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Kv1.1 channels regulate early postnatal neurogenesis in mouse hippocampus via the TrkB signaling pathway

  1. Shu-Min Chou
  2. Ke-Xin Li
  3. Ming-Yueh Huang
  4. Chao Chen
  5. Yuan-Hung Lin King
  6. Grant Guangnan Li
  7. Wei Zhou
  8. Chin Fen Teo
  9. Yuh Nung Jan
  10. Lily Yeh Jan  Is a corresponding author
  11. Shi-Bing Yang  Is a corresponding author
  1. Institute of Biomedical Sciences, Academia Sinica, Taiwan
  2. Howard Hughes Medical Institute, Departments of Physiology, Biochemistry and Biophysics, University of California, San Francisco, United States
  3. Institute of Statistics, Academia Sinica, Taiwan
  4. Neuroscience Graduate Program, University of California, San Francisco, United States
  5. Nkarta Therapeutics Inc, United States
  6. Department of Anesthesia and Perioperative Care, University of California, San Francisco, United States
  7. Neuroscience Program of Academia Sinica, Academia Sinica, Taiwan
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Cite this article as: eLife 2021;10:e58779 doi: 10.7554/eLife.58779

Abstract

In the postnatal brain, neurogenesis occurs only within a few regions, such as the hippocampal sub-granular zone (SGZ). Postnatal neurogenesis is tightly regulated by factors that balance stem cell renewal with differentiation, and it gives rise to neurons that participate in learning and memory formation. The Kv1.1 channel, a voltage-gated potassium channel, was previously shown to suppress postnatal neurogenesis in the SGZ in a cell-autonomous manner. In this study, we have clarified the physiological and molecular mechanisms underlying Kv1.1-dependent postnatal neurogenesis. First, we discovered that the membrane potential of neural progenitor cells is highly dynamic during development. We further established a multinomial logistic regression model for cell-type classification based on the biophysical characteristics and corresponding cell markers. We found that the loss of Kv1.1 channel activity causes significant depolarization of type 2b neural progenitor cells. This depolarization is associated with increased tropomyosin receptor kinase B (TrkB) signaling and proliferation of neural progenitor cells; suppressing TrkB signaling reduces the extent of postnatal neurogenesis. Thus, our study defines the role of the Kv1.1 potassium channel in regulating the proliferation of postnatal neural progenitor cells in mouse hippocampus.

Introduction

In mammals, the majority of neurons in the central nervous system are generated during embryonic development, and postnatal neurogenesis is limited to only a few brain regions, such as the subgranular zone (SGZ) of the dentate gyrus and the sub-ventricular zone (SVZ) of the lateral ventricles (Kriegstein and Alvarez-Buylla, 2009). Neural progenitor cells in the SGZ are categorized into different developmental stages based on distinct cellular functions, and cells of each stage can be identified by the expression of specific cell-fate markers. For example, type 1 radial glia-like neural stem cells have the potential for self-renewal and mostly stay quiescent; these cells are positive for Brain Lipid Binding Protein (BLBP), Glial Fibrillary Acidic Protein (GFAP), and nestin. Another widely used neural stem cell marker is Sox2, a transcription factor that is essential for maintaining stem cell pluripotency. Type 1 cells undergo asymmetric cell division to generate highly proliferative type 2a neural progenitor cells, which are double-positive for Sox2 and Tbr2, transcription factors that control cell proliferation and differentiation. Type 2a cells then generate proliferative but lineage-restricted type 2b neural progenitor cells, which express Tbr2 and doublecortin (DCX) (Gonçalves et al., 2016; Ming and Song, 2011; Spampanato et al., 2012). Type 2b cells exhibit limited mitotic potential (Gonçalves et al., 2016), and after two to five rounds of mitosis, these progenitor cells differentiate into immature neurons (Gao et al., 2014). In the adult SGZ, the newly generated granule cells contribute to memory formation, likely by facilitating the ability to distinguish similar patterns, a learning process referred to as pattern separation (Sahay et al., 2011). Importantly, postnatal neurogenesis is tightly regulated by the balance between self-renewal and differentiation (Ming and Song, 2005). While the regulation of these processes by intrinsic transcription factors has been studied extensively (Aimone et al., 2014), the impacts of membrane potential and ion channels on postnatal neurogenesis are much less clear (Fukuda et al., 2003; Swayne and Wicki-Stordeur, 2012).

Ion channels are expressed in almost all cell types, including highly proliferative stem cells and cancers; however, many ion channel-expressing cell types are considered to be electrically non-excitable (Bates, 2015; Fukuda et al., 2003; Shin et al., 2015). The type 1 stem cells in the SGZ display an immense passive conductance comprised of connexin-based gap junctions (Kunze et al., 2009; Rozental et al., 1998) as well as Kir4.1- and Kir5.1-mediated glial-type inwardly rectifying potassium channels (Yasuda et al., 2008). This passive conductance renders neural stem cells unable to fire action potentials (Fukuda et al., 2003; Swayne and Wicki-Stordeur, 2012). In addition to the passive conductance, neural stem cells and progenitor cells also exhibit various features of active conductance, such as voltage-gated potassium channels (Bates, 2015; Shin et al., 2015), and to a lesser extent, calcium channels (D'Ascenzo et al., 2006; Xu et al., 2018). One such voltage-gated potassium channel expressed in the embryonic brain and postnatal neural stem cells is Kv1.1 (Hallows and Tempel, 1998; Shin et al., 2015). This channel is found mainly in mature neurons (Wang et al., 1994), and it is predominantly localized in axons due to microtubule End-Binding 1 (EB1)-directed targeting (Gu et al., 2006; Hallows and Tempel, 1998). Functionally, Kv1.1 is best-known for its role in tuning action potential firing patterns by regulating the duration of the repolarization phase (Foust et al., 2011; Jan and Jan, 2012; Storm, 1988). Mutations of the Kv1.1 channel cause various neurological disorders, such as epilepsy and episodic ataxia, in humans and mouse models (Beraud et al., 2006; Heeroma et al., 2009; Petersson et al., 2003; Robbins and Tempel, 2012). Moreover, since Kv1.1 can be activated at a relatively low voltage (near the resting potential), it has been suggested that this potassium channel could modulate membrane electrical properties such as the membrane potential in various cell types, including non-excitable neural progenitor cells (Foust et al., 2011; Storm, 1988; Sundelacruz et al., 2013).

Kv1.1 channel, the product of the gene Kcna1, is thought to regulate postnatal neurogenesis since megencephaly mice (mceph) lacking functional Kv1.1 channels have enhanced adult neurogenesis that leads to enlargement of the hippocampi (Persson et al., 2007). However, the mechanism of this action is largely unknown. Many ion channels are widely expressed in the central nervous system, and their mutations may either directly influence both neural progenitor cells and their progeny neurons (cell-autonomous) or indirectly affect neural progenitor cells by modulating the excitability of mature neurons (non-cell-autonomous) (Espinosa et al., 2009; Piggott et al., 2019). Whereas seizures resulting from the loss of Kv1.1 function may impact postnatal neurogenesis (Almgren et al., 2008; Holth et al., 2013), our previous study using mosaic analysis with double markers (MADM) (Muzumdar et al., 2007; Zong et al., 2005) on heterozygous mceph mice without seizures revealed that Kv1.1 regulates postnatal neurogenesis via a cell-autonomous mechanism (Yang et al., 2012a). To avoid the potentially confounding effects of seizures, which start by 3–4 weeks of age in Kv1.1-null (Kcna1-/-) mice, we focused on early postnatal neurogenesis in the current study. We first showed that Kv1.1 affects early postnatal neurogenesis without having a detectable impact on embryonic neurogenesis. Then, we searched for the molecular and physiological mechanisms that mediate the Kv1.1-dependent postnatal neurogenesis in mouse hippocampus. Our results indicated that Kv1.1 cell-autonomously modulates the membrane excitability of type 2b neural progenitor cells and TrkB signaling, which accounts for increased proliferating neural progenitor cells in Kv1.1KO mice.

Results

Kv1.1 regulates postnatal neuron generation in a cell-autonomous manner

The Kv1.1 channel is widely expressed throughout the entire central nervous system (Hallows and Tempel, 1998), and the loss of Kv1.1 function in mice homozygous for either the megencephaly mutation or the Kv1.1-null mutation (Kv1.1KO) causes seizures, starting 3 weeks after birth (Donahue et al., 1996; Petersson et al., 2003). Our previous study in 3-month-old Kcna1mceph/+ mice carrying the MADM-6 b cassettes (Rosa26TG/GT) showed that Kv1.1 acts cell-autonomously to regulate the number of neuronal progeny (Yang et al., 2012a). We further carried out the MADM study in Kcna1- mice, which did not show signs of seizures before reaching adulthood (Figure 1). We first generated Nestin-cre;Kcna1; MADM-6 quadruple transgenic mice that carried Nestin-cre, Kcna1-, Rosa26TG, and Rosa26GT. Nestin-Cre mediated somatic recombination in a subset of neural progenitor cells that carried the MADM-6 cassettes, and the daughter cells bearing the Kcna1-/- alleles were labeled with green fluorescent protein (GFP) (green), while the wild-type sibling daughter cells were labeled with tdTomato (red) (Figure 1A,B,C,D). Comparable numbers of green Kv1.1KO neurons and red wild-type neurons were observed in 1-month-old Nestin-cre;Kcna1+/-;MADM-6 mice; however, a significantly larger number of green Kv1.1KO neurons was found in 2- to 3-month-old Nestin-cre;Kcna1+/-;MADM-6 mice compared to wild-type controls (Figure 1E). As expected for granule cells born postnatally, the newly generated green Kv1.1KO neurons were located farther from the SGZ in the granule cell layer (Figure 1F). Unlike adult-born neurons, which gradually decrease in number over the course of a month owing to apoptosis, developmentally-born neurons generated during late embryogenesis and early postnatal stages typically survive for more than 2 months before the onset of cell death; generation and maturation of these neurons take about 1 month, with those generated early in life located farther from the SGZ (Cahill et al., 2017; Dayer et al., 2003; Kerloch et al., 2019; Toni and Schinder, 2015). Thus, the MADM experiments revealed an overproduction of developmentally born neurons from Kv1.1KO neural progenitor cells in early postnatal stages.

Figure 1 with 2 supplements see all
Kv1.1 channels control dentate gyrus neuron number in a cell-autonomous manner.

Mosaic analysis with double markers (MADM) of the dentate gyrus in wild-type or Kcna1+/- mice. Kv1.1KO and wild-type neurons can be respectively identified as green (GFP) (A) and red (TdTomato) (B) neurons. (C) 4′,6-diamidino-2-phenylindole (DAPI) counterstain. (D) Overlay of signals in (A) and (B), scale bar = 100 µm. (E) Statistical analysis of the red wild-type and green Kv1.1KO neurons in the dentate gyrus. The numbers of red wild-type and green Kv1.1KO neurons were comparable in the dentate gyrus of 1-month-old mice; however, compared to the numbers of red wild-type neurons, the numbers of green Kv1.1KO neurons were much higher in the dentate gyrus of 2- to 3-month-old mice (two-way ANOVA followed by Sidak's multiple comparisons test; p=0.0008, for 2- to 3-month-old mice). n = 9–12 for each group. (F) Compared to the red wild-type neurons, green Kv1.1KO neurons were more often positioned farther away from the sub-granular zone (SGZ) in 2- to 3-month-old mice, indicating that the green Kv1.1KO neurons were born in the postnatal period (p=0.0002, Mann-Whitney U-test). n = 100 for each group.

To test whether Kv1.1 function is essential for neurogenesis during embryogenesis, we examined embryos with or without Kv1.1 and found no significant difference in the numbers of hippocampal progenitors or neurons at E16.5 (Figure 1—figure supplement 1). We also analyzed interneurons expressing parvalbumin (PV) or somatostatin (SST) in the dentate gyrus and found no significant difference between mice with or without Kv1.1 at P10 (Figure 1—figure supplement 2). Taken together, our experiments indicate that Kv1.1 functions in postnatal neural progenitors of the SGZ to regulate the production of neuronal progeny during the first 3 months of life, raising the question regarding the mechanisms underlying this process.

Functional expression of Kv1.1 in SGZ neural progenitor cells

Kv1.1 is highly expressed throughout the entire central nervous system (Wang et al., 1994). Given that neural progenitor cells only account for a small fraction of total cells in the brain, we decided to utilize Fezf2-GFP reporter mice to specifically examine neural stem cells and progenitor cells in the SGZ (Gong et al., 2003). The majority of the Fezf2-GFP-positive cells in the SGZ co-expressed BLBP and GFAP, two well-established neural stem cell markers (Berberoglu et al., 2014). We also found that Kv1.1 mRNA was expressed in the granule cell layer of the dentate gyrus (red dots, Figure 2A); a portion of the Kv1.1 mRNA signal was in close proximity to the GFP mRNA (green dots), which indicates Fezf2-GFP neural progenitor cells in the SGZ (Figure 2A,B). To further corroborate this finding, we performed immunostaining to determine the distribution pattern of the Kv1.1 protein in the mouse dentate gyrus. We found that Kv1.1 protein was highly expressed in mature granule cells and interneurons as reported previously (Grosse et al., 2000; Wang et al., 1994). A closer look further revealed the presence of Kv1.1 in DCX+ cells but not in Sox2+ cells, thereby confirming the expression of Kv1.1 in late-stage neural progenitor cells (Figure 2C).

Functional expression of Kv1.1 channel in SGZ neural progenitor cells expressing Fezf2-GFP at postnatal 2 weeks.

(A) In situ hybridization results showed that Kcna1 mRNA is expressed in Fezf2-GFP-positive neural progenitor cells. Inset is displayed at a higher magnification. (B) Kcna1 mRNA was not detected in the Kv1.1KO mouse, which served as a negative control. (C) Kv1.1 protein was expressed in the doublecortin (DCX)-expressing late-stage neural progenitor cells (arrows) but not Sox2-positive early-stage neural progenitor cells. Kv1.1 protein was highly expressed in the inhibitory interneurons (yellow arrows). (D–J) Pharmacological isolation of Kv1 currents in Fezf2-GFP-positive cells. Kv1.1 currents were elicited by trains of voltage steps from -80 mV to +40 mV in 10 mV increments from the holding potential of -80 mV in the absence (D and G) or presence of the Kv1-specific blocker dendrotoxin-k (DTX-K; 100 nM) (E and H). The DTX-K-sensitive currents were considered Kv1-mediated potassium currents (F, I, and J), which were much reduced in the Kv1.1KO mice. n = 4 cells from each phenotype. Scale bar = 20 μm in (C). Data are presented as mean ± SEM.

Next, we wanted to determine whether Kv1.1 protein could form functional potassium channels in the Fezf2-GFP-positive cells. As Kv1.1-mediated potassium currents can be inactivated by holding at relatively high voltages (> −50 mV) (Storm, 1988) and are sensitive to dendrotoxin-K (DTX-K) (Grissmer et al., 1994), a potent blocker of Kv1 family channels, we performed whole-cell patch-clamp recording in wild-type (Figure 2D,E,F) and Kv1.1KO (Figure 2F,G,I) Fezf2-GFP-positive cells. We could detect DTX-K-sensitive and low-voltage inactivated potassium currents in wild-type but not Kv1.1KO (Figure 2J) Fezf2-GFP+ cells. These findings reveal that Kv1.1 forms functional channels in Fezf2-GFP neural progenitor cells.

Loss of Kv1.1 depolarizes a subset of the neural progenitor cells in SGZ

Next, we looked into the impact of removing Kv1.1 from Fezf2-GFP cells at different developmental stages (Figure 3A). This experiment was performed within the first postnatal month to avoid complications from seizures that begin later in life. We sought to evaluate quiescent Sox2+ type 1 radial glia-like stem cells, highly proliferative Sox2+Tbr2+ type 2a neural progenitor cells, and type 2b neural progenitor cells that only express Tbr2. Based on the expression of cell-type markers, we first calculated the proportions of these three cell types among Fezf2-GFP cells. We found a high proportion of Tbr2+-only type 2b neural progenitor cells in Kv1.1KO SGZ compared to wild type (Figure 3B,C, arrowheads). These results suggested that the presence of Kv1.1 limits the number of late-stage neural progenitor cells.

Loss of Kv1.1 channels depolarizes type 2b neural progenitor cells in SGZ at postnatal 2 weeks.

(A) Based on the expression of the cell-fate markers, the neural progenitor cells in the sub-granular zone (SGZ) can be categorized into several developmental stages (see Figure 4 for detailed images). (B) Among all the Fezf2-GFP-positive cells in the SGZ, radial glia-like type 1 neural progenitor cells expressed predominantly Sox2, type 2a neural progenitor cells expressed both Sox2 and Tbr2 (white arrows), and type 2b progenitor cells expressed Tbr2. Post-mitotic immature neurons expressed doublecortin (DCX) and could also be identified as POMC-GFP-positive cells. (C) Among these cell types, type 2b cells were significantly increased in adult Kv1.1KO dentate gyrus compared to wild type (WT), according to the numbers of Tbr2-positive Fezf2-GFP-positive cells (n = 9 for each group; two-way ANOVA followed by Sidak's multiple comparisons test; p=0.0009, for type 2b cells). Scale bar = 20 μm.

Voltage-gated potassium channels are known to be involved in regulating action potential waveforms and firing frequencies, but this type of channel plays only minor roles in tuning passive properties such as the resting membrane potential (Corbin-Leftwich et al., 2018). For example, neurons lacking functional Kv1.1 display normal resting potentials but elevated action potential firing rates (Robbins and Tempel, 2012; Smart et al., 1998). To test whether the loss of Kv1.1 affects the membrane potential of neural progenitor cells, we recorded from Fezf2-GFP cells and POMC-GFP immature neurons, as the Pomc-GFP transgenic line faithfully labels immature neurons in the dentate gyrus (Overstreet et al., 2004). In addition, a previous study has shown that the radial glia-like cells are coupled by gap junctions that are essential for adult neurogenesis in the SGZ (Kunze et al., 2009). In order to label the recorded neural progenitor cells in brain slices, we included a gap-junction-permeable tracer neurobiotin in the pipette solution (Figure 4, A3–F3 and Figure 5A). After whole-cell patch-clamp recording to characterize the membrane properties, the brain slices were fixed with 4% paraformaldehyde (PFA). The cell-type identity of the recorded cell was characterized by examining the expression of cell-fate markers (Figure 3A). The membrane potentials of these cells were hyperpolarized and electrically silent; notably, the current injection could cause depolarization of POMC-GFP immature neurons but not firing of action potentials, while such depolarization of mature granule neurons could lead to action potential firing (data not shown). Remarkably, the Tbr2+/Fezf2+ type 2b neural progenitor cells lacking Kv1.1 displayed more depolarized resting membrane potentials than their wild-type counterparts (Figure 4G). Moreover, we found that type 2a progenitor cells were coupled via gap junctions (Figure 4B,E), a property that has not been reported previously.

Classification of Fezf2-GFP progenitor cells in SGZ.

Based on the expression of the cell-fate markers, neural progenitor cells in the sub-granular zone (SGZ) can be categorized into several developmental stages. Among all the Fezf2-GFP-positive cells (A–F), Sox2-positive type 1 cells (A1–F1) are radial glia-like cells (A–A4, C–C4) and can give rise to Sox2+/Tbr2+ type 2a transit-amplifying progenitor cells (B–B4, D–D4). Type 2a cells further differentiate into type 2b neuroblasts that are positive for Tbr2 only (C–C4, F–F4). Type 1 (A3 and D3) and type 2a (B3 and E3) cells formed extensive syncytial connections with other cells from the same developmental stage, as indicated by the gap-junction-permeable avidin-neurobiotin (A–B) staining. Scale bar = 20 μm. (G) Type 1 and type 2a Fezf2-GFP-positive neural progenitor cells were hyperpolarized; by contrast, type 2b cells lacking Kv1.1 channels were significantly more depolarized than the wild-type (WT) cells (n = 14, 14, 9, 10, 9 (WT) and 28, 14, 10, 11, 8 (Kv1.1KO) for type 1 cells (Fezf2-GFP+/Sox2+), type 2a cells (Fezf2-GFP+/Sox2+/Tbr2+), type 2b cells (Fezf2-GFP+/Tbr2+), immature neurons (POMC-GFP+), and label-free mature neurons; (two-way ANOVA followed by Sidak's multiple comparisons test; p=0.02, for type 2b cells)).

Multinomial logistic regression for cell-type prediction.

(A) Acute brain slice recording from the DG of an Fezf2-GFP mouse. (B and C) A multinomial logistic regression model was constructed using the biophysical characteristics of cells that were identified previously (same cohort of cells from Figure 3D) as the training dataset. Two individual regression models were generated for wild-type (B) and Kv1.1KO (C) cells. The cell types of unknown cells were later classified according to the resting membrane potential, input resistance, and membrane capacitance. Heatmaps show the estimated probabilities for each cell type against membrane potential (D), input resistance (E), and membrane capacitance (D). The cell types were determined based on maximum likelihood. (G) Resting membrane potentials of wild-type and Kv1.1KO progenitor cells. The predicted type 2b cells lacking Kv1.1 channels were significantly more depolarized (two-way ANOVA, followed by Sidak's multiple comparisons test; p<0.0001, for type 2b cells). Comparable input resistances (H) and membrane capacitances (I) were observed between wild-type and Kv1.1KO cells. n = 144, 25, and 22 for type 1, 2a, and 2b cells, respectively, in the wild-type group; n = 71, 70, and 22 for type 1, 2a, and 2b cells, respectively, in the Kv1.1KO group. (J–L) Voltage responses from type 1 (J), type 2a (K), type 2b (L) to series voltage from -120 mV to +40 mV or -80 mV to +40 mV, with a holding potential of -80 mV. (M) Current–voltage curves in (J–L) (the circles indicate the positions of measurements; type 1 (7 cells), type 2a (7 cells), type 2b (10 cells)). (N, O) Voltage response from -80 mV to +40 mV, with a holding potential of -80 mV and leak subtraction, shown for type 2b (N); current–voltage curve of type 2b (n = 17 cells) with leak subtraction (O). (P) A representative transient inward current (sodium current) was observed in 9 out of 25 type 2b cells. Data are presented as mean ± SD in (G), (H), and (I); mean ± SEM in (M, O).

Figure 5—source data 1

multiple logistic regression datasets for biophysical analysis of the neural progenitor cells in postnatal mouse hippocampus.

https://cdn.elifesciences.org/articles/58779/elife-58779-fig5-data1-v3.xlsx

Although we have obtained convincing results showing that the type 2b neural progenitor cells lacking Kv1.1 channels were more depolarized, the invasive nature of the patch-clamp technique caused more than 70% of the recorded cells to be either damaged or lost during the subsequent immunostaining procedure, and therefore, their developmental stages were not determined. We tried to classify those Fezf2-GFP-positive cells based on their resting membrane potential, input resistance, and membrane capacitance, the three basic biophysical characteristics obtained from patch-clamp recording (Figure 5). First, we used the biophysical characteristics of cells with unequivocal cell-type identification determined by post-hoc immunostaining as a training dataset (Figure 4G) to construct separate multinomial logistic regression models for wild-type and Kv1.1KO cells (Fahrmeir and Tutz, 2001). The probability of each cell belonging to a given cell type was calculated by fitting biophysical characteristics to the models: resting membrane potentials (Figure 5D), input resistance (Figure 5E), and membrane capacitance (Figure 5F). We found that more than 80% of the Fezf2-GFP-positive cells with known cell types could be accurately predicted using this regression model. Interestingly, judging from the gap-junction-permeable neurobiotin labeling, we noticed that cells from the same subtypes clustered closely together (Figure 5B, C). Of note, type 1 neural stem cells tended to have a more hyperpolarized resting membrane potential, lower input resistance, and larger membrane capacitance, while type 2b neural progenitor cells tended to have more depolarized resting membrane potentials, higher input resistance, and smaller membrane capacitance. The cell type was then assigned based on the highest probability. Consistent with the results shown in Figure 4G, we found that the assigned type 2b neural progenitor cells lacking Kv1.1 channel were also significantly more depolarized than their wild-type counterparts. Nevertheless, both the input resistance (Figure 5E) and membrane capacitance (Figure 5F) were comparable between wild-type and Kv1.1KO cells. To validate the progenitor classification and reveal the cell membrane properties, we plotted I-V curves for the three subgroups, as classified by the multinomial logistic regression model. Similar to the results of a previous study using progenitor cell recording (Steiner et al., 2006), type 1 neural stem cells characteristically displayed passive, non-inactivating currents with a linear current–voltage relationship (Figure 5J,M), similar to the properties of astrocytes. In contrast, type 2b neural progenitor cells expressed small outwardly rectifying currents (Figure 5L,M). Of note, in 9 out of 25 type 2b neural progenitor cells, we observed transient inward currents induced by depolarizations more positive than −30 mV, followed by outwardly rectifying currents; these observations are indicative of sodium currents, hence consistent with neuronal differentiation (Figure 5P). The delayed outward rectifying currents in type 2b neural progenitor cells were more apparent when characterized by means of leak subtraction (Figure 5P,O). Moreover, the electrophysiological features of type 2a neural progenitor cells were suggestive of a transition phase between type 1 neural stem cells and type 2b neural progenitor cells, since type 2a neural progenitor cells displayed outwardly rectifying currents but no detectable sodium currents (Figure 5K,M).

Kv1.1 regulates neural progenitor cell number via the TrkB signaling pathway

A previous work has shown that suppressing TrkB signaling by removing brain-derived neurotrophic factor (BDNF) from neural progenitor cells drastically reduces the thickness of the dentate gyrus granule cell layer (Li et al., 2008), while enhancing TrkB signaling by overexpressing BDNF in neural progenitor cells augments neurogenesis (Quesseveur et al., 2013). Notably, increased BDNF expression has been found in the Kv1.1KO mouse brains (Diez et al., 2003). Carbamazepine, an anti-epileptic drug, could antagonize this increase of BDNF levels and also suppress the excessive neurogenesis in SGZ in adult Kv1.1KO mice (Lavebratt et al., 2006). We hypothesized that the excessive depolarization of type 2b neural progenitor cells lacking Kv1.1 (Figure 4G and Figure 5G) might stimulate neural progenitor cell proliferation by elevating the level of TrkB signaling. Restrained with the antibody incompatibility for double labeling, we stained the neural progenitor cells in SGZ with antibodies against phospho-TrkB (Tyr816), together with either Sox2 or Tbr2. We found most of the phospho-TrkB-positive cells within the SGZ region (Figure 6, Figure 6—figure supplement 1, and Figure 7—figure supplement 1), and a greater number of phospho-TrkB-positive cells in the dentate gyrus of Kv1.1KO mice as compared to the wild-type mice (Figure 6). Moreover, phospho-TrkB was found primarily in Tbr2+ or DCX+ cells (Figure 6B and Figure 6—figure supplement 1) but rarely in Sox2+ cells (Figure 6A and Figure 6—figure supplement 1), despite the fact that the expression levels of TrkB receptor are higher in type 1 neural progenitor cells (Vilar and Mira, 2016). Not only did the loss of Kv1.1 cause an increase of Tbr2+ cells with phospho-TrkB signals, but also the phospho-TrkB signals in the Tbr2+ cells were much more intense in the Kv1.1KO mice, suggesting that the TrkB signaling pathway was activated in the Tbr2-expressing type 2b cells in Kv1.1KO mice (Figure 3).

Figure 6 with 2 supplements see all
TrkB is mostly active in Tbr2-positive neural progenitor cells.

Phospho-TrkB (Tyr816) signal represents a surrogate measure for TrkB activity. Phospho-TrkB-positive cells rarely colocalized with the Sox2-positive, presumably type 1 and type 2b neural progenitor cells (A); by contrast, phospho-TrkB-positive cells colocalized with the majority of Tbr2-positive, presumably type 2b cells. (B) More Tbr2+/phospho-TrkB+ neural progenitor cells could be found in the sub-granular zone (SGZ) of Kv1.1KO mice. Scale bar = 100 μm (A) and 50 μm (B). (C) Quantification analysis of phospho-TrkB levels in Sox2+ or Tbr2+ cells. The phospho-TrkB fluorescent intensity (F1) of each Sox2+ or Tbr2+ cell was measured and normalized to the Sox2+ or Tbr2+ fluorescent intensity and the total measured cell area (F2 X nm2). n = 246, 243, 69, and 92 for Sox2+/WT, Sox2+/Kv1.1KO, Tbr2+/WT, and Tbr2+/Kv1.1KO cells, respectively. **** p<0.0001.

To test whether antagonizing TrkB activity could reduce the hyperplastic effect of Kv1.1 on adult neurogenesis, we performed daily intraperitoneal injections of GNF-5837 (20 mg/kg), a brain-permeable Trk inhibitor (Albaugh et al., 2012), into mice for 3 weeks starting at the first postnatal week. This 3-week GNF-5837 treatment was sufficient to suppress TrkB signaling, as the phospho-TrkB levels were drastically reduced in the hippocampus (Figure 7—figure supplement 1). Both Fezf2-GFP-positive cells and Ki67-positive cells in Kv1.1KO and control mice were comparable in number after this GNF-5837 treatment (Figure 7B,C,D). By contrast, age-matched Kv1.1KO mice receiving vehicle-only injection had significantly more Fezf2-GFP- and Ki67-positive cells in the SGZ than those in control mice (Figure 7A,B,C), in agreement with a previous report (Almgren et al., 2007). Thus, pharmacological inhibition of Trk receptors prevented the increase of neural progenitor cells in the SGZ of Kv1.1KO mice.

Figure 7 with 2 supplements see all
Kv1.1 channels regulate neural progenitor cell numbers via the TrkB signaling pathway.

(A, C, and D) Kv1.1KO mice have more Fezf2-GFP- (C) and Ki67-positive cells (D) than wild-type mice, with vehicle treatment. p=0.0014, one-way ANOVA followed by Tukey's test in (C); p<0.0001, one-way ANOVA followed by Tukey's test in (D). (B, C, and D) Suppression of Kv1.1-dependent neurogenesis by GNF-5837, a potent Trk inhibitor. Mice receiving daily GNF-5837 (20 mg/kg) administration had comparable numbers of Fezf2-GFP- (C) and Ki67-positive cells (D) between wild-type and Kv1.1KO mice; n = 6–8 mice from each genotype with vehicle-only or GNF-5837 treatment. (E) Clonal analysis of adult neurogenesis. Tamoxifen (0.5 mg) was administered at postnatal 3 weeks to sparsely delete Ntrk2 (a gene that encodes the TrkB receptor) in a subset of neural progenitor cells. In cells lacking only one allele of TrkB, Kv1.1KO had larger clone sizes than wild-type cells; by contrast, the Kv1.1-dependent proliferation advantage was abrogated in clones lacking both TrkB alleles. p=0.0389, comparing wild-type and Kv1.1KO on the Ntrk2flox/+ background; two-way ANOVA followed by Sidak's multiple comparisons test; n = 39–157 for each group. Scale bar = 100 μm. Data are presented as mean ± SEM. *p<0.05, **p<0.01; ***p<0.001; ****p<0.0001; n.s., no significant difference. (F) Kolmogorov-Smirnov plots showing a rightward shift of clone sizes in Kcna1-/-;Gli1creERT2/+;Ntrk2flox/+;Rosa26Tom/+ mice (red trace) compared to wild-type Gli1creERT2/+;Ntrk2flox/+;Rosa26Tom/+ mice (black trace) (p=0.0029, t-test), but this effect was absent in mice lacking TrkB receptor (p>0.05 between wild-type Gli1creERT2/+;Ntrk2flox/+;Rosa26Tom/+ (black trace) and Gli1creERT2/+;Ntrk2flox/flox;Rosa26Tom/+ (blue trace); Kcna1-/-;Gli1creERT2/+;Ntrk2flox/flox;Rosa26Tom/+ (green trace)).

If Kv1.1 channels limit neural progenitor cell proliferation, Kv1.1KO neural progenitor cells should generate larger clones than controls. To estimate the clone size, we generated Gli1creERT2/+;Ntrk2flox/flox;Rosa26Tom/+ and Gli1creERT2/+;Ntrk2flox/+;Rosa26Tom/+ mice in the background of either wild-type or Kv1.1KO. These quadruple transgenic mouse lines carried a tamoxifen-inducible cre-recombinase Gli1creERT2 that can sparsely delete the floxed-Ntrk2 gene that encodes the TrkB receptor in the neural stem cells and progenitor cells of the SGZ in the presence of tamoxifen. The Cre-dependent TdTomato reporter (Rosa26Tom) was used to label tamoxifen-activated CreER recombinase cells and their progeny (Li et al., 2013; Singh et al., 2015). We intraperitoneally injected 3-week-old mice with a single dose of tamoxifen (0.5 mg/kg) to delete the floxed-Ntrk2 in the SGZ, and the clone sizes were estimated at 8 weeks of age. A single clone was defined as encompassing all the cells within a 100-µm radius of the clone center (Singh et al., 2015). Indeed, TrkB deletion abolished the hyperplastic phenotype in Kv1.1KO mice, as Kcna1-/-;Gli1creERT2/+;Ntrk2flox/+;Rosa26Tom/+ mice had larger clone sizes than Gli1creERT2/+;Ntrk2flox/+;Rosa26Tom/+, Kcna1-/-;Gli1creERT2/+;Ntrk2flox/flox;Rosa26Tom/+, and Gli1creERT2/+;Ntrk2flox/flox;Rosa26Tom/+ mice (Figure 7E and Figure 7—figure supplement 2). The cumulative clone-size plots further confirmed a rightward skewness distribution rather than just an outlier bias (red trace) in Kcna1-/-;Gli1creERT2/+;Ntrk2flox/+;Rosa26Tom/+ mice, and this shift was not observed for the neural progenitor cells lacking TrkB receptors (green trace) (Figure 7F).

Discussion

In this study, we have shown that Kv1.1, a voltage-gated potassium channel, functions as a brake to fine-tune the rate of neurogenesis in mouse dentate gyrus within the first 2 months of postnatal life. Removing the Kv1.1 channel depolarized the late-stage neural progenitor cells that exhibit high input resistance and small capacitance (Figure 5), presumably the transit-amplifying type 2b neural progenitor cells (Figure 4D). Depolarization of type 2b neural progenitor cells causes cell-autonomous over-activation of the TrkB signaling pathway that promotes neural progenitor cell proliferation. Consequently, mice lacking functional Kv1.1 develop a megencephalic phenotype at early postnatal stages, as the neural progenitor cells without Kv1.1 over-proliferate due to elevated TrkB signaling (Figure 8).

Summary of the role of Kv1.1 channels in regulating early postnatal neurogenesis in SGZ.

The membrane potentials in type 1 radial glia-like neural stem cells and type 2a transit-amplifying progenitor cells are relatively hyperpolarized. In type 2b neural progenitors, cells lacking the Kv1.1 channel are more depolarized than wild types, further stimulating the proliferation of type 2b cells via activating the TrkB signaling pathway. The mature granule cells become hyperpolarized again.

In the central nervous system, mature neurons are capable of generating action potentials, while neural progenitor cells and immature neurons are considered electrically non-excitable and do not fire action potentials (Bean, 2007; Fukuda et al., 2003). In this study, our electrophysiological characterization of postnatal neural progenitors raised the possibility that alterations in membrane potential could impact postnatal neurogenesis. Although neural progenitor cells are not electrically excitable, these cells do express a variety of ion channels (Shin et al., 2015; Yamashita, 2012). The radial glia-like type 1 neural stem cells express high levels of glial inwardly rectifying potassium channels, mostly Kir4.1 and Kir5.1 (Yasuda et al., 2008). In addition to the inwardly rectifying potassium channels, type 1 neural stem cells in the SGZ are electrically coupled via gap junctions formed by connexins (Figure 4Kunze et al., 2009; Rozental et al., 1998). Both inwardly rectifying potassium channels and gap junctions contribute to the extremely low input resistance in type 1 cells (Figure 5E,H) and keep these neural stem cells hyperpolarized (Figures 4G and 5D,G). Once a type 1 cell commits to the neural progenitor cell fate, it will leave the extensive network of type 1 radial glia-like neural stem cells that are electrically coupled via gap junctions, as evidenced by the reduced capacitance and increased input resistance. Eventually, type 2b neural progenitor cells lose all gap junction connections and exist as single cells. Our multinomial logistic regression models faithfully depicted this process; when cells transited from the hyperpolarized network of quiescent type 1 neural stem toward individual highly proliferative type 2b neural progenitor cells, the input resistance was gradually increased, and the membrane capacitance was decreased due to the loss of gap junction coupling (Figure 5E,F,H,I). Moreover, our regression model provides a simple method for studying neural progenitor cell physiology. We showed that the identity of the neural progenitor cells within the SGZ could be accurately predicted based on the membrane potential, input resistance, and membrane capacitance obtained from patch-clamp recording, and there was no further need for post-hoc immunostaining of cell-type markers, a time-consuming procedure with a low success rate.

Among all voltage-gated potassium channels, the Kv1 family is crucial for regulating the resting membrane potential, as Kv1 channels can be activated at subthreshold membrane potentials (Dodson et al., 2002; Grissmer et al., 1994). Although Kv1.1 is expressed in most cells in the dentate gyrus, especially the inhibitory interneurons (yellow arrows, Figure 2CLi et al., 2012), we only observed significant depolarization of type 2b neural progenitor cells lacking Kv1.1 (Figures 4G and 5D,G). One plausible explanation for this specificity of effect is that the type 1 stem cells and type 2a neural progenitor cells remain hyperpolarized by the immense inwardly rectifying potassium currents and are further stabilized by the extensive electrical coupling through gap junctions. As stipulated by the Goldman-Hodgkin-Katz equation (Hille, 2001), conditions of low input resistance and large capacitance (Figure 5E,F,H,I) will diminish the effect of voltage-gated channels, such as Kv1.1, on the membrane potential to negligible levels. By contrast, a small potassium conductance could be sufficient to keep cells with higher input resistance and smaller capacitance at relatively hyperpolarized membrane potentials.

Despite decades of extensive studies on postnatal neurogenesis, how ion channels and membrane potentials affect neurogenesis remains an intriguing open question. Ion channels have been shown to regulate postnatal and adult neurogenesis via both environmental (non-cell-autonomous) and intrinsic (cell-autonomous) mechanisms. Several studies have found that neural circuits may regulate the neural stem cell fate via non-cell-autonomous synaptic mechanisms. For example, increased gamma aminobutyric acid (GABA) tone of hippocampal parvalbumin-expressing interneurons facilitates the transition of radial glia-like cells into a quiescent state via γ2-containing GABAA receptors expressed in SGZ neural stem cells (Song et al., 2012). Furthermore, moderate activation of indirect glutamatergic mossy cells increases the radial glia-like stem cell quiescence (Yeh et al., 2018). On the other hand, several voltage-gated ion channels regulate neurogenesis in a cell-autonomous manner. Deleting Paralytic, the only voltage-gated sodium channel in Drosophila, shrinks the brain lobes due to reduced proliferation and enhanced apoptosis in type I and type II neuroblasts (Piggott et al., 2019). Moreover, in addition to regulating progenitor cell proliferation, hyperpolarization of progenitor cells in the cortex by inwardly rectifying potassium channels shifts neurogenesis from direct corticogenesis to indirect corticogenesis via suppression of WNT (Wingless-related integration site) activity (Vitali et al., 2018). In our study, the affected type 2b neural progenitor cells had already lost gap junctions and displayed high input resistance, so the minuscule Kv1.1 window current may be sufficient to keep wild-type but not Kv1.1KO type 2b neural progenitor cells hyperpolarized (Figure 4G and Figure 5Maylie et al., 2002). This finding further raises the possibility that the plasticity of neurogenesis can be affected by bioelectric membrane properties (Sundelacruz et al., 2009).

One intriguing question concerns how membrane depolarization might activate the TrkB receptor in a cell-autonomous manner. The canonical ligands that activate the TrkB receptor are BDNF, released via the regulated secretory pathway, and neurotrophin 4/5 (NT4/5), released via the constitutive secretory pathway (Bothwell, 2014). BDNF is a plausible candidate for the endogenous neurotrophin that mediates the Kv1.1-dependent postnatal neurogenesis in mouse hippocampus, because BDNF is the only neurotrophin that has been detected in the SGZ in the mouse brain, and genetic deletion of NT4/5 did not impair adult neurogenesis (Vilar and Mira, 2016). BDNF plays a multifaceted role in the central nervous system, including promoting synaptogenesis, axonal guidance, dendrite outgrowth, and postnatal neurogenesis (Jan and Jan, 2010; Jeanneteau et al., 2010; Liu and Nusslock, 2018). Depolarizing the neural progenitor cells may elevate the intracellular calcium level through the voltage-gated calcium channels, which could trigger BDNF release via activating the SNARE complex (Shimojo et al., 2015; Wong et al., 2015; Xu et al., 2018). Furthermore, the unique biochemical properties of BDNF may allow such a diffusible signaling molecule to act cell-autonomously in regulating neurogenesis in mouse hippocampus. BDNF is a sticky peptide with multiple positively charged residues, and therefore, BDNF has a limited range of diffusion upon release (Sasi et al., 2017). In brain slices, BDNF only acts within 4.5 µm of its release site, which is less than the diameter of a single neural progenitor cell (Mändl et al., 2002). Hence, depolarization of the neural progenitor cells could release BDNF to activate TrkB signaling in a cell-autonomous manner due to its short effective range. Interestingly, GABA, another diffusible factor, has also been shown to cell-autonomously regulate neurogenesis in adult hippocampus. GABA activates the inhibitory GABAA receptors on the same neural progenitor cells by involving the GABA transporter VGAT. Removal of this inhibitory GABA signaling promotes neural progenitor cell proliferation by shortening the cell cycle via activation of S-phase checkpoint kinases and the histone variant H2AX (Andäng et al., 2008). Moreover, deleting a subset of GABAA receptors in neural progenitor cells not only stimulates neurogenesis, but also alters the positioning of newborn neurons in adult hippocampus, reminiscent of our finding that Kv1.1KO neurons are positioned farther away from the SGZ (Figure 1FDuveau et al., 2011). Consistent with our results, over-activation of BDNF modulates the positioning in the SGZ of granule cells generated during early postnatal stages (Kerloch et al., 2019; Scharfman et al., 2005). Nevertheless, we cannot exclude the possible involvement of other signaling pathways, such as GSK3β and DISC1, since disrupting these signaling pathways causes failures of guidance for newborn neuron migration and positioning (Duan et al., 2007; Ng et al., 2016).

Given that previous studies have shown that TrkB receptors can be activated by mechanisms other than the neurotrophins, the elevated TrkB signaling we observed in Kv1.1KO mice could be BDNF-independent. For example, membrane depolarization itself could activate TrkB via elevating the intracellular cAMP levels, which has been demonstrated in cultured neurons previously (Meyer-Franke et al., 1998). Under certain circumstances, TrkB receptors can also be auto-activated in the absence of neurotrophins by increasing the receptor abundance (Gupta et al., 2020). The immature form of TrkB receptor that lacks N-glycosylation on the extracellular domain is constitutively active, even if it is located intracellularly; the membrane potential could indirectly regulate TrkB activity by tuning the cellular glycosylation process (Gupta et al., 2020; Watson et al., 1999). Moreover, TrkB receptors can also be transactivated via cross-talk with certain G-protein-coupled receptors, such as EGF (Puehringer et al., 2013) and adenosine A2a receptors (Lee and Chao, 2001). Lastly, TrkB signaling can be elevated by increasing Ntrk2 gene expression (Yamashita et al., 2021). It will be of interest to pursue experiments to investigate whether these mechanisms are involved in Kv1.1-dependent postnatal neurogenesis in mouse hippocampus.

One important limitation of our study is the age of animals we used. To avoid the confounding effects of seizures that begin in 3- to 4-week-old Kv1.1KO mice, we focused our study on early postnatal neurogenesis. A recent work using virally labeled neural progenitor cells in the SGZ has revealed a massive burst of postnatal neurogenesis within the first week, as evidenced by viral labeling of neural progenitor cells at P6; these neurons persist for about 2 months before undergoing apoptosis, a time course distinct from adult-born neurons produced later in life (Ciric et al., 2019). Our study of young mice describes the involvement of Kv1.1 in the generation of neurons by neural progenitor cells beginning in the first postnatal week. How the loss of Kv1.1 function affects neurogenesis later in life will require further study.

In summary, our study has uncovered a unique role of Kv1.1 in regulating neurogenesis within the postnatal dentate gyrus during the first 2 months of life. Alterations in adult neurogenesis in the dentate gyrus have been reported for patients with psychiatric and neurological diseases (Gonçalves et al., 2016; Sahay and Hen, 2007), and recent studies have suggested that neural progenitor cells might be potential targets for treating neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease (Christie and Turnley, 2012). Thus, our findings regarding Kv1.1 modulation of early postnatal neurogenesis may help lay the groundwork for future identification of novel therapeutic targets for neurodegenerative and psychiatric diseases (Christian et al., 2014).

Materials and methods

Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Strain background (Mus musculus)ICR (CD-1 or Swiss Outbred)BioLASCO TaiwanOutbred strain
Genetic reagent (Mus musculus)Kcna1-
(Kcna1tm1Tem)
PMID:9581771MGI:
1861959
Dr. Bruce Tempel (University of Washington, USA)
Genetic reagent (Mus musculus)Rosa26GT (Gt(ROSA)26Sortm6(ACTB-EGFP*,-tdTomato))PMID:22479386MGI:
5314252
Dr. Liqun Luo (Stanford University, USA)
Genetic reagent (Mus musculus)Rosa26TG (Gt(ROSA)26Sortm7(ACTB-EGFP*))PMID:22479386MGI:
5314253
Dr. Liqun Luo (Stanford University, USA)
Genetic reagent (Mus musculus)POMC-GFP (Tg(Pomc-EGFP)1)PMID:11373681MGI: 3776091Dr. Jeffery Friedman (Rockefeller University, USA)
Genetic reagent (Mus musculus)Fezf2-GFP (Tg(Fezf2-EGFP)CO61Gsat)PMID:14586460MGI: 3847288Dr. Su Guo (University of California, San Francisco, USA)
Genetic reagent (Mus musculus)Ntrk2flox
(Ntrk2tm1Lfr)
PMID:10995833MGI: 2384391Dr. Louis Reichardt (University of California, San Francisco, USA)
Genetic reagent (Mus musculus)Nestin-cre (Tg(Nes-cre)1Kln)PMID:10471508MGI: 2176173Jackson Laboratory, USA
Genetic reagent (Mus musculus)Gli1creERT2 (Gli1tm3(cre/ERT2)Alj)PMID:15315762MGI: 3053957Jackson Laboratory, USA
Genetic reagent (Mus musculus)Rosa26Tom (Gt(ROSA)26Sortm14(CAG-tdTomato)Hze)PMID:20023653MGI: 3809524Jackson Laboratory, USA
AntibodyAnti-GFP (chicken polyclonal)Aves, USACat#: GFP-1010
RRID:AB_2307313
1:400
AntibodyAnti-Sox2 (mouse monoclonal, IgG2b)Millipore, USACat#: MAB4343
RRID:AB_11205572
1:400
AntibodyAnti-Tbr2 (rabbit monoclonal)Abcam,
USA
Cat#: ab183991 RRID:AB_27210401:400
AntibodyAnti-Tbr2 (chicken polyclonal)Millipore, USACat#: AB15894 RRID:AB_106156041:400
AntibodyAnti-Doublecortin (rabbit monoclonal)Cell Signaling,
USA
Cat#:
14802
1:400
AntibodyAnti-phospho-TrkB (Tyr816) (rabbit polyclonal)Millipore, USACat#: ABN1381RRID:AB_27211991:100
AntibodyAnti-Kv1.1 (mouse polyclonal, IgG2b)Aves, USACat#: 75–105RRID:AB_21285661:200
AntibodyAnti-Ki67 (rabbit polyclonal)Invitrogen, USACat#: MA5-14520RRID:AB_109794881:500
Commercial assay or kitFluoromount GSouthernBiotech, USACat#: 0100–01 RRID:SCR_015961
Commercial assay or kitRNAscope Fluorescent Multiplex KitAdvanced Cell Diagnostics, Inc, USACat#: 320850
Recombinant DNA reagentProbe-Mm-GFPAdvanced Cell Diagnostics, Inc, USACat#: 400281
Recombinant DNA reagentProbe-Mm-KcnaAdvanced Cell Diagnostics, Inc, USACat#: 435901
Chemical compound, drugGNF-5837Tocris, UKCat#: 4559
Chemical compound, drugPEG400
(Polyethylene glycol 400)
Sigma-Aldrich, USACat#: 1546445
Chemical compound, drugCremophor ELSigma-Aldrich, USACat#: C5135
Chemical compound, drugDendrotoxin-KAlomone Labs, IsraelCat#:
D-400
Chemical compound, drugCremophor ELSigma-Aldrich, USACat#: C5135
Chemical compound, drugNeurobiotinVector Laboratories, USACat#:
SP-1120
0.3% in the pipette solution
Chemical compound, drugLucifer yellow-conjugated dextransInvitrogen, USACat#:
D-1825
0.2% in the pipette solution
Chemical compound, drugNeutravidinThermo Fisher,
USA
Cat#:
31000
0.25%
Software, algorithmpClamp 10.0Molecular Devices,
USA
RRID:SCR_011323
Software, algorithmGraphPad Prism 7.0Graphpad,
USA
RRID:SCR_002798
Software, algorithmImaris 9.0Bitplane, SwitzerlandRRID:SCR_007370
Software, algorithmR Project for Statistical ComputingThe R foundationRRID:SCR_001905

Animals

This study was carried out in strict accordance with the recommendations found in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. The experimental protocols were approved by the Institutional Animal Care and Use Committee of Academia Sinica (protocol #: 15-01-813) and the University of California, San Francisco. Mice (3–5 per cage) were housed in the animal facility and fed with a regular chow diet on a standard 12 hr light/12 hr dark cycle. At least three animals were used for every experimental group. The Kcna1- mice were obtained from Dr. Bruce Tempel's lab at the University of Washington, USA. Rosa26GT (Gt(ROSA)26Sortm6(ACTB-EGFP*,-tdTomato)) and Rosa26TG (Gt(ROSA)26Sortm7(ACTB-EGFP*)), two transgenic mouse lines for producing MADM-6 mice, were obtained from Dr. Liqun Luo's lab at Stanford University, USA. The Ntrk2flox mice were obtained from Dr. Louis Reichardt's lab at the University of California, San Francisco, USA. POMC-GFP (Tg(Pomc-EGFP)1) mice were obtained from Dr. Jeffery Friedman's lab at Rockefeller University, USA. Fezf2-GFP (Tg(Fezf2-EGFP)CO61Gsat) mice were obtained from Dr. Su Guo's lab at the University of California, San Francisco, USA. Nestin-cre (Tg(Nes-cre)1Kln), Gli1creERT2 (Gli1tm3(cre/ERT2)), and Rosa26Tom (Gt(ROSA)26Sortm14(CAG-tdTomato)) mice were obtained from Jackson Laboratory (Bar Harbor, Maine, USA). All mice were maintained on an ICR (Institute of Cancer Research) background. GNF-5837 (Tocris, UK) was dissolved in dimethyl sulfoxide (DMSO) (Sigma, USA), and then diluted in a solvent composed of 65% PEG400 (Sigma, USA) and 35% Cremophor EL (Sigma, USA) for intraperitoneal injection.

Electrophysiology

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Brain slices (250 µm thickness) containing the hippocampus were prepared as described previously (Yang et al., 2012b). Mice were first anesthetized with isoflurane and then decapitated. The brain was swiftly removed and placed in cutting solution: 110 mM choline chloride, 25 mM NaHCO3, 11 mM glucose, 2.5 mM KCl, 1.25 mM NaH2PO4, 11.6 mM sodium ascorbate, 3.1 mM sodium pyruvate, 7 mM MgCl2, and 0.5 mM CaCl2, equilibrated with 95% O2/5% CO2. Brain slices were obtained from tissue immersed in the cutting solution using a compresstome (Precisionary Instruments, USA). Slices were then incubated in artificial cerebrospinal fluid (aCSF): 126 mM NaCl, 21.4 mM NaHCO3, 10 mM glucose, 2.5 mM KCl, 1.25 mM NaH2PO4, 1.2 mM MgCl2, and 2 mM CaCl2, equilibrated with 95% O2/5% CO2. An Axon700B amplifier (Molecular Devices Corp, USA) was used to measure membrane currents and membrane capacitance in the standard whole-cell patch-clamp configuration. Data were acquired at 5 kHz with Clampex10 software (Molecular Devices Corp, USA). The intracellular solution contained 135 mM potassium gluconate, 15 mM KCl, 10 mM HEPES, 5 mM Mg2ATP, 1 mM Na3GTP, 10 mM sodium phosphocreatine, and 0.05 mM EGTA; pH was adjusted to 7.2 with KOH. Dendrotoxin-κ (Alomone Labs, Israel) was used to specifically block the Kv1.1 channel. Pipettes were pulled from 1.5 mm borosilicate glass capillaries (Sutter Inc, USA) and had a resistance of 3–5 MΩ when filled with the intracellular solution; data were excluded from further analyses if the series resistance was higher than 20 MΩ and the holding current at −70 mV was lower than −100 pA. All experiments were performed at room temperature.

Immunostaining

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Mice were fed ad libitum and were anesthetized with intraperitoneal Zoletil/Xylazine injection before transcardial perfusion with saline followed by 4% PFA. Brains were removed and post-fixed overnight in 4% PFA. Brains were then cryoprotected overnight in saline containing 30% sucrose at 4°C until they sank. For antigen retrieval, the brain sections (16 µm) were boiled in sodium citrate buffer (10 mM sodium citrate, 0.05% Tween 20, pH 6.0) between 95 and 100°C for 20 min. After the buffer was cooled to room temperature, the samples were further processed. The brain sections were washed in a blocking medium containing 0.1% Triton X-100% and 5% donkey serum (Jackson Immunoresearch Laboratories), and incubated overnight (4°C) with primary antibodies against GFP (chicken, 1:400; Aves, USA), Sox2 (mouse IgG2b, 1:400; Millipore, USA), Ctip2 (rabbit, 1:500; Abcam, USA), Tbr2 (rabbit, 1:400; Abcam, USA.), Tbr2 (chicken, 1:400; Millipore, USA), Doublecortin (rabbit, 1:400; Cell Signaling, USA), Kv1.1 (1:200; Antibodies Inc, USA), phospho-TrkB (rabbit, 1:200; Millipore, USA), or Ki67 (rabbit, 1:500; Invitrogen, USA), followed by Alexa dye-tagged secondary antibodies (donkey 1:100; Invitrogen, USA). For immunostaining of samples after electrophysiology recording, the brain slices were fixed in 4% PFA at 4°C for 2 hr. The internal solution contained Neurobiotin (0.3%, MW: 367 Da; Vector Laboratories, USA) and Lucifer yellow-conjugated dextrans (0.2%, MW: 10 kDa; Invitrogen, USA) to respectively label gap junction-coupled cells and recorded cells. The slices were washed three times at room temperature for 40 min in 0.3% Triton X-100 and 3% Bovine Serum Albumin (BSA) (Sigma Aldrich, USA) for blocking and permeabilization, followed by incubation overnight at 4°C with Neutravidin (0.25%; Thermo Fisher Scientific, USA) and primary antibodies against GFP (chicken, 1:400; Aves, USA), Sox2 (mouse IgG2b, 1:400; Millipore, USA) or Tbr2 (rabbit, 1:400; Abcam, USA). Secondary antibodies conjugated with goat anti-rabbit IgG Alexa 405, goat anti-chicken IgG Alexa 488, and goat anti-mouse IgG2b Alexa 633 were purchased from Invitrogen. The slides were mounted using Fluoromount G mounting medium containing 4′,6-diamidino-2-phenylindole (DAPI) (Southern Biotech, USA), and images were acquired using a confocal microscope (Zeiss, Germany).

In situ hybridization

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The mouse brains were frozen and sectioned, as previously described (Li et al., 2019). Sections were fixed with chilled 4% PFA for 15 min and then washed with 0.1 M phosphate buffered saline (PBS) twice. Sections were then dehydrated with 50% ethanol, 70% ethanol, and 100% ethanol sequentially. Slides were treated with protease and then incubated with a customized probe for 2 hr. Signal was detected using Probe-Mm-GFP and Probe-Mm-Kcna and further amplified by RNAscope Fluorescent Multiplex Kit (Advanced Cell Diagnostics, USA). Images were acquired using a confocal microscope (Zeiss, Germany).

Clonal analysis

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The clonal analysis was performed as described previously (Singh et al., 2015). Briefly, for sparsely labeling the progenitor cells, 3-week-old mice carrying Gli1creERT2; Rosa26Tom with wild-type or Kcna1-/- and Ntrk2flox/flox or Ntrk2flox/+ were injected with a single dose of 0.5 mg/kg of tamoxifen (Sigma, USA) dissolved in corn oil (Sigma, USA). At 8 weeks of age, mice were killed by an intraperitoneal injection of 150 mg/kg Zoletil + 20 mg/kg xylazine. Both hippocampi were dissected out and fixed overnight in a PBS solution containing 4% PFA. The hippocampi were rendered transparent in scale 0 for 2 days at 37°C, and then transferred to scale 4 for 1 day at 4°C (Hama et al., 2015). The whole-mount hippocampus was imaged in 3D using a Zeiss LSM700 confocal microscope system (Zeiss, Germany). Imaris9.7 (Oxford Instruments, Switzerland) was used to identify TdTomato-positive neural progenitor cells. The clonal clusters were defined as the TdTomato-positive cells within 100-μm radius of the clone center, as illustrated in Figure 7—figure supplement 1 (Singh et al., 2015).

Multinomial logistic regression classification of cell types

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To classify cells and make associations between cell type and resting membrane potentials, input resistance and membrane capacitance, we applied the multinomial logistic regression model as follows:

P(C=c|X=x)P(C=0|X=x)=exp(βc,0+x1βc,1+x2βc,2+x3βc,3),c=1,2,

where C = 0, 1, 2 represents type 1, 2a, and 2b cells, respectively, and X = (X1,X2,X3) represents the centralized and standardized (logCm,logRm,Vm). By using a standard maximum likelihood estimation, the estimated coefficients are

(β1,0,β1,1,β1,2,β1,3,β2,0,β2,1,β2,2,β2,3)=(0.343,1.067,1.317,1.681,3.074,2.746,0.782,1.359)

for wild-type cells and

(β1,0,β1,1,β1,2,β1,3,β2,0,β2,1,β2,2,β2,3)=(0.567,1.373,0.051,0.302,5.353,6.935,1.626,5.549)

for Kv1.1KO cells.

Each cell was then assigned to the class with the highest probability P(C=c|X=x),c=0,1,2. Based on the estimated coefficients, it appeared that smaller values of Cm and larger values of Vm were associated with a higher probability of being type 2b neural progenitor cells than being type 1 neural stem cells.

Statistical analyses

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For immunostaining experiments, cell counts were performed on two to three images per mouse, and n-values indicate numbers of different mice, except for the assessment of clonal analysis, where n-values correspond to numbers of different clonal pools from four to six mice per genotype. For electrophysiological experiments, n-values correspond to numbers of different cells from each individual brain slice. Statistical analyses were performed with Prism software (Graphpad, USA) or R Project for Statistical Computing (The R Foundation, USA). Two-way ANOVA with Sidak's multiple comparisons post-hoc test, one-way ANOVA with Tukey's test, Mann-Whitney U-test, or Student's t-test for pair-wise comparisons were used as appropriate. p<0.05 was considered statistically significant.

Data availability

Most of our results are presented as scatterplots with the intention to show the distribution of our raw data. The variables for the multinomial logistic regression model (fig 5) can be found in the methods section.

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    Constitutively Active TrkB Kinase Signalling Reduces Actin Filopodia Dynamics and Cell Migration
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Decision letter

  1. Kenton J Swartz
    Senior Editor; National Institute of Neurological Disorders and Stroke, National Institutes of Health, United States
  2. Moses V Chao
    Reviewing Editor; New York University Langone Medical Center, United States
  3. Robert Blum
    Reviewer; University Hospital Würzburg, Germany
  4. Juan P Zanin
    Reviewer; Rutgers University, United States

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Acceptance summary:

This manuscript investigates the mechanism by which Kv1.1 potassium channels regulate postnatal neurogenesis. This is an important topic since the physiological and molecular mechanisms that regulate the decision of neurogenesis versus differentiation are not well understood. In this study, a loss of Kv1.1 channels increased proliferation of progenitor cells, which is attributed to a depolarization of the membrane potential and signaling through the BDNF/TrkB receptor system.

Decision letter after peer review:

Thank you for submitting your article "Kv1.1 channels regulate early postnatal neurogenesis in mouse hippocampus via the BDNF-TrkB pathway" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Kenton Swartz as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Robert Blum (Reviewer #1); Juan P. Zanin (Reviewer #3).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

As the editors have judged that your manuscript is of interest, but as described below that additional experiments are required before it is published, we would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). First, because many researchers have temporarily lost access to the labs, we will give authors as much time as they need to submit revised manuscripts. We are also offering, if you choose, to post the manuscript to bioRxiv (if it is not already there) along with this decision letter and a formal designation that the manuscript is "in revision at eLife". Please let us know if you would like to pursue this option. (If your work is more suitable for medRxiv, you will need to post the preprint yourself, as the mechanisms for us to do so are still in development.)

Summary:

This manuscript addresses the mechanism through which Kv1.1 potassium channels regulate postnatal neurogenesis in the SGZ of the dentate gyrus. This is a significant topic because the physiological and molecular mechanisms regulating neurogenesis vs. differentiation are not well understood. Specifically, this paper investigates a presumed cell-autonomous increase in early postnatal neurogenesis in mice that lack Kv1.1. Deletion of the potassium channel shifts the resting membrane potential to a more depolarized state. There is evidence presented that loss of Kv1.1 increased proliferation of type 2b progenitor cells, and this increased proliferation is attributed to a depolarization of the membrane potential, leading to cell-autonomous BDNF/TrkB-mediated signaling.

Overall, this is a potentially exciting set of results but the main conclusions in the paper require the support of additional data, as detailed below.

Essential revisions:

The role of BDNF-TrkB signaling is not convincingly established. More evidence is needed to show BDNF-TrkB signaling is responsible for the described main effect (more cells in Kv1.1KO, an effect that was already described in 2012). The mechanism, namely that Kv1.1 KO increases excitability in Type 2b cells and causes TrkB activation to speed up cell division is plausible, but not shown. However, it would be possible to produce such data. It is essential that the link between Kv1.1-dependent depolarization and BDNF-TrkB induced proliferation be better supported.

Figure 6 attempted to provide evidence that BDNF/TrkB signaling is required for increased proliferation of Type 2b cells. However no support is provided of the selectivity of GNF5837. At best, it is stated to be a Trk inhibitor, not selective for TrkB. There is also no rationale or explanation of the use of Ki67 as a marker. For the experiments using TrkB deletion, the difference between WT and KO in the heterozygous deletion is not convincing because it appears to be accounted for by a few outliers, and there is no discussion of why this difference is not seen with homozygous TrkB deletion.

Experimental concerns

1. Figure 1E: It is not clear what the authors measured and how they did it. The y-axis tells us something about distance from SGZ in percent. The interpretation in direction of increased proliferation is not unlikely, especially in context of figure 7. However, S-phase shortening ihas been done at postnatal day 10, a time point when BDNF expression is rather low and under developmental control. The data are not linked and therefore not fully conclusive at this point of investigation.

2. Figure 2: In Figure 2, we expect to see that Kv1.1 is expressed in the dentate gyrus and is present in Fezf2-positve cells. The images are not easy to interpret. Overview images are missing. Where are these in situ dots? Which controls were used and how did the controls look like? I suppose that these are the progenitors close to the SVZ. Later in their study, Kv1.1 becomes functionally important in type2b cells or MADM-labelled cells within the DGin Fezf2-GFP positive cells. This image does not clarify whether Kv1.1 is also expressed in these cells, albeit it is very likely. Furthermore, immunolabeling of Kv1.1 minus mice (IHC) is missing. IHC, using this protocol, should be able to check immunoreactivity in the type2b cell type. This is important, as the authors provide evidence for changes in electrophysiology in type2b cells, but not the other cells that also express Kv1.1.

3. For Figure 2D-G, in order to support the conclusion that there are functional Kv1.1 channels in these progenitor cells, it is essential to present the raw un-subtracted current traces before and after Dtx-K application.

4. Figure 3C shows that there is a higher proportion of type 2b cells compared to other subtypes in the Kv1.1 knockout. This is interpreted as increased cell proliferation in the absence of Kv1.1. However, since Type 2A cells differentiate to Type 2b, a higher proportion of Type 2b cells could instead be accounted for by enhanced differentiation. This issue is not addressed.

5. Figure 3D shows that in Type 2b cells specifically, KV1.1 KO cells had a more depolarized RMP than WT. It is not clear if a sufficient number of cells was recorded for each group for this critical experiment, the figure legend reports a wide range of n=5 to 28 cells per group. The data in 3D are rather important, but are not well explained. Data should be presented as single data points. As the 2b cell type is in the focus of the analysis, a table with the cell type prediction data would help. The main effect is type 2b WT versus Kv1.1 KO, but a direct comparison of the data is missing. The authors should better explain why they used this statistical test (hypothesis?) and why they did the statistical comparison between the different groups.

6. It has not been shown whether the systemically applied Trk inhibitor affects Trk phosphorylation in the hippocampus, meaning across the blood brain barrier, in these experiments.

7. Clonal analysis in Figure 6A-C affects Fezf2-GFP, but the criteria for clonal analysis is not well described. By going through the methods I realized that this is the 3D analysis of clones using Td Tomato. Image data of this analysis should be presented and the way of analysis must be clear. As it is not easy to obtain unbiased analysis of clone sizes with such an approach, it is important to show how it has been done and how the images look like.

8. The most critical point is that knocking out TrkB from adult born neurons is sufficient to interfere with neurogenesis (e.g. Bergami et al. PNAS 2008) and this effect was not be connected to Kv1.1. So the links between BDNF, TrkB, and more division at early stages are not causally connected. The overall idea is that Type2b cells that lack Kv1.1 are briefly depolarized, that this causes local BDNF release and a stimulation of cell division. However, it has not been shown that these cells, or close neighbors express more BDNF, that this stimulates TrkB and that this specific cell type causes the increase in adult born neuron numbers. Furthermore, it may be that the increase in the RMP does not lead to a higher activity of the neuron and activity-dependent gene expression of BDNF, because an increase in this parameter may induce a depolarization block; unlikely, but not ruled out and a relevant problem in excitability research.

https://doi.org/10.7554/eLife.58779.sa1

Author response

Essential revisions:

The role of BDNF-TrkB signaling is not convincingly established. More evidence is needed to show BDNF-TrkB signaling is responsible for the described main effect (more cells in Kv1.1KO, an effect that was already described in 2012). The mechanism, namely that Kv1.1 KO increases excitability in Type 2b cells and causes TrkB activation to speed up cell division is plausible, but not shown. However, it would be possible to produce such data. It is essential that the link between Kv1.1-dependent depolarization and BDNF-TrkB induced proliferation be better supported.

To make the connection between Kv1.1KO and BDNF-TrkB signaling, we aimed to investigate whether the phospho-TrkB levels were elevated in Kv1.1KO type 2b cells. The first step of activation of TrkB by BDNF is the auto-phosphorylation of TrkB receptor at Tyr816, and therefore, we expected to detect phospho-TrkB signals in cells with BDNF-TrkB activation. As expected, we did observe elevated phospho-TrkB levels in the SGZ in Kv1.1KO mice (Figure 6 and Figure 6—figure supplement 1). Moreover, we noticed that the phospho-TrkB levels were much elevated in cells expressing Tbr2 or doublecortin but not Sox2, indicating that in Kv1.1KO mice, the BDNF-TrkB was preferentially activated in late-stage neural progenitor cells (Figure 6C). Both pharmacological inhibition and genetic deletion of Trk signaling prevented the increase of BDNF-TrkB activation in Kv1.1KO neural progenitor cells, as well as suppressing the over-production of neural progenitor cells and reducing the clone size (Figure7). These new results support the association of the hyperplastic effect of Kv1.1KO with the overactive BDNF-TrkB signaling primarily in late-stage neural progenitor cells that are depolarized in the absence of Kv1.1.

Figure 6 attempted to provide evidence that BDNF/TrkB signaling is required for increased proliferation of Type 2b cells. However no support is provided of the selectivity of GNF5837. At best, it is stated to be a Trk inhibitor, not selective for TrkB. There is also no rationale or explanation of the use of Ki67 as a marker. For the experiments using TrkB deletion, the difference between WT and KO in the heterozygous deletion is not convincing because it appears to be accounted for by a few outliers, and there is no discussion of why this difference is not seen with homozygous TrkB deletion.

We agree with the reviewer about the lack of subtype specificity of GNF5837, as this compound inhibits TrkA TrkB and TrkC all at around 10 nM. For pharmacological inhibition, GNF5837 has been shown to be capable of crossing the blood-brain barrier (Albaugh et al., 2012). Previous studies have shown that deleting either TrkB or TrkC had little effect on neuronal death in the dentate gyrus since both TrkB and TrkC are active in DG, and one of these two Trk receptors could compensate for the loss of the other. Only double deletion of TrkB and TrkC could have a profound effect on cell survival in the dentate gyrus (Minichiello and Klein, 1996). Interestingly, we observed that GNF5837 injection modestly reduced the Fezf2-GFP+ progenitor cell number (Kv1.1 WT vs. Kv1.1 WT/GNF5837, Figure 7C), indicating a pan-Trk receptor suppression in DG. However, the genetic deletion of TrkB had no additional effect on the clone size (Figure 7 E and F). We hypothesize that the TrkC may compensate for the loss of TrkB in the neural progenitor cells and prevent further cell death. On the other hand, a gain-of-function of the Trk receptors could have a profound effect on cell function, such as enhanced cell proliferation. This gain-of-function can be specifically nullified by genetic deletion without affecting the basal level of Trk receptor function, which could be maintained by TrkC receptor.

The distribution of clone size is skewed as shown in a previous study (see Figure 1C, D from Singh et al., 2015). Although we only used a single TdTomato marker to label the clones, combined with a low-dose tamoxifen injection, we obtained comparable clone size distribution (Figure 7E and F).

If the larger clone in Kcna1-/-;Ntrk2Flox/+ was caused by the outliers, we would expect the distribution of the clone size to otherwise be comparable. However, our Kolmogorov-Smirnov cumulative plots of the clone size showed that the curve for Kcna1-/-;Ntrk2Flox/+ deviated from those for the other 3 genotypes (Figure 7F), which is consistent with the notion that the overall distribution of the clone size in Kcna1-/-;Ntrk2Flox/+ was right-shifted rather than affected by the outliers. This statistical analysis supports our hypothesis that Kv1.1KO mice tend to have larger clones.

Experimental concerns

1. Figure 1E: It is not clear what the authors measured and how they did it. The y-axis tells us something about distance from SGZ in percent. The interpretation in direction of increased proliferation is not unlikely, especially in context of figure 7. However, S-phase shortening ihas been done at postnatal day 10, a time point when BDNF expression is rather low and under developmental control. The data are not linked and therefore not fully conclusive at this point of investigation.

For Figure 1E, we measured the relative position of the MADM-labeled neurons in the dentate gyrus. We first drew a vertical line (perpendicular to the SGZ) from the MADM-labeled neuronal soma so that it spans the distance from the SGZ to the border between the granule cell layer and molecular layer. For quantification, We designated the SGZ as the zero reference point (0%) and the granule layer/molecular layer boundary as the maximal position (100%), the farthest location the granule neurons can migrate into.

As stated in the first section in Results, "developmentally-born neurons generated during late embryogenesis and early postnatal stages typically survive for more than two months before the onset of cell death; generation and maturation of these neurons take about one month, with those generated early in life located farther from the SGZ (Cahill et al., 2017; Dayer et al., 2003; Kerloch et al., 2019; Toni and Schinder, 2015)." We found that the majority of green Kv1.1KO neurons were positioned farther away from SGZ. This result further supports the idea that the increase of Kv1.1KO neurons detected in 3 months old but not one-month-old MADM mice were born during the postnatal period. We have revised the text to clarify this point.

Although at P10, the BDNF level is low and under developmental control, the expression level can still be regulated by intrinsic as well as external factors, such as early postnatal environmental enrichment (Liu et al., 2012). Moreover, the Kv1.1 affects the membrane potentials that could directly regulate the BDNF releasing probability without affecting its mRNA expression, so the shortening of the S phase can still be observed at P10. Another reason we chose P10 as the age to investigate the S phase duration is we would like to avoid seizure attacks starting a week later, which could confound the study.

Nevertheless, to keep our manuscript concise and focused on the main point, we decided to remove Figure 8 and focus more on the BDNF/TrkB and electrophysiology.

2. Figure 2: In Figure 2, we expect to see that Kv1.1 is expressed in the dentate gyrus and is present in Fezf2-positve cells. The images are not easy to interpret. Overview images are missing. Where are these in situ dots? Which controls were used and how did the controls look like? I suppose that these are the progenitors close to the SVZ. Later in their study, Kv1.1 becomes functionally important in type2b cells or MADM-labelled cells within the DGin Fezf2-GFP positive cells. This image does not clarify whether Kv1.1 is also expressed in these cells, albeit it is very likely. Furthermore, immunolabeling of Kv1.1 minus mice (IHC) is missing. IHC, using this protocol, should be able to check immunoreactivity in the type2b cell type. This is important, as the authors provide evidence for changes in electrophysiology in type2b cells, but not the other cells that also express Kv1.1.

We have added new figures with overview and higher magnification images (Figure 2 A and B). We used the RNAscope technique for in situ detection of Kcna1 mRNAs. The RNAscope technique is sensitive enough to detect a single mRNA molecule, and each dot represents one single mRNA molecule. Given the minuscule size of the mRNA dots, we have to show high-magnification images of each sample. The SGZ area is labeled with GFP granules (Fezf2-GFP), and numerous red Kcna1 mRNA signals colocalize in the same area, indicating that the Kv1.1 is expressed in the Fezf2-GFP positive neural progenitor cells. We also performed the same experiments using Fezf2-GFP;Kcna1-/- as the negative control (Figure 2B). The green GFP granules are still presented in the SGZ area; however, the red Kcna1 mRNA signals are largely absent, thus providing evidence for the specificity of the Kcna1 mRNA signal in Figure 2A.

We also performed IHC to detect the expression pattern of the Kv1.1 proteins. As shown in Figure 2C, Kv1.1 protein is expressed in SGZ and the granule layer of DG in control. Specifically, Kv1.1 immunoreactivity resides in doublecortin positive late-stage neural progenitor cells (white arrows), which largely overlap with type 2b cells. We found a very weak or undetectable Kv1.1 signal in Sox 2 positive cells. As expected, we also observed strong cytosolic Kv1.1 expression in DG neurons, which could be PV positive interneurons. This Kv1.1 protein signal is completely absent in Kv1.1KO mice. Interestingly, we noticed that the Sox2 signals were also detected in 2 out of 3 presumed inhibitory interneurons (yellow arrows). This phenomenon has been reported previously, indicating that Sox2 also can be detected occasionally in mature neurons (Kang and Hébert, 2012).

3. For Figure 2D-G, in order to support the conclusion that there are functional Kv1.1 channels in these progenitor cells, it is essential to present the raw un-subtracted current traces before and after Dtx-K application.

We have added raw data (Figure 2D to J) to show the un-subtracted current traces before and after DTX-K application. As shown in Figure 2 D to F, DTX-K sensitive currents can be seen in wild-type but not Kv1.1KO progenitor cells.

4. Figure 3C shows that there is a higher proportion of type 2b cells compared to other subtypes in the Kv1.1 knockout. This is interpreted as increased cell proliferation in the absence of Kv1.1. However, since Type 2A cells differentiate to Type 2b, a higher proportion of Type 2b cells could instead be accounted for by enhanced differentiation. This issue is not addressed.

If the differentiation from 2a to 2b is enhanced, we would expect to see relatively fewer 2a cells in Kv1.1KO mice. However, during our patch-clamp recording of the Fezf2-GFP positive cells, the chances of hitting type 2a and type 2b were comparable in both wild-type and Kv1.1KO mice (n for type 2a and 2b cells were 14 and 9 for wild-type and 14 and 10 for Kv1.1KO; p>0.05, Chi-square test). If the type 2a to 2b differentiation is enhanced in Kv1.1KO mice, it ought to reduce the probability of finding record type 2a cells for recording. Nevertheless, the possibility for enhanced differentiation cannot be completely ruled out.

5. Figure 3D shows that in Type 2b cells specifically, KV1.1 KO cells had a more depolarized RMP than WT. It is not clear if a sufficient number of cells was recorded for each group for this critical experiment, the figure legend reports a wide range of n=5 to 28 cells per group. The data in 3D are rather important, but are not well explained. Data should be presented as single data points. As the 2b cell type is in the focus of the analysis, a table with the cell type prediction data would help. The main effect is type 2b WT versus Kv1.1 KO, but a direct comparison of the data is missing. The authors should better explain why they used this statistical test (hypothesis?) and why they did the statistical comparison between the different groups.

We have added more cells and listed the n number for each group of cell type (n = 14, 14, 9, 10, 9 (WT) and 28, 14, 10, 11, 8) (Kv1.1KO) for type1 cells (Fezf2-GFP+/Sox2+), type 2a cells (Fezf2-GFP+/Sox2+/Tbr2+), type 2b cells (Fezf2-GFP+/Tbr2+), immature neurons (POMC-GFP+) and label-free mature neurons, respectively; (2-way ANOVA followed by Sidak's multiple comparisons test, p = 0.02, for type 2b cells), so sufficient sample sizes were used to perform the comparison for each cell type. We used scatter plots instead of single data points so the data distribution and skewness can be appreciated. The single data points of Figure 4G can also be seen in Figure 5 B and C.

The 3D plots (Figure 5 B and C) show the non-linearity among the 3 biophysical parameters for cell type prediction. Nevertheless, we still can observe a continuous transition from Type 1 cells through type 2a cells towards type 2b cells. The labeled cells are dispersed among the cells with unknown cell identity, and therefore, so we decided to use the Multinomial logistic regression. This simplified machine-learning method can handle datasets with a relatively smaller sample size. The cell type was determined based on the highest probability, and despite a smaller training dataset, we still obtained a reasonable accuracy rate (~80%), similar to the more complex AI-based machine learning method that handles a much larger dataset.

We used 2 separate training datasets for classification. This would give us more stringent classification criteria, as Kv1.1KO type 2b cells were more depolarized (Figure 4G). Those cells in the Kv1.1KO group must reach more depolarized membrane potential to be qualified as type 2b cells. Despite that, we still clearly observed that more Kv1.1KO cells had more depolarized resting membrane potentials, and the majority of these cells also had smaller capacitance and higher input resistance, which allowed them to be classified as type 2b cells in the Kv1.1KO group that entails more stringent criteria.

6. It has not been shown whether the systemically applied Trk inhibitor affects Trk phosphorylation in the hippocampus, meaning across the blood brain barrier, in these experiments.

We found the intraperitoneal injection of GNF5837 completely suppressed the auto-phosphorylation of TrkB (Figure 6—figure supplement 2), suggesting our regimen was sufficient for GNF5837 to cross the blood-brain barrier and inhibit the TrkB signaling. Moreover, this result also demonstrated that TrkB was activated locally in the SGZ.

7. Clonal analysis in Figure 6A-C affects Fezf2-GFP, but the criteria for clonal analysis is not well described. By going through the methods I realized that this is the 3D analysis of clones using Td Tomato. Image data of this analysis should be presented and the way of analysis must be clear. As it is not easy to obtain unbiased analysis of clone sizes with such an approach, it is important to show how it has been done and how the images look like.

We defined a single clone by including all the TdTomato-positive cells contained within a 100-μm radius of the clone center. We added Figure 7—figure supplement 1 to illustrate how the clones were identified and quantified. During this revision, we tried to generated Gli1-creER;Kcna1;MADM6 mice so the clones can be better identified by 3 colors instead of a single color and the resolution can be increased as well. Unfortunately, we have tried 3 different tamoxifen regimens and analyzed more than 20 mice, only one single clone was found. We suspect the rare inter-chromosomal recombination of MADM plus the low-efficiency of tamoxifen-inducible Gli1-cre rendered this inducible MADM not feasible for clonal analysis.

8. The most critical point is that knocking out TrkB from adult born neurons is sufficient to interfere with neurogenesis (e.g. Bergami et al. PNAS 2008) and this effect was not be connected to Kv1.1. So the links between BDNF, TrkB, and more division at early stages are not causally connected. The overall idea is that Type2b cells that lack Kv1.1 are briefly depolarized, that this causes local BDNF release and a stimulation of cell division. However, it has not been shown that these cells, or close neighbors express more BDNF, that this stimulates TrkB and that this specific cell type causes the increase in adult born neuron numbers. Furthermore, it may be that the increase in the RMP does not lead to a higher activity of the neuron and activity-dependent gene expression of BDNF, because an increase in this parameter may induce a depolarization block; unlikely, but not ruled out and a relevant problem in excitability research.

As described by the reviewer, BDNF has a wide range of expression patterns in the dentate gyrus, including both mature neurons and the neural progenitor cells in SGZ (Minichiello and Klein, 1996). Moreover, previous studies have also demonstrated an increase of BDNF mRNA expression in SGZ in megencephaly mice (Lavebratt et al., 2006). For these reasons, attempting to identify the origin of BDNF that activates the TrkB signaling in SGZ has become a daunting task. BDNF acts as a short-range neuromodulator, and just like other neurotransmitters and neuromodulators, the release of BDNF is calcium-dependent, which mostly requires membrane depolarization that activates calcium channels (Mandl et al., 2002). Our electrophysiological recording results show that only Type 2b cells were more depolarized in Kv1.1KO mice. Even though we cannot exclude the possibility that neurons could also serve as another source of BDNF, our clonal analysis and MADM results do not support this idea. For a more definitive assessment, we will need more sophisticated and sensitive methods to detect the BDNF release from different cell types, but these tools are still under development (Inutsuka et al., 2021).

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https://doi.org/10.7554/eLife.58779.sa2

Article and author information

Author details

  1. Shu-Min Chou

    Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
    Present address
    Program in Neuroscience and Behavioral Disorders, Duke-National, University of Singapore Medical School, Singapore, Singapore
    Contribution
    Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing - review and editing
    Contributed equally with
    Ke-Xin Li and Ming-Yueh Huang
    Competing interests
    No competing interests declared
  2. Ke-Xin Li

    Howard Hughes Medical Institute, Departments of Physiology, Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - review and editing
    Contributed equally with
    Shu-Min Chou and Ming-Yueh Huang
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3879-294X
  3. Ming-Yueh Huang

    Institute of Statistics, Academia Sinica, Taipei, Taiwan
    Contribution
    Data curation, Software, Formal analysis, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing
    Contributed equally with
    Shu-Min Chou and Ke-Xin Li
    Competing interests
    No competing interests declared
  4. Chao Chen

    Howard Hughes Medical Institute, Departments of Physiology, Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
    Contribution
    Data curation, Formal analysis, Visualization, Writing - review and editing
    Competing interests
    No competing interests declared
  5. Yuan-Hung Lin King

    1. Howard Hughes Medical Institute, Departments of Physiology, Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
    2. Neuroscience Graduate Program, University of California, San Francisco, San Francisco, United States
    Contribution
    Data curation, Formal analysis
    Competing interests
    No competing interests declared
  6. Grant Guangnan Li

    Nkarta Therapeutics Inc, South San Francisco, United States
    Contribution
    Resources, Investigation, Methodology
    Competing interests
    Grant Guangnan Li is affiliated with Nkarta Therapeutics Inc, The author has no financial interests to declare."
  7. Wei Zhou

    Department of Anesthesia and Perioperative Care, University of California, San Francisco, San Francisco, United States
    Contribution
    Data curation, Formal analysis
    Competing interests
    No competing interests declared
  8. Chin Fen Teo

    Howard Hughes Medical Institute, Departments of Physiology, Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
    Contribution
    Data curation
    Competing interests
    No competing interests declared
  9. Yuh Nung Jan

    Howard Hughes Medical Institute, Departments of Physiology, Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
    Contribution
    Resources, Supervision, Funding acquisition, Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1367-6299
  10. Lily Yeh Jan

    Howard Hughes Medical Institute, Departments of Physiology, Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
    Contribution
    Resources, Supervision, Funding acquisition, Investigation, Methodology, Project administration, Writing - review and editing
    For correspondence
    Lily.Jan@ucsf.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3938-8498
  11. Shi-Bing Yang

    1. Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
    2. Neuroscience Program of Academia Sinica, Academia Sinica, Taipei, Taiwan
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing
    For correspondence
    sbyang@ibms.sinica.edu.tw
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8061-3963

Funding

Ministry of Science and Technology, Taiwan (106-2320-B-001-013)

  • Shi-Bing Yang

Ministry of Science and Technology, Taiwan (107-2320-B-001-026-MY3)

  • Shi-Bing Yang

NIH Blueprint for Neuroscience Research (R01MH065334)

  • Lily Yeh Jan

Howard Hughes Medical Institute

  • Yuh Nung Jan
  • Lily Yeh Jan

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We thank Drs. Su Guo (University of California, San Francisco), Bruce Tempel (University of Washington), Liqun Luo (Stanford University), and Hui Zong (University of Oregon) for providing transgenic mice. We thank the outstanding technical supports provided by the Neuro-imaging core facility of the Neuroscience Program, Microscopy facility and Electrophysiology facility of the Institute of Biomedical Sciences, Academia Sinica. This work was supported by the Institute of Biomedical Sciences at Academia Sinica and the Ministry of Science and Technology (106–2320-B-001–013 and 107–2320-B-001–026-MY3 to SBY) and by the National Institute of Health (R01MH065334 to LYJ). YNJ and LYJ are Howard Hughes Medical Institute investigators.

Ethics

Animal experimentation: This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health, and used protocol approved by the Institutional Animal Care and Use Committee of Academia Sinica (protocol#:15-01-813) and the University of California, San Francisco. Mice (3-5 per cage) housed in the animal facility were fed with regular chow diet and subjected to a standard 12-h light/12-h dark cycle. At least 3 animals were used for every single experiment. Mice were first anesthetized with isoflurane followed by decapitation for electrophysiological recordings and immunostaining.

Senior Editor

  1. Kenton J Swartz, National Institute of Neurological Disorders and Stroke, National Institutes of Health, United States

Reviewing Editor

  1. Moses V Chao, New York University Langone Medical Center, United States

Reviewers

  1. Robert Blum, University Hospital Würzburg, Germany
  2. Juan P Zanin, Rutgers University, United States

Publication history

  1. Received: May 11, 2020
  2. Accepted: May 20, 2021
  3. Accepted Manuscript published: May 21, 2021 (version 1)
  4. Accepted Manuscript updated: May 26, 2021 (version 2)
  5. Version of Record published: June 16, 2021 (version 3)

Copyright

© 2021, Chou et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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