27 research outputs found

    Справа Івана Дзюби

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    У статті автор, використовуючи документи Галузевого державного архіву СБ України, досліджує постать видатного літературознавця, громадського діяча Івана Дзюби у контексті боротьби співробітників органів держбезпеки УРСР з «українським буржуазним націоналізмом».В статье автор, используя документы Отраслевого государственного архива СБ Украины, исследует личность выдающегося литературоведа, общественного деятеля Ивана Дзюбы в контексте борьбы сотрудников органов госбезопасности УССР с «украинским буржуазным национализмом».Using the documents of State branch archive of State Security of Ukraine, the author investigates the personality of Ivan Dzyuba during the struggle of KGB of the UkSSR against the «Ukrainian bourgeois nationalism»

    Insights into the Molecular Evolution of the PDZ/LIM Family and Identification of a Novel Conserved Protein Motif

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    The PDZ and LIM domain-containing protein family is encoded by a diverse group of genes whose phylogeny has currently not been analyzed. In mammals, ten genes are found that encode both a PDZ- and one or several LIM-domains. These genes are: ALP, RIL, Elfin (CLP36), Mystique, Enigma (LMP-1), Enigma homologue (ENH), ZASP (Cypher, Oracle), LMO7 and the two LIM domain kinases (LIMK1 and LIMK2). As conventional alignment and phylogenetic procedures of full-length sequences fell short of elucidating the evolutionary history of these genes, we started to analyze the PDZ and LIM domain sequences themselves. Using information from most sequenced eukaryotic lineages, our phylogenetic analysis is based on full-length cDNA-, EST-derived- and genomic- PDZ and LIM domain sequences of over 25 species, ranging from yeast to humans. Plant and protozoan homologs were not found. Our phylogenetic analysis identifies a number of domain duplication and rearrangement events, and shows a single convergent event during evolution of the PDZ/LIM family. Further, we describe the separation of the ALP and Enigma subfamilies in lower vertebrates and identify a novel consensus motif, which we call ‘ALP-like motif’ (AM). This motif is highly-conserved between ALP subfamily proteins of diverse organisms. We used here a combinatorial approach to define the relation of the PDZ and LIM domain encoding genes and to reconstruct their phylogeny. This analysis allowed us to classify the PDZ/LIM family and to suggest a meaningful model for the molecular evolution of the diverse gene architectures found in this multi-domain family

    Fine-grained, nonlinear registration of live cell movies reveals spatiotemporal organization of diffuse molecular processes.

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    We present an application of nonlinear image registration to align in microscopy time lapse sequences for every frame the cell outline and interior with the outline and interior of the same cell in a reference frame. The registration relies on a subcellular fiducial marker, a cell motion mask, and a topological regularization that enforces diffeomorphism on the registration without significant loss of granularity. This allows spatiotemporal analysis of extremely noisy and diffuse molecular processes across the entire cell. We validate the registration method for different fiducial markers by measuring the intensity differences between predicted and original time lapse sequences of Actin cytoskeleton images and by uncovering zones of spatially organized GEF- and GTPase signaling dynamics visualized by FRET-based activity biosensors in MDA-MB-231 cells. We then demonstrate applications of the registration method in conjunction with stochastic time-series analysis. We describe distinct zones of locally coherent dynamics of the cytoplasmic protein Profilin in U2OS cells. Further analysis of the Profilin dynamics revealed strong relationships with Actin cytoskeleton reorganization during cell symmetry-breaking and polarization. This study thus provides a framework for extracting information to explore functional interactions between cell morphodynamics, protein distributions, and signaling in cells undergoing continuous shape changes. Matlab code implementing the proposed registration method is available at https://github.com/DanuserLab/Mask-Regularized-Diffeomorphic-Cell-Registration

    SMIFH2 has effects on Formins and p53 that perturb the cell cytoskeleton

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    <p>Formin proteins are key regulators of the cytoskeleton involved in developmental and homeostatic programs, and human disease. For these reasons, small molecules interfering with Formins’ activity have gained increasing attention. Among them, small molecule inhibitor of Formin Homology 2 domains (SMIFH2) is often used as a pharmacological Formin blocker. Although SMIFH2 inhibits actin polymerization by Formins and affects the actin cytoskeleton, its cellular mechanism of action and target specificity remain unclear.<br>Here we show that SMIFH2 induces remodelling of actin filaments, microtubules and the Golgi complex as a result of its effects on Formins and p53.<br>We found that SMIFH2 triggers alternated depolymerization-repolymerization cycles of actin and tubulin, increases cell migration, causes scattering of the Golgi complex, and also cytotoxicity at high dose. Moreover, SMIFH2 reduces expression and activity of p53 through a post-transcriptional, proteasome-independent mechanism that influences remodelling of the cytoskeleton.<br>As the action of SMIFH2 may go beyond Formin inhibition, only short-term and low-dose SMIFH2 treatments minimize confounding effects induced by loss of p53 and cytotoxicity. </p

    Particle retracking algorithm capable of quantifying large, local matrix deformation for traction force microscopy.

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    Deformation measurement is a key process in traction force microscopy (TFM). Conventionally, particle image velocimetry (PIV) or correlation-based particle tracking velocimetry (cPTV) have been used for such a purpose. Using simulated bead images, we show that those methods fail to capture large displacement vectors and that it is due to a poor cross-correlation. Here, to redeem the potential large vectors, we propose a two-step deformation tracking algorithm that combines cPTV, which performs better for small displacements than PIV methods, and newly-designed retracking algorithm that exploits statistically confident vectors from the initial cPTV to guide the selection of correlation peak which are not necessarily the global maximum. As a result, the new method, named 'cPTV-Retracking', or cPTVR, was able to track more than 92% of large vectors whereas conventional methods could track 43-77% of those. Correspondingly, traction force reconstructed from cPTVR showed better recovery of large traction than the old methods. cPTVR applied on the experimental bead images has shown a better resolving power of the traction with different-sized cell-matrix adhesions than conventional methods. Altogether, cPTVR method enhances the accuracy of TFM in the case of large deformations present in soft substrates. We share this advance via our TFMPackage software

    Particle retracking algorithm capable of quantifying large, local matrix deformation for traction force microscopy

    No full text
    Deformation measurement is a key process in traction force microscopy (TFM). Conventionally, particle image velocimetry (PIV) or correlation-based particle tracking velocimetry (cPTV) have been used for such a purpose. Using simulated bead images, we show that those methods fail to capture large displacement vectors and that it is due to a poor cross-correlation. Here, to redeem the potential large vectors, we propose a two-step deformation tracking algorithm that combines cPTV, which performs better for small displacements than PIV methods, and newly-designed retracking algorithm that exploits statistically confident vectors from the initial cPTV to guide the selection of correlation peak which are not necessarily the global maximum. As a result, the new method, named \u27cPTV-Retracking\u27, or cPTVR, was able to track more than 92% of large vectors whereas conventional methods could track 43-77% of those. Correspondingly, traction force reconstructed from cPTVR showed better recovery of large traction than the old methods. cPTVR applied on the experimental bead images has shown a better resolving power of the traction with different-sized cell-matrix adhesions than conventional methods. Altogether, cPTVR method enhances the accuracy of TFM in the case of large deformations present in soft substrates. We share this advance via our TFMPackage software

    Figure 3

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    <p>Sequence alignments showing the conserved motifs. (A) Conserved amino acids constituting the Alp-like (AM) motif, which was only present in the ALP family genes and neither found neither in the Enigma subfamily nor in their mutual precursor <i>eat-1/tungus.</i> (B) Conserved amino acids constituting the ZASP-like (ZM) motif found in both ALP subfamily and Enigma subfamily genes.</p

    Figure 1

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    <p>Exon structure, domain composition and the six basic forms of PDZ/LIM genes. (A) The exon composition of the human PDZ-LIM domain encoding genes in alphabetical order. Indicated are <i>ALP</i> (ENSG00000154553), <i>ZASP</i> (ENSG00000122367, Elfin (ENSG00000107438), ENIGMA (ENSG00000196923), <i>Enigma-Homolog</i> (ENH) (ENSG00000163110) <i>LIMK1</i> (ENSG00000106683, OTTHUMG00000023448), <i>LIMK2</i> (ENSG00000182541), <i>LMO7</i> (ENSG00000136153), <i>Mystique</i> (ENSG00000120913) and RIL (ENSG00000131435). Domains are color coded on the exons: LIM yellow, PDZ blue, CH red and ZM motif green, while transcription start sites are indicated after non coding regions (colored white) with a small arrow on top. (B) Presence of domain architectures for PDZ and LIM genes and their species distribution. Six basic gene structures can be found amongst the different taxons. The <i>tungus gene</i>, found in the two <i>arthropod species investigated and the nematode homolog Eat-1 both</i> encode one N-terminal PDZ and four C-terminal LIM domains. Eat-1 has been described earlier as the <i>Caenorhabditis elegans</i> ALP/Enigma gene <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0000189#pone.0000189-McKeown1" target="_blank">[50]</a>. Only a single <i>LIMK</i> gene was found per invertebrate species examined, and the <i>LMO7</i> homolog lacks the CH domain (<i>CG31534</i>). The LMO7 gene of <i>Drosophila</i> melanogaster lacks not only the CH domain but also the PDZ domain (not shown, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0000189#pone.0000189.s002" target="_blank">Supplemental table S1</a>). As not all ALP and Enigma subfamily members share the ZM domain (ZASP and ALP contain 2 and Elfin one ZM motif) we have excluded the ZM motif from these groups and show only a ZM motif for eat-1/tungus in this figure.</p
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