Identification of the Ligands of Protein Interaction Domains through a Functional Approach
2006; Elsevier BV; Volume: 6; Issue: 2 Linguagem: Inglês
10.1074/mcp.m600289-mcp200
ISSN1535-9484
AutoresGinevra Caratù, Danilo Allegra, Marida Bimonte, Gabriele G. Schiattarella, Chiara D’Ambrosio, Andrea Scaloni, Maria Napolitano, Tommaso Russo, Nicola Zambrano,
Tópico(s)Computational Drug Discovery Methods
ResumoThe identification of protein-protein interaction networks has often given important information about the functions of specific proteins and on the cross-talk among metabolic and regulatory pathways. The availability of entire genome sequences has rendered feasible the systematic screening of collections of proteins, often of unknown function, aimed to find the cognate ligands. Once identified by genetic and/or biochemical approaches, the interaction between two proteins should be validated in the physiologic environment. Herein we describe an experimental strategy to screen collections of protein-protein interaction domains to find and validate candidate interactors. The approach is based on the assumption that the overexpression in cultured cells of protein-protein interaction domains, isolated from the context of the whole protein, could titrate the endogenous ligand and, in turn, exert a dominant negative effect. The identification of the ligand could provide us with a tool to check the relevance of the interaction because the contemporary overexpression of the isolated domain and of its ligand could rescue the dominant negative phenotype. We explored this approach by analyzing the possible dominant negative effects on the cell cycle progression of a collection of phosphotyrosine binding (PTB) domains of human proteins. Of 47 PTB domains, we found that the overexpression of 10 of them significantly interfered with the cell cycle progression of NIH3T3 cells. Four of them were used as baits to identify the cognate interactors. Among these proteins, CARM1, interacting with the PTB domain of RabGAP1, and EF1α, interacting with RGS12, were able to rescue the block of the cell cycle induced by the isolated PTB domain of the partner protein, thus confirming in vivo the relevance of the interaction. These results suggest that the described approach can be used for the systematic screening of the ligands of various protein-protein interaction domains also by using different biological assays. The identification of protein-protein interaction networks has often given important information about the functions of specific proteins and on the cross-talk among metabolic and regulatory pathways. The availability of entire genome sequences has rendered feasible the systematic screening of collections of proteins, often of unknown function, aimed to find the cognate ligands. Once identified by genetic and/or biochemical approaches, the interaction between two proteins should be validated in the physiologic environment. Herein we describe an experimental strategy to screen collections of protein-protein interaction domains to find and validate candidate interactors. The approach is based on the assumption that the overexpression in cultured cells of protein-protein interaction domains, isolated from the context of the whole protein, could titrate the endogenous ligand and, in turn, exert a dominant negative effect. The identification of the ligand could provide us with a tool to check the relevance of the interaction because the contemporary overexpression of the isolated domain and of its ligand could rescue the dominant negative phenotype. We explored this approach by analyzing the possible dominant negative effects on the cell cycle progression of a collection of phosphotyrosine binding (PTB) domains of human proteins. Of 47 PTB domains, we found that the overexpression of 10 of them significantly interfered with the cell cycle progression of NIH3T3 cells. Four of them were used as baits to identify the cognate interactors. Among these proteins, CARM1, interacting with the PTB domain of RabGAP1, and EF1α, interacting with RGS12, were able to rescue the block of the cell cycle induced by the isolated PTB domain of the partner protein, thus confirming in vivo the relevance of the interaction. These results suggest that the described approach can be used for the systematic screening of the ligands of various protein-protein interaction domains also by using different biological assays. The identification of novel protein-protein interactions has become a common strategy to assess the function of gene products. Taking into account the availability of biological sequence data and the annotations of genes in several species, systematic approaches have been realized in model organisms, from yeast to human, to define the molecular frames of binary interactions among proteins, which can be used to define the interactome of a given species (for a review, see Ref. 1Cusick M.E. Klitgord N. Vidal M. Hill D.E. Interactome: gateway into systems biology..Hum. Mol. Gen. 2005; 14: 171-181Crossref PubMed Scopus (319) Google Scholar). Identification of protein-protein interactions has taken advantage, in the last 2 decades, of both genetic and biochemical traps. Since its introduction, yeast two-hybrid screening (2Fields S. Song O. A novel genetic system to detect protein-protein interactions..Nature. 1989; 340: 245-246Crossref PubMed Scopus (4880) Google Scholar) has served as a potent genetic tool to trap molecular interactions among proteins; its suitability to high throughput performance has been the result of its fundamental relevance to interactome mapping projects in invertebrates (3Li S. Armstrong C.M. Bertin M. Ge H. Milstein S. Boxem M. Vidalain P.O. Han J.D. Chesmeau A. Hao T. Goldberg D.S. Li N. Martinez M. Rual J.F. Lamesch P. Xu L. Tewari M. Wong S.L. Zhang L.V. Berriz G.F. Jacotot L. Vaglio P. Reboul J. Hirozane-Kishikawa T. Li Q. Gabel H.W. Elewa A. Baumgartner B. Rose D.J. Yu H. Bosak S. Sequerra R. Fraser A. Mango S.E. Saxton W.M. Strome S. van Den Heuvel S. Piano F. Vandenhaute J. Sardet C. Gerstein M. Doucette-Stamm L. Gunsalus K.C. Harper J.W. Cusick M.E. Roth F.P. Hill D.E. Vidal M. A map of the interactome network of the metazoan C. elegans..Science. 2004; 303: 540-543Crossref PubMed Scopus (1453) Google Scholar) as well as in mammalian species including human (4Rual J.F. Venkatesan K. Hao T. Hirozane-Kishikawa T. Dricot A. Li N. Berriz G.F. Gibbons F.D. Dreze M. Ayivi-Guedehoussou N. Klitgord N. Simon C. Boxem M. Milstein S. Rosenberg J. Goldberg D.S. Zhang L.V. Wong S.L. Franklin G. Li S. Albala J.S. Lim J. Fraughton C. Llamosas E. Cevik S. Bex C. Lamesch P. Sikorski R.S. Vandenhaute J. Zoghbi H.Y. Smolyar A. Bosak S. Sequerra R. Doucette-Stamm L. Cusick M.E. Hill D.E. Roth F.P. Vidal M. Towards a proteome-scale map of the human protein-protein interaction network..Nature. 2005; 437: 1173-1178Crossref PubMed Scopus (2302) Google Scholar). Besides genetic screens, alternative approaches are needed to overcome the limitations of the yeast systems. For instance, not all post-translational modifications relevant to some protein-protein interactions may properly occur in yeast cells (i.e. tyrosine phosphorylation). Furthermore the use of molecular baits encoding protein domains particularly small and/or prone to complex with other proteins, such as transcription activation domains, may in some cases preclude the feasibility of a genetic screen because of the high background. In this context, identification of biochemical interactions among proteins through co-precipitation assays provides a valid alternative approach to a detailed characterization of interactomes. This may be useful to find interactors for small protein binding motifs, which can be easily synthesized and derivatized for effective coupling to activated resins, or take advantage of recombinant expression of appropriate biochemical baits in bacteria or in eukaryotic cells. Once again, the availability of detailed annotations of biological sequences has accelerated the accumulation of data defining novel protein-protein interactions, also benefited by the availability of protein tagging strategies and the increased sensitivity of mass spectrometry-based methodologies for protein identification (5Gavin A.C. Bosche M. Krause R. Grandi P. Marzioch M. Bauer A. Schultz J. Rick J.M. Michon A.M. Cruciat C.M. Remor M. Hofert C. Schelder M. Brajenovic M. Ruffner H. Merino A. Klein K. Hudak M. Dickson D. Rudi T. Gnau V. Bauch A. Bastuck S. Huhse B. Leutwein C. Heurtier M.A. Copley R.R. Edelmann A. Querfurth E. Rybin V. Drewes G. Raida M. Bouwmeester T. Bork P. Seraphin B. Kuster B. Neubauer G. Superti-Furga G. Functional organization of the yeast proteome by systematic analysis of protein complexes..Nature. 2002; 415: 141-147Crossref PubMed Scopus (4010) Google Scholar, 6Ho Y. Gruhler A. Heilbut A. Bader G.D. Moore L. Adams S.L. Millar A. Taylor P. Bennett K. Boutilier K. Yang L. Wolting C. Donaldson I. Schandorff S. Shewnarane J. Vo M. Taggart J. Goudreault M. Muskat B. Alfarano C. Dewar D. Lin Z. Michalickova K. Willems A.R. Sassi H. Nielsen P.A. Rasmussen K.J. Andersen J.R. Johansen L.E. Hansen L.H. Jespersen H. Podtelejnikov A. Nielsen E. Crawford J. Poulsen V. Sorensen B.D. Matthiesen J. Hendrickson R.C. Gleeson F. Pawson T. Moran M.F. Durocher D. Mann M. Hogue C.W. Figeys D. Tyers M. Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry..Nature. 2002; 415: 180-183Crossref PubMed Scopus (3086) Google Scholar). In any event, downstream of the capture of novel protein-protein interactions by either genetic or biochemical traps, molecular (co-fractionation and co-immunoprecipitation) and/or cellular (confocal microscopy and fluorescence resonance energy transfer analysis) approaches are required to confirm the occurrence of the complexes in living cells, and functional assays are necessary to assess their physiological relevance in the appropriate cellular context. Adaptor proteins are specialized products, assembled through evolution-driven sequence modification and combinatorial shuffling of protein-protein interaction domains. For instance, SH2 1The abbreviations used are: SH, Src homology; PTB, phosphotyrosine binding; IRS, insulin receptor substrate; EF1α, elongation factor 1α; GAP, GTPase-activating protein; EPS, epidermal growth factor receptor protein substrate; BrdUrd, 5′-bromo-2′-deoxyuridine; LDL, low density lipoprotein; LRP1, LDL receptor-related protein 1; GFP, green fluorescent protein; EGFP, enhanced green fluorescent protein; HEK, human embryonic kidney; FACS, fluorescence-assisted cell sorting; JNK, c-Jun N-terminal kinase; RGS, regulators of G protein signaling; E13.5, embryonic day 13.5; SNARE, soluble N-ethylmaleimide-sensitive factor attachment protein receptors. and PTB domains from selected adaptors link activation of receptor tyrosine kinases to downstream signaling events regulating cellular proliferation, differentiation, and survival (7Pawson T. Specificity in signal transduction: from phosphotyrosine-SH2 domain interactions to complex cellular systems..Cell. 2004; 116: 191-203Abstract Full Text Full Text PDF PubMed Scopus (690) Google Scholar). Molecular adaptors are indeed involved in scaffolding the protein complexes necessary to perform and integrate distinct signaling pathways. Indeed the modular structures of adaptor proteins allow them to form complexes with one or more proteins at the same time. In turn, the bound proteins may link the former complexes to other proteins and, finally, to effector proteins. For these reasons, the expression of a protein domain, isolated from the context of the complete adaptor molecule, can render ineffective the progression of this molecular flow of interactions, preventing the formation of the ordered and functional protein complexes required for the effectiveness of the pathway. Thus, the overexpression of an isolated protein-protein interaction domain can be used as a functional tool to perturb cellular processes through dominant negative mechanisms. In this study, we describe a strategy aimed to identify and validate protein complexes based on the functional assay of the interaction. We decided to explore the interactions involving the phosphotyrosine binding domains (PTB or PID (phosphotyrosine interaction domain); for a review, see Ref. 8Uhlik M.T. Temple B. Bencharit S. Kimple A.J. Siderovski D.P. Johnson G.L. Structural and evolutionary division of phosphotyrosine binding (PTB) domains..J. Mol. Biol. 2005; 345: 1-20Crossref PubMed Scopus (213) Google Scholar) present in a collection of human proteins. Despite the acronym, which would define this domain as a selective ligand for phosphotyrosine (Tyr(P)) residues, PTB domains are heterogeneous in their binding specificities: although IRS- and Shc-based PTB modules actually interact with phosphotyrosines, PTB domains from other proteins, such as Fe65, do not require the Tyr(P) residue for complex formation (9Zambrano N. Buxbaum J.D. Minopoli G. Fiore F. De Candia P. De Renzis S. Faraonio R. Sabo S. Cheetham J. Sudol M. Russo T. Interaction of the phosphotyrosine interaction/phosphotyrosine binding-related domains of Fe65 with wild-type and mutant Alzheimer's β-amyloid precursor proteins..J. Biol. Chem. 1997; 272: 6399-6405Abstract Full Text Full Text PDF PubMed Scopus (140) Google Scholar). Also in the absence of Tyr(P), which can be substituted for by unmodified tyrosine or by phenylalanine, the binding often requires a hydrophobic residue at −5, Asn at −3, and the Pro at −2. However, in several interactors of PTB domains it was impossible to find sequences with these characteristics, thus indicating pronounced heterogeneity in binding specificities (8Uhlik M.T. Temple B. Bencharit S. Kimple A.J. Siderovski D.P. Johnson G.L. Structural and evolutionary division of phosphotyrosine binding (PTB) domains..J. Mol. Biol. 2005; 345: 1-20Crossref PubMed Scopus (213) Google Scholar). Given their participation in important cellular mechanisms, the proteins containing PTB domains often do participate in pathogenic mechanisms, such as in the case of oncogenic transformation (Shc) (10Pelicci G. Lanfrancone L. Grignani F. McGlade J. Cavallo F. Forni G. Nicoletti I. Grignani F. Pawson T. Pelicci P.G. A novel transforming protein (SHC) with an SH2 domain is implicated in mitogenic signal transduction..Cell. 1992; 70: 93-104Abstract Full Text PDF PubMed Scopus (1140) Google Scholar), hypercholesterolemia (ARH) (11Garcia C.K. Wilund K. Arca M. Zuliani G. Fellin R. Maioli M. Calandra S. Bertolini S. Cossu F. Grishin N. Barnes R. Cohen J.C. Hobbs H.H. Autosomal recessive hypercholesterolemia caused by mutations in a putative LDL receptor adaptor protein..Science. 2001; 292: 1394-1398Crossref PubMed Scopus (478) Google Scholar), diabetes (IRS-1) (12Porzio O. Federici M. Hribal M.L. Lauro D. Accili D. Lauro R. Borboni P. Sesti G. The Gly972→Arg amino acid polymorphism in IRS-1 impairs insulin secretion in pancreatic beta cells..J. Clin. Investig. 1999; 104: 357-364Crossref PubMed Scopus (128) Google Scholar), and developmental disorders (Dab) (13Sheldon M. Rice D.S. D'Arcangelo G. Yoneshima H. Nakajima K. Mikoshiba K. Howell B.W. Cooper J.A. Goldowitz D. Curran T. Scrambler and yotari disrupt the disabled gene and produce a reeler-like phenotype in mice..Nature. 1997; 389: 730-733Crossref PubMed Scopus (561) Google Scholar). Considering the involvement of PTB domain-containing proteins in several signal transduction mechanisms, we speculated that at least some of these proteins could be involved in the regulation of cell cycle. Therefore, we have examined the possibility that isolated protein domains could act as dominant negative effectors, thus interfering with the progression of the cell cycle. According to this approach, we examined 47 PTB domains and found that the overexpression of 10 of them perturbed the cell cycle regulation. The ligands of four of these proteins were identified. Two of these ligands, CARM1, interacting with the PTB domain of RabGAP1, and EF1α, interacting with RGS12, were able to rescue the block of the cell cycle induced by the PTB domain of the partner protein, thus validating in vivo the relevance of the interaction. To obtain a full list of human PTB domains, we searched the Conserved Domains Section of the National Center for Biotechnology Information (NCBI) and the Ensembl databases; for the search in the latter database we considered both the annotated gene list (ENSG) and the protein family list (ENSF). The PTB domains were isolated from the full protein sequence using InterPro (14Mulder N.J. Apweiler R. Attwood T.K. Bairoch A. Bateman A. Binns D. Bradley P. Bork P. Bucher P. Cerutti L. Copley R. Courcelle E. Das U. Durbin R. Fleischmann W. Gough J. Haft D. Harte N. Hulo N. Kahn D. Kanapin A. Krestyaninova M. Lonsdale D. Lopez R. Letunic I. Madera M. Maslen J. McDowall J. Mitchell A. Nikolskaya A.N. Orchard S. Pagni M. Ponting C.P. Quevillon E. Selengut J. Sigrist C.J. Silventoinen V. Studholme D.J. Vaughan R. Wu C.H. InterPro, progress and status in 2005..Nucleic Acids Res. 2005; 33: 201-205Crossref PubMed Scopus (461) Google Scholar). The PTB domains showing a positive hit to one or more structural prediction programs were included; furthermore the PTB domains of EPS8L3 and CTEN, which were not detected by our approach, were also included, given their homology to the EPS8 family paralogs for EPS8L3 (15Tocchetti A. Confalonieri S. Scita G. Di Fiore P.P. Betsholtz C. In silico analysis of the EPS8 gene family: genomic organization, expression profile, and protein structure..Genomics. 2003; 81: 234-244Crossref PubMed Scopus (32) Google Scholar) and to the Tensin family members for CTEN (16Lo S.H. Tensin..Int. J. Biochem. Cell Biol. 2004; 36: 31-34Crossref PubMed Scopus (166) Google Scholar). The 47 human PTB domains were aligned with ClustalX (17Jeanmougin F. Thompson J.D. Gouy M. Higgins D.G. Gibson T.J. Multiple sequence alignment with Clustal X..Trends Biochem. Sci. 1998; 23: 403-405Abstract Full Text Full Text PDF PubMed Scopus (2397) Google Scholar) to determine the boundaries of the PTB domains; such information was used to design specific primers for RT-PCR amplification of the cDNA regions containing the domains. Total RNA preparations were obtained with the use of the RNeasy Mini kit (Qiagen) by three different human cell lines: human embryonic kidney HEK293 cells, IMR-90 fibroblasts, and SHSY-5Y neuroblastoma cells. The cDNAs for amplification were obtained through reverse transcription with Superscript II reverse transcriptase (Invitrogen) from DNase-treated RNA preparations using either oligo(dT) or random hexamers for priming. The individual PTB domain cDNAs were obtained by at least one of the three cell lines (for the sequences of the primers see Supplemental Table sd2) and cloned in the pEGFP-C1 vector (Invitrogen) in-frame to the EGFP coding region. The amplified cDNAs of the PTB domains were also cloned into a modified version of the pGEX2TK vector in which a sequence encoding the Strep-tag sequence WSHPQFEK was inserted 3′ to the vector polylinker. The cloning of the cDNAs allowed the expression of recombinant PTB domain polypeptides with an N-terminal GST tag and a C-terminal Strep-tag. Cloning of the full-length cDNAs was achieved through RT-PCR amplification of EPS8L3, RabGAP1, RGS12, Q7Z2X4/P-CLI1, NMD3, and CARM1 cDNAs from at least one of the above cited human cell lines; the cDNAs for EF1α1 and the expression vector for LRP1 were a gift from Prof. P. Arcari and Prof. Strickland, respectively. The cDNAs for the PTB domain-containing proteins EPS8L3, RabGAP1, RGS12, and Q7Z2X4/P-CLI1 were cloned in-frame to a Myc tag, whereas the cDNAs of the ligands were cloned in-frame to the FLAG sequence, in the pRcCMV vector (Invitrogen). Supplemental Table sd3 reports the sequences of the oligonucleotides used for these amplifications. NIH3T3, HEK293, IMR-90, and SHSY-5Y cells were grown in Dulbecco's modified Eagle's medium (Invitrogen) supplemented with 10% fetal bovine serum (Hyclone) using standard procedures. For metabolic labeling, NIH3T3 cultures were starved of methionine and cysteine for 30 min and then incubated in Dulbecco's modified Eagle's medium containing 0.08 mCi/ml [35S]Met and [35S]Cys mixture (Promix, GE Healthcare) for 12 h before preparation of protein extracts. Cells were transfected with Lipofectamine 2000 (Invitrogen) according to the manufacturer's instructions. For fluorescence-assisted cell sorting (FACS) analysis, mouse fibroblasts NIH3T3 were plated in 60-mm dishes, allowed to attach to the dish overnight, and transiently transfected with the appropriate plasmids (10 μg of total DNA) using Lipofectamine 2000 (Invitrogen). Thirty hours after transfection, cells were dissociated from the plates with trypsin and washed with PBS without CaCl2 and MgCl2. Cells were then washed twice and fixed in 70% ethanol in PBS. Following another wash in the PBS, cells were treated with 10 μg/ml RNase A and then stained with 25 μg/ml propidium iodide. Transfected cells (20,000 cells for each experiment) were selected for analysis of DNA content (as measured by monitoring fluorescence from propidium iodide) by gating on fluorescein isothiocyanate-positive cells due to EGFP using a FACScan (BD Pharmingen). Cell cycle analysis was performed by the CELL-FIT program (BD Pharmingen). Three independent experiments were performed in triplicate. Statistical analysis was carried out with the Student's t test. For 5-bromo-2′-deoxyuridine (BrdUrd) incorporation experiments, NIH3T3 cells were grown on polylysine-precoated glass coverslips in 60-mm dishes and transfected with the appropriate vectors (10 μg of DNA) by using Lipofectamine 2000 (Invitrogen) according to the instructions from the manufacturer. Thirty hours after transfection, cells were incubated with 10 μm 5-bromo-2′-deoxyuridine (Roche Applied Science) for 2 h. Cells on coverslips were fixed with paraformaldehyde (4% in PBS, pH 7.4), permeabilized with 0.3% Triton X-100, and incubated with anti-BrdUrd monoclonal antibody (5-bromo-2′-deoxyuridine labeling and detection kit, Roche Applied Science) following the instructions of the supplier; then the cells were stained with Texas Red-conjugated secondary antibody (Jackson ImmunoResearch Laboratories). The coverslips were mounted in Mowiol (Calbiochem) onto a glass microscope slide, and fluorescence was examined using an Axiophot microscope (Zeiss). BrdUrd incorporation experiments were repeated three times for each transfected construct. In each independent experiment, BrdUrd-positive cells were scored from at least 200 EGFP-positive and 200 EGFP-negative cells. The ratios from the independent experiments were averaged, and standard deviation was calculated and reported on the chart. The recombinant PTB domains from the modified pGEX2TK vector were expressed in the BL21 strain of Escherichia coli following induction of exponentially growing cultures with 0.25 mm isopropyl 1-thio-β-d-galactopyranoside for 3 h at room temperature. Recombinant proteins were extracted and purified on GSH-Sepharose following described procedures (9Zambrano N. Buxbaum J.D. Minopoli G. Fiore F. De Candia P. De Renzis S. Faraonio R. Sabo S. Cheetham J. Sudol M. Russo T. Interaction of the phosphotyrosine interaction/phosphotyrosine binding-related domains of Fe65 with wild-type and mutant Alzheimer's β-amyloid precursor proteins..J. Biol. Chem. 1997; 272: 6399-6405Abstract Full Text Full Text PDF PubMed Scopus (140) Google Scholar) and further purified on Streptactin-Sepharose columns. Final eluates, obtained with 2.5 mm desthiobiotin in 100 mm Tris-HCl, 150 mm NaCl, 1 mm EDTA, pH 8.00, were dialyzed against PBS containing 1 mm DTT and stored at −80 °C until use. Cellular and embryo extracts were obtained by lysis in a buffer containing 50 mm Tris-HCl, 150 mm NaCl, 0,5% Triton X-100, 10% glycerol, pH 7.5, 50 mm NaF, 1 mm Na3VO4, 1 mm DTT, 0,4 mm EDTA, pH 8.0, and a mixture of protease inhibitors (Complete, Roche Applied Science). Lysates were clarified by centrifugation at 12,000 × g for 20 min at 4 °C. For radioactive pulldown, 250 μg of radiolabeled extracts from NIH3T3 cells were added to 10 μg of each recombinant protein bound to 10 μl of GSH-Sepharose resin; binding reactions were allowed to proceed for 2 h at 4 °C followed by washes in lysis buffer, elution, and loading onto 9% polyacrylamide gels for SDS-PAGE. Detection of bound proteins was obtained by scanning the fixed and dried gels on a Typhoon 9400 phosphorimaging system with the ImageQuant software (GE Healthcare). Preparative pulldown experiments were performed with 10 nmol of the recombinant proteins bound to 100 μl of GSH-Sepharose. The embryo lysates (25 mg) were first run on a GST column for preclearing, then added to the recombinant proteins, and incubated for 2 h at 4 °C. The unbound proteins were removed by five washes in lysis buffer, and then the bound polypeptides were eluted by lysis buffer containing 1 m NaCl or by 2% SDS in Tris-HCl, pH 6.8. Alternatively after washes, the resin containing the bound material was exposed to thrombin protease (3 units) for 12 h at room temperature to release the PTB domains and the bound proteins. The collected material was separated by SDS-PAGE on 9% polyacrylamide gels, which were stained with silver nitrate according to standard procedures. Bands from SDS-PAGE were excised from the gel, minced, and washed with water. Proteins were in-gel reduced, S-alkylated, and digested with trypsin as reported previously (18D'Ambrosio C. Arena S. Fulcoli G. Scheinfeld M.H. Zhou D. D'Adamio L. Scaloni A. Hyperphosphorylation of JNK-interacting protein 1, a protein associated with Alzheimer disease..Mol. Cell. Proteomics. 2006; 5: 97-113Abstract Full Text Full Text PDF PubMed Scopus (53) Google Scholar). Digest aliquots were removed and subjected to a desalting/concentration step on C18 ZipTips (Millipore Corp., Bedford, MA) using acetonitrile as eluent before MALDI-TOF-MS analysis. Peptide mixtures were loaded on the MALDI target, using the dried droplet technique and α-cyano-4-hydroxycinnamic acid as matrix, and analyzed by using a Voyager-DE PRO mass spectrometer (Applied Biosystems, Framingham, MA). Internal mass calibration was performed with peptides derived from enzyme autoproteolysis. The PROWL software package was used to identify bands unambiguously from the updated mammalian NCBI non-redundant sequence database (19Zhang W. Chait B.T. ProFound: an expert system for protein identification using mass spectrometric peptide mapping information..Anal. Chem. 2000; 72: 2482-2489Crossref PubMed Scopus (552) Google Scholar). Candidates with ProFound estimated Z scores >1.8 were further evaluated by the comparison with their calculated mass using the experimental values obtained from SDS-PAGE. Detailed peptide mass fingerprint analysis is reported in the supplemental data. Validation of the interactions was performed by pulldown followed by Western blot with antibodies directed against the endogenous or FLAG-tagged interactors of PTB domains: anti-CARM1 T-16 goat polyclonal (Santa Cruz Biotechnology); anti-eEF1α, CBP-KK1 mouse monoclonal (Upstate); anti-LRP1, rabbit polyclonal 483 (a kind gift from Dr. J. Herz); anti-FLAG peptide M2, mouse monoclonal (Sigma). Co-immunoprecipitations were carried out with the following antibody pairs: anti-FLAG M2 as precipitating antibody for NMD3-FLAG, CARM1-FLAG; anti-Myc 9E10 mouse monoclonal (Santa Cruz Biotechnology) as precipitating antibody for RGS12-Myc; anti-cubilin A-20 goat polyclonal (Santa Cruz Biotechnology). Detection of immune complexes in Western blot was carried out with the following antibodies: anti-Myc 9E10 for EPS8L3-Myc, RabGAP-Myc and Q7Z2X4; anti-eEF1α CBP-KK1. Detection for Western blot was carried out with the chemiluminescence system LiteAblot from Euroclone using horseradish peroxidase-conjugated protein A (GE Healthcare). To build a collection of PTB domains, we searched GenBank™ and Ensembl databases to select the genes encoding proteins with this module. Considering the high level of conservation among the PTB domains of mammalian species, we focused on the human dataset, also assuming the presence of a higher number of entries and a more detailed annotation for human genes. To reduce the redundancy of information arising from GenBank and to avoid duplications from the combination of the outputs from the two databases, we aligned the 47 domains with ClustalW (20Higgins D. Thompson J. Gibson T. Thompson J.D. Higgins D.G. Gibson T.J. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting position-specific gap penalties and weight matrix choice..Nucleic Acids Res. 1994; 22: 4673-4680Crossref PubMed Scopus (56003) Google Scholar). We removed from analysis the proteins possessing an IRS-like PTB domain (8Uhlik M.T. Temple B. Bencharit S. Kimple A.J. Siderovski D.P. Johnson G.L. Structural and evolutionary division of phosphotyrosine binding (PTB) domains..J. Mol. Biol. 2005; 345: 1-20Crossref PubMed Scopus (213) Google Scholar), which is annotated as a distinct entry in public databases (InterPro domain IPR002404). Our analysis was then focused on the remaining domains, classified as InterPro domain IPR006020, comprising both Shc-like and Dab-like PTBs (8Uhlik M.T. Temple B. Bencharit S. Kimple A.J. Siderovski D.P. Johnson G.L. Structural and evolutionary division of phosphotyrosine binding (PTB) domains..J. Mol. Biol. 2005; 345: 1-20Crossref PubMed Scopus (213) Google Scholar). This approach led to the identification of 42 human genes coding for products with PTB domains. Considering that some proteins, such as Fe65 family members, do possess two PTB domains, the total number of our in silico search gave rise to 47 PTB modules. These are listed in Supplemental Table sd1; the table also indicates the known ligands for the PTB domains of previously characterized proteins. To examine the possible dominant effect of the overexpression of isolated PTB domains on the cell cycle progression, we generated the collection of PTB domains in the pEGFP-N eukaryotic expression vector, which allowed
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