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

Quiescence and Activation of Stem and Precursor Cell Populations in the Subependymal Zone of the Mammalian Brain Are Associated with Distinct Cellular and Extracellular Matrix Signals

The subependymal zone (SEZ) of the lateral ventricles is one of the areas of the adult brain where new neurons are continuously generated from neural stem cells (NSCs), via rapidly dividing precursors. This neurogenic niche is a complex cellular and extracellular microenvironment, highly vascularized compared to non-neurogenic periventricular areas, within which NSCs and precursors exhibit distinct behavior. Here, we investigate the possible mechanisms by which extracellular matrix molecules and their receptors might regulate this differential behavior. We show that NSCs and precursors proceed through mitosis in the same domains within the SEZ of adult male mice—albeit with NSCs nearer ependymal cells—and that distance from the ventricle is a stronger limiting factor for neurogenic activity than distance from blood vessels. Furthermore, we show that NSCs and precursors are embedded in a laminin-rich extracellular matrix, to which they can both contribute. Importantly, they express differential levels of extracellular matrix receptors, with NSCs expressing low levels of α6β1 integrin, syndecan-1, and lutheran, and in vivo blocking of β1 integrin selectively induced the proliferation and ectopic migration of precursors. Finally, when NSCs are activated to reconstitute the niche after depletion of precursors, expression of laminin receptors is upregulated. These results indicate that the distinct behavior of adult NSCs and precursors is not necessarily regulated via exposure to differential extracellular signals, but rather via intrinsic regulation of their interaction with their microenvironment

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

Interactions between the Evolutionarily Conserved, Actin-related Protein, Arp11, Actin, and Arp1

The dynein activator dynactin is a multiprotein complex with distinct microtubule- and cargo-binding domains. The cargo-binding domain contains a short, actin-like filament of the actin-related protein Arp1, a second actin-related protein, Arp11, and conventional actin. The length of this filament is invariant in dynactin isolated from multiple species and tissues, suggesting that activities that regulate Arp1 polymerization are important for dynactin assembly. Arp11 is present in a protein complex localized at the pointed end of the Arp1 minifilament, whereas actin capping protein (CapZ) is present at the barbed end. Either might cooperate with conventional actin to cap Arp1. We tested the ability of Arp11 to interact with conventional actin and found it could coassemble. Like Arp1, cytosolic Arp11 is found only in dynactin, suggesting that Arp11 and free cytosolic actin do not interact significantly. Recombinant Arp11 and Arp1 were demonstrated to interact by coprecipitation. We developed an in vivo assay for Arp11–Arp1 interaction based on previous observations that Arp1 forms filamentous assemblies when overexpressed in cultured cells. Arp11 significantly decreases the formation of these organized Arp1 assemblies. Finally, this assay was used to confirm the identity of a putative Arp11 homolog in Drosophila melanogaster

Interactions between the evolutionarily conserved, actin-related protein

The dynein activator, dynactin, is a multiprotein complex with distinct microtubule- and cargo-binding domains. The cargo-binding domain contains a short, actin-like filament of the actin-related protein, Arp1, a second actin-related protein, Arp11, and conventional actin. The length of this filament is invariant in dynactin isolated from multiple species and tissues, suggesting that activities that regulate Arp1 polymerization are important for dynactin assembly. Arp11 is present in a protein complex localized at the pointed end of the Arp1 minifilament, whereas actin capping protein (CapZ) is present at the barbed end. Either might cooperate with conventional actin to cap Arp1. We tested the ability of Arp11 to interact with conventional actin and found it could coassemble. Like Arp1, cytosolic Arp11 is found only in dynactin, suggesting that Arp11 and free cytosolic actin do not interact significantly. Recombinant Arp11 and Arp1 were demonstrated to interact by coprecipitation. We developed an in vivo assay for Arp11-Arp1 interaction based on previous observations that Arp1 forms filamentous assemblies when overexpressed in cultured cells. Arp11 significantly decreases the formation of these organized Arp1 assemblies. Finally, this assay was used to confirm the identity of a putative Arp11 homologue in Drosophila melanogaster. 2 Eckley and Schroe

The incenps: Chromosomal proteins with an essential cytoskeletal role during mitosis

The INCENPs (INnerCENtromereProteins - Mr133 and 145 kDa) are tightly bound to chromatin until early metaphase, and arrive at the metaphase spindle plate as integral components of the chromosomes (Cooke et al., 1987; Earnshaw &amp; Cooke, 1991). It is thus surprising that the INCENPs leave the chromosomes during the latter part of metaphase to become associated with fibrous structures traversing the metaphase plate (presumably the overlapping polar microtubules of the spindle). Following the onset of anaphase, the INCENPs remain closely associated with the stem body material in the central spindle and also become associated with the inner surface of the cell membrane at the position where the cleavage furrow subsequently forms.By combining library screening with reverse-transcriptase PCR, we have recovered cDNA clones that contain the complete open reading frames (ORFs) of the two chicken INCENPs. Class 1 INCENP cDNA contains an ORF of 839 codons, which includes a predicted central coiled-coil domain of about 200 residues.</jats:p