268 research outputs found

    Genomic analysis of a sexually-selected character: EST sequencing and microarray analysis of eye-antennal imaginal discs in the stalk-eyed fly Teleopsis dalmanni (Diopsidae)

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    <p>Abstract</p> <p>Background</p> <p>Many species of stalk-eyed flies (Diopsidae) possess highly-exaggerated, sexually dimorphic eye-stalks that play an important role in the mating system of these flies. Eye-stalks are increasingly being used as a model system for studying sexual selection, but little is known about the genetic mechanisms producing variation in these ornamental traits. Therefore, we constructed an EST database of genes expressed in the developing eye-antennal imaginal disc of the highly dimorphic species <it>Teleopsis dalmanni</it>. We used this set of genes to construct microarray slides and compare patterns of gene expression between lines of flies with divergent eyespan.</p> <p>Results</p> <p>We generated 33,229 high-quality ESTs from three non-normalized libraries made from the developing eye-stalk tissue at different developmental stages. EST assembly and annotation produced a total of 7,066 clusters comprising 3,424 unique genes with significant sequence similarity to a protein in either <it>Drosophila melanogaster </it>or <it>Anopheles gambiae</it>. Comparisons of the transcript profiles at different stages reveal a developmental shift in relative expression from genes involved in anatomical structure formation, transcription, and cell proliferation at the larval stage to genes involved in neurological processes and cuticle production during the pupal stages. Based on alignments of the EST fragments to homologous sequences in <it>Drosophila </it>and <it>Anopheles</it>, we identified 20 putative gene duplication events in <it>T. dalmanni </it>and numerous genes undergoing significantly faster rates of evolution in <it>T. dalmanni </it>relative to the other Dipteran species. Microarray experiments identified over 350 genes with significant differential expression between flies from lines selected for high and low relative eyespan but did not reveal any primary biological process or pathway that is driving the expression differences.</p> <p>Conclusion</p> <p>The catalogue of genes identified in the EST database provides a valuable framework for a comprehensive examination of the genetic basis of eye-stalk variation. Several candidate genes, such as <it>crooked legs</it>, <it>cdc2</it>, <it>CG31917 </it>and <it>CG11577</it>, emerge from the analysis of gene duplication, protein evolution and microarray gene expression. Additional comparisons of expression profiles between, for example, males and females, and species that differ in eye-stalk sexual dimorphism, are now enabled by these resources.</p

    Windowed Eigen-Decomposition Algorithm for Motion Artifact Reduction in Optical Coherence Tomography-Based Angiography

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    Optical coherence tomography-based angiography (OCTA) has attracted attention in clinical applications as a non-invasive and high-resolution imaging modality. Motion artifacts are the most seen artifact in OCTA. Eigen-decomposition (ED) algorithms are popular choices for OCTA reconstruction, but have limitations in the reduction of motion artifacts. The OCTA data do not meet one of the requirements of ED, which is that the data should be normally distributed. To overcome this drawback, we propose an easy-to-deploy development of ED, windowed-ED (wED). wED applies a moving window to the input data, which can contrast the blood-flow signals with significantly reduced motion artifacts. To evaluate our wED algorithm, pre-acquired dorsal wound healing data in a murine model were used. The ideal window size was optimized by fitting the data distribution with the normal distribution. Lastly, the cross-sectional and en face results were compared among several OCTA reconstruction algorithms, Speckle Variance, A-scan ED (aED), B-scan ED, and wED. wED could reduce the background noise intensity by 18% and improve PSNR by 4.6%, compared to the second best-performed algorithm, aED. This study can serve as a guide for utilizing wED to reconstruct OCTA images with an optimized window size

    Distinct Interactions of 2′- and 3′-O-(N-Methyl)anthraniloyl-Isomers of ATP and GTP with the Adenylyl Cyclase Toxin of Bacillus anthracis, Edema Factor

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    Anthrax disease is caused by the spore-forming bacterium, Bacillus anthracis. Bacillus anthracis produces a calmodulin-activated adenylyl cyclase (AC) toxin, edema factor (EF). Through excessive cAMP accumulation EF disrupts host defence. In a recent study we showed that various 2′(3′)-O-N-(methyl)anthraniloyl (MANT)-substituted nucleoside 5′-triphosphates are potent inhibitors (Ki values in the 0.1-5 μM range) of purified EF. Upon interaction with calmodulin we observed efficient fluorescence resonance energy transfer (FRET) between tryptophan and tyrosine residues of EF and the MANT-group of MANT-ATP. Molecular modelling suggested that both the 2′- and 3′-MANT-isomers can bind to EF. The aim of the present study was to examine the effects of defined 2′- and 3′-MANT-isomers of ATP and GTP on EF. 3′-MANT-2′-deoxy-ATP inhibited EF more potently than 2′-MANT-3′-deoxy-ATP, whereas the opposite was the case for the corresponding GTP analogs. Calmodulin-dependent direct MANT-fluorescence and FRET was much larger with 2′-MANT-3′-deoxy-ATP and 2′-MANT-3′-deoxy-GTP compared to the corresponding 3′-MANT-2′-deoxy-isomers and the 2′(3′)-racemates. Ki values of MANT-nucleotides for inhibition of catalysis correlated with Kd values of MANT-nucleotides in FRET studies. Molecular modelling indicated different positioning of the MANT-group in 2′-MANT-3′-deoxy-ATP/GTP and 3′-MANT-2′-deoxy-ATP/GTP bound to EF. Collectively, EF interacts differentially with 2′-MANT- and 3′-MANT-isomers of ATP and GTP, indicative for conformational flexibility of the catalytic site and offering a novel approach for the development of potent and selective EF inhibitors. Moreover, our present study may serve as a general model of how to use MANT-nucleotide isomers for the analysis of the molecular mechanisms of nucleotide/protein interactions

    Lipidomic Analysis of Glioblastoma Multiforme Using Mass Spectrometry

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    Glioblastoma multiforme (GBM) is the most common and malignant form of primary brain tumors. It is highly invasive and current treatment options have not improved the survival rate over the past twenty years. Novel approaches and technologies from systems biology have the potential to identify biomarkers that could serve as new therapeutic targets for GBM. This study employed lipid profiling technology to investigate lipid biomarkers in ectopic and orthotopic human GBM xenograft models. Primary patient cell lines, GBM10 and GBM43, were injected into the flank and the right cerebral hemisphere of NOD/SCID mice. Tumors were harvested from the brain and flank and proteins, metabolites, and lipids extracted from each sample. Reverse phase based high performance liquid chromatography coupled with Fourier transform ion cyclotron resonance mass spectrometry (LC-FTMS) was used to analyze the lipid profiles of tumor samples. Statistical and clustering analyses were performed to detect differences. Over 500 lipids were identified in each tumor model and lipids with the greatest fold effect in the comparison of ectopic versus orthotopic tumor models fell predominantly into four main classes of lipids: glycosphingolipids, glycerophoshpoethanolamines, triradylglycerols, and glycerophosphoserines. Lipidomic analysis revealed differences in glycosphingolipid and triglyceride profiles when the same tumor was propagated in the flank versus the brain. These results underscore the importance of the surrounding physiological environment on tumor development and are consistent with the hypothesis that specific classes of lipids are critical for GBM tumor growth in different anatomical sites

    Lipidomic Analysis of Glioblastoma Multiforme Using Mass Spectrometry

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    Glioblastoma multiforme (GBM) is the most common and malignant form of primary brain tumors. It is highly invasive and current treatment options have not improved the survival rate over the past twenty years. Novel approaches and technologies from systems biology have the potential to identify biomarkers that could serve as new therapeutic targets for GBM. This study employed lipid profiling technology to investigate lipid biomarkers in ectopic and orthotopic human GBM xenograft models. Primary patient cell lines, GBM10 and GBM43, were injected into the flank and the right cerebral hemisphere of NOD/SCID mice. Tumors were harvested from the brain and flank and proteins, metabolites, and lipids extracted from each sample. Reverse phase based high performance liquid chromatography coupled with Fourier transform ion cyclotron resonance mass spectrometry (LC-FTMS) was used to analyze the lipid profiles of tumor samples. Statistical and clustering analyses were performed to detect differences. Over 500 lipids were identified in each tumor model and lipids with the greatest fold effect in the comparison of ectopic versus orthotopic tumor models fell predominantly into four main classes of lipids: glycosphingolipids, glycerophoshpoethanolamines, triradylglycerols, and glycerophosphoserines. Lipidomic analysis revealed differences in glycosphingolipid and triglyceride profiles when the same tumor was propagated in the flank versus the brain. These results underscore the importance of the surrounding physiological environment on tumor development and are consistent with the hypothesis that specific classes of lipids are critical for GBM tumor growth in different anatomical sites

    Human cytomegalovirus interactome analysis identifies degradation hubs, domain associations and viral protein functions

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    Human cytomegalovirus (HCMV) extensively modulates host cells, downregulating >900 human proteins during viral replication and degrading ≥133 proteins shortly after infection. The mechanism of degradation of most host proteins remains unresolved, and the functions of many viral proteins are incompletely characterised. We performed a mass spectrometry-based interactome analysis of 169 tagged, stably-expressed canonical strain Merlin HCMV proteins, and two non-canonical HCMV proteins, in infected cells. This identified a network of >3,400 virus-host and >150 virus-virus protein interactions, providing insights into functions for multiple viral genes. Domain analysis predicted binding of the viral UL25 protein to SH3 domains of NCK Adaptor Protein-1. Viral interacting proteins were identified for 31/133 degraded host targets. Finally, the uncharacterised, non-canonical ORFL147C protein was found to interact with elements of the mRNA splicing machinery, and a mutational study suggested its importance in viral replication. The interactome data will be important for future studies of herpesvirus infection

    Deep Learning Approach for Automated Thickness Measurement of Epithelial Tissue and Scab using Optical Coherence Tomography

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    Significance: In order to elucidate therapeutic treatment to accelerate wound healing, it is crucial to understand the process underlying skin wound healing, especially re-epithelialization. Epidermis and scab detection is of importance in the wound healing process as their thickness is a vital indicator to judge whether the re-epithelialization process is normal or not. Since optical coherence tomography (OCT) is a real-time and non-invasive imaging technique that can perform a cross-sectional evaluation of tissue microstructure, it is an ideal imaging modality to monitor the thickness change of epidermal and scab tissues during wound healing processes in micron-level resolution. Traditional segmentation on epidermal and scab regions was performed manually, which is time-consuming and impractical in real-time.Aim: Develop a deep-learning-based skin layer segmentation method for automated quantitative assessment of the thickness of in-vivo epidermis and scab tissues during a time course of healing within a murine model.Approach: Five convolution neural networks (CNN) were trained using manually labelled epidermis and scab regions segmentation from 1000 OCT B-scan images (assisted by its corresponding angiographic information). The segmentation performance of five segmentation architectures were compared qualitatively and quantitatively for validation set.Results: Our results show higher accuracy and higher speed of the calculated thickness compared with human experts. The U-Net architecture represents a better performance than other deep neural network architectures with a 0.894 at F1-score, 0.875 at mean IOU, 0.933 at dice similarity coefficient, and 18.28 μm at an average symmetric surface distance. Furthermore, our algorithm is able to provide abundant quantitative parameters of the wound based on its corresponding thickness mapping in different healing phases. Among them, normalized epidermis thickness is recommended as an essential hallmark to describe the re-epithelialization process of the mouse model.Conclusions: The automatic segmentation and thickness measurements within different phases of wound healing data demonstrates that our pipeline provides a robust, quantitative, and accurate method for serving as a standard model for further research into effect of external pharmacological and physical factors
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