Dataset Information

Systematic Screen for Drosophila Transcriptional Regulators Phosphorylated in Response to Insulin/mTOR Pathway.

ABSTRACT: Insulin/insulin-like growth factor signaling (IIS) is a conserved mechanism to regulate animal physiology in response to nutrition. IIS activity controls gene expression, but only a subset of transcriptional regulators (TRs) targeted by the IIS pathway is currently known. Here we report the results of an unbiased screen for Drosophila TRs phosphorylated in an IIS-dependent manner. To conduct the screen, we built a library of 857 V5/Strep-tagged TRs under the control of Copper-inducible metallothionein promoter (pMt). The insulin-induced phosphorylation changes were detected by using Phos-tag SDS-PAGE and Western blotting. Eight proteins were found to display increased phosphorylation after acute insulin treatment. In each case, the insulin-induced phosphorylation was abrogated by mTORC1 inhibitor rapamycin. The hits included two components of the NURF complex (NURF38 and NURF55), bHLHZip transcription factor Max, as well as the Drosophila ortholog of human proliferation-associated 2G4 (dPA2G4). Subsequent experiments revealed that the expression of the dPA2G4 gene was promoted by the mTOR pathway, likely through transcription factor Myc. Furthermore, NURF38 was found to be necessary for growth in larvae, consistent with the role of IIS/mTOR pathway in growth control.

SUBMITTER: Liu Y

PROVIDER: S-EPMC7407460 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Publications

Systematic Screen for <i>Drosophila</i> Transcriptional Regulators Phosphorylated in Response to Insulin/mTOR Pathway.

Liu Ying Y Mattila Jaakko J Hietakangas Ville V

G3 (Bethesda, Md.) 20200805 8

Insulin/insulin-like growth factor signaling (IIS) is a conserved mechanism to regulate animal physiology in response to nutrition. IIS activity controls gene expression, but only a subset of transcriptional regulators (TRs) targeted by the IIS pathway is currently known. Here we report the results of an unbiased screen for <i>Drosophila</i> TRs phosphorylated in an IIS-dependent manner. To conduct the screen, we built a library of 857 V5/Strep-tagged TRs under the control of Copper-inducible me ...[more]

PMID: 32554565

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Project description:Large-scale RNAi-based screens are playing a critical role in defining sets of genes that regulate specific cellular processes. Numerous screens have been completed and in some cases more than one screen has examined the same cellular process, enabling a direct comparison of the genes identified in separate screens. Surprisingly, the overlap observed between the results of similar screens is low, suggesting that RNAi screens have relatively high levels of false positives, false negatives, or both.We re-examined genes that were identified in two previous RNAi-based cell cycle screens to identify potential false positives and false negatives. We were able to confirm many of the originally observed phenotypes and to reveal many likely false positives. To identify potential false negatives from the previous screens, we used protein interaction networks to select genes for re-screening. We demonstrate cell cycle phenotypes for a significant number of these genes and show that the protein interaction network is an efficient predictor of new cell cycle regulators. Combining our results with the results of the previous screens identified a group of validated, high-confidence cell cycle/cell survival regulators. Examination of the subset of genes from this group that regulate the G1/S cell cycle transition revealed the presence of multiple members of three structurally related protein complexes: the eukaryotic translation initiation factor 3 (eIF3) complex, the COP9 signalosome, and the proteasome lid. Using a combinatorial RNAi approach, we show that while all three of these complexes are required for Cdk2/Cyclin E activity, the eIF3 complex is specifically required for some other step that limits the G1/S cell cycle transition.Our results show that false positives and false negatives each play a significant role in the lack of overlap that is observed between similar large-scale RNAi-based screens. Our results also show that protein network data can be used to minimize false negatives and false positives and to more efficiently identify comprehensive sets of regulators for a process. Finally, our data provides a high confidence set of genes that are likely to play key roles in regulating the cell cycle or cell survival.

Dataset Information

Systematic Screen for Drosophila Transcriptional Regulators Phosphorylated in Response to Insulin/mTOR Pathway.

Publications

Systematic Screen for <i>Drosophila</i> Transcriptional Regulators Phosphorylated in Response to Insulin/mTOR Pathway.

Similar Datasets

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