1,390 research outputs found

    Image informatics strategies for deciphering neuronal network connectivity

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    Brain function relies on an intricate network of highly dynamic neuronal connections that rewires dramatically under the impulse of various external cues and pathological conditions. Among the neuronal structures that show morphologi- cal plasticity are neurites, synapses, dendritic spines and even nuclei. This structural remodelling is directly connected with functional changes such as intercellular com- munication and the associated calcium-bursting behaviour. In vitro cultured neu- ronal networks are valuable models for studying these morpho-functional changes. Owing to the automation and standardisation of both image acquisition and image analysis, it has become possible to extract statistically relevant readout from such networks. Here, we focus on the current state-of-the-art in image informatics that enables quantitative microscopic interrogation of neuronal networks. We describe the major correlates of neuronal connectivity and present workflows for analysing them. Finally, we provide an outlook on the challenges that remain to be addressed, and discuss how imaging algorithms can be extended beyond in vitro imaging studies

    Enriched transcriptome analysis of laser capture microdissected populations of single cells to investigate intracellular heterogeneity in immunostained FFPE sections

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    To investigate intracellular heterogeneity, cell capture of particular cell populations followed by transcriptome analysis has been highly effective in freshly isolated tissues. However, this approach has been quite challenging in immunostained formalin-fixed paraffin-embedded (FFPE) sections. This study aimed at combining the standard pathology techniques, immunostaining and laser capture microdissection, with whole RNA-sequencing and bioinformatics analysis to characterize FFPE breast cancer cell populations with heterogeneous expression of progesterone receptor (PR). Immunocytochemical analysis revealed that 60% of MCF-7 cells admixture highly express PR. Immunocytochemistry-based targeted RNA-seq (ICC-RNAseq) and in silico functional analysis revealed that the PR-high cell population is associated with upregulation in transcripts implicated in immunomodulatory and inflammatory pathways (e.g. NF-ÎşB and interferon signaling). In contrast, the PR-low cell population is associated with upregulation of genes involved in metabolism and mitochondrial processes as well as EGFR and MAPK signaling. These findings were cross-validated and confirmed in FACS-sorted PR high and PR-low MCF-7 cells and in MDA-MB-231 cells ectopically overexpressing PR. Significantly, ICC-RNAseq could be extended to analyze samples captured at specific spatio-temporal states to investigate gene expression profiles using diverse biomarkers. This would also facilitate our understanding of cell population-specific molecular events driving cancer and potentially other diseases

    Differences of size and shape of active and inactive X-chromosome domains in human amniotic fluid cell nuclei

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    It is a widely held belief that the inactive X-chromosome (Xi) in female cell nuclei is strongly condensed as compared to the largely decondensed active X-chromosome (Xa). We have reconsidered this problem and painted X-chromosome domains in nuclei of subconfluent, female and male human amniotic fluid cell cultures (46, XX and 46, XY) by chromosomal in situ suppression (CISS) hybridization with biotinylated human X-chromosome specific library DNA. FITC-conjugated avidin was used for probe detection and nuclei were counterstained with propidium iodide (PI). The shape of these nuclei resembling flat ellipsoids or elliptical cylinders makes them suitable for both two-dimensional (2D) and three-dimensional (3D) analyses. 2D analyses of Xi- and Xa-domains were performed in 34 female cell nuclei by outlining of the painted domains using a camera lucida. Identification of the sex chromatin body in DAPI-stained nuclei prior to CISS-hybridization was confirmed by its colocalization with one of the two painted X-domains. In 31 of the 34 nuclei the area AXi for the inactive X-domain was smaller than the area AXa for the active domain (mean ratio AXa/AXi = 1.9 ± 0.8 SD, range 1.0-4.3). The signed rank test showed a highly significant (P r(Xi) demonstrating a generally more elongated structure of Xa. For 3D analysis a confocal scanning laser fluorescence microscope (CSLFM) was used. Ten to 20 light optical sections (PI-image, FITC-image) were registered with equal spacings (approx. 0.4 m). A thresholding procedure was applied to determine the PI-labeled nuclear and FITC-labeled X-domain areas in each section. Estimated slice volumes were used to compute total nuclear and X-domain volumes. In a series of 35 female nuclei most domains extended from the top to the bottom nuclear sections. The larger of the two X-chromosome domains comprised (3.7 ± 1.7 S.D.)% of the nuclear volume. A mean ratio of 1.2 ± 0.2 SD (range 1.1-2.3) was found for the volumes of the larger and the smaller X-domains in these female nuclei. In a series of 27 male amniotic fluid cell nuclei the relative X-chromosome domain volume comprised (4.0 ± 2.6 S.D.)%. These findings indicate that differences in the 3D expansion of active and inactive X-chromosome domains are less pronounced than previously thought. A current model suggests that chromosome domains consist of a compact core surrounded by loosely coiled outer chromatin fiber loops. The latter fraction may be considerably larger in Xa- as compared to Xi-domains. We suggest that the interactive outlining procedure used in the 2D analyses included the loosely structured domain periphery more accurately, while the threshold algorithm applied to light optical sections delineated the more compact core of the domains, leading to smaller and more similar volume estimates of Xa and Xi. Present limitations of nuclear and chromosome domain volume measurements using confocal laser scanning microscopy are discussed

    Comparison of two automatic cell-counting solutions for fluorescent microscopic images

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    Cell counting in microscopic images is one of the fundamental analysis tools in life sciences, but is usually tedious, time consuming and prone to human error. Several programs for automatic cell countinghavebeendeveloped sofar,butmostof them demand additional training or data input from the user. Most of them do not allow the users to online monitor the counting results, either. Therefore, we designed two straightforward, simple-to-use cell-counting programs that also allow users to correct the detection results. In this paper, we present the CELLCOUNTER and LEARN123 programs for automatic and semiautomatic counting of objects in fluorescent microscopic images (cells or cell nuclei) with a user-friendly interface. Although CELLCOUNTER is based on predefined and fine-tuned set of filters optimized on sets of chosen experiments, LEARN123 uses an evolutionary algorithm to determine the adapt filter parameters based on a learning set of images. CELLCOUNTER also includes an extension for analysis of overlaying images. The efficiency of both programs was assessed on images of cells stained with different fluorescent dyes by comparing automatically obtained results with results that were manually annotated by an expert. With both programs, the correlation between automatic and manual counting was very high (R2 < 0.9), although CELLCOUNTER had some difficulties processing images with no cells or weakly stained cells, where sometimes the background noise was recognized as an object of interest. Nevertheless, the differences between manual and automatic counting were small compared to variations between experimental repeats. Both programs significantly reduced the time required to process the acquired images from hours tominutes. The programs enable consistent, robust, fast and accurate detection of fluorescent objects and can therefore be applied to a range of different applications in different fields of life sciences where fluorescent labelling is used for quantification of various phenomena. Moreover, CELLCOUNTER overlay extension also enables fast analysis of related images thatwouldotherwise require imagemergingforaccurateanalysis, whereas LEARN123’s evolutionary algorithm can adapt counting parameters to specific sets of images of different experimental settings

    Protein expression differs between neural progenitor cells from the adult rat brain subventricular zone and olfactory bulb

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    <p>Abstract</p> <p>Background</p> <p>Neural progenitor cells can be isolated from various regions of the adult mammalian brain, including the forebrain structures of the subventricular zone and the olfactory bulb. Currently it is unknown whether functional differences in these progenitor cell populations can already be found on the molecular level. Therefore, we compared protein expression profiles between progenitor cells isolated from the subventricular zone and the olfactory bulb using a proteomic approach based on two-dimensional gel electrophoresis and mass spectrometry. The subventricular zone and the olfactory bulb are connected by the Rostral Migratory Stream (RMS), in which glial fibrillary acidic protein (GFAP)-positive cells guide neuroblasts. Recent literature suggested that these GFAP-positive cells possess neurogenic potential themselves. In the current study, we therefore compared the cultured neurospheres for the fraction of GFAP-positive cells and their morphology of over a prolonged period of time.</p> <p>Results</p> <p>We found significant differences in the protein expression patterns between subventricular zone and olfactory bulb neural progenitor cells. Of the differentially expressed protein spots, 105 were exclusively expressed in the subventricular zone, 23 showed a lower expression and 51 a higher expression in the olfactory bulb. The proteomic data showed that more proteins are differentially expressed in olfactory bulb progenitors with regard to proteins involved in differentiation and microenvironmental integration, as compared to the subventricular zone progenitors. Compared to 94% of all progenitors of the subventricular zone expressed GFAP, nearly none in the olfactory bulb cultures expressed GFAP. Both GFAP-positive subpopulations differed also in morphology, with the olfactory bulb cells showing more branching. No differences in growth characteristics such as doubling time, and passage lengths could be found over 26 consecutive passages in the two cultures.</p> <p>Conclusion</p> <p>In this study, we describe differences in protein expression of neural progenitor populations isolated from two forebrain regions, the subventricular zone and the olfactory bulb. These subpopulations can be characterized by differential expression of marker proteins. We isolated fractions of progenitor cells with GFAP expression from both regions, but the GFAP-positive cells differed in number and morphology. Whereas in vitro growth characteristics of neural progenitors are preserved in both regions, our proteomic and immunohistochemical data suggest that progenitor cells from the two regions differ in morphology and functionality, but not in their proliferative capacity.</p

    â„®-conome: an automated tissue counting platform of cone photoreceptors for rodent models of retinitis pigmentosa

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    <p>Abstract</p> <p>Background</p> <p>Retinitis pigmentosa is characterized by the sequential loss of rod and cone photoreceptors. The preservation of cones would prevent blindness due to their essential role in human vision. Rod-derived Cone Viability Factor is a thioredoxin-like protein that is secreted by rods and is involved in cone survival. To validate the activity of Rod-derived Cone Viability Factors (RdCVFs) as therapeutic agents for treating retinitis Pigmentosa, we have developed e-conome, an automated cell counting platform for retinal flat mounts of rodent models of cone degeneration. This automated quantification method allows for faster data analysis thereby accelerating translational research.</p> <p>Methods</p> <p>An inverted fluorescent microscope, motorized and coupled to a CCD camera records images of cones labeled with fluorescent peanut agglutinin lectin on flat-mounted retinas. In an average of 300 fields per retina, nine Z-planes at magnification X40 are acquired after two-stage autofocus individually for each field. The projection of the stack of 9 images is subject to a threshold, filtered to exclude aberrant images based on preset variables. The cones are identified by treating the resulting image using 13 variables empirically determined. The cone density is calculated over the 300 fields.</p> <p>Results</p> <p>The method was validated by comparison to the conventional stereological counting. The decrease in cone density in <it>rd1 </it>mouse was found to be equivalent to the decrease determined by stereological counting. We also studied the spatiotemporal pattern of the degeneration of cones in the <it>rd1 </it>mouse and show that while the reduction in cone density starts in the central part of the retina, cone degeneration progresses at the same speed over the whole retinal surface. We finally show that for mice with an inactivation of the Nucleoredoxin-like genes <it>Nxnl1 </it>or <it>Nxnl2 </it>encoding RdCVFs, the loss of cones is more pronounced in the ventral retina.</p> <p>Conclusion</p> <p>The automated platform â„®-conome used here for retinal disease is a tool that can broadly accelerate translational research for neurodegenerative diseases.</p
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