| 1. |
- Dever, Thomas E, et al.
(författare)
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Modulation of tRNA(iMet), eIF-2, and eIF-2B expression shows that GCN4 translation is inversely coupled to the level of eIF-2.GTP.Met-tRNA(iMet) ternary complexes
- 1995
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Ingår i: Molecular and Cellular Biology. - : American Society for Microbiology. - 0270-7306 .- 1098-5549. ; 15:11, s. 6351-6363
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Tidskriftsartikel (refereegranskat)abstract
- To understand how phosphorylation of eukaryotic translation initiation factor (eIF)-2 alpha in Saccharomyces cerevisiae stimulates GCN4 mRNA translation while at the same time inhibiting general translation initiation, we examined the effects of altering the gene dosage of initiator tRNA(Met), eIF-2, and the guanine nucleotide exchange factor for eIF-2, eIF-2B. Overexpression of all three subunits of eIF-2 or all five subunits of eIF-2B suppressed the effects of eIF-2 alpha hyperphosphorylation on both GCN4-specific and general translation initiation. Consistent with eIF-2 functioning in translation as part of a ternary complex composed of eIF-2, GTP, and Met-tRNA(iMet), reduced gene dosage of initiator tRNA(Met) mimicked phosphorylation of eIF-2 alpha and stimulated GCN4 translation. In addition, overexpression of a combination of eIF-2 and tRNA(iMet) suppressed the growth-inhibitory effects of eIF-2 hyperphosphorylation more effectively than an increase in the level of either component of the ternary complex alone. These results provide in vivo evidence that phosphorylation of eIF-2 alpha reduces the activities of both eIF-2 and eIF-2B and that the eIF-2.GTP. Met-tRNA(iMet) ternary complex is the principal component limiting translation in cells when eIF-2 alpha is phosphorylated on serine 51. Analysis of eIF-2 alpha phosphorylation in the eIF-2-overexpressing strain also provides in vivo evidence that phosphorylated eIF-2 acts as a competitive inhibitor of eIF-2B rather than forming an excessively stable inactive complex. Finally, our results demonstrate that the concentration of eIF-2-GTP. Met-tRNA(iMet) ternary complexes is the cardinal parameter determining the site of reinitiation on GCN4 mRNA and support the idea that reinitiation at GCN4 is inversely related to the concentration of ternary complexes in the cell.
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| 2. |
- Moxley, J.F., et al.
(författare)
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Linking transcriptional regulation and high resolution metabolic fluxes in yeast modulated by the global regulator Gcn4p
- 2009
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 106:16, s. 6477-6482
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Tidskriftsartikel (refereegranskat)abstract
- Genome sequencing dramatically increased our ability to understand cellular response to perturbation. Integrating system-wide measurements such as gene expression with networks of protein protein interactions and transcription factor binding revealed critical insights into cellular behavior. However, the potential of systems biology approaches is limited by difficulties in integrating metabolic measurements across the functional levels of the cell despite their being most closely linked to cellular phenotype. To address this limitation, we developed a model-based approach to correlate mRNA and metabolic flux data that combines information from both interaction network models and flux determination models. We started by quantifying 5,764 mRNAs, 54 metabolites, and 83 experimental (13)C-based reaction fluxes in continuous cultures of yeast under stress in the absence or presence of global regulator Gcn4p. Although mRNA expression alone did not directly predict metabolic response, this correlation improved through incorporating a network-based model of amino acid biosynthesis (from r = 0.07 to 0.80 for mRNA-flux agreement). The model provides evidence of general biological principles: rewiring of metabolic flux (i.e., use of different reaction pathways) by transcriptional regulation and metabolite interaction density (i.e., level of pairwise metabolite-protein interactions) as a key biosynthetic control determinant. Furthermore, this model predicted flux rewiring in studies of follow-on transcriptional regulators that were experimentally validated with additional (13)C-based flux measurements. As a first step in linking metabolic control and genetic regulatory networks, this model underscores the importance of integrating diverse data types in large-scale cellular models. We anticipate that an integrated approach focusing on metabolic measurements will facilitate construction of more realistic models of cellular regulation for understanding diseases and constructing strains for industrial applications.
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