through the rostral migratory stream (RMS). In this study, we investigated the distribution of these putative immature neurons using enhanced green fluorescent protein (EGFP) expression in the area surrounding the RMS of the juvenile Dcx-EGFP mice. Through the combined use of an optical clearing reagent (a 2,2'-thiodiethanol solution) and two-photon microscopy, we visualized three-dimensionally the EGFP-positive cells in the entire RMS and its surroundings. The resulting wide-field and high-definition images along with computational image processing methods developed in this study were used to comprehensively determine the position of the EGFP-positive cells. Our findings revealed that the EGFP-positive cells were heterogeneously distributed in the area surrounding the RMS. In addition, the orientation patterns of the leading process of these cells, which displayed the morphology of migrating immature neurons, differed depending on their location. These novel results provide highly precise morphological information for immature neurons and suggest that a portion of immature neurons may be detached from the RMS and migrate in various directions.

ANGUSTIFOLIA contributes to the regulation of three-dimensional morphogenesis in the liverwort Marchantia polymorpha

Arabidopsis thaliana mutants deficient in ANGUSTIFOLIA (AN) exhibit several phenotypes at the sporophyte stage, such as narrow and thicker leaves, trichomes with two branches, and twisted fruits. It is thought that these phenotypes are caused by abnormal arrangement of cortical microtubules (MTs). AN homologs are present in the genomes of diverse land plants, including the basal land plant Marchantia polymorpha, and their molecular functions have been shown to be evolutionarily conserved in terms of the ability to complement the A. thaliana an-1 mutation. However, the roles of ANs in bryophytes, the life cycle of which includes a dominant haploid gametophyte generation, remain unknown. Here, we have examined the roles of AN homologs in the model bryophyte M. polymorpha (MpAN). Mpan knockout mutants showed abnormal twisted thalli and suppressed thallus growth along the growth axis. Under weak blue light conditions, elongated thallus growth was observed in wild-type plants, whereas it was suppressed in the mutants. Moreover, disordered cortical MT orientations were observed. Our findings suggest that MpAN contributes to three-dimensional morphogenesis by regulating cortical MT arrangement in the gametophytes of bryophytes.

Making microscopy count: quantitative light microscopy of dynamic processes in living plants

Cell theory has officially reached 350 years of age as the first use of the word 'cell' in a biological context can be traced to a description of plant material by Robert Hooke in his historic publication 'Micrographia: or some physiological definitions of minute bodies'. The 2015 Royal Microscopical Society Botanical Microscopy meeting was a celebration of the streams of investigation initiated by Hooke to understand at the subcellular scale how plant cell function and form arises. Much of the work presented, and Honorary Fellowships awarded, reflected the advanced application of bioimaging informatics to extract quantitative data from micrographs that reveal dynamic molecular processes driving cell growth and physiology. The field has progressed from collecting many pixels in multiple modes to associating these measurements with objects or features that are meaningful biologically. The additional complexity involves object identification that draws on a different type of expertise from computer science and statistics that is often impenetrable to biologists. There are many useful tools and approaches being developed, but we now need more interdisciplinary exchange to use them effectively. In this review we show how this quiet revolution has provided tools available to any personal computer user. We also discuss the oft-neglected issue of quantifying algorithm robustness and the exciting possibilities offered through the integration of physiological information generated by biosensors with object detection and tracking.