Introduction
In the adult mammalian brain, radial-glial neural stem cells (RGLs) in the dentate gyrus subregion of the hippocampus give rise to dentate granule cells and astrocytes (Seri et al., 2001; Garcia et al., 2004; Ahn and Joyner, 2005; Lagace et al., 2007; Bonaguidi et al., 2011; Encinas et al., 2011; Gonçalves et al., 2016b; Moss et al., 2016; Pilz et al., 2018), a process referred to as adult hippocampal neurogenesis (Altman and Das, 1965; Eriksson et al., 1998; Spalding et al., 2013; Boldrini et al., 2018; Sorrells et al., 2018; Moreno-Jiménez et al., 2019; Tobin et al., 2019; Gage, 2019; Knoth et al., 2010). Adult-born dentate granule cells integrate into hippocampal circuitry by remodeling the network and ultimately contribute to hippocampal-dependent learning and memory and regulation of emotion (Gonçalves et al., 2016b; Anacker and Hen, 2017; Miller and Sahay, 2019). Levels of adult hippocampal neurogenesis are highly sensitive to experience (Cope and Gould, 2019; Vicidomini et al., 2020) suggesting that neurogenesis may represent an adaptive mechanism by which hippocampal-dependent memory functions are optimized in response to environmental demands. Essential to this adaptive flexibility is the capacity of RGLs to balance long-term maintenance with current or future demands for neurogenesis (‘anticipatory neurogenesis’) in response to distinct physiological signals (Bonaguidi et al., 2011; Cope and Gould, 2019; Vicidomini et al., 2020; Dranovsky et al., 2011; Schouten et al., 2020).
Depending on environmental conditions, RGLs make decisions to stay quiescent or self-renew asymmetrically or symmetrically. Whereas enriching experiences (e.g., complex environments, exploration, and socialization) bias RGLs toward asymmetric divisions to generate astrocytes and neurons (Dranovsky et al., 2011; Song et al., 2012), unfavorable conditions promote RGL quiescence (e.g., chronic stress and aging) or symmetric self-renewal to support neural stem cell (NSC) expansion at the expense of neurogenesis (e.g., social isolation, seizures, and aging) (Dranovsky et al., 2011; Sierra et al., 2015; Ibrayeva et al., 2021). Asymmetric self-renewal of RGLs predominates over symmetric self-renewal division mode in the adult hippocampus and it ensures maintenance of RGL numbers while supporting current neurogenic demands (Pilz et al., 2018; Vicidomini et al., 2020). Conversely, symmetric self-renewal decouples RGL divisions from differentiation and is thought to serve distinct functions. First, symmetric divisions prevent premature differentiation of RGLs in a nonpermissive or unhealthy niche, and consequently, avert aberrant integration of adult-born dentate granule cells detrimental to hippocampal functions (Ibrayeva et al., 2021; Cho et al., 2015). As such, RGL amplification anticipates future demands for neurogenesis upon return to favorable conditions. Second, RGL expansion may represent an efficient mechanism to replenish the adult RGL pool after injury. Third, symmetric stem cell divisions maybe more efficient than asymmetric divisions for long-term maintenance since fewer divisions are required to maintain RGL numbers. Furthermore, symmetric divisions may be associated with a lower rate of mutations and reduced replicative aging (Shahriyari and Komarova, 2013).
Extracellular physiological signals recruit transcription factors (TFs) within adult hippocampal RGLs to execute quiescence-activation decisions and symmetric or asymmetric self-renewal divisions (Vicidomini et al., 2020; Andersen et al., 2014; Urbán et al., 2019). A growing number of transcriptional regulators of quiescence and asymmetric (neurogenic or astrogenic) stem cell renewal have been identified (Mukherjee et al., 2016; Jones et al., 2015; Zhang et al., 2019; Ehm et al., 2010; Imayoshi et al., 2010). Deletion of such factors results in loss of RGL quiescence, increased neurogenesis and ultimately, differentiation-coupled depletion of the RGL pool. In sharp contrast, the identities of TFs that regulate RGL expansion have remained elusive. Here, we report that expression of the ubiquitously expressed TF, Kruppel-like factor 9 (
Results
Inducible
To characterize
Figure 1.
(A, B)
Figure 1—figure supplement 1.
Generation and characterization of Kruppel-like factor 9 (
(A) Schematic of wild-type and modified
Figure 1—figure supplement 2.
Estimation of Kruppel-like factor 9 (
(A) Representative low magnification images of
Figure 1—figure supplement 3.
Inducible overexpression of Kruppel-like factor 9 (
(A, B) Two cohorts of adult
We next asked what happens when we delete
We next asked how Klf9 loss-of-function in RGLs affects self-renewal division mode. Population-level lineage tracing experiments at short-term chase time points suggested that Klf9 loss in Gli1+ RGLs increased RGL numbers (data not shown). However, analysis of NSC dynamics at the population level is encumbered by changes in numbers of labeled progeny overtime (Bonaguidi et al., 2011; Bottes et al., 2021). The challenges of interpreting population-level analysis are exacerbated because
Figure 2.
Kruppel-like factor 9 (
(A–D) Clonal analysis of sparsely labeled Gli1+ RGLs in adult
Figure 2—figure supplement 1.
Analysis of clonal composition in Figure 2C.
Representative images of labeled radial-glial neural stem cell (RGL) clones and descendants. Identification was based on tdTomato+ morphology and GFAP immunohistochemistry. Z-series of confocal images in Figure 2C were processed using Imaris software. Scale bar: 15 µm.
Figure 2—video 1.
Three-dimensional (3D) images of representative radial-glial neural stem cell (RGL) clonal compositions depicted in Figure 2C 1 RGL.
Figure 2—video 2.
Three-dimensional (3D) images of representative radial-glial neural stem cell (RGL) clonal compositions depicted in Figure 2C 1 RGL.
Figure 2—video 3.
Three-dimensional (3D) images of representative radial-glial neural stem cell (RGL) clonal compositions depicted in Figure 2C 1 RGL+ P + A.
Figure 2—video 4.
Three-dimensional (3D) images of representative radial-glial neural stem cell (RGL) clonal compositions depicted in Figure 2C 1 RGL+ A.
Figure 2—video 5.
Three-dimensional (3D) images of representative radial-glial neural stem cell (RGL) clonal compositions depicted in Figure 2C 1 RGL+ P.
Figure 2—video 6.
Three-dimensional (3D) images of representative radial-glial neural stem cell (RGL) clonal compositions depicted in Figure 2C 2 RGLs.
Figure 2—video 7.
Three-dimensional (3D) images of representative radial-glial neural stem cell (RGL) clonal compositions depicted in Figure 2C 2 RGLs+ P + A.
Figure 2—video 8.
Three-dimensional (3D) images of representative radial-glial neural stem cell (RGL) clonal compositions depicted in Figure 2C 2 RGLs+ P.
To unequivocally establish clonal origin of labeled progeny and directly test the hypothesis that
Figure 3.
Kruppel-like factor 9 (Klf9) functions as a brake on symmetric self-renewal of radial-glial neural stem cells (RGLs).
(A) Diagram of experimental design for in vivo two-photon imaging experiments. Inset is a high magnification image of a sparsely labeled single RGL in an adult
Figure 3—figure supplement 1.
Representative images of radial-glial neural stem cell (RGL) divisions captured using two-photon imaging in vivo.
(A) Representative two-photon images of RGL cells R1 and R2 in vivo and their respective post hoc fluorescence image. (B) Confocal immunofluorescence images of the same GFAP+/tdTomato+ cells at different depths, confirming their RGL identity. (C) Imaris deconvolution of tdTomato-labeled RGLs in B. Scale bar: 20 µm.
Figure 3—video 1.
In vivo two-photon imaging of Gli1-postive radial-glial neural stem cells (RGLs).
Narrated example of longitudinal imaging of asymmetric neural stem cell (NSC) divisions. Two-photon imaging across days showing two examples of asymmetric division of NSCs (red arrows).
Figure 3—video 2.
In vivo two-photon imaging of Gli1-postive radial-glial neural stem cells (RGLs).
Narrated example of longitudinal imaging of symmetric cell divisions. Two-photon imaging across days showing two examples of symmetric division of neural stem cells (NSCs; blue arrows).
Figure 3—video 3.
In vivo two-photon imaging of Gli1-postive radial-glial neural stem cells (RGLs).
Three-dimensional reconstruction of RGL cells imaged in vivo before undergoing symmetric division. Field of view corresponds to second row of Figure 3B at 18 dpi.
Figure 3—video 4.
In vivo two-photon imaging of Gli1-postive radial-glial neural stem cells (RGLs).
Three-dimensional reconstruction of RGL cells imaged in vivo after undergoing symmetric division. Field of view corresponds to second row of Figure 3B at 30 dpi.
To understand how Klf9 regulates RGL division mode, we performed in vivo molecular profiling of RGLs lacking
Figure 4.
Kruppel-like factor 9 (
(A) Schematic of experimental workflow to biochemically isolate and sequence translated mRNAs from Gli1+ RGLs (
Figure 4—figure supplement 1.
Annotation of upregulated and downregulated differentially expressed genes (DEGs) in Gli1+ radial-glial neural stem cells (RGLs) following Kruppel-like factor 9 (
Gene ontology annotation (gGOSt, https://biit.cs.ut.ee/gprofiler/gost) of DEGs in Gli1+ RGLs following
For validation of DEGs previously linked with NSC quiescence and activation (Mukherjee et al., 2016; Zhang et al., 2019; Codega et al., 2014; Shin et al., 2015; Knobloch et al., 2013; Baser et al., 2019), we performed qRT-PCR on an independent replicate of biochemically isolated mRNAs from this population of Gli1+ RGLs in vivo. We first confirmed downregulation of Klf9 in RGLs. Next, we validated downregulation of canonical quiescence signaling factors (Bmp4) and upregulation of genes involved in lipid metabolism (Pla2g7), cell cycle (Ccn1a), mitogen signaling (epidermal growth factor receptor, Egfr), and Notch signaling (Lunatic fringe, Lfng) (Figure 4D). Consistent with Lfng-mediated potentiation of Notch1 signaling through cleavage of the Notch1 intracellular domain (NICD), we observed significantly elevated levels of NICD in Gli1+ RGLs lacking Klf9 (Figure 4E; Hochgerner et al., 2018; Zhao and Wu, 2018). We infer from our loss-of-function data that high levels of Klf9 in RGLs induce BMP4 expression and repress gene modules specifying mitogen signaling, fatty acid oxidation, RGL differentiation, and cell-cycle exit to inhibit RGL expansion.
Discussion
Central to experience-dependent regulation of neurogenesis is the ability of RGLs to constantly balance demands for neurogenesis and astrogenesis or RGL expansion with self-preservation through regulation of quiescence. Since interpretation of the external world is dependent on integration and convergence of physiological extracellular signals upon TFs in RGLs, enriching and adverse experiences are likely to modulate the balance between transcriptional programs that regulate RGL division modes supporting amplification or asymmetric self-renewal (Vicidomini et al., 2020). However, in contrast to our knowledge of TFs that regulate asymmetrical self-renewal of RGLs in the adult hippocampus (Mukherjee et al., 2016; Jones et al., 2015; Zhang et al., 2019; Ehm et al., 2010; Imayoshi et al., 2010), the identities of transcriptional regulators of symmetric self-renewal of RGLs have remained elusive. By combining conditional mouse genetics with in vivo clonal analysis and longitudinal two-photon imaging of RGLs, we demonstrated that Klf9 acts as a transcriptional brake on RGL activation state and expansion through inhibition of symmetric self-renewal (Figure 5).
Figure 5.
Summary schematic conveying Kruppel-like factor 9 (
That Klf9 expression is higher in nondividing RGLs than in activated RGLs is consistent with gene expression profiling of quiescent adult hippocampal RGLs (Bottes et al., 2021; Knobloch et al., 2013; Jaeger and Jessberger, personal communication) and other quiescent somatic stem cells such as satellite cells (Pallafacchina et al., 2010) and NSCs in the subventricular zone (Codega et al., 2014; Morizur et al., 2018; Renault et al., 2009). Loss of Klf9 in Gli1+ RGLs resulted in increased RGL activation. Based on our clonal analysis of RGL output and in vivo translational profiling, we think that this increased RGL activation reflects maintenance of an activated or cycling state (also discussed later) to support increased symmetric self-renewal (Encinas et al., 2011).
Our current knowledge of TFs that regulate symmetric self-renewal in the adult hippocampus can only be extrapolated from studies on hippocampal development (Noguchi et al., 2019). Clonal analysis of Gli1-targeted RGLs revealed multi-RGL containing clones with progeny. This potentially reflects competition between TFs that dictate balance between symmetric and asymmetric divisions, compensation by downstream effectors of Klf9 or constraints on RGL expansion imposed by availability of niche factors. Such compensatory mechanisms may also explain why constitutive deletion of
Studies on adult hippocampal neural stem and progenitor cells have relied on assays that induce quiescence and activation in vitro (Knobloch et al., 2013), unbiased single cell profiling of neurogenesis (Shin et al., 2015; Hochgerner et al., 2018) or FACS sorting of neural stem and progenitor cells in vivo (Zhang et al., 2019). Because asymmetric self-renewal is the predominant mode of division, it is most certainly the case that the RGL activation profile inferred from these studies is biased toward asymmetric, rather than symmetric, self-renewal. In contrast, our in vivo translational profiling of long-term self-renewing Gli1+ RGL population following cell-autonomous deletion of Klf9 allowed us to infer how changes in gene expression relate to RGL symmetric division mode and create an exploratory resource for the NSC research community. While ribosomal profiling does not allow us to isolate transcripts from single RGLs, it offers other advantages such as minimizing stress response associated with cell dissociation (Machado et al., 2021). Since
Bioinformatics analysis of our data identified enhanced fatty acid β-oxidation (FAO), a substrate for energy production and lipogenesis as a metabolic program recruited to sustain RGL expansion (Figure 5). In fact, lineage tracing studies on embryonic neocortical NSCs have demonstrated a role for FAO in maintenance of NSC identity and proliferation (Namba et al., 2021). Specifically, inhibition of Tmlhe (a carnitine biosynthesis enzyme) and carnitine-dependent long-chain FAO (carnitine palmitoyltransferase I, CPT1, which catalyzes the rate-limiting reaction in this process) resulted in a marked increase in symmetric differentiating divisions at expense of both symmetric and asymmetric self-renewal of NSCs (Xie et al., 2016). Inhibition of FAO prevented hematopoietic stem cell maintenance and promoted symmetric differentiating divisions of hematopoietic stem cells (Ito et al., 2012). High levels of FAO are directly linked to intestinal stemness (Mana et al., 2021) and persistence of proliferative capacity across cancers (Oren et al., 2021). In sharp contrast to these findings, it has been suggested that high levels of FAO are important for maintaining RGL quiescence. Specifically, deletion of Cpt1a (and inhibition of FAO) in adult hippocampal NSC and progenitors impaired expansion and reduced numbers of RGLs. However, it could not be determined if this was due to death and/or inhibition of symmetric self-renewal of RGLs (Knobloch et al., 2017). Based on our data, we propose that NSCs, like other somatic stem cells and progenitors, require high levels of FAO for symmetric self-renewal or expansion.
How does Klf9 function as a brake on RGL symmetric self-renewal? We propose that Klf9 corepresses a suite of genes associated with maintenance of RGLs in symmetric division mode. Pioneering studies have implicated Notch signaling in sustaining symmetric divisions of neuroepithelial cells (Egger et al., 2010), expansion of putative NSCs and progenitors (Androutsellis-Theotokis et al., 2006) and maintenance of radial glial cell like identity through inhibition of differentiation and cell-cycle exit (Gaiano et al., 2000; Yoon et al., 2008). Importantly, genetic gain-of-function of Notch1 signaling in RGLs in the adult DG maintains RGLs at the expense of hippocampal neurogenesis (Breunig et al., 2007). Klf9 may also directly suppress a proneurogenic program in RGLs (e.g., NeuroD4, downregulated DEG, Supplementary file 3; Masserdotti et al., 2015) or indirectly via competitive interactions with TFs that regulate RGL asymmetric self-renewal. Taken together, loss of Klf9 in RGLs drives expansion through enhanced mitogen and cell-cycle signaling (Berdugo-Vega et al., 2020), prevention of RGL differentiation, and elevation of lipogenic and FAO metabolic programs (Figure 5).
Our findings stimulate discussion on how experiential signals regulate RGL activation and expansion. To date, GABA(A) R signaling and PTEN signaling (by inhibiting PI3K–Akt pathway) have been shown to promote quiescence and suppress RGL amplifying divisions (Bonaguidi et al., 2011; Song et al., 2012). It is plausible that Klf9 participates in these signaling pathways as a downstream actuator.
Our genome-wide dataset serves as a general exploratory community resource in several ways. First, it catalyzes further enquiry into mechanisms underlying NSC quiescence and expansion. By way of example, candidate genes such as the cell adhesion molecule Embigin (downregulated DEG) regulates quiescence of hematopoietic stem/progenitor cells (Silberstein et al., 2016) whereas the alpha7 nicotinic receptor (upregulated DEG), ChrnA7, has been shown to be required for maintaining RGL numbers (Otto and Yakel, 2019). Second, numerous genes identified in our blueprint are implicated in driving tumorigenesis and as such may guide differentiation-based strategies to block tumor proliferation (Carracedo et al., 2013). Third, our work motivates assessment of how Klf9 may link extracellular, physiological signals with genetic and metabolic programs in RGLs. Fourth, our findings may guide investigation of functional significance of Klf9 enrichment in other quiescent neural (SVZ) (Codega et al., 2014; Morizur et al., 2018; Renault et al., 2009) and somatic stem cell populations (Pallafacchina et al., 2010).
Our study enables a more holistic assessment of how competing transcriptional programs in RGLs mediate decision making by including regulators of symmetric and asymmetric self-renewal. A deeper understanding of Klf9-dependent regulation of RGL homeostasis may guide genetic and metabolic strategies to replenish the RGL reservoir and restore neurogenesis following injury or expand the NSC pool in anticipation of future neurogenic demands to support hippocampal-dependent memory processing and emotional regulation (Anacker and Hen, 2017; Miller and Sahay, 2019; McAvoy et al., 2016).
Materials and methods
Animals were handled and experiments were conducted in accordance with procedures approved by the Institutional Animal Care and Use Committee at the Massachusetts General Hospital and Albert Einstein College of Medicine in accordance with NIH guidelines. Mice were housed three to four per cage in a 12 hr (7:00 a.m. to 7:00 p.m.) light/dark colony room at 22–24°C with ad libitum access to food and water.
Mouse lines
The following mouse lines were obtained from Jackson Labs:
BrdU administration
For analysis of cell proliferation in dentate gyrus, mice were injected with BrdU (200 mg/kg body weight, i.p.) and sampled 2 hr later. For analysis of long-term retaining cells in dentate gyrus, mice were given daily injection of BrdU (25 mg/kg body weight, i.p.) for 14 days and sampled 24 hr after the last injection.
Tamoxifen administration
Tamoxifen (20 mg/ml, Sigma, T5648) was freshly prepared in a 10% ethanol of corn oil (Sigma C8267). For population analysis, a dose of 150 or 250 mg/kg was intraperitoneally injected into 8-week-old male and female mice (Figure 1F). For clonal analysis, a dose of 50 and 100 mg/kg were used in reporter lines of Ai14 and mT/mG, respectively (Figure 2A, E). Mice were sampled 7 or 28 days post-tamoxifen injection. For two-photon imaging (Figure 3A), one dose of 150 mg/kg tamoxifen was given 2 days prior to in vivo imaging. For ribosomal profiling, a dose of 250 mg/kg body weight was intraperitoneally injected into 2–3 months mice every 12 hr for three times. Mice were sampled 4 days after the last injection (Figure 4A).
Tissue processing and immunostaining
35 μm cryosections obtained from perfused tissue were stored in phosphate-buffered saline (PBS) with 0.01% sodium azide at 4°C. For immunostaining, floating sections were washed in PBS, blocked in PBS containing 0.3% Triton X-100% and 10% normal donkey serum and incubated with primary antibody overnight at 4°C overnight (Rockland, rabbit anti RFP, 1:500; Millipore, chicken anti-GFAP, 1:2000; goat anti-GFP, Novus, 1:500; Santa Cruz, sc-8066, Goat anti-DCX, 1:500). The Mcm2 (BD Biosciences, mouse anti-Mcm2; 1:500), GFP (Abcam, Chicken anti-GFP, 1:2000), LacZ (Promega, Mouse anti-beta Galactosidase, 1:2000), and Nestin (Aves lab, chicken anti-Nestin, 1:400) antigens were retrieved by incubating brain sections in citric buffer in pressure cooker (Aprum, 2100 retriever) for 20 min, followed by 60 min cooling to room temperature. BrdU antigen was retrieved by incubating brain sections in 2 N HCl for 30 min at 37°C following 15 min fixation in 4% paraformaldehyde (PFA on previously processed fluorescent signal). On the next day, sections were rinsed three times for 10 min in PBS and incubated for 90 min with fluorescent-label-coupled secondary antibody (Jackson ImmunoResearch, 1:500). Sections were rinsed three times for 10 min each in PBS before mounting onto glass slides (if applicable) and coverslipped with mounting media containing DAPI (Fluoromount with DAPI, Southern Biotech). NICD (rabbit anti-cleaved Notch1, Assay Biotech Cat# L0119 RRID:AB_10687460 at 1:100) immunostaining was performed as described (Semerci et al., 2017).
We used a transgenic mouse line that expresses GFP under the control of the Nestin promoter to label the cell bodies (Mignone et al., 2004). Mice were sacrificed 2 hr after a single BrdU injection (200 mg/kg).
Estimation of
Images acquisition and analysis
Images were obtained from one set of brain sections (six sets generated for each brain) for each immunostaining experiment (set of antigens). Stained sections were imaged at ×20 or ×40 on a Nikon A1R Si confocal laser, a TiE inverted research microscope or a Leica SP8 confocal microscope. All of analysis were performed by an experimenter blind to group identity.
LacZ intensity quantification. We used mice carrying a LacZ allele knocked into the endogenous
Clonal lineage analysis
Clonal analysis was conducted with sparse labeling after optimizing dose of tamoxifen as previously described (Bonaguidi et al., 2011). Ai14 and mTmG reporter mice were used to visualize the recombined cells. Serial coronal sections were generated and immunostained for GFAP, RFP, or GFP antigens. Images acquisition and analysis were restricted to entire dentate gyri ~2000 μm along the dorsal–ventral axis. RGLs were classified as cells that were located in the subgranular zone, had radial projections that extended into the granule cell layer, and were colabeled with GFAP and RFP or GFP. Cells with GFAP labeling without radial processes but exhibiting a bushy morphology were identified as astrocytes. Recombined GFP+ or RFP+ cells without GFAP labeling in close spatial proximity to other cells were identified as neuronal progeny cells. A ring with a radius of 50 μm from the center of the RGL was used to determine the clone composition. A single cell (astrocyte or neuron) was not counted as a clone. Images (1024 resolution) were acquired using a Leica SP8 confocal microscope as 20–25 Z-stacks with a step size of 1.5 μm. Mice with less than two clones per hemisection on average were determined as standard for sparse labeling and were selected for clonal analysis. Except for the single RGL clone category, all the labeled cells within one clone were in close spatial proximity to each other. Clones were categorized according to the presence or absence of an RGL and the type of progeny. For imaris image analysis, Z-series confocal images were processed for all the channels. The intensity of each channel was adjusted and representative images were used to generate a TIFF file by taking a ‘screen snapshot’.
Two-photon imaging of Gli1+
Twelve- to sixteen-week-old
Window implantation: We followed an established protocol to implant a cranial window over the right hemisphere of the dorsal hippocampus (Pilz et al., 2018). Briefly, we drilled a ~3-mm wide craniotomy, removed the underlying dura mater and aspirated the cortex and corpus callosum. A 3-mm diameter, 1.3-mm deep titanium implant, with a glass sealed to the bottom was then placed above the hippocampus. The implant and a titanium bar (29 × 3.8 × 1.3 mm) were held in place with dental cement. A titanium bar was used in order to secure the animal to the microscope stage. Mice were given a single dose of dexamethasone (1 mg/kg, i.p.) before surgery to reduce brain swelling, and carprofen (5 mg/kg, i.p.) for inflammation and analgesic relief after surgery completion. Implanted animals were given 2 weeks to recover from surgery and allow any inflammation to subside.
Two-photon imaging of aRGL divisions: In vivo imaging was done on a custom two-photon laser scanning microscope (based on Thorlabs Bergamo) using a femtosecond-pulsed laser (Coherent Fidelity 2, 1075 nm) and a ×16 water immersion objective (0.8 NA, Nikon). We imaged mice under isoflurane anesthesia (~1% isoflurane in O2, vol/vol) and head-fixed to the microscope stage via a titanium bar implant while resting on a 37°C electrical heating pad (RWD ThermoStar). Expression of the tdTomato fluorescent label in Gli1+ RGLs was induced with a single injection of Tamoxifen (150 µl/mg) 2 weeks after window implantation. Imaging began 2 days after tamoxifen injection (2 dpi) and continued every day until 6 dpi in order to locate sparse labeled RGLs. Afterwards, mice were imaged every 3 days, whenever possible and were imaged up to 60 days. Using a coordinate system, we marked locations of RGLs for recurrent imaging of the same cell. At each time point, we acquired a three-dimensional image stack of each field of view containing tdTomato-expressing cells and annotated their location so that the same cell could be imaged again in the following session.
Cell division classification: Cell divisions were analyzed by two different experimenters blinded to genotype. We first compiled all Z-stacks into a single sum-projected image for each time point, and then we used FIJI-ImageJ to analyze the images. Only the first recorded cell division for a given clone was included in the analysis. We defined RGL symmetric division as a new RGL generated from the mother RGL, characterized by the development of a stable radial process and static behavior of cell bodies for at least 6 days after birth. We defined asymmetric division as new NPCs generated from the mother RGL that exhibited shorter and less stable processes. These NPCs often began to migrate away within one to two imaging sessions (3–6 days).
Ribotag isolation of mRNAs from Gli1+ RGLs
We used
RNA-seq analysis
NGS libraries were constructed from total RNA using Clontech SMARTer v4 kit (Takara), followed by sequencing on an Illumina HiSeq 2500 instrument, resulting in 20–30 million 50 bp reads per sample. The STAR aligner (Dobin et al., 2013) was used to map sequencing reads to transcriptome in the mouse mm9 reference genome. Read counts for individual genes were produced using the unstranded count function in HTSeq v.0.6.0 (Anders et al., 2015), followed by the estimation of expression values and detection of differentially expressed transcripts using EdgeR (Robinson et al., 2010) and including only the genes with count per million reads >1 for one or more samples (Anders et al., 2013). DEGs were defined by at least 1.2-fold change with p < 0.05. NCBI GEO accession number GSE164889.
qRT-PCR mRNA was biochemically pooled and isolated as described above for ribosomal profiling. The first-stranded complementary DNA was generated by reverse transcription with SuperScript IV first-strand synthesis system (Thermo Fisher Scientific). For quantification of mRNA levels, aliquoted cDNA was amplified with specific primers and PowerUp SYBR Master Mix (BioRad) by CFX384 Touch Real-Time PCR detection system (BioRad). Primers were optimized and designed to hybridize with different exons. Primers are listed here (name and sequence 5′ → 3′ are indicated).
pla2g7 F:
Egfr F:
Lfng F:
Ccn1a F:
Klf9 F:
Bmp4 F:
Actb F:
Statistical analysis
Statistical analysis was carried out using GraphPad Prism software. Both data collection and quantification were performed in a blinded manner. Data in figure panels reflect several independent experiments performed on different days. An estimate of variation within each group of data is indicated using standard error of the mean. Comparison of two groups was performed using two-tailed Student’s unpaired
Two-photon imaging: In order to compare differences in the modes of RGL division between the two genotypes, we used the R statistical analysis software to fit a generalized linear mixed effects model to the division numbers across different mice, using genotype as a fixed effect, and including animal identity as a random effect in order to account for differences between individual animals [DivisionType ~ Genotype + (1|MouseIdentity)]. p values were calculated with a likelihood-ratio test comparing our model to a null model with no genotype information and identical random effects [DivisionType ~ 1 + (1|MouseIdentity)].
Antibodies | Source | Identifier |
---|---|---|
Rat anti-BrdU | BioRad | Cat# MCA2483T, RRID:AB_1055584 |
Rabbit anti-GFAP | Millipore | Cat# AB5804, RRID:AB_2109645 |
Chicken anti-Nestin | Aves lab | Cat# NES, RRID:AB_2314882 |
Rabbit anti-RFP | Rockland | Cat# 600-401-379, RRID:AB_2209751 |
Chicken anti-GFAP | Millipore | Cat# AB5541, RRID:AB_177521 |
Goat anti-GFP | Novus | NB100-1770, RRID:AB_10128178 |
Goat anti-DCX | Santa Cruz Biotechnology | Cat# sc-8066, RRID:AB_2088494 |
Mouse anti-beta galactosidase | Promega | Cat# Z3781, RRID:AB_430877 |
Chicken anti-GFP | Abcam | Cat# ab13970, RRID:AB_300798 |
Mouse anti-Mcm2 | BD Biosciences | Cat# 610700, RRID:AB_2141952 |
NICD, rabbit anticleaved Notch1 | Assay Biotech | Cat# L0119, RRID:AB_10687460 |
Rabbit anti-HA | Cell Signaling | Cat# 3724, RRID:AB_1549585 |
Anti-digoxigenin Fab fragments Antibody, POD conjugated | Roche | Cat# 11207733910, RRID:AB_514500 |
Anti-digoxigenin Fab fragments Antibody, AP conjugated | Roche | Cat# 11093274910, RRID:AB_514497 |
Alexa Fluor 488-, Cy3-, or Cy5-conjugated donkey secondary | Jackson ImmunoResearch | N/A |
Goat anti-RFP | Sicgen | Cat# AB1140-100, RRID:AB_2877097 |
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Abstract
Experience governs neurogenesis from radial-glial neural stem cells (RGLs) in the adult hippocampus to support memory. Transcription factors (TFs) in RGLs integrate physiological signals to dictate self-renewal division mode. Whereas asymmetric RGL divisions drive neurogenesis during favorable conditions, symmetric divisions prevent premature neurogenesis while amplifying RGLs to anticipate future neurogenic demands. The identities of TFs regulating RGL symmetric self-renewal, unlike those that regulate RGL asymmetric self-renewal, are not known. Here, we show in mice that the TF Kruppel-like factor 9 (
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer