Meijia Yang

Bio: Meijia Yang is an academic researcher from Stony Brook University. The author has contributed to research in topics: Polynucleotide & Nucleic acid. The author has an hindex of 9, co-authored 29 publications receiving 5657 citations.

A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae

Abstract: Two large-scale yeast two-hybrid screens were undertaken to identify protein-protein interactions between full-length open reading frames predicted from the Saccharomyces cerevisiae genome sequence. In one approach, we constructed a protein array of about 6,000 yeast transformants, with each transformant expressing one of the open reading frames as a fusion to an activation domain. This array was screened by a simple and automated procedure for 192 yeast proteins, with positive responses identified by their positions in the array. In a second approach, we pooled cells expressing one of about 6,000 activation domain fusions to generate a library. We used a high-throughput screening procedure to screen nearly all of the 6,000 predicted yeast proteins, expressed as Gal4 DNA-binding domain fusion proteins, against the library, and characterized positives by sequence analysis. These approaches resulted in the detection of 957 putative interactions involving 1,004 S. cerevisiae proteins. These data reveal interactions that place functionally unclassified proteins in a biological context, interactions between proteins involved in the same biological function, and interactions that link biological functions together into larger cellular processes. The results of these screens are shown here.

PDGF-D, a new protease-activated growth factor

Abstract: Platelet-derived growth factor (PDGF) has been directly implicated in developmental and physiological processes, as well as in human cancer, fibrotic diseases and arteriosclerosis. The PDGF family currently consists of at least three gene products, PDGF-A, PDGF-B and PDGF-C, which selectively signal through two PDGF receptors (PDGFRs) to regulate diverse cellular functions. After two decades of searching, PDGF-A and B were the only ligands identified for PDGFRs. Recently, however, database mining has resulted in the discovery of a third member of the PDGF family, PDGF-C, a functional analogue of PDGF-A that requires proteolytic activation. PDGF-A and PDGF-C selectively activate PDGFR-alpha, whereas PDGF-B activates both PDGFR-alpha and PDGFR-beta. Here we identify and characterize a new member of the PDGF family, PDGF D, which also requires proteolytic activation. Recombinant, purified PDGF-D induces DNA synthesis and growth in cells expressing PDGFRs. In cells expressing individual PDGFRs, PDGF-D binds to and activates PDGFR-beta but not PDGFR-alpha. However, in cells expressing both PDGFRs, PDGF-D activates both receptors. This indicates that PDGFR-alpha activation may result from PDGFR-alpha/beta heterodimerization.

Protein-peptide interactions analyzed with the yeast two-hybrid system

Abstract: The yeast two-hybrid system was used to screen a library of random peptides fused to a transcriptional activation domain in order to identify peptides capable of binding to the retinoblastoma protein (Rb) Seven peptides were identified, all of which contain the Leu-X-Cys-X-Glu motif found in Rb-binding proteins, although their activity in the yeast assay varied over a 40-fold range Mutagenesis of the DNA encoding two of these peptides followed by screening in the two-hybrid system allowed the delineation of residues apart from the invariant Leu, Cys and Glu that affect binding to Rb Binding affinities of a peptide and one of its variants to Rb, determined by surface plasmon resonance, correlated with results from the two-hybrid assay This method offers several advantageous features compared to existing technology for screening peptide libraries: in vivo detection of protein-peptide interactions, high sensitivity, the capacity for rapid genetic screening to identify stronger and weaker binding peptide variants, and the use of a simple assay (transcriptional activity) as a means to assess binding affinity

Angioarrestin: an antiangiogenic protein with tumor-inhibiting properties.

Abstract: The angiopoietins comprise a family of proteins that have pro or antiangiogenic activities. Through a proprietary technology designed to identify transcripts of all expressed genes, we isolated a cDNA encoding an angiopoietin-related protein that we designate angioarrestin. The mRNA expression profile of angioarrestin was striking in that it was down-regulated in many tumor tissues when compared with adjacent nontumor tissue, suggesting a role for this protein in tumor inhibition. To test this hypothesis, we ectopically expressed angioarrestin in HT1080 tumor cells and measured pulmonary tumor nodule formation in nude mice. HT1080 cells expressing angioarrestin showed a marked reduction in the number and size of tumor nodules. In vitro, the recombinant protein was systematically tested in a number of endothelial cell assays and found to block critical processes involved in the angiogenic cascade, such as vascular endothelial growth factor/basic fibroblast growth factor-mediated endothelial cell proliferation, migration, tubular network formation, and adhesion to extracellular matrix proteins. These findings reveal a novel function for angioarrestin as an angiogenesis inhibitor and indicate that the molecule may be a potential cancer therapeutic.

Identification and comparison of protein-protein interactions that occur in populations and identification of inhibitors of these interactors

Abstract: Methods are described for detecting protein-protein interactions, among two populations of proteins, each having a complexity of at least 1,000. For example, proteins are fused either to the DNA-binding domain of a transcriptional activator or to the activation domain of a transcriptional activator. Two yeast strains, of the opposite mating type and carrying one type each of the fusion proteins are mated together. Productive interactions between the two halves due to protein-protein interactions lead to the reconstitution of the transcriptional activator, which in turn leads to the activation of a reporter gene containing a binding site for the DNA-binding domain. This analysis can be carried out for two or more populations of proteins. The differences in the genes encoding the proteins involved in the protein-protein interactions are characterized, thus leading to the identification of specific protein-protein interactions, and the genes encoding the interacting proteins, relevant to a particular tissue, stage or disease. Furthermore, inhibitors that interfere with these protein-protein interactions are identified by their ability to inactivate a reporter gene. The screening for such inhibitors can be in a multiplexed format where a set of inhibitors will be screened against a library of interactors.

The Structure and Function of Complex Networks

Abstract: Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.

Network biology: understanding the cell's functional organization

Abstract: A key aim of postgenomic biomedical research is to systematically catalogue all molecules and their interactions within a living cell. There is a clear need to understand how these molecules and the interactions between them determine the function of this enormously complex machinery, both in isolation and when surrounded by other cells. Rapid advances in network biology indicate that cellular networks are governed by universal laws and offer a new conceptual framework that could potentially revolutionize our view of biology and disease pathologies in the twenty-first century.

Lethality and centrality in protein networks

Abstract: The most highly connected proteins in the cell are the most important for its survival. Proteins are traditionally identified on the basis of their individual actions as catalysts, signalling molecules, or building blocks in cells and microorganisms. But our post-genomic view is expanding the protein's role into an element in a network of protein–protein interactions as well, in which it has a contextual or cellular function within functional modules1,2. Here we provide quantitative support for this idea by demonstrating that the phenotypic consequence of a single gene deletion in the yeast Saccharomyces cerevisiae is affected to a large extent by the topological position of its protein product in the complex hierarchical web of molecular interactions.

Functional organization of the yeast proteome by systematic analysis of protein complexes

Abstract: Most cellular processes are carried out by multiprotein complexes. The identification and analysis of their components provides insight into how the ensemble of expressed proteins (proteome) is organized into functional units. We used tandem-affinity purification (TAP) and mass spectrometry in a large-scale approach to characterize multiprotein complexes in Saccharomyces cerevisiae. We processed 1,739 genes, including 1,143 human orthologues of relevance to human biology, and purified 589 protein assemblies. Bioinformatic analysis of these assemblies defined 232 distinct multiprotein complexes and proposed new cellular roles for 344 proteins, including 231 proteins with no previous functional annotation. Comparison of yeast and human complexes showed that conservation across species extends from single proteins to their molecular environment. Our analysis provides an outline of the eukaryotic proteome as a network of protein complexes at a level of organization beyond binary interactions. This higher-order map contains fundamental biological information and offers the context for a more reasoned and informed approach to drug discovery.