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Identification of Functional Marker Proteins in the Mammalian Growth Cone

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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 pro- teins 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.
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