Fast linear feature detection using multiple directional non-maximum suppression

A portable fluorescence spectroscopy imaging system for automated root phenotyping in soil cores in the field

Root architecture traits are a target for pre-breeders. Incorporation of root architecture traits into new cultivars requires phenotyping. It is attractive to rapidly and directly phenotype root architecture in the field, avoiding laboratory studies that may not translate to the field. A combination of soil coring with a hydraulic push press and manual core-break counting can directly phenotype root architecture traits of depth and distribution in the field through to grain development, but large teams of people are required and labour costs are high with this method. We developed a portable fluorescence imaging system (BlueBox) to automate root counting in soil cores with image analysis software directly in the field. The lighting system was optimized to produce high-contrast images of roots emerging from soil cores. The correlation of the measurements with the root length density of the soil cores exceeded the correlation achieved by human operator measurements (R (2)=0.68 versus 0.57, respectively). A BlueBox-equipped team processed 4.3 cores/hour/person, compared with 3.7 cores/hour/person for the manual method. The portable, automated in-field root architecture phenotyping system was 16% more labour efficient, 19% more accurate, and 12% cheaper than manual conventional coring, and presents an opportunity to directly phenotype root architecture in the field as part of pre-breeding programs. The platform has wide possibilities to capture more information about root health and other root traits in the field.

Design of Steerable Wavelets to Detect Multifold Junctions

We propose a framework for the detection of junctions in images. Although the detection of edges and key points is a well examined and described area, the multiscale detection of junction centers, especially for odd orders, poses a challenge in pattern analysis. The goal of this paper is to build optimal junction detectors based on 2D steerable wavelets that are polar-separable in the Fourier domain. The approaches we develop are general and can be used for the detection of arbitrary symmetric and asymmetric junctions. The backbone of our construction is a multiscale pyramid with a radial wavelet function where the directional components are represented by circular harmonics and encoded in a shaping matrix. We are able to detect M -fold junctions in different scales and orientations. We provide experimental results on both simulated and real data to demonstrate the effectiveness of the algorithm.

Quantitative analyses on dynamic changes in the organization of host Arabidopsis thaliana actin microfilaments surrounding the infection organ of the powdery mildew fungus Golovinomyces orontii

Obligate biotrophic fungi that cause powdery mildew on host plants form a specialized infection organ called the haustorium in the host apoplast. It was previously reported that the haustorium is surrounded by host actin microfilaments (AFs). The previous study used fixed cells, in which AFs were stained with fluorescently labeled phalloidine, therefore the structural dynamics of haustorium-surrounding AFs has not been examined. In the present study, we performed a live imaging analysis to examine the dynamics and developmental changes in the organization of haustorium-surrounding host AFs using host Arabidopsis thaliana and A. thaliana-adapted powdery mildew fungus Golovinomyces orontii. Image correlation-based velocimetry analysis suggested that AFs around haustorium are rather static compared to the dynamicity of AFs at the cell surface. Quantification of AF density and bundling showed that the density, but not the level of bundling, of haustorium-surrounding AFs increased as the haustorium matures. The possible role of AFs around haustoria is discussed.

An atypical tubulin kinase mediates stress-induced microtubule depolymerization in Arabidopsis

BACKGROUND

As sessile organisms, plants adapt to adverse environmental conditions by quickly adjusting cell physiology and metabolism. Transient depolymerization of interphase microtubules is triggered by various acute stresses and biotic interactions with pathogenic organisms. Although rapid remodeling of plant microtubule arrays in response to external stresses is an intriguing phenomenon, the underlying molecular mechanisms and the advantages of this response to plant performance are poorly understood.

RESULTS

A domain with weak homology to the slime mold actin-fragmin kinase in the Arabidopsis mitogen-activated protein kinase phosphatase PROPYZAMIDE-HYPERSENSITIVE 1 (PHS1) is a Mn2+-dependent kinase. This atypical kinase domain phosphorylates Thr349 of α-tubulin at the longitudinal interdimer interface, thereby generating a polymerization-incompetent isoform, and effectively depolymerizes microtubule arrays when ectopically expressed in plant or animal cells. The intrinsic tubulin kinase activity is normally suppressed by the phosphatase activity of PHS1 but is unmasked immediately after osmotic stress. In the phs1 null mutant, stress-induced microtubule depolymerization does not occur.

CONCLUSIONS

The rapid and reversible modification of tubulin subunits by PHS1-mediated phosphorylation enables dynamic remodeling of the plant microtubule cytoskeleton in response to external stimuli. Suppression of the potent tubulin kinase activity by the juxtaposed phosphatase domain tightly controls this stress-activated microtubule regulator.

Myosin XIK of Arabidopsis thaliana accumulates at the root hair tip and is required for fast root hair growth

Myosin motor proteins are thought to carry out important functions in the establishment and maintenance of cell polarity by moving cellular components such as organelles, vesicles, or protein complexes along the actin cytoskeleton. In Arabidopsis thaliana, disruption of the myosin XIK gene leads to reduced elongation of the highly polar root hairs, suggesting that the encoded motor protein is involved in this cell growth. Detailed live-cell observations in this study revealed that xik root hairs elongated more slowly and stopped growth sooner than those in wild type. Overall cellular organization including the actin cytoskeleton appeared normal, but actin filament dynamics were reduced in the mutant. Accumulation of RabA4b-containing vesicles, on the other hand, was not significantly different from wild type. A functional YFP-XIK fusion protein that could complement the mutant phenotype accumulated at the tip of growing root hairs in an actin-dependent manner. The distribution of YFP-XIK at the tip, however, did not match that of the ER or several tip-enriched markers including CFP-RabA4b. We conclude that the myosin XIK is required for normal actin dynamics and plays a role in the subapical region of growing root hairs to facilitate optimal growth.

Validation of an algorithm to quantify changes in actin cytoskeletal organization

The actin cytoskeleton plays an important role in most, if not all, processes necessary for cell survival. Given the fundamental role that the actin cytoskeleton plays in the progression of cancer, it is an ideal target for chemotherapy. Although it is possible to image the actin cytoskeleton in a high-throughput manner, there is currently no validated method to quantify changes in the cytoskeleton in the same capacity, which makes research into its organization and the development of anticytoskeletal drugs difficult. We have validated the use of a linear feature detection algorithm, allowing us to measure changes in actin filament organization. Its ability to quantify changes associated with cytoskeletal disruption will make it a valuable tool in the development of compounds that target the cytoskeleton in cancer. Our results show that this algorithm can quantify cytoskeletal changes in a cell-based system after addition of both well-established and novel anticytoskeletal agents using either fluorescence microscopy or a high-content imaging approach. This novel method gives us the potential to screen compounds in a high-throughput manner for cancer and other diseases in which the cytoskeleton plays a key role.

Multiple linear feature detection based on multiple-structuring-element center-surround top-hat transform

Linear feature detection is an important technique in different applications of image processing. To detect linear features in different types of images, a simple but effective algorithm based on a multiple-structuring-element center-surround top-hat transform is proposed. The center-surround top-hat transform is discussed and analyzed. Based on the properties of this transform for image feature detection, multiple structuring elements are constructed corresponding to the possible linear features at different directions. The whole algorithm is divided into four parts. First, the algorithm uses the center-surround top-hat transform to detect all the possible linear features at different directions through constructing multiple structuring elements. Second, the detected linear feature regions at each direction are processed by a closing operation to remove the possible holes or unconnected regions. Third, the processed results of the detected linear feature regions at all directions are combined to form all the possible detected linear feature regions. Fourth, the combined result is refined by using some simple operations to form the final result. Experimental results on different types of images from different applications verified the effective performance of the proposed algorithm. Moreover, the experimental results indicate that the proposed algorithm could be used in different applications.

Identifying weak linear features with the "coalescing shortest path image transform"

The detection of line-like features in images finds many applications in microanalysis. Actin fibers, microtubules, neurites, pilis, DNA, and other biological structures all come up as tenuous curved lines in microscopy images. A reliable tracing method that preserves the integrity and details of these structures is particularly important for quantitative analyses. We have developed a new image transform called the "Coalescing Shortest Path Image Transform" with very encouraging properties. Our scheme efficiently combines information from an extensive collection of shortest paths in the image to delineate even very weak linear features.

Automatic 3D neuron tracing using all-path pruning

Motivation: Digital reconstruction, or tracing, of 3D neuron structures is critical toward reverse engineering the wiring and functions of a brain. However, despite a number of existing studies, this task is still challenging, especially when a 3D microscopic image has low signal-to-noise ratio (SNR) and fragmented neuron segments. Published work can handle these hard situations only by introducing global prior information, such as where a neurite segment starts and terminates. However, manual incorporation of such global information can be very time consuming. Thus, a completely automatic approach for these hard situations is highly desirable.

Results: We have developed an automatic graph algorithm, called the all-path pruning (APP), to trace the 3D structure of a neuron. To avoid potential mis-tracing of some parts of a neuron, an APP first produces an initial over-reconstruction, by tracing the optimal geodesic shortest path from the seed location to every possible destination voxel/pixel location in the image. Since the initial reconstruction contains all the possible paths and thus could contain redundant structural components (SC), we simplify the entire reconstruction without compromising its connectedness by pruning the redundant structural elements, using a new maximal-covering minimal-redundant (MCMR) subgraph algorithm. We show that MCMR has a linear computational complexity and will converge. We examined the performance of our method using challenging 3D neuronal image datasets of model organisms (e.g. fruit fly).

Availability: The software is available upon request. We plan to eventually release the software as a plugin of the V3D-Neuron package at http://penglab.janelia.org/proj/v3d.

Contact:pengh@janelia.hhmi.org

The Rho kinase inhibitor Fasudil up-regulates astrocytic glutamate transport subsequent to actin remodelling in murine cultured astrocytes

BACKGROUND AND PURPOSE

Glutamate transporters play a major role in maintaining brain homeostasis and the astrocytic transporters, EAAT1 and EAAT2, are functionally dominant. Astrocytic excitatory amino acid transporters (EAATs) play important roles in various neuropathologies wherein astrocytes undergo cytoskeletal changes. Astrocytic plasticity is well documented, but the interface between EAAT function, actin and the astrocytic cytoskeleton is poorly understood. Because Rho kinase (ROCK) is a key determinant of actin polymerization, we investigated the effects of ROCK inhibitors on EAAT activity and astrocytic morphology.

EXPERIMENTAL APPROACH

The functional activity of glutamate transport was determined in murine cultured astrocytes after exposure to the ROCK inhibitors Fasudil (HA-1077) and Y27632 using biochemical, molecular and morphological approaches. Cytochemical analyses assessed changes in astrocytic morphology, F-/G-actin, and localizations of EAAT1/2.

RESULTS

Fasudil and Y27632 increased [(3)H]-D-aspartate (D-Asp) uptake into astrocytes, and the action of Fasudil was time-dependent and concentration-related. The rapid stellation of astrocytes (glial fibrillary acidic protein immunocytochemistry) induced by Fasudil was accompanied by reduced phalloidin staining of F-actin and increased V(max) for [(3)H]-D-Asp uptake. Immunoblotting after biotinylation demonstrated that Fasudil increased the expression of EAAT1 and EAAT2 on the cell surface. Immunocytochemistry indicated that Fasudil induced prominent labelling of astrocytic processes by EAAT1/2.

CONCLUSION AND IMPLICATIONS

These data show for the first time that ROCK plays a major role in determining the cell surface expression of EAAT1/2, providing new evidence for an association between transporter function and astrocytic phenotype. ROCK inhibitors, via the actin cytoskeleton, effect a consequent elevation of glutamate transporter function - this activity profile may contribute to their beneficial actions in neuropathologies.

NeurphologyJ: an automatic neuronal morphology quantification method and its application in pharmacological discovery

Background

Automatic quantification of neuronal morphology from images of fluorescence microscopy plays an increasingly important role in high-content screenings. However, there exist very few freeware tools and methods which provide automatic neuronal morphology quantification for pharmacological discovery.

Results

This study proposes an effective quantification method, called NeurphologyJ, capable of automatically quantifying neuronal morphologies such as soma number and size, neurite length, and neurite branching complexity (which is highly related to the numbers of attachment points and ending points). NeurphologyJ is implemented as a plugin to ImageJ, an open-source Java-based image processing and analysis platform. The high performance of NeurphologyJ arises mainly from an elegant image enhancement method. Consequently, some morphology operations of image processing can be efficiently applied. We evaluated NeurphologyJ by comparing it with both the computer-aided manual tracing method NeuronJ and an existing ImageJ-based plugin method NeuriteTracer. Our results reveal that NeurphologyJ is comparable to NeuronJ, that the coefficient correlation between the estimated neurite lengths is as high as 0.992. NeurphologyJ can accurately measure neurite length, soma number, neurite attachment points, and neurite ending points from a single image. Furthermore, the quantification result of nocodazole perturbation is consistent with its known inhibitory effect on neurite outgrowth. We were also able to calculate the IC50 of nocodazole using NeurphologyJ. This reveals that NeurphologyJ is effective enough to be utilized in applications of pharmacological discoveries.

Conclusions

This study proposes an automatic and fast neuronal quantification method NeurphologyJ. The ImageJ plugin with supports of batch processing is easily customized for dealing with high-content screening applications. The source codes of NeurphologyJ (interactive and high-throughput versions) and the images used for testing are freely available (see Availability).

Neuron tracing in perspective

The study of the structure and function of neuronal cells and networks is of crucial importance in the endeavor to understand how the brain works. A key component in this process is the extraction of neuronal morphology from microscopic imaging data. In the past four decades, many computational methods and tools have been developed for digital reconstruction of neurons from images, with limited success. As witnessed by the growing body of literature on the subject, as well as the organization of challenging competitions in the field, the quest for a robust and fully automated system of more general applicability still continues. The aim of this work, is to contribute by surveying recent developments in the field for anyone interested in taking up the challenge. Relevant aspects discussed in the article include proposed image segmentation methods, quantitative measures of neuronal morphology, currently available software tools for various related purposes, and morphology databases. (c) 2010 International Society for Advancement of Cytometry.

HCA-vision: Automated neurite outgrowth analysis

Automating the analysis of neurons in culture represents a key aspect of the search for neuroactive compounds. A number of commercial neurite analysis software packages tend to measure some basic features such as total neurite length and number of branching points. However, with only these measurements, some differences between neurite morphologies that are clear to a human observer cannot be identified. The authors have developed a suite of image analysis tools that will allow researchers to produce quality analyses at primary screening rates. The suite provides sensitive and information-rich measurements of neurons and neurites. It can discriminate subtle changes in complex neurite arborization even when neurons and neurites are dense. This allows users to selectively screen for compounds triggering different types of neurite outgrowth behavior. In mixed cell populations, neurons can be filtered and separated from other brain cell types so that neurite analysis can be performed only on neurons. It supports batch processing with a built-in database to store the batch-processing results, a batch result viewer, and an ad hoc query builder for users to retrieve features of interest. The suite of tools has been deployed into a software package called HCA-Vision. The free version of the software package is available at http://www.hca-vision.com.

Automatic robust neurite detection and morphological analysis of neuronal cell cultures in high-content screening

Cell-based high content screening (HCS) is becoming an important and increasingly favored approach in therapeutic drug discovery and functional genomics. In HCS, changes in cellular morphology and biomarker distributions provide an information-rich profile of cellular responses to experimental treatments such as small molecules or gene knockdown probes. One obstacle that currently exists with such cell-based assays is the availability of image processing algorithms that are capable of reliably and automatically analyzing large HCS image sets. HCS images of primary neuronal cell cultures are particularly challenging to analyze due to complex cellular morphology. Here we present a robust method for quantifying and statistically analyzing the morphology of neuronal cells in HCS images. The major advantages of our method over existing software lie in its capability to correct non-uniform illumination using the contrast-limited adaptive histogram equalization method; segment neuromeres using Gabor-wavelet texture analysis; and detect faint neurites by a novel phase-based neurite extraction algorithm that is invariant to changes in illumination and contrast and can accurately localize neurites. Our method was successfully applied to analyze a large HCS image set generated in a morphology screen for polyglutamine-mediated neuronal toxicity using primary neuronal cell cultures derived from embryos of a Drosophila Huntington's Disease (HD) model.