Association of p60c-src with endosomal membranes in mammalian fibroblasts.

We have examined the subcellular localization of p60c-src in mammalian fibroblasts. Analysis of indirect immunofluorescence by three-dimensional optical sectioning microscopy revealed a granular cytoplasmic staining that co-localized with the microtubule organizing center. Immunofluorescence experiments with antibodies against a number of membrane markers demonstrated a striking co-localization between p60c-src and the cation-dependent mannose-6-phosphate receptor (CI-MPR), a marker that identifies endosomes. Both p60c-src and the CI-MPR were found to cluster at the spindle poles throughout mitosis. In addition, treatment of interphase and mitotic cells with brefeldin A resulted in a clustering of p60c-src and CI-MPR at a peri-centriolar position. Biochemical fractionation of cellular membranes showed that a major proportion of p60c-src co-enriched with endocytic membranes. Treatment of membranes containing HRP to alter their apparent density also altered the density of p60c-src-containing membranes. Similar density shift experiments with total cellular membranes revealed that the majority of membrane-associated p60c-src in the cell is associated with endosomes, while very little is associated with plasma membranes. These results support a role for p60c-src in the regulation of endosomal membranes and protein trafficking

Characterization of nuclear polyadenylated RNA-binding proteins in Saccharomyces cerevisiae.

To study the functions of heterogeneous nuclear ribonucleoproteins (hnRNPs), we have characterized nuclear polyadenylated RNA-binding (Nab) proteins from Saccharomyces cerevisiae. Nab1p, Nab2p, and Nab3p were isolated by a method which uses UV light to cross-link proteins directly bound to poly(A)+ RNA in vivo. We have previously characterized Nab2p, and demonstrated that it is structurally related to human hnRNPs. Here we report that Nab1p is identical to the Np13p/Nop3p protein recently implicated in both nucleocytoplasmic protein shuttling and pre-rRNA processing, and characterize a new nuclear polyadenylated RNA-binding protein, Nab3p. The intranuclear distributions of the Nab proteins were analyzed by three-dimensional immunofluorescence optical microscopy. All three Nab proteins are predominantly localized within the nucleoplasm in a pattern similar to the distribution of hnRNPs in human cells. The NAB3 gene is essential for cell viability and encodes an acidic ribonucleoprotein. Loss of Nab3p by growth of a GAL::nab3 mutant strain in glucose results in a decrease in the amount of mature ACT1, CYH2, and TPI1 mRNAs, a concomitant accumulation of unspliced ACT1 pre-mRNA, and an increase in the ratio of unspliced CYH2 pre-mRNA to mRNA. These results suggest that the Nab proteins may be required for packaging pre-mRNAs into ribonucleoprotein structures amenable to efficient nuclear RNA processing

Publishing and sharing multi-dimensional image data with OMERO

Imaging data are used in the life and biomedical sciences to measure the molecular and structural composition and dynamics of cells, tissues, and organisms. Datasets range in size from megabytes to terabytes and usually contain a combination of binary pixel data and metadata that describe the acquisition process and any derived results. The OMERO image data management platform allows users to securely share image datasets according to specific permissions levels: data can be held privately, shared with a set of colleagues, or made available via a public URL. Users control access by assigning data to specific Groups with defined membership and access rights. OMERO’s Permission system supports simple data sharing in a lab, collaborative data analysis, and even teaching environments. OMERO software is open source and released by the OME Consortium at www.openmicroscopy.org

Wndchrm – an open source utility for biological image analysis

<p>Abstract</p> <p>Background</p> <p>Biological imaging is an emerging field, covering a wide range of applications in biological and clinical research. However, while machinery for automated experimenting and data acquisition has been developing rapidly in the past years, automated image analysis often introduces a bottleneck in high content screening.</p> <p>Methods</p> <p><it>Wndchrm </it>is an open source utility for biological image analysis. The software works by first extracting image content descriptors from the raw image, image transforms, and compound image transforms. Then, the most informative features are selected, and the feature vector of each image is used for classification and similarity measurement.</p> <p>Results</p> <p><it>Wndchrm </it>has been tested using several publicly available biological datasets, and provided results which are favorably comparable to the performance of task-specific algorithms developed for these datasets. The simple user interface allows researchers who are not knowledgeable in computer vision methods and have no background in computer programming to apply image analysis to their data.</p> <p>Conclusion</p> <p>We suggest that <it>wndchrm </it>can be effectively used for a wide range of biological image analysis tasks. Using <it>wndchrm </it>can allow scientists to perform automated biological image analysis while avoiding the costly challenge of implementing computer vision and pattern recognition algorithms.</p

Rule-based knowledge aggregation for large-scale protein sequence analysis of influenza A viruses

Background: The explosive growth of biological data provides opportunities for new statistical and comparative analyses of large information sets, such as alignments comprising tens of thousands of sequences. In such studies, sequence annotations frequently play an essential role, and reliable results depend on metadata quality. However, the semantic heterogeneity and annotation inconsistencies in biological databases greatly increase the complexity of aggregating and cleaning metadata. Manual curation of datasets, traditionally favoured by life scientists, is impractical for studies involving thousands of records. In this study, we investigate quality issues that affect major public databases, and quantify the effectiveness of an automated metadata extraction approach that combines structural and semantic rules. We applied this approach to more than 90,000 influenza A records, to annotate sequences with protein name, virus subtype, isolate, host, geographic origin, and year of isolation. Results: Over 40,000 annotated Influenza A protein sequences were collected by combining information from more than 90,000 documents from NCBI public databases. Metadata values were automatically extracted, aggregated and reconciled from several document fields by applying user-defined structural rules. For each property, values were recovered from ≥88.8% of records, with accuracy exceeding 96% in most cases. Because of semantic heterogeneity, each property required up to six different structural rules to be combined. Significant quality differences between databases were found: GenBank documents yield values more reliably than documents extracted from GenPept. Using a simple set of semantic rules and a reasoner, we reconstructed relationships between sequences from the same isolate, thus identifying 7640 isolates. Validation of isolate metadata against a simple ontology highlighted more than 400 inconsistencies, leading to over 3,000 property value corrections. Conclusion: To overcome the quality issues inherent in public databases, automated knowledge aggregation with embedded intelligence is needed for large-scale analyses. Our results show that user-controlled intuitive approaches, based on combination of simple rules, can reliably automate various curation tasks, reducing the need for manual corrections to approximately 5% of the records. Emerging semantic technologies possess desirable features to support today's knowledge aggregation tasks, with a potential to bring immediate benefits to this field

Pattern Recognition Software and Techniques for Biological Image Analysis

The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image analysis systems are tailored for specific types of microscopy, contrast methods, probes, and even cell types. This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. One of the approaches to address these limitations is pattern recognition, which was originally developed for remote sensing, and is increasingly being applied to the biology domain. This approach relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for specific image processing tasks. The generality of this approach promises to enable data mining in extensive image repositories, and provide objective and quantitative imaging assays for routine use. Here, we provide a brief overview of the technologies behind pattern recognition and its use in computer vision for biological and biomedical imaging. We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays

A novel application of motion analysis for detecting stress responses in embryos at different stages of development.

Motion analysis is one of the tools available to biologists to extract biologically relevant information from image datasets and has been applied to a diverse range of organisms. The application of motion analysis during early development presents a challenge, as embryos often exhibit complex, subtle and diverse movement patterns. A method of motion analysis able to holistically quantify complex embryonic movements could be a powerful tool for fields such as toxicology and developmental biology to investigate whole organism stress responses. Here we assessed whether motion analysis could be used to distinguish the effects of stressors on three early developmental stages of each of three species: (i) the zebrafish Danio rerio (stages 19 h, 21.5 h and 33 h exposed to 1.5% ethanol and a salinity of 5); (ii) the African clawed toad Xenopus laevis (stages 24, 32 and 34 exposed to a salinity of 20); and iii) the pond snail Radix balthica (stages E3, E4, E6, E9 and E11 exposed to salinities of 5, 10 and 15). Image sequences were analysed using Sparse Optic Flow and the resultant frame-to-frame motion parameters were analysed using Discrete Fourier Transform to quantify the distribution of energy at different frequencies. This spectral frequency dataset was then used to construct a Bray-Curtis similarity matrix and differences in movement patterns between embryos in this matrix were tested for using ANOSIM

Mechanical stretch and shear flow induced reorganization and recruitment of fibronectin in fibroblasts

It was our objective to study the role of mechanical stimulation on fibronectin (FN) reorganization and recruitment by exposing fibroblasts to shear fluid flow and equibiaxial stretch. Mechanical stimulation was also combined with a Rho inhibitor to probe their coupled effects on FN. Mechanically stimulated cells revealed a localization of FN around the cell periphery as well as an increase in FN fibril formation. Mechanical stimulation coupled with chemical stimulation also revealed an increase in FN fibrils around the cell periphery. Complimentary to this, fibroblasts exposed to fluid shear stress structurally rearranged pre-coated surface FN, but unstimulated and stretched cells did not. These results show that mechanical stimulation directly affected FN reorganization and recruitment, despite perturbation by chemical stimulation. Our findings will help elucidate the mechanisms of FN biosynthesis and organization by furthering the link of the role of mechanics with FN

Spatiotemporally Controlled Cardiac Conduction Block Using High-Frequency Electrical Stimulation

Background: Methods for the electrical inhibition of cardiac excitation have long been sought to control excitability and conduction, but to date remain largely impractical. High-amplitude alternating current (AC) stimulation has been known to extend cardiac action potentials (APs), and has been recently exploited to terminate reentrant arrhythmias by producing reversible conduction blocks. Yet, low-amplitude currents at similar frequencies have been shown to entrain cardiac tissues by generation of repetitive APs, leading in some cases to ventricular fibrillation and hemodynamic collapse in vivo. Therefore, an inhibition method that does not lead to entrainment – irrespective of the stimulation amplitude (bound to fluctuate in an in vivo setting) – is highly desirable. Methodology/Principal Findings: We investigated the effects of broader amplitude and frequency ranges on the inhibitory effects of extracellular AC stimulation on HL-1 cardiomyocytes cultured on microelectrode arrays, using both sinusoidal and square waveforms. Our results indicate that, at sufficiently high frequencies, cardiac tissue exhibits a binary response to stimulus amplitude with either prolonged APs or no effect, thereby effectively avoiding the risks of entrainment by repetitive firing observed at lower frequencies. We further demonstrate the ability to precisely define reversible local conduction blocks in beating cultures without influencing the propagation activity in non-blocked areas. The conduction blocks were spatiotemporally controlled by electrode geometry and stimuli duration, respectively, and sustainable for long durations (300 s). Conclusion/Significance: Inhibition of cardiac excitation induced by high-frequency AC stimulation exhibits a binary response to amplitude above a threshold frequency, enabling the generation of reversible conduction blocks without the risks of entrainment. This inhibition method could yield novel approaches for arrhythmia modeling in vitro, as well as safer and more efficacious tools for in vivo cardiac mapping and radio-frequency ablation guidance applications