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Benjamin L King

Publications and source records attributed to Benjamin L King.

4 recordsLinked to original sources

Characterization of multiple signaling pathways of insulin in the regulation of vascular endothelial growth factor expression in vascular cells and angiogenesis.

The effects of insulin on vascular endothelial growth factor (VEGF) expression in cultured vascular cells and in angiogenesis were characterized. Insulin increased VEGF mRNA levels in mouse aortic smooth muscle cells from 10(-9) to 10(-7) m with an initial peak of 3.7-fold increases at 1 h and a second peak of 2.8-fold after 12 h. The first peak of VEGF expression was inhibited by LY294002, an inhibitor of phosphatidylinositol (PI) 3-kinase, and by the overexpression of dominant negative forms of p85 subunit of PI 3-kinase or Akt. Inhibitors of MEK kinase, PD98059, or overexpression of dominant negative forms of Ras was ineffective. In contrast, the chronic effect of insulin on VEGF expression was partially inhibited by both LY294002 or PD98059 as well as by the overexpression of dominant negatives of PI 3-kinase or Ras. The importance of PI 3-kinase-Akt pathway on VEGF expression was confirmed in mouse aortic smooth muscle cells isolated from insulin receptor substrate -1 knockout (IRS-1-/-) mice that showed parallel reductions of 46-49% in insulin-stimulated VEGF expression and PI 3-kinase-Akt activation. Insulin-induced activation of PI 3-kinase-Akt on hypoxia-induced VEGF expression and neovascularization was reduced by 40% in the retina of neonatal hypoxia model using IRS-1-/- mice. Thus, unlike other cells, insulin can regulate VEGF expression by both IRS-1/PI 3-kinase-Akt cascade and Ras-MAPK pathways in aortic smooth muscle cells. The in vivo results provide direct evidence that insulin can modulate hypoxia-induced angiogenesis via reduction in VEGF expression in vivo.

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Integrating computationally assembled mouse transcript sequences with the Mouse Genome Informatics (MGI) database.

Databases of experimentally generated and computationally derived transcript sequences are valuable resources for genome analysis and annotation. The utility of such databases is enhanced when the sequences they contain are integrated with such biological information as genomic location, gene function, gene expression and phenotypic variation. We present the analysis and results of a semi-automated process of connecting transcript assemblies with highly curated biological information for mouse genes that is available through the Mouse Genome Informatics (MGI) database.

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Connecting sequence and biology in the laboratory mouse.

The Mouse Genome Sequencing Consortium and the RIKEN Genome Exploration Research grouphave generated large sets of sequence data representing the mouse genome and transcriptome, respectively. These data provide a valuable foundation for genomic research. The challenges for the informatics community are how to integrate these data with the ever-expanding knowledge about the roles of genes and gene products in biological processes, and how to provide useful views to the scientific community. Public resources, such as the National Center for Biotechnology Information (NCBI; http://www.ncbi.nih.gov), and model organism databases, such as the Mouse Genome Informatics database (MGI; http://www.informatics.jax.org), maintain the primary data and provide connections between sequence and biology. In this paper, we describe how the partnership of MGI and NCBI LocusLink contributes to the integration of sequence and biology, especially in the context of the large-scale genome and transcriptome data now available for the laboratory mouse. In particular, we describe the methods and results of integration of 60,770 FANTOM2 mouse cDNAs with gene records in the databases of MGI and LocusLink.

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Functional and comparative genomic analysis of the piebald deletion region of mouse chromosome 14.

Several developmentally important genomic regions map within the piebald deletion complex on distal mouse chromosome 14. We have combined computational gene prediction and comparative sequence analysis to characterize an approximately 4.3-Mb segment of the piebald region to identify candidate genes for the phenotypes presented by homozygous deletion mice. As a result we have ordered 13 deletion breakpoints, integrated the sequence with markers from a bacterial artificial chromosome (BAC) physical map, and identified 16 known or predicted genes and >1500 conserved sequence elements (CSEs) across the region. The candidate genes identified include Phr1 (formerly Pam) and Spry2, which are mouse homologs of genes required for development in Drosophila melanogaster. Gene content, order, and position are highly conserved between mouse chromosome 14 and the orthologous region of human chromosome 13. Our studies combining computational gene prediction with genetic and comparative genomic analyses provide insight regarding the functional composition and organization of this defined chromosomal region.

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