RNA was isolated from the chosen tissue and segregated into a total RNA fraction and a polysome-bound RNA fraction. Polysome-bound RNAs was isolated via fractionation in sucrose gradient as previously described (Lou et al., 2014), with fractions containing RNA bound to two or more ribosomes collected.

The samples were profiled with Affymetrix arrays (model Mouse430_a2) with RNA input amounts of 5 and 3 μg for total and polysome-bound RNA fractions respectively. Array data is accessible from GEO (GSE92657). Array data corresponding to each fraction were normalized separately, as polysome-bound RNA is a subset of total RNA and standard microarray normalization methods that assume equality of distributions of total intensity between arrays could not be used.

Normalization was performed using the vsn method as implemented in the vsnrma function from the R/bioconductor package vsn (Huber et al., 2002). lts.quantile = 0.5 was used to allow for robust normalization when many genes are differentially expressed. Differential expression was calculated using limma (Smyth, 2004) from R/bioconductor at the level of probesets, the parameter “trend” was set to TRUE for the empirical moderation of standard errors. Probesets with Benjamini-Hochberg false-discovery rates (FDR) <0.05 were considered as differentially expressed. Probesets were then translated to Ensembl gene IDs (Ensembl v72; www.ensembl.org), and those mapping to multiple IDs were excluded from subsequent analysis. For cell marker analysis normalized microarray intensities were averaged over replicates. The expression values for 103 measured marker genes were used to show the composition of samples.

Enrichment analysis of GO biological process categories between up- and down-regulated genes were performed separately for each of the RNA fractions. To this end, up-regulated genes were compared against a background of all differentially expressed genes with the hypergeometric distribution, using GOstats (Falcon and Gentleman, 2007) and annotation from the org.Mm.eg.db v2.14.0 package, both from R/bioconductor. Under-representation of up-regulated genes in a category is equivalent to having an enrichment of down-regulated genes, and is displayed as such.

For the enrichment study of CPE in the mouse and fly genomes, GO annotations from annotation packages org.Mm.eg.db v2.14.0 and org.Dm.eg.db v2.14.0 with experimental evidence code (i.e., EXP, IDA, IPI, IMP, IGI, IEP) were used. The selectiveness is because GO annotations are based on different kinds of evidence including homology, and circularity would occur when comparing results from two different genomes with homology included. To prevent artificially inflating the number of motifs when genes have more than one transcript with common 3′UTR, we performed the enrichment analysis at the level of genes. Transcripts with annotation of transcript biotype as protein coding were translated to Ensembl gene ID and then to Entrez. Genes with only CPE-containing transcripts were compared against all genes (excluding those with both CPE-containing and CPE-free transcripts) with the hypergeometric distribution using GOstats.

Results from the enrichment analyses were visualized using Cytoscape v3.0.2 (Shannon et al., 2003). Results were represented on the GO subnetworks comprising of categories significant in at least one of the comparisons (Benjamini-Hochberg FDR <1e-4 for Figure 2 and <1e-5 for Figure 4C), with each node referring to one GO category. Color represents the direction of enrichment, and the intensity of color and size of the node represent significance (Benjamini-Hochberg BH FDR >0.05 is depicted as white).

The UTR sequences from transcripts belonging to genes with Ensembl annotation as known and protein coding were obtained from Ensembl v72 and searched for regular expressions representing motifs. Sequences used for each motif (Tian et al., 2005; Piqué et al., 2008; Spasic et al., 2012) are listed in Table S4.

Probesets were translated to Ensembl transcript ID (Ensembl v72), and only probesets mapping a unique transcript were used. Distributions of log2 (fold change) were compared using the Kolmogorov-Smirnov test in R (http://cran.rproject.org/). To represent the expression change profiles for transcripts from specific GO categories, we used GO annotation at the level of transcript downloaded from Ensembl v72 with the R/Bioconductor package biomaRt.

Western blotting against Cpeb1 protein in spinal cord tissues was performed with standard procedures using an antibody raised in-house by the group of H. Zentgraf. Cell lysates of murine hippocampal HT22 cells transiently over-expressing Cpeb1 were used as positive control.

FISH was performed using RNAscope Fluorescent Multiplex Kit (Advanced Cell Diagnostics) as per the manufacturer's protocol. Briefly, spinal cords were cryosectioned into 10 μm thick sections. Antigen retrieval for FISH was performed by immersing sections in boiling Target Retrieval solution for 5 min, thereafter washing in 100% ethanol. Protease 3 was added to the sections and incubated at 40°C for 30 min. FISH probes for Cpeb1 (channel C1) and dapB (bacterial gene as negative control, channel C3) were added and incubated at 40°C for 2 h. Sections were then incubated with various amplification solutions according to the standard manufacturer's protocol.

After FISH was completed, sections were blocked with 3% goat serum and 0.3% Triton X in PBS for 1 h, then incubated with B3-tubulin antibody (Abcam 21057, 1:200) at 4°C overnight, followered by donkey anti-goat Alexa555 antibody (1:500) and DAPI at room temperature for 2 h.

Experimental procedures were performed in compliance with animal protocols approved by the Animal and Plant Care Facility at the Hong Kong University of Science and Technology. C57BL/6 mice of 5–6 weeks of age were anesthetized with ketamine (80 mg/kg) and xylazine (10 mg/kg) and received Meloxicam (1 mg/kg) as analgesia after the surgery. AAV-vectors (serotype 2/2, titer 1 × 10¹² vg/ml, 2 μl injection volume) expressing either Cpeb1-HA or Gfp under the neuron-specific human synapsin promoter (hSyn) were injected into the left vitreous bodies of 12 mice with a Hamilton microsyringe. Five weeks after vector injection, the optic nerve was gently exposed intraorbitally and crushed with jeweler's forceps (Dumont #5; Fine Science Tools) around 1 mm behind the optic disk. Mice were kept for 2 weeks after injury before tracing. To visualize RGC axons in the optic nerve, 1.5 μl cholera toxin β subunit conjugated with Alexa555 (CTB555, 2 μg/μl, Invitrogen) were injected into the vitreous bodies. Two days after the CTB injection, animals were sacrificed by transcardial perfusion for histology examination. In each mouse, the completeness of optic nerve crush was verified by showing that anterograde tracing did not reach the superior colliculi.

Eyes and optic nerves were cryosectioned and examined under an epifluorescence (Nikon, TE2000) or confocal microscope (Zeiss, LSM Meta710). For determination of RGC infection efficiency and expression levels of Cpeb1, retinal sections were stained with anti-HA (Cell Signaling 2367), and anti-Cpeb1 (Proteintech 13274-1-AP) antibodies. Total numbers of RGCs were determined by whole-mount retina staining with mouse anti-Tuj1 antibody (Covance). Twelve images (3 for each quarter, covering peripheral to central regions of the retina) from each retina were captured under a confocal microscope (400X) and Tuj1-positive cells were counted in a blind fashion. To detect traced axons after optic nerve crush, longitudinal sections of optic nerves were serially collected. To analyze the extent of axonal regeneration in the optic nerve, the number of axons that passed through distance d from the lesion site was estimated using the following formula: ∑ad=πr2×[average axon numbers per mm/t], where r is equal to half the width of the nerve at the counting site, the average number of axons per mm is equal to the average of (axon number)/(nerve width) in 4 sections per animal, and t is equal to the section thickness (8 μm). Axons were manually counted in a blind fashion. An exponential decrease model was fitted to the data and used to compare the starting numbers of axons and the rates of decrease as one moves away from the lesion point.

Primary cultures of cortical neurons were prepared from embryos of Cpeb1^flox/flox mice. Cre-mediated excision will remove exon 4 of Cpeb1 and cause a frameshift that affects the phosphorylation site for activation of Cpeb1 as well as its RNA recognition motifs. Cultures were prepared from cortices of E16.5 embryos. Briefly, dissected cortices were digested with 0.05% trypsin for 15 min, triturated with a fire-polished glass pipette and plated on poly-L-lysine coated surfaces. Neurons were cultured in HS-MEM [1x MEM (Thermo Fisher), 10% horse serum, 1.2% glucose, 4 mM L-glutamine, 1 mM sodium pyruvate, 0.22% NaHCO₃, 100 U/ml penicillin-streptomycin] and infected with serotype 2 AAV encoding CAG-Cre at an MOI of 1 × 10⁵. Twenty-four hours later medium was replaced with N2B27-MEM [1x MEM (Thermo Fisher), 1x N2 supplement, 1x B27 supplement, 0.1% ovalbumin, 0.6% glucose, 2 mM L-glutamine, 1 mM sodium pyruvate, 0.22% NaHCO₃, 100 U/ml penicillin-streptomycin].

Neurons were cultured on Fluoroblok transwell chambers with PET membranes with 3 μm pores (Millipore) that allow extension of neuronal processes to the underside of the membrane while keeping cell somas on the top. After 7 days in culture, the underside was scraped with sterile cotton swabs to cut the processes. Twenty-four hours after injury, processes were labeled with addition of 1 μM of Calcein AM (BD Biosciences) to the culture medium and imaged with a Zeiss Cell Observer epifluorescence microscope. Images were analyzed and traced with a custom wrote macro in ImageJ in a blind manner. A mixed effects model was used for statistical comparison to account for variability in various levels of the experimental setup.

To measure axonal outgrowth during development, flies were reared at 25°C and were dissected in fresh PBS. A minimum of 5 fly brains (10 sLNv projections) per genotype were fixed in 4% formaldehyde and stained with an anti-GFP antibody (Molecular Probes; 1:500), according to standard methods (Ayaz et al., 2008). For the axonal regrowth analysis after injury, flies were reared at 18°C (to minimize developmental effects), and shifted to 25°C 1 day prior to injury. Whole brain explants on culture plate inserts were prepared as described (Ayaz et al., 2008; Koch and Hassan, 2012). In brief, culture plate inserts (Milipore) were coated with laminin and polylysine (BD Biosciences). Fly brains were carefully dissected out in a sterile Petri dish containing ice cold Schneider's Drosophila Medium (GIBCO), and transferred to one culture plate insert containing culture medium (10 000 U/ml penicillin, 10 mg/ml streptomycin, 10% Fetal Bovine Serum, and 10 μg/ml insulin in Schneider's Drosophila Medium (GIBCO). sLNv axonal injury was performed using an ultrasonic microchisel controlled by a powered device (Eppendorf) as described (Ayaz et al., 2008; Koch and Hassan, 2012) and dishes were kept in a humidified incubator at 25°C. Four days later, cultured brains were fixed and immunohistochemical staining was performed as for freshly dissected samples.

For the outgrowth experiments, brains were visualized under a fluorescent microscope equipped with a GFP filter and classified as having “increased outgrowth,” “reduced outgrowth,” or “no observable effect” according to comparison of sLNv length with that of controls.

For the injury experiments, de novo growth was assessed 4 days after injury by measuring injured sLNv projection that has formed at least one new axonal sprout of a minimum length of 12 μm. The exact injury location was accessed by comparison with axonal projection length at 5 h (where no de novo growth has occurred). Imaging was performed on a Zeiss 500 or 700 confocal microscope and analyzed with Image J. Regenerated length was defined as the de novo axon lengths using the manual tracing tool. Projected distance was defined as the displacement of the axon sprouts from the lesion site, measured in a straight line. All images were analyzed in a blind manner. Statistical comparisons were performed with two-tailed student's t-test.

To study post-transcriptional regulation in the spinal cord during the abortive regeneration phase following injury, we performed simultaneous profiling of the transcriptome and translatome from injured and naïve mice via translation state array analysis (TSAA). Total and polysome-bound RNAs were extracted from spinal cord tissues of injured and naïve mice 9 h after injury (Figure 1A). This time point was chosen to be within the transient regenerative phase after spinal cord injury, thereby allowing sufficient time for transcriptional and translation changes to take place, under limited immune response conditions (Hausmann, 2003; Trivedi et al., 2006; Schwanhäusser et al., 2011; Gadani et al., 2015). Spinal cord tissue surrounding the injury site was used for RNA profiling, to gain insights into the processes taking place in the axonal ends affected by the injury. In order to obtain sufficient input materials, 2.5 cm of spinal cord tissues were taken. Polysome-bound RNAs were isolated via sucrose gradient fractionation, and fractions containing RNA bound to two or more ribosomes were collected. Samples were subsequently hybridized onto Affymetrix microarrays. Expression changes are listed in Table S1. Notably, correlation plots between arrays shows low variability between replicates, and assessment of expression changes by quantitative real-time PCR (qPCR) largely validated the expression changes obtained from microarray analysis (Figures S1A,B).

Since the chosen tissue not only contains the injured neuronal processes, but also other cellular subtypes, we first analyzed whether the injury would have a major impact on cellular tissue composition at this early time point. To this end we compared the intensities of probesets mapped to marker genes for motor neurons and other local neurons, oligodendrocytes, microglia, precursor cells present in the central canal, and blood-borne cells (Figure S1C, Table S2). The analysis revealed a high correlation between expression patterns of naïve and injured spinal cord (0.97 and 0.99 Pearson correlation for total and polysome-bound RNA fraction, respectively), indicating the absence of major changes in tissue composition upon injury. By contrast, a high proportion of probesets in both total and polysome-bound RNA fractions exhibited significant changes upon injury (Figure 1B). Importantly, for many differentially expressed probesets, the changes in total and polysome-bound RNA fractions do not correlate (Figures 1B–D). A large proportion of changes occur only in the total RNA fraction with no corresponding changes in the polysome-bound RNA fraction. This agrees with previous observations in which stress conditions trigger a general shut down of translation to maximize cell survival (Park et al., 2008; Yamasaki and Anderson, 2008). Differentially regulated genes in the total RNA fraction are similarly distributed between up- and down-regulation. On the other hand, the polysome-bound RNA fraction showed fewer differentially regulated genes than the total RNA fraction, with most of those being down-regulated (Figures 1B,C). The difference in numbers of differentially regulated genes between the total and polysome-bound fractions indicates that the translational response to injury is highly uncoupled from RNA availability. In addition, many genes displayed opposing directions of regulation, suggesting considerable influence of post-transcriptional regulation (Figure 1D).

To assess the functional role of the observed uncoupling effect, Gene Ontology (GO) (Ashburner et al., 2011) enrichment analysis was performed and visualized using Cytoscape (Shannon et al., 2003). Enrichment of up- and down-regulated genes was represented as red and blue nodes respectively. In the total-RNA fractions, transcript availability of genes related to translation, RNA processing, protein catabolic processes and protein transport was increased upon injury, but decreased for genes related to CNS development (Figure 2A and Table S3). Excitingly, in the polysome-bound RNA fraction, injury increased ribosome-loading of genes related to regulation of CNS development, as well as cell death, transcription, RNA processing, and immune response (Figure 2B and Table S3). Notably, there were no significantly under-represented categories in the polysome-bound RNA fraction, indicating that the decrease in translation after injury is a general effect and neither directed nor functionally clustered.

Different trends of enrichment were observed for many GO categories between the total and polysome-bound RNA fractions, suggesting that uncoupling serves specific functional purposes. Of particular note, categories related to CNS development, which are decreased in the total RNA fraction, remain stable or enriched in ribosomal-loaded transcripts. This might explain the temporary regeneration observed following injury, which is absent at later stages of the injury response, as existing transcripts from regenerative genes continue to be translated at first, but are not replaced upon eventual degradation.

As the RNA profiling was performed using spinal cord tissues which contain various cell types, it is necessary to investigate if the uncoupled transcripts are of neuronal origin, and thereby affect axonal growth. For this purpose, we turned to Drosophila, which allows generation of a large number of neuron-specific transgenic animals in a fast and robust way. Using the UAS-Gal 4 (Brand and Perrimon, 1993), we expressed each of a total of 38 candidate uncoupled genes—for which a fly homolog exists and a UAS line was available—in a fly CNS neuron population called the small ventral lateral neurons (sLNvs) (Figure 3A). Most of the genes tested have reduced transcript availability but stable ribosomal loading in both naïve and injured spinal cord (Table S1). A minimum of 5 brains per genotype was analyzed. Indeed, we found that 19 (50%) of the tested candidates influenced the developmental growth of the sLNv axonal projection, indicating that they have a function in neurons and a role in axonal growth. Amongst them, 12 increased growth, while seven resulted in shorter sLNv projections (Figure 3B and Figure S2).

Next, we asked whether there are common features shared among the uncoupled transcripts, especially since the Drosophila experiments suggest that such transcripts are enriched for genes modulating axonal growth. To address this question, we examined the presence of common RNA features. It has been shown that the 3′UTR harbors a myriad of regulatory motifs that regulates stability, intracellular localization and translation of its RNA host (Moore, 2005; Szostak and Gebauer, 2013). Many important neuronal mRNAs such as Map2, Bdnf, β-actin, and Gap43 are regulated via their 3′UTRs (Blichenberg et al., 1999; Lau et al., 2010; Donnelly et al., 2011). This prompted us to investigate the association of 3′UTR motifs in a given transcript with its expression upon injury. Since this has to be performed on the transcript level, only probe sets mapping to a unique transcript were used. We have chosen several 3′UTR motifs to be analyzed based on their published relevance to neuronal functions: cytoplasmic polyadenylation element (CPE) (Si et al., 2010; Darnell and Richter, 2012), Pumilio binding element (PBE) (Vessey et al., 2006; Kaye et al., 2009), and Musashi binding element (MBE) (Nakamura et al., 1994; Hadziselimovic et al., 2014). Hex (hexanucleotide involved in polyadenylation) and AU-rich (AUR) elements (AREs) were also analyzed for their well reported functions in regulating RNA polyadenylation and stability respectively (Colgan and Manley, 1997; Gingerich et al., 2004). The sequences of the motifs used in the analysis are listed in Table S5. To investigate differences in expression changes upon injury relative to motif-free transcripts, we plotted the density curves showing the probability of a data point to have a given log2-fold change, thus reflecting the pattern of distribution of expression of the set of transcripts of interest (Figure 4 and Figures S3, S5).

This analysis revealed that there is a general decrease in levels of transcripts in the total RNA fraction, as indicated by the peaks of the density curves being below zero log2 fold change. However, the density curve of CPE-containing RNAs is notably shifted toward the right side when compared with non-CPE-containing RNAs, and the two curves are significantly different from each other as assessed by Kolmogorov-Smirnov test. (Figure 4A) This shows that CPE-containing transcripts are associated with resistance to injury-induced down-regulation as compared to transcripts devoid of CPE. Notably, this association is also seen when looking specifically at subsets of genes in axon and CNS development GO categories (Figure 4C). In contrast, presence or absence of CPE did not influence injury-induced changes on the level of ribosomal-loading (Figure 4B,D). Likewise, RNA transcripts possessing PBE, MBE, Hex, and AREs were also associated with resistance to injury-induced down-regulation in the total but not in the polysome-bound RNA fractions (Figures S3, S5). However, in contrast to CPE, presence of PBE, MBE and Hex do not affect the levels of RNA in the total fraction of transcripts in axon and CNS development GO categories (Figure S4). We next investigated whether there is a link between AREs and CPE, PBE, MBE, and Hex, and found that they tend to co-occur in the mouse transcriptome. In fact, transcripts containing CPE, PBE, MBE, or Hex tend to also include AREs sequences. In addition, having AREs and one of these motifs is associated with resistance to injury-induced down-regulation in total RNA fraction, suggesting that the AREs motifs might function with the other motifs in a synergistic manner (Figures S5C,D, S6). To ensure that the observed associations between the motifs and fold changes are genuine, the same analysis was performed with the motifs on the 5′UTR or with random motifs. As expected, this control experiment does not show any significant association (Figure S7).

Taken together, the data suggest that CPE, PBE, MBE and Hex confer transcript stability against the global decrease induced by spinal cord injury by increasing RNA stability in conjunction with ARE motifs. Although all the tested 3′UTR motifs are associated with higher resistance to injury-induced down-regulation, only CPE maintained this association in transcripts included in CNS development and axon development GO categories. In addition, CPE-containing genes include validated positive regulators of axonal regeneration such as Cebpβ and c-Jun (Yan et al., 2009; Fontana et al., 2012), which are among the CPE-containing transcripts with the highest up-regulation upon injury in the total RNA fraction (Table S1). Together with the fact that Cpeb1 overexpression in Drosophila promoted robust axonal growth of developing sLNvs (Figure 3 and Figure S2B), we chose Cpeb1 for further detailed investigation.

To elucidate whether CPE has a general functional role, GO enrichment analysis was performed on the prevalence of CPE among all protein coding genes of the mouse and fly genomes. Many nervous system development categories were enriched among CPE containing genes in the mouse genome, including neuron projection morphogenesis, axonogenesis and axon guidance (Figure 4E and Table S6). There were no categories found with an under-representation of CPE. Interestingly, almost all categories in the mouse genome enriched in CPE-containing genes are also enriched in Drosophila, suggesting a high level of conservation of CPE function between the two species.

Our data suggest that CPE-enriched transcripts are temporarily protected from degradation after injury. Accordingly, we found that whereas the cpeb1 transcript already decreases at 9 h following injury, the decrease in the protein level is delayed, starting at 24 h, as assessed by RT-PCR and WB of whole spinal tissues in naïve and at different time points following SCI (Figures S8A,B). Due to the lack of a high quality antibody for immunohistochemical staining of endogenous Cpeb1 in spinal cord tissue, we performed RNA FISH instead in combination with B3-tubulin staining (Figure S8C). Cpeb1 RNA was mainly found in B3-tubulin positive cells with a morphology characteristic of motor neurons. Altogether, these data indicate that Cpeb1 localizes to neurons, and while its transcript tend to decrease immediately following spinal cord injury, the decrease in protein levels is delayed to later time points, which may explain the observed protection of CPE-transcripts at 9 h following SCI.

To address the neuronal specific role of Cpeb1 in axonal regeneration, and specifically whether the failure to up-regulate Cpeb1 might in part explain the transient and abortive nature of the regenerative response to injury, we overexpressed the fly homolog of Cpeb1, Orb, exclusively in the sLNvs. Fly brains were dissected and kept in culture as described (Ayaz et al., 2008; Koch and Hassan, 2012; Koch et al., 2018). sLNvs were mechanically injured and the regenerative response was assessed after 4 days. 13 and 12 brains were analyzed for Orb+Gfp and Gfp only control respectively (Figures 5A,B). It was observed that the number of regenerated sprouts increased from a mean of 2.42 ± 0.336 (SEM) per brain in controls to 3.75 ± 0.279 (SEM) with the overexpression of Orb (Figure 5C). In addition, regenerated length was increased from 31.61 μm ± 2.87 (SEM) per brain in controls to 126.74 μm ± 10.6 (SEM) with Orb overexpression (Figure 5D). Likewise, displacement from the lesion point, which is the distance between the lesion point and the axon tip and accounts for proper pathfinding, also increased from 25.42 μm ± 2.39 (±SEM) per brain in controls to 93.76 μm ± 7.17 (SEM) with Orb overexpression. (Figure 5E).

To investigate whether this effect is conserved in mammals too, we turned to a mouse model of optic crush injury that allows overexpression of Cpeb1 in mouse retinal ganglion cells (RGCs). RGCs were infected with adeno-associated viral (AAV) vectors expressing Cpeb1-HA or Gfp under the neuron-specific human synapsin (hSyn) promoter. Thereafter, regeneration of RGC axons was assessed 2 weeks following a crush injury of the optic nerve. Six optic nerves from six animals with Cpeb1 overexpression and six control optic nerves with GFP virus infection were analyzed 2 weeks after injury. Staining of RGCs indicated a similar infection efficiency for AAV-Cpeb1-HA (79%) and the control AAV-Gfp (70%), and overexpression of Cpeb1 was verified by staining (Figures 5F,G). Regeneration was quantified as the number of regenerating axons reaching different distances from the lesion point. Importantly, as in Drosophila, over-expression of Cpeb1 in RGCs significantly increased the number and lengths of regenerating axons (Figures 5H,I). AAV-Cpeb1 infected RGCs start with approximately double the number of axons than AAV-Gfp infected ones at 0.1 mm past the lesion point (p = 0.0005). While the number of axons from both groups decrease across distance, this ratio is nearly maintained (test for difference in rate of decrease p = 0.0759), meaning that about twice the number of axons crosses distances up to 1.0 mm in the AAV-Cpeb1 infected RGCs than the control infected ones (Figure 5I). The number of survived RGCs in the retinas remained constant, indicating that the regenerative effect is not due to reduced cell death after injury (Figures 5J,K). To test whether knockout of Cpeb1 produces an opposite effect, we knocked out Cpeb1 in primary cultures of mouse cortical neurons. Efficient knockout is triggered via AAV-Cre mediated deletion of exon 4 (Figure S9A), which causes a frameshift that affects the activation and RNA recognition domains of Cpeb1. Neurons were cultured in a transwell chamber which specifically allows neurites to grow on the underside of the chamber. Scraping the lower side of the transwell mimicked a transection-injury. Thereafter, regenerating neurites on the underside were traced after 24 h (Figure S9B). Notably, knockout of Cpeb1 reduced the number of regenerating neurites from a mean of 447.41 ± 101.6 (SEM) to 167 ± 41.8 (SEM) per chamber (Figure S9C). The length of regenerated neurites was also reduced, albeit mildly, from 60.1 μm ± 2.14 (SEM) to 55.39 μm ± 1.57 (SEM) per chamber (Figure S9D). Together, these data support the notion that Cpeb1 is an enhancer of regeneration, and that this function is conserved between mice and Drosophila.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.