Voltar
Artigo Acesso aberto Revisado por pares
BIBTEX RIS

Proteomic Analysis of the Human Cyclin-dependent Kinase Family Reveals a Novel CDK5 Complex Involved in Cell Growth and Migration

2014; Elsevier BV; Volume: 13; Issue: 11 Linguagem: Inglês

10.1074/mcp.m113.036699

ISSN

1535-9484

Autores

Shuangbing Xu, Xu Li, Zihua Gong, Wenqi Wang, Yujing Li, Binoj C. Nair, Hai‐long Piao, Kunyu Yang, Gang Wu, Junjie Chen,

Tópico(s)

Cancer, Hypoxia, and Metabolism

Resumo

Cyclin-dependent kinases (CDKs) are the catalytic subunits of a family of mammalian heterodimeric serine/threonine kinases that play critical roles in the control of cell-cycle progression, transcription, and neuronal functions. However, the functions, substrates, and regulation of many CDKs are poorly understood. To systematically investigate these features of CDKs, we conducted a proteomic analysis of the CDK family and identified their associated protein complexes in two different cell lines using a modified SAINT (Significance Analysis of INTeractome) method. The mass spectrometry data were deposited to ProteomeXchange with identifier PXD000593 and DOI 10.6019/PXD000593. We identified 753 high-confidence candidate interaction proteins (HCIPs) in HEK293T cells and 352 HCIPs in MCF10A cells. We subsequently focused on a neuron-specific CDK, CDK5, and uncovered two novel CDK5-binding partners, KIAA0528 and fibroblast growth factor (acidic) intracellular binding protein (FIBP), in non-neuronal cells. We showed that these three proteins form a stable complex, with KIAA0528 and FIBP being required for the assembly and stability of the complex. Furthermore, CDK5-, KIAA0528-, or FIBP-depleted breast cancer cells displayed impaired proliferation and decreased migration, suggesting that this complex is required for cell growth and migration in non-neural cells. Our study uncovers new aspects of CDK functions, which provide direction for further investigation of these critical protein kinases. Cyclin-dependent kinases (CDKs) are the catalytic subunits of a family of mammalian heterodimeric serine/threonine kinases that play critical roles in the control of cell-cycle progression, transcription, and neuronal functions. However, the functions, substrates, and regulation of many CDKs are poorly understood. To systematically investigate these features of CDKs, we conducted a proteomic analysis of the CDK family and identified their associated protein complexes in two different cell lines using a modified SAINT (Significance Analysis of INTeractome) method. The mass spectrometry data were deposited to ProteomeXchange with identifier PXD000593 and DOI 10.6019/PXD000593. We identified 753 high-confidence candidate interaction proteins (HCIPs) in HEK293T cells and 352 HCIPs in MCF10A cells. We subsequently focused on a neuron-specific CDK, CDK5, and uncovered two novel CDK5-binding partners, KIAA0528 and fibroblast growth factor (acidic) intracellular binding protein (FIBP), in non-neuronal cells. We showed that these three proteins form a stable complex, with KIAA0528 and FIBP being required for the assembly and stability of the complex. Furthermore, CDK5-, KIAA0528-, or FIBP-depleted breast cancer cells displayed impaired proliferation and decreased migration, suggesting that this complex is required for cell growth and migration in non-neural cells. Our study uncovers new aspects of CDK functions, which provide direction for further investigation of these critical protein kinases. Cell division is a precisely regulated process that is mainly driven by two classes of molecules, cyclin-dependent kinases (CDKs) 1The abbreviations used are:CDKsCyclin-dependent kinasesSAINTSignificance Analysis of INTeactomeHCIPhigh-confidence candidate interacting proteinsPPIprotein-protein interactionshRNAshort-hairpin RNASFBS tag-Flag tag-SBPGOgene ontology. 1The abbreviations used are:CDKsCyclin-dependent kinasesSAINTSignificance Analysis of INTeactomeHCIPhigh-confidence candidate interacting proteinsPPIprotein-protein interactionshRNAshort-hairpin RNASFBS tag-Flag tag-SBPGOgene ontology. and their activating subunits, cyclins (1Morgan D.O. Cyclin-dependent kinases: engines, clocks, and microprocessors.Annu. Rev. Cell Dev. Biol. 1997; 13: 261-291Crossref PubMed Scopus (1797) Google Scholar, 2Malumbres M. Barbacid M. Mammalian cyclin-dependent kinases.Trends Biochem. Sci. 2005; 30: 630-641Abstract Full Text Full Text PDF PubMed Scopus (949) Google Scholar, 3Satyanarayana A. Kaldis P. Mammalian cell-cycle regulation: several Cdks, numerous cyclins and diverse compensatory mechanisms.Oncogene. 2009; 28: 2925-2939Crossref PubMed Scopus (556) Google Scholar). Cdks are the catalytic subunits of this large family of heterodimeric serine/threonine protein kinases whose best-characterized members are involved in controlling progression throughout the various cell cycle phases (2Malumbres M. Barbacid M. Mammalian cyclin-dependent kinases.Trends Biochem. Sci. 2005; 30: 630-641Abstract Full Text Full Text PDF PubMed Scopus (949) Google Scholar, 4Malumbres M. Barbacid M. Cell cycle, CDKs and cancer: a changing paradigm.Nat. Rev. Cancer. 2009; 9: 153-166Crossref PubMed Scopus (2643) Google Scholar, 5Johnson N. Shapiro G.I. Cyclin-dependent kinases (cdks) and the DNA damage response: rationale for cdk inhibitor-chemotherapy combinations as an anticancer strategy for solid tumors.Expert Opin. Ther. Targets. 2010; 14: 1199-1212Crossref PubMed Scopus (73) Google Scholar). According to the latest versions of human and mouse genomes, there are 20 genes encoding CDKs and five additional genes encoding a more distant group of proteins named CDK-like (CDKL1-CDKL5) kinases (2Malumbres M. Barbacid M. Mammalian cyclin-dependent kinases.Trends Biochem. Sci. 2005; 30: 630-641Abstract Full Text Full Text PDF PubMed Scopus (949) Google Scholar, 6Malumbres M. Harlow E. Hunt T. Hunter T. Lahti J.M. Manning G. Morgan D.O. Tsai L.H. Wolgemuth D.J. Cyclin-dependent kinases: a family portrait.Nat. Cell Biol. 2009; 11: 1275-1276Crossref PubMed Scopus (316) Google Scholar). The current CDK family consists of 11 classic CDKs (CDK1–11), two newly proposed family members (CDK12 and 13), and additional proteins whose names are based on the presence of a cyclin-binding element (PFTAIRE proteins, including CDK14 and CDK15; PCTAIRE proteins, including CDK16, CDK17, and CDK18) or on a sequence relationship with the original CDKs, such as CDC2-like kinase (CDK19) or cell cycle-related kinase (CDK20). Cyclin-dependent kinases Significance Analysis of INTeactome high-confidence candidate interacting proteins protein-protein interaction short-hairpin RNA S tag-Flag tag-SBP gene ontology. Cyclin-dependent kinases Significance Analysis of INTeactome high-confidence candidate interacting proteins protein-protein interaction short-hairpin RNA S tag-Flag tag-SBP gene ontology. The CDK family has been widely studied in the past two decades and implicated in control of cell-cycle progression, gene transcription, and neuronal functions, which are key events required during development, tissue homeostasis, and tumorigenesis (7Malumbres M. Barbacid M. Cell cycle kinases in cancer.Curr. Opin. Genet. Dev. 2007; 17: 60-65Crossref PubMed Scopus (282) Google Scholar, 8Malumbres M. Physiological relevance of cell cycle kinases.Physiol. Rev. 2011; 91: 973-1007Crossref PubMed Scopus (158) Google Scholar). In addition, because of their catalytic activities, some CDKs are considered druggable targets, and selective inhibitors for these CDKs are being developed for cancer therapy (5Johnson N. Shapiro G.I. Cyclin-dependent kinases (cdks) and the DNA damage response: rationale for cdk inhibitor-chemotherapy combinations as an anticancer strategy for solid tumors.Expert Opin. Ther. Targets. 2010; 14: 1199-1212Crossref PubMed Scopus (73) Google Scholar). Until now, the studies of some CDKs, such as those focused on CDK1, CDK2, CDK4, and CDK6, have been very extensive; however, the physiological roles of other CDKs and their activating partners remain largely unknown. Therefore, we used a modified tandem affinity purification coupled with mass spectrometry analysis (TAP-MS) approach to conduct a proteomic study of the CDK family, with a goal of understanding the regulations and functions of this critical family of protein kinases. An unexpected finding is the identification of a novel CDK5-containing protein complex in non-neuronal cells. Despite the recent recognition that many CDKs may have regulatory functions beyond cell cycle control, CDK5 remains the most unusual member of the CDK family (9Dhariwala F.A. Rajadhyaksha M.S. An unusual member of the Cdk family: Cdk5.Cell. Mol. Neurobiol. 2008; 28: 351-369Crossref PubMed Scopus (137) Google Scholar). This is because unlike other CDKs, CDK5 is activated by p35 and p39, two proteins that are expressed only in the brain (10Tsai L.H. Delalle I. Caviness Jr., V.S. Chae T. Harlow E. p35 is a neural-specific regulatory subunit of cyclin-dependent kinase 5.Nature. 1994; 371: 419-423Crossref PubMed Scopus (809) Google Scholar, 11Lew J. Huang Q.Q. Qi Z. Winkfein R.J. Aebersold R. Hunt T. Wang J.H. A brain-specific activator of cyclin-dependent kinase 5.Nature. 1994; 371: 423-426Crossref PubMed Scopus (539) Google Scholar). CDK5 also binds to d-type and E-type cyclins but does not display kinase activity (12Contreras-Vallejos E. Utreras E. Gonzalez-Billault C. Going out of the brain: non-nervous system physiological and pathological functions of Cdk5.Cell Signal. 2012; 24: 44-52Crossref PubMed Scopus (66) Google Scholar). Therefore, Cdk5 is often regarded as a neuron-specific kinase, which is not involved in cell cycle control, but instead plays an essential role in neuronal development, including neuronal migration, axon guidance, and synaptic plasticity (13Lopes J.P. Agostinho P. Cdk5: multitasking between physiological and pathological conditions.Prog. Neurobiol. 2011; 94: 49-63Crossref PubMed Scopus (96) Google Scholar, 14Lalioti V. Pulido D. Sandoval I.V. Cdk5, the multifunctional surveyor.Cell Cycle. 2010; 9: 284-311Crossref PubMed Scopus (55) Google Scholar, 15Su S.C. Tsai L.H. Cyclin-dependent kinases in brain development and disease.Annu. Rev. Cell Dev. Biol. 2011; 27: 465-491Crossref PubMed Scopus (242) Google Scholar, 16Feldmann G. Mishra A. Hong S.M. Bisht S. Strock C.J. Ball D.W. Goggins M. Maitra A. Nelkin B.D. Inhibiting the cyclin-dependent kinase CDK5 blocks pancreatic cancer formation and progression through the suppression of Ras-Ral signaling.Cancer Res. 2010; 70: 4460-4469Crossref PubMed Scopus (126) Google Scholar). However, CDK5 is ubiquitously expressed. Emerging evidence indicates that CDK5 may have extraneuronal functions that comprise transcript-selective translation control, glucose-inducible insulin secretion, vascular angiogenesis, cell adhesion, migration, and wound healing (12Contreras-Vallejos E. Utreras E. Gonzalez-Billault C. Going out of the brain: non-nervous system physiological and pathological functions of Cdk5.Cell Signal. 2012; 24: 44-52Crossref PubMed Scopus (66) Google Scholar, 17Rosales J.L. Lee K.Y. Extraneuronal roles of cyclin-dependent kinase 5.Bioessays. 2006; 28: 1023-1034Crossref PubMed Scopus (99) Google Scholar, 18Liebl J. Furst R. Vollmar A.M. Zahler S. Twice switched at birth: cell cycle-independent roles of the "neuron-specific" cyclin-dependent kinase 5 (Cdk5) in non-neuronal cells.Cell Signal. 2011; 23: 1698-1707Crossref PubMed Scopus (39) Google Scholar, 19Arif A. Extraneuronal activities and regulatory mechanisms of the atypical cyclin-dependent kinase Cdk5.Biochem. Pharmacol. 2012; 84: 985-993Crossref PubMed Scopus (63) Google Scholar). Importantly, CDK5 also plays critical roles in the development and progression of many types of human cancers, which include liver cancer (20Selvendiran K. Koga H. Ueno T. Yoshida T. Maeyama M. Torimura T. Yano H. Kojiro M. Sata M. Luteolin promotes degradation in signal transducer and activator of transcription 3 in human hepatoma cells: an implication for the antitumor potential of flavonoids.Cancer Res. 2006; 66: 4826-4834Crossref PubMed Scopus (178) Google Scholar), colorectal cancer (21Kim E. Chen F. Wang C.C. Harrison L.E. CDK5 is a novel regulatory protein in PPARgamma ligand-induced antiproliferation.Int. J. Oncol. 2006; 28: 191-194PubMed Google Scholar), pancreatic cancer (16Feldmann G. Mishra A. Hong S.M. Bisht S. Strock C.J. Ball D.W. Goggins M. Maitra A. Nelkin B.D. Inhibiting the cyclin-dependent kinase CDK5 blocks pancreatic cancer formation and progression through the suppression of Ras-Ral signaling.Cancer Res. 2010; 70: 4460-4469Crossref PubMed Scopus (126) Google Scholar, 22Eggers J.P. Grandgenett P.M. Collisson E.C. Lewallen M.E. Tremayne J. Singh P.K. Swanson B.J. Andersen J.M. Caffrey T.C. High R.R. Ouellette M. Hollingsworth M.A. Cyclin-dependent kinase 5 is amplified and overexpressed in pancreatic cancer and activated by mutant K-Ras.Clin. Cancer Res. 2011; 17: 6140-6150Crossref PubMed Scopus (63) Google Scholar), prostate cancer (23Strock C.J. Park J.I. Nakakura E.K. Bova G.S. Isaacs J.T. Ball D.W. Nelkin B.D. Cyclin-dependent kinase 5 activity controls cell motility and metastatic potential of prostate cancer cells.Cancer Res. 2006; 66: 7509-7515Crossref PubMed Scopus (128) Google Scholar, 24Hsu F.N. Chen M.C. Chiang M.C. Lin E. Lee Y.T. Huang P.H. Lee G.S. Lin H. Regulation of androgen receptor and prostate cancer growth by cyclin-dependent kinase 5.J. Biol. Chem. 2011; 286: 33141-33149Abstract Full Text Full Text PDF PubMed Scopus (74) Google Scholar), and lung cancer (25Choi H.S. Lee Y. Park K.H. Sung J.S. Lee J.E. Shin E.S. Ryu J.S. Kim Y.H. Single-nucleotide polymorphisms in the promoter of the CDK5 gene and lung cancer risk in a Korean population.J. Hum. Genet. 2009; 54: 298-303Crossref PubMed Scopus (18) Google Scholar, 26Lockwood W.W. Chari R. Coe B.P. Girard L. Macaulay C. Lam S. Gazdar A.F. Minna J.D. Lam W.L. DNA amplification is a ubiquitous mechanism of oncogene activation in lung and other cancers.Oncogene. 2008; 27: 4615-4624Crossref PubMed Scopus (97) Google Scholar). Unfortunately, precisely how CDK5 functions outside of neuronal tissues and participates in tumorigenesis is largely unknown. Our proteomics study of the CDK family led to the discovery of many novel CDK-associated proteins, expanded the roles of CDKs in multiple biological processes, and established comparable interaction networks in two different cell lines. Specifically for CDK5, we uncovered a novel complex that contains CDK5, a previously uncharacterized protein KIAA0528, and fibroblast growth factor (acidic) intracellular binding protein (FIBP). We provide evidence suggesting that this complex is important for regulating cell growth and migration in breast cancer cells and therefore offer a new mechanism of CDK5 function in non-neuronal tissues. The CDK family proteins (CDK1, CDK2, CDK3, CDK4, CDK5, CDK6, CDK7, CDK8, CDK9, CDK10, CDK13, CDK14, CDK15, CDK16, CDK17, CDK18, CDK19, CDK20, CDKL1, and CDKL4), 24 controls (RSF1, MSI1, TNK1, YES1, PTK6, LCK, TRAF6, FAF1, NDRG4, SMYD4, MXI1, TRIM16, ERCC8, BLK, FER, BMX, ZAP70, TNK2, AMOTL1, AMOTL2, ST3, STK4, TEAD2, and YAP), and KIAA0528 and FIBP plasmids were purchased from Harvard Plasmids (Harvard Medical School, Boston, MA) and Open Biosystems (Huntsville, AL). CDK11 plasmid was kindly provided by Dr. Re′gis Giet (Universite′ de Rennes I). CDK12 plasmid was kindly provided by Dr. Dalibor Blazek (University of California at San Francisco). CDKL5 plasmid was kindly provided by Dr. Marsha Rich Rosner (University of Chicago). All constructs were generated by polymerase chain reaction (PCR) and subcloned into pDONOR201 vector with use of Gateway Technology (Invitrogen, Carlsbad, CA) as the entry clones. For the TAP-MS, all entry clones were subsequently recombined into lentiviral-gateway-compatible destination vector for the expression of C-terminal SFB-tagged fusion proteins. Gateway-compatible destination vectors with indicated SFB tag or Myc tag were also used to express various fusion proteins for the CDK5, KIAA0528, and FIBP studies. Mutations were introduced in these constructs by using the Quik-Change Site-Directed Mutagenesis Kit (Stratagene, La Jolla, CA), and all mutations were verified by DNA sequencing. All lentiviral supernatants were generated by transient transfection of HEK293T cells with packaging plasmids pSPAX2 and pMD2G (kindly provided by Dr. Zhou Songyang, Baylor College of Medicine) and harvested 48 h after transfection. Supernatants were passed through a 0.45-μm filter and used to infect MDA-MB-231 cells with the addition of 8 μg/ml Polybrene. Two individual pGIPZ lentiviral shRNAs targeting CDK5, KIAA0528, and FIBP, respectively, were obtained from the shRNA and ORFeome core facility at The University of Texas MD Anderson Cancer Center. The shRNA sequences were as follows: Control shRNA: 5′-TCTCGCTTGGGCGAGAGTAAG-3′ CDK5 shRNA-1# (V3LHS_390938): 5′-TGAGTAGGCAGATCTCCCG-3′; CDK5 shRNA-2# (V3LHS_390942): 5′-ATCTTTTCCAGTTTCTCGT-3′; KIAA0528 shRNA-1# (V2LHS_232289): 5′-TATTCATTAGCTGAGTATG-3′; KIAA0528 shRNA-2# (V3LHS_398207): 5′-AATTCTGTAACTTCATCCG-3′; FIBP shRNA-1# (V3LHS_351216): 5′-TGCTGAATATTGTCCACCA-3′; FIBP shRNA-2# (V3LHS_351217): 5′-TTGGTGCTGATGTCATCCA-3′; The KIAA0528–1# and FIBP-1# shRNA resistant wild-type and mutant constructs were generated by six nucleotide substitutions and verified by DNA sequencing. Anti-CDK5 antibody was purchased from Santa Cruz Biotechnology (Santa Cruz, CA). Anti-KIAA0528 antibody was purchased from Bethyl Laboratories Montgomery, TX. Anti-FIBP polyclonal antibody was purchased from Abgent. Anti-Beta-actin and anti-Flag (M2) monoclonal antibodies and anti-Flag polyclonal antibodies were obtained from Sigma-Aldrich. Anti-Myc and GAPDH monoclonal antibodies were purchased from Santa Cruz Biotechnology. HEK293T and MCF10A cells were purchased from the American Type Culture Collection and maintained in Dulbecco modified essential medium (DMEM) supplemented with 10% fetal bovine serum at 37 °C in 5% CO2 (v/v). MDA-MB-231 cells were kindly provided by Dr. Li Ma (MD Anderson Cancer Center). MCF10A cells were maintained in DMEM/F12 medium supplemented with 5% horse serum, 200 ng/ml epidermal growth factor, 500 ng/ml hydrocortisone, 100 ng/ml cholera toxin, and 10 μg/ml insulin at 37 °C in 5% CO2 (v/v). All culture media contained 1% penicillin and streptomycin antibiotics. Plasmid transfection was performed with use of the polyethylenimine reagent. HEK293T cells were transfected with plasmids encoding various SFB-tagged proteins. Stable cell lines were selected with media containing 2 μg/ml puromycin and confirmed by immunostaining and Western blotting. MCF10A cells (or MDA-MB-231 cells) were infected by lentivirus expressing tet-on inducible SFB-tagged proteins, and stable pools were selected with media containing 500 μg/ml G418 (or 2 μg/ml puromycin) and confirmed by immunostaining and Western blotting. For affinity purification, HEK293T, MCF10A, or MDA-MB-231 cells were subjected to lysis in NETN buffer (with protease inhibitors) at 4 °C for 20 min. Crude lysates were subjected to centrifugation at 4 °C and 14,000 rpm for 20 min. Supernatants were incubated with streptavidin-conjugated beads (Amersham Biosciences) for 2 h at 4 °C. The beads were washed three times with NETN buffer, and bounded proteins were eluted with NETN buffer containing 2 mg/ml biotin (Sigma) for 2 h at 4 °C. Elutes were incubated with S protein beads (Novagen) for 1 h. The beads were washed three times with NETN buffer and subjected to SDS-PAGE. Protein bands were excised and subjected to mass spectrometry analysis (performed by Taplin Mass Spectrometry Facility, Harvard Medical School). Excised gel bands were cut into ∼1 mm3 pieces. Gel pieces were then subjected to in-gel trypsin digestion (27Shevchenko A. Wilm M. Vorm O. Mann M. Mass spectrometric sequencing of proteins silver-stained polyacrylamide gels.Anal. Chem. 1996; 68: 850-858Crossref PubMed Scopus (7807) Google Scholar) and dried. Samples were reconstituted in 5 μl of HPLC solvent A (2.5% acetonitrile, 0.1% formic acid). A nano-scale reverse-phase HPLC capillary column was created by packing 5 μm C18 spherical silica beads into a fused silica capillary (100-μm inner diameter x ∼20-cm length) with a flame-drawn tip. After the column was equilibrated, each sample was loaded via a Famos autosampler (LC Packings, San Francisco, CA) onto the column. A gradient was formed, and peptides were eluted with increasing concentrations of solvent B (97.5% acetonitrile, 0.1% formic acid). As peptides eluted, they were subjected to electrospray ionization and then entered into an LTQ Velos ion-trap mass spectrometer (ThermoFisher, San Jose, CA). Peptides were detected, isolated, and fragmented to produce a tandem mass spectrum of specific fragment ions for each peptide. All the default parameters were used. Peptide sequences (and hence protein identity) were determined by matching the acquired fragmentation pattern with protein databases by the software program, SEQUEST (ver. 28) (ThermoFisher). Enzyme specificity was set to partially tryptic with two missed cleavages. Modifications included carboxyamidomethyl (cysteines, fixed) and oxidation (methionine, variable). Mass tolerance was set to 2.0 for precursor ions and to 1.0 for fragment ions. Because we used HEK293T and MCF10A cells, the database searched was the Human IPI databases version 3.6. The number of entries in the database was 160,900, which included both the target (forward) and the decoy (reversed) human sequences. Spectral matches were filtered to contain less than 1% FDR at the peptide level based on the target-decoy method (28Elias J.E. Gygi S.P. Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry.Nat. Methods. 2007; 4: 207-214Crossref PubMed Scopus (2827) Google Scholar). Finally, only tryptic matches were reported, and spectral matches were manually examined. When peptides matched to multiple proteins, the peptide was assigned so that only the most logical protein was included (Occam's razor). This same principle was used for isoforms when present in the database. The longest isoform was reported as the match. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository with the data set identifier PXD000593 and DOI 10.6019/PXD000593 (29Vizcaino J.A. Cote R.G. Csordas A. Dianes J.A. Fabregat A. Foster J.M. Griss J. Alpi E. Birim M. Contell J. O'Kelly G. Schoenegger A. Ovelleiro D. Perez-Riverol Y. Reisinger F. Rios D. Wang R. Hermjakob H. The PRoteomics IDEntifications (PRIDE) database and associated tools: status in 2013.Nucleic Acids Res. 2013; 41: D1063-D1069Crossref PubMed Scopus (1595) Google Scholar, 30Vizcaino J.A. Deutsch E.W. Wang R. Csordas A. Reisinger F. Rios D. Dianes J.A. Sun Z. Farrah T. Bandeira N. Binz P.A. Xenarios I. Eisenacher M. Mayer G. Gatto L. Campos A. Chalkley R.J. Kraus H.J. Albar J.P. Martinez-Bartolome S. Apweiler R. Omenn G.S. Martens L. Jones A.R. Hermjakob H. ProteomeXchange provides globally coordinated proteomics data submission and dissemination.Nat. Biotechnol. 2014; 32: 223-226Crossref PubMed Scopus (2071) Google Scholar, 31Cote R.G. Griss J. Dianes J.A. Wang R. Wright J.C. van den Toorn H.W. van Breukelen B. Heck A.J. Hulstaert N. Martens L. Reisinger F. Csordas A. Ovelleiro D. Perez-Rivevol Y. Barsnes H. Hermjakob H. Vizcaino J.A. The PRoteomics IDEntification (PRIDE) Converter 2 framework: an improved suite of tools to facilitate data submission to the PRIDE database and the ProteomeXchange consortium.Mol. Cell. Proteomics. 2012; 11: 1682-1689Abstract Full Text Full Text PDF PubMed Scopus (96) Google Scholar). supplemental Table S1 contains the lists of the proteins identified during these analyses. supplemental Table S2 contains the lists of the peptides identified and during these analyses. To apply SAINT algorithms, we first gathered information about baits and preys including the spectra counts, prey protein length, and assignment of control baits. We reorganized the data to the format compatible to the SAINT program and used two-pool analysis, which recognizes the control group as a separate pool. We did not remove outlier data points. However, during the data analysis, we temporarily removed the bait self-identification in the identification list before applying the SAINT algorithms, and added it back after the data filtration. The statistics used to assess accuracy and significance of measurements was referred to the SAINT algorithms, where SS (SAINT score) > 0.80 was taken as the threshold required for the data quantification, as indicated by the SAINT method (32Choi H. Larsen B. Lin Z.Y. Breitkreutz A. Mellacheruvu D. Fermin D. Qin Z.S. Tyers M. Gingras A.C. Nesvizhskii A.I. SAINT: probabilistic scoring of affinity purification-mass spectrometry data.Nat. Methods. 2011; 8: 70-73Crossref PubMed Scopus (386) Google Scholar). For overall interactomes generated by Cytoscape (33Saito R. Smoot M.E. Ono K. Ruscheinski J. Wang P.L. Lotia S. Pico A.R. Bader G.D. Ideker T. A travel guide to Cytoscape plugins.Nat. Methods. 2012; 9: 1069-1076Crossref PubMed Scopus (1035) Google Scholar, 34Smoot M.E. Ono K. Ruscheinski J. Wang P.L. Ideker T. Cytoscape 2.8: new features for data integration and network visualization.Bioinformatics. 2011; 27: 431-432Crossref PubMed Scopus (3477) Google Scholar), we analyzed the network and created custom styles, then applied yFiles organic layout with minor adjustments when necessary. For the individual CDK interactomes generated by Cytoscape, we used unweighted force directed distributions with minor adjustments when necessary. The reported interactions (orange lines) were performed with literature-based search provided by BioGrid (35Chatr-Aryamontri A. Breitkreutz B.J. Heinicke S. Boucher L. Winter A. Stark C. Nixon J. Ramage L. Kolas N. O'Donnell L. Reguly T. Breitkreutz A. Sellam A. Chen D. Chang C. Rust J. Livstone M. Oughtred R. Dolinski K. Tyers M. The BioGRID interaction database: 2013 update.Nucleic Acids Res. 2013; 41: D816-D823Crossref PubMed Scopus (561) Google Scholar) and other databases when necessary. The heatmap for the hierarchical clustering was generated by MEV_4.8.1 Heatmap Builder software. For the prey-bait heat-map, we used HCL clustering based on Pearson correlation with average linkage clustering and set the color lower limit to 0, midpoint value to 10.0, and upper limit to 20.0. The Gene-Ontology annotations with p values were performed based on the Knowledge Base provided by Ingenuity pathway software (Ingenuity Systems, www.ingenuity.com), which contains findings and annotations from multiple sources including the Gene Ontology database. We used -log (p value) of individual functions to make GO annotation heatmaps. In these GO-heatmaps, we arranged the baits in alphabetical order and did not cluster them. We used a rainbow scheme and set the color lower limit to 1, midpoint value to 2.5, and upper limit to 5.0. Cells were lysed in NETN buffer (20 mm Tris-HCl, pH 8.0, 100 mm NaCl, 1 mm EDTA, and 0.5% Nonidet P-40), and the clarified lysates were resolved by SDS-PAGE and transferred to PVDF membranes for Western blotting. Alternatively, the clarified supernatants were first incubated with S-protein beads (Novagen, Madison, WI) for 2 h, and the precipitates were washed five times with NETN buffer. To investigate the interaction between CDK5 and KIAA0528 or FIBP at the endogenous level, the clarified supernatants were first incubated with anti-CDK5 or KIAA0528 for 2 h at 4 °C. Protein A/G-agaroses were then added overnight, and the precipitates were washed five times with NETN buffer and analyzed by Western blotting. This assay was performed as described previously (36Wang J. Leung J.W. Gong Z. Feng L. Shi X. Chen J. PHF6 regulates cell cycle progression by suppressing ribosomal RNA synthesis.J. Biol. Chem. 2013; 288: 3174-3183Abstract Full Text Full Text PDF PubMed Scopus (69) Google Scholar). Briefly, CDK5-, KIAA0528-, or FIBP-deficient, reconstituted, or control MDA-MB-231 cells were seeded at low density (1.6 × 104 cells/6 well plate). Cell numbers were quantified every day by digesting cells into suspension using trypsin/EDTA and resuspending in a given volume of fresh medium. The data presented represent the mean of all measured points ±S.E. (n = 3). The soft-agar colony assay was performed essentially as described previously (37Wang W. Huang J. Wang X. Yuan J. Li X. Feng L. Park J.I. Chen J. PTPN14 is required for the density-dependent control of YAP1.Genes Dev. 2012; 26: 1959-1971Crossref PubMed Scopus (144) Google Scholar). Briefly, MDA-MB-231 cells (2.5 × 103) were added to 1.5 ml of growth medium with 0.33% agar and layered onto beds of 0.5% agar (2 ml) in six-well plates. Viable colonies were scored after 3 weeks of incubation, and the quantified data were presented from three independent experiments. This assay was performed as described previously (38Wang W. Huang J. Chen J. Angiomotin-like proteins associate with and negatively regulate YAP1.J. Biol. Chem. 2011; 286: 4364-4370Abstract Full Text Full Text PDF PubMed Scopus (201) Google Scholar). Briefly, Confluent MDA-MB-231 cells were scratched with 200 μl pipette tips, washed twice with PBS, and then refreshed with appropriate medium. Images were captured 22 h later with use of a microscope. This assay was performed as described previously (39Chen D. Sun Y. Wei Y. Zhang P. Rezaeian A.H. Teruya-Feldstein J. Gupta S. Liang H. Lin H.K. Hung M.C. Ma L. LIFR is a breast cancer metastasis suppressor upstream of the Hippo-YAP pathway and a prognostic marker.Nat. Med. 2012; 18: 1511-1517Crossref PubMed Scopus (321) Google Scholar). Briefly, 5.0 × 104 MDA-MB-231 cells in 200 μl of serum-free DMEM were added to the cell culture inserts with an 8-μm Pore Polycarbonate Membrane (Corning, NY, USA). DMEM conditioned medium containing 10% FBS was added to the bottom chamber. After 22 h of incubation, the cells on the lower surface of the chamber were fixed, stained, and then examined with use of a microscope. The numbers of migrated cells in three random optical fields from triplicate fi

Referência(s)