The RNA-binding proteomes from yeast to man harbour conserved enigmRBPs

Nature Communications

Volumn 6, Issue , 2015, Pages

  Beckmann, Benedikt M ^a,b   Horos, Rastislav ^a   Fischer, Bernd ^a,c   Castello, Alfredo ^a,d   Eichelbaum, Katrin ^a,e   Alleaume, Anne Marie ^a   Schwarzl, Thomas ^a   Curk, Tomaž ^a,f   Foehr, Sophia ^a   Huber, Wolfgang ^a   Krijgsveld, Jeroen ^a   Hentze, Matthias W ^a  

^a EUROPEAN MOLECULAR BIOLOGY LABORATORY   (Germany)

^b HUMBOLDT UNIVERSITY   (Germany)

^c GERMAN CANCER RESEARCH CENTER DKFZ   (Germany)

^d UNIVERSITY OF OXFORD   (United Kingdom)

^e MAX DELBRÜCK CENTER FOR MOLECULAR MEDICINE   (Germany)

^f UNIVERSITY OF LJUBLJANA   (Slovenia)

Author keywords

[No Author keywords available]

Indexed keywords

ADENOSINE TRIPHOSPHATE; ARGININE; BINDING PROTEIN; COLD SHOCK DOMAIN CONTAINING PROTEIN E1; COLD SHOCK PROTEIN; LYSINE; MESSENGER RNA; OXIDOREDUCTASE; POLYADENYLATED RNA; POLYPYRIMIDINE TRACT BINDING PROTEIN 1; PROTEOME; RNA BINDING PROTEIN; RNA METHYLTRANSFERASE; TESTOSTERONE 17BETA DEHYDROGENASE; TESTOSTERONE 17BETA DEHYDROGENASE 10; TRANSFERASE; TRIPEPTIDE; UNCLASSIFIED DRUG; SACCHAROMYCES CEREVISIAE PROTEIN;

CELLS AND CELL COMPONENTS; DATA SET; ENZYME ACTIVITY; GENE EXPRESSION; METABOLISM; PROTEIN; RNA; YEAST;

ARTICLE; CARBON METABOLISM; CONTROLLED STUDY; CYTOLYSIS; EMBRYO; ENZYME ACTIVITY; ENZYME BINDING; FEMALE; FUNGAL STRAIN; GENE CONTROL; GLYCOLYSIS; HEK293 CELL LINE; HELA CELL LINE; HUMAN; HUMAN CELL; IN VIVO CULTURE; LIVER CELL; NONHUMAN; ORTHOLOGY; PROTEIN ANALYSIS; PROTEIN CROSS LINKING; PROTEIN EXPRESSION; PROTEIN FOLDING; PROTEIN FUNCTION; PROTEIN METABOLISM; PROTEIN PROTEIN INTERACTION; PROTEIN TARGETING; RNA BINDING; SACCHAROMYCES CEREVISIAE; SIGNAL TRANSDUCTION; CHEMISTRY; CONSERVED SEQUENCE; GENETICS; METABOLISM; MOLECULAR EVOLUTION; PROTEIN MOTIF; TUMOR CELL LINE;

EUKARYOTA; SACCHAROMYCES CEREVISIAE;

AMINO ACID MOTIFS; CELL LINE, TUMOR; CONSERVED SEQUENCE; EVOLUTION, MOLECULAR; HUMANS; PROTEOME; RNA-BINDING PROTEINS; SACCHAROMYCES CEREVISIAE; SACCHAROMYCES CEREVISIAE PROTEINS;

EID: 84949310063     PISSN: None     EISSN: 20411723     Source Type: Journal    
DOI: 10.1038/ncomms10127     Document Type: Article

References (40)

1. Gerstberger, S., Hafner, M. & Tuschl, T. A census of human RNA-binding proteins. Nat. Rev. Genet. 15, 829-845 (2014).
2. Castello, A. et al. Insights into RNA biology from an atlas of mammalian mRNA-binding proteins. Cell 149, 1393-1406 (2012).
3. Baltz, A. G. et al. The mRNA-bound proteome and its global occupancy profile on protein-coding transcripts. Mol. Cell 46, 674-690 (2012).
4. Cech, T. R. & Steitz, J. A. The noncoding RNA revolution-trashing old rules to forge new ones. Cell 157, 77-94 (2014).
5. Hentze, M. W. & Preiss, T. The REM phase of gene regulation. Trends. Biochem. Sci. 35, 423-426 (2010).
6. Kwon, S. C. et al. The RNA-binding protein repertoire of embryonic stem cells. Nat. Struct. Mol. Biol. 20, 1122-1130 (2013).
7. Castello, A. et al. System-wide identification of RNA-binding proteins by interactome capture. Nat. Protoc. 8, 491-500 (2013).
8. Creamer, T. J. et al. Transcriptome-wide binding sites for components of the Saccharomyces cerevisiae non-poly(A) termination pathway: Nrd1, Nab3, and Sen1. PLoS Genet. 7, e1002329 (2011).
9. Mitchell, S. F., Jain, S., She, M. & Parker, R. Global analysis of yeast mRNPs. Nat. Struct. Mol. Biol. 20, 127-133 (2013).
10. Picotti, P. et al. A complete mass-spectrometric map of the yeast proteome applied to quantitative trait analysis. Nature 494, 266-270 (2013).
11. Kato, M. et al. Cell-free formation of RNA granules: low complexity sequence domains form dynamic fibers within hydrogels. Cell 149, 753-767 (2012).
12. Jonas, S. & Izaurralde, E. The role of disordered protein regions in the assembly of decapping complexes and RNP granules. Genes Dev. 27, 2628-2641 (2013).
13. Han, T. W. et al. Cell-free formation of RNA granules: bound RNAs identify features and components of cellular assemblies. Cell 149, 768-779 (2012).
14. Wu, C. et al. Identification of novel nuclear targets of human thioredoxin 1. Mol. Cell. Proteomics 13, 3507-3518 (2014).
15. Hakimi, H. et al. Plasmodium knowlesi thioredoxin peroxidase 1 binds to nucleic acids and has RNA chaperone activity. Parasitol. Res. 113, 3957-3962 (2014).
16. Chang, C. H. et al. Posttranscriptional control of T cell effector function by aerobic glycolysis. Cell 153, 1239-1251 (2013).
17. Tsvetanova, N. G., Klass, D. M., Salzman, J. & Brown, P. O. Proteome-wide search reveals unexpected RNA-binding proteins in Saccharomyces cerevisiae. PloS ONE 5, e12671 (2010).
18. Hentze, M. W., Muckenthaler, M. U., Galy, B. & Camaschella, C. Two to tango: regulation of Mammalian iron metabolism. Cell 142, 24-38 (2010).
19. Konig, J. et al. iCLIP - transcriptome-wide mapping of protein-RNA interactions with individual nucleotide resolution. J. Vis. Exp. e2638, doi:10.3791/2638 (2011).
20. Rauschenberger, K. et al. A non-enzymatic function of 17beta-hydroxysteroid dehydrogenase type 10 is required for mitochondrial integrity and cell survival. EMBO Mol. Med. 2, 51-62 (2010).
21. Holzmann, J. et al. RNase P without RNA: identification and functional reconstitution of the human mitochondrial tRNA processing enzyme. Cell 135, 462-474 (2008).
22. Ojala, D., Montoya, J. & Attardi, G. tRNA punctuation model of RNA processing in human mitochondria. Nature 290, 470-474 (1981).
23. Vilardo, E. et al. A subcomplex of human mitochondrial RNase P is a bifunctional methyltransferase - extensive moonlighting in mitochondrial tRNA biogenesis. Nucleic Acids Res. 40, 11583-11593 (2012).
24. Rossmanith, W. Processing of human mitochondrial tRNA(Ser(AGY))GCU: a novel pathway in tRNA biosynthesis. J. Mol. Biol. 265, 365-371 (1997).
25. Vilardo, E. & Rossmanith, W. Molecular insights into HSD10 disease: impact of SDR5C1 mutations on the human mitochondrial RNase P complex. Nucleic Acids Res. 43, 5112-5119 (2015).
26. Mitchell, S. F. & Parker, R. Principles and properties of eukaryotic mRNPs. Mol. Cell 54, 547-558 (2014).
27. Hentze, M. W. & Preiss, T. Circular RNAs: splicing's enigma variations. EMBO J. 32, 923-925 (2013).
28. Lu, J. & Deutsch, C. Electrostatics in the ribosomal tunnel modulate chain elongation rates. J. Mol. Biol. 384, 73-86 (2008).
29. Charneski, C. A. & Hurst, L. D. Positively charged residues are the major determinants of ribosomal velocity. PLoS Biol. 11, e1001508 (2013).
30. Kim, Y. et al. PKR is activated by cellular dsRNAs during mitosis and acts as a mitotic regulator. Genes Dev. 28, 1310-1322 (2014).
31. Yu, M. & Levine, S. J. Toll-like receptor, RIG-I-like receptors and the NLRP3 inflammasome: key modulators of innate immune responses to double-stranded RNA viruses. Cytokine Growth Factor Rev. 22, 63-72 (2011).
32. Boersema, P. J., Raijmakers, R. & Lemeer, S. Mohammed S, Heck AJ. Multiplex peptide stable isotope dimethyl labeling for quantitative proteomics. Nat. Protoc. 4, 484-494 (2009).
33. 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).
34. 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).
35. Smyth, G. K. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat. Appl. Genet. Mol. Biol. 3, 1-25 (2004).
36. Dosztanyi, Z., Csizmok, V., Tompa, P. & Simon, I. IUPred: web server for the prediction of intrinsically unstructured regions of proteins based on estimated energy content. Bioinformatics 21, 3433-3434 (2005).
37. Ostlund, G. et al. InParanoid 7: new algorithms and tools for eukaryotic orthology analysis. Nucleic Acids Res. 38, D196-D203 (2010).
38. Huang, D. W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44-57 (2009).
39. Huang, D. W. et al. DAVID Bioinformatics Resources: expanded annotation database and novel algorithms to better extract biology from large gene lists. Nucleic Acids Res. 35, W169-W175 (2007).
40. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).