Delayed Correlation of mRNA and Protein Expression in Rapamycin-treated Cells and a Role for Ggc1 in Cellular Sensitivity to Rapamycin*

To identify new molecular targets of rapamycin, an anticancer and immunosuppressive drug, we analyzed temporal changes in yeast over 6 h in response to rapamycin at the transcriptome and proteome levels and integrated the expression patterns with functional profiling. We show that the integration of transcriptomics, proteomics, and functional data sets provides novel insights into the molecular mechanisms of rapamycin action. We first observed a temporal delay in the correlation of mRNA and protein expression where mRNA expression at 1 and 2 h correlated best with protein expression changes after 6 h of rapamycin treatment. This was especially the case for the inhibition of ribosome biogenesis and induction of heat shock and autophagy essential to promote the cellular sensitivity to rapamycin. However, increased levels of vacuolar protease could enhance resistance to rapamycin. Of the 85 proteins identified as statistically significantly changing in abundance, most of the proteins that decreased in abundance were correlated with a decrease in mRNA expression. However, of the 56 proteins increasing in abundance, 26 were not correlated with an increase in mRNA expression. These protein changes were correlated with unchanged or down-regulated mRNA expression. These proteins, involved in mitochondrial genome maintenance, endocytosis, or drug export, represent new candidates effecting rapamycin action whose expression might be post-transcriptionally or post-translationally regulated. We identified GGC1, a mitochondrial GTP/GDP carrier, as a new component of the rapamycin/target of rapamycin (TOR) signaling pathway. We determined that the protein product of GGC1 was stabilized in the presence of rapamycin, and the deletion of the GGC1 enhanced growth fitness in the presence of rapamycin. A dynamic mRNA expression analysis of Δggc1 and wild-type cells treated with rapamycin revealed a key role for Ggc1p in the regulation of ribosome biogenesis and cell cycle progression under TOR control.

[1]  K. Inoki,et al.  Signaling by Target of Rapamycin Proteins in Cell Growth Control , 2005, Microbiology and Molecular Biology Reviews.

[2]  F. Palmieri,et al.  Identification of the Mitochondrial GTP/GDP Transporter in Saccharomyces cerevisiae* , 2004, Journal of Biological Chemistry.

[3]  D. A. Foster,et al.  Phospholipase D confers rapamycin resistance in human breast cancer cells , 2003, Oncogene.

[4]  J. Yates,et al.  Large-scale analysis of the yeast proteome by multidimensional protein identification technology , 2001, Nature Biotechnology.

[5]  Y. Benjamini,et al.  Controlling the false discovery rate in behavior genetics research , 2001, Behavioural Brain Research.

[6]  Steven P Gygi,et al.  Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry , 2007, Nature Methods.

[7]  E. Winzeler,et al.  Protein pathway and complex clustering of correlated mRNA and protein expression analyses in Saccharomyces cerevisiae , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[8]  J. Yates,et al.  DTASelect and Contrast: tools for assembling and comparing protein identifications from shotgun proteomics. , 2002, Journal of proteome research.

[9]  Steven P Gygi,et al.  Comparative evaluation of mass spectrometry platforms used in large-scale proteomics investigations , 2005, Nature Methods.

[10]  A. Gingras,et al.  Rapamycin blocks the phosphorylation of 4E‐BP1 and inhibits cap‐dependent initiation of translation. , 1996, The EMBO journal.

[11]  D. Pain,et al.  GTP in the mitochondrial matrix plays a crucial role in organellar iron homoeostasis. , 2006, The Biochemical journal.

[12]  G. Kroemer,et al.  Current development of mTOR inhibitors as anticancer agents , 2006, Nature Reviews Drug Discovery.

[13]  Rafael A Irizarry,et al.  Exploration, normalization, and summaries of high density oligonucleotide array probe level data. , 2003, Biostatistics.

[14]  F. Cohen,et al.  Expression profiling of the schizont and trophozoite stages of Plasmodium falciparum with a long-oligonucleotide microarray , 2003, Genome Biology.

[15]  Joaquín Dopazo,et al.  BABELOMICS: a systems biology perspective in the functional annotation of genome-scale experiments , 2006, Nucleic Acids Res..

[16]  V. Thorsson,et al.  Integrated Genomic and Proteomic Analyses of Gene Expression in Mammalian Cells*S , 2004, Molecular & Cellular Proteomics.

[17]  S. Sehgal,et al.  Rapamycin (AY-22,989), a new antifungal antibiotic. II. Fermentation, isolation and characterization. , 1975, The Journal of antibiotics.

[18]  X. Roucou,et al.  Insights into ATP synthase assembly and function through the molecular genetic manipulation of subunits of the yeast mitochondrial enzyme complex. , 2000, Biochimica et biophysica acta.

[19]  T. Griffin,et al.  Hsf1 Activation Inhibits Rapamycin Resistance and TOR Signaling in Yeast Revealed by Combined Proteomic and Genetic Analysis , 2008, PloS one.

[20]  A I Saeed,et al.  TM4: a free, open-source system for microarray data management and analysis. , 2003, BioTechniques.

[21]  M. Washburn,et al.  Quantitative proteomic analysis of distinct mammalian Mediator complexes using normalized spectral abundance factors , 2006, Proceedings of the National Academy of Sciences.

[22]  Timothy J. Mitchison,et al.  Comparison of three directly coupled HPLC MS/MS strategies for identification of proteins from complex mixtures: single-dimension LC-MS/MS, 2-phase MudPIT, and 3-phase MudPIT , 2002 .

[23]  Michael K. Coleman,et al.  Analyzing chromatin remodeling complexes using shotgun proteomics and normalized spectral abundance factors. , 2006, Methods.

[24]  T. Powers,et al.  Regulation of ribosome biogenesis by the rapamycin-sensitive TOR-signaling pathway in Saccharomyces cerevisiae. , 1999, Molecular biology of the cell.

[25]  I. Stansfield,et al.  An MBoC Favorite: TOR controls translation initiation and early G1 progression in yeast , 2012, Molecular biology of the cell.

[26]  John D. Venable,et al.  MS1, MS2, and SQT-three unified, compact, and easily parsed file formats for the storage of shotgun proteomic spectra and identifications. , 2004, Rapid communications in mass spectrometry : RCM.

[27]  Russell G. Jones,et al.  AMP-activated protein kinase induces a p53-dependent metabolic checkpoint. , 2005, Molecular cell.

[28]  J. Heitman,et al.  The TOR signaling cascade regulates gene expression in response to nutrients. , 1999, Genes & development.

[29]  Utpal Banerjee,et al.  Distinct mitochondrial retrograde signals control the G1-S cell cycle checkpoint , 2008, Nature Genetics.

[30]  Andrea Splendiani,et al.  A power law global error model for the identification of differentially expressed genes in microarray data , 2004, BMC Bioinformatics.

[31]  Ross Ihaka,et al.  Gentleman R: R: A language for data analysis and graphics , 1996 .

[32]  Norman Pavelka,et al.  Statistical Similarities between Transcriptomics and Quantitative Shotgun Proteomics Data *S , 2008, Molecular & Cellular Proteomics.

[33]  Kathleen A. Hinchman,et al.  Progression , 1896, Journal of Adolescent & Adult Literacy.

[34]  E. O’Shea,et al.  Quantification of protein half-lives in the budding yeast proteome , 2006, Proceedings of the National Academy of Sciences.

[35]  M. Hidalgo,et al.  The rapamycin-sensitive signal transduction pathway as a target for cancer therapy , 2000, Oncogene.

[36]  Gordon K Smyth,et al.  Statistical Applications in Genetics and Molecular Biology Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments , 2011 .

[37]  Michael K. Coleman,et al.  Statistical analysis of membrane proteome expression changes in Saccharomyces cerevisiae. , 2006, Journal of proteome research.

[38]  J. Boeke,et al.  Designer deletion strains derived from Saccharomyces cerevisiae S288C: A useful set of strains and plasmids for PCR‐mediated gene disruption and other applications , 1998, Yeast.

[39]  J. Yates,et al.  An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database , 1994, Journal of the American Society for Mass Spectrometry.

[40]  Andrew Emili,et al.  Integrating gene and protein expression data: pattern analysis and profile mining. , 2005, Methods.

[41]  T. A. Brown,et al.  A rapid and simple method for preparation of RNA from Saccharomyces cerevisiae. , 1990, Nucleic acids research.

[42]  Takeshi Noda,et al.  Tor, a Phosphatidylinositol Kinase Homologue, Controls Autophagy in Yeast* , 1998, The Journal of Biological Chemistry.

[43]  T. Finkel,et al.  Coordination of mitochondrial bioenergetics with G1 phase cell cycle progression , 2008, Cell cycle.

[44]  B. Séraphin,et al.  The tandem affinity purification (TAP) method: a general procedure of protein complex purification. , 2001, Methods.

[45]  Tania Nolan,et al.  Quantification of mRNA using real-time RT-PCR , 2006, Nature Protocols.

[46]  L. Hood,et al.  Complementary Profiling of Gene Expression at the Transcriptome and Proteome Levels in Saccharomyces cerevisiae*S , 2002, Molecular & Cellular Proteomics.

[47]  John D. Venable,et al.  Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra , 2004, Nature Methods.

[48]  B. Cox,et al.  Effect of cell cycle position on thermotolerance in Saccharomyces cerevisiae , 1987, Journal of bacteriology.

[49]  S. Sehgal,et al.  Rapamycin (AY-22,989), a new antifungal antibiotic. I. Taxonomy of the producing streptomycete and isolation of the active principle. , 1975, The Journal of antibiotics.

[50]  S. Schreiber,et al.  Rapamycin-modulated transcription defines the subset of nutrient-sensitive signaling pathways directly controlled by the Tor proteins. , 1999, Proceedings of the National Academy of Sciences of the United States of America.