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.

Identification of protein-protein interactions often provides insight into protein function, and many cellular processes are performed by stable protein complexes. We used tandem affinity purification to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae. Each preparation was analysed by both matrix-assisted laser desorption/ionization-time of flight mass spectrometry and liquid chromatography tandem mass spectrometry to increase coverage and accuracy. Machine learning was used to integrate the mass spectrometry scores and assign probabilities to the protein-protein interactions. Among 4,087 different proteins identified with high confidence by mass spectrometry from 2,357 successful purifications, our core data set (median precision of 0.69) comprises 7,123 protein-protein interactions involving 2,708 proteins. A Markov clustering algorithm organized these interactions into 547 protein complexes averaging 4.9 subunits per complex, about half of them absent from the MIPS database, as well as 429 additional interactions between pairs of complexes. The data (all of which are available online) will help future studies on individual proteins as well as functional genomics and systems biology.

Human immunodeficiency virus (HIV) has a small genome and therefore relies heavily on the host cellular machinery to replicate. Identifying which host proteins and complexes come into physical contact with the viral proteins is crucial for a comprehensive understanding of how HIV rewires the host’s cellular machinery during the course of infection. Here we report the use of affinity tagging and purification mass spectrometry1-3 to determine systematically the physical interactions of all 18 HIV-1 proteins and polyproteins with host proteins in two different human cell lines (HEK293 and Jurkat). Using a quantitative scoring system that we call MiST, we identified with high confidence 497 HIV–human protein–protein interactions involving 435 individual human proteins, with ~40% of the interactions being identified in both cell types. We found that the host proteins hijacked by HIV, especially those found interacting in both cell types, are highly conserved across primates. We uncovered a number of host complexes targeted by viral proteins, including the finding that HIV protease cleaves eIF3d, a subunit of eukaryotic translation initiation factor 3. This host protein is one of eleven identified in this analysis that act to inhibit HIV replication. This data set facilitates a more comprehensive and detailed understanding of how the host machinery is manipulated during the course of HIV infection.

Physical, genetic, and chemical-genetic interactions centered on the conserved chaperone Hsp90 were mapped at high resolution in yeast using systematic proteomic and genomic methods. Physical interactions were identified using genome-wide two hybrid screens combined with large-scale affinity purification of Hsp90-containing protein complexes. Genetic interactions were uncovered using synthetic genetic array technology and by a microarray-based chemical-genetic screen of a set of about 4700 viable yeast gene deletion mutants for hypersensitivity to the Hsp90 inhibitor geldanamycin. An extended network, consisting of 198 putative physical interactions and 451 putative genetic and chemical-genetic interactions, was found to connect Hsp90 to cofactors and substrates involved in a wide range of cellular functions. Two novel Hsp90 cofactors, Tah1 (YCR060W) and Pih1 (YHR034C), were also identified. These cofactors interact physically and functionally with the conserved AAA(+)-type DNA helicases Rvb1/Rvb2, which are key components of several chromatin remodeling factors, thereby linking Hsp90 to epigenetic gene regulation.

Set2 methylates Lys36 of histone H3. We show here that yeast Set2 copurifies with RNA polymerase II (RNAPII). Chromatin immunoprecipitation analyses demonstrated that Set2 and histone H3 Lys36 methylation are associated with the coding regions of several genes that were tested and correlate with active transcription. Both depend, as well, on the Paf1 elongation factor complex. The C terminus of Set2, which contains a WW domain, is also required for effective Lys36 methylation. Deletion of CTK1, encoding an RNAPII CTD kinase, prevents Lys36 methylation and Set2 recruitment, suggesting that methylation may be triggered by contact of the WW domain or C terminus of Set2 with Ser2-phosphorylated CTD. A set2 deletion results in slight sensitivity to 6-azauracil and much less ␤-galactosidase produced by a reporter plasmid, resulting from a defect in transcription. In synthetic genetic array (SGA) analysis, synthetic growth defects were obtained when a set2 deletion was combined with deletions of all five components of the Paf1 complex, the chromodomain elongation factor Chd1, the putative elongation factor Soh1, the Bre1 or Lge1 components of the histone H2B ubiquitination complex, or the histone H2A variant Htz1. SET2 also interacts genetically with components of the Set1 and Set3 complexes, suggesting that Set1, Set2, and Set3 similarly affect transcription by RNAPII.In Saccharomyces cerevisiae RNA polymerase II (RNAPII) initiates transcription in concert with general transcription factors and a 20-subunit mediator complex (16,38,59). During initiation it becomes phosphorylated by the Kin28 subunit of the general transcription factor TFIIH on Ser5 of the heptapeptide repeats, YSPTSPS, in the carboxy-terminal domain (CTD) of its largest subunit, Rpb1, resulting in recruitment of the mRNA-capping enzyme to the transcription complex (23,32,49,69). Ser5 phosphorylation declines during the early stages of elongation and is replaced by Ser2 phosphorylation, mediated mainly by the cyclin-dependent kinase, Ctk1, during the later stages of elongation by RNAPII (10, 23). General transcription factors and mediator dissociate from the transcription complex or remain behind at the promoter and are replaced by various elongation factors during chain elongation by RNAPII (25,43). Among these elongation factors are Spt4/ Spt5, Spt6/Iws1, and Spt16/Pob3, whose patterns of genetic interactions suggest that they participate in transcription on chromatin templates (66). Another elongation factor is the Paf1 complex, which consists of Paf1, Rtf1, Cdc73, Ctr9, and Leo1 and associates with RNAPII (25, 34, 52). Chromatin immunoprecipitation (ChIP) experiments have shown that all of these polypeptides are associated with transcribed regions (25,43).Histone methylation by SET domain-containing histone lysine methyltransferases has important roles in chromatin structure and function (44). Lysines 4, 9, 27, and 79 are well-studied sites of methylation on histone H3, while lysine 20 is the only known methylated lysine in histone H4 (55, 64). The...