Proteome analysis of yeast response to various nutrient limitations

We compared the response of Saccharomyces cerevisiae to carbon (glucose) and nitrogen (ammonia) limitation in chemostat cultivation at the proteome level. Protein levels were differentially quantified using unlabeled and (15)N metabolically labeled yeast cultures. A total of 928 proteins covering a wide range of isoelectric points, molecular weights and subcellular localizations were identified. Stringent statistical analysis identified 51 proteins upregulated in response to glucose limitation and 51 upregulated in response to ammonia limitation. Under glucose limitation, typical glucose-repressed genes encoding proteins involved in alternative carbon source utilization, fatty acids β-oxidation and oxidative phosphorylation displayed an increased protein level. Proteins upregulated in response to nitrogen limitation were mostly involved in scavenging of alternative nitrogen sources and protein degradation. Comparison of transcript and protein levels clearly showed that upregulation in response to glucose limitation was mainly transcriptionally controlled, whereas upregulation in response to nitrogen limitation was essentially controlled at the post-transcriptional level by increased translational efficiency and/or decreased protein degradation. These observations underline the need for multilevel analysis in yeast systems biology

Composition-based statistics and translated nucleotide searches: Improving the TBLASTN module of BLAST

BACKGROUND: TBLASTN is a mode of operation for BLAST that aligns protein sequences to a nucleotide database translated in all six frames. We present the first description of the modern implementation of TBLASTN, focusing on new techniques that were used to implement composition-based statistics for translated nucleotide searches. Composition-based statistics use the composition of the sequences being aligned to generate more accurate E-values, which allows for a more accurate distinction between true and false matches. Until recently, composition-based statistics were available only for protein-protein searches. They are now available as a command line option for recent versions of TBLASTN and as an option for TBLASTN on the NCBI BLAST web server. RESULTS: We evaluate the statistical and retrieval accuracy of the E-values reported by a baseline version of TBLASTN and by two variants that use different types of composition-based statistics. To test the statistical accuracy of TBLASTN, we ran 1000 searches using scrambled proteins from the mouse genome and a database of human chromosomes. To test retrieval accuracy, we modernize and adapt to translated searches a test set previously used to evaluate the retrieval accuracy of protein-protein searches. We show that composition-based statistics greatly improve the statistical accuracy of TBLASTN, at a small cost to the retrieval accuracy. CONCLUSION: TBLASTN is widely used, as it is common to wish to compare proteins to chromosomes or to libraries of mRNAs. Composition-based statistics improve the statistical accuracy, and therefore the reliability, of TBLASTN results. The algorithms used by TBLASTN are not widely known, and some of the most important are reported here. The data used to test TBLASTN are available for download and may be useful in other studies of translated search algorithms

Hsf1 Activation Inhibits Rapamycin Resistance and TOR Signaling in Yeast Revealed by Combined Proteomic and Genetic Analysis

TOR kinases integrate environmental and nutritional signals to regulate cell growth in eukaryotic organisms. Here, we describe results from a study combining quantitative proteomics and comparative expression analysis in the budding yeast, S. cerevisiae, to gain insights into TOR function and regulation. We profiled protein abundance changes under conditions of TOR inhibition by rapamycin treatment, and compared this data to existing expression information for corresponding gene products measured under a variety of conditions in yeast. Among proteins showing abundance changes upon rapamycin treatment, almost 90% of them demonstrated homodirectional (i.e., in similar direction) transcriptomic changes under conditions of heat/oxidative stress. Because the known downstream responses regulated by Tor1/2 did not fully explain the extent of overlap between these two conditions, we tested for novel connections between the major regulators of heat/oxidative stress response and the TOR pathway. Specifically, we hypothesized that activation of regulator(s) of heat/oxidative stress responses phenocopied TOR inhibition and sought to identify these putative TOR inhibitor(s). Among the stress regulators tested, we found that cells (hsf1-R206S, F256S and ssa1-3 ssa2-2) constitutively activated for heat shock transcription factor 1, Hsf1, inhibited rapamycin resistance. Further analysis of the hsf1-R206S, F256S allele revealed that these cells also displayed multiple phenotypes consistent with reduced TOR signaling. Among the multiple Hsf1 targets elevated in hsf1-R206S, F256S cells, deletion of PIR3 and YRO2 suppressed the TOR-regulated phenotypes. In contrast to our observations in cells activated for Hsf1, constitutive activation of other regulators of heat/oxidative stress responses, such as Msn2/4 and Hyr1, did not inhibit TOR signaling. Thus, we propose that activated Hsf1 inhibits rapamycin resistance and TOR signaling via elevated expression of specific target genes in S. cerevisiae. Additionally, these results highlight the value of comparative expression analyses between large-scale proteomic and transcriptomic datasets to reveal new regulatory connections

Transcriptional responses to glucose in Saccharomyces cerevisiae strains lacking a functional protein kinase A

Background The pattern of gene transcripts in the yeast Saccharomyces cerevisiae is strongly affected by the presence of glucose. An increased activity of protein kinase A (PKA), triggered by a rise in the intracellular concentration of cAMP, can account for many of the effects of glucose on transcription. In S. cerevisiae three genes, TPK1, TPK2, and TPK3, encode catalytic subunits of PKA. The lack of viability of tpk1 tpk2 tpk3 triple mutants may be suppressed by mutations such as yak1 or msn2/msn4. To investigate the requirement for PKA in glucose control of gene expression, we have compared the effects of glucose on global transcription in a wild-type strain and in two strains devoid of PKA activity, tpk1 tpk2 tpk3 yak1 and tpk1 tpk2 tpk3 msn2 msn4. Results We have identified different classes of genes that can be induced -or repressed- by glucose in the absence of PKA. Representative examples are genes required for glucose utilization and genes involved in the metabolism of other carbon sources, respectively. Among the genes responding to glucose in strains devoid of PKA some are also controlled by a redundant signalling pathway involving PKA activation, while others are not affected when PKA is activated through an increase in cAMP concentration. On the other hand, among genes that do not respond to glucose in the absence of PKA, some give a full response to increased cAMP levels, even in the absence of glucose, while others appear to require the cooperation of different signalling pathways. We show also that, for a number of genes controlled by glucose through a PKA-dependent pathway, the changes in mRNA levels are transient. We found that, in cells grown in gluconeogenic conditions, expression of a small number of genes, mainly connected with the response to stress, is reduced in the strains lacking PKA. Conclusions In S. cerevisiae, the transcriptional responses to glucose are triggered by a variety of pathways, alone or in combination, in which PKA is often involved. Redundant signalling pathways confer a greater robustness to the response to glucose, while cooperative pathways provide a greater flexibility.BT/BiotechnologyApplied Science

Detection of changes in gene regulatory patterns, elicited by perturbations of the Hsp90 molecular chaperone complex, by visualizing multiple experiments with an animation

<p>Abstract</p> <p>Background</p> <p>To make sense out of gene expression profiles, such analyses must be pushed beyond the mere listing of affected genes. For example, if a group of genes persistently display similar changes in expression levels under particular experimental conditions, and the proteins encoded by these genes interact and function in the same cellular compartments, this could be taken as very strong indicators for co-regulated protein complexes. One of the key requirements is having appropriate tools to detect such regulatory patterns.</p> <p>Results</p> <p>We have analyzed the global adaptations in gene expression patterns in the budding yeast when the Hsp90 molecular chaperone complex is perturbed either pharmacologically or genetically. We integrated these results with publicly accessible expression, protein-protein interaction and intracellular localization data. But most importantly, all experimental conditions were simultaneously and dynamically visualized with an animation. This critically facilitated the detection of patterns of gene expression changes that suggested underlying regulatory networks that a standard analysis by pairwise comparison and clustering could not have revealed.</p> <p>Conclusions</p> <p>The results of the animation-assisted detection of changes in gene regulatory patterns make predictions about the potential roles of Hsp90 and its co-chaperone p23 in regulating whole sets of genes. The simultaneous dynamic visualization of microarray experiments, represented in networks built by integrating one's own experimental with publicly accessible data, represents a powerful discovery tool that allows the generation of new interpretations and hypotheses.</p

Multiple Signals Converge on a Differentiation MAPK Pathway

An important emerging question in the area of signal transduction is how information from different pathways becomes integrated into a highly coordinated response. In budding yeast, multiple pathways regulate filamentous growth, a complex differentiation response that occurs under specific environmental conditions. To identify new aspects of filamentous growth regulation, we used a novel screening approach (called secretion profiling) that measures release of the extracellular domain of Msb2p, the signaling mucin which functions at the head of the filamentous growth (FG) MAPK pathway. Secretion profiling of complementary genomic collections showed that many of the pathways that regulate filamentous growth (RAS, RIM101, OPI1, and RTG) were also required for FG pathway activation. This regulation sensitized the FG pathway to multiple stimuli and synchronized it to the global signaling network. Several of the regulators were required for MSB2 expression, which identifies the MSB2 promoter as a target “hub” where multiple signals converge. Accessibility to the MSB2 promoter was further regulated by the histone deacetylase (HDAC) Rpd3p(L), which positively regulated FG pathway activity and filamentous growth. Our findings provide the first glimpse of a global regulatory hierarchy among the pathways that control filamentous growth. Systems-level integration of signaling circuitry is likely to coordinate other regulatory networks that control complex behaviors