Peter Uetz

A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae

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.

A network of protein–protein interactions in yeast

A global analysis of 2,709 published interactions between proteins of the yeast Saccharomyces cerevisiae has been performed, enabling the establishment of a single large network of 2,358 interactions among 1,548 proteins. Proteins of known function and cellular location tend to cluster together, with 63% of the interactions occurring between proteins with a common functional assignment and 76% occurring between proteins found in the same subcellular compartment. Possible functions can be assigned to a protein based on the known functions of its interacting partners. This approach correctly predicts a functional category for 72% of the 1,393 characterized proteins with at least one partner of known function, and has been applied to predict functions for 364 previously uncharacterized proteins.

The minimum information required for reporting a molecular interaction experiment (MIMIx)

A wealth of molecular interaction data is available in the literature, ranging from large-scale datasets to a single interaction confirmed by several different techniques. These data are all too often reported either as free text or in tables of variable format, and are often missing key pieces of information essential for a full understanding of the experiment. Here we propose MIMIx, the minimum information required for reporting a molecular interaction experiment. Adherence to these reporting guidelines will result in publications of increased clarity and usefulness to the scientific community and will support the rapid, systematic capture of molecular interaction data in public databases, thereby improving access to valuable interaction data.

Protein interaction data curation: the International Molecular Exchange (IMEx) consortium

The International Molecular Exchange (IMEx) consortium is an international collaboration between major public interaction data providers to share literature-curation efforts and make a nonredundant set of protein interactions available in a single search interface on a common website (http://www.imexconsortium.org/). Common curation rules have been developed, and a central registry is used to manage the selection of articles to enter into the dataset. We discuss the advantages of such a service to the user, our quality-control measures and our data-distribution practices.

Towards an understanding of complex protein networks

Large-scale two-hybrid screens have generated a wealth of information describing potential protein--protein interactions. When compiled with data from systematic localizations of proteins, mutant screens and other functional tests, a network of interactions among proteins and between proteins and other components of eukaryotic cells can be deduced. These networks can be viewed as maps of the cell, depicting potential signaling pathways and interactive complexes. Most importantly, they provide potential clues to the function of previously uncharacterized proteins. Focusing on recent experiments, we explore these protein-interaction studies and the maps derived from such efforts.

The Burmese python genome reveals the molecular basis for extreme adaptation in snakes

Significance The molecular basis of morphological and physiological adaptations in snakes is largely unknown. Here, we study these phenotypes using the genome of the Burmese python (Python molurus bivittatus), a model for extreme phenotypic plasticity and metabolic adaptation. We discovered massive rapid changes in gene expression that coordinate major changes in organ size and function after feeding. Many significantly responsive genes are associated with metabolism, development, and mammalian diseases. A striking number of genes experienced positive selection in ancestral snakes. Such genes were related to metabolism, development, lungs, eyes, heart, kidney, and skeletal structure—all highly modified features in snakes. Snake phenotypic novelty seems to be driven by the system-wide coordination of protein adaptation, gene expression, and changes in genome structure. Snakes possess many extreme morphological and physiological adaptations. Identification of the molecular basis of these traits can provide novel understanding for vertebrate biology and medicine. Here, we study snake biology using the genome sequence of the Burmese python (Python molurus bivittatus), a model of extreme physiological and metabolic adaptation. We compare the python and king cobra genomes along with genomic samples from other snakes and perform transcriptome analysis to gain insights into the extreme phenotypes of the python. We discovered rapid and massive transcriptional responses in multiple organ systems that occur on feeding and coordinate major changes in organ size and function. Intriguingly, the homologs of these genes in humans are associated with metabolism, development, and pathology. We also found that many snake metabolic genes have undergone positive selection, which together with the rapid evolution of mitochondrial proteins, provides evidence for extensive adaptive redesign of snake metabolic pathways. Additional evidence for molecular adaptation and gene family expansions and contractions is associated with major physiological and phenotypic adaptations in snakes; genes involved are related to cell cycle, development, lungs, eyes, heart, intestine, and skeletal structure, including GRB2-associated binding protein 1, SSH, WNT16, and bone morphogenetic protein 7. Finally, changes in repetitive DNA content, guanine-cytosine isochore structure, and nucleotide substitution rates indicate major shifts in the structure and evolution of snake genomes compared with other amniotes. Phenotypic and physiological novelty in snakes seems to be driven by system-wide coordination of protein adaptation, gene expression, and changes in the structure of the genome.

Evolutionarily conserved herpesviral protein interaction networks.

Herpesviruses constitute a family of large DNA viruses widely spread in vertebrates and causing a variety of different diseases. They possess dsDNA genomes ranging from 120 to 240 kbp encoding between 70 to 170 open reading frames. We previously reported the protein interaction networks of two herpesviruses, varicella-zoster virus (VZV) and Kaposis sarcoma-associated herpesvirus (KSHV). In this study, we systematically tested three additional herpesvirus species, herpes simplex virus 1 (HSV-1), murine cytomegalovirus and Epstein-Barr virus, for protein interactions in order to be able to perform a comparative analysis of all three herpesvirus subfamilies. We identified 735 interactions by genome-wide yeast-two-hybrid screens (Y2H), and, together with the interactomes of VZV and KSHV, included a total of 1,007 intraviral protein interactions in the analysis. Whereas a large number of interactions have not been reported previously, we were able to identify a core set of highly conserved protein interactions, like the interaction between HSV-1 UL33 with the nuclear egress proteins UL31/UL34. Interactions were conserved between orthologous proteins despite generally low sequence similarity, suggesting that function may be more conserved than sequence. By combining interactomes of different species we were able to systematically address the low coverage of the Y2H system and to extract biologically relevant interactions which were not evident from single species.

Systematic and large-scale two-hybrid screens

The increasing rate at which complete genome sequences become available necessitates rapid and robust methods for investigating the functions of their encoded proteins. Efforts have been made to study protein function by systematically screening large sets of proteins using the two-hybrid method. Analyses of the complete proteomes of baceriophage T7, the mammalian viruses hepatitis C and vaccinia, as well as of several protein complexes including RNA splicing proteins and RNA polymerase III from yeast, have been undertaken. Saccharomyces cerevisiae has been studied extensively by two-hybrid methods, with more than 2500 protein-protein interactions described. Systematic studies on metazoan proteomes are, however, still in their infancy.

MPIDB: the microbial protein interaction database

Summary: The microbial protein interaction database (MPIDB) aims to collect and provide all known physical microbial interactions. Currently, 22 530 experimentally determined interactions among proteins of 191 bacterial species/strains can be browsed and downloaded. These microbial interactions have been manually curated from the literature or imported from other databases (IntAct, DIP, BIND, MINT) and are linked to 24 060 experimental evidences (PubMed ID, PSI-MI methods). In contrast to these databases, interactions in MPIDB are further supported by 8150 additional evidences based on interaction conservation, co-purification and 3D domain contacts (iPfam, 3did). Availability: http://www.jcvi.org/mpidb/ Contact: jgoll@jcvi.org

[1] High-throughput screening for protein-protein interactions using two-hybrid assay

Publisher Summary The accumulation of large amounts of genomic sequence data has prompted studies in protein biology on an unprecedented scale. Determining the functions of uncharacterized open reading frames (ORFs) from yeast and other organisms is a major challenge, and traditional biochemical and genetic approaches are struggling to keep up with sequence data. One strategy to help determine the functions is to identify protein–protein interactions using the two-hybrid system, a genetic assay that takes place within living yeast cells. An array format is developed in the chapter to increase the throughput of proteins that can be screened by the two-hybrid method. An array is a spatially ordered set of separated elements in which each element is a unique protein potentially available for interaction. This chapter describes methods for constructing and screening a protein array that contains most of the proteins present in S. cerevisiae . However, the array may represent any group of proteins: all the expressed proteins present in an organism a family of related proteins, or even a set of proteins or peptides, not found in nature.