Boguslaw Obara

Variability in the Control of Cell Division Underlies Sepal Epidermal Patterning in Arabidopsis thaliana

Live cell imaging and computational modeling explains how variability in the timing of cell division generates a characteristic pattern of cell sizes during development.

Bisque: a platform for bioimage analysis and management

MOTIVATION Advances in the field of microscopy have brought about the need for better image management and analysis solutions. Novel imaging techniques have created vast stores of images and metadata that are difficult to organize, search, process and analyze. These tasks are further complicated by conflicting and proprietary image and metadata formats, that impede analyzing and sharing of images and any associated data. These obstacles have resulted in research resources being locked away in digital media and file cabinets. Current image management systems do not address the pressing needs of researchers who must quantify image data on a regular basis. RESULTS We present Bisque, a web-based platform specifically designed to provide researchers with organizational and quantitative analysis tools for 5D image data. Users can extend Bisque with both data model and analysis extensions in order to adapt the system to local needs. Bisques extensibility stems from two core concepts: flexible metadata facility and an open web-based architecture. Together these empower researchers to create, develop and share novel bioimage analyses. Several case studies using Bisque with specific applications are presented as an indication of how users can expect to extend Bisque for their own purposes.

Silencing of CDK5 Reduces Neurofibrillary Tangles in Transgenic Alzheimer's Mice

Alzheimers disease is a major cause of dementia for which treatments remain unsatisfactory. Cyclin-dependent kinase 5 (CDK5) is a relevant kinase that has been hypothesized to contribute to the tau pathology. Several classes of chemical inhibitors for CDK5 have been developed, but they generally lack the specificity to distinguish among various ATP-dependent kinases. Therefore, the efficacy of these compounds when tested in animal models cannot definitively be attributed to an effect on CDK5. However, RNA interference (RNAi) targeting of CDK5 is specific and can be used to validate CDK5 as a possible treatment target. We delivered a CDK5 RNAi by lentiviral or adenoassociated viral vectors and analyzed the results in vitro and in vivo. Silencing of CDK5 reduces the phosphorylation of tau in primary neuronal cultures and in the brain of wild-type C57BL/6 mice. Furthermore, the knockdown of CDK5 strongly decreased the number of neurofibrillary tangles in the hippocampi of triple-transgenic mice (3×Tg-AD mice). Our data suggest that this downregulation may be attributable to the reduction of the CDK5 availability in the tissue, without affecting the CDK5 kinase activity. In summary, our findings validate CDK5 as a reasonable therapeutic target for ameliorating tau pathology.

A biosegmentation benchmark for evaluation of bioimage analysis methods

BackgroundWe present a biosegmentation benchmark that includes infrastructure, datasets with associated ground truth, and validation methods for biological image analysis. The primary motivation for creating this resource comes from the fact that it is very difficult, if not impossible, for an end-user to choose from a wide range of segmentation methods available in the literature for a particular bioimaging problem. No single algorithm is likely to be equally effective on diverse set of images and each method has its own strengths and limitations. We hope that our benchmark resource would be of considerable help to both the bioimaging researchers looking for novel image processing methods and image processing researchers exploring application of their methods to biology.ResultsOur benchmark consists of different classes of images and ground truth data, ranging in scale from subcellular, cellular to tissue level, each of which pose their own set of challenges to image analysis. The associated ground truth data can be used to evaluate the effectiveness of different methods, to improve methods and to compare results. Standard evaluation methods and some analysis tools are integrated into a database framework that is available online at http://bioimage.ucsb.edu/biosegmentation/.ConclusionThis online benchmark will facilitate integration and comparison of image analysis methods for bioimages. While the primary focus is on biological images, we believe that the dataset and infrastructure will be of interest to researchers and developers working with biological image analysis, image segmentation and object tracking in general.

Evaluation and benchmark for biological image segmentation

This paper describes ongoing work on creating a benchmarking and validation dataset for biological image segmentation. While the primary target is biological images, we believe that the dataset would be of help to researchers working in image segmentation and tracking in general. The motivation for creating this resource comes from the observation that while there are a large number of effective segmentation methods available in the research literature, it is difficult for the application scientists to make an informed choice as to what methods would work for her particular problem. No one single tool exists that is effective on a diverse set of application contexts and different methods have their own strengths and limitations. We describe below three different classes of data, ranging in scale from subcellular to cellular to tissue level images, each of which pose their own set of challenges to image analysis. Of particular value to the image processing researchers is that the data comes with associated ground truth information that can be used to evaluate the effectiveness of different methods. The analysis and evaluation are also integrated into a database framework that is available online at http://dough.ece.ucsb.edu.

Flagellar Hook Flexibility Is Essential for Bundle Formation in Swimming Escherichia coli Cells

Swimming Escherichia coli cells are propelled by the rotary motion of their flagellar filaments. In the normal swimming pattern, filaments positioned randomly over the cell form a bundle at the posterior pole. It has long been assumed that the hook functions as a universal joint, transmitting rotation on the motor axis through up to ∼90° to the filament in the bundle. Structural models of the hook have revealed how its flexibility is expected to arise from dynamic changes in the distance between monomers in the helical lattice. In particular, each of the 11 protofilaments that comprise the hook is predicted to cycle between short and long forms, corresponding to the inside and outside of the curved hook, once each revolution of the motor when the hook is acting as a universal joint. To test this, we genetically modified the hook so that it could be stiffened by binding streptavidin to biotinylated monomers, impeding their motion relative to each other. We found that impeding the action of the universal joint resulted in atypical swimming behavior as a consequence of disrupted bundle formation, in agreement with the universal joint model.

Contrast-Independent Curvilinear Structure Detection in Biomedical Images

Many biomedical applications require detection of curvilinear structures in images and would benefit from automatic or semiautomatic segmentation to allow high-throughput measurements. Here, we propose a contrast-independent approach to identify curvilinear structures based on oriented phase congruency, i.e., the phase congruency tensor (PCT). We show that the proposed method is largely insensitive to intensity variations along the curve and provides successful detection within noisy regions. The performance of the PCT is evaluated by comparing it with state-of-the-art intensity-based approaches on both synthetic and real biological images.

Identification of transcrystalline microcracks observed in microscope images of a dolomite structure using image analysis methods based on linear structuring element processing

This paper presents an image analysis algorithm for transcrystalline microcracks recognition. The algorithm is applied for the analysis of microscope images of a dolomite structure. Linear structures are derived using an image analysis method based on mathematical morphology functions utilizing linear structuring elements. Next, the standard deviation function of microcracks and grain boundaries of surrounding pixel values is used to determine transcrystalline microcracks. All operations were executed in CIELab colour representations of dolomite images. The results obtained confirm the adequacy of this approach as a robust segmentation tool. Accordingly, an algorithm was derived that allows a fully automatic segmentation of transcrystalline microcracks. This is followed by geometrical and statistical analysis. The developed algorithm may facilitate petrographical and stereological studies of rock structures observed under a polarizing microscope.

CDC-42 and RAC-1 regulate opposite chemotropisms in Neurospora crassa.

ABSTRACT Cell polarization and fusion are crucial developmental processes that occur in response to intracellular and extracellular signals. Asexual spores (conidia) of the mold Neurospora crassa differentiate two types of polarized cell protrusions, germ tubes and conidial anastomosis tubes (CATs), which exhibit negative and positive chemotropism, respectively. We provide the first evidence that shared and separate functions of the Rho-type GTPases CDC-42 and RAC-1 regulate these opposite chemotropisms. We demonstrate that RAC-1 is essential for CAT formation and cell fusion, whereas CDC-42 is necessary and sufficient for normal germ tube development. Cdc42-Rac-interactive-binding (CRIB) reporters were constructed to exclusively label locally activated GTP-bound GTPases. Time course analyses showed that repositioning of these activated GTPase clusters within germ tube and CAT tip apices controls directional growth in the absence of a tip-localized vesicle supply center (Spitzenkörper). We propose a model in which the local assembly of a plasma-membrane-associated GTPase–PAK–MAPK signaling platform regulates chemoattractant perception and secretion in order to synchronize oscillatory cell–cell communication and directional CAT tip growth.

A bioimage informatics approach to automatically extract complex fungal networks

MOTIVATION Fungi form extensive interconnected mycelial networks that scavenge efficiently for scarce resources in a heterogeneous environment. The architecture of the network is highly responsive to local nutritional cues, damage or predation, and continuously adapts through growth, branching, fusion or regression. These networks also provide an example of an experimental planar network system that can be subjected to both theoretical analysis and experimental manipulation in multiple replicates. For high-throughput measurements, with hundreds of thousands of branches on each image, manual detection is not a realistic option, especially if extended time series are captured. Furthermore, branches typically show considerable variation in contrast as the individual cords span several orders of magnitude and the compressed soil substrate is not homogeneous in texture making automated segmentation challenging. RESULTS We have developed and evaluated a high-throughput automated image analysis and processing approach using Phase Congruency Tensors and watershed segmentation to characterize complex fungal networks. The performance of the proposed approach is evaluated using complex images of saprotrophic fungal networks with 10(5)-10(6) edges. The results obtained demonstrate that this approach provides a fast and robust solution for detection and graph-based representation of complex curvilinear networks. AVAILABILITY AND IMPLEMENTATION The Matlab toolbox is freely available through the Oxford e-Research Centre website: http://www.oerc.ox.ac.uk/research/bioimage/software CONTACTS boguslaw.obara@oerc.ox.ac.uk.