XB-ART-50287
Dev Biol
December 15, 2015;
408
(2):
269-91.
An in vivo screen to identify candidate neurogenic genes in the developing Xenopus visual system.
Bestman JE
,
Huang LC
,
Lee-Osbourne J
,
Cheung P
,
Cline HT
.
Abstract
Neurogenesis in the brain of Xenopus laevis continues throughout larval stages of development. We developed a 2-tier screen to identify candidate genes controlling neurogenesis in Xenopus optic tectum in vivo. First, microarray and NanoString analyses were used to identify candidate genes that were differentially expressed in Sox2-expressing neural progenitor cells or their neuronal progeny. Then an in vivo, time-lapse imaging-based screen was used to test whether morpholinos against 34 candidate genes altered neural progenitor cell proliferation or neuronal differentiation over 3 days in the optic tectum of intact Xenopus tadpoles. We co-electroporated antisense morpholino oligonucleotides against each of the candidate genes with a plasmid that drives GFP expression in Sox2-expressing neural progenitor cells and quantified the effects of morpholinos on neurogenesis. Of the 34 morpholinos tested, 24 altered neural progenitor cell proliferation or neuronal differentiation. The candidates which were tagged as differentially expressed and validated by the in vivo imaging screen include: actn1, arl9, eif3a, elk4, ephb1, fmr1-a, fxr1-1, fbxw7, fgf2, gstp1, hat1, hspa5, lsm6, mecp2, mmp9, and prkaca. Several of these candidates, including fgf2 and elk4, have known or proposed neurogenic functions, thereby validating our strategy to identify candidates. Genes with no previously demonstrated neurogenic functions, gstp1, hspa5 and lsm6, were identified from the morpholino experiments, suggesting that our screen successfully revealed unknown candidates. Genes that are associated with human disease, such as such as mecp2 and fmr1-a, were identified by our screen, providing the groundwork for using Xenopus as an experimental system to probe conserved disease mechanisms. Together the data identify candidate neurogenic regulatory genes and demonstrate that Xenopus is an effective experimental animal to identify and characterize genes that regulate neural progenitor cell proliferation and differentiation in vivo.
PubMed ID: 25818835
PMC ID: PMC4584193
Article link: Dev Biol
Grant support: [+]
R01 EY011261 NEI NIH HHS , R01 NS076006 NINDS NIH HHS , EY011261 NEI NIH HHS , NS076006 NINDS NIH HHS
Species referenced: Xenopus
Genes referenced: actn1 arl9 armc8 chn2 cpeb1 ctdnep1 dio3 efna3 eif3a elk4 ephb1 epx fbxw7 fgf2 fmr1 fxr1 glis2 gstp1 hat1 hdac6 hspa5 hspd1 lsm6 mecp2 mkrn2 mocs3 prkaca pura r3hdm2 rbfox2 slc12a2 sox2 tecta.2 tle1 vangl1 wnt7b
Morpholinos: actn1 MO1 arl9 MO1 armc8 MO1 chn1 MO1 cpeb1 MO2 ctdnep1 MO3 dio3 MO1 efna3 MO1 eif3a MO1 elk4 MO1 ephb1 MO1 epx MO1 fbxw7 MO1 fgf2 MO1 fmr1 MO2 fxr1 MO1 glis2 MO1 gstp1 MO1 hat1 MO1 hdac6 MO1 hspa5 MO2 lsm6 MO1 mecp2 MO2 mkrn2 MO3 mmp9.1 MO2 mocs3 MO1 prkaca MO2 pura MO1 r3hdm2 MO1 rbfox2 MO1 slc12a2 MO1 tle1 MO1 vangl1 MO1 wnt7b MO1
Phenotypes: Xla Wt + actn1 MO (fig.8) [+]
Xla Wt + actn1 MO
(Fig.8.A)
Xla Wt + arl9 MO (fig.8)
Xla Wt + arl9 MO (Fig.8.A)
Xla Wt + armc8 MO (fig.7.d1-d5)
Xla Wt + armc8 MO (fig.7.d1-d5)
Xla Wt + armc8 MO (fig.8)
Xla Wt + armc8 MO (fig.8)
Xla Wt + armc8 MO (Fig.8.A)
Xla Wt + armc8 MO (Fig.8.B-C)
Xla Wt + chn1 MO (fig.8)
Xla Wt + chn1 MO (fig.8)
Xla Wt + chn1 MO (Fig.8.A)
Xla Wt + chn1 MO (Fig.8.B-C)
Xla Wt + cpeb1 MO (fig.8)
Xla Wt + cpeb1 MO (Fig.8.A)
Xla Wt + ctdnep1 MO (fig.8)
Xla Wt + ctdnep1 MO (Fig.8.A)
Xla Wt + elk4 MO (fig.8)
Xla Wt + elk4 MO (Fig.8.A)
Xla Wt + ephb1 MO (fig.8)
Xla Wt + ephb1 MO (Fig.8.A)
Xla Wt + fgf2 MO (fig.8)
Xla Wt + fgf2 MO (Fig.8.A)
Xla Wt + fmr1 MO (fig.8)
Xla Wt + fmr1 MO (Fig.8.A)
Xla Wt + fxr1 MO (fig.8)
Xla Wt + fxr1 MO (Fig.8.A)
Xla Wt + glis2 MO (fig.8)
Xla Wt + glis2 MO (Fig.8.A)
Xla Wt + gstp1 MO (fig.7.b1-b5)
Xla Wt + gstp1 MO (fig.7.b1-b5)
Xla Wt + gstp1 MO (fig.8)
Xla Wt + gstp1 MO (fig.8)
Xla Wt + gstp1 MO (Fig.8.A)
Xla Wt + gstp1 MO (Fig.8.B-C)
Xla Wt + hat1 MO (fig.8)
Xla Wt + hdac6 MO (fig.8)
Xla Wt + hdac6 MO (Fig.8.A)
Xla Wt + hspa5 MO (fig.7.c1-c5)
Xla Wt + hspa5 MO (fig.7.c1-c5)
Xla Wt + hspa5 MO (fig.7.c1-c5)
Xla Wt + hspa5 MO (fig.8)
Xla Wt + hspa5 MO (fig.8)
Xla Wt + hspa5 MO (Fig.8.A)
Xla Wt + hspa5 MO (Fig.8.B-C)
Xla Wt + lsm6 MO (fig.8)
Xla Wt + lsm6 MO (Fig.8.A)
Xla Wt + mmp9 MO (fig.8)
Xla Wt + mmp9 MO (Fig.8.A)
Xla Wt + mocs3 MO (fig.8)
Xla Wt + mocs3 MO (Fig.8.A)
Xla Wt + prkaca MO (fig.8)
Xla Wt + prkaca MO (Fig.8.A)
Xla Wt + arl9 MO (fig.8)
Xla Wt + arl9 MO (Fig.8.A)
Xla Wt + armc8 MO (fig.7.d1-d5)
Xla Wt + armc8 MO (fig.7.d1-d5)
Xla Wt + armc8 MO (fig.8)
Xla Wt + armc8 MO (fig.8)
Xla Wt + armc8 MO (Fig.8.A)
Xla Wt + armc8 MO (Fig.8.B-C)
Xla Wt + chn1 MO (fig.8)
Xla Wt + chn1 MO (fig.8)
Xla Wt + chn1 MO (Fig.8.A)
Xla Wt + chn1 MO (Fig.8.B-C)
Xla Wt + cpeb1 MO (fig.8)
Xla Wt + cpeb1 MO (Fig.8.A)
Xla Wt + ctdnep1 MO (fig.8)
Xla Wt + ctdnep1 MO (Fig.8.A)
Xla Wt + elk4 MO (fig.8)
Xla Wt + elk4 MO (Fig.8.A)
Xla Wt + ephb1 MO (fig.8)
Xla Wt + ephb1 MO (Fig.8.A)
Xla Wt + fgf2 MO (fig.8)
Xla Wt + fgf2 MO (Fig.8.A)
Xla Wt + fmr1 MO (fig.8)
Xla Wt + fmr1 MO (Fig.8.A)
Xla Wt + fxr1 MO (fig.8)
Xla Wt + fxr1 MO (Fig.8.A)
Xla Wt + glis2 MO (fig.8)
Xla Wt + glis2 MO (Fig.8.A)
Xla Wt + gstp1 MO (fig.7.b1-b5)
Xla Wt + gstp1 MO (fig.7.b1-b5)
Xla Wt + gstp1 MO (fig.8)
Xla Wt + gstp1 MO (fig.8)
Xla Wt + gstp1 MO (Fig.8.A)
Xla Wt + gstp1 MO (Fig.8.B-C)
Xla Wt + hat1 MO (fig.8)
Xla Wt + hdac6 MO (fig.8)
Xla Wt + hdac6 MO (Fig.8.A)
Xla Wt + hspa5 MO (fig.7.c1-c5)
Xla Wt + hspa5 MO (fig.7.c1-c5)
Xla Wt + hspa5 MO (fig.7.c1-c5)
Xla Wt + hspa5 MO (fig.8)
Xla Wt + hspa5 MO (fig.8)
Xla Wt + hspa5 MO (Fig.8.A)
Xla Wt + hspa5 MO (Fig.8.B-C)
Xla Wt + lsm6 MO (fig.8)
Xla Wt + lsm6 MO (Fig.8.A)
Xla Wt + mmp9 MO (fig.8)
Xla Wt + mmp9 MO (Fig.8.A)
Xla Wt + mocs3 MO (fig.8)
Xla Wt + mocs3 MO (Fig.8.A)
Xla Wt + prkaca MO (fig.8)
Xla Wt + prkaca MO (Fig.8.A)
Article Images: [+] show captions
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Fig. 1. Flow diagram of the protocols for animal rearing, cell isolation, RNA preparation and microarray hybridization. At stage 46 or 48, tadpoles were electroporated with a GFP-expression construct and placed in one of three visual experience conditions: normal 12 h light:12 h dark conditions; visual deprivation (vd), or enhanced visual experience. These rearing conditions produced 5 cell groups: active NPCs (aNPCs), Mature Neurons, Immature Neurons, Active NPCs isolated from visually-deprived tadpoles (aNPCvd), and quiescent NPCs (qNPCs). See text for details. GFP+ cells were harvested from dissociated midbrains and RNA was isolated and prepared for microarrays. The bottom panel shows which samples were compared by microarray analysis to identify differentially expressed genes that might be involved in cell proliferation and neurogenesis. |
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Fig. 2. Relationships between the multiple microarray comparisons. (A) Venn diagram of the overlap of the transcripts with differential expression (p<0.05) between the 3 microarray comparisons. About 50% of differentially expressed transcripts were shared between the 3 datasets. Sizes of the ovals represent the number of transcripts showing significant differential expression in each microarray comparison. The overlap represents the proportion of transcripts shared by multiple microarray comparisons. The aNPC vs Mature Neuron set contains 1606 transcripts, 672 of which were shared with at least one other group. The aNPC vs qNPC comparison has 932 differentially expressed transcripts, and shared 573 transcripts with other comparisons. The aNPCvd vs Immature Neuron comparison had 702 genes with significant differential expression, with 395 shared between the different comparisons. In total, 124 genes were shared between all 3 gene groups. (B) DAVID analyses reveal gene ontology traits from the microarray comparisons. Differentially expressed transcripts with p<0.05 from the aNPC vs qNPC, aNPC vs Immature Neuron, and aNPC vs Mature Neuron microarray comparisons were clustered using the DAVID Functional Annotation Clustering tool. The enriched gene clusters are shown in pie charts for each comparison. The number of transcripts identified in each cluster is indicated in the diagram or in the legend. Transcripts in the nucleosome and chromatin assembly pathways (black) were common to all three microarray comparisons. The RNA recognition RNP-1 family (white) was abundant in both the aNPCvd vs Immature Neuron and the aNPC vs Mature Neurons microarray comparisons. These data are provided in Supplementary Table 2. |
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Fig. 3. aNPCs share networks of differentially expressed transcripts. (A) Networks of differentially-expressed transcripts that are shared between NPCs. Transcripts with positive expression values (more highly expressed in NPCs) or negative expression values (more highly expressed in neurons or quiescent NPCs) were analyzed separately. Each node of the network indicates the groups of positively (blue) or negatively (red)-expressed genes for each microarray comparison, nodes separated by short distances and thicker connections indicate that the groups share many transcripts. The size of the pie diagram at each node represents the total number of differentially expressed genes and the number of unique genes unshared (black) and shared between groups (blue, gray or red). Blue represents genes enriched in aNPCs with high proliferative capability, gray represents enrichment in qNPCs and red indicates enrichment in neurons with the lowest proliferative capability. Numbers on the connecting segments are the numbers of transcripts in common between the groups. (B) DAVID Functional Annotation Clustering tool identified 5 gene families that are enriched in multiple aNPC datasets: nucleosome and chromatin assembly genes, RNA recognition motif RNP-1 family, CHROMO domain containing chromatin binding genes, the TCP-1 chaperonin family and genes associated with oxygen transport. |
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Fig. 4. MetaCore analysis of differentially expressed transcripts in NPCs and Neurons. Map Folders (left column), which identify broad functional categories, and Canonical Pathways Maps (right column), which identify more specific candidate interaction pathways, are listed in the order of significance, from top to bottom of the lists. Pathway Maps that are within Map Folders are color coded. The top 10 significant pathways from MetaCore (p<0.05 and False Discovery Rate <0.05) are presented here. Specific components of the Pathway Maps that were identified in the microarray comparisons are shown in Supplementary Table 3. |
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Fig. 5. Concordance of differentially-expressed transcripts detected by NanoString and microarrays. (A) Pie chart illustrating the degree of concordance of 95 transcripts analyzed by NanoString and microarrays. 49% of transcripts tested by NanoString share the same expression profile as microarray; 25% of transcripts were detected as differentially expressed by only NanoString analysis and 21% were detected as differentially expressed only by microarray analysis. Only 5% of the transcripts that were differentially expressed in the NanoString analysis exhibited differential expression in opposite directions in the microarray analysis. (B) Differential expression of transcripts analyzed by NanoString and microarrays for aNPCvd and Immature Neurons. Transcripts that are more highly expressed in aNPCvd than Immature Neurons (green), more highly expressed in Immature Neurons (red) or not differentially expressed (white) are shown for concordant transcripts (NanoString=Microarray) or those that were detected as differentially expressed only by NanoString or microarray. Transcripts to the far right were differentially expressed but in opposite directions between NanoString and microarray analyses. |
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Fig. 6. In vivo time-lapse imaging protocol. We electroporated optic tecta of stage 46 tadpoles with pSox2-bd::tGFP and control morpholinos (MO) or MOs targeted against genes of interest. After 24 h, all tGFP-labeled cells in each tectal lobe were imaged at daily intervals over 3 days.Cell proliferation over 2 days and the proportions of labeled NPCs and neurons were determined for each timepoint. |
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Fig. 7. Morpholinos against candidate neurogenic genes alter cell proliferation and differentiation. A1–D3 Projections of confocal stacks of the right tectal lobe imaged 1 day after co-electroporation with pSox2-bd::tGFP and control morpholinos (A1–A3), or morpholinos against glutathione S-transferase pi 1 (gstp1; B1–B3), armadillo repeat containing 8 (armc8; C1–C3), or heat shock protein 5 (hspa5; D1–D3), GFP-labeled cells are relatively sparse on day 1 (A1, B1, C1, D1). Arrows point to the distal pial endfoot of example neural progenitor cells and asterisks indicate neurons. Under control conditions, the number of NPCs decreases over the subsequent two days (A2 and A3). The tectal lobes with targeted gene knockdown show decreases (gstp1 and hspa5) and increases (armc8) in cell proliferation, as well as higher proportions of NPCs (hspa5) or neurons (gstp1 and armc8) on the third day of imaging. A4–D4, A5–D5 Summary graphs of changes in the proportion of cells in the tectum of the control (A) and morpholino-treated (B–D) animals that are NPCs (A4–D4) or neurons (A5–D5). Each line represents data from a separate animal. An asterisk over day 1 or day 3 indicates a significant difference from the mean control values (Mann–Whitney U test, p<0.05) and an asterisk over the center bracket indicates that there was a significant change between day 1 and day 3 levels (Wilcoxon Signed Rank test, p<0.05). Summary graphs for all control and morpholino results are provided in Supplementary Fig. 1. Data are shown in Table 2, Table 3, Table 4 and Table 5. |
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Fig. 8. Morpholinos against candidate neurogenic genes generate a range of neurogenesis phenotypes. Summary of the in vivo imaging data showing the numbers of GFP-labeled cells generated over time (A), the proportion of the cells that were neurons (B) or NPCs (C) for each experimental condition. (A) The genes targeted with morpholinos are arranged by the magnitude of the change in cell number over 3 days. The asterisks indicate a significant decrease or increase compared to control morpholino conditions (red line). The mean values, SEMs and p-values are in Table 4. (B–C) The proportion of neurons (B) and NPCs (C) as a percentage of all cells counted on day 3. The genes targeted are listed along the y-axis and arranged by those that produced the greatest proportion of neurons. Asterisks indicate differences in the proportion of cell types between the experimental and matched control morpholino groups (Mann–Whitney U test, p<0.05). Gene symbols listed in red identify the morpholinos that resulted in a significant difference in the proportions of cell types compared to control (Pearson X-square test, p<0.05). The mean values, SEMs and p-values are in Table 2. Red lines on graphs indicate the mean control morpholino (conMO) values for the proportion of neurons or NPCs. The mean values, SEMs, and p-values are in Table 5. |
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Fig. 9. Candidate gene sets defined by neurogenesis phenotypes. Categories of neurogenesis phenotypes from morpholinos are shown as colored ellipses where the area of each ellipse is proportional to the number of genes in that category. Of the 34 candidate genes (red) tested with morpholino treatment, 24 significantly altered the proportions of cell types (blue circle, Pearson's Chi-square) and 19 significantly altered the proliferation rate (yellow, Mann–Whitney U test). The morpholinos against 15 candidate genes altered both the cell types generated and the proliferation rate. The overlap between these two categories is shown in green. Among these 15 genes, 5 generated significant differences in the proportions of NPCs (purple, Mann–Whitney U test) and of those, 3 also had significant differences in the number of neurons that were generated (light blue, Mann–Whitney U test). One of the 5 (purple) changed both proliferation rate and NPC number (peach). |
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Fig. 10. Summary of neurogenic outcomes under control conditions and with candidate gene morpholinos. (A) Diagram of NPC fates summarized from in vivo imaging experiments. NPCs can either differentiate into neurons or divide and generate NPCs or neurons. (B) Cartoons of the proportions of NPCs and neurons observed on day 1 and day 3 for control animals and animals electroporated with morpholinos against several candidate genes, which represent a range of neurogenic outcomes found in the present study. In control animals, the proportion of NPCs decreases and the proportion of neurons increases over the observation period. Morpholinos against armc8 result in an exaggerated increase in neurons, gstp1 morpholinos result in a rapid shift in the proportion of NPCs to neurons, whereas hspa5 morpholinos result in an increase in the proportion of NPCs and a decrease in the proportion of neurons. |
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Townsend, Novel role for glutathione S-transferase pi. Regulator of protein S-Glutathionylation following oxidative and nitrosative stress. 2008, Pubmed
Tremblay, Regulation of radial glial motility by visual experience. 2009, Pubmed , Xenbase
Uy, Evolutionarily conserved role for SoxC genes in neural crest specification and neuronal differentiation. 2014, Pubmed , Xenbase
Valenzuela-Fernández, HDAC6: a key regulator of cytoskeleton, cell migration and cell-cell interactions. 2008, Pubmed
Vasanth, Identification of nuclear localization, DNA binding, and transactivating mechanisms of Kruppel-like zinc finger protein Gli-similar 2 (Glis2). 2011, Pubmed
Vergaño-Vera, Fibroblast growth factor-2 increases the expression of neurogenic genes and promotes the migration and differentiation of neurons derived from transplanted neural stem/progenitor cells. 2009, Pubmed
Walton, Adult neurogenesis transiently generates oxidative stress. 2012, Pubmed
Wang, Extracellular proteolysis by matrix metalloproteinase-9 drives dendritic spine enlargement and long-term potentiation coordinately. 2008, Pubmed
Willardsen, The ETS transcription factor Etv1 mediates FGF signaling to initiate proneural gene expression during Xenopus laevis retinal development. 2014, Pubmed , Xenbase
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Wu, Dendritic dynamics in vivo change during neuronal maturation. 1999, Pubmed , Xenbase
Wu, Time-lapse in vivo imaging of the morphological development of Xenopus optic tectal interneurons. 2003, Pubmed , Xenbase
Zhang, HDAC6 modulates cell motility by altering the acetylation level of cortactin. 2007, Pubmed
Zoghbi, SILencing misbehaving proteins. 2005, Pubmed