Current Science

Open Access Open Access  Restricted Access Subscription Access

BOP1– A Key Player of Ribosomal Biogenesis


Affiliations
1 Applied Biology Division, CSIR – Indian Institute of Chemical Technology, Uppal Road, Hyderabad 500 007, India
2 Department of Biology, University of Iowa, 129 E, Jefferson Street, Iowa City, 52242, United States
 

Ribosomal biogenesis involves coordination of protein complexes for translation, cell growth and differentiation. An analysis of ribosomal biogenesis factor ERB1/ BOP1 in evolution and cancer was carried out using comparative bioinformatics approaches focusing on protein domain identification, phylogenetic analysis, homology modelling, analyses of gene expression and interaction networks. We have identified WD40 domain as an essential co-occurring domain in all the BOP1 proteins predominantly in eukaryotes and also identified some key structural motifs in BOP1. A strong correlation of BOP1 has been observed in multiple signalling pathways, dysregulation of which leads to cancer. Using interaction networks and data mining, which are literature-derived, we have identified important interaction partners of PeBoW complex that co-express with BOP1 in signalling pathways. Analysis of BOP1 differential gene expression and interaction pathways reveals that BOP1 plays an important role in regulating p53 signalling and cellcycle networks, and provides a crosstalk with key cellular processes. Examination of cancer and tissue expression profiling points to the upregulation of BOP1 in a variety of cancers. Thus BOP1 can be considered as a potential cancer biomarker and therapeutic target.

Keywords

Cancer Biomarker, Molecular Phylogeny, Protein Complexes, Ribosomal Biogenesis, Therapeutic Target.
User
Notifications
Font Size

  • Thomas, G., An encore for ribosome biogenesis in the control of cell proliferation. Nature Cell Biol., 2000, 2, E71–E72.

  • Thomson, E., Ferreira-Cerca, S. and Hurt, E., Eukaryotic ribosome biogenesis at a glance. J. Cell Sci., 2013, 126, 4815–4821.

  • Huret, J. L. et al., Atlas of genetics and cytogenetics in oncology and haematology in 2013. Nucleic Acids Res., 2013, 41, D920– D924.

  • Killian, A. et al., Contribution of the bop1 gene, located on 8q24, to colorectal tumorigenesis. Genes, Chromosomes Cancer, 2006, 45, 874–881.

  • Strezoska, Z., Pestov, D. G. and Lau, L. F., BOP1 is a mouse WD40 repeat nucleolar protein involved in 28s and 5. 8s rRNA processing and 60S ribosome biogenesis. Mol. Cell. Biol., 2000, 20, 5516–5528.

  • Pestov, D. G., Grzeszkiewicz, T. M. and Lau, L. F., Isolation of growth suppressors from a cDNA expression library. Oncogene, 1998, 17, 3187–3197.

  • Lapik, Y. R., Fernandes, C. J., Lau, L. F. and Pestov, D. G., Physical and functional interaction between PES1 and BOP1 in mammalian ribosome biogenesis. Mol. Cell, 2004, 15, 17–29.

  • Pestov, D. G., Strezoska, Z. and Lau, L. F., Evidence of p53dependent cross-talk between ribosome biogenesis and the cell cycle: effects of nucleolar protein BOP1 on g(1)/s transition. Mol. Cell. Biol., 2001, 21, 4246–4255.

  • Akanni, W. A., Wilkinson, M., Creevey, C. J., Foster, P. G. and Pisani, D., Implementing and testing Bayesian and maximumlikelihood supertree methods in phylogenetics. R. Soc. Open Sci., 2015, 2, 140436.

  • Bininda-Emonds, O. R., Supertree construction in the genomic age. Methods Enzymol., 2005, 395, 745–757.

  • Uchiyama, I., Hierarchical clustering algorithm for comprehensive orthologous-domain classification in multiple genomes. Nucl. Acids Res., 2006, 34, 647–658.

  • Geer, L. Y., Domrachev, M., Lipman, D. J. and Bryant, S. H., CDART: protein homology by domain architecture. Genome Res., 2002, 12, 1619–1623.

  • Marchler-Bauer, A. et al., CDD/SPARCLE: functional classification of proteins via subfamily domain architectures. Nucleic Acids Res., 2017, 45, D200–D203.

  • Letunic, I., Doerks, T. and Bork, P., SMART 7: recent updates to the protein domain annotation resource. Nucleic Acids Res., 2012, 40, D302–D305.

  • Finn, R. D. et al., The PFAM protein families database: towards a more sustainable future. Nucleic Acids Res., 2016, 44, D279–D285.

  • Kumar, S., Stecher, G. and Tamura, K., MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol. Biol. Evol., 2016, 33, 1870–1874.

  • Katoh, K. and Standley, D. M., MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol., 2013, 30, 772–780.

  • Felsenstein, J., Evolutionary trees from DNA sequences: a maximum likelihood approach. J. Mol. Evol., 1981, 17, 368–376.

  • Szklarczyk, D. et al., String v10: protein–protein interaction networks, integrated over the tree of life. Nucleic Acids Res., 2015, 43, D447–D452.

  • Williams, K. E., Lemieux, G. A., Hassis, M. E., Olshen, A. B., Fisher, S. J. and Werb, Z., Quantitative proteomic analyses of mammary organoids reveals distinct signatures after exposure to environmental chemicals. Proc. Natl. Acad. Sci. USA, 2016, 113, E1343–E1351.

  • Qi, J. et al., New wnt/beta-catenin target genes promote experimental metastasis and migration of colorectal cancer cells through different signals. Gut, 2016, 65, 1690–1701.

  • Ahsan, S. and Drăghici, S., Identifying significantly impacted pathways and putative mechanisms with ipathwayguide. Curr. Proto. Bioinform., 2017, 57, 7.15.11–17.15.30.

  • Draghici, S. et al., A systems biology approach for pathway level analysis. Genome Res., 2007, 17, 1537–1545.

  • Fabregat, A. et al., The reactome pathway knowledgebase. Nucleic Acids Res., 2016, 44, D481–D487.

  • Bohler, A. et al., Reactome from a wikipathways perspective. PLOS Comput. Biol., 2016, 12, e1004941.

  • Slenter, D. N. et al., Wikipathways: A multifaceted pathway database bridging metabolomics to other omics research. Nucleic Acids Res., 2017, 46, D661–D667.

  • Herwig, R., Hardt, C., Lienhard, M. and Kamburov, A., Analyzing and interpreting genome data at the network level with consensuspathdb. Nature Protoc., 2016, 11, 1889–1907.

  • Chatr-Aryamontri, A. et al., The bioGRID interaction database: 2015 update. Nucleic Acids Res., 2015, 43, D470–D478.

  • Orchard, S. et al., The mintact project – intact as a common curation platform for 11 molecular interaction databases. Nucleic Acids Res., 2014, 42, D358–D363.

  • Paz, A. et al., SPIKE: a database of highly curated human signaling pathways. Nucleic Acids Res., 2011, 39, D793–D799.

  • Licata, L. et al., MINT, the molecular interaction database: 2012 update. Nucleic Acids Res., 2012, 40, D857–D861.

  • Peri, S. et al., Development of human protein reference database as an initial platform for approaching systems biology in humans. Genome Res., 2003, 13, 2363–2371.

  • Franz, M., Lopes, C. T., Huck, G., Dong, Y., Sumer, O. and Bader, G. D., Cytoscape. js: a graph theory library for visualisation and analysis. Bioinformatics, 2016, 32, 309–311.

  • Biasini, M. et al., SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. Nucleic Acids Res., 2014, 42, W252–W258.

  • Colovos, C. and Yeates, T. O., Verification of protein structures: patterns of nonbonded atomic interactions. Protein Sci., 1993, 2, 1511–1519.

  • Wang, W., Xia, M., Chen, J., Deng, F., Yuan, R., Zhang, X. and Shen, F., Data set for phylogenetic tree and RAMPAGE Ramachandran plot analysis of SODS in Gossypium raimondii and G. arboreum. Data Brief, 2016, 9, 345–348.

  • Crooks, G. E., Hon, G., Chandonia, J. M. and Brenner, S. E., WebLogo: a sequence logo generator. Genome Res., 2004, 14, 1188–1190.

  • Shin, G., Kang, T. W., Yang, S., Baek, S. J., Jeong, Y. S. and Kim, S. Y., GENT: gene expression database of normal and tumor tissues. Cancer Informat., 2011, 10, 149–157.

  • Hornbeck, P. V., Zhang, B., Murray, B., Kornhauser, J. M., Latham, V. and Skrzypek, E., PhosphoSitePlus, 2014: mutations, ptms and recalibrations. Nucleic Acids Res., 2015, 43, D512–D520.

  • Li, D. and Roberts, R., WD-repeat proteins: structure characteristics, biological function, and their involvement in human diseases. Cell. Mol. Life Sci., 2001, 58, 2085–2097.

  • Stirnimann, C. U., Petsalaki, E., Russell, R. B. and Muller, C. W., WD40 proteins propel cellular networks. Trends Biochem. Sci., 2010, 35, 565–574.

  • Gough, J., Convergent evolution of domain architectures (is rare). Bioinformatics, 2005, 21, 1464–1471.

  • Olsen, G. J. and Woese, C. R., Ribosomal RNA: a key to phylogeny. FASEB J., 1993, 7, 113–123.

  • Lecompte, O., Ripp, R., Thierry, J. C., Moras, D. and Poch, O., Comparative analysis of ribosomal proteins in complete genomes: an example of reductive evolution at the domain scale. Nucleic Acids Res., 2002, 30, 5382–5390.

  • Tamura, K. and Alexander, R. W., Peptide synthesis through evolution. Cell. Mol. Life Sci., 2004, 61, 1317–1330.

  • Schwikowski, B., Uetz, P. and Fields, S., A network of protein– protein interactions in yeast. Nature Biotechnol., 2000, 18, 1257– 1261.

  • Stuart, J. M., Segal, E., Koller, D. and Kim, S. K., A genecoexpression network for global discovery of conserved genetic modules. Science, 2003, 302, 249–255.

  • Sachs, A. B. and Davis, R. W., Translation initiation and ribosomal biogenesis: involvement of a putative rRNA helicase and RPL46. Science, 1990, 247, 1077–1079.

  • Zebarjadian, Y., King, T., Fournier, M. J., Clarke, L. and Carbon, J., Point mutations in yeast CBF5 can abolish in vivo pseudouridylation of rRNA. Mol. Cell. Biol., 1999, 19, 7461–7472.

  • Naryshkina, T., Bruning, A., Gadal, O. and Severinov, K., Role of second-largest RNA polymerase i subunit Zn-binding domain in enzyme assembly. Eukaryotic Cell, 2003, 2, 1046–1052.

  • Yang, Y. -T., Ting, Y. -H., Liang, K. -J. and Lo, K. -Y., The roles of puf6 and loc1 in 60S biogenesis are interdependent and both are required for efficient accommodation of rpl43. J. Biol. Chem., 2016, 291, 19312–19323.

  • Oeffinger, M., Dlakic, M. and Tollervey, D., A pre-ribosomeassociated heat-repeat protein is required for export of both ribosomal subunits. Genes Dev., 2004, 18, 196–209.

  • Milkereit, P. et al., Maturation and intranuclear transport of preribosomes requires NOC proteins. Cell, 2001, 105, 499–509.

  • Jensen, B. C., Wang, Q., Kifer, C. T. and Parsons, M., The NOG1 GTP-binding protein is required for biogenesis of the 60S ribosomal subunit. J. Biol. Chem., 2003, 278, 32204–32211.

  • Lebreton, A., Saveanu, C., Decourty, L., Jacquier, A. and Fromont-Racine, M., Nsa2 is an unstable, conserved factor required for the maturation of 27 SB Pre-rRNAs. J. Biol. Chem., 2006, 281, 27099–27108.

  • Dunbar, D. A., Dragon, F., Lee, S. J. and Baserga, S. J., A nucleolar protein related to ribosomal protein l7 is required for an early step in large ribosomal subunit biogenesis. Proc. Natl. Acad. Sci. USA, 2000, 97, 13027–13032.

  • Grimm, T. et al., Dominant-negative PES1 mutants inhibit ribosomal RNA processing and cell proliferation via incorporation into the PeBow-complex. Nucl. Acids Res., 2006, 34, 3030– 3043.

  • Holzel, M. et al., Mammalian wdr12 is a novel member of the PES1-BOP1 complex and is required for ribosome biogenesis and cell proliferation. J. Cell Biol., 2005, 170, 367–378.

  • Rohrmoser, M. et al., Interdependence of PES1, BOP1, and WDR12 controls nucleolar localization and assembly of the pebow complex required for maturation of the 60s ribosomal subunit. Mol. Cell. Biol., 2007, 27, 3682–3694.

  • Guerriero, G., Silvestrini, L., Obersriebnig, M., Hausman, J. F., Strauss, J. and Ezcurra, I., A wdr gene is a conserved member of a chitin synthase gene cluster and influences the cell wall in Aspergillus nidulans. Int. J. Mol. Sci., 2016, 17, 1031.

  • Schroder, W., Lambert, D. G., Ko, M. C. and Koch, T., Functional plasticity of the n/ofq-nop receptor system determines analgesic properties of nop receptor agonists. Br. J. Pharmacol., 2014, 171, 3777–3800.

  • Leal, M. F. et al., Identification of suitable reference genes for investigating gene expression in anterior cruciate ligament injury by using reverse transcription-quantitative pcr. PLOS ONE, 2015, 10, e0133323.

  • Mann, K. M., Ying, H., Juan, J., Jenkins, N. A. and Copeland, N. G., KRAS-related proteins in pancreatic cancer. Pharmacol. Therapeut., 2016.

  • Suzuki, Y., Orita, M., Shiraishi, M., Hayashi, K. and Sekiya, T., Detection of ras gene mutations in human lung cancers by singlestrand conformation polymorphism analysis of polymerase chain reaction products. Oncogene, 1990, 5, 1037–1043.

  • Chung, K. Y., Cheng, I. K., Ching, A. K., Chu, J. H., Lai, P. B. and Wong, N., Block of proliferation 1 (BOP1) plays an oncogenic role in hepatocellular carcinoma by promoting epithelial-tomesenchymal transition. Hepatology, 2011, 54, 307–318.

  • Wrzeszczynski, K. O. et al., Identification of tumor suppressors and oncogenes from genomic and epigenetic features in ovarian cancer. PLOS ONE, 2011, 6, e28503.

  • Sherry, S. T., Ward, M. H., Kholodov, M., Baker, J., Phan, L., Smigielski, E. M. and Sirotkin, K., dbsNP: the NCBI database of genetic variation. Nucleic Acids Res., 2001, 29, 308–311.

  • Amanchy, R., Periaswamy, B., Mathivanan, S., Reddy, R., Tattikota, S. G. and Pandey, A., A curated compendium of phosphorylation motifs. Nature Biotechnol., 2007, 25, 285–286.

  • Rechsteiner, M. and Rogers, S. W., Pest sequences and regulation by proteolysis. Trends Biochem. Sci., 1996, 21, 267–271.

  • Rechsteiner, M., Pest sequences are signals for rapid intracellular proteolysis. Sem. Cell Biol., 1990, 1, 433–440.

  • Chen, C. K., Chan, N. L. and Wang, A. H., The many blades of the beta-propeller proteins: conserved but versatile. Trends Biochem. Sci., 2011, 36, 553–561.

  • Strezoska, Z., Pestov, D. G. and Lau, L. F., Functional inactivation of the mouse nucleolar protein BOP1 inhibits multiple steps in pre-rRNA processing and blocks cell cycle progression. J. Biol. Chem., 2002, 277, 29617–29625.

  • Riley, T., Sontag, E., Chen, P. and Levine, A., Transcriptional control of human p53-regulated genes. Nature Rev. Mol. Cell Biol., 2008, 9, 402–412.


Abstract Views: 420

PDF Views: 129




  • BOP1– A Key Player of Ribosomal Biogenesis

Abstract Views: 420  |  PDF Views: 129

Authors

Nabajyoti Borah
Applied Biology Division, CSIR – Indian Institute of Chemical Technology, Uppal Road, Hyderabad 500 007, India
Krishna Madhav Nukala
Department of Biology, University of Iowa, 129 E, Jefferson Street, Iowa City, 52242, United States
Varahalarao Vadlapudi
Applied Biology Division, CSIR – Indian Institute of Chemical Technology, Uppal Road, Hyderabad 500 007, India
Satya Prakash Gubbala
Applied Biology Division, CSIR – Indian Institute of Chemical Technology, Uppal Road, Hyderabad 500 007, India
Ramars Amanchy
Applied Biology Division, CSIR – Indian Institute of Chemical Technology, Uppal Road, Hyderabad 500 007, India

Abstract


Ribosomal biogenesis involves coordination of protein complexes for translation, cell growth and differentiation. An analysis of ribosomal biogenesis factor ERB1/ BOP1 in evolution and cancer was carried out using comparative bioinformatics approaches focusing on protein domain identification, phylogenetic analysis, homology modelling, analyses of gene expression and interaction networks. We have identified WD40 domain as an essential co-occurring domain in all the BOP1 proteins predominantly in eukaryotes and also identified some key structural motifs in BOP1. A strong correlation of BOP1 has been observed in multiple signalling pathways, dysregulation of which leads to cancer. Using interaction networks and data mining, which are literature-derived, we have identified important interaction partners of PeBoW complex that co-express with BOP1 in signalling pathways. Analysis of BOP1 differential gene expression and interaction pathways reveals that BOP1 plays an important role in regulating p53 signalling and cellcycle networks, and provides a crosstalk with key cellular processes. Examination of cancer and tissue expression profiling points to the upregulation of BOP1 in a variety of cancers. Thus BOP1 can be considered as a potential cancer biomarker and therapeutic target.

Keywords


Cancer Biomarker, Molecular Phylogeny, Protein Complexes, Ribosomal Biogenesis, Therapeutic Target.

References





DOI: https://doi.org/10.18520/cs%2Fv117%2Fi3%2F422-433