Jinhui Zhong

Bio: Jinhui Zhong is an academic researcher from Wayne State University. The author has contributed to research in topics: Protein–protein interaction & Two-hybrid screening. The author has an hindex of 5, co-authored 5 publications receiving 2740 citations.

A Protein Interaction Map of Drosophila melanogaster

Abstract: Drosophila melanogaster is a proven model system for many aspects of human biology. Here we present a two-hybrid-based protein-interaction map of the fly proteome. A total of 10,623 predicted transcripts were isolated and screened against standard and normalized complementary DNA libraries to produce a draft map of 7048 proteins and 20,405 interactions. A computational method of rating two-hybrid interaction confidence was developed to refine this draft map to a higher confidence map of 4679 proteins and 4780 interactions. Statistical modeling of the network showed two levels of organization: a short-range organization, presumably corresponding to multiprotein complexes, and a more global organization, presumably corresponding to intercomplex connections. The network recapitulated known pathways, extended pathways, and uncovered previously unknown pathway components. This map serves as a starting point for a systems biology modeling of multicellular organisms, including humans.

A Drosophila protein-interaction map centered on cell-cycle regulators

Abstract: Background: Maps depicting binary interactions between proteins can be powerful starting points for understanding biological systems. A proven technology for generating such maps is highthroughput yeast two-hybrid screening. In the most extensive screen to date, a Gal4-based twohybrid system was used recently to detect over 20,000 interactions among Drosophila proteins. Although these data are a valuable resource for insights into protein networks, they cover only a fraction of the expected number of interactions. Results: To complement the Gal4-based interaction data, we used the same set of Drosophila open reading frames to construct arrays for a LexA-based two-hybrid system. We screened the arrays using a novel pooled mating approach, initially focusing on proteins related to cell-cycle regulators. We detected 1,814 reproducible interactions among 488 proteins. The map includes a large number of novel interactions with potential biological significance. Informative regions of the map could be highlighted by searching for paralogous interactions and by clustering proteins on the basis of their interaction profiles. Surprisingly, only 28 interactions were found in common between the LexA- and Gal4-based screens, even though they had similar rates of true positives. Conclusions: The substantial number of new interactions discovered here supports the conclusion that previous interaction mapping studies were far from complete and that many more interactions remain to be found. Our results indicate that different two-hybrid systems and screening approaches applied to the same proteome can generate more comprehensive datasets with more cross-validated interactions. The cell-cycle map provides a guide for further defining important regulatory networks in Drosophila and other organisms.

Interaction mating methods in two-hybrid systems

Abstract: Publisher Summary The yeast two-hybrid system is a powerful assay for protein–protein interactions. The two proteins to be tested for interaction are expressed as hybrids in the nucleus of a yeast cell. One of the proteins is fused to the deoxyribonucleic acid (DNA)-binding domain (DBD) of a transcription factor and the other is fused to a transcription activation domain (AD). If the two hybrid proteins interact, they reconstitute a functional transcription factor that activates one or more reporter genes that contain binding sites for the DBD. This simple assay has been widely used to identify new interacting proteins from libraries, to test interactions between small and large sets of proteins, to map protein networks, and to address the functions of individual proteins and protein interactions. This chapter describes interaction mating, a two-hybrid variation that can be adapted to most versions of the system and that can simplify and facilitate most two-hybrid experiments.

A strategy for constructing large protein interaction maps using the yeast two-hybrid system: regulated expression arrays and two-phase mating.

Abstract: Maps representing the binary interactions among proteins have become valuable tools for understanding how proteins work together to mediate biological processes. One of the most effective methods for detecting biologically important protein interactions has been the yeast two-hybrid system. Here we present an efficient two-hybrid strategy to facilitate construction of protein interaction maps on a genome-wide scale. The strategy begins with two arrays of yeast expressing known proteins fused to either a DNA binding domain (BD), or a transcription activation domain (AD). The fusion proteins are conditionally expressed using regulated promoters that can be repressed during construction and amplification of the yeast arrays. Interaction assays are conducted in two phases. In the first phase, small pools of AD strains are mated with the array of BD strains. In the second phase, individual BD strains are mated with appropriate subsets of the AD array corresponding to positive pools in the first phase. This strategy has several advantages over previously described approaches, including the ability to detect interactions with proteins that inhibit yeast growth or that activate transcription as BD fusions. Moreover, by minimizing the number of mating operations and sequencing reactions needed to test large sets of binary interactions, this strategy is more efficient than either matrix or library screening approaches. We also present a three-dimensional pooling scheme to further increase the efficiency of large-scale two-hybrid analyses.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

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.

Network Medicine: A Network-Based Approach to Human Disease

Abstract: Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular and intercellular network that links tissue and organ systems. The emerging tools of network medicine offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships among apparently distinct (patho)phenotypes. Advances in this direction are essential for identifying new disease genes, for uncovering the biological significance of disease-associated mutations identified by genome-wide association studies and full-genome sequencing, and for identifying drug targets and biomarkers for complex diseases.

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.