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Metabolic coessentiality mapping identifies C12orf49 as a regulator of SREBP processing and cholesterol metabolism

Bayraktar, Erol C., La, Konnor, Karpman, Kara, Unlu, Gokhan, Ozerdem, Ceren, Ritter, Dylan J., Alwaseem, Hanan, Molina, Henrik, Hoffmann, Hans-Heinrich, Millner, Alec, Atilla-Gokcumen, G. Ekin, Gamazon, Eric R., Rushing, Amy R., Knapik, Ela W., Basu, Sumanta, Birsoy, Kıvanç·2020·Nature Metabolism

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  1. Wang, T. et al. Gene essentiality profiling reveals gene networks and synthetic lethal interactions with oncogenic Ras. Cell 168, 890–903 e815 (2017). · DOI · Paper page
  2. Pan, J. et al. Interrogation of mammalian protein complex structure, function, and membership using genome-scale fitness screens. Cell Syst. 6, 555–568.e7 (2018). · DOI
  3. Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y. & Morishima, K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 45, D353–D361 (2017). · DOI · Paper page
  4. Rozman, J. et al. Identification of genetic elements in metabolism by high-throughput mouse phenotyping. Nat. Commun. 9, 288 (2018). · DOI
  5. Schnoes, A. M., Brown, S. D., Dodevski, I. & Babbitt, P. C. Annotation error in public databases: misannotation of molecular function in enzyme superfamilies. PLoS Comput. Biol. 5, e1000605 (2009). · DOI
  6. Pandey, A. K., Lu, L., Wang, X., Homayouni, R. & Williams, R. W. Functionally enigmatic genes: a case study of the brain ignorome. PLoS One 9, e88889 (2014). · DOI · Paper page
  7. Hadadi, N., MohammadiPeyhani, H., Miskovic, L., Seijo, M. & Hatzimanikatis, V. Enzyme annotation for orphan and novel reactions using knowledge of substrate reactive sites. Proc. Natl Acad. Sci. USA 116, 7298–7307 (2019). · DOI
  8. Meyers, R. M. et al. Computational correction of copy number effect improves specificity of CRISPR–Cas9 essentiality screens in cancer cells. Nat. Genet. 49, 1779–1784 (2017). · DOI · Paper page
  9. Tsherniak, A. et al. Defining a cancer dependency map. Cell 170, 564–576.e16 (2017). · DOI · Paper page
  10. Kim, E et al. A network of human functional gene interactions from knockout fitness screens in cancer cells. Life Sci. Alliance 2, e201800278 (2019). · DOI
  11. Krumsiek, J., Suhre, K., Illig, T., Adamski, J. & Theis, F. J. Gaussian graphical modeling reconstructs pathway reactions from high-throughput metabolomics data. BMC Syst. Biol. 5, 21 (2011). · DOI
  12. Basu, S. et al. Sparse network modeling and metscape-based visualization methods for the analysis of large-scale metabolomics data. Bioinformatics 33, 1545–1553 (2017). · DOI
  13. Schumacher, M. M., Elsabrouty, R., Seemann, J., Jo, Y. & DeBose-Boyd, R. A. The prenyltransferase UBIAD1 is the target of geranylgeraniol in degradation of HMG CoA reductase. eLife 4, e05560 (2015). · DOI
  14. Zhu, X. G. et al. CHP1 regulates compartmentalized glycerolipid synthesis by activating GPAT4. Mol. Cell 74, 45–58.e7 (2019). · DOI
  15. Gallego-Garcia, A. et al. A bacterial light response reveals an orphan desaturase for human plasmalogen synthesis. Science 366, 128–132 (2019). · DOI
  16. Garcia-Bermudez, J. et al. Squalene accumulation in cholesterol auxotrophic lymphomas prevents oxidative cell death. Nature 567, 118–122 (2019). · DOI
  17. Horton, J. D., Goldstein, J. L. & Brown, M. S. SREBPs: activators of the complete program of cholesterol and fatty acid synthesis in the liver. J. Clin. Invest. 109, 1125–1131 (2002). · DOI · Paper page
  18. Wang, X., Sato, R., Brown, M. S., Hua, X. & Goldstein, J. L. SREBP-1, a membrane-bound transcription factor released by sterol-regulated proteolysis. Cell 77, 53–62 (1994). · DOI
  19. Brown, M. S. & Goldstein, J. L. The SREBP pathway: regulation of cholesterol metabolism by proteolysis of a membrane-bound transcription factor. Cell 89, 331–340 (1997). · DOI · Paper page
  20. Sakai, J. et al. Sterol-regulated release of SREBP-2 from cell membranes requires two sequential cleavages, one within a transmembrane segment. Cell 85, 1037–1046 (1996). · DOI · Paper page
  21. Sakakura, Y. et al. Sterol regulatory element-binding proteins induce an entire pathway of cholesterol synthesis. Biochem. Biophys. Res. Commun. 286, 176–183 (2001). · DOI
  22. Matsuda, M. et al. SREBP cleavage-activating protein (SCAP) is required for increased lipid synthesis in liver induced by cholesterol deprivation and insulin elevation. Genes Dev. 15, 1206–1216 (2001). · DOI · Paper page
  23. Yang, J. et al. Decreased lipid synthesis in livers of mice with disrupted Site-1 protease gene. Proc. Natl Acad. Sci. USA 98, 13607–13612 (2001). · DOI · Paper page
  24. Hua, X., Nohturfft, A., Goldstein, J. L. & Brown, M. S. Sterol resistance in CHO cells traced to point mutation in SREBP cleavage-activating protein. Cell 87, 415–426 (1996). · DOI · Paper page
  25. Kleinfelter, L. M. et al. Haploid genetic screen reveals a profound and direct dependence on cholesterol for hantavirus membrane fusion. mBio 6, e00801 (2015). · DOI · Paper page
  26. Osuna-Ramos, J. F., Reyes-Ruiz, J. M. & Del Ángel, R. M. The role of host cholesterol during Flavivirus infection. Front. Cell Infect. Microbiol. 8, 388 (2018). · DOI
  27. Pombo, J. P. & Sanyal, S. Perturbation of intracellular cholesterol and fatty acid homeostasis during Flavivirus infections. Front. Immunol. 9, 1276 (2018). · DOI
  28. Ericsson, J., Jackson, S. M. & Edwards, P. A. Synergistic binding of sterol regulatory element-binding protein and NF-Y to the farnesyl diphosphate synthase promoter is critical for sterol-regulated expression of the gene. J. Biol. Chem. 271, 24359–24364 (1996). · DOI
  29. Vallett, S. M., Sanchez, H. B., Rosenfeld, J. M. & Osborne, T. F. A direct role for sterol regulatory element binding protein in activation of 3-hydroxy-3-methylglutaryl coenzyme A reductase gene. J. Biol. Chem. 271, 12247–12253 (1996). · DOI
  30. Guan, G., Dai, P. H., Osborne, T. F., Kim, J. B. & Shechter, I. Multiple sequence elements are involved in the transcriptional regulation of the human squalene synthase gene. J. Biol. Chem. 272, 10295–10302 (1997). · DOI
  31. Edwards, P. A., Tabor, D., Kast, H. R. & Venkateswaran, A. Regulation of gene expression by SREBP and SCAP. Biochim. Biophys. Acta 1529, 103–113 (2000). · DOI
  32. DeBose-Boyd, R. A. et al. Transport-dependent proteolysis of SREBP: relocation of site-1 protease from Golgi to ER obviates the need for SREBP transport to Golgi. Cell 99, 703–712 (1999). · DOI · Paper page
  33. Lippincott-Schwartz, J., Yuan, L. C., Bonifacino, J. S. & Klausner, R. D. Rapid redistribution of Golgi proteins into the ER in cells treated with brefeldin A: evidence for membrane cycling from Golgi to ER. Cell 56, 801–813 (1989). · DOI
  34. Espenshade, P. J., Cheng, D., Goldstein, J. L. & Brown, M. S. Autocatalytic processing of site-1 protease removes propeptide and permits cleavage of sterol regulatory element-binding proteins. J. Biol. Chem. 274, 22795–22804 (1999). · DOI · Paper page
  35. Cheng, D. et al. Secreted site-1 protease cleaves peptides corresponding to luminal loop of sterol regulatory element-binding proteins. J. Biol. Chem. 274, 22805–22812 (1999). · DOI
  36. Velho, R. V. et al. Site-1 protease and lysosomal homeostasis. Biochim. Biophys. Acta Mol. Cell Res. 1864, 2162–2168 (2017). · DOI
  37. Asada, R., Kanemoto, S., Kondo, S., Saito, A. & Imaizumi, K. The signalling from endoplasmic reticulum-resident bZIP transcription factors involved in diverse cellular physiology. J. Biochem. 149, 507–518 (2011). · DOI
  38. Shao, W. & Espenshade, P. J. Sterol regulatory element-binding protein (SREBP) cleavage regulates Golgi-to-endoplasmic reticulum recycling of SREBP cleavage-activating protein (SCAP). J. Biol. Chem. 289, 7547–7557 (2014). · DOI · Paper page
  39. Passeri, M. J., Cinaroglu, A., Gao, C. & Sadler, K. C. Hepatic steatosis in response to acute alcohol exposure in zebrafish requires sterol regulatory element binding protein activation. Hepatology 49, 443–452 (2009). · DOI
  40. Unlu, G. et al. GRIK5 genetically regulated expression associated with eye and vascular phenomes: discovery through iteration among biobanks, electronic health records, and zebrafish. Am. J. Hum. Genet. 104, 503–519 (2019). · DOI
  41. Roden, D. M. et al. Development of a large-scale de-identified DNA biobank to enable personalized medicine. Clin. Pharmacol. Ther. 84, 362–369 (2008). · DOI
  42. Gamazon, E. R. et al. A gene-based association method for mapping traits using reference transcriptome data. Nat. Genet. 47, 1091–1098 (2015). · DOI
  43. Mazumder, R. & Hastie, T. Exact covariance thresholding into connected components for large-scale graphical lasso. J. Mach. Learn. Res. 13, 781–794 (2012).
  44. Weber, R. A. et al. Maintaining iron homeostasis Is the key role of lysosomal acidity for cell proliferation. Mol. Cell 77, 645–655.e7 (2020). · DOI · Paper page
  45. Jankova, J.& van de Geer, S. Confidence intervals for high-dimensional inverse covariance estimation. Electron J. Statist. 9, 1205–1229 (2015). · DOI
  46. Cullot, G. et al. CRISPR–Cas9 genome editing induces megabase-scale chromosomal truncations. Nat. Commun. 10, 1136 (2019). · DOI · Paper page
  47. Harsha, H. C. et al. Activated epidermal growth factor receptor as a novel target in pancreatic cancer therapy. J Proteome Res. 7, 4651–4658 (2008). · DOI
  48. Schilling, B. et al. Platform-independent and label-free quantitation of proteomic data using MS1 extracted ion chromatograms in skyline: application to protein acetylation and phosphorylation. Mol. Cell Proteomics 11, 202–214 (2012). · DOI
  49. Rappsilber, J., Mann, M. & Ishihama, Y. Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips. Nat. Protoc. 2, 1896–1906 (2007). · DOI · Paper page
  50. Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372 (2008). · DOI · Paper page
  51. Tyanova, S. et al. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 13, 731–740 (2016). · DOI · Paper page
  52. Perez-Riverol, Y. et al. The PRIDE database and related tools and resources in 2019: improving support for quantification data. Nucleic Acids Res. 47, D442–D450 (2019). · DOI
  53. Montague, T. G., Cruz, J. M., Gagnon, J. A., Church, G. M. & Valen, E. CHOPCHOP: a CRISPR/Cas9 and TALEN web tool for genome editing. Nucleic Acids Res. 42, W401–W407 (2014). · DOI
  54. Varshney, G. K et al. High-throughput gene targeting and phenotyping in zebrafish using CRISPR/Cas9. Genome Res. 25, 1030–1042 (2015). · DOI
  55. Yin, L. et al. Multiplex conditional mutagenesis using transgenic expression of Cas9 and sgRNAs. Genetics 200, 431–441 (2015). · DOI
  56. Levic, D. S. et al. Animal model of Sar1b deficiency presents lipid absorption deficits similar to Anderson disease. J. Mol. Med. 93, 165–176 (2015). · DOI
  57. Unlu, G. et al. Phenome-based approach identifies RIC1-linked Mendelian syndrome through zebrafish models, biobank associations and clinical studies. Nat. Med. 26, 98–109 (2020). · DOI
  58. Denny, J. C. et al. Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data. Nat. Biotechnol. 31, 1102–1110 (2013). · DOI
  59. The GTEx Consortium The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348, 648–660 (2015). · DOI · Paper page
  60. Storey, J. D. & Tibshirani, R. Statistical significance for genomewide studies. Proc. Natl Acad. Sci. USA 100, 9440–9445 (2003). · DOI · Paper page
  61. Schaffter, T., Marbach, D. & Floreano, D. GeneNetWeaver: in silico benchmark generation and performance profiling of network inference methods. Bioinformatics 27, 2263–2270 (2011). · DOI
  62. Shi, X., van Mierlo, J. T., French, A. & Elliott, R. M. Visualizing the replication cycle of Bunyamwera orthobunyavirus expressing fluorescent protein-tagged Gc glycoprotein. J. Virol. 84, 8460–8469 (2010). · DOI
  63. del Solar, V. et al. Differential regulation of specific sphingolipids in colon cancer cells during staurosporine-induced apoptosis. Chem. Biol. 22, 1662–1670 (2015). · DOI

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Metadata

Authors
Bayraktar, E. C., La, K., Karpman, K., Unlu, G., Ozerdem, C., Ritter, D. J., Alwaseem, H., Molina, H., Hoffmann, H.-H., Millner, A., Atilla-Gokcumen, G. E., Gamazon, E. R., Rushing, A. R., Knapik, E. W., Basu, S., & Birsoy, K.
Venue
Nature Metabolism
Published
2020-06-01
Volume
2
Issue
6
Pages
487-498
ISSN
2522-5812
Cited by
60
References
5
Language
en

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