Pleiotropy, the ability of a single mutant gene to cause multiple mutant phenotypes, is a relatively common but poorly understood phenomenon in biology. Perhaps the greatest challenge in the analysis of pleiotropic genes is determining whether phenotypes associated with a mutation result from the loss of a single function or of multiple functions encoded by the same gene. Here we estimate the degree of pleiotropy in yeast by measuring the phenotypes of 4710 mutants under 21 environmental conditions, finding that it is significantly higher than predicted by chance. We use a biclustering algorithm to group pleiotropic genes by common phenotype profiles. Comparisons of these clusters to biological process classifications, synthetic lethal interactions, and protein complex data support the hypothesis that this method can be used to genetically define cellular functions. Applying these functional classifications to pleiotropic genes, we are able to dissect phenotypes into groups associated with specific gene functions.

Changes in DNA supercoiling are induced by a wide range of environmental stresses in Escherichia coli, but the physiological significance of these responses remains unclear. We now demonstrate that an increase in negative supercoiling is necessary for transcriptional activation of a large subset of osmotic stress-response genes. Using a microarray-based approach, we have characterized supercoiling-dependent gene transcription by expression profiling under conditions of high salt, in conjunction with the microbial antibiotics novobiocin, pefloxacin, and chloramphenicol. Algorithmic clustering and statistical measures for gauging cellular function show that this subset is enriched for genes critical in osmoprotectant transport/synthesis and rpoS-driven stationary phase adaptation. Transcription factor binding site analysis also supports regulation by the global stress factor rpoS. In addition, these studies implicate 60 uncharacterized genes in the osmotic stress regulon, and offer evidence for a broader role for supercoiling in the control of stress-induced transcription.

The majority of unstable proteins in eukaryotic cells are targeted for degradation through the ubiquitin-proteasome pathway. Substrates for degradation are recognized by the E1, E2, and E3 ubiquitin conjugation machinery and tagged with polyubiquitin chains, which are thought to promote the proteolytic process through their binding with the proteasome. We describe a method to bypass the ubiquitination step artificially both in vivo and in a purified in vitro system. Seven proteasome subunits were tagged with Fpr1, and fusion reporter constructs were created with the Fpr1-rapamycin binding domain of Tor1. Reporter proteins were localized to the proteasome by the addition of rapamycin, a drug that heterodimerizes Fpr1 and Tor1. Degradation of reporter proteins was observed with proteasomes that had either Rpn10 or Pre10 subunits tagged with Fpr1. Our experiments resolved a simple but central problem concerning the design of the ubiquitin-proteasome pathway. We conclude that localization to the proteasome is sufficient for degradation and, therefore, any added functions polyubiquitin chains possess beyond tethering substrates to the proteasome are not strictly necessary for proteolysis.ATP-dependent protease complexes degrade the majority of unstable cellular proteins, a process that is conserved across all three kingdoms of life. These molecular machines function both generally in protein turnover and specifically in the regulation of processes such as transcription, apoptosis, antigen presentation, and cell cycle progression (1). A high degree of conservation is evident among them; the archaebacterial and eukaryotic 20S proteolytic core particles share both sequence and structural homology (2), whereas eubacteria have functionally related complexes: ClpYQ, ClpXP, and ClpAP (3-5). The 20S core particle is composed of four stacked heptameric rings structured in an ␣-␤-␤-␣ configuration. Access to the proteolytic central chamber is obstructed at both ends of the cylindrical assembly by N-terminal projections of the ␣-subunits, thus preventing uncontrolled proteolytic degradation (5, 6). In eukaryotes, docking with the 19S regulatory particle (RP) 1 to form the complete 26S proteasome is sufficient to relieve this block, opening a channel into the core (6, 7).Eukaryotes have evolved an elaborate system that operates in conjunction with the proteasome to facilitate the temporal and specific regulation of intracellular proteolysis. Most proteins are targeted for degradation through ubiquitination, mediated by the E1, E2, E3 ubiquitin (Ub) conjugation machinery. These three consecutively acting enzymes are necessary for target recognition, transfer of a ubiquitin moiety to the substrate, and subsequent elongation of the ubiquitin branched chain (8). Modularity and the large number of E2 Ub-conjugating enzymes and E3 Ub ligases allow for greater specificity and flexibility in recognizing a diverse range of substrates. Once a protein is polyubiquitinated, it is targeted to and degraded by the 26S proteasome.The polyubiqui...

Yeast metabolic networks

An iterative approach that integrates high-throughput measurements of yeast deletion mutants and flux balance model predictions improves understanding of both experimental and computational results.

We use decision trees to predict phenotypes associated with Saccharomyces cerevisiae genes on the basis of Gene Ontology (GO) functional annotations from the Saccharomyces Genome Database (SGD) and other phenotypic annotations from the Yeast Phenotype Catalog at the Munich Information Center for Protein Sequences (MIPS). We assess the methodology in three ways: (1) we use cross-validation on the phenotypic annotations listed in MIPS, and show ROC curves indicating the tradeoff between true-positive rate and false-positive rate; (2) we do a literature-search for 100 of the predicted gene-phenotype associations that are not listed in MIPS, and find evidence for 43 of them; (3) we use deletion strains to experimentally assess 61 predicted gene-phenotype associations not listed in MIPS; significantly more of these deletion strains show abnormal growth than would be expected by chance.