Novel asymmetrically localizing components of human centrosomes identified by complementary proteomics methods
2011; Springer Nature; Volume: 30; Issue: 8 Linguagem: Inglês
10.1038/emboj.2011.63
ISSN1460-2075
AutoresLis Jakobsen, Katja Vanselow, Marie Skogs, Yusuke Toyoda, Emma Lundberg, Ina Poser, Lasse Gaarde Falkenby, Martin V. Bennetzen, Jens Westendorf, Erich A. Nigg, Mathias Uhlén, Anthony A. Hyman, Jens Andersen,
Tópico(s)Plant nutrient uptake and metabolism
ResumoArticle11 March 2011free access Novel asymmetrically localizing components of human centrosomes identified by complementary proteomics methods Lis Jakobsen Lis Jakobsen Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark Search for more papers by this author Katja Vanselow Katja Vanselow Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark Search for more papers by this author Marie Skogs Marie Skogs School of Biotechnology, AlbaNova University Center, Royal Institute of Technology (KTH), Stockholm, Sweden Search for more papers by this author Yusuke Toyoda Yusuke Toyoda Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany Search for more papers by this author Emma Lundberg Emma Lundberg School of Biotechnology, AlbaNova University Center, Royal Institute of Technology (KTH), Stockholm, Sweden Search for more papers by this author Ina Poser Ina Poser Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany Search for more papers by this author Lasse G Falkenby Lasse G Falkenby Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark Search for more papers by this author Martin Bennetzen Martin Bennetzen Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark Search for more papers by this author Jens Westendorf Jens Westendorf Department of Cell Biology, Max Planck Institute of Biochemistry, Martinsried, Germany Search for more papers by this author Erich A Nigg Erich A Nigg Biozentrum, University of Basel, Basel, Switzerland Search for more papers by this author Mathias Uhlen Mathias Uhlen School of Biotechnology, AlbaNova University Center, Royal Institute of Technology (KTH), Stockholm, Sweden Search for more papers by this author Anthony A Hyman Anthony A Hyman Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany Search for more papers by this author Jens S Andersen Corresponding Author Jens S Andersen Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark Search for more papers by this author Lis Jakobsen Lis Jakobsen Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark Search for more papers by this author Katja Vanselow Katja Vanselow Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark Search for more papers by this author Marie Skogs Marie Skogs School of Biotechnology, AlbaNova University Center, Royal Institute of Technology (KTH), Stockholm, Sweden Search for more papers by this author Yusuke Toyoda Yusuke Toyoda Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany Search for more papers by this author Emma Lundberg Emma Lundberg School of Biotechnology, AlbaNova University Center, Royal Institute of Technology (KTH), Stockholm, Sweden Search for more papers by this author Ina Poser Ina Poser Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany Search for more papers by this author Lasse G Falkenby Lasse G Falkenby Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark Search for more papers by this author Martin Bennetzen Martin Bennetzen Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark Search for more papers by this author Jens Westendorf Jens Westendorf Department of Cell Biology, Max Planck Institute of Biochemistry, Martinsried, Germany Search for more papers by this author Erich A Nigg Erich A Nigg Biozentrum, University of Basel, Basel, Switzerland Search for more papers by this author Mathias Uhlen Mathias Uhlen School of Biotechnology, AlbaNova University Center, Royal Institute of Technology (KTH), Stockholm, Sweden Search for more papers by this author Anthony A Hyman Anthony A Hyman Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany Search for more papers by this author Jens S Andersen Corresponding Author Jens S Andersen Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark Search for more papers by this author Author Information Lis Jakobsen1, Katja Vanselow1, Marie Skogs2, Yusuke Toyoda3, Emma Lundberg2, Ina Poser3, Lasse G Falkenby1, Martin Bennetzen1, Jens Westendorf4, Erich A Nigg5, Mathias Uhlen2, Anthony A Hyman3 and Jens S Andersen 1 1Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark 2School of Biotechnology, AlbaNova University Center, Royal Institute of Technology (KTH), Stockholm, Sweden 3Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany 4Department of Cell Biology, Max Planck Institute of Biochemistry, Martinsried, Germany 5Biozentrum, University of Basel, Basel, Switzerland *Corresponding author. Department of Biochemistry and Molecular Biology, University of Southern Denmark, Campusvej 55, DK-5230 Odense M, Denmark. Tel.: +45 6550 2365; Fax: +45 6593 3018; E-mail: [email protected] The EMBO Journal (2011)30:1520-1535https://doi.org/10.1038/emboj.2011.63 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Centrosomes in animal cells are dynamic organelles with a proteinaceous matrix of pericentriolar material assembled around a pair of centrioles. They organize the microtubule cytoskeleton and the mitotic spindle apparatus. Mature centrioles are essential for biogenesis of primary cilia that mediate key signalling events. Despite recent advances, the molecular basis for the plethora of processes coordinated by centrosomes is not fully understood. We have combined protein identification and localization, using PCP-SILAC mass spectrometry, BAC transgeneOmics, and antibodies to define the constituents of human centrosomes. From a background of non-specific proteins, we distinguished 126 known and 40 candidate centrosomal proteins, of which 22 were confirmed as novel components. An antibody screen covering 4000 genes revealed an additional 113 candidates. We illustrate the power of our methods by identifying a novel set of five proteins preferentially associated with mother or daughter centrioles, comprising genes implicated in cell polarity. Pulsed labelling demonstrates a remarkable variation in the stability of centrosomal protein complexes. These spatiotemporal proteomics data provide leads to the further functional characterization of centrosomal proteins. Introduction The definition of the components of large non-membranous organelles, their relative abundance, and their turnover rates, are important, but unsolved goals in cell biology. Generally, organelles cannot be purified to homogeneity and methods are required to determine the actual components. Furthermore, the components change through the cell cycle and development. In an attempt to address these challenges, we focused on the centrosome which is a dynamic cell organelle with a proteinaceous matrix of pericentriolar material assembled around a pair of centrioles. The single centrosome present in G1-phase cells is usually positioned near the nucleus where it organizes microtubules that coordinate the shape, polarity, adhesion, and mobility of the cell, and facilitates intracellular transport and positioning of the organelles (Doxsey, 2001; Bornens, 2002; Nigg, 2002). Centrosomes at this stage harbour a daughter centriole and a mature mother centriole. The mature centriole has the ability to function as a basal body that seeds the growth of a primary cilium protruding from the cell surface. In multiciliated epithelial cells, de novo assembled basal bodies nucleate motile cilia important for fluid flow and cell migration (Satir and Christensen, 2007). It is now clear that primary cilia are sensory organelles that regulate signalling pathways such as sonic hedgehog and Wnt/planar cell polarity pathways, which in turn regulate essential cellular and developmental processes. The significance of sensory cilia is underlined by the recent findings that mutations affecting genes essential for their formation or function can lead to a number of severe human diseases and developmental defects, now known as the ‘ciliopathies’ (Fliegauf et al, 2007). During the S-phase of the cell cycle, the centrosome duplicates by the formation of procentrioles adjacent to each of the two parental centrioles. At the G2-M transition, the microtubule-nucleating capacities are increased by the recruitment of γ-tubulin ring complexes (γ-TuRCs) before the centrosomes separate and promote the formation of spindle asters and the positioning of the two spindle poles important for chromosome and centrosome segregation during mitosis. The duplication and segregation cycles of centrosomes and chromosomes are coordinated to avoid the numerical aberration of centrosomes, the missegregation of chromosomes, and the ploidy changes that are typical features of human tumours (Nigg, 2006). Moreover, the equal segregation of one centrosome per cell ensures that each cell has the potential to grow a single primary cilium (Tsou and Stearns, 2006). Plurifunctional roles in cell division are further supported by multiple lines of evidence, suggesting that the centrosome also contributes to cell-cycle regulation and checkpoints, asymmetric division and fate of sister cells, and acts as a scaffold for additional regulatory processes in the cell (Doxsey, 2001; Doxsey et al, 2005; Wang et al, 2009). Information about the protein composition of centrosomes and centrosome-related structures has been obtained through the application of proteomics, genomics, and bioinformatics in various eukaryotic cells (Bettencourt-Dias and Glover, 2007). The yeast spindle poles were the first to be characterized by mass spectrometry (MS)-based proteomics (Wigge et al, 1998). This study has been followed by the proteomic analyses of centrosomes from human lymphoblast cells (Andersen et al, 2003), the midbody from Chinese hamster ovary cells (Skop et al, 2004), the mitotic spindle from synchronized HeLa S3 cells (Sauer et al, 2005), in vitro-assembled spindle structures from Xenopus and HeLa cell extracts (Liska et al, 2004), and the centrosome of Dictyostelium discoideum (Reinders et al, 2006). Proteomic studies have also revealed the composition of ciliary and flagellar structures including the human ciliary axoneme (Ostrowski et al, 2002), the mouse photoreceptor sensory cilium complex (Liu et al, 2007), the flagellum and basal body of Chlamydomonas reinhardtii (Keller et al, 2005; Pazour et al, 2005), and the flagellum of Trypanosoma brucei (Broadhead et al, 2006). The cilia and flagella studies have been complemented by comparative genomics to identify genes that exist exclusively in organisms that have basal bodies and cilia (Li et al, 2004; Chen et al, 2006; Baron et al, 2007; Merchant et al, 2007). Taken together, these efforts have revealed candidate proteins associated with the centrosome, the centrioles, the mitotic spindle, midbody, and the cilium, some of which have been validated through localization (Andersen et al, 2003; Keller et al, 2005; Sauer et al, 2005) and RNA interference studies (Graser et al, 2007a; Lawo et al, 2009). The above findings illustrate how different strategies have contributed to the identification of >100 proteins associated with the centrosome leading to functional insight and molecular understanding of genetic disorders (Chang et al, 2006; Sayer et al, 2006; Valente et al, 2006; den Hollander et al, 2006; Spektor et al, 2007; Graser et al, 2007a, 2007b; Nigg and Raff, 2009). Despite these advances, many unsolved questions regarding centrosome and cilia function remain. For example, while the studies described above have revealed the identity of cilia and centrosomes components, we still do not know how most of these components dynamically localize, interact, and function at the molecular, cellular, and organismal level. Likewise, the causative gene in families with ciliopathies is unknown in most cases, suggesting that additional genes expected to be associated with cilia or centrosomes remain to be identified (Otto et al, 2010). To address these questions, we describe here the combined use of complementary proteomics strategies based on MS and microscopy to further explore the localization, abundance, and turnover of centrosomal proteins. The combined efforts resulted in a more comprehensive coverage of the human centrosome proteome than previously reported, comprising known and novel components. The advancement was made possible by the availability of affinity purified antibodies form the Human Protein Atlas (HPA) project (Barbe et al, 2008) and by the development of a novel MS-based proteomics method, which improved the confidence in identifying genuine organelle components from a background of non-specific proteins. Candidates were validated by image analyses of cells stably expressing fluorescently tagged fusion proteins at the endogenous level employing BAC TransgeneOmics (Poser et al, 2008). Additional microscopy and MS-based experiments revealed the dynamic and asymmetric association of novel proteins with the mother and daughter centriole. The resulting spatiotemporal proteomics data are likely to provide leads to further insight into the functional significance of centrosome-associated proteins. Results Complementary proteomics methods identify novel centrosomal proteins To evaluate the dynamic composition and localization of the centrosome proteome with the ultimate goal to better understand its structure and function we carried out two complementary screens. In the ‘MS-screen’, we developed an MS-based proteomics method to selectively identify centrosomal proteins from a background of unrelated proteins typically present in preparations of biochemically purified centrosomes. In the ‘HPA-screen’, we identified additional components localizing to the centrosomes by evaluating confocal images of three different cell lines stained with HPA antibodies (Barbe et al, 2008). An outline of the two screens and the follow-up experiments performed to validate and further characterize the identified candidate proteins are summarized in Figure 1A. The resulting data are visualized as a dynamic network of proteins associated with the centrosome and its substructures (Figure 1B). Figure 1.Mapping the centrosome proteome. (A) Schematic outline of the mass spectrometry and microscopy-based screens carried out to identify and characterize candidate centrosomal proteins. In the MS-screen (left), centrosomal proteins were identified by the PCP-SILAC method (see Figure 2) and validated by co-localization experiments using antibodies and GFP-tagged proteins. In the HPA-screen (right), images of three different cell lines were evaluated for centrosomal staining using human protein atlas (HPA) antibodies. In follow-up experiments, we estimated the abundance, measured the turnover, and determined the subcellular localization of the identified proteins. The number of ‘profiled’ proteins refers to those quantified in all fractions out of those quantified in at least one fraction. The number of ‘MS-candidate’ and ‘MS-known’ refers to those annotated as novel or known centrosomal proteins, respectively, out of those scored as centrosomal proteins by the PCP-SILAC method (*) or those tested by microscopy. References to the relevant tables and figures are shown in brackets. (B) Dynamic protein localization network of the identified proteins. The network is manually curated using the software ‘Cytoscape’ and protein localization data extracted from this study and from the literature. The shape of the nodes indicates our classification of proteins as known or novel or identified by the MS-screen or the HPA-screen. The colour of the nodes indicates the percentage of metabolic isotope labelling after 20 h (protein turnover). A green node border indicates proteins validated in this study by fluorescence microscopy. For simplicity, each protein is shown with a single localization pattern. Download figure Download PowerPoint MS-screen: PCP-SILAC increases the confidence in identifying novel centrosomal proteins We have previously characterized the protein composition of the human centrosome by using protein correlation profiling (PCP) (Andersen et al, 2003). In this approach, proteins identified by MS are profiled from peptide intensity signals in several gradient centrifugation fractions and distinguished as genuine components when matching a consensus profile determined for known organellar proteins. The principle idea of this method is powerful to sort out unrelated proteins, but the inaccuracy of label-free protein quantitation diminishes its performance; in particular for proteins identified by a few peptides. Thus, to further advance our ability to classify organelle proteins, we aimed at increasing the accuracy of protein quantitation in PCP by introducing stable isotope labelling by amino acids in cell culture (SILAC) (Figure 2A). This was achieved by generating an unlabelled matching internal standard that could be mixed with the corresponding fractions prepared from one or two differentially isotope-labelled cell populations. The method, termed PCP-SILAC, has features distinct from related strategies based on chemical isotope labelling by ICAT (Dunkley et al, 2004; Sadowski et al, 2006), iTRAQ (Borner et al, 2006; Yan et al, 2008), and strategies based on subtractive proteomics (Yates et al, 2005). Figure 2.Identification of centrosomal proteins by PCP-SILAC. (A) Schematic outline of the PCP-SILAC method used to distinguish centrosomal proteins from a background of co-purifying proteins. Centrosomes were isolated by sucrose gradient centrifugation from isotope-labelled and unlabelled cells. The six centrosome-containing fractions collected from the unlabelled cells were pooled to generate an internal standard, which was distributed into the six corresponding fractions collected from the labelled cells before processing these samples for MS analysis. (B) The enrichment of proteins relative to the internal standard is illustrated by the mass spectra of a single peptide (DFLQETVDEK) from the centrosomal protein CEP135 in fractions 1–6 where the peptide isotope clusters are marked by a triangle for signals representing the unlabelled internal standard (light isotope-labelled peptide) and by an asterisk for signals representing the sample in each fraction (heavy isotope-labelled peptide). (C) The enrichment profile of CEP135 was calculated from the isotope ratios shown in (B). (D) Profiles of 32 known centrosomal proteins and the resulting average consensus centrosomal profile. (E, F) Profiles of the DFLQETVDEK peptide from CEP135 and the consensus set of centrosomal proteins were determined from an independent experiment using only four fractions. The 32 proteins co-eluting in both experiments are included in Supplementary Tables S1 and S2). Download figure Download PowerPoint In practice, two centrosome preparations were isolated in parallel from asynchronously growing human cells cultured in medium containing either normal lysine (Lys0) or 13C615N2 isotope-labelled lysine (Lys8). Fractions collected after the final sucrose gradient centrifugation were tested for the presence of centrosomal proteins by MS analysis of peptides derived from in-solution digests of aliquots taken from each fraction (data not shown). The analysis identified six fractions with detectable levels of centrosomal proteins. These fractions collected from Lys0-labelled cells were mixed to generate a common internal standard for peptide isotope ratio determination. Aliquots of the internal standard were distributed into the corresponding six centrosome-containing fractions collected from Lys8-labelled cells. Proteins in these six samples were then separated by one-dimensional gel electrophoresis, in-gel digested with endoproteinase Lys-C, and the resulting peptides analysed by LC-MS (see Materials and methods). Mass spectra of the peptide DFLQETVDEK derived from the centrosomal protein CEP135 displayed a large analyte to internal standard ratio (Lys8/Lys0) for the peak centrosomal fraction as compared with spectra of the corresponding peptide in the other fractions (Figure 2B, panel 2). The six isotope ratios allowed us to calculate a protein enrichment profile as the median of the Lys8/Lys0 isotope ratio for all lysine-containing peptides identified for CEP135 in each of the six samples (Figure 2C). Protein enrichment profiles were then calculated for all proteins. A group of 32 known centrosomal proteins were selected for inter-experiment comparison and for determination of a consensus profile for organelle classification (Supplementary Table S1). Profiles of the centrosomal proteins closely followed the CEP135 profile and demonstrate that accurate enrichment profiles can be obtained by PCP-SILAC (Figure 2D). A second independent PCP-SILAC experiment with four fractions and inverted isotope labelling demonstrated that the method can be performed with a variable number of fractions and reproducibly identify centrosomal proteins with a narrow distribution of profiles (Figure 2E and F; Supplementary Table S2). In a third experiment, we explored the ability of PCP-SILAC to profile simultaneously the enrichment of proteins in two independent centrosome preparations using a third preparation as a common internal standard. The correlated distributions between two different gradients were expected to further increase the confidence in organelle classification. To this end, three cell populations were labelled with different isotopes. The centrosome-containing fractions prepared from unlabelled cells were mixed and used as the common internal standard for the corresponding fractions prepared from each of the two labelled cell populations (Supplementary Figure S1A). The set of 32 known centrosomal proteins were represented by a total of 4661 peptide ratios in the peak fraction and resulted in a narrow distribution of profiles in both experiments (Figure 3A and B). The consensus profiles derived from these data were compared with the profiles of proteasomal and ribosomal subunits, representing co-purifying contaminants residing in structures of different sizes. The profiles were clearly separate from the consensus profiles and displayed consistently altered fractionation behaviour for all proteins in these structures (Figure 3C–F). A goodness of fit was determined as the Mahalanobis distance from the centrosomal consensus profiles, which take into account the variance and the covariance of the measured ratios. Distance scores 15) (Figure 3G; Supplementary Table S4). Moreover, only three apparent false positive proteins (ALDOA, ALDOC, and ADSL) had distance scores <9. These data demonstrate that the double PCP-SILAC experiment has indeed the ability to distinguish organelle proteins from a background of unrelated proteins with a high degree of confidence on the basis of correlated profile distributions. Data derived from this experiment also demonstrated a clear gain in the sensitivity and specificity of the PCP-SILAC method to distinguish true centrosomal proteins from a large background of unrelated proteins as compared with its label-free version (Supplementary Figures S3 and S4). Importantly, the relative enrichment profile of 1318 proteins quantified in the 2 × 5 fractions revealed a group of 150 proteins that fulfilled the stringent criteria of distance scores <9 in both experiments (Figure 3G). With few exceptions, this list comprises the majority of known centrosomal proteins (110 proteins) including the 23 novel proteins reported in our previous study (Andersen et al, 2003) (Table I; Supplementary Tables S3 and S4). Figure 3.Identification of centrosomal proteins by the double PCP-SILAC experiment. (A, B) Centrosomes were isolated by sucrose gradient centrifugation from three different isotope-labelled cell populations to profile the elution of proteins in two separate preparations simultaneously in a single experiment using one of the preparations as an internal standard (see outline of the double PCP-SILAC experiment in Supplementary Figure S1). The profiles for 32 known centrosomal proteins follow a narrow enrichment profile in both preparations and demonstrate that these proteins co-elute. The shape of the profiles is not critical for organelle classification but reflects a shift in the elution of proteins between the two experiments. (C–F) The profiles of proteasomal and ribosomal subunits obtained from the same data set are distinct from the centrosomal consensus profiles. (G) An organelle classification score was calculated as the Mahalanobis distance between the centrosomal consensus profile and all other proteins with a complete enrichment profile in the double PCP-SILAC experiments 3A and 3B. Known centrosomal proteins and likely candidates clustered in a region with distance scores <9 as compared with, for example, proteasomal and ribosomal subunits with high distance scores. Download figure Download PowerPoint Table 1. Candidate centrosomal proteins identified by PCP-SILAC Gene name Suggested new name Localization Turn over (%) Substructure PCP-SILAC score GFP HPA KIAA0562 CEP104 7.8 × 95 Centriole IFFO2 4.7 — 94 CKAP2L 7.1 × 93 Spindle pole, spindle, midbody MIB1 6.4 × × 89 GFP: satellites, spindle poles HPA: centrosomal with some satellites AKNA 2.7 — 86 CCDC21 CEP85 2.3 × × 83 GFP: centrosomal, spindle poles HPA: nucleolar interphase, spindle poles C6orf182 2.6 — 83 CCDC14 6.1 × 77 Satellites FBXW11 3.0 × 75 Probably centrosomal, spindle pole MAP7D3 4.1 74 MPHOSPH9 3.0 — × 72 Centriole Albatross 4.8 × 72 Mother centriole, spindle pole SLAIN1 1.7 (×) — 71 Weak spindle CCDC123 CEP89 1.8 × × 71 GFP: near centrosomes, spindle poles HPA: satellites CCHCR1 2.5 — 71 CCDC102A 2.2 — 66 GARNL4 6.5 × 64 Centrosomal in some cells CCDC34 2.4 64 C3orf34 CEP19 5.0 × 64 Preferentially mother centriole C6orf204 1.9 (×) × 62 GFP: weak midbody and spindle HPA: spindle poles, possibly centrosomal KIAA1712 CEP44 3.0 × 60 Centrosomal (two dots), spindle poles, weak midbody, possibly spindle ANKRD26 2.8 × 58 Centrosomal, spindle poles SLAIN2 2.2 (×) × 58 GFP: very weak spindle, weak midbody HPA: centrosomal, spindle poles KIAA0753 3.5 × × 56 GFP: satellites, spindle poles, some midbody HPA: near centrosomes CCDC45 CEP45 3.9 × × 54 GFP: weak HPA: centrosomal (two dots), spindle poles C16orf63 6.2 × 50 Satellites around centrosome, spindle poles TCHP 2.3 × 49 Spindle, midbody, possibly weak centrosomal C1orf96 6.7 × 48 Midbody, possibly spindle and spindle poles CCDC46 CEP112 4.1 × 48 Centrosomal (two dots), around spindle poles in some cells C14orf145 CEP128 0.5 × 40 Mother centriole, spindle pole ACTR1B 8.7 × 38 Spindle poles, possibly centrosomal ACTR10 5.3 34 CCDC41 3.0 (×) 28 C7orf47 3.8 22 RTTN 6.4 — 21 NOG 3.8 19 PRKACB 3.3 × NA Satellites, possibly midbody WDR90 3.3 — NA IIP45 5.0 NA IRAK1BP1 6.0 — — NA Novel proteins identified with low PCP-SILAC organelle classification score were validated by fluorescence microscopy using human protein atlas antibodies (HPA) or cell pools stable expressing fluorescently tagged proteins (GFP), where indicated. Protein turnover rates were calculated as the percentage of stable isotope labelling after 20 h. Novel factors are termed CEP and a number, where CEP stands for centrosomal protein and is followed by the Mr calculated from the full-length sequence. For additional information, see Supplementary Table S4. Image analysis of cells stably expressing GFP-fusion proteins or stained with antibodies confirms centrosome localization for candidate proteins identified by PCP-SILAC To confirm the in vivo subcellular localization of the identified MS-candidates at any stage of the cell cycle, we stably expressed N- or C-terminally tagged green fluorescent fusion proteins at their endogenous levels in HeLa Kyoto cells using BAC TransgeneOmics (Poser et al, 2008). The resulting cell pools were immunostained with anti α- or γ-tubulin antibodies to visualize centrosomes and anti-GFP antibody to enhance the fluorescence signal of the tagged proteins. In vivo localization to centrosomes and spindles were observed for 14 of 27 tested candidate proteins (Figure 4, Supplementary Figure S5; Table I, Supplementary Table S4). MS-candidate proteins were also confirmed by immunofluorescence microscopy in U-2 OS cells using HPA antibodies. Localization to centrosomes were observed for 11 of 16 tested candidate proteins (MPHOSPH9, C6orf204, SLAIN2, CCDC46, Albatross, C14orf145*, CCDC45*, MIB1*, KIAA0753*, CCDC21*, and GARNL4). Candidates marked by an asterisk were also confirmed in HeLa cells stably expressing the corresponding GFP-tagged fusion protein. Images are available at http://www.cebi.sdu.dk/CepDB. In general, we observed a goo
Referência(s)