16 research outputs found
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
The accessory gas vesicle protein GvpM of haloarchaea and its interaction partners during gas vesicle formation
Bioengineering radioresistance by overproduction of RPA, a mammalian-type single-stranded DNA-binding protein, in a halophilic archaeon
Drug–Drug Interaction Potential of Marketed Oncology Drugs: In Vitro Assessment of Time-Dependent Cytochrome P450 Inhibition, Reactive Metabolite Formation and Drug–Drug Interaction Prediction
Purpose: To evaluate 26 marketed oncology drugs for time-dependent inhibition (TDI) of cytochrome P450 (CYP) enzymes. Evaluate TDI-positive drugs for potential to generate reactive intermediates. Assess clinical drug-drug interaction (DDI) risk using static mechanistic models. Methods: Human liver microsomes and CYP-specific probes were used to assess TDI in a dilution shift assay followed by generation of K I and k inact. Reactive metabolite trapping studies were performed with stable label probes. Static mechanistic model was used to predict DDI risk using a 1.25-fold AUC increase as a cut-off for positive DDI. Results: Negative TDI across CYPs was observed for 13/26 drugs; the rest were time-dependent inhibitors of, predominantly, CYP3A. The k inact/K I ratios for 11 kinase inhibitors ranged from 0.7 to 42.2 ml/min/μmol. Stable label trapping agent-drug conjugates were observed for ten kinase inhibitors. DDI predictions gave no false negatives, one true negative, four false positives and three true positives. The magnitude of DDI was overestimated irrespective of the inhibitor concentration selected. Conclusions: 13/26 oncology drugs investigated showed TDI potential towards CYP3A, formation of reactive metabolites was also observed. An industry standard static mechanistic model gave no false negative predictions but did not capture the modest clinical DDI potential of kinase inhibitors. © 2012 Springer Science+Business Media, LLC