MatrixDB, the extracellular matrix interaction database

MatrixDB (http://matrixdb.ibcp.fr) is a freely available database focused on interactions established by extracellular proteins and polysaccharides. Only few databases report protein–polysaccharide interactions and, to the best of our knowledge, there is no other database of extracellular interactions. MatrixDB takes into account the multimeric nature of several extracellular protein families for the curation of interactions, and reports interactions with individual polypeptide chains or with multimers, considered as permanent complexes, when appropriate. MatrixDB is a member of the International Molecular Exchange consortium (IMEx) and has adopted the PSI-MI standards for the curation and the exchange of interaction data. MatrixDB stores experimental data from our laboratory, data from literature curation, data imported from IMEx databases, and data from the Human Protein Reference Database. MatrixDB is focused on mammalian interactions, but aims to integrate interaction datasets of model organisms when available. MatrixDB provides direct links to databases recapitulating mutations in genes encoding extracellular proteins, to UniGene and to the Human Protein Atlas that shows expression and localization of proteins in a large variety of normal human tissues and cells. MatrixDB allows researchers to perform customized queries and to build tissue- and disease-specific interaction networks that can be visualized and analyzed with Cytoscape or Medusa

ComPPI: a cellular compartment-specific database for protein-protein interaction network analysis

Here we present ComPPI, a cellular compartment-specific database of proteins and their interactions enabling an extensive, compartmentalized protein-protein interaction network analysis (URL: http://ComPPI.LinkGroup.hu). ComPPI enables the user to filter biologically unlikely interactions, where the two interacting proteins have no common subcellular localizations and to predict novel properties, such as compartment-specific biological functions. ComPPI is an integrated database covering four species (S. cerevisiae, C. elegans, D. melanogaster and H. sapiens). The compilation of nine protein-protein interaction and eight subcellular localization data sets had four curation steps including a manually built, comprehensive hierarchical structure of >1600 subcellular localizations. ComPPI provides confidence scores for protein subcellular localizations and protein-protein interactions. ComPPI has user-friendly search options for individual proteins giving their subcellular localization, their interactions and the likelihood of their interactions considering the subcellular localization of their interacting partners. Download options of search results, whole-proteomes, organelle-specific interactomes and subcellular localization data are available on its website. Due to its novel features, ComPPI is useful for the analysis of experimental results in biochemistry and molecular biology, as well as for proteome-wide studies in bioinformatics and network science helping cellular biology, medicine and drug design

Basement membrane ligands initiate distinct signalling networks to direct cell shape

Cells have evolved mechanisms to sense the composition of their adhesive microenvironment. Although much is known about general mechanisms employed by adhesion receptors to relay signals between the extracellular environment and the cytoskeleton, the nuances of ligand-specific signalling remain undefined. Here, we investigated how glomerular podocytes, and four other basement membrane-associated cell types, respond morphologically to different basement membrane ligands. We defined the composition of the respective adhesion complexes using mass spectrometry-based proteomics. On type IV collagen, all epithelial cell types adopted a round morphology, with a single lamellipodium and large adhesion complexes rich in actin-binding proteins. On laminin (511 or 521), all cell types attached to a similar degree but were polygonal in shape with small adhesion complexes enriched in endocytic and microtubule-binding proteins. Consistent with their distinctive morphologies, cells on type IV collagen exhibited high Rac1 activity, while those on laminin had elevated PKCα. Perturbation of PKCα was able to interchange morphology consistent with a key role for this pathway in matrix ligand-specific signalling. Therefore, this study defines the switchable basement membrane adhesome and highlights two key signalling pathways within the systems that determine distinct cell morphologies. Proteomic data are availableviaProteomeXchange with identifier PXD017913

MINT, the molecular interaction database: 2012 update

The Molecular INTeraction Database (MINT, http://mint.bio.uniroma2.it/mint/) is a public repository for protein-protein interactions (PPI) reported in peer-reviewed journals. The database grows steadily over the years and at September 2011 contains approximately 235,000 binary interactions captured from over 4750 publications. The web interface allows the users to search, visualize and download interactions data. MINT is one of the members of the International Molecular Exchange consortium (IMEx) and adopts the Molecular Interaction Ontology of the Proteomics Standard Initiative (PSI-MI) standards for curation and data exchange. MINT data are freely accessible and downloadable at http://mint.bio.uniroma2.it/mint/download.do. We report here the growth of the database, the major changes in curation policy and a new algorithm to assign a confidence to each interaction

A study on Carbon Nanotube-Gene Interaction in Induction of Glial Cells to Neuron Cell

Introduction: Reprogramming different cell to neuron have yet remained attractive field in regenerative medicine, so discovery new methodsor improve existing methods could be helpful. The aim of this study was to evaluate the Carbon Nanotube-Gene Interaction in Induction ofGlial Cells to Neuron Cell.Materials and Methods: Accordingly, we analyzed the transcriptome data of glial and neuron cells to determine thedifferent gene expression in both groups. Then, based on this transcriptome data, the gene chemical interaction was determined to find the mostimportant chemical structure which induces glial cell to neurons. Data extract from transcriptome database related rat cerebral cortex cellsgenerated by RNA sequencing transcriptomic (RNAseq) technique. By comparison neuron against glial cells (astrocyte, oligodenderocyte andmicroglia) determined different gene expression. In Comparative Toxicogenomics Database (CTD) determined the most important chemicalto interact with this gene set. Then by using genetrail2 database determined mechanism of gene set associated to chemicals and miRNA enriched.Results: Result determined different chemical with the risk factor and protective factor properties related to 500 genes that enriched in a neuronin comparison with glial cells. The carbon nanotube is the first important chemicals that interact with 75 genes of 500. Gene ontology analysisdetermined the carbon nanotube effect on genes that induce neurogenesis, neurodevelopment, and differentiation. Genetrail2 release the 29significant miRNAs enriched in gene interacts with carbon nanotube in which miR-34a and miR-449a are the most significant molecules.Network analysis of these genes represents KIT (tyrosine-protein kinase, CD117), Gria1, Syt1, Rab3c, and Tubb3 have central roles inneurogenesis by the carbon nanotube.Conclusion: In sum up, the carbon nanotube is an electrical stimulator that has biocompatibility toinduce glial cell to the neuron which applies as devise lonely or combination with a cell in damage part of the neural tissue