Localized translation near the mitochondrial outer membrane: An update

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Abstract

Local synthesis of proteins near their activity site has been demonstrated in many biological systems, and has diverse contributions to cellular functions. Studies in recent years have revealed that hundreds of mitochondria-destined proteins are synthesized by cytosolic ribosomes near the mitochondrial outer membrane, indicating that localized translation also occurs at this cellular locus. Furthermore, in the last year central factors that are involved in this process were identified in yeast, Drosophila, and human cells. Herein we review the experimental evidence for localized translation on the cytosolic side of the mitochondrial outer membrane; in addition, we describe the factors that are involved in this process and discuss the conservation of this mechanism among various species. We also describe the relationship between localized translation and import into the mitochondria and suggest avenues of study that look beyond cotranslational import. Finally we discuss future challenges in characterizing the mechanisms for localized translation and its physiological significance.

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Global analysis of mRNA localization reveals a prominent role in organizing cellular architecture and function.

Eric Lecuyer, Hideki Yoshida, Neela Parthasarathy … (2007)

Although subcellular mRNA trafficking has been demonstrated as a mechanism to control protein distribution, it is generally believed that most protein localization occurs subsequent to translation. To address this point, we developed and employed a high-resolution fluorescent in situ hybridization procedure to comprehensively evaluate mRNA localization dynamics during early Drosophila embryogenesis. Surprisingly, of the 3370 genes analyzed, 71% of those expressed encode subcellularly localized mRNAs. Dozens of new and striking localization patterns were observed, implying an equivalent variety of localization mechanisms. Tight correlations between mRNA distribution and subsequent protein localization and function, indicate major roles for mRNA localization in nucleating localized cellular machineries. A searchable web resource documenting mRNA expression and localization dynamics has been established and will serve as an invaluable tool for dissecting localization mechanisms and for predicting gene functions and interactions.

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Extensive Association of Functionally and Cytotopically Related mRNAs with Puf Family RNA-Binding Proteins in Yeast

André Gerber, Daniel Herschlag, Patrick O Brown (2004)

Introduction The dynamic structure and physiology of a cell depend on coordinated synthesis, assembly, and localization of its macromolecular components (Orphanides and Reinberg 2002). The timing and level of expression of the genes that encode these components are controlled by transcription factors that regulate initiation of transcription in a gene-specific manner by binding to specific DNA sequences proximal to the genes they regulate. The combinatorial binding and activity of specific transcription factors confer a distinctive program of regulation on each individual gene while enabling coherent global responses of large sets of genes in physiological and developmental programs. Much less is known about either the system architecture or molecular mechanisms that underlie regulation of the post-transcriptional steps in the gene expression program. There are approximately 15,000 mRNA molecules in each Saccharomyces cerevisiae cell during exponential growth in rich medium (Hereford and Rosbash 1977) and at least a 10-fold larger number in a typical mammalian cell (Hastie and Bishop 1976). The extent to which the location, activity, and fates of these diverse populations of mRNAs are coordinated and the post-transcriptional mechanisms that might mediate their coordinated regulation remain largely unknown. RNA-binding proteins (RBPs) have been implicated in diverse aspects of post-transcriptional gene regulation, including RNA processing, export, localization, degradation, and translational control (Dreyfuss et al. 2002; Maniatis and Reed 2002; Mazumder et al. 2003). Although there appear to be hundreds of RBPs encoded in eukaryotic genomes (Costanzo et al. 2001; Issel-Tarver et al. 2002), for only a few of these proteins have the RNA targets been systematically identified (Takizawa et al. 2000; Tenenbaum et al. 2000; Brown et al. 2001; Hieronymus and Silver 2003; Li et al. 2003; Shepard et al. 2003; Waggoner and Liebhaber 2003). For example, a recent study in S. cerevisiae found that two nuclear RNA export factors were each associated with large and distinct mRNA populations, and common functional themes were found among the 1,000 or so proteins encoded by each population (Hieronymus and Silver 2003). These observations support a role for RBPs in the coordinated regulation of mRNA subpopulations (Keene and Tenenbaum 2002; Keene 2003). Systematic identification of the mRNA targets of RBPs can be a powerful approach to understanding the cellular roles of RBPs and the mechanisms by which they might regulate the post-transcriptional lives of mRNAs. We have focused first on the Pumilio–Fem-3-binding factor (FBF) (Puf) proteins from S. cerevisiae, which belong to a structurally related family of cytoplasmic RBPs that are implicated in developmental processes in various eukaryotes (Wickens et al. 2002). Puf proteins are defined by the presence of several (typically eight) consecutive repeats of the Pumilio homology domain (Pum-HD), which confers RNA binding activity (Zamore et al. 1997; Wang et al. 2002a). The Puf proteins characterized to date have been reported to bind to 3′-untranslated region (UTR) sequences encompassing a so-called UGUR tetranucleotide motif and thereby to repress gene expression by affecting mRNA translation or stability. Despite the widespread occurrence of Puf family members, only a few mRNA targets have been identified for these RBPs (Wickens et al. 2002). For example, in Drosophila, the PUMILIO protein binds maternal hunchback mRNA and, in concert with NANOS protein, represses translation of the mRNA at the posterior pole during early embryogenesis. The Caenorhabditis elegans Puf homologs, called Fem-3-binding factors (FBFs), regulate the switch from spermatogenesis to oogenesis by repressing fem-3 translation, and they are implicated in the propagation of germline stem cells through binding and inhibition of gld-1 mRNA expression (Zhang et al. 1997; Crittenden et al. 2002). Less is known about the human homologs: PUMILIO-2 protein interacts with DAZ (deleted in azoospermia) protein and is expressed in embryonic stem cells and germ cells, whereas PUMILIO-1 is almost ubiquitously expressed (Moore et al. 2003). In S. cerevisiae, five proteins, termed Puf1p to Puf5p, bear six to eight Puf repeats (Figure 1). Little is known about the physiological function of these proteins. Mutations in either PUF4 or PUF5 result in diminished longevity (Kennedy et al. 1997). PUF1 was isolated as a multicopy suppressor of certain microtubule mutants (Machin et al. 1995), and a PUF2 null mutant displayed increased resistance to cycloheximide and paromomycin (Waskiewicz-Staniorowska et al. 1998). However, S. cerevisiae mutants lacking all five PUF genes are viable (Olivas and Parker 2000). A genome-wide analysis of mRNA expression patterns in yeast mutants lacking all five PUF genes found differential expression of 7%–8% of all mRNAs under steady-state conditions, but no common theme was found among the affected genes (Olivas and Parker 2000). Only two specific mRNA targets have been identified for yeast Puf proteins: Puf3p binds to the COX17 mRNA 3′-UTR in vitro and may regulate its turnover (Olivas and Parker 2000), and Puf5p negatively regulates expression of reporter genes substituting for the HO endonuclease (Tadauchi et al. 2001). Using DNA microarrays to identify the specific mRNAs that interact with the five S. cerevisiae Puf proteins, we have found that each Puf protein bound to a large set of distinct and functionally related mRNAs. We identified novel and conserved sequence elements in the mRNAs bound by Puf3p, Puf4p, and Puf5p. The results suggest a system for large-scale coordinated control of cytoplasmic mRNAs and provide insights into the physiological logic of the gene expression program. Results Systematic Identification of mRNAs Associated with Specific RBPs To identify RNAs associated with Puf proteins, tandem-affinity purification (TAP)-tagged proteins were purified from whole-cell extracts of S. cerevisiae (Figure 2). The TAP tag (Rigaut et al. 1999), a sequence encoding two IgG-binding units of protein A, a specific protease recognition site, and a calmodulin-binding domain, was fused in-frame at the C-terminus of the respective open reading frame (ORF) in its original chromosomal location (Ghaemmaghami et al. 2003). This design was intended to preserve normal regulation of the expression of the fusion protein. Cells of the TAP-tagged strains showed growth rates and cell morphologies similar to wild-type cells. Cells were grown to mid-log phase in rich medium, extracts were prepared, and ribonucleoprotein complexes were recovered by affinity selection on IgG beads and subsequent cleavage with tobacco etch virus (TEV) protease (see Materials and Methods). To control for nonspecifically enriched mRNAs, the same procedure was performed with wild-type cells lacking the TAP tag. TEV protease cleavage was superior to direct elution of proteins from beads, as it gave lower contamination from nonspecifically interacting RNAs in the resulting purified fractions (data not shown). RNA was isolated from the purified protein samples and from extracts. We obtained 0.8–2 μg of RNA from the Puf affinity-isolated samples gathered from 1-l cultures, but no detectable RNA (<0.1 μg) was recovered when the same procedure was applied to untagged control cells. The yield of RNA from the Puf affinity isolation procedure was sufficient to perform further labeling steps directly, without amplification of RNA by PCR, as had been required in previous studies (Takizawa et al. 2000; Hieronymus and Silver 2003). Two samples from each cell population, total RNA, and RNA isolated by the Puf affinity procedure were used to prepare cDNA probes labeled with different fluorescent dyes, which were mixed and hybridized to S. cerevisiae DNA microarrays containing all known and putative ORFs, introns, and the mitochondrial genome (see Materials and Methods). The ratio of the fluorescent hybridization signals from the two differentially labeled RNA samples, at the array element representing each specific gene, provided an assay for enrichment of the corresponding mRNA by the Puf-affinity procedure. Puf3p is the only one of the five S. cerevisiae Puf proteins for which direct in vitro interaction with an mRNA (COX17) has previously been described, thereby providing an internal positive control (Olivas and Parker 2000). COX17 mRNA was substantially and consistently enriched in four independent Puf3p affinity isolations (ratio = 10 ± 1.4; Figure 3A), but not in mock isolations (ratio = 0.8 ± 1.2). In general, after filtering for spots with high background or irregular shapes, enrichment values for the entire set of arrayed sequences were reproducible (median of standard deviations in all arrayed spots = 0.35 on a log2 scale) (see Materials and Methods). To define targets specific to each Puf protein, we first selected all sequences for which enrichment factors in the corresponding affinity isolation procedures were at least two standard deviations above the mean for all arrayed sequences (Figure S1; for samples isolated by the Puf3p-affinity procedure, this corresponded to an enrichment factor of greater than or equal to 2.5). Second, we eliminated from this selected group any sequences that were also consistently enriched in the mock procedure (see Materials and Methods). Although no cutoff can perfectly distinguish the actual physiological targets from false positives, the high reproducibility of the results (see Figure 3B), the occurrence of distinct mRNA populations associated with the different Puf proteins, and the characterization of these targets described in the subsequent sections, including the identification of distinct sequence motifs and in vivo confirmation of the role of these motifs in specific RNA–protein interactions, strongly support the validity of the majority of the targets. Finally, the list of target mRNAs did not change substantially by application of other statistical methods for selection (see Lieb et al. 2001). A large number of arrayed sequences, 818, identified transcripts associated with at least one Puf protein (see Figure 3B; Table S1), with 735 encoding distinct ORFs. This represents approximately 12% of the known and predicted protein-coding sequences in the S. cerevisiae genome. Of these, 90 transcripts interact with more than one Puf protein. The largest overlap was observed between the groups of transcripts associated with Puf1p and Puf2p—which also have the greatest overall similarity in amino acid sequence among the Puf proteins (45% identical); 36 of the 40 Puf1p targets were also associated with Puf2p. Twenty-eight mRNAs were bound by both Puf4p and Puf5p, and 16 were bound both by Puf2p and Puf5p. Seven transcripts were enriched with three different Puf proteins (DHH1 and YOL109w mRNAs with Puf1p, Puf2p, and Puf5p; NOP1 mRNA with Puf1p, Puf4p, and Puf5p; SUR7 and SFL1 mRNAs with Puf2p, Puf4p, and Puf5p; and IFM1 mRNA with Puf3p, Puf4p, and Puf5p). The remaining 645 target mRNAs were each associated with only one of the Puf proteins. Thus, each Puf protein associates with a distinct and highly specific subset of mRNAs (see Tables S3–S7). We estimated the number of Puf proteins per cell by a filter affinity blot analysis using protein A as a standard for calibration (Table S2). We found that Puf1p, Puf2p, Puf3p, and Puf5p were similar in abundance, with 350–400 molecules per cell. Puf4p was approximately twice as abundant (approximately 900 molecules per cell). The relatively low abundance of the Puf proteins is therefore comparable to that of transcription factors, protein kinases, and cell cycle proteins (Futcher et al. 1999). Moreover, our measurements imply that the intracellular concentrations of the Puf proteins range between 20 and 50 nM, approximately one order of magnitude higher than the dissociation constants for binding of their metazoan homologs to the cognate target RNAs. The number of Puf proteins per cell approximates the estimated numbers of cognate Puf target mRNA molecules present in the cell (Holstege et al. 1998; Wang et al. 2002b) (Table S2), consistent with a model in which each Puf protein molecule is associated with one mRNA molecule in the cell. Puf3p Specifically Binds mRNAs Encoding Mitochondrial Proteins As a first step toward identifying functional themes among the mRNAs associated with each Puf protein, we retrieved the Gene Ontology (GO) annotations for process, function, and compartment from the Saccharomyces Genome Database (SGD) (Issel-Tarver et al. 2002). (The target mRNAs for each Puf protein are listed in Tables S3–S7.) We then searched for significant shared GO terms in the lists of Puf mRNA targets (Table S8). Puf3p associated almost exclusively with transcripts of nuclear genes that encode mitochondrial proteins (p < 10−88; see Table S5). In particular, of the 154 Puf3p-associated transcripts for which GO annotation of subcellular localization was available, 135 (87%) were assigned to mitochondria (Figure 4A). Of the Puf3p-associated mitochondrial gene products, 80 (59%) are involved in protein biosynthesis, including structural components of the ribosome (55 genes), tRNA ligases (12 genes), and translational regulators (nine genes). Twenty-two of the Puf3p-bound transcripts are involved in mitochondrial organization and biogenesis, 17 in aerobic respiration, and 12 in mitochondrial translocation. Based on this striking cytotopic (relating to location in the cell) concordance, we suggest that the remaining 66 Puf3p mRNA substrates (30%) for which no GO annotations were available are likely to encode mitochondrial proteins. (While this paper was under review, a genome-wide analysis of protein localization in S. cerevisiae [Huh et al. 2003] reported a mitochondrial localization for 27 additional Puf3p targets, raising the total to 162 of the 220 putative Puf3p mRNA targets encoding mitochondrial proteins.) Puf1p- and Puf2p-Associated mRNAs Disproportionately Encode Membrane-Associated Proteins Of all the characterized S. cerevisiae genes for which any information about subcellular localization is available, 18% are currently classified as encoding membrane-associated proteins (Yeast Proteome Database [YPD], May 2003; see Costanzo et al. 2001). A much greater fraction of the mRNAs associated with Puf1p and Puf2p encode membrane-associated proteins: 16 of the 28 (57%) known proteins encoded by Puf1p-interacting mRNAs and 55 of 106 (52%) known proteins encoded by Puf2p-interacting mRNAs (see Figure 3B; see Tables S3 and S4). Transcripts encoding proteins associated with the plasma membrane were particularly enriched among the Puf1p- and Puf2p-bound mRNAs. Most of the mRNAs bound by Puf1p were also associated with Puf2p. However, Puf2p bound uniquely to many additional mRNAs (146 Puf2p mRNA targets versus 40 for Puf1p). In terms of cellular processes, many Puf1p- and Puf2p-associated transcripts encode proteins with roles in transmembrane transport and vesicular trafficking of proteins: 9 out of 26 (34%; p < 0.0002) of annotated Puf1p targets and 24 out of 104 (23%; p < 10−5) annotated Puf2p targets (compared to 9% of all characterized genes) (YPD, May 2003). This group includes transporters for spermine (Tpo1, Tpo2, Tpo3), proteins (Nce101, Nce102, Ast1, Vps72, Mas6, Sfk1, Mup3), vesicles (Sso2, Snc2, Yip1, Aps3, Ypr157w), and lipids (Pdr16, Ykl091c, Fps1 [glycerol]). (Tpo2 and Tpo3 may cross-hybridize on arrays because of their high sequence identity [89%], but Tpo1 does not [Shepard et al. 2003]). Puf4p and Puf5p Interact Selectively with mRNAs Encoding Nuclear Components Among the Puf5p targets (see Table S6), we found two common themes. First, a remarkable fraction encodes nuclear proteins that participate in covalent modification of histones, chromatin-remodeling complexes, or transcriptional regulation (64 of the 113 annotated genes [57%; p < 3 × 10−6]). Second, the Puf5p-associated transcripts included a substantial fraction of the mRNAs known to encode components or regulators of the mitotic spindle apparatus in yeast: 14 mRNAs that encode microtubule-based spindle components, including seven of the 25 (28%; p < 4 × 10−5) structural components of the spindle pole body (Kar1, Ccd31, Spc19, Spc42, Bbp1, Cnm67, and Nuf2) (Wigge et al. 1998). Messages encoding nuclear and cytoplasmic proteins that regulate polarized growth (Ame1, Boi2, Bsp1, Bub1, Bud9, Dad2, Elm1, Gic1, Kar9, Rax2, Ste7), some of them known to interact with spindle components, were also Puf5p targets. Transcripts encoding nucleolar proteins were highly enriched among the Puf4p-bound mRNAs: 36 of the 133 (27%) annotated genes in this group encode nucleolar proteins, as compared to 3% of all the annotated genes in the S. cerevisiae genome (p < 10−12). Of these 36, 29 are directly involved in ribosomal RNA (rRNA) synthesis, processing, and ribosome maturation (p < 10−15), major functions of the nucleolus (Fatica and Tollervey 2002; Gerbi et al. 2003) (see Tables S5 and S8). Twenty-eight transcripts were enriched in both the Puf4p and Puf5p affinity isolations, including six transcripts encoding components of the nucleosome (p < 10−11), among them the four core histone proteins (histones 2A and 2B, histone 3, and histone 4; note that histones 2A and 2B are 98% identical and therefore cross-hybridize). Diverse Functional Links among Transcripts Associated with Each Puf Protein In addition to the cytotopic relationships within each group of Puf-associated mRNAs, we were struck by the frequency with which transcripts encoding different components of protein complexes or systems of interacting proteins were bound by the Puf proteins. For example, most of the nuclear transcripts encoding components of the mitochondrial ribosome (55 out of the 77 known genes; Gan et al. 2002) were Puf3p-associated. This observation prompted us to search for other protein complexes and functional systems that shared similarly Puf-associated mRNAs. Other examples of coordinate “tagging” of transcripts encoding subunits of multiprotein complexes include Puf4p association of mRNAs encoding three of the four protein components of the H/ACA core particle (Cbf5p, Gar1p, and Nhp2p), which synthesizes pseudouridine in rRNAs (Henras et al. 1998) (Figure S2; no data were obtained for the fourth component, Nop10p). Puf5p bound mRNAs encoding histone acetylases (Ada2p, Spt8p, and Hfi1p), which are components of the Spt–Ada–Gcn5–acetyltransferase (SAGA) complex, and transcripts encoding at least four of the six members of the RSC (remodels the structure of chromatin) family of DNA-stimulated ATPases with bromodomains (Bdf1p, Bdf2p, Rsc2p, and Rsc4p; no array data were obtained for the two other members, Rsc1p and Spt7p). As mentioned above, the mRNAs encoding at least three of the four core histones were enriched in both Puf4p and Puf5p affinity isolations. We also found numerous cases in which the transcripts encoding multiple members of a functional group of proteins were bound by the same Puf protein. For example, the transcripts encoding the Tpo1, Tpo2, and Tpo3 proteins, the three known spermine transporters in the plasma membrane (Albertsen et al. 2003; see note above about cross-hybridization), and the two known genes implicated in the nonclassical protein export pathway (NCE101, NCE102) (Cleves et al. 1996) were bound by Puf1p and Puf2p and by Puf2p, respectively. Puf5p was associated with all of the histone deacetylases (HDACs) that act on histones located around coding sequences—Sin3p (a class I HDAC), Hda1p (a class II HDAC), and both components of the Set3C complex (Hst1p and Snt1p) (Kurdistani and Grunstein 2003). (Two other HDACs, Hos1p and Hos3p, which deacetylate histones around the ribosomal DNA locus, were not enriched in Puf5p affinity isolations.) Finally, we identified cases in which the mRNAs encoding multiple components of a specific regulatory system were bound by the same Puf protein. For example, Puf2p associates with mRNAs encoding diverse proteins regulating Pma1p, which is an ATP-dependent proton transporter located in the plasma membrane, and with PMA1 mRNA itself (Figure S2). All of the mRNAs encoding nucleolar glycine/arginine-rich (GAR) domain-bearing proteins (Sbp1p, Nsr1p, Nop1p, Gar1p) as well as HMT1 mRNA, encoding a dimethylase that modifies the nucleolar GAR proteins (Xu et al. 2003), were associated with Puf4p, while none of the mRNAs encoding the distinct group of nonnucleolar GAR proteins were bound by Puf4p (Figure S2). Sequence Motifs in the 3′-UTR of mRNA Targets Direct Binding by Puf Proteins The Puf homologs in Drosophila and C. elegans bind to sequences in the 3′-UTR of mRNAs (Wickens et al. 2002). We therefore examined the sets of mRNAs associated with each of the S. cerevisiae Puf proteins for the presence of common sequence motifs in 5′-UTRs and 3′-UTRs, using multiple expectation maximization for motif elicitation (MEME) as a motif discovery tool (Bailey and Elkan 1994). We identified distinct 10- or 11-nucleotide sequence motifs in the 3′-UTR among the mRNAs interacting with Puf3p, Puf4p, and Puf5p (Figure 5A, Tables S9–S11). We have thus far been unable to identify conserved sequence elements among Puf1p and Puf2p targets; these proteins may recognize structural elements in the RNA rather than simple sequence strings, possibly via their classical RNA-binding domains instead of their six-repeat Pumillio domains. The conserved motifs we identified in the Puf3p, Puf4p, and Puf5p targets each include a UGUR tetranucleotide sequence, which is a feature of all previously reported RNA targets of Puf family proteins (Wickens et al. 2002). Furthermore, in each case, the consensus sequence contains a conserved dinucleotide (UA), located two, three, or four nucleotides downstream of the UGUR motif, in the consensus sites for Puf3p, Puf4p, and Puf5p. Remarkably, the Puf3p consensus motif matches a sequence (CYUGUAAAUA) previously identified by computational tools in 3′-UTR sequences of nuclear genes coding for mitochondrial proteins (Jacobs Anderson and Parker 2000). We examined the distribution of the consensus sequence motifs in the entire S. cerevisiae genome (Table 1). Of the genes whose mRNAs were predicted by computational analysis to contain one of these three target sequences in their 3′-UTRs, 42% were identified experimentally as targets in the corresponding affinity isolation procedure (Table 1). The consensus motifs were occasionally found in the coding sequence of an experimentally identified target gene, but were much rarer in the predicted 5′-UTR sequences (Table 1). Moreover, only a few mRNAs had two copies of the motifs: five mRNAs among the Puf3p targets, six among the Puf4p targets, and one among the Puf5p targets (see Tables S5–S7). As our computational method did not detect the cognate consensus sequence elements in all the experimentally identified targets, alternative sequences or structural elements in RNAs might also allow specific interactions with Puf proteins, some mRNAs may be associated indirectly as part of larger complexes, and some of the putative mRNA targets identified by our affinity procedure are likely to be false positives. To test the in vivo function of the putative recognition elements identified by the computational analysis, we assayed RNA–protein interactions in vivo using the yeast three-hybrid system (Bernstein et al. 2002) (see Figure 5B). Puf3p, Puf4p, and Puf5p bound specifically to a sequence matching to the cognate consensus sequence, as assayed by activation of the lacZ and HIS3 reporter genes (see Figure 5C and 5D). For Puf3p and Puf4p, the Pum-HD alone was sufficient to confer specific binding (see Figure 5C and 5D), but no interaction could be seen with the Puf5p Pum-HD alone (data not shown). These interactions were specific: mutations in the UGU of the Puf3p consensus sequence disrupted binding, and each Puf protein interacted with its cognate consensus sequence in preference to the closely related consensus sequences recognized by the other Puf proteins. We detected a weak interaction between Puf3p and the Puf4p target sequence, an interaction that was not seen with the Puf3p Pum-HD alone. These results suggest that binding of the Puf proteins to these specific cis-acting elements directs their functions to specific sets of mRNAs. Subcellular Distribution of Puf Proteins We investigated the localization of the TAP-tagged Puf proteins by immunofluorescence with antibodies against the TAP tag (see Materials and Methods). All five Puf proteins were predominantly localized to multiple discrete foci in the cytoplasm (Figure 6). The predominantly cytoplasmic localization is consistent with previous reports for S. cerevisiae Puf3p and Puf5p (Tadauchi et al. 2001) and for the homologous proteins in higher eukaryotes (Lehmann and Nüsslein-Volhard 1991; Zhang et al. 1997). The distribution of the foci of Puf proteins was not obviously related to distinct cellular organelles or structures, with the exception of Puf1p and Puf2p, which localized in foci enriched near the periphery of the cell. Because of the diffuse and pleiomorphic distribution of mitochondria in the cell, we cannot exclude the possibility that Puf3p, which specifically bound transcripts of proteins destined for the mitochondria, is associated with mitochondria. Altered Levels of Puf3p-Associated mRNAs in a puf3Δ Mutant A previous study compared steady-state mRNAs levels of cells bearing deletions of all five Puf proteins and wild-type cells grown in rich media (Olivas and Parker 2000). Only 12 of the 148 (8%) mRNAs whose abundance changed by more than 2-fold were selectively enriched in our affinity isolations with Puf proteins. The lack of a simple relationship between the mRNA binding specificity we observed and the reported effects of these multiple mutations on global gene expression prompted us to design a more specific experiment to search for a possible connection between specific mRNAs levels and binding to Puf proteins. We focused on Puf3p, as its strong association with mRNA-encoding mitochondrial proteins suggested that we should look for a regulatory function for this protein in mitochondrial physiology. Indeed, we found that puf3Δ cells grew more slowly than isogenic puf3+ cells on minimal media plates with glycerol as the carbon source (Figure S3). We therefore compared mRNA levels in the puf3Δ and puf3+ cells grown under these conditions by DNA microarray hybridization. Although the magnitude of the change was small, the relative expression levels of the 220 Puf3p-associated mRNAs were selectively increased in puf3Δ cells, compared to all other mRNAs analyzed (p < 10−34) (Figure 7). Of the 16 mRNAs whose abundance was increased by more than 2-fold in the puf3Δ mutant, 11 (70%) were among the transcripts identified as Puf3p targets by our co-purification experiments, and all encode mitochondrial proteins. This result could reflect a direct effect of Puf3p on its target mRNAs, for example, by promoting mRNA decay (Olivas and Parker 2000). However, the levels of transcripts involved in respiration and mitochondrial function, including many that did not appear to be bound directly by Puf3p, were increased in the puf3Δ mutant, suggesting the possibility that the elevated abundance of Puf3p target mRNAs could instead be an indirect response to impaired mitochondrial and respiratorial function in puf3Δ cells. Discussion In an analysis of just five of the hundreds of RBPs encoded by the S. cerevisiae genome, we found that more than 700 transcripts appeared to be specifically bound by one or more RBPs, with each of the five Puf family proteins “tagging” a distinct set of mRNAs. These sets encode functionally and cytotopically related proteins. For three of the Puf proteins, we identified distinct short sequences in the associated specific set of mRNAs, typically in the 3′-UTR, which were sufficient for specific binding to the cognate Puf protein in vivo. Many sets of mRNAs encoding proteins localized to the same subcellular compartment, protein complex, or functional system were bound by the same Puf protein. Puf3p, which specifically associated with cytoplasmic mRNAs encoding mitochondrial proteins, generally affected the steady-state levels of its mRNA targets as reflected by their increased abundance in puf3 mutant cells. The selective “tagging” by sequence-specific RBPs of mRNAs that share common physiological roles suggests a general and widespread mechanism for coordinated control of their expression. Previous reports have identified coordinated regulation of small sets of functionally related mRNAs by specific RBPs. For example, mammalian stem–loop binding protein (SLBP) associates with all five classes of histone mRNAs and guides proper 3′-end formation (Dominski and Marzluff 1999). Iron regulatory proteins (IRPs) bind to and regulate translation of five different mRNAs encoding proteins involved in iron metabolism (Eisenstein and Ross 2003), and a cytoplasmic poly(A) polymerase regulates multiple mRNAs in early development (Mendez and Richter 2001). Based on these and other examples (Tenenbaum et al. 2000), Keene and Tenenbaum (2002) have suggested that messenger RBPs could define “post-transcriptional operons.” Our results provide strong support for this general idea of coordination of gene expression via RBPs and suggest that the post-transcriptional control afforded by combinatorial binding of RBPs to mRNAs could allow greater regulatory flexibility than a simple operon (see also Keene and Tenenbaum 2002). Further, we suggest that RBPs may play important roles in subcellular localization and efficient assembly of protein complexes. The RBPs encoded in eukaryotic genomes rival specific transcription factors in their numbers and diversity, raising the intriguing possibility that specific regulation of the localization, translation, and survival of mRNAs might be comparable in their richness and complexity to regulation of transcription itself. Each of the five Puf proteins interacts with a distinct large set of mRNAs, comprising more than 700 different mRNAs in total. Five other RBPs in S. cerevisiae have been subjected to a similar genome-wide survey of their mRNA targets. She2p, which plays a critical role in selective targeting of specific mRNAs to the bud tip (Shepard et al. 2003), Khd1p, which has also been implicated in localizing gene expression to the nascent bud (A. P. Gerber, unpublished data), and Scp160p, an RBP implicated in genome stability (Li et al. 2003), were each found to bind from 20 to hundreds of distinct mRNAs, and two proteins implicated in RNA export from the nucleus, Yra1p and Mex67p, were each associated with more than 1,000 mRNAs (Hieronymus and Silver 2003). Thus, just ten of the 567 S. cerevisiae proteins known or predicted from the genome sequence to have RNA binding activity (Costanzo et al. 2001) have been found to bind, in a functionally specific pattern, a total of approximately 2,500 different transcripts (approximately 40% of the transcriptome). The extent and specificity of the RNA–protein interactions represented by the proteins studied to date, extrapolated to the hundreds of putative RBPs that remain to be investigated, suggest the existence of an extensive network of RNA–protein interactions that coordinate the post-transcriptional fate of large sets of cytotopically and functionally related RNAs through each stage of its “lifecycle.” It further suggests a potential regulatory repertoire comparable in its diversity and richness to that of the DNA-binding transcription factors (Figure 8). Indeed, the combinatorial binding of mRNAs by multiple RBPs could, in principle, define a specific post-transcriptional fate for each individual mRNA (for an example, see Sonoda and Wharton 2001). Many sets of mRNAs bound by the same Puf protein encode proteins that act in the same subcellular location, form stochiometric complexes, or are implicated in the same cellular pathway. This organization is most clearly exemplified by Puf3p, which selectively bound mRNAs encoding mitochondrial proteins, including at least 70% of all mitochondrial ribosomal proteins (see Figure 4). Combinations of RBPs could specify smaller sets of RNAs encoding more precisely defined functional groups of proteins. For example, the mRNAs encoding the core histone proteins were among the small set of mRNAs that were associated with both Puf4p and Puf5p. These results therefore hint that networks of functional and physical interactions among proteins could be reflected in a corresponding network of mRNA–protein interactions that coordinate post-transcriptional control of their expression and fate. For three of the Puf proteins, we found that RNA–protein interactions were directed by compact sequence elements, usually located in the 3′-UTR of the mRNA (see Figure 5). Interactions with 3′-UTR sequences have been described for many cytoplasmic RBPs involved in post-transcriptional regulation (Mazumder et al. 2003). Our analysis has revealed that such recognition elements are probably much more widespread than previously recognized. Sequence and structural elements in mRNAs that are related to the function or cellular localization of the encoded proteins may be a general feature of eukaryotic genes, paralleling the role of the DNA sequences that direct specific transcription factors to promoters and enhancers (Cliften et al. 2003). The multifocal cytoplasmic distribution of Puf proteins raises the possibility that the mRNAs associated with each Puf protein are colocalized (see Figure 6). In mammalian cells, specific mRNA molecules and specific messenger RBPs have also been found to be localized to specific “granular” subcytoplasmic loci, although the generality of this phenomenon has not been established (Andersen and Kedersha 2002; Eystathioy et al. 2002; Farina et al. 2003). One function of the Puf proteins and related proteins that bind specific families of mRNAs could be to localize functionally related mRNAs to specific cytoplasmic loci. Physical clustering of functionally related groups of mRNAs could aid the assembly of complexes and the coordinated control of translation or RNA turnover. In support of this idea, it has recently been suggested that mRNA decay in the cytoplasm of S. cerevisiae occurs in distinct loci (Sheth and Parker 2003) and, further, that mRNAs encoding different subunits of stoichiometric complexes do indeed have concordant decay rates (Wang et al. 2002b). We propose that the location in the cell at which any mRNA is translated or degraded is not left to chance. Instead, every mRNA that leaves the nucleus may be delivered, in a process directed by specific protein–RNA interactions, to one of a limited number of specific foci in the cytoplasm, designated as destinations for a specific functionally related family of mRNAs. These foci could serve to colocalize and coregulate synthesis of proteins that need to assemble or act together, thereby facilitating efficient and rapid assembly and localization of the proteins. The number of distinct families of functionally specialized foci may be quite large. The locations of these foci need not correspond to recognizable cellular features, but may simply be ad hoc sites for localized, coordinated translation of proteins that are to be assembled into a complex or a functional unit. Specific predictions of this hypothesis, such as colocalized translation of the subunits of stoichiometric complexes, should be amenable to direct experimental tests. Combinatorial binding of mRNAs by specific regulatory proteins, linking their post-transcriptional regulation to specific signal transduction pathways, could allow rapid and efficient reprogramming of gene expression during development or in response to changing physiological conditions. Indeed, regulation of specific genes by external signals via RPBs has been described in higher eukaryotes (Lasko 2003). For example, the signal transduction and activation of RNA (STAR) proteins contain RNA-binding motifs combined with protein–protein interaction domains and phosphorylation sites, which could allow integration of stimuli conducted by signal transduction cascades (Lasko 2003). Similarly, the Puf proteins contain numerous putative phosphorylation motifs, as well as domains with characteristics often implicated in protein–protein interactions, such as glutamine/arginine-rich regions (Michelitsch and Weissman 2000) (see Figure 1). Coordination of cellular processes has long been thought to be mediated primarily at the transcriptional and post-translational level. Our results join a growing body of studies (Tenenbaum et al. 2000; Eystathioy et al. 2002; Wang et al. 2002b; Hieronymus and Silver 2003; Shepard et al. 2003; see also Keene and Tenenbaum 2002) that suggest that the localization, translation, and stability of mRNAs are subject to extensive and important regulation and coordination by interaction with a diverse set of RBPs. Systematic mapping of these interactions and deciphering their roles, molecular mechanisms, and coordination will undoubtedly yield important new insights into biological regulation and the gene expression program. Materials and Methods Oligonucleotide primers Restriction sites are in italics: Puf3-F1, 5′-cgggatccATGGAAATGAACATGGATATGGATATGG-3′; Puf3-R1, 5′-ggaattcTCACACCTCCGCATTTTCAACCAATG-3′; Puf3-F6nco, 5′-cCATGgCACTAAAAGACATCTTTGG-3′; Puf4-F2nco, 5′-ccatgGCGGACGCAGTTTTAGACCAATA-3′; Puf4-R1eco, 5′-gaattcgTGAATCTAAATGTAACATTCCG-3′; Puf5-F2nco, 5′-ccATGGTCGAAATCAGCGCACTACC-3′; Puf5-R1xho, 5′-ctcgagcACTTGGAAGTAATTCTTTTGTA-3′; M16-1, 5′-GGGCTCGAGtagggaataccttgtaaatatcctatgaaaGCATG-3′; M16-2, 5′-CtttcataggatatttacaaggtattccctaCTCGAGCCC-3′; M16-1mut, 5′-GGGCTCGAGtagggaatacctacaaaatatcctatgaaaGCATG-3′; M16-2mut, 5′-CtttcataggatattttgtaggtattccctaCTCGAGCCC-3′; Caf-1, 5′-GGGCTCGAGtgggcacgattgtaataatacttcatgataaGCATG-3′; Caf-2, 5′-CttatcatgaagtattattacaatcgtgcccaCTCGAGCCC-3′; Yor-1, 5′-GGGCTCGAGgctttcatcatctgtataatatttatatgtcGCATG-3′; and Yor-2, 5′-CgacatataaatattatacagatgatgaaagcCTCGAGCCC-3′. Strains and plasmid construction The TAP-tagged Puf3p strain (SC1249) was obtained from Cellzome (Heidelberg, Germany) (Gavin et al. 2002). TAP-tagged Puf1p, Puf2p, Puf4p, and Puf5p strains were a gift from Dr. Erin O'Shea (Ghaemmaghami et al. 2003). Correct genomic integration of each tag was verified by PCR and by immunoblot analysis of cell extracts (data not shown). Strain BY4741 was used for mock-control affinity isolations of RNA, and deletions of the PUF3 and PUF4 genes in this strain were obtained from Dr. Ron Davis (Winzeler et al. 1999). The ORF of PUF3 was amplified by PCR with primers Puf3-F1 and Puf3-R1 from S. cerevisiae genomic DNA and cloned into pCR2.1 using the TOPO TA Cloning Kit (Invitrogen, San Diego, California, United States). The PUF3 ORF was sequenced and subcloned into pACTII via NcoI and EcoRI restriction sites, resulting in plasmid pACTII-Puf3. A full-length Puf5p construct pGAD-MPT5 was a gift from Dr. Kenji Irie (Tadauchi et al. 2001). Sequences encoding the Pum-HD domains of Puf3p (amino acids 535–879), Puf4p (amino acids 557–888), and Puf5p (amino acids 202–578) were PCR-amplified from genomic DNA with oligo pairs Puf3-F6nco/Puf3-R1, Puf4-F2nco/Puf4-R1eco, and Puf5-F2nco/Puf5-R1xho, respectively. Products were ligated into pCR2.1-TOPO, sequenced, and further cloned into pACTII via restriction sites present in the oligonucleotides used for amplification. The RNA consensus sequences interacting with Puf proteins plus ten nucleotides of flanking sequences were cloned into the SmaI and SphI sites of the vector pIIIA/MS2-2 (Bernstein et al. 2002) using annealed synthetic oligonucleotides. The PUF3 RNA consensus sequence spanning nucleotides 24–33 in the 3′-UTR of YBL038w/MRPL16 was constructed with oligonucleotides M16-1 and M16-2. In M16mut the conserved UGU motif was changed to ACA. The PUF4 consensus (nucleotides 24–34 in the 3′-UTR of YOR145c) was constructed with oligonucleotides Yor-1 and Yor-2. The PUF5 consensus (nucleotides 105–114 in the 3′-UTR of YNL278w/CAF120) was constructed with oligonucleotides Caf-1 and Caf-2. Isolating RNAs specifically associated with selected RBPs For a detailed protocol, see the Supporting Information on our Web site. In brief, 1 l of cells were cultured in YPAD medium (yeast–peptone–dextrose [YPD] supplemented with 20 mg/ml adenine–sulfate) at 30°C and collected during exponential growth by centrifugation. Cells were washed twice with ice-cold buffer A (20 mM Tris–HCl [pH 8.0], 140 mM KCl, 1.8 mM MgCl2, 0.1% Nonidet P-40 [NP-40], 0.02 mg/ml heparin) and resuspended in 5 ml of buffer B (buffer A plus 0.5 mM dithiothreitol [DTT], 1 mM phenylmethylsulfonylfluoride, 0.5 μg/ml leupeptin, 0.8 μg/ml pepstatin, 20 U/ml DNase I, 100 U/ml RNasin [Promega, Madison, Wisconsin, United States], and 0.2 mg/ml heparin). Cells were broken mechanically with glass beads, and extracts were incubated with 400-μl slurry (50% [v/v]) IgG–agarose beads (Sigma, St. Louis, Missouri, United States) for 2 h at 4°C. The beads were washed four times for 15 min at 4°C with buffer C (20 mM Tris–HCl [pH 8.0], 140 mM KCl, 1.8 mM MgCl2, 0.5 mM DTT, 0.01% NP-40, 10 U/ml RNasin). Puf proteins were released from the beads by incubation with 80 U of TEV protease (Invitrogen) for 2 h at 15°C. RNA was isolated from the TEV eluates, which corresponds to the purified fraction and from extracts (input) by extraction with phenol/chloroform and isopropanol precipitation. Microarray analysis and data selection Equal amounts of a pool of five synthetically prepared Bacillus subtilis RNAs were added to each RNA sample prior to labeling and served as a control for the labeling procedure (Wang et al. 2002b). Total RNA (3 μg) derived from the extract and 300 ng of affinity-isolated RNA (or up to 40% of isolated RNA) were labeled with Cy3 and Cy5 fluorescent dyes, respectively, following cDNA synthesis with amino-allyl dUTP in addition to the four natural dNTPs using a 1:1 mixture of oligo(dT) and random nonamer primers. The Cy3- and Cy5-labeled cDNA samples were mixed and competitively hybridized to DNA microarrays representing all S. cerevisiae ORFs, introns, and the mitochondrial genome (see http://brownlab.stanford.edu/protocols.html). Microarrays were scanned with an Axon Instruments (Foster City, California, United States) Scanner 4000. Scanning parameters were adjusted to give similar fluorescent intensities for B. subtilis spots in both channels. Data were collected with the GENEPIX 3.0 Program (Axon Instruments), and spots with abnormal morphology were excluded from further analysis. Arrays were computer normalized by the Stanford Microarray Database (SMD) (Gollub et al. 2003). Log2 median ratios were retrieved from SMD and exported into Microsoft (Redmond, Washington, United States) Excel after filtering for regression correlation of greater than 0.6 (filters for large variations in the ratios of pixels within each spot), CH1I/CH1B of greater than 1.8 (signal over background in the channel measuring total RNA from extract), and CH2I/CH2B of greater than 1.0 (affinity-isolated RNA signal greater than background) and for data from at least two independent measurements. Average log2 ratios were calculated for each gene across the four independent experiments performed for each Puf protein (microarrays and raw data can be downloaded from our supporting Web sites [http://microarray-pubs.stanford.edu/yeast_puf/ and http://genome-www5.stanford.MicroArray/SMD/]). Genes for which the enrichment ratios were at least two standard deviations above the median across all genes were selected. A total of 923 genes were selected in this way. To eliminate nonspecifically enriched RNAs from this gene list, the results from the affinity enrichments for each of the Puf proteins and the data obtained from four independent mock affinity enrichments were clustered by the Pearson correlation algorithm (Eisen et al. 1998). Transcripts of 84 genes were enriched beyond the two standard deviation threshold in all the Puf affinity isolations as well as in the mock procedure. These were presumed to represent RNAs whose enrichment was unrelated to specific interactions with Puf proteins and therefore were excluded from further analysis. Among the finally selected target mRNAs (see Tables S3–S7), most were represented in the four independent measurements: PUF1, 98%; PUF2, 97%; PUF3, 82%; PUF4, 93%; PUF5, 97%. Gene expression profiling puf3 mutant and wild-type cells were cultured in minimal media supplemented with 3% glycerol and harvested during exponential growth (OD600 = 0.5). Total RNA (8 μg) isolated from wild-type and mutant cells were used to prepare Cy3 and Cy5 fluorescently labeled cDNA as described above, except that only an oligo(dT) primer was used. The two differentially labeled cDNAs were mixed together and hybridized to yeast DNA microarrays. Arrays were scanned and the data were collected, entered into SMD, and computer normalized (Gollub et al. 2003). Log2 median ratios were retrieved from SMD after filtering for regression correlation of greater than 0.6 and signal over background of greater than 1.5. Results from three independent experiments were averaged for this analysis (raw data can be retrieved from our Web site). Motif searches As the exact 5′- and 3′-UTR lengths are unknown for most of the Puf target mRNAs, we used the estimated average lengths from yeast (Mignone et al. 2002). Hence, the coding 237 nucleotides of predicted 3′-UTR and 134 nucleotides of predicted 5′-UTR sequences were retrieved from SGD for the Puf target genes. The sequences were searched for motifs in the sense strand with the program MEME under the proposed default settings (http://meme.sdsc.edu/meme/website/intro.html) (Bailey and Elkan 1994) (see Tables S9–S11). The number and location of consensus motifs in the S. cerevisiae genome was obtained by searching “Pattern Match” in the SGD (Issel-Tarver et al. 2002). Thereby, nucleotides that were at least 19% conserved among the MEME selected sequences were used to compile the Consensus Motif that was searched for. Three-hybrid assays Three-hybrid assays were performed as described elsewhere (Bernstein et al. 2002). Immunofluorescence Immunofluorescence was performed as described at http://www.med.unc.edu/%7Ehdohlman/IF.html. Fixed and permeabilized cells were treated with 5 μg/ml purified rabbit immunoglobulin (Sigma) for 1 h at room temperature. After washing, cells were incubated with Cy3 goat anti-rabbit antibodies (1:400). Images were obtained on a Zeiss (Oberkochen, Germany) Axioplan-2 microscope using an Axiocam HRC camera. Supporting Information Full microarray results and other supporting information can be viewed at http://microarray-pubs.stanford.edu/yeast_puf/ and at http://genome-www5.stanford.MicroArray/SMD/. Figure S1 Distribution of Average Cy5/Cy3 Fluorescence Ratios from Quadruplicate Microarray Hybridizations Analyzing mRNA Targets for Puf1p, Puf2p, Puf4p, and Puf5p See Figure 3A for Puf3p. (167 KB EPS). Click here for additional data file. Figure S2 Examples of Groups of mRNAs Associated with the Same Puf Protein and Encoding Related Proteins (A) Puf2p-bound mRNAs encode diverse proteins involved in regulation of ATP-dependent proton transport. PMA1 and PMA2 encode plasma membrane proteins that comprise the major ATP-dependent proton transporters and regulate cellular pH levels. Pmp1p, Pmp2p, and Pmp3p are small isoproteolipids, which are present in a physical complex with Pma1p and act as regulators of its activity upon stress conditions (Navarre et al. 1994). Hrk1p is a protein histidine kinase, which activates Pma1p in response to glucose (Goossens et al. 2000). Ast1p is implicated in proper delivery of Pma1p to plasma membranes (Bagnat et al. 2001). (B) Puf4p-bound mRNAs encode the nucleolar GAR proteins (blue), members of the H/ACA core complex (boxed), and Hmt1p, a dimethylase acting on GAR proteins. Nop1p performs 2′-O-ribose methylation of pre-rRNA, a process guided by small nucleolar RNAs (snoRNAs) of the box C/D family. Cbf5p catalyzes pseudouridine formation with box H/ACA snoRNAs, and three of the four components of the H/ACA core complex were Puf4p-associated (Cbf5, Gar1, and Nhp2 [Henras et al. 1998]; no data were obtained for the fourth component, Nop10, shown in gray). All transcripts encoding nucleolar proteins of the GAR repeats family (Gar1p, Sbp1p, Nop1p, Nsr1p) were Puf4p-bound. The GAR domain is dimethylated at arginine residues. Remarkably, several mRNAs coding for S-adenosylmethionine-dependent methyltransferases were Puf4p-bound including Hmt1p, the major protein arginine-methyltransferase in yeast (Gary et al. 1996). Hmt1p has recently been shown to dimethylate arginines of the proteins Gar1p, Nop1p, and Nsr1p (Xu et al. 2003). (38 KB EPS). Click here for additional data file. Figure S3 Phenotypic Analysis of puf3Δ Cells Serial dilutions (1:10) of cells were spotted on plates supplemented with the indicated media. Plates were incubated for 3 d at 30°C. Abbreviations: YPD, yeast–peptone–dextrose; YPGE, yeast–peptone–3% glycerol–2% ethanol; SC, synthetic complete. (264 KB PDF). Click here for additional data file. Table S1 Number of mRNA Targets Shared between Puf Proteins (15 KB XLS). Click here for additional data file. Table S2 Protein Copy Number Determination of Puf Proteins Cells were grown to mid-log phase in YPAD medium and the number of cells was counted. Whole-cell extracts were prepared as described previously (Hoffman et al. 2002). In brief, cells were resuspended in 1× SDS-PAGE sample buffer, incubated at 100°C for 10 min, and vortexed for 2 min with glass beads. After a short centrifugation, eight dilutions of cell extracts and protein A (Amersham, Little Chalfont, United Kingdom), which served as a reference standard, were spotted on a nitrocellulose filter. Expression of IgG-binding domains was monitored with rabbit peroxidase–anti-peroxidase soluble complex at 1:5,000 (Sigma). Chemiluminescence was measured with a Typhoon 8600 Imager (Molecular Dynamics, Sunnyvale, California, United States) and quantified with the ImageQuant 5.2 software. Averaged numbers from two independent measurements were used for calculations. The total number of mRNA copies in the pool associated with each Puf protein was estimated as follows: copy numbers for individual mRNAs were retrieved from two independent genome-wide measurements (Holstege et al. 1998; Wang et al. 2002b). For genes with no data, we added the median value for copy numbers of all mRNAs in the respective pool. (30 KB XLS). Click here for additional data file. Table S3 List of Puf1p Target mRNAs Columns indicate the following (from left to right): ORF; gene name; GO annotations; classification of gene products (soluble/membrane-associated); average log2 ratios of enrichment across four independent Puf affinity isolations; standard deviations; association of mRNA with other Puf proteins; mRNA copy numbers. (28 KB XLS). Click here for additional data file. Table S4 List of Puf2p Target mRNAs Notations are as in Table S3. (52 KB XLS). Click here for additional data file. Table S5 List of Puf3p Target RNAs Columns indicate the following (from left to right): ORF; gene name; GO annotations; classification of gene products (soluble/membrane-associated); average log2 ratios of enrichment across four independent Puf affinity isolations; standard deviations; association of mRNA with other Puf proteins; location of consensus motif identified by MEME; mRNA copy numbers. (70 KB XLS). Click here for additional data file. Table S6 List of Puf4p Target mRNAs Notations are as in Table S5. (61 KB XLS). Click here for additional data file. Table S7 List of Puf5p Target mRNAs Notations are as in Table S5. (64 KB XLS). Click here for additional data file. Table S8 Significant Shared GO Annotations among Puf mRNA Targets Only annotations with p values of less than 0.001 are indicated. GO annotations were retrieved from the SGD with GO Finder (http://db.yeastgenome.org/cgi-bin/SGD/GO/goTermFinder) on May 21, 2003. Respective p values are indicated in a column next to the names of the GO term. (30 KB XLS). Click here for additional data file. Table S9 Results of MEME Motif Searches: Motifs among Puf3p mRNA Targets (63 KB XLS). Click here for additional data file. Table S10 Results of MEME Motif Searches: Motifs among Puf4p mRNA Targets (55 KB XLS). Click here for additional data file. Table S11 Results of MEME Motif Searches: Motifs among Puf5p mRNA Targets (34 KB XLS). Click here for additional data file. Accession Numbers All accession numbers for human, Drosophila, or C. elegans proteins are from the SwissProt database (http://www.ebi.ac.uk/swissprot/): CPEB (Q18317), GLD1 (Q17339), DAZL (Q92904), FBF-1 (Q9N5M6), FEM3 (P34691), IRP (P21399), NANOS (P25724), Drosophila PUMILIO (P25822), human PUMILIO-1 (Q14671), human PUMILIO-2 (Q9HAN2), and SLBP (P97330). The accession numbers for S. cerevisiae genes are from SGD (http://genome-www.stanford.edu/Saccharomyces/) (ORF/SGD identification number): ADA2 (YDR448W/S0002856), AME1 (YBR211C/S0000415), APS3 YJL024C/S0003561), AST1 (YBL069W/S0000165), BBP1 (YPL255W/S0006176), BDF1 (YLR399C/S0004391), BDF2 (YDL070W/S0002228), BOI2 (YER114C/S0000916), BSP1 (YPR171W/S0006375), BUB1 (YGR188C/S0003420), BUD9 (YGR041W/S0003273), CBF5 (YLR175W/S0004165), CDC31 (YOR257W/S0005783), CNM67 (YNL225C/S0005169), COX17 (YLL009C/S0003932), DAD2 (YKR083C/S0001791), DHH1 (YDL160C/S0002319), ELM1 (YKL048C/S0001531), FPS1 (YLL043W/S0003966), GAR1 (YHR089C/S0001131), GIC1 (YHR061C/S0001103), HDA1 (YNL021W/S0004966), HFI1 (YPL254W/S0006175), HMT1 (YBR034C/S0000238), HOS1 (YPR068C/S0006272), HOS3 (YPL116W/S0006037), HST1 (YOL068C/S0005429), HTA1 (YDR225W/S0002633), IFM1 (YOL023W/S0005383), KAR1 (YNL188W/S0005132), KAR9 (YPL269W/S0006190), KHD1 (YBL032W/S0000128), MAS6 (YNR017W/S0005300), MEX67 (YPL169C/S0006090), MUP3 (YHL036W/S0001028), NCE101 (YJL205C/S0003742), NCE102 (YPR149W/S0006353), NHP2 (YDL208W/S0002367), NOP1 (YDL014W/S0002172), NSR1 (YGR159C/S0003391), NUF2 (YOL069W/S0005430), PDR16 (YNL231C/S0005175), PMA1 (YGL008C/S0002976), PUF1 (YJR091C/S0003851), PUF2 (YPR042C/S0006246), PUF3 (YLL013C/S0003936), PUF4 (YGL014W/S0002982), PUF5 (YGL178W/S0003146), RAX2 (YLR084C/S0004074), RSC1 (YGR056W/S0003288), RSC2 (YLR357W/S0004349), RSC4 (YKR008W/S0001716), SBP1 (YHL034C/S0001026), SCP160 (YJL080C/S0003616), SFK1 (YKL051W/S0001534), SFL1 (YOR140W/S0005666), SHE2 (YKL130C/S0001613), SIN3 (YOL004W/S0005364), SNC2 (YOR327C/S0005854), SNT1 (YCR033W/S0000629), SPC19 (YDR201W/S0002609), SPC42 (YKL042W/S0001525), SPT7 (YBR081C/S0000285), SPT8 (YLR055C/S0004045), SSO2 (YMR183C/S0004795), STE7 (YDL159W/S0002318), SUR7 (YML052W/S0004516), TPO1 (YLL028W/S0003951), TPO2 (YGR138C/S0003370), TPO3 (YPR156C/S0006360), VPS72 (YDR485C/S0002893), YIP1 (YGR172C/S0003404), YKL091c (YKL091C/S0001574), YPR157w (YPR157W/S0006361), and YRA1 (YDR381W/S0002789).

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The Central Dogma Decentralized: New Perspectives on RNA Function and Local Translation in Neurons

Christine Elizabeth Holt, Erin M. Schuman (2013)

Main Text Background It is now clear that individual neurons are highly compartmentalized with specific functions and/or signaling that occur in restricted subcellular domains. Extrinsic signals are often spatially localized such that they are “seen” by restricted parts of a neuron, such as synaptic input to a specific dendritic spine or a guidance cue encountered by a growth cone. Twenty-five years ago, when the first issue of Neuron was published, it was well appreciated that the neurons were capable of local information processing, but the potential cellular mechanisms that established and regulated local compartments were not well understood. Dendritic spines had been proposed as biochemical and/or electrical compartments (Harris and Kater, 1994; Koch and Zador, 1993), and polyribosomes had been identified at the base of spines (Steward and Levy, 1982). However, the view that dominated until nearly the end of the twentieth century was that the central dogma (DNA-RNA-protein) was carried out centrally—in the nuclei and somata of neurons. In that context, the localization of mRNA observed in some cells was thought to represent a specialized mechanism that operated in unique biological systems, such as egg cells, where storage of mRNAs is needed for subsequent patterning of the early embryo (see Martin and Ephrussi, 2009 for review). Evidence from a number of studies in the last decade, particularly in neurons, has led to a revolution in our thinking. Although the field is still young, it is becoming clear that RNA-based mechanisms provide a highly adaptable link between extrinsic signals in the environment and the functional responses of a neuron or parts of a neuron. This is accomplished by the localization of both protein-coding and noncoding RNA in neuronal processes and the subsequent regulated local translation of mRNA into protein. Here we discuss some of the key findings that lead us to the view that mRNA localization and RNA-regulated and localized translation underlie many fundamental cellular processes that are regulated by extrinsic signals in neurons, such as memory, dendrite and arbor branching, synapse formation, axon steering, survival, and likely proteostasis. The dynamic regulation of protein synthesis is essential for all cells, including neurons. Over 50 years ago, in vivo experiments (in a variety of species) established a clear functional link between protein synthesis and long-term memory (see Davis and Squire, 1984 for review), indicating that proteome remodeling underlies behavioral plasticity. These observations were paralleled by in vitro studies of synaptic plasticity demonstrating a clear requirement for newly synthesized proteins in the long-term modification of synaptic function (see Sutton and Schuman, 2006 for review; also, Tanaka et al., 2008). This link between protein synthesis and long-term plasticity is most recently reinforced by studies showing that targeted genetic disruption of signaling molecules that regulate protein translation interfere with long-term synaptic or behavioral memories (Costa-Mattioli et al., 2009). The above studies, while indicating a requirement for protein synthesis, do not address the location. We now know dendrites and axons of neurons represent specialized cellular “outposts” that can function with a high degree of autonomy at long distances from the soma, as illustrated by the remarkable ability of growing axons to navigate correctly after soma removal (Harris et al., 1987) or isolated synapses to undergo plasticity (Kang and Schuman, 1996; Vickers et al., 2005). The identification of polyribosomes at the base or in spines (Steward and Levy, 1982) together with metabolic labeling experiments that provided the first evidence of de novo synthesis of specific proteins in axons and dendrites (Feig and Lipton, 1993; Giuditta et al., 1968; Koenig, 1967; Torre and Steward, 1992) indicated the competence of these compartments for translation. Subsequent studies demonstrated that specific subsets of mRNAs localize to synaptic sites (Steward et al., 1998) and directly linked synaptic plasticity with local translation in dendrites (Aakalu et al., 2001; Huber et al., 2000; Kang and Schuman, 1996; Martin et al., 1997; Vickers et al., 2005), providing definitive proof that dendrites are a source of protein during plasticity. In axons, the idea of local protein synthesis has been slower to find acceptance, no doubt hindered by the classical view of axons as information transmitters rather than receivers; so, why would local protein synthesis be required? Although ribosomes were identified in growth cones in early ultrastructural studies (Bunge, 1973; Tennyson, 1970), they were rarely observed in adult axons. It is now thought that at least part of the explanation for their apparent paucity lies in their localization close to the plasma membrane in axons (Sotelo-Silveira et al., 2008) where ribosomal subunits can associate directly with surface receptors (Tcherkezian et al., 2010). In addition, evidence indicates that myelinated axons can tap into an external supply of ribosomes by the translocation of ribosomal proteins from Schwann cells (Court et al., 2011). Growing and navigating axons are clearly information receivers, like dendrites, since their growth cones steer using extrinsic signals. Indeed, the first functional evidence for local protein synthesis in axons came from studies that showed that cue-induced directional steering is abolished by inhibitors of protein synthesis, including rapamycin, in surgically isolated axons (Campbell and Holt, 2001). Subsequent studies confirmed this result in different neurons (Wu et al., 2005; Yao et al., 2006) and revealed that local protein synthesis underlies growth-cone adaptation, gradient sensing, and directional turning in growing axons (Leung et al., 2006; Ming et al., 2002; Piper et al., 2005; Yao et al., 2006). In addition, axonal protein synthesis is elicited in response to injury and plays key roles in axon regeneration and maintenance (Jung et al., 2012; Perry et al., 2012; Verma et al., 2005; Yoon et al., 2012; Zheng et al., 2001). Compartments Neuronal function is highly dependent on spatially precise signaling. Increasing evidence indicates that the complex morphology of neurons has created biological compartments that subdivide the neuron into spatially distinct signaling domains important for neuronal function (Hanus and Schuman, 2013). Dendritic spines represent a specialized (“classical”) cellular compartment in which subsets of specific proteins (e.g. receptors, channels, signaling molecules, and scaffolds) are collected together with a common function for receiving and processing electrical and chemical input. Spines have a distinct structural morphology and, as such, are easy to classify as a compartment. Although spines are small (∼1 μm3), they can still be subdivided into further functional compartments (see Chen and Sabatini, 2012 for review) with multiple microdomains, raising the question of how a compartment is defined. For example, a recent superresolution imaging study demonstrated that, within synapses, AMPA receptors are clustered into small nanodomains (∼70 nm in diameter) that contain on average ∼20 receptors (Nair et al., 2013). These nanodomains are dynamic in both their shape and position and may have a limited lifetime. Anatomically and functionally distinct compartments also exist in axons, such as the growth cone, the axon initial segment, and terminal arbor. Equally, there are examples of compartments that exhibit no obvious “anatomical” specializations. In axons, for example, some membrane proteins are localized to restricted segments of the axon (Fasciclins, Tag1/L1, Robo) (Bastiani et al., 1987; Dodd et al., 1988; Katsuki et al., 2009; Rajagopalan et al., 2000) indicative of plasma-membrane compartmentalization. In addition, second-messenger signaling molecules such as calcium and cyclic nucleotides, once thought to signal extensively throughout a cell, are now known to be highly regulated such that increases in concentration can be confined to a small space, creating a signaling compartment. Selective activation of a single spine on a dendrite, for example, can provide the receiving neuron with information about a specific stimulus (Varga et al., 2011). Compartments may be overlapping or distinct and range in size depending on the biological function. Ultimately, a neuron must integrate the information received from multiple compartments. As such, future experiments aimed at understanding how different compartments emerge and what mechanisms generate such spatially precise intracellular patterning will be very informative. Compartmentalized signaling presents several challenges to the cell, a prime one being the localization of its component parts. Specific molecules must be transported and delivered to the appropriate subcellular destinations. One of the remarkable features of RNA is its ability to be spatially localized and, therefore, potentially contribute to neuronal compartmentalization. Historically, localized mRNAs have been studied during development (see Martin and Ephrussi, 2009). That localized RNA is more often the rule than the exception is spectacularly illustrated by the finding that 71% of the Drosophila embryo transcriptome is localized to specific subcellular compartments (Lécuyer et al., 2007). The proteins encoded by localized mRNAs are also concentrated at the site suggesting that mRNA localization and the ensuing local translation plays an important role in positioning proteins for cellular functions. Asymmetry and Spatial Signaling A general function of mRNA localization is the generation of asymmetry. mRNAs tend to be abundantly localized to the peripheral domains and motile parts of neurons where they are optimally positioned for the arrival of external signals, e.g., in dendrites (synaptic activation) and growth cones. Subcellular asymmetry can lead to highly polarized dynamics and cell morphology that can operate on a remarkably fine scale. Growth-Cone Spatial Signaling To navigate, growth cones must be able to make directional turns, which demands asymmetry. In retinal growth cones, for example, which are only 5 μm in diameter, a polarized external gradient of netrin-1 triggers increases in both the transport and translation of β-actin mRNA on the gradient near side (Leung et al., 2006; Yao et al., 2006). This polarized translation leads to a rapid (5 min) polarized increase in β-actin protein that helps to drive axon turning towards the gradient source. Interestingly, different cues show specificity in their effects on mRNA transport and translation. Different growth factors, for example, trigger the transport of a specific repertoire of mRNAs in axons (Willis et al., 2005, 2007; Zhang et al., 1999), and different guidance cues elicit the translation of specific subsets of mRNAs (Leung et al., 2006; Piper et al., 2006; Shigeoka et al., 2013; Wu et al., 2005; Yao et al., 2006). β-actin mRNA translation is triggered by netrin-1 but not Sema3A, whereas RhoA and cofilin mRNA translation is induced by Sema3A but not netrin-1. This has given rise to the differential translation model suggesting that translation-dependent repulsive and attractive turning in growth cones depends on the differential translation of mRNAs involved in assembly or disassembly of the actin cytoskeleton (Lin and Holt, 2007). Several aspects of this translation-driven cue-induced turning remain to be understood, such as how receptor activation signals mRNA recruitment and, critically, how specific subsets of mRNA are translated. Readout of Spatial Position In Vivo Navigating growth cones encounter a series of patterned molecular cues along the pathway from which they must read out their spatial position. Although there are several examples of stimulus-induced local translation in axons in vitro (Shigeoka et al., 2013), it has only recently become possible to investigate translation in neuronal compartments in vivo. Early studies by Flanagan and colleagues showing compartmentalized expression of EphA2, recapitulated by a translation reporter, in the post-midline crossing segment of commissural spinal cord axons introduced the idea that the growing tip of the axon is stimulated by a regionally expressed cue (e.g., at the midline) that triggers the region-specific translation of proteins needed for pathfinding (Brittis et al., 2002). A recent study provides direct evidence for this type of mechanism in the control of Robo expression and midline guidance (Colak et al., 2013). Two Robo3 receptor isoforms have opposing roles in guiding axons to and away from the midline, and their expression is compartmentalized in pre-crossing (Robo3.1) and postcrossing (Robo3.2) axonal segments (Chen et al., 2008). The switch to Robo3.2 expression at the midline (the transcript of which contains a premature termination codon) is controlled by midline-induced axonal protein synthesis coupled with nonsense-mediated mRNA decay. This provides an elegant mechanism for turning on synthesis time linked to the crossing event (Colak et al., 2013). It was not previously technically possible to inhibit translation of a specific transcript in a compartment-specific manner. Recently, however, new tools have been developed that allow separate manipulation of specific neuronal compartments in vivo such as targeted delivery of siRNAs or antisense morpholinos and conditional targeting of 3′UTRs (Perry et al., 2012; Yoon et al., 2012). These subcellular-directed approaches are beginning to yield information suggesting that local translation is involved in regulating multiple aspects of axonal and dendritic biology. Guidance cues induce immediate steering responses in growth cones via classical signaling pathways that involve receptor activation and phosphorylation of downstream signaling molecules (Bashaw and Klein, 2010). Some of these “immediate” steering responses also involve local translation, as discussed above. Thus, local translation can provide new proteins on demand at subcellular sites for “immediate” use. Interestingly, local translation in response to extrinsic cues has recently been shown to provide proteins for “delayed” use in axon growth and regeneration. Examples of this are the de novo synthesis of proteins that shuttle back to the nucleus where they influence transcriptional output (Cox et al., 2008; Perry et al., 2012), and another is the de novo synthesis of surface receptor proteins that are employed later in a growth cone’s journey (Leung et al., 2013). Spatial Signaling in Dendrites Recent advances in experimental procedures, allowing the stimulation of individual synapses, have shown that synapses can be independently regulated by synaptic activity (Matsuzaki et al., 2004). On the other hand, other studies emphasize the consideration of the dendritic branch as a computational unit (Govindarajan et al., 2011). Taken together, it seems reasonable to consider a range of spatial domains over which signaling can occur, which would span the scale from subdomains in spines to dendritic branches to the entire neuron. These data can be compared to what we know about the quantitative localization of the protein-synthesis machinery. Indeed, it is clear that many synapses possess a polyribosome nearby (Ostroff et al., 2002). Moreover, recent high-resolution in situ hybridization data suggest that mRNA molecules are distributed in local domains (Cajigas et al., 2012), but not necessarily specific to individual synapses. Preliminary estimates of mRNA numbers indicate that there may not be sufficient copies of individual mRNA species for each synapse to have an exclusive and dedicated molecular toolbox. These data imply that there is local sharing of cell biological machineries, including the machinery for protein synthesis and degradation. It remains unclear, however, over what spatial scale local translation can be regulated and stimulated in dendrites. For example, is stimulation of a single spine sufficient to regulate local translation, and, if so, over what spatial domain do the newly synthesized proteins function? RNA in Neurons The past view that RNA acts primarily as an inert intermediate between genes and proteins has undergone a revolution in recent years with discoveries of both new classes of RNAs (e.g., noncoding RNAs, (see Ulitsky and Bartel, 2013 for review) and new RNA-based mechanisms of gene regulation (e.g., microRNA and RNAi silencing) (see McNeill and Van Vactor, 2012 for review). Indeed, given the relatively constrained diversity of proteomes across cells and organisms, RNA-based mechanisms (diverse RNA species and RNA functions) represent a unique platform to diversify and specialize cells, especially neurons. Numerous new roles for RNA have been found in recent years, expanding the role of RNA to controlling many and diverse cellular processes, including stimulus-induced local translation that underlie adaptive responses in neurons (e.g., memory, axon guidance, and maintenance). In addition, RNA’s role may not be limited to the cells where it is synthesized, as new studies indicate it can be transferred between cells (via exosomes) (Sharma et al., 2013) and even between organisms (Sarkies and Miska, 2013), bringing a whole new era of RNA function in cellular communication into focus. mRNA The demonstrations that local protein translation functions during synaptic development and plasticity led to the hunt for specific mRNAs that could be translated in these local compartments. For many years, in situ hybridization was the method of choice, and several individual mRNAs were visualized in dendrites, including the mRNA for the Ca2+-calmodulin-dependent protein kinase alpha subunit, CaMKIIα (Burgin et al., 1990; Mayford et al., 1996), MAP2 (Garner et al., 1988), Shank (Böckers et al., 2004), and β-actin (Tiruchinapalli et al., 2003). In growth cones and axons, in situ hybridization provided evidence for several different mRNAs, including β-actin (Bassell et al., 1998; Kaplan et al., 1992; Wu et al., 2005). Recent microarray approaches and deep RNA sequencing have dramatically expanded the local transcriptome in both dendrites and axons (Poon et al., 2006; Zhong et al., 2006). One of the most surprising findings to come out of these studies is the vast number of mRNAs that are present in these neuronal compartments. Growing axons have 1000–4500 mRNAs (Zivraj et al., 2010), while dendrites have >2500 mRNAs (Cajigas et al., 2012). The mRNAs resident in these compartments span many different functional classes of molecules: metabolism, translation, degradation, receptors/channels, cytoskeleton, etc. Many functional categories are shared between the two compartments, although there are numerous distinct compartment-specific subsets of mRNAs, e.g., GAP43 mRNA in axons and neurotransmitter receptor subunits in dendrites. The localization of mRNA to cellular compartments involves recognition of information that is contained in the 3′ and/or 5′ untranslated (UTR) sequences. The use of mRNA localization to achieve protein localization may arise from the fact that, at least theoretically, unlimited address information can be built into the 3′ and/or 5′ UTRs of mRNA without altering its gene-coding function, whereas there is a tight limit to how much additional coding sequence can be added to a protein without ramifications for function. The family of proteins that bind, transport, localize, and regulate the translation of mRNAs are known as RNA-binding proteins (RBPs) (see Darnell, 2013 for review). RBPs bind to cis-elements in the 3′ and 5′ UTRs of mRNAs. RNA-binding proteins complexed with mRNA, other RNA species, and accessory proteins are thought to be assembled in the cell body and form RNA granules (Kiebler and Bassell, 2006). During transport on microtubules and microfilaments to its destination (e.g., Hirokawa, 2006 and Czaplinski and Singer, 2006), the mRNA cargo is thought to be “silenced” by translational repressors (Krichevsky and Kosik, 2001). Once transported, it is unclear how or whether mRNAs are anchored near translational sites—or if they show continued dynamics. Both stationary and anchored particles have been observed in dynamic mRNA imaging experiments (Lionnet et al., 2011). RNA-binding proteins are an important class of regulatory molecule that recognizes specific nucleotide sequences in RNA (Ray et al., 2013). IP-Seq analysis has revealed, unexpectedly, that some RBPs can bind hundreds of different mRNAs (see Darnell, 2013 for review). Some RBPs, however, appear to be cell-type specific, such as Hermes (RPBMS2) that is expressed exclusively in retinal ganglion cells in the CNS and its knockdown causes severe defects in axon terminal branching (Hörnberg et al., 2013). The number of mRNA-binding proteins identified by known RNA-binding domains is relatively small (around 270) given the increasingly large number of transcripts found in axons and dendrites. Recent work using interactome capture in embryonic stem cells has significantly expanded the number of RBPs, adding a further ∼280 proteins to the repertoire, including, remarkably, many enzymes such as E3 ubiquitin ligases with previously unknown RNA-binding function (Kwon et al., 2013). Several RBPs have been implicated in neurological disorders, such as FMRP in Fragile X syndrome and survival of motor neuron protein (SMN) in spinal muscular atrophy (Bear et al., 2008; Liu-Yesucevitz et al., 2011), and translation dysregulation has recently been implicated as a major factor in autism (Gkogkas et al., 2013; Santini et al., 2013). Noncoding RNAs In recent years the discovery of noncoding RNAs, including miRNAs (which use sequence complementarity to recognize target mRNA), has revealed unanticipated and enormous potential for the regulation of mRNA stability and translation, as well as other functions. Given the huge and unanticipated number of mRNAs detected in axons and dendrites, it is perhaps not surprising that these noncoding RNAs also exist—and are even enriched—in neuronal compartments. One might even argue the complex morphology and functional specialization of neurons provides a hotbed for mRNA regulation that can potentially be mediated by noncoding RNAs. Indeed, an analysis of 100 different miRNAs discovered the differential distribution of some miRNAs in dendrites versus somata and copy numbers in individual neurons as high as 10,000—equivalent to the number of synapses a typical pyramidal neuron possesses (Kye et al., 2007). Recently, the differential distribution of miRNAs has been also reported in axons versus soma (Natera-Naranjo et al., 2010; Sasaki et al., 2013) and recently emerged as regulators of axon growth and branching (Kaplan et al., 2013). Moreover, the enrichment of miRNAs in synaptosomes isolated from specific brain regions has also been reported (Pichardo-Casas et al., 2012). miRNAs have now been shown to regulate many synaptic functions (see Schratt, 2009 for review). In addition, miRNAs themselves are regulated by behavioral experience (Krol et al., 2010) as well as synaptic plasticity (Park and Tang, 2009). More recently, the appreciation of other types of noncoding RNAs have come into focus, though very little is known about their function in neurons. This includes small-nucleolar RNA-derived and transfer RNA-derived small RNAs, firstly identified as degradation products, and long noncoding RNA known as regulators of gene transcription, that may regulate gene expression posttranscriptionally. A recent study demonstrated, for example, that a long noncoding RNA that is anti-sense to a K+ channel subunit (Kcna2) is upregulated following peripheral nerve injury, leading to a downregulation of the K+ channel and a resulting increase in the excitability of DRG neurons, increasing neuropathic pain (Zhao et al., 2013). Technical Hurdles and Advances Isolating Compartments In the early years, the study of local translation was hampered by the technical difficulty of obtaining pure and sufficient quantities of dendrites and axons for analysis. Pioneering studies used metabolic labeling to demonstrate the synthesis of specific proteins such as tubulin in axons (Giuditta et al., 1968; Koenig, 2009), but the possibility that the signal arose from cell-body contamination could not be eliminated due to these technical limitations. Localized translation was convincingly demonstrated by surgically severing the soma from its processes (Aakalu et al., 2001; Campbell and Holt, 2001; Kang and Schuman, 1996) and, more recently, by the use of chambers in which the processes (dendrites or axons) are fluidically isolated from cell bodies (Eng et al., 1999; Taylor et al., 2010). Other methods for isolating neuronal processes include substrates with limited pore size that allow axons to penetrate but not cell bodies (Torre and Steward, 1992; Zheng et al., 2001) and laser capture microdissection (Zivraj et al., 2010). These methods combined with the rapid increase in the sensitivity of profiling techniques have enabled genome-wide transcriptome analyses to be performed on axons and dendrites in a variety of neurons (see below). Tagging Newly Synthesized Proteins The visualization and identification of newly synthesized proteins has also been a hurdle due to issues of sensitivity (detecting low levels of newly synthesized proteins) as well as difficulties in distinguishing between the movement of existing proteins and the synthesis of new proteins. Puromycin, a tRNA analog, can be used together with fluorescent tags (Smith et al., 2005) or antibodies (Schmidt et al., 2009) to label sites of protein synthesis. Fluorescent reporters, such as photo-switchable Kaede, fused to the 3′UTR regulatory region of mRNAs of interest have enabled de novo protein synthesis to be monitored live in neuronal processes (Aakalu et al., 2001; Brittis et al., 2002; Leung et al., 2006). In addition, new methods have been developed to selectively label the pool of newly synthesized proteins, to ascertain a given cell type or cellular compartment as the site of synthesis, and to visualize the newly synthesized proteins. These methods make use of noncanonical amino acids that cross cell membranes and get charged onto tRNAs by the cell’s own tRNA synthetases and then incorporated into new protein during protein synthesis. These techniques, bio-orthogonal noncanonical amino acid tagging (BONCAT) and fluorescent noncanonical amino acid tagging (FUNCAT) can be used to selectively identify (Dieterich et al., 2006) or visualize (Dieterich et al., 2010) newly synthesized proteins. A modification of the NCAT method, which in principle enables one to label newly synthesized proteins in specific cell types, has also recently been developed (Ngo et al., 2012), and NCAT can be used in combination with 2D difference gel electrophoresis (DIGE-NCAT) to compare the proteomes of specific subcellular (e.g. axonal) compartments (Yoon et al., 2012). Looking Ahead There are many questions for the future, as noted below. 1. How Should We Think about Subcellular Compartments? We know that some compartments (like spines) have plasma membrane as a boundary that can serve to compartmentalize chemical and electrical signals. Other compartments could be determined by the spatial arrangement of molecules, cytoskeleton, or limited diffusion. Are compartments “static” when bounded by anatomy (e.g., a spine) but dynamic when determined by signaling molecule volumes? What defines a subcellular compartment such that mRNAs contain specific addresses to target them there? 2. How Do mRNAs Reach Neuronal Compartments? Some mRNAs are targeted specifically to axons and dendrites and even to the growth cone—how is this targeting achieved? While we have in hand several “zip codes,” there are certainly many messages for which a clear consensus sequence in the UTR has not emerged. In addition, in some cases the signal for recognition by an RNA-binding protein may reside in the secondary structure of the mRNA, rather than the nucleotide sequence. The fact that current secondary structure prediction techniques are limited to small stretches of nucleotides (∼100) complicates our ability to identify binding motifs in 3′UTRs. Adding to the complexity is the recent observation that low-complexity regions of RNA-binding proteins are sufficient to create reversible RNA granule-like structures (Kato et al., 2012). The expanded identification of RBPs as well as the ability to define the binding sites with methods like HITS-CLIP (Licatalosi et al., 2008) should dramatically enhance our knowledge of the binding sites. Future studies should focus on the dynamics of the RNA-protein interactions in cellular contexts. In addition, the possibility that RNA might be delivered from extracellular sources (e.g., via exosomes from neighboring neurons or glia) is a recently suggested exciting idea. 3. How Is the Repertoire of Localized mRNAs Regulated? Unbiased genome-wide analyses have shown that the mRNA repertoire is dynamically regulated with the mRNA repertoire changing over time (Gumy et al., 2011; Zivraj et al., 2010). In addition, it is clear that synaptic activity can lead to the regulated trafficking of mRNA to the distal processes (e.g., Steward et al., 1998). Is this regulated at the level of transcription, or is there some “gating” mechanism that regulates the trafficking of specific transcripts into dendrites/axons? Evidence with ephrinB in RGCs indicates that although the transcripts are present in somas early in development, they do not move into axons until later, suggesting that some kind of specific gating mechanism may exist. 4. How Many Molecules of mRNA Are in a Compartment? Currently, little is known about the quantitative aspects of mRNA localization and translation in neurons. For example, how many RNA molecules are needed to provide a functionally significant amount of protein? How many proteins are synthesized from a single mRNA? One might speculate that some classes of proteins, such as cytoskeletal, would be translated much more than others—such as receptors or channels—and transcript abundance could reflect this difference. In theory, just a few new channel or receptor proteins could be sufficient to alter signaling characteristics within a neuronal microdomain. In addition, a low abundant transcript could be stable and translated with high efficiency. Thus, low-abundance transcripts could exert a significant physiological effect and should not be overlooked in profiling analyses. This also raises the intriguing question of whether translation from monosomes, rather than polysomes, may be more common in distal neuronal compartments where there could be demand for a few highly localized proteins. New high-resolution single molecule detection methods (Cajigas et al., 2012; Park et al., 2012) and live-imaging methods for translation (Chao et al., 2012) will be valuable when answering these sorts of questions. 5. What mRNAs Are Translated in Subcellular Compartments In Vivo? With the advent of TRAP (translating affinity purification) technology (Heiman et al., 2008) it will be possible in the future to answer this question in specific neuronal compartments of specific subsets of neurons. For example, cell-type specific Cre-driver lines can be crossed with the RiboTag mouse (Sanz et al., 2009), which expresses HA-tagged endogenous ribosomal protein (Rrl22), thereby generating mice with specific neurons expressing HA-tagged ribosomes. These can be isolated from mouse brains by immunoprecipitation at different ages and under different conditions (and diseased), and RNA-Seq analysis can identify the ribosome-protected, and therefore, actively translating transcripts. This will be of huge importance in characterizing and understanding the translatome of neuronal compartments. Thus, current technology now offers the exciting possibility of being able to discover differences in the dendritic or axonal translatome of diseased (e.g., autosomal models) individuals. 6. How Is Translation Regulated in Space? How does the spatial morphology of the dendrite, axon, or spine contribute to or constrain protein synthesis? It was recently shown that spines enhance the cooperative interaction among multiple inputs (Harnett et al., 2012). These observations suggest that the amplifying and coordinating properties of dendritic spines have an effect on neuronal input processing and may influence information storage by promoting the induction of clustered forms of synaptic and dendritic plasticity among coactive spines. This could allow spines to enhance the ability of neurons to detect, uniquely respond to, and store distinct synaptic input patterns (Harnett et al., 2012). Different patterns of synapse activation can lead to protein synthesis-dependent or -independent plasticity (Govindarajan et al., 2011). However, the importance and mechanism of specific protein translation remains to be examined in this cooperativity. Since there are mRNAs that are differentially distributed in the length of the dendrites, it is tempting to speculate that there is a role for protein synthesis in regulating the functional compartment in dendrites and spines. Thus, while it is clear that protein synthesis occurs in the dendrite and that it is regulated by neuronal activity, the extent to which the activity of single synapses or synaptic regions stimulates protein synthesis, or alters protein localization, remains unknown. Moreover, the importance and impact of synapse location along the dendrite or axon for protein synthesis is unknown. 7. How Is Translation Coordinated with Degradation? In the small cytoplasmic volume of a dendritic spine or growth cone, there is a limit to the amount of protein that can fit into the space before molecular crowding becomes a problem. While it is clear that changes in synaptic transmission involve extensive regulation of the synaptic proteome via the regulated synthesis and degradation of proteins (Fonseca et al., 2006; Wang et al., 2009), it is not well understood how these two processes are coordinately regulated to achieve the desired level of individual proteins at synapses. Indeed, this is another level of homeostatic control that must exist in order for synapses to maintain the desired level of receptors, scaffolds, and signaling molecules. Changes in the steady-state level of a protein have to be particularly fast and fine-tuned in neurons, due to the fast nature of synaptic transmission and the rapid induction of plasticity. 8. How Specific Is mRNA Translation, and How Is It Regulated? How are specific mRNAs translated and not others? Studies using either global activity manipulations (TTX/APV) (Sutton et al., 2004) or application of an D1/D5 agonist (Hodas et al., 2012) have suggested large-scale (at least ∼100 distinct proteins synthesized) changes in the dendritic proteome. Similarly, global cue stimulation of axons elicits the de novo translation of hundreds of new proteins (Yoon et al., 2012). In these studies, however, the stimulation was applied to the entire network (dish of cultured neurons or brain slice). Under physiological conditions the spatial and temporal profile of synaptic and cue stimulation is on a much finer scale and the translational readout is likely limited. Indeed, we know that different cues can trigger translation of specific subsets of mRNAs in the growth cone (Lin and Holt, 2007). The mechanisms by which specific patterns of synaptic signals (e.g., different frequencies of stimulation, different concentrations or gradients of agonists) and receptor activation lead to activation of the translation machinery are not well understood. Mechanistically, it is clear that elements contained in the 5′ and 3′UTR of mRNAs can regulate their translation initiation. In addition, it is probably the case that the spatial proximity of an mRNA to an active translation site plays a role. The use of high-resolution imaging techniques and focal stimulation should provide answers to these questions. 9. What Roles Do MicroRNA and Other Noncoding RNAs Play in Regulating Local Translation and Neuronal Function? In neurons, the miRNA function has been explored both individually and on a population level, but a broad conceptual understanding is still lacking. Moreover, if miRNAs regulate mRNA translation and expression in different neuronal compartments, what regulates the expression of miRNA themselves? The accessibility of deep sequencing has enabled the detection of other noncoding RNA species in neurons. These additional RNA classes can directly regulate translation, regulate miRNA function, or serve as scaffolds for other molecules, making the levels of regulation and interactions potentially extremely complicated. In addition, the recent appreciation of the abundance and regulatory potential of other noncoding RNAs, mostly in nonneuronal cell types, adds another level of complexity, including the recent demonstration of regulation by circular RNAs that may serve as either shuttles, assembly factories, or sponges for miRNAs and/or RBPs (Hentze and Preiss, 2013). Based on this, it is likely that a real understanding of the complexity of RNA function in neurons will require not only investigation of individual molecules but also a systems biology perspective where the entire network of RNA molecules and their targets can be considered together (see Peláez and Carthew, 2012). 10. Do Specialized Ribosomes Exist, and Can They Tune Translation? While ribosomes are readily visible in dendrites spines (Ostroff et al., 2002) and growth cones (Bassell et al., 1998; Bunge, 1973) how they are transported and whether they are sequestered or anchored is not well understood. A mechanism that could provide specificity or docking would be the specialization of ribosomes by accessory proteins or subunits. One of the most intriguing questions raised by recent work is whether ribosomes are tuned to translating specific mRNAs. This possibility is suggested by recent studies showing that haplo-insufficiency of several different ribosomal proteins give rise to specific phenotypes rather than affecting all cells ubiquitously (Kondrashov et al., 2011; Uechi et al., 2006; Xue and Barna, 2012). This has given rise to the notion of a “ribocode” that suggests heterogeneity in the composition of ribosomes, enabling ribosomes to be tuned to translate specific mRNAs via specific ribosomal proteins (Xue and Barna, 2012). In addition, a striking and curious feature of many recent sequencing studies is the detection of many ribosomal subunits in dendritic or axonal fractions. Indeed, the single most abundant class of mRNAs encode ribosomal proteins in axons (Andreassi et al., 2010; Gumy et al., 2011; Taylor et al., 2009; Zivraj et al., 2010). Thus, an additional intriguing possibility suggested by the abundance of ribosomal protein mRNA in axons and dendrites is that ribosomal proteins may be synthesized de novo. This could provide proteins for in situ repair of ribosomes, or even more interestingly could provide onsite “tuning” of translation (Lee et al., 2013). 11. Does Dysregulated Protein Synthesis Underlie a Wide Range of Neurological Disorders? One of the most exciting clinically relevant findings to emerge from recent work is the link between dysregulated synaptic protein synthesis and neurological disorders (Bear et al., 2008; Darnell and Klann, 2013; Liu-Yesucevitz et al., 2011). Mouse models of neurodevelopmental disorders such as autism spectrum disorder (ASD) show significant improvement on treatment with reagents that target the protein-synthesis pathway (Bear et al., 2008; Darnell and Klann, 2013; Gkogkas et al., 2013; Santini et al., 2013), opening up new possibilities in terms of potential therapeutics. Much of the focus has been on the postsynaptic side of the synapse, the predominant site of plasticity and learning. Recent evidence indicates that regulated protein synthesis in the presynaptic compartment is also important for synapse formation (Taylor et al., 2013) and axon arborization (Hörnberg and Holt, 2013; Hörnberg et al., 2013; Kalous et al., 2013), raising the question of whether defects in axonal protein synthesis contribute to the miswiring aspects of neurodevelopmental disorders. Dysregulated protein synthesis may also underlie a broad range of neurodegenerative disorders (Fallini et al., 2012; Liu-Yesucevitz et al., 2011) consistent with axonal protein synthesis being required for axon maintenance (Hillefors et al., 2007; Yoon et al., 2012). Indeed, the first “effective” oral drug treatment that prevents neurodegeneration in a prion disease/Alzheimer’s mouse model targets a kinase (PERK) that shuts down protein synthesis as part of the unfolded protein response (Moreno et al., 2013). Summary Recent years have witnessed a transformation in our appreciation of RNA function in dendrites/axons on the one hand and of neuronal compartments as spatially distinct signaling/processing units on the other. Here we have highlighted the convergence of these two areas and have sought to define some of the many interesting questions and challenges that lie ahead. As technical approaches become increasingly sensitive for unbiased profiling there is the promise of improved “understanding” of the qualitative concepts that govern the various active RNA species and formation and function of compartments as well as quantitative details on the stoichiometries of all of the players positioned within the morphological framework of the neuron and its remarkable dendritic and axonal arbor.

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Journal ID (nlm-ta): RNA Biol

Journal ID (iso-abbrev): RNA Biol

Journal ID (pmc): KRNB

Title: RNA Biology

Publisher: Taylor & Francis

ISSN (Print): 1547-6286

ISSN (Electronic): 1555-8584

Publication date Collection: August 2015

Publication date (Electronic): 7 July 2015

Volume: 12

Issue: 8

Pages: 801-809

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Department of Biology; Technion – Israel Institute of Technology ; Haifa, Israel

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[* ]Correspondence to: Yoav Arava; Email: arava@ 123456tx.technion.ac.il

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Publisher ID: 1058686

DOI: 10.1080/15476286.2015.1058686

PMC ID: 4615199

PubMed ID: 26151724

SO-VID: b66c0218-17a5-4059-b7fb-b68eb5280102

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This is an Open Access article distributed under the terms of the Creative Commons Attribution-Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The moral rights of the named author(s) have been asserted.

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Date received : 20 April 2015

Date revision received : 19 May 2015

Date accepted : 29 May 2015

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