Identification of Functional Marker Proteins in the Mammalian Growth Cone

Identification of functional marker proteins in the mammalian growth cone

Motohiro Nozumia,b, Tetsuya Toganoa,c, Kazuko Takahashi-Nikia, Jia Lua,c, Atsuko Hondaa,b, Masato Taokad,e, Takashi Shinkawad,e, Hisashi Kogaf,g, Kosei Takeuchia,b, Toshiaki Isobed,e, and Michihiro Igarashia,b,1

Divisions of aMolecular Cell Biology and cOphthalmology, Graduate School of Medical and Dental Sciences, and bTransdisciplinary Research Program, Niigata University, 1-757 Asahi-machi, Chuo-ku, Niigata, Niigata 951-8510, Japan; dDepartment of Chemistry, Graduate School of Science, Tokyo Metropolitan University, 1-1 Minami-Osawa, Hachioji, Tokyo 192-0397, Japan; eCore Research for Evolutional Science and Technology, Japan Science and Technology Agency, Sanbancho 5, Chiyoda-ku, Tokyo 102-0075, Japan; and fChiba Industry Advancement Center and gCollaboration of Regional Entities for the Advancement of Technological Excellence Program, Kazusa DNA Research Institute, 2-6-7 Kazusa-Kamatari, Kisarazu, Chiba 292-0818, Japan

Edited by Lynn T. Landmesser, Case Western Reserve University, Cleveland, OH, and approved August 24, 2009 (received for review April 18, 2009) Identification of proteins in the mammalian growth cone has the mammalian growth cone functions, in particular interactions or potential to advance our understanding of this critical regulator of relationships among signaling pathways, at least in part because of neuronal growth and formation of neural circuit; however, to date, an insufficient understanding of what key molecules are important only one growth cone marker protein, GAP-43, has been reported. for function (1, 2). Here, we successfully used a proteomic approach to identify 945 Indeed, even what proteins might be present, i.e., molecular proteins present in developing rat forebrain growth cones, including markers of the growth cone, is a relatively unexplored territory, highly abundant, membrane-associated and actin-associated pro- particularly as compared with our understanding of synaptic mo- teins. Almost 100 of the proteins appear to be highly enriched in the lecular marker proteins. In the case of adult synapses, a large growth cone, as determined by quantitative immunostaining, and for number of marker proteins localized to various sublocations in the 17 proteins, the results of RNAi suggest a role in axon growth. Most synapse are known (5, 6). These include proteins localized to of the proteins we identified have not previously been implicated in synaptic vesicles, presynaptic and postsynaptic membranes, active axon growth and thus their identification presents a significant step zones, and postsynaptic density (5, 6). forward, providing marker proteins and candidate neuronal growth- Without a doubt, identification of synaptic marker proteins has associated proteins. markedly enriched our knowledge of the molecular machinery GAP-43 ͉ proteomics ͉ RNAi ͉ neuronal growth-associated proteins ͉ underpinning synaptic structures and functions (5, 6). This stands axon guidance in contrast to the very small amount of marker protein information available for the growth cone. Indeed, GAP-43 (growth-associated protein 43-kDa; neuromodulin) (7) is the only previously identified euronal growth cones execute important steps in neural wiring, functional molecular marker of growth cones (ideally, a ‘‘functional including axonal growth and pathfinding, and accurate synap- N molecular marker’’ would be a protein that is both highly concen- togenesis (1, 2). Whether or not an injured axon in the adult neuron regenerates or degenerates depends on surrounding factors that trated in the growth cone and involved in axon growth). GAP-43 is either maintain or inhibit formation of growth cone-like structures, concentrated in the growth cone, highly expressed, transported consistent with a critical role for growth cones in neural plasticity when a damaged axon can regrow, and involved in sprouting (7). and repair of the adult brain (3, 4). It follows, then, that identifying the Although it is concentrated in the growth cone, GAP-43 is also molecular basis of growth cone behavior will be critical to understand- detectable in the axon (7). Given the severely limited amount of ing the cellular mechanisms of higher brain functions. A significant information about functional markers concentrated in or localized barrier to this understanding, however, is that little is known about to growth cones, it follows that identification of putative novel the molecular makeup of the mammalian growth cone. functional molecular markers of the mammalian growth cone Classical genetic approaches to identifying key players in brain would be extremely valuable to further study. function have been informative in model systems such as Caeno- To help gain a systemwide understanding of the molecular rhabditis elegans and Drosophila. For example, identification of components of growth cones and identify novel molecular marker mutations in specific C. elegans and Drosophila genes contributed candidates, we introduced proteome-scale approaches that have greatly to the discovery and functional characterization of axon been used successfully to identify large numbers of proteins present guidance molecules in the mammalian brain, such as netrin and in other specific cells or tissues, thus contributing to a more global semaphorins (1, 2). But these are not the only useful tools with understanding of the functions of those cells or tissues (8–11). We which to dissect growth cone functions, and they have significant succeeded in identifying 945 species of proteins in growth cone limitations in terms of their ability to further our understanding of particle (GCP) and/or a growth cone membrane membrane (GCM) the complete picture of the molecular machinery that controls (12–14). By combining the results of immunolocalization and RNAi mammalian growth cones (1, 2). Among these limitations are that studies with proteomics, we provide evidence that 17 of the proteins similar studies are not feasible in mammals and mammalian growth we identified are highly concentrated in the growth cone area and cone functions are thought to be much more complicated than growth regulate axonal growth, concluding that they are unique functional cone functions in C. elegans and Drosophila. Additionally, the molecular molecular markers of the growth cone. redundancy involved in growth cone functions in the mammalian CNS is likely to be much larger than in model organisms. Despite the knowledge gap, however, we know of no previous Author contributions: K.T., T.I., and M.I. designed research; M.N., T.T., K.T.-N., J.L., A.H., report that applies a systematic approach to identification of M.T., and T.S. performed research; H.K. contributed new reagents/analytic tools; M.N., mammalian growth cone proteins. However, cell biological studies M.T., T.I., and M.I. analyzed data; and M.I. wrote the paper. combined with pharmacological tools to detect second messengers The authors declare no conflict of interest. ϩ (Ca2 or cyclic nucleotides) or the cytoskeleton (i.e., F-actin or This article is a PNAS Direct Submission. microtubules) have revealed some of the signaling pathways in- 1To whom correspondence should be addressed. E-mail: [email protected]. volved in control of mammalian growth cone behavior or guidance. This article contains supporting information online at www.pnas.org/cgi/content/full/ Nonetheless, we are far from having a complete understanding of 0904092106/DCSupplemental.

17210–17215 ͉ PNAS ͉ October 6, 2009 ͉ vol. 106 ͉ no. 40 www.pnas.org͞cgi͞doi͞10.1073͞pnas.0904092106 Downloaded by guest on September 26, 2021 Fig. 1. Proteomic analysis of GCPs and adult A B GCP(629) GCM (592) synaptosomes. (A) Electron micrograph of GCPs. The GCP fraction was prepared by using the method described by Gordon-Weeks (14) (see SI 353 276 316 Text). The criterion for a GCP was a particle with a diameter of Ϸ1–2 ␮m and the presence of small clear vesicles. (Scale bar: 10 ␮m.) (B) GCP proteins C and proteins found in a membrane subfraction of GCP (GCM). In total, 629 GCP and 592 GCM proteins were identified, with 276 proteins common to both. Note that 316 proteins were identified only in the GCM subfraction. (C) Comparison of the GCP/GCM proteome with the proteome of adult synaptosomes. A total of 1,407 synaptoso- Number of proteins (%) D 0 5 10 15 20 25 30 mal proteins were identified, for about twice as many as were identified in GCP or GCM. (D) Cat- Metabolic enzyme 23.0 Cytoskeletal 14.8 egorization of GCP, GCM, and synaptosomal pro- Signaling 7.3 teins. Categories are color-coded as follows: met- GTP-bindingGTP binding 10.1 Ion transport/Channel 6.9 E abolic enzymes, violet; cytoskeletal proteins, Membrane traffic 5.8 60 navy; signaling (except GTP-binding or phosphor- Kinase/Phosphatase 4.4 50 GCP > GCM Receptor 1.0 ylation), blue; proteins involved in guanine nucle- 40 GCP Chaperone 5.4 otide cycling (including GTP-binding proteins), Proteasome/Ubiquitination 3.8 GCP 30 GCM Cell adhesion 2.6 20 Synaptosome cyan; ion transport/channels, green; membrane Ribosomal 4.6 10 traffic, lime; kinases or phosphatases, yellow; re- Protein translation 1.5 of peptides Number Miscellaneous 8.8 0 ceptors, orange; chaperone, brown; proteasome/ ubiquitination-related proteins, maroon; cell ad- Metabolic enzyme 12.6 hesion proteins, red; ribosomal, magenta; Cytoskeletal 9.4 Signaling 7.9 proteins involved in translation, olive; miscella- GTP-binding 11.2 neous proteins (including organelle-specific or Ion transport/Channel 10.3 Membrane traffic 8.7 60 undefined), gray. Note that the ratio of cell adhe- Kinase/Phosphatase 3.5 50 GCP < GCM sion molecules, receptors, and transporters/ Receptor 8.7 40 Chaperone 4.0 channels is higher in GCM than in GCP, consistent 30 Proteasome/Ubiquitination 0.9 GCM with enrichment of membrane components in

Cell adhesion 6.5 of ber peptides 20

m GCM. See Table S1, Table S2, and Table S3 for a Ribosomal 4.5 10 Protein translation 0.9 Nu detailed report. (E) The major proteins of GCP or Miscellaneous 10.9 0 GCM as compared with synaptosomal proteins as Metabolic enzyme 24.9 indicated by the number of identified peptides. Cytoskeletal 11.4 Among proteins for which 12 or more peptides Signaling 10.2 GTP-binding 7.6 were identified, we chose the subset identified as Ion transport/Channel 7.5 peptides at least twice as many times in GCP or in Membrane traffic 6.6 Kinase/Phosphatase 4.9 GCM than in synaptosomes. The number of pep- Receptor 3.0 tide identifications is shown. (Upper) GCP Ͼ GCM. Chaperone 2.7 Ͼ Proteasome/Ubiquitination 2.5 Synaptosome (Lower) GCM GCP. Color-coded by functional Cell adhesion 2.1 category as in D. Note that the number of identi- Ribosomal 0.6 Protein translation 0.6 fied peptides is an indicator of relative protein Miscellaneous 15.4 levels.

Results number of proteins are newly synthesized and added to synaptic Large-Scale Identification of Proteins in Rat Brain Growth Cones. Our components for synaptic transmission after synaptogenesis. We first goal was to identify a large number of proteins expressed in succeeded in identifying 96 and 141 proteins in the GCP or GCM, growth cones, including proteins common to many cell types and respectively, that were not found in the synaptosomes (Fig. 1C). proteins involved in growth cone-specific functions. To do this, we first separated proteins from the developing rat forebrain via Proteins Identified by Proteomics Analysis. We next used bioinformat- subcellular fractionation to obtain a GCP fraction (Fig. 1A). We ics analysis to categorize the proteins into functionally related then obtained a GCM via hypotonic treatment of the GCP fraction groups (Fig. 1 C–E and Table S1, Table S2, and Table S3). We (see details in SI Text) with the goal of identifying minor membrane included synaptosome data in our analysis, because the presynaptic proteins in the growth cone. Subsequently, we used multidimen- axon terminal is the adult counterpart of the growth cone. The sional liquid chromatography-tandem mass spectrometry (LC/MS/ proteins were in the following functional categories: those required MS) to identify unique proteins in the sample, because the method for cytoskeletal reorganization, involved in vesicular trafficking, has been shown to be suitable to large-scale protein identification and related to signal transduction, including protein kinases, phos- (15, 16). The method proved powerful in this study as well, with a phatases, and G proteins (2, 4). As expected, previously identified total of 945 species of proteins identified in GCP and GCM (Fig. key players in growth cone function were identified in the study NEUROSCIENCE 1B). Because Ͻ50 of the proteins were previously known to be (including MAP1B and myosin II heavy chain). But intriguingly, expressed in the mammalian growth cone, identification of this most proteins in each category were newly identified (i.e., not large number of proteins provides a wealth of molecular informa- previously reported as GCPs) (2, 4, 15) (Fig. 1 D and E; see Table tion about mammalian growth cones (2, 4, 17). For comparison, we S1, Table S2, and Table S3). also analyzed adult synaptosomes, the counterpart of the growth As expected, the GCP fraction contained both cytosolic and cone, and identified 1,407 species of synaptosomal proteins (i.e., membrane-bound proteins; the GCM fraction was enriched for twice as many as we found for the GCP and GCM). Approximately membrane and membranous organelle-associated proteins; and the 65% of the synaptosomal proteins we identified are not found in the set of proteins found in the GCP fraction but not the GCM fraction GCP or the GCM sets (Fig. 1C), which may be because a large was enriched for cytosolic proteins (Fig. 1D). As shown in Fig. 1D,

Nozumi et al. PNAS ͉ October 6, 2009 ͉ vol. 106 ͉ no. 40 ͉ 17211 Downloaded by guest on September 26, 2021 10 Fig. 2. Immunoﬂuorescence quantiﬁcation of GCP. 9 Horizontal axis, FI ratio (growth cone/distal axon), Lon- Ank2 Macf1 gitudinal axis, area ratio (growth cone/distal axon).

8 The horizontal axis shows the GC accumulation index F-actin (a ratio of 1.0; the vertical black dotted line indicates Odz2 7 Nrxn1 that a given protein is evenly distributed in the distal axon versus the growth cone). The FI ratio for GAP-43 Cap1 Pacs1 Munc-18 (Gap43; 1.315) is shown as a blue dotted line. Proteins 6 Igsf4 Picalm Ptprd Cotl1 Ncdn in the upper right region of the graph are more con- Clptm1 Calnexin PP2A Rab3a Syt RKM23 PAR3B Rab35 Capzb Vcp Camkv Ndrg1 centrated in the growth cone than in the axon. Many 5 Sept2 Ppfia1 Gng2 Marcksl1 Inexa Stx1 Rcp Hist4 GAP-43 ClaspSv2a Tpbg Snap29 of these are actin-binding proteins and proteins in- Tip120 Ctnna2Crmp4 Pclo Ctnna1 Pak Arhgdia PSD-93 Farp2 Palm Atp6v1a Rtn4 Stmn1 volved in vesicular trafﬁcking. The FI ratio of each Strap Crmp3GnaoFapb5 4 Cd47 Cofilin Sv2b Syn2 Xlas Lphn3 Rtn1 Rab18TmodStx7 Cltc Fabp7 Gng3Scamp Ap2b1 Ptprs Fish Destrin protein was tested by using the Kruskal-Willis statisti- Lasp1Letm1 Calm Area ratio (GC/Axon) ratio Area Dynamin Cyfip1 Vamp Rab9 Gdi1M6a Basigin Ripx Scg10 cal test (46) with GAP-43 as the comparison point. The Tau Arp1 Crmp5 Git1 Pin Rac 3 Ap180 4.1NGnai214-3-3e Snap25 CAR Myo5a proteins were grouped based on the two-sided 95% Spg3a V-1 Ktn Hsp110Gnb2 Arvcf Ras Tubb3 C1Crmp1 Ap2a1 Tmsb4x Ctnnb1 Rala Dclk1 Fascin Stx8 conﬁdence interval, i.e., was it higher than, similar to, Dcx Caspr2 Prph Camk2 Crmp2 2 Plxnc1 Lyric Stx16 Celsr3 or less than that of GAP-43 (shown in red, blue, and BIP Csnk2 Lamp1 Atp1a1 black, respectively). Note that as expected, F-actin (as Map1b 1 NF200 detected with rhodamine phalloidin; in red), which is ␤ Tuba1 concentrated in the growth cone, and -tubulin 0 (green), which is at higher levels in the axon than in the 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1. 4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 growth cone, are distant from each other on the graph. Fluorescent intensity ratio (GC/Axon) See Table S4 for detailed information.

the set of membrane-associated proteins we identified included cell commonly expressed proteins such as metabolic enzymes and adhesion molecules (2.6% in GCP and 6.5% in GCM), receptors molecular chaperones so that we could instead focus on proteins and receptor-like membrane proteins (1.0% in GCP and 8.7% in that may be particularly relevant to growth cone-specific functions. GCM), and transporters/channels (6.9% in GCP and 10.3% in In total, we looked at the distributions of 131 proteins (i.e., Ϸ15% GCM). Components of ubiquitin proteasome were detected only of the proteins we identified). The data confirm that in cultured rat in the GCP fraction (Fig. 1D). Synaptosomes contain a larger cortical neurons all of the proteins we tested are detectable in the numbers of metabolic enzymes, but the percentages of ribosomal growth cone area (Fig. 2 and Table S4). Indeed, no proteins we proteins and local protein translation proteins detected in synap- tested could be detected in other axonal regions but not in the tosomes were lower than in GCP (Fig. 1D). growth cone, suggesting a very low false-positive rate and validating In our shotgun proteomic analysis, we tentatively assumed that our overall approach. In addition, our proteomic data in GCP or the number of times a given peptide is identified correlates with the GCM contained no transcription factors, suggesting that contam- abundance of the protein in cells (18). In Fig. 1E, we report those ination with nuclear components is also negligible (Fig. 1D, Table proteins for which peptides were independently identified 12 or S1, and Table S2). more times in GCP or GCM (together, these comprise 50% of the peptides identified in GCP or GCM), and for which the abundance Proteins More Concentrated in the Growth Cone Than in the Distal Axon. in GCP or GCM was 2-fold or more compared with levels in We next sought to determine the extent to which the proteins synaptosomes. These appear to be the most highly abundant identified in our study are specific or locally specific to the growth proteins in the GCP and GCM fractions, and thus we defined cone. To do this, we compared the distributions of the proteins in proteins appearing 12 or more times as ‘‘major proteins’’ in the GCP growth cones with their distribution in distal axons. To the extent or in GCM fractions. These include cytoskeletal components that the method is quantitative, we were also able to compare the (tubulins, the microtubule-associated protein MAP1B, dynein relative concentrations of proteins in growth cones versus distal heavy chains, and myosin heavy chains), collapsin response medi- axons (Fig. 2 and Table S4). We defined the growth cone accu- ator proteins (CRMPs), catenins, 14-3-3 proteins, and G␣ proteins mulation index as the ratio of fluorescence intensity (FI) in the (namely, Gq, Gi1, and Gi2). The known or predicted biochemical growth cone compared with that in the distal axon (Fig. 2, Table S4, and/or biological activities of the major proteins are consistent with SI Text, and Fig. S1). We also used another index, i.e., the area ratio, functional relevance in growth cones. Moreover, identification of to examine the distribution patterns of each protein (Fig. S2). The the translation factor elongation factor 1␣ is consistent with the growth cone accumulation index is an indication of the relative level finding that local protein synthesis is important for growth cone of protein accumulation in the growth cone. By applying the behavior (19). Additionally, identification of CRMP family mem- statistical Wilcoxon rank-sum test to our results, facilitating strict bers (CRMP4b, CRMP1, and CRMP5; Fig. 1E) as the most classification of the examined proteins as compared with GAP-43, abundant GCP proteins in growth cones correlates well with a our quantification of the systematic immunostaining approach report that CRMP2 acts as a tubulin adapter protein and is involved using this index revealed that as many as 69 proteins identified by in axon formation (20). proteomics were detected at higher levels in the growth cone area than in the distal axon. These proteins appear to be at much higher Verification of Growth Cone Localization Suggests a Negligible False- levels in growth cones than the currently established growth cone Positive Rate. We next wanted to determine the specificity of our marker protein GAP-43 (7) (Fig. 2, shown in red). We also found proteomics approach,; i.e., to determine the false-positive rate. that for 33 proteins the statistical error areas overlap with that of Generally, a comparison of a given fraction should be made to GAP-43, thus we categorize this set of proteins as concentrated in another biochemical fraction. However, no fractions from the the growth cone to a similar degree as is GAP-43 (Fig. 2, shown in developing brain can be prepared with comparable purity to the blue). GCP or GCM fractions. Thus, to facilitate generation of a comparison dataset, we performed systematic immunodetection of a RNAi Analysis Reveals Relevance to Axon Length and Functional Markers subset of the proteins in cultured cortical neurons (see Table S4, of the Growth Cone. We used an RNAi-based approach to test the Table S5, Table S6, and Table S7). We excluded ubiquitous or roles of marker protein candidates in axonal growth. Activity-

17212 ͉ www.pnas.org͞cgi͞doi͞10.1073͞pnas.0904092106 Nozumi et al. Downloaded by guest on September 26, 2021 A 120 Most of the candidates listed in Fig. 3A revealed previously undetected associations with growth cones and were functionally 100 related (Table 1). Sept2, Cap1 (a G-actin-binding protein), Snap25a, and Cyfip1 have been suggested to play roles in growth 80 cone behavior, based on studies in PC12 cells or chick or Drosophila neurons (21–24), but their precise roles in the mammalian growth 60 cone are not known. For the two GTP-binding proteins (Gnai2, 40 Gnao1) and the regulator (Farp2), involvement in regulation of a

Axonal length (%) Axonal growth cone response to inhibitors has been reported, although it 20 is not known whether they are necessary or indispensable for axonal

113 138 64 75 74 73 69 410 169 56 28 45 55 72 78 30 53 322 39 growth (25–27). To the best of our knowledge, none of the other 10 0 proteins were previously reported to be growth cone regulators in mammalian cells or invertebrate model organisms such as C. elegans or Drosophila, although their paralogues may be related to neurite growth [for example, syntaxin-1A (28) and syntaxin-3 (29), paral- B ogues of Syx7]. We briefly summarize the current information about these proteins in Table 1. At most 3 of the 17 proteins identified in our study and tested with RNAi have been previously implicated in axonal growth, suggesting that we succeeded in efficient identification of additional molecules involved in growth cone functions. In total, the results of RNAi analysis point to 17 proteins with higher or similar FI ratios than GAP-43, making them strong candidates for novel neuronal growth-associated proteins (nGAPs; refs. 4 and 30). Fig. 3. Identification of nGAPs by RNAi. (A) Genes affecting axonal growth. The growth cone is comprised of morphologically and function- Roles for the identified proteins in growth cone activity were assayed by ally distinct regions referred to as the central (C) and peripheral (P) looking for RNAi-induced reduction of axonal growth. RNAi was performed as regions (31). The C region is enriched in vesicles and microtubules described (45). The eight proteins to the left of the hatched line have FI ratios and is probably involved in membrane expansion for axonal growth. superior to GAP-43 as judged statistically by using the Kruskal-Willis test (red; The P region is enriched in actin filaments and probably generates also shown in red in Fig. 2), and the nine proteins to the right of the hatched motive force. Using tubulin as a marker for the C region (see Fig. line have FI ratios similar to that of GAP-43 as judged by the same test. The axonal lengths of EGFP-positive neurons (no siRNA) were used as the control S3), we classified the marker proteins into four groups: group I, (blue; also shown in blue in Fig. 2). All siRNAs (except GFP) have P Ͻ 0.002 in localized predominantly in the P region; group II, detected in both Wilcoxon rank-sum test (vs. control) (46). The data are shown as mean Ϯ SEM. regions; group III, localized predominantly in the C region; and The number of neurons measured is shown in at the bottom of each bar. (B) group IV, specifically localized in the C region (Fig. 3B; see also Classification of candidate growth cone marker proteins by immunolocaliza- Figs. S3 and S4). tion. We defined the C and P domains of a growth cone by using quantitative The patterns of localization we observed were somewhat differ- analysis of immunostaining images (diagram at top; see SI Text and Fig. S2). ent from what might have been predicted. For example, Pacs1 has We classified the proteins into four groups: group I (ex. Pacs1), predominantly been reported to be involved in organelle sorting but in axons, Pacs1 localized in the P region (C [dlt ]P); group II (ex. Syx7), detected in both the C localizes to the P region, where F-actin is enriched (Fig. 3B). A and P regions (C Ӎ P); group III (ex. Gnai2), predominantly localized to the C ϾϾ putative soluble adapter protein, Strap, which has been reported as region (C P); and group IV (ex. Rtn1), specifically localized in the C region ␤ (C). In each case, the left diagram is summary of a typical protein distribution downstream of TGF- signaling (32), and Clptm1, an unknown for each group. Immunofluorescence micrographs of anticandidate protein transmembrane protein (33), are also localized in the P region. In antibodies detection in cultured rat cortical neurons are shown in A. Magenta contrast, Sept 2 is detected near the tubulin-positive region despite and green show antigen protein and ␣-tubulin views, respectively. The far the fact that it was previously reported to be found in the P domain views show the merged image. Three groups (groups I-III) are also shown in the in PC12 cells (21). Only Rtn1, an ER protein and putative mem- legend for Fig. S4. Note that ␣-tubulin is primarily detected in the axon, brane trafficking regulator (34), was specifically localized in the C although it is also detectable in the central region of the growth cone. See region, making it potentially useful as a C-region marker. Table 1 for a detailed characterization of each protein and abbreviated names. (Scale bars: 10 ␮m.) Discussion The growth cone is responsible for axon guidance and synaptogen- inducing axonal growth was assessed by measuring axonal length esis. Thus, understanding growth cone functions at the molecular (see SI Text; for confirmation of knockdown and specificity, see also level will contribute to our overall understanding of how neural networks form and are maintained (35). Using a proteomic ap- Fig. S1). We selected 68 genes for RNAi treatment and found that Ϸ disruption of 17 of them led to shorter axonal length, by application proach, we identified 1,000 proteins likely to be components of mammalian growth cones, including actin-associated proteins that of a stringent nonparametric test, i.e., the Kruskal-Willis test (Fig. may be involved in axon growth and motility (Figs. 1 and 2, Table 3A, Table 1, and Table S8). We categorize the 17 proteins as S1, Table S2, Table S3, and Fig. S4). The results of immunostaining putative functional growth cone markers (Table 1). Considering the suggest that several of the proteins we identified will serve as useful results of the quantitative immunostaining (Fig. 2), these proteins

markers for growth cones in the mammalian brain and validated our NEUROSCIENCE can be classified into proteins more concentrated than GAP-43 approach (Fig. 2). Most of the proteins we identified were not (proteins shown in red in Fig. 2) or similar to GAP-43 (proteins previously reported as growth cone-associated in mammalian or shown in blue in Fig. 2). Of these 17 proteins, there are five model systems. Our ability to identify such a large number of cytoskeletal proteins (Tmod2, Cap1, Cotl1, CapZb, and Sept 2), putative growth cone marker proteins seems remarkable, particu- four membrane trafficking proteins (Pacs1, Stx7, Snap25a, and larly given that previous to this study, and despite a decade of work Rtn1), two GTP-binding proteins (Gnai2, Gnao1), two proteins by many laboratories, there has been only one marker available for involved in small G protein signaling (Farp2 and Cyfip1), three studies (namely, GAP-43) (7). The results of our analysis should signaling adapter proteins (Strap, FABP7, and Crmp1), and one help to advance our understanding of the molecular machinery receptor candidate (Clptm1). underlying growth cones and their functions (36).

Nozumi et al. PNAS ͉ October 6, 2009 ͉ vol. 106 ͉ no. 40 ͉ 17213 Downloaded by guest on September 26, 2021 Table 1. Novel candidates for nGAPs National Center for Localization Biotechnology Abbreviated in growth Information D. melanogaster C. elegans (WormBase name cone RefSeq mRNA no. (FlyBase gene ID) gene ID) Putative functions

Tmod2 I NM 031613 FBgn0082582; tmod WBGene00006581; Neuron-specific isoform of (tropomodulin) unc-94/tmd-1 tropomyosin, blocks the elongation and depolymerization of actin filaments Pacs1 I NM 134406 FBgn0020647; KrT95D WBGene00044077; Involved in the localization of tag-232 trans-Golgi network Rtn1 IV NM 053865 FBgn0053113; Rtnl1 WBGene00004336; ret-1 Associated with the endoplasmic (reticulon1) reticulum and are involved in membrane trafficking Snap25 III NM 030991 FBgn0011288; snap WBGene00004364; ric-4 t-SNARE protein; involved in vesicular fusion Stx7 II NM 021869 FBgn0033583; Syx7 WBGene00009478; A SNARE protein mediating fusion F36F2.4 of late endosomes Gnai2 III NM 031035 FBgn0001104; G-ia65A WBGene00001648; goa-1 Gi family protein; heterotrimeric G protein alpha Gnao1 III NM 017327 FBgn0001122; Goa47A WBGene00001648; goa-1 Go protein; heterotrimeric G protein ␣ Fabp7 III NM 030832 FBgn0037913; CG6783 WBGene00002258; lbp-6 Brain-type fatty acid-binding protein Cotl1 II NM 001108452 FBgn0030955; CG6891 WBGene00010664; Essential eukaryotic actin K08E3.4 regulatory proteins Cap1 II NM 022383 FBgn0028388; capulet WBGene00000294; cas-1 G-actin-binding; promotes cofilin-induced actin dynamics Capzb II NM 001005903 FBgn0011570; cpb (capping WBGene00000293; cap-2 F-actin capping protein protein beta) Sept2 III NM 057148 FBgn0011710; Sep1(Septin-1) WBGene00006795; unc-61 Cytoskeletal component interacting with actin-based structures Strap II NM 001011969 FBgn0034876; wmd (wing WBGene00001232; eif-3.I WD domain protein in TGF-␤ morphogenesis defect) signaling Clptm1 II NM 001106232 FBgn0031590; CG3702 WBGene00016469; A transmembrane protein with an C36B7.6 unknown function Cyfip1 II NM 001107517 FBgn0038320; sra-1 (specifically WBGene00001579; gex-2 Rac1-associated protein; link Rac to Rac1-associated protein 1) actin assembly driving lamellipodia formation Crmp1 III NM 012932 FBgn0023023; Crmp WBGene00000963; unc-33 May play a role in neuronal plasticity by transduction of signals from semaphorins Farp2 II NM 001107287 FBgn0051536; Cdep WBGene00001490; frm-3 Rho GEF protein; involved in (FERM domain family) semaphorin-signaling

For the proteins listed here, siRNAs directed against the corresponding genes result in signiﬁcant reduction of axonal length as compared with the control (see Fig. 3A). Markers detected at higher levels than GAP-43 are the ﬁrst seven shown; the rest were detected at similar levels (Fig. 3A; see also Fig. 2). The localization of each protein in growth cones is as shown in Fig. 3B (see also Fig. S4). Homologues in C. elegans or D. melanogaster are indicated (WormBase or FlyBase ID numbers and gene symbols).

The ability to follow up on initial results with RNAi-based gene including Syx7, Rtn1, and Pacs1, suggesting a novel mechanism of knockdown allowed us to rapidly categorize a subset of 17 proteins axonal growth underlying vesicular transport, as has been shown for as functionally relevant to axonal growth, indicating that proteomic Drosophila dendrites (37). Combining this finding with the results approaches offer useful alternatives for learning about mammalian reported here, the list of functional markers for growth cones has growth cones instead of or complementing genetic approaches in been expanded Ͼ10-fold, which should have a profound impact on model organisms, and conventional research methods focused on a the ability to study growth cone functions. small number of proteins. A perhaps surprising and certainly The role of some molecules implicated in axon guidance, such as interesting result of our study is that most of the proteins we netrin and semaphorins, has been characterized in the mammalian identified had not previously been implicated in axonal growth in brain. These sometimes act as chemoattractants, but in other cases, mammals or axon pathfinding in well-studied model organisms, the same molecules act as chemorepellants (35), which indicates despite the fact that the proteins we identified have been evolu- that external guidance molecules alone cannot determine the fate tionarily conserved (Table 1). The results suggest that a large of a growth cone; instead, the specific type of response appears to number of genes and a wide variety of biochemical functions are be determined by the activity of intrinsic signaling pathways. In this relevant to axonal growth. For example, among the proteins we context, it is easy to understand the importance of learning what identified, some have been implicated in membrane trafficking, molecules are present in growth cones.

17214 ͉ www.pnas.org͞cgi͞doi͞10.1073͞pnas.0904092106 Nozumi et al. Downloaded by guest on September 26, 2021 In conclusion, we have performed a large-scale identification of using 4% paraformaldehyde (see SI Text). For double-labeling via immuno- growth cone proteins that provides an important starting point for fluorescence, the primary antibody was mixed with anti-␣-tubulin antibody, further investigation in mammalian axon development, growth, and and then with a secondary antibody conjugated with Alexa Fluor-488 or -568. regeneration (1–4, 38). Genomic microdeletion of Cyfip1, one of our candidates, has been suggested to be associated with human Quantitation of Fluorescence Intensities. An Axiovert 200 microscope (Zeiss) with an ORCA-ER camera (Hamamatsu) and LD Acroplan lens (40 ϫ 0.6 NA) was used schizophrenia (37), further suggesting that our lists might help to to collect image data. From each image (1,344 ϫ 1,024 pixels), a square growth provide a molecular foothold for study of psychiatric disorders based on cone or axon area was digitally excised (100 ϫ 100 pixels), and the fluorescent disruption of neuronal developmental (38–40). The availability of a intensity was calculated per pixel by using ImageJ. Double-labeling with anti-␣- long list of candidate genes that may be related to growth cone tubulin and another antibody, followed by immunofluorescence detection, was functions, along with a large set of new marker proteins for the used to determine the subcellular localization of proteins identified in this study. growth cone, provides an important resource for further investigation. Functional Analysis Using RNAi. RNAi experiments were done as described (ref. 45; see also SI Text). Chemically synthesized siRNAs (final concentration, 83.3 nM) Methods were applied to cortical neurons derived from E19 ‘‘green rat’’ (SD-Transgenic rat Proteomic Analysis. The GCP and GCM fractions were prepared from postnatal expressing CAG-EGFP; Japan SLC), together with 83.3 nM siRNA against EGFP day 1–2 rat forebrains, and adult synaptosmal fractions were prepared from (Ambion) by using Lipofectamine 2000 (Invitrogen) just after the neurons were young adult rat cortices by subcellular fractionation (41, 42). Both fractions were dissociated and plated. After 72 h, we measured axon lengths for neurons in S-carbamoylmethylated and digested with trypsin, and the digests were sub- which EGFP was not detectable. Any siRNA-dependent decreases in target gene jected to direct nanoflow 2D LC-MS/MS for protein identification (43, 44). Exper- expression were quantified by using an antibody against the target protein, with imental conditions and data processing were as described (refs. 15, 16, and 47; see anti-GFP (MBL) included as an additional control (Ambion). SI Text). The GCP, GCM, and synaptosomal proteins identified in this work are See SI Text for additional details. listed in Table S1, Table S2, and Table S3. ACKNOWLEDGMENTS. We thank all those who donated antibodies (see Table S6), Prof. K. Akazawa for statistical analysis, and the Proteomics Committee in the Cell Culture and Immunostaining. Rat cortical neurons [embryonic day 19 (E19)] Integrated Brain Research group for support. This work was supported in part by were cultured on glass chamber slides for 3 days on polyethylenimine in the Grants-in-Aid 16015240 and 17023019 for Scientific Research on Priority Areas presence of neurobasal medium containing 0.5 mM glutamine and fixed with from the Ministry of Education, Culture, Sports, Science, and Technology of Japan 2.5% glutaraldehyde. For RNAi, dispersed neurons were plated on poly-L- (to M.I.) and Project Research Promoting Grants from Niigata University (to M.I. lysine-coated four-well chamber slides made of Permanox (Nunc) and fixed by and M.N.).

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