Kosuke Tashiro

Bio: Kosuke Tashiro is an academic researcher from Kyushu University. The author has contributed to research in topics: Xenopus & Gene. The author has an hindex of 33, co-authored 187 publications receiving 7431 citations. Previous affiliations of Kosuke Tashiro include United States Department of Agriculture & University of Tokyo.

Molecular cloning and expression of human hepatocyte growth factor

Abstract: Hepatocyte growth factor (HGF) is the most potent mitogen for mature parenchymal hepatocytes in primary culture, and seems to be a hepatotrophic factor that acts as a trigger for liver regeneration after partial hepatectomy and liver injury. The partial purification and characterization of HGF have been reported. We have demonstrated that pure HGF from rat platelets is a new growth factor effective at concentrations as low as 1 ng ml-1. The effects of HGF and epidermal growth factor (EGF) are additive. The activity of HGF is not species-specific, although it does not stimulate growth in Swiss 3T3 fibroblasts. HGF has a relative molecular mass (Mr) of 82,000 and is a heterodimer composed of a large alpha-subunit of Mr 69,000 and a small beta-subunit of Mr 34,000. Here we report the amino-acid sequence of human HGF determined by complementary DNA cloning and the expression of biologically active human HGF from COS-1 cells transfected with cloned cDNA. The nucleotide sequence of the human HGF cDNA reveals that both alpha- and beta-chains are contained in a single open reading frame coding for a pre-pro precursor protein of 728 amino acids.

Toward a protein–protein interaction map of the budding yeast: A comprehensive system to examine two-hybrid interactions in all possible combinations between the yeast proteins

Abstract: tions, constituting '10% of the total to be tested, has revealed 183 independent two-hybrid interactions, more than half of which are entirely novel. Notably, the obtained binary data allow us to extract more complex interaction networks, including the one that may explain a currently unsolved mechanism for the connection between distinct steps of vesicular transport. The approach de- scribed here thus will provide many leads for integration of various cellular functions and serve as a major driving force in the com- pletion of the protein-protein interaction map.

Deduced primary structure of rat hepatocyte growth factor and expression of the mRNA in rat tissues.

Abstract: The primary structure of rat hepatocyte growth factor (HGF) was elucidated by determining the base sequence of the complementary DNA (cDNA) of HGF. The cDNA for rat HGF was isolated by screening a liver cDNA library with oligonucleotides based on the partial N-terminal amino acid sequence of the beta subunit of purified rat HGF. HGF is encoded in an mRNA of about 6 kilobases. Both alpha and beta subunits of HGF are specified in a single open reading frame for a 728-amino acid protein with a calculated molecular weight of 82,904. The N-terminal part of HGF has a signal sequence and a prosequence with 30 and 25 amino acid residues, respectively. The mature heterodimer structure is derived proteolytically from this single pre-pro precursor polypeptide. The calculated molecular weights of the alpha and beta subunits are 50,664 and 25,883, respectively, and each subunit has two potential N-linked glycosylation sites. The amino acid sequence of HGF is 38% identical with that of plasminogen. The alpha subunit of HGF contains four "kringle" structures, and the beta subunit has 37% amino acid identity with the serine protease domain of plasmin. Northern blot analysis revealed that HGF mRNA was expressed in rat various tissues, including the liver, kidney, lung, and brain.

Power-Law Distributions in Empirical Data

Abstract: Power-law distributions occur in many situations of scientific interest and have significant consequences for our understanding of natural and man-made phenomena. Unfortunately, the detection and characterization of power laws is complicated by the large fluctuations that occur in the tail of the distribution—the part of the distribution representing large but rare events—and by the difficulty of identifying the range over which power-law behavior holds. Commonly used methods for analyzing power-law data, such as least-squares fitting, can produce substantially inaccurate estimates of parameters for power-law distributions, and even in cases where such methods return accurate answers they are still unsatisfactory because they give no indication of whether the data obey a power law at all. Here we present a principled statistical framework for discerning and quantifying power-law behavior in empirical data. Our approach combines maximum-likelihood fitting methods with goodness-of-fit tests based on the Kolmogorov-Smirnov (KS) statistic and likelihood ratios. We evaluate the effectiveness of the approach with tests on synthetic data and give critical comparisons to previous approaches. We also apply the proposed methods to twenty-four real-world data sets from a range of different disciplines, each of which has been conjectured to follow a power-law distribution. In some cases we find these conjectures to be consistent with the data, while in others the power law is ruled out.

Epithelial–mesenchymal transitions in tumour progression

Abstract: Without epithelial–mesenchymal transitions, in which polarized epithelial cells are converted into motile cells, multicellular organisms would be incapable of getting past the blastula stage of embryonic development. However, this important developmental programme has a more sinister role in tumour progression. Epithelial–mesenchymal transition provides a new basis for understanding the progression of carcinoma towards dedifferentiated and more malignant states.

BioGRID: a general repository for interaction datasets

Abstract: Access to unified datasets of protein and genetic interactions is critical for interrogation of gene/protein function and analysis of global network properties. BioGRID is a freely accessible database of physical and genetic interactions available at http://www.thebiogrid.org. BioGRID release version 2.0 includes >116 000 interactions from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens. Over 30 000 interactions have recently been added from 5778 sources through exhaustive curation of the Saccharomyces cerevisiae primary literature. An internally hyper-linked web interface allows for rapid search and retrieval of interaction data. Full or user-defined datasets are freely downloadable as tab-delimited text files and PSI-MI XML. Pre-computed graphical layouts of interactions are available in a variety of file formats. User-customized graphs with embedded protein, gene and interaction attributes can be constructed with a visualization system called Osprey that is dynamically linked to the BioGRID.

A comprehensive two-hybrid analysis to explore the yeast protein interactome

Abstract: Protein-protein interactions play crucial roles in the execution of various biological functions. Accordingly, their comprehensive description would contribute considerably to the functional interpretation of fully sequenced genomes, which are flooded with novel genes of unpredictable functions. We previously developed a system to examine two-hybrid interactions in all possible combinations between the approximately 6,000 proteins of the budding yeast Saccharomyces cerevisiae. Here we have completed the comprehensive analysis using this system to identify 4,549 two-hybrid interactions among 3,278 proteins. Unexpectedly, these data do not largely overlap with those obtained by the other project [Uetz, P., et al. (2000) Nature (London) 403, 623-627] and hence have substantially expanded our knowledge on the protein interaction space or interactome of the yeast. Cumulative connection of these binary interactions generates a single huge network linking the vast majority of the proteins. Bioinformatics-aided selection of biologically relevant interactions highlights various intriguing subnetworks. They include, for instance, the one that had successfully foreseen the involvement of a novel protein in spindle pole body function as well as the one that may uncover a hitherto unidentified multiprotein complex potentially participating in the process of vesicular transport. Our data would thus significantly expand and improve the protein interaction map for the exploration of genome functions that eventually leads to thorough understanding of the cell as a molecular system.

Evolution of networks

Abstract: We review the recent rapid progress in the statistical physics of evolving networks. Interest has focused mainly on the structural properties of complex networks in communications, biology, social sciences and economics. A number of giant artificial networks of this kind have recently been created, which opens a wide field for the study of their topology, evolution, and the complex processes which occur in them. Such networks possess a rich set of scaling properties. A number of them are scale-free and show striking resilience against random breakdowns. In spite of the large sizes of these networks, the distances between most of their vertices are short - a feature known as the 'small-world' effect. We discuss how growing networks self-organize into scale-free structures, and investigate the role of the mechanism of preferential linking. We consider the topological and structural properties of evolving networks, and percolation and disease spread on these networks. We present a number of models demonstrat...