KIF2C regulates synaptic plasticity and cognition in mice through dynamic microtubule depolymerization

  1. Rui Zheng
  2. Yonglan Du
  3. Xintai Wang
  4. Tailin Liao
  5. Zhe Zhang
  6. Na Wang
  7. Xiumao Li
  8. Ying Shen
  9. Lei Shi
  10. Jianhong Luo  Is a corresponding author
  11. Jun Xia  Is a corresponding author
  12. Ziyi Wang  Is a corresponding author
  13. Junyu Xu  Is a corresponding author
  1. Department of Neurobiology and Department of Rehabilitation of the Children’s Hospital, Zhejiang University School of Medicine, China
  2. NHC and CAMS Key Laboratory of Medical Neurobiology, Ministry of Education Frontier Science Center for Brain Research and Brain Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, China
  3. Department of Orthopedic Surgery, the Second Affiliated Hospital, Zhejiang University School of Medicine, China
  4. Department of Physiology and Department of Neurology of First Affiliated Hospital, Zhejiang University School of Medicine, China
  5. JNU-HKUST Joint Laboratory for Neuroscience and Innovative Drug Research, Jinan University, China
  6. Division of Life Science and The Brain and Intelligence Research Institute, The Hong Kong University of Science and Technology, China
  7. Innovative Institute of Basic Medical Sciences of Zhejiang University (Yuhang), China

Abstract

Dynamic microtubules play a critical role in cell structure and function. In nervous system, microtubules are the major route for cargo protein trafficking and they specially extend into and out of synapses to regulate synaptic development and plasticity. However, the detailed depolymerization mechanism that regulates dynamic microtubules in synapses and dendrites is still unclear. In this study, we find that KIF2C, a dynamic microtubule depolymerization protein without known function in the nervous system, plays a pivotal role in the structural and functional plasticity of synapses and regulates cognitive function in mice. Through its microtubule depolymerization capability, KIF2C regulates microtubule dynamics in dendrites, and regulates microtubule invasion of spines in neurons in a neuronal activity-dependent manner. Using RNAi knockdown and conditional knockout approaches, we showed that KIF2C regulates spine morphology and synaptic membrane expression of AMPA receptors. Moreover, KIF2C deficiency leads to impaired excitatory transmission, long-term potentiation, and altered cognitive behaviors in mice. Collectively, our study explores a novel function of KIF2C in the nervous system and provides an important regulatory mechanism on how activity-dependent microtubule dynamic regulates synaptic plasticity and cognition behaviors.

Editor's evaluation

In this manuscript, the authors report a set of exciting and novel data suggesting a critical role of the microtubule depolymerizing kinesin-13 KIF2C/MCAK in glutamate receptor trafficking, synaptic plasticity and behaviours related to learning and memory. The authors use multiple experimental approaches, ranging from electron microscopy to mouse behavioral analysis to support the conclusions, which are convincing and provide novel insights into the in vivo functions of KIF2C in the regulation of excitatory synaptic structure and function and cognitive behaviors.

https://doi.org/10.7554/eLife.72483.sa0

Introduction

Microtubules (MTs) are eukaryotic cytoskeletons that play an important role in cell function. In the central nervous system, MTs serve as a structural basis for trafficking material throughout the neuron and are the primary regulators of neuronal differentiation (Dent and Baas, 2014). The MTs dynamic instability, that is the growing or shrinking of MT plus end, has been detected in both shaft and dendritic protrusions (Mitchison and Kirschner, 1984) and is involved in spine formation and synaptic function (Hu et al., 2008; Gu et al., 2008; Merriam et al., 2011; Tada and Sheng, 2006). Inhibition of MT polymerization results in deficits in long-term potentiation (LTP) and negatively affects memory formation or retention (Shumyatsky et al., 2005; Jaworski et al., 2009). The abnormal MTs dynamics is associated with several neurodegenerative and psychiatric diseases, including Alzheimer’s disease, Parkinson’s disease, schizophrenia, and depression (Brunden et al., 2014). During neuronal activities, MTs can be regulated to extend from the dendritic shaft into spines and affect synaptic structure and function (3-8), which could be an important event for synaptic plasticity. However, regulatory mechanism underlying MT dynamics in or out from synapse upon neuronal activity is still unclear, nor its role in learning and memory.

The polymerization dynamics of MTs are essential for their biological functions and can be regulated by many MT-associated proteins (MAPs) (Akhmanova and Steinmetz, 2015; Bowne-Anderson et al., 2015). The kinesin-13 family of kinesin superfamily proteins (KIFs) has a distinct function in depolymerizing MTs (Howard and Hyman, 2007), and therefore is involved in many MT-dependent events (Kline-Smith et al., 2004; Homma et al., 2003). KIF2C, also called mitotic centromere-associated kinesin (MCAK), is the best-characterized family member and is localized to the spindle poles, spindle midzone, and kinetochores in dividing cells. KIF2C utilizes MT depolymerase activity to regulate spindle formation and correct inappropriate MT attachments at kinetochores (Gorbsky, 2004; Helenius et al., 2006; Knowlton et al., 2006). KIF2C uses ATP hydrolysis for MT depolymerization from both ends and directly interacts with EBs to enhance its destabilizing ability (Wordeman, 2005; Walczak, 2003; Wang et al., 2015; Moore et al., 2005; Lee et al., 2008). Particularly, KIF2C is associated with Alzheimer’s disease and suicidality psychiatric disorders. In vitro study showed that Oligomeric amyloid-β (Aβ) directly inhibits the MT-dependent ATPase activity of KIF2C and leads to abnormal mitotic spindles, which may cause chromosome mis-segregation and increased aneuploid neurons and thereby contributes to the development of Alzheimer’s disease (Borysov et al., 2011). Clinical evidence shows that KIF2C is significantly decreased in suicidal ideation cohort and could be utilized as a reference for predicting suicidality (Niculescu et al., 2015). However, the in vivo physiological function of KIF2C in the CNS remains to be elucidated.

In this study, we have found that KIF2C in the CNS is expressed in a brain-wide and synaptic localized pattern, which could be regulated by neuronal activity. Using a nervous-system-specific KIF2C conditional knockout (cKO) mouse, we further confirmed its pivotal role in spine morphology, synaptic transmission, and synaptic plasticity. By re-expression of KIF2C wild-type (WT) and MT depolymerization-defective mutation, we have found that KIF2C regulates synaptic plasticity by mediating MT depolymerization and affecting MT synaptic invasion. Furthermore, KIF2C cKO mice exhibit deficiencies in multiple cognition-associated tasks, which could be rescued by re-expression of KIF2C(WT) but not the MT depolymerization-defective mutant. Overall, our study explores a novel function of KIF2C in neurons and synaptic plasticity, and reveals how MT dynamics in synapses upon neuronal activity contributes to cognition.

Results

KIF2C is highly expressed in the brain and at the synapse

Previous studies have showed that KIF2C plays an important role during cell division in mitotic cells (Andrews et al., 2004; Lan et al., 2004; Sanhaji et al., 2014); however, it is not clear whether KIF2C is also present in the nervous system. Western blot analyses showed that KIF2C was expressed in multiple regions of the brain (Figure 1A), and shows sustained high expression in the hippocampus throughout the postnatal stages (Figure 1B). To identify KIF2C abundance in neurons, western blot analyses were performed on whole-cell extracts of cultured hippocampal neurons (Figure 1C). The results showed that KIF2C was expressed in a development-related pattern in cultured neurons: detectable at day in vitro 3 (DIV 3) and significantly increased at DIV 10. Moreover, the subcellular fractionation analysis showed an enrichment of KIF2C in the postsynaptic density (PSD) fraction (Figure 1D). Immunofluorescent staining of cultured neurons revealed KIF2C expression as granular puncta of different sizes along dendrites overlapping with the postsynaptic marker PSD-95 and presynaptic protein Bassoon (Figure 1E). These results show that KIF2C is abundantly expressed in CNS neurons and is enriched at postsynaptic density, suggesting a possible function in synapses.

Expression of KIF2C in the central nervous system.

(A) Expression of KIF2C in different mouse brain regions by immunoblotting. (B) Expression of KIF2C and EB3 in mouse hippocampus at different day in vitro. (C) Developmental expression patterns of KIF2C and EB3 in cultured hippocampal neurons. (D) Subcellular distribution of KIF2C in mouse hippocampus. H, homogenate; S1, low-speed supernatant; P1, nuclei; S2, microsomal fraction; P2, synaptosomal fraction; S3, presynaptosomal fraction; P3, postsynaptic density and synapto, synaptophysin. (E) Representative images of hippocampal neurons double-labeled with antibodies against KIF2C, PSD-95 (postsynaptic marker) and Bassoon (presynaptic marker). Scale bar, 5 μm.

Figure 1—source data 1

Original files of blots with the relevant bands.

https://cdn.elifesciences.org/articles/72483/elife-72483-fig1-data1-v1.zip

KIF2C knockdown affects spine morphology, synaptic transmission and long-term potentiation in vitro and in vivo

To explore the function of KIF2C in synapses, KIF2C was knocked down in cultured hippocampal neurons using lentiviral-mediated KIF2C shRNA (shkif2c) (Figure 2A, Figure 2—figure supplement 1A) at DIV 7–10 and the spine morphology was examined at DIV 18–20. The results showed that KIF2C knockdown did not affect spine density (Figure 2B). Electrophysiological recordings also showed similar frequency and amplitude of miniature excitatory synaptic currents (mEPSCs) in control and knockdown neurons (Figure 2—figure supplement 1B, C), suggesting that acute knockdown of KIF2C in cultured neurons does not affect basal synaptic transmission. We then investigated whether KIF2C regulates spine morphology in an activity-dependent manner. The induction of LTP results in changes in spine structure (Fifková, 1985; Oertner and Matus, 2005; Vlachos et al., 2009; Fortin et al., 2010). To test whether KIF2C is involved in spine structural plasticity, we further conducted a glycine-induced chemical LTP (cLTP) assay to produce synaptic enhancements that mimic LTP (Lu et al., 2001) in KIF2C knockdown hippocampal neurons. Spine density in knockdown neurons was consistent with control after cLTP stimulation (Figure 2C and D). However, the spine head width significantly increased in control hippocampal neurons, whereas it was not affected in the KIF2C knockdown neurons after cLTP stimulation (Figure 2E), indicating that KIF2C is essential for spine structural plasticity. In addition, both subcellular fractionation and immunocytochemical results showed that KIF2C was not colocalizing as much with PSD-95 and expressed more in dendritic shafts after cLTP (Figure 2F–I), suggesting a translocation of KIF2C from synaptic protrusions into dendrites. Together, these data indicate that KIF2C is removed from postsynaptic sites by neuronal activity, which may contribute to synaptic plasticity.

Figure 2 with 1 supplement see all
KIF2C displays translocation after cLTP and is required for synaptic structure plasticity.

(A) Electrophoresis of kif2c and gapdh amplicons from individual control and shkif2c hippocampal neurons. Histograms show percentage changes of kif2c mRNA levels (% of control, **p < 0.01, n = 6, Student’s t-test). (B) Cultured hippocampal neurons were infected by control shRNA and shkif2c lentivirus at DIV 7–10, and captured at DIV 18–20. GFP was used to label neuron volume. Scale bar, 1 μm. Spine number per 1 μm (right), n = 20 neurons from three independent culture. Student’s t-test. (C–E) Cultured hippocampal neurons were infected by control shRNA and shkif2c lentivirus at DIV 7–10, and incubated with ECS or glycine (200 μM) for 10 min at DIV 18–20. Scale bar, 1 μm. Spine density (D) and spine head width (E) are calculated. Spine density, n = 17 neurons from three independent culture. Spine head width, n = 24 neurons from three independent culture. n.s., p > 0.05, *p < 0.05, ****p < 0.0001; One way-ANOVA for spine density and head width (post hoc comparison).(F) Subcellular fraction of KIF2C in cultured hippocampus neurons after 10 min of glycine treatment. N-cadherin (N-cad) was served as negative control. H, Homogenate; S2, microsomal fraction; P2, synaptosomal fraction and P3, postsynaptic density from ECS and cLTP treated neurons. (G) Quantification of KIF2C and β-tubulin accumulation with or without cLTP treatment in each fraction. *p < 0.05, **p < 0.01; Student’s t-test, n = 7 experimental repeats. (H) Representative images of co-localization of KIF2C (red), PSD-95 (green), and Microtubule associated protein 2 (MAP2) (blue). Scale bar, 1 μm. (I) The percentage of KIF2C puncta that were colocalized with PSD-95 puncta decreased after cLTP treatment. n = 20 neurons from three cultures. n.s., p > 0.05, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001; Student’s t-test.

Figure 2—source data 1

Values for kif2c mRNA levels; Values for spine density and spine head width before or after cLTP stimulation in control and shkif2c neurons; Values for KIF2C synaptic expression before or after cLTP stimulation.

https://cdn.elifesciences.org/articles/72483/elife-72483-fig2-data1-v1.xlsx
Figure 2—source data 2

Original files of gels and blots with the relevant bands.

https://cdn.elifesciences.org/articles/72483/elife-72483-fig2-data2-v1.zip

To further determine the effect of KIF2C on synaptic function, KIF2C was knocked down in hippocampal CA1 neurons in vivo and the electrophysiological properties in acute slices were measured. Mice were injected with either AAV-scramble shRNA (control) or AAV-KIF2C shRNA (shkif2c) in the CA1 region (Figure 2—figure supplement 1D), and mEPSCs were recorded. Compared to the control, KIF2C knockdown neurons had enhanced amplitude but similar frequency of mEPSCs (Figure 3A). This discrepancy between cultured neurons and brain slices may result from activity-dependent synaptic scaling in free-behaving mice after viral injection. KIF2C knockdown blocked cLTP-induced increased spine width (Figure 2E), so we wondered whether the increased mEPSCs amplitude after cLTP stimulation could also be blocked in shkif2c neurons. Hippocampal CA1 slices were incubated with ACSF or glycine (200 μM) for 10 min before mEPSCs recording. The results showed that mEPSCs amplitude was significantly increased in control hippocampal neurons, whereas it was not affected in the shkif2c neurons after cLTP stimulation (Figure 2—figure supplement 1E, F). These data indicate that KIF2C knockdown blocks the raise of mEPSCs amplitude induced by cLTP. Furthermore, we investigated whether KIF2C regulated presynaptic function retrogradely by comparing paired-pulse ratios (PPRs). KIF2C knockdown neurons exhibited comparable PPRs to the control, suggesting that KIF2C had a minimal effect on contacting presynaptic function (Figure 3B). In addition, the excitatory postsynaptic current ratio of N-methyl-D-aspartic acid receptor (NMDAR)/α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) was decreased in knockdown hippocampal slices (Figure 3C). The input-output relationship of NMDAR/AMPAR-mediated EPSCs showed that amplitude of NMDAR-mediated EPSCs under various stimulation intensities was comparable, while AMPAR-mediated EPSCs was increased in KIF2C knockdown neurons (Figure 3D–E), indicating a specific change in AMPAR-mediated synaptic currents. To test whether synaptic plasticity was affected in KIF2C knockdown neurons, we measured whole-cell LTP in CA1 pyramidal neurons by stimulating Schaffer collaterals. The magnitude of LTP was significantly attenuated in knockdown hippocampal slices (Figure 3F). These results suggest that KIF2C is necessary for synaptic plasticity in hippocampal neurons, and its insufficiency may affect the basal function of AMPARs in the hippocampus.

Knockdown KIF2C impairs synaptic transmission and plasticity.

(A) mEPSCs recorded from control and shkif2c CA1 pyramidal neurons. n = 10 per group, n.s., p > 0.05, **p < 0.01, Student’s t-test; For the cumulative probability curves, *p < 0.05, ****p < 0.0001, Kolmogorov-Smirnov test. (B) Paired-pulse stimuli evoked EPSCs with different interval. n = 9 neurons per group. The data were analyzed in separate t-tests at each stimulus intensity; n.s., p > 0.05. (C) AMPAR and NMDAR EPSCs in CA1 pyramidal neurons. Sample sweeps illustrating NMDAR-EPSCs recorded at +40 mV and AMPAR-EPSCs recorded at –70 mV (left). Histograms show ratio of NMDAR-EPSCs amplitude / AMPAR-EPSCs amplitude (right). n = 22 neurons per group; *p < 0.05, Student’s t-test. (D) Sample traces and input-output curve of NMDA receptor-mediated EPSCs of control and shkif2c neurons (n = 6, p > 0.05). The data were analyzed in separate t-tests at each stimulus intensity. (E) Sample traces and input-output curve of AMPA receptor-mediated EPSCs between control and shkif2c neurons (n = 6, *p < 0.05). The data were analyzed in separate t-tests at each stimulus intensity. (F) Example EPSCs before (baseline) and after (t = 40 min) 2× HFS stimulation in control and shkif2c CA1 pyramidal neurons. Time course of percentage changes of EPSCs amplitudes in control and shkif2c CA1 pyramidal neurons(left). Histogram shows EPSC amplitude of control and shkif2c neurons (35–40 min) (right). ***p < 0.001; Student’s t-test.

Figure 3—source data 1

Values for mEPSCs of control and shkif2c neurons.

Values for PPR ratio; Values for input-output curve of AMPAR and NMDAR mediated EPSCs between control and shkif2c neurons; Values for percentage changes of EPSCs amplitudes in control and shkif2c CA1 pyramidal neurons.

https://cdn.elifesciences.org/articles/72483/elife-72483-fig3-data1-v1.xlsx

KIF2C knockout affects spine morphology, synaptic transmission, and long-term potentiation in vivo

To further investigate the functions of KIF2C in vivo, we generated cKO mice using the CRISPR/Cas9 system (Figure 4A). To obtain cKO mice, kif2cflox/flox mice were mated with NestinCre transgenic mice, which resulted in KIF2C deletion only in the nestin cell lineage (Figure 4—figure supplement 1A). The knockout efficiency was confirmed using a hippocampal tissue RT-PCR assay (Figure 4—figure supplement 1B). There were no significant differences in body weight or brain size between kif2cflox/flox;NestinCre (cKO) and kif2cflox/flox (WT) mice (Figure 4—figure supplement 1C). In addition, using Nissl staining, we found that the thickness of hippocampal CA1 and CA3 regions did not change significantly in cKO mice (Figure 4B). Further examination of neuronal morphology of CA1 pyramidal cells by Golgi staining and Sholl analysis showed no significant differences in dendritic complexity or spine density between WT mice and KIF2C cKO mice (Figure 4C–E). However, the density of mushroom-type spines decreased in basal and apical dendrites of hippocampal neurons in cKO mice, whereas the density of filopodia-type spines increased (Figure 4F). Furthermore, electron microscopy analysis revealed that the length and thickness of the PSD fraction were remarkably reduced in the hippocampus of cKO mice (Figure 4G and H). Mushroom spines are commonly considered mature spines (Bourne and Harris, 2008; Rochefort and Konnerth, 2012); therefore, these results indicate impaired spine maturation in the hippocampal CA1 region of cKO mice.

Figure 4 with 1 supplement see all
Abnormal spine formation in KIF2C conditional knockout mice.

(A) Targeting strategy to generate kif2cflox/flox mice. Two LoxP sites were inserted into intron 1–2 and 8–9. (B) Nissl staining of adult mice brain coronal sections and magnified images of hippocampal CA1 and CA3 regions. Scale bar, 50 μm. n = 4 mice per genotypes; n.s., p > 0.05, Student’s t-test. (C–F) Golgi staining of WT and cKO hippocampus CA1 pyramidal neuron. n = 4 mice per genotypes; Scale bar, 2 μm. (D) Sholl analysis of dendritic arborization. The number of intersections related to distance from soma was quantified. p > 0.05, Two-way ANOVA RM and post hoc comparisons. (E) Histograms show spine number per 1 μm of WT and cKO CA1 pyramidal neuron. p = 0.3809. Student’s t-test. (F) The density of four types of spines in WT and cKO CA1 pyramidal neuron. Mushroom spine density was 0.32 ± 0.009 μm–1 (WT) and 0.23 ± 0.01 μm–1 (cKO) (****p < 0.0001). Filopodia spine density was 0.16 ± 0.009 μm–1 (WT) and 0.22 ± 0.01 μm–1 (cKO) (***p < 0.001). Stubby spine density was 0.12 ± 0.009 μm–1 (WT) and 0.13 ± 0.01 μm–1 (cKO) (p = 0.3104). Thin spine density was 0.41 ± 0.009 μm–1 (WT) and 0.43 ± 0.01 μm–1 (cKO) (p = 0.5511). Student’s t-test. (G) Transmission EM of synapse in hippocampal CA1 region from WT and KIF2C cKO mice (n = 3 mice per genotype) at 6–8 weeks. Scale bar, 500 nm. (H) Quantification of PSD thickness and length. PSD thickness: 40.02 ± 0.93 nm (WT) and 36.37 ± 0.58 nm (cKO). PSD length: 301.4 ± 6.8 nm (WT) and 247.7 ± 5.4 nm (cKO). ***p < 0.001; ****p < 0.0001; Student’s t-test.

Figure 4—source data 1

Values for CA1 and CA3 thickness in WT and cKO mice; Values for Sholl analysis and spine density; Values for PSD thickness and length.

https://cdn.elifesciences.org/articles/72483/elife-72483-fig4-data1-v1.xlsx

To determine whether such impaired spine maturation may affect synaptic transmission and synaptic plasticity in cKO mice, mEPSCs were first examined in CA1 hippocampal pyramidal neurons. Consistent with the shRNA knockdown experiments in CA1, the amplitude of mEPSCs increased in cKO mice compared to that in WT controls, whereas the frequency of mEPSCs was similar between the two groups (Figure 5A). The increased mEPSC amplitude was not due to altered presynaptic activity as the PPRs were not affected in cKO neurons (Figure 5B), indicating a postsynaptic influence in mEPSC property. Therefore, we examined the NMDAR/AMPAR ratio as well as the input-output relationship of NMDAR/AMPAR-mediated EPSCs. Result showed a decreased ratio NMDAR/AMPAR in cKO mice (Figure 5C). The amplitude of NMDAR-mediated EPSCs was comparable under various stimulation, while AMPAR-mediated EPSCs was increased (Figure 5D–E), indicating a specific defect in AMPAR-mediated synaptic currents. In addition, we performed cell-surface biotinylation experiments to examine the surface expression of these two receptors. The level of surface AMPA receptors was significantly increased in the cKO hippocampus (Figure 5F), which coincided with the electrophysiological abnormalities in AMPAR-mediated synaptic transmission in cKO mice. We also measured synaptic plasticity in the hippocampal CA1 region in WT and cKO mice. Result showed that the LTP magnitude was significantly attenuated in cKO hippocampal by two different induction protocols: single high-frequency stimulation (1× HFS) and 4-train LTP (4× HFS) (Figure 5G and H). Long-term depression (LTD) was not altered (Figure 5I). Taken together, these results suggest that KIF2C plays a critical role in LTP induction and maintenance.

KIF2C deficiency impairs synaptic transmission and plasticity.

(A) mEPSCs recorded from WT and cKO CA1 pyramidal neurons. n = 21 neurons per group; ***p < 0.001, Student’s t-test; For the cumulative probability curves, n.s. p > 0.05, ****p < 0.0001, Kolmogorov-Smirnov test. (B) Paired-pulse stimuli evoked EPSPs with different interval. n = 9 neurons per group, p > 0.05. The data were analyzed in separate t-tests at each stimulus intensity. (C) AMPAR and NMDAR EPSCs in CA1 pyramidal neurons of WT and cKO mice. Sample sweeps illustrating NMDAR-EPSCs recorded at +40 mV and AMPAR-EPSCs recorded at −70 mV. Histograms show ratio of NMDAR-EPSCs amplitude / AMPAR-EPSCs amplitude (right). n = 10 neurons, *p < 0.05. Student’s t-test. (D) Sample traces and input-output curve of NMDA receptor-mediated EPSCs between WT and cKO mice (n = 6 neurons, p > 0.05). The data were analyzed in separate t-tests at each stimulus intensity. (E) Sample traces and input-output curve of AMPA receptor-mediated EPSCs between WT and cKO mice (n = 6 neurons, *p < 0.05). The data were analyzed in separate t-tests at each stimulus intensity. (F) Cell-surface biotinylation shows a significant increase in GluA1 and GluA2 subunit surface expression in cKO hippocampus compared with WT. Histograms show percent change of GluA1, GluA2, GluN1, GluN2A, GluN2B subunits in total and biotinylation fraction. Flotillin was the internal control. n = 7 experiment repeats, *p < 0.05, **p < 0.01, Student’s t-test. (G) Example fEPSP before (baseline) and after (t = 60 min) 1× HFS stimulation in WT and cKO CA1 slices. Time course of percentage changes of fEPSP slope in WT and cKO CA1 slices. WT, n = 9 slices from 7 mice; cKO, n = 7 slices from 6 mice. Histogram shows fEPSP slope of WT and cKO neurons (55–60 min). *p < 0.05, Student’s t-test. (H) Example fEPSP before (baseline) and after (t = 135 min) 4× HFS stimulation in WT and cKO CA1 slices. Time course of percentage changes of fEPSP slope in WT and cKO CA1 slices. WT, n = 4 slices from 4 mice; cKO, n = 5 slices from 4 mice. Histogram shows fEPSP slope of WT and cKO neurons (130–135 min). *p < 0.05, Student’s t-test. (I) Time course of percentage changes of fEPSP slope before (baseline) and after low frequency stimulus (LFS) in control and cKO CA1 slices. WT, n = 7 slices from 5 mice; cKO, n = 7 slices from 6 mice. Histogram shows fEPSP slope of WT and cKO neurons (55–60 min). p = 0.7642, Student’s t-test.

Figure 5—source data 1

Values for mEPSCs of WT and cKO neurons.

Values for PPR ratio; Values for input-output curve of AMPAR and NMDAR mediated EPSCs between WT and cKO neurons; Values for NMDAR and AMPAR subunit surface expression; Values for percentage changes of fEPSCs amplitudes in WT and cKO neurons.

https://cdn.elifesciences.org/articles/72483/elife-72483-fig5-data1-v1.xlsx
Figure 5—source data 2

Original files of blots with the relevant bands.

https://cdn.elifesciences.org/articles/72483/elife-72483-fig5-data2-v1.zip

KIF2C regulates synaptic transmission and plasticity by mediating dynamic microtubule depolymerization in dendrites and spines

Extensive studies on KIF2C in dividing cells have shown that KIF2C regulates MT dynamics by mediating MT depolymerization (Gorbsky, 2004; Helenius et al., 2006; Knowlton et al., 2006). Moreover, dynamic MTs are reported to be involved in regulating dendritic spine morphology and synaptic plasticity (Gu and Zheng, 2009). Therefore, we speculated that KIF2C might regulate synaptic plasticity through adjusting dynamic MTs. To further explore this, we transfected EB3-tdtomato into WT or cKO hippocampal neurons to mark the MT plus end and observed the MT dynamics in mature neurons by live-cell imaging. Quantitative results showed that the speed of EB3 was increased in cKO dendrites (WT: 8.9 ± 0.8 μm / min, cKO: 12.4 ± 0.5 μm / min) (Figure 6A and B), indicating an increased rate of MT polymerization in cKO mice. Using the plusTipTracker software, which is designed to track MT growth parameters (Myers et al., 2011), we analyzed the polymerization properties of the EB3-labeled MT plus ends in dendrites. Depletion of KIF2C significantly increased MT plus-end growth speed (WT: 24.0 ± 1.1 μm / min, cKO: 31.0 ± 1.0 μm / min), and decreased its growth lifetime (WT: 9.4 ± 0.4 s, cKO: 6.7 ± 0.1 s) (Figure 6B). MT plus end growth length was not significantly altered (WT: 3.1 ± 0.1 μm, cKO: 3.0 ± 0.1 μm) (Figure 6B). These results suggest that KIF2C regulates MT depolymerization in hippocampal neurons and that MT dynamics become disordered with KIF2C deficiency.

Figure 6 with 1 supplement see all
Abnormal MT dynamics causes deficit in synaptic transmission and plasticity.

(A) Time-lapse recordings of EB3-tdtomato-infected neurons showing EB3-tdtomato comets in dendrite of WT and cKO hippocampus neuron. Subsequent images show low-pass-filtered time series in row. Scale bar is 1 μm, time in seconds. (B) Analysis of the EB3 comet dynamics in dendrites of WT and cKO hippocampus neuron. n = 58 per group from seven independent experiments. Histograms show EB3 speed velocity (***p < 0.001), MT growth speed (****p < 0.0001), MT growth lifetime (****p < 0.0001) and MT growth length (p = 0.2850). Student’s t-test. (C) Images of dendrites from WT and cKO cultured hippocampal neurons transfected with EB3-tdtomato (red) and GFP (green). Scale bar, 5 μm. Spines labeled with ‘‘*’’ were depicted in the kymograph. The invasion shown in the red boxed region of kymograph is depicted below. Sequential frames showed an MT entering the labeled spine of cKO neuron. Scale bar,1 μm. Histograms show MT-spine invasion frequency (invasions/spine/hour). (WT: 0.45 ± 0.07, n = 15; cKO: 1.07 ± 0.15, n = 17. **p < 0.01). Student’s t-test. (D) Tyrosinated α-tubulin antibody-labeled MTs (white arrows) were detected in a small percentage of phalloidin (F-actin) -labeled spines under basal conditions (DIV 18–20). Quantification of the number of spines containing MTs before and after BDNF treatment. Scale bar, 5 μm. 2.9% ± 0.32% (WT, n = 29), 5.9% ± 0.5% (WT+ BDNF, n = 31), 4.5% ± 0.46% (cKO, n = 24), 3.3% ± 0.29% (cKO+ BDNF, n = 30). *p < 0.05, ****p < 0.0001, One-way ANOVA (post hoc comparison). (E) DIV 18–20 cKO hippocampus neurons transfected with GFP vector or GFP-KIF2C labeled with GFP (white), tyrosinated α-tubulin (green) and phalloidin (red). Quantification of the number of spines containing MTs before and after BDNF treatment. Scale bar, 2 μm. 3.6% ± 0.31% (cKO+ GFP + control, n = 27), 2.9% ± 0.20% (cKO+ GFP + BDNF, n = 27), 2.4% ± 0.19% (cKO+ KIF2 C(WT)+ control, n = 25), 4.2% ± 0.34% (cKO+ KIF2 C(WT)+ BDNF, n = 33). *p < 0.05, ****p < 0.0001, One-way ANOVA (post hoc comparison). (F) mEPSCs recorded from control (n = 18 neurons), KIF2C(WT) (n = 21 neurons) and KIF2C(G491A) (n = 15 neurons) expressed in cKO CA1 pyramidal neurons. n.s. p > 0.05, *p < 0.05, ***p < 0.001, One-way ANOVA (post hoc comparison). (G) Example fEPSP before (baseline) and after (t = 60 min) 1× HFS stimulation in cKO+ control, cKO+ KIF2 C(WT) and cKO+ KIF2 C(G491A) CA1 slices. Time course of percentage changes of fEPSP slope in cKO+ control, cKO+ KIF2 C(WT) and cKO+ KIF2 C(G491A) CA1 pyramidal neurons. cKO+ control, n = 13 slices from 10 mice; cKO+ KIF2 C(WT) and cKO+ KIF2 C(G491A), n = 5 slices from 4 mice. Histogram shows fEPSP slope of cKO+ control, cKO+ KIF2 C(WT) neurons and cKO+ KIF2 C(G491A) (55–60 min). *p < 0.05, **p < 0.01; One-way ANOVA (post hoc comparison).

Figure 6—source data 1

Values for EB3 speed velocity, MT growth speed, MT growth lifetime, and MT growth length.

Values for MT invasion frequency; Values for number of spines containing MTs before and after BDNF treatment; Values for mEPSCs of cKO+ control, cKO+ KIF2 C(WT), and cKO+ KIF2 C(G491A); Values for percentage changes of fEPSCs amplitudes of cKO+ control, cKO+ KIF2 C(WT), and cKO+ KIF2 C(G491A).

https://cdn.elifesciences.org/articles/72483/elife-72483-fig6-data1-v1.xlsx

MTs remain dynamic in mature neurons and are capable of invading dendritic protrusions, which depends on neuronal activity (Hu et al., 2011). To observe MT invasion, cultured hippocampus neurons were co-transfected with EB3-tdtomato (to label MT plus end) and GFP (to outline neuron volume and mark the spines). Quantitative results showed that MT spine invasion frequency was increased significantly (Figure 6C) in cKO neurons. We further treated neurons with 50 ng/mL of brain-derived neurotrophic factor (BDNF) to induce spine plasticity, and labeled newly polymerized MTs with an antibody against tyrosinated-α-tubulin. We found that without BDNF treatment, the population of spines containing tyrosinated-α-tubulin was larger in cKO neurons (Figure 6D), suggesting that KIF2C deficiency led to an increased MT spine invasion events under basal state. After BDNF treatment, MT spine invasion was robustly increased in WT neurons, while making no change in cKO neurons (Figure 6D), and such abolished augment could be rescued by re-expression GFP-KIF2C (Figure 6E), indicating that KIF2C is required for the activity-dependent MT invasion in spines.

In mitotic cells, KIF2C binds to the end of MTs and couples ATP hydrolysis to initiate MT depolymerization (Sanhaji et al., 2011). To further confirm whether the MT depolymerization property of KIF2C is critical for regulating synaptic transmission and plasticity, we constructed an MT depolymerization loss-of-function KIF2C mutant (KIF2C G491A). Its human homologous KIF2C G495A mutant has been previously reported to lose ATP hydrolyzing and hence MT depolymerization abilities (Wang et al., 2012; Wang et al., 2015). The KIF2C(G491A) mutant was first tested in HEK 293T cells for its MT depolymerization function. Immunocytochemical analysis showed that KIF2C(G491A) transfected cells had intact cell morphology, while the KIF2C(WT) successfully depolymerized MTs and maintained cell rounding (Figure 6—figure supplement 1A). Furthermore, we expressed KIF2C(WT) or mutant in the hippocampal CA1 region of cKO mice by AAV-mediated gene delivery (Figure 6—figure supplement 1B, C) and examined synaptic transmission and plasticity using an electrophysiological approach. The results showed that re-expression of KIF2C(WT) significantly reduced the elevated amplitude of mEPSCs (Figure 6F) and restored LTP in cKO mice (Figure 6G). However, without MT depolymerization activity, the KIF2C (G491A) mutant failed to show significant differences in mEPSC properties (Figure 6F) or LTP induction in the cKO CA1 neurons (Figure 6G). These findings indicate that KIF2C regulates synaptic transmission and plasticity by mediating dynamic MT depolymerization in dendrites and spines.

KIF2C plays an important role in CA1-dependent cognitive behaviors

KIF2C deficiency leads to abnormalities in synaptic transmission and synaptic plasticity; we speculate whether KIF2C plays a role in higher order brain function. Therefore, we examined KIF2C cKO mice for several behavioral tests. The KIF2C cKO mice showed normal motion and anxiety levels in the open field test and elevated zero maze compared to those of the WT mice (Figure 7—figure supplement 1A, B), and had normal grooming frequencies in the commonly used repetitive behavioral test (Figure 7—figure supplement 1C). The Morris water maze task also elicited similar learning curves and probe performance in both KIF2C cKO and WT mice (Figure 7—figure supplement 1D), suggesting normal spatial learning and memory ability in mice with KIF2C deficiency. However, when we subjected the mice to the Y-maze test, KIF2C cKO mice showed significant impairment in spontaneous alternation behavior compared to that of the WT mice (Figure 7A), indicating that KIF2C cKO mice were deficient in short working memory, which could be due to the special role of CA1 in temporal processing (Hoge and Kesner, 2007; Ji and Maren, 2008; Farovik et al., 2010).

Figure 7 with 1 supplement see all
KIF2C cKO mice exhibit abnormal cognitive behaviors.

(A) Y maze test from WT and cKO. n = 13 per genotype. n.s., p > 0.05, *p < 0.05, **p < 0.01, Student’s t-test. (B–C) Cued fear conditioning test. (B), WT and cKO mice showed no significant differences of freezing response to the tone across three conditional stimulus (CS)-unconditional stimulus (US) pairings. p > 0.05; Two-way ANOVA. (C), Expression of conditioned freezing response to the background context or CS at indicated time. WT: n = 12; cKO: n = 10. *p < 0.05, Two-way ANOVA RM comparisons. (D–E) Three-chamber test. (D), WT and cKO mice spent more time with stranger one in sociability test. n.s., p > 0.05, ****p < 0.0001. Student’s t-test. (E), cKO mice did not display a preference for stranger two in social novelty test. n = 11 per genotype. n.s., p > 0.05, **p < 0.01, Student’s t-test. (F) cKO mice with KIF2C(WT) re-expression displayed a normal alternation in the Y-maze test. cKO mice with KIF2C(G491A) re-expression displayed similar deficiency in the Y-maze test. cKO+ mCherry, n = 9; cKO+ KIF2 C(WT), n = 9; cKO+ mNeonGreen, n = 8; cKO+ KIF2 C(G491A), n = 8. n.s., p > 0.05, *p < 0.05, One-way ANOVA (post hoc comparison). (G–H) KIF2C(WT) re-expression in CA1 can restore social novelty in cKO mice. cKO mice with KIF2C(G491A) expression displayed similar deficiency in social novelty test. cKO+ mCherry: n = 8; cKO+ KIF2 C(WT): n = 6; cKO+ mNeonGreen: n = 8; cKO+ KIF2 C(G491A): n = 9. n.s., p > 0.05, *p < 0.05, ***p < 0.001. One-way ANOVA (post hoc comparison).

Figure 7—source data 1

Values for Y-maze test of WT and cKO mice.

Values for freezing levels during fear conditioning test of WT and cKO mice; Values for close interaction time during three-chamber test of WT and cKO mice; Values for Y-maze test of cKO+ mCherry, cKO+ KIF2 C(WT), cKO+ mNeonGreen, and cKO+ KIF2 C(G491A) mice; Values for close interaction time during three-chamber test of cKO+ mCherry, cKO+ KIF2 C(WT), cKO+ mNeonGreen, and cKO+ KIF2 C(G491A) mice.

https://cdn.elifesciences.org/articles/72483/elife-72483-fig7-data1-v1.xlsx

To investigate whether this learning deficit would translate to other cognitive disorders, we examined the mice for cued conditioned fear memory and social memory. The conditioned fear learning test showed that KIF2C cKO mice displayed a comparatively weaker freezing response to the context and tone conditioned stimulus (CS) during the acquisition stage (Figure 7B). We monitored the conditioned freezing response to the background context and CS until seven or 8 days after acquisition, respectively, and found that cKO mice still showed less freezing time compared to WT mice, particularly in context-dependent freezing (Figure 7C). These results suggest that fear memory in KIF2C cKO mice was impaired. The percentage change in freezing time between the KIF2C WT and cKO mice showed no significant difference, indicating an intact fear memory maintenance in cKO mice (Figure 7—figure supplement 1E). In a prepulse inhibition test, WT and cKO mice showed the same extent of inhibition as the prepulse (Figure 7—figure supplement 1F), showing that the cKO mice had normal sensorimotor gating. In the three-chambered social test, both WT and KIF2C cKO mice exhibited no position preference in habituation stage (Figure 7—figure supplement 1G). KIF2C cKO mice exhibited a normal preference for the chamber in which a stranger mouse (S1) was present, compared with the empty chamber (Figure 7D). However, with the introduction of a second stranger (S2), KIF2C cKO mice exhibited no preference for the novel stranger (S2), compared with the familiar mouse (S1) (Figure 7E). These results showed that KIF2C cKO mice showed normal sociability but significantly reduced social novelty, indicating that KIF2C is essential for social memory maintenance.

Based on the behavioral tests, we found that KIF2C plays an important role in CA1-mediated cognitive and memory functions. The deficiencies observed in the Y-maze test, cued conditioned fear memory, and three-chambered social test of KIF2C cKO mice were highly likely due to the lack of LTP in the CA1 region (Figure 5G and H). As re-expression of KIF2C(WT) in the CA1 region restored LTP (Figure 6G), we speculated whether such CA1-specific rescue could also ameliorate the behavioral abnormalities in KIF2C cKO mice. In our pretests, over-expression of KIF2C in mice for a long time would lead to neuronal death (data not shown). Therefore, we re-expressed KIF2C in the cKO mice CA1 region using a doxycycline-induced viral expression system (Figure 6—figure supplement 1C, Figure 7—figure supplement 1H) and examined the rescuing effects in the Y-maze test and three-chambered social test. The results showed that cKO mice with KIF2C(WT) re-expression displayed a normal alternation in the Y-maze test compared to cKO mice with control virus (Figure 7F, Figure 7—figure supplement 1I). Furthermore, cKO mice with KIF2C(WT) re-expression also showed normal interaction with the stranger mouse in the social novelty test (Figure 7G–H). In addition, we tested whether the expression of the functional-null mutant KIF2C(G491A) in the CA1 region of cKO mice would have any rescue effect. The results showed that cKO mice injected with KIF2C(G491A) virus still showed impaired working and social memory (Figure 7F–H, Figure 7—figure supplement 1I). Therefore, these results suggest that KIF2C is critical for cognitive function, and this functional role is mediated by its MT depolymerization ability in synapses during LTP.

Discussion

KIF2C is an ATP-dependent MT depolymerization factor that functions in several mitotic processes, such as spindle assembly, MT dynamics, correct kinetochore-MT attachment, and chromosome positioning and segregation (Sanhaji et al., 2011). However, its function in the CNS was largely unknown. Our study elucidated the functions of KIF2C in regulating spine morphology, synaptic transmission, and plasticity in hippocampal neurons and its critical role in CA1-mediated cognitive behaviors. Our study unveils the critical role of KIF2C in the CNS, showing that its known function in regulating dynamic MT stability also takes place in neurons.

The stabilization of dendritic spines is an important structural basis for synaptic plasticity. According to our results, KIF2C deficiency seems to have higher impact on synaptic structure plasticity than that on spine formation, which provides a link between dynamic MT stability and synaptic plasticity. We have also found that both acute knockdown or genetic deficiency of KIF2C eliminated LTP but not LTD expression. On the molecular basis, KIF2C knockdown or cKO hippocampal neurons exhibited a higher AMPAR-mediated EPSC amplitude and an increase in surface AMPARs expression. It is possible that increased expression of ionic glutamate receptors, particularly AMPARs, on synapses leads to LTP occlusion. Moreover, 4-train LTP impairment in cKO mice, which requires further gene transcription and protein synthesis in the postsynaptic neuron, suggests that KIF2C might also be involved in the expression and/or transportation of synaptic substances for LTP long-lasting maintenance. It would be interesting to further explore the mechanism of KIF2C-involved receptor trafficking or synaptic expression.

As important architectural elements in neurons, MTs are also responsible for intracellular transport. It has been reported that NMDA receptors can be transported by KIF17 (Setou et al., 2000) and AMPA receptors can be transported by KIF5 along MTs in dendrites (Setou et al., 2002). It is possible that KIF2C regulates membrane receptor trafficking by mediating MT dynamics through the regulation of MT stability. We observed MT dynamics using live cell imaging of KIF2C cKO hippocampal neurons. We observed that depletion of KIF2C induced faster, shorter lived MT growth in dendrites. KIF2C deficiency also increased the frequency of MT invasion under basal conditions, which was probably due to the loss of MT polymerization suppression. These results suggest that KIF2C regulates MT depolymerization and stability in hippocampal neurons. Furthermore, MT dynamic stability regulates AMPARs postsynaptic localization and synaptic plasticity (McVicker et al., 2016; Uchida et al., 2014). In the case of AMPARs trafficking, MT-dependent trafficking has been typically associated with long-range transport along the dendrites, supporting the continuous supply and redistribution of AMPARs among synapses (Hoerndli et al., 2013; Heisler et al., 2014), which can also be regulated by neuronal activity (Hoerndli et al., 2013). We speculate that KIF2C may also confine the AMPARs’ trafficking to the synaptic site through MT depolymerization and stability.

Activity-dependent MT invasion of dendritic spines becomes disabled after BDNF stimulation in cKO hippocampal neurons. Our findings reveal that during cLTP induction, KIF2C was removed from the synapses (Figure 2F–I). It is possible that translocation of KIF2C out from synapse or depletion of synaptic KIF2C during synaptic activation is required to ensure robust MT invasion into spines, where and MT depolymerization should be inhibited. However, we still need direct evidence to prove this hypothesis. Even though the genetic depletion of KIF2C increases the basal MT invasion into spines, and largely prevents further increase in MT invasion after BDNF stimulation, we are not clear whether this is the result of depletion of KIF2C’s function in spines or a followup consequence after dendritic failure of MT depolymerization, that is, after depletion of KIF2C’s function in dendrites. KIF2C’s translocation after cLTP induction would be a touch to its pure role in spines, and it would be interesting to further explore the underlying mechanism.

Abnormal dynamic MT stability would further lead to synaptic plasticity failure and, finally, cognition defects. This hypothesis was further supported by our rescue experiments using the KIF2C(G491A) mutant, in which ATP hydrolyzing and MT depolymerization capabilities are abolished (Wang et al., 2015). Re-expression of KIF2C(WT), but not KIF2C(G491A) mutant, rescued the mEPSC hyper-amplitude in KIF2C cKO mice. KIF2C(G491A) also failed to restore the impaired LTP or cognitive function in KIF2C cKO mice during working memory or social memory tests. Therefore, the MT depolymerization function of KIF2C plays a critical role in regulating synaptic plasticity and cognitive behaviors.

Interestingly, Oligomeric amyloid-β directly inhibits the MT-dependent ATPase activity of KIF2C in vitro, and thereby leads to the generation of defective mitotic structures which may contributes to the development of Alzheimer’s disease (Borysov et al., 2011). Aβ stabilizes MT by reducing catastrophe-frequency (Qu et al., 2017), which is similar with KIF2C conditional knockout phenotype. Furthermore, KIF2C was recently discovered as a blood biomarker for suicidal ideation in psychiatric patients, such as patients with schizophrenia (Niculescu et al., 2015).Therefore, KIF2C could be a therapeutic target for Alzheimer’s disease or suicidality psychiatric disorders. Nevertheless, whether KIF2C plays other important roles in higher-order brain functions remain to be explored.

Materials and methods

Generation of kif2c flox/flox mice and animal maintenance kif2cflox/flox mouse was generated via CRISPR/Cas9 system in the Model Animal Research Center of Nanjing University (Nanjing, China). In brief, Cas9 mRNA, sgRNA and donor were co-injected into zygotes. sgRNA-5’ end: 5’- TCC ACT GTG GAA TGG TCT AA –3’; sgRNA-3’ end: 5’- CTG GTT GTG AGA CAC CTG TA-3’. Mouse kif2c gene is composed of 20 exons. The sgRNA directs Cas9 endonuclease cleavage in intron 1–2 and intron 8–9 and create a DBS (double-strand break). DBS breaks were repaired by homologous recombination, and resulted in LoxP sites inserted in intron 1–2 and intron 8–9 respectively. The mouse pups were genotyped by PCR and Southern blot followed by sequence analysis. Conditional knockout mice (kif2cflox/flox;NestinCre) were obtained by crossing kif2cflox/flox mice with NestinCre mice (Wang et al., 2019). The resulting offspring were genotyped by PCR of genomic DNA. The primers information: kif2c floxP fragment, F: 5’-GGT CCA GCT CTT TAC TGA TGT GTT C –3’; R: 5’-ACA AAG CAA GTC CAG GTC CAA G-3’; Nestin-Cre, F: 5’-TGC AAC GAG TGA TGA GGT TC-3’; R: 5’- GCT TGC ATG ATC TCC GGT AT-3’. Mice were kept under temperature-controlled conditions on a 12:12 hr light/dark cycle with sufficient food and water ad libitum. Experiments were done in male littermates at the age of 1~3 month. All animal experiments were performed in accordance with the ethical guidelines of the Zhejiang University Animal Advisory Committee (2020–19500#), and were in complete compliance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals. All surgeries were performed under sodium pentobarbital anesthesia, and every effort was made to minimize suffering.

Antibodies and reagents

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Antibody to KIF2C (12139–1-AP, RRID:AB_2877829) was purchased from Proteintech (Rosemont, IL). The anti-PSD-95 (ab2723, RRID:AB_303248), anti-MAP2 (ab5392, RRID:AB_2138153), anti-α-tubulin antibody (ab52866, RRID:AB_869989), anti-mCherry (ab167453, RRID:AB_2571870), anti-GFP (ab6556, RRID:AB_305564) and anti-EB3 (ab157217, RRID: AB_2890656) were purchased from Abcam (Cambridge, UK). The anti-α-tubulin, tyrosinated (MAB1864-I, RRID:AB_2890657), anti-synaptophysin (MAB368, RRID:AB_94947), anti-GAPDH (MAB374, RRID:B_2107445), anti-GluA1(04–855, RRID:AB_1977216), and anti-GluA2 (MAB397, RRID:AB_2113875) were purchased from Millipore (Billerica, MA). The anti-GluN2A (4205, RRID:AB_2112295), anti-GluN2B (4207, RRID:AB_1264223), anti-GluN1 (5704, RRID:AB_1904067) were from Cell Signaling Technology (Danvers, MA). The anti-flotillin was from BD (610820, RRID:AB_398139). The anti-β-tubulin (sc-5274, RRID:AB_2288090) was from Santa Cruz (Dallas, TX). The anti-bassoon (ADI-VAM-PS003-F, RRID:AB_11181058) was from Enzo Life Sciences (Farmingdale, NY). Anti-N-cadherin Antibody (BS2224, RRID:AB_1664028) was purchased from Bioworld Technology (Bloomington, MN, USA). The Phalloidin was from Yeasen (40,734ES75, Shanghai, China). Horseradish peroxidase-conjugated secondary antibodies for immunoblotting were from Jackson and for immunostaining were from Invitrogen (Carlsbad, CA). Dulbecco’s modified Eagle’s medium (DMEM), Neurobasal medium, B27 were from Gibco. GlutMax, 4',6-diamidino-2-phenylindole (DAPI), and Alexa Fluor-conjugated secondary antibodies were from Invitrogen (Carlsbad, CA). Nissl was from Beyotime (Shanghai, China). Protease inhibitor cocktail was from Merck Chemicals. Other chemicals were from Sigma (St. Louis, MO) unless stated otherwise.

qRT-PCR

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For single-cell analysis, the tip of a conventional patch-clamp pipette was placed tightly on the soma of a selected individual CA1 neuron. Gentle suction was applied to the pipette. After complete incorporation of the soma, the negative pressure was released and the pipette was quickly removed from the bath. The harvested contents were subjected to qRT-PCR using OneStep Kit (Qiagen, Hilden, Germany).

For tissue analysis, the hippocampus tissue RNA was extract by using RNeasy Mini Kit (Qiagen, Hilden, Germany). In brief, hippocampus tissue was homogenized in buffer RLT. The lysate was centrifuged at 12,000× g (4 °C for 3 min). The supernatant was transferred and 1 volume of 70% ethanol was added. Then RNA was absorbed on RNeasy Mini spin column and purified by washing with buffer RW1 and RPE. The harvested contents were subjected to Reverse Transcription Kit (Vazyme). The qPCR reaction was performed on HiScript II 1st Strand cDNA Synthesis Kit (R212-02) (Vazyme, Nanjing, China) using ChamQ Universal SYBR qPCR Master Mix (Vazyme, Q711). Primer information: gapdh: F 5’- AGG TCG GTG TGA ACG GAT TTG-3’; R 5’- TGT AGA CCA TGT AGT TGA GGT CA-3’. kif2c: F 5’-TGC CGT TGT TGA TGG TCA GTG-3’; R 5’-GGA GAC ACT TGC TGG GAA CAG-3’. shkif2c: F 5’-TGG ATC GAA GGA GGT ACC AC-3’; R 5’- CAC TGA CCA TCA ACA ACG GCA-3’. The following parameters were used: 95 °C for 30 s, followed by 39 cycles of 95 °C for 10 s, 60 °C for 30 s in accordance with the manufacturer’s protocol.

Hippocampal neuron culture and transfection

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Primary cultures of hippocampal neurons were prepared from embryonic day 18 mice. The isolated hippocampi were dissociated with 2.5% trypsin at 37 °C for 20 min. The neurons were quantified and centrifuged at 1800 rpm for 6 min and then plated on the glass coverslips pre-coated with poly-L-lysine (Sigma). The culture medium was Neurobasal (Gibco) supplemented with 2% B27 (Gibco), GlutaMax (Invitrogen) and 1% Penicillin-Streptomycin (Life Technologies) in a 5% CO2 atmosphere at 37 °C. Neurons were transfected at DIV 7–10 using a modified calcium phosphate protocol (Jiang and Chen, 2006). More than 10 days after transfection, neurons were directly subjected to live imaging under a Nikon A1R confocal scanning microscope.

HEK 293T culture and transfection

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HEK 293T cell line was purchased from ATCC (CRL-3216) through Chinese Academy of Sciences Stem Cell Bank (Serial number: SCSP-502). A spin-off strain with high transfection efficiency produced after the 293 cell line is inserted into the temperature-sensitive gene of the SV40 T-antigen. Mycoplasma test result was negative. The results of STR identification are: D5S818: 8,9; D13S317: 12,14; D7S820: 11; D16S539: 9,13; vWA: 16,19; THO1: 7,9.3; Amelogenin: X; TPOX: 11; CSF1PO: 11,12. HEK 293T cells were cultured in MEM media (Gibco) containing 10% fetal bovine serum (Gibco) and Penicillin-Streptomycin (Life Technologies). HEK 293T cells were transfected using the lipofectamine 2000.

DNA constructs

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The shRNA targeting sequence is designed against position 820–838 of mouse kif2c (Gene ID: 73804) open reading frame (5’-CCGGATGATCAAAGAATTT-3’), using Bgl Ⅱ/SalⅠ restriction enzymes. GFP-KIF2C(WT) used the Nhe Ⅰ/BamH Ⅰ restriction enzymes. GFP-KIF2C(G491A) point mutations were replaced a G to A at 491 position, using the Nhe Ⅰ/BamH Ⅰ restriction enzymes. Plasmid synthesis and virus construction were completed by the company (OBIO, Shanghai, China). KIF2C shRNA was sub-cloned into AAV backbone pAKD-CMV-bGlobin-mcherry-H1-shRNA. The KIF2C shRNA lentivirus used for infecting primary hippocampal neurons were prepared as described (Xu et al., 2016). KIF2C(WT) was sub-cloned into AAV backbone pAAV-CMV-MCS-3FLAG-P2A-mNeonGreen-CW3SL (OBIO, Shanghai, China) and rAAV-TRE3G-MCS-3*Flag-2A-mCherry-WPRE-pA (BrainVTA, Wuhan, China). KIF2C(G491A) was sub-cloned into AAV backbone pAAV-CMV-MCS-3FLAG-P2A-mNeonGreen-CW3SL (OBIO, Shanghai, China).

Live-cell imaging and microtubule dynamics analysis

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The hippocampus neurons were cultured in the glass bottom dish (Cellvis, D35-20-1-N) pre-coated with poly-L-lysine, transfected by plasmids at DIV 7–10 and imaged at DIV 18–20. Live-cell imaging of EB3-tdtomato comets were captured with Nikon A1R confocal microscope with perfect focus system. Neurons were kept at 37 °C in a Nikon incubation chamber with 5% CO2 concentration and humidity during time-lapse imaging. All images were collected at 1 s time intervals, for total 10 min durations. EB3-tdtomato comets polymerization speed, lifetime and length were measured by plusTipTracker software. The following tracking settings were used: camera bit depth, 16 bits; detection method, watershed-based method with σ1 = 1 and σ2 = 4 and K = 5. Parameters used for comet tracking were as follows: search radius range, 3–15 pixels; minimum sub-track length, 3 frames; maximum gap length, 3 frames; maximum shrinkage factor, 1.5; maximum forward angle, 30°; maximum backward angle, 10°; fluctuation radius, 1.25 pixels (Lazarus et al., 2013; Sánchez-Huertas et al., 2020). Kymographs were created from lines drawn along the length of invaded spines. Invasion frequency, defined as the number of MT invasions per spine per hour, was calculated for each neuron by counting the total number of MT-spine invasions during 10 min.

Adeno-associated virus microinjection

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For virus microinjection, WT or KIF2C cKO mice were randomly allocated to experimental groups and processed. A small craniotomy was performed after anesthetizing the mouse. The flow rate (40 nl/min) was controlled by a micro-injector (World Precision Instruments). Virus was microinjected in both left and right hippocampal CA1 region (from bregma, 3 weeks: ML: 1.45 mm; AP: 1.8 mm; DV: 1.5 mm; 2 months: ML: 1.65 mm; AP: 1.82 mm; DV: 1.62 mm). For electrophysiology, 4- to 6-week-old mice were subjected for experiments at least 3 days after injection. For KIF2C re-expression mice subjected for behavioral tests, mice were injected and bred until 2- to 3-month-old, then took water containing (40 μg/ml) doxycycline for 2.5–3 days to induce KIF2C expression before tests.

Glycine-induced LTP

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Hippocampal neurons were infected by shRNA virus at DIV 7–10, and subjected for chemical LTP induction at DIV 18–20. Briefly, neurons were firstly incubated in extracellular solution (ECS; in mM: 140 NaCl, 2 CaCl2, 5 KCl, 5 HEPES, 20 glucose) supplemented with 500 nM TTX, 1 μM strychnine, 20 μM bicuculline (Buffer A; pH 7.4) at 37 °C for 5 min, and treated with 200 μM glycine in Buffer A for 10 min. Then neurons were incubated in Buffer A for another 5–10 min. The cells were then harvested for experiments (Lu et al., 2001; Merriam et al., 2013; Zhang et al., 2015).

Western blots

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After determining protein concentration with BCA protein assay (Thermo, 23225), equal quantities of proteins were loaded and fractionated on SDS-PAGE and transferred to NT nitrocellulose membrane (Pall Corporation), immunoblotted with antibodies, and visualized by enhanced chemiluminescence (Pierce Biotechnology). Primary antibody dilutions used were GluA1 (1:1000), GluA2 (1:2000), GluN1 (1:2000), GluN2A (1:2000), GluN2B (1:2000), flotillin (1:1000), KIF2C (1:500), EB3 (1:10,000), PSD-95 (1:1000), synaptophysin (1:2000), β-tubulin (1:2000), N-cadherin (1:1000), mCherry (1:2000), GAPDH (1:10,000), and secondary antibodies (1:10,000). Film signals were digitally scanned and quantitated using Image J software.

Immunocytochemistry and immunofluorescence quantification

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DIV 18–20 hippocampal neurons were fixed in 4% paraformaldehyde (PFA) containing 4% sucrose for 20 min, and then treated with 1% Triton X-100 in PBS for 10 min at room temperature (RT). After washing with 1× PBS, neurons were transferred into blocking solution (10% normal donkey serum, NDS in PBS) for 1 hr at RT. Neurons were then incubated with primary antibodies at 4 °C overnight and incubated with secondary antibodies for 3 hr at RT. Primary antibody dilutions used for immunocytochemistry were PSD-95 (1:1000), KIF2C (1:500), bassoon (1:1000), GFP (1:2000), tyrosinated α-tubulin (1:500), α-tubulin (1:1000) and MAP2 (1:10,000), and secondary antibodies (1:1000). All antibodies were diluted in 1× PBS containing 3% NDS. All images were collected by confocal laser scanning microscope Nikon A1R. Measures of spine head width and spine density in cultured hippocampal neurons were performed using Imaris software and colocalization analysis was performed by Metamorph software. Generally, fluorescence intensity was measured using region measurements function in MetaMorph. Single dendrites were selected randomly. A threshold value was set manually and separately to optimize the representation of puncta in green (PSD-95) and red (KIF2C) channels and then applied to all images from the same experiment. For the colocalization quantification, the area percentage of KIF2C overlapping PSD-95 was performed using Measurement Colocalization function. Dendritic shaft areas were manual selected and the shaft KIF2C intensity were calculated. For the quantification of synaptic KIF2C density and intensity, all the puncta on the green (PSD-95) channel were selected and used as a mask for red channel (KIF2C) overlapping to filter out the PSD-95-colocalized KIF2C puncta automatically, using the Process function, and Integrated Morphometric Analysis function was used to identify the puncta and measure their properties.

Immunohistochemistry

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Mice were anesthetized and transcranially perfused with 4% PFA. Coronal slices with 30 μm thickness were prepared and placed in blocking solution for 1 hr at RT. After washing with 1× PBS, slices were incubated with primary antibodies overnight at 4 °C and incubated with secondary antibodies for 3 hr at RT. Images were acquired using an automated fluorescence microscope Olympus BX53.

Nissl staining

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Nissl staining was performed using Nissl staining Kit (Beyotime, C0117). Coronal slices (30 μM thickness) were immersed in Nissl staining solution for 10 min at 37 °C, rinsed with ddH2O, dehydrated in ethanol, and cleared in xylene. Images of cortex and hippocampus were captured using an Olympus VS120 microscope. Hippocampus CA1 and CA3 thickness was calculated by Image J software.

Golgi staining

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Golgi-Cox staining of hippocampus CA1 tissue was performed using the FD Rapid GolgiStain Kit (FD NeuroTechnologies, PK401) following the manufacturer’s protocol. In brief, mice were deeply anesthetized with intraperitoneal injection of 4% chloral hydrate (10 μl/g), the brain was rapidly removed and rinsed briefly in ddH2O. The tissues were immersed in impregnation solution made by mixing equal volumes of solution A and B, and then stored at RT for 2 weeks in the dark. Tissues were transferred to solution C and store at 4 °C in dark for 7 days. Coronal slices (150 µm thickness) were prepared using a vibrating tissue slicer (Leica VT1000S) in solution C. Slices were mounted on gelatin-coated slides (FD NeuroTechnologies, PO101) with solution C and dry naturally at RT. Slices were rinsed in ddH2O twice and placed in a mixture consisting of 1 part solution D, 1 part solution E and two part ddH2O for 10 min. Slices were rinsed in ddH2O twice, dehydrated in 50%, 75%, 95%, and 100% ethanol for 4 min, cleared with xylene for three times, sealed with permount (Sigma, 06522). Images of hippocampus CA1 pyramidal neurons were captured by an Olympus BX61 microscope with 100× objective lens. The Sholl analysis, spine density and the morphological classification of the spines were calculated by Image J software (Ferreira et al., 2014). The morphological classification of spines as previously described (Okamura et al., 2004; Malone et al., 2008; Rochefort and Konnerth, 2012): mushroom, big protrusions with a well-defined neck and a very voluminous head; stubby, short protrusions without a distinguishable neck and head; long-thin, protrusions with a long neck and a clearly visible small bulbous head; filopodia, thin, hair-like protrusions without bulbous head.

Preparation of subcellular fractionation

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Hippocampal tissues were homogenized in buffer C (320 mM sucrose, 20 mM Tris-HCl [pH = 8.0], 2 mM EDTA and 200 μg/ml PMSF) supplemented with protease inhibitors (Merck Chemicals) and centrifuged at 800× g for 10 min at 4 °C to result in P1 and supernatant S1. The supernatant S1 was centrifugated at 12,000× g for 15 min at 4 °C to yield P2 and S2. Then P2 fraction was resuspended in buffer D (20 mM Tris-HCl [pH = 8.0], 1 mM EDTA, 100 mM NaCl, and 1.3% Triton X-100) and centrifuged at 100,000× g for 1 hr to produce a supernatant S3 and a pellet P3. The pellet represented PSD fraction, and the protein concentration was measured using BCA protein assay kit (Thermo, 23225).

Surface biotinylation assay

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Acute mouse coronal slices containing hippocampus region (250 μm) were prepared from anesthetic mice using a vibrating tissue slicer (Leica VT1000S) in ice-cold artificial cerebrospinal fluid (ACSF) containing: 125 mM NaCl, 2.5 mM KCl, 1.25 mM NaH2PO4, 1 mM MgCl2, 2 mM CaCl2, 26 mM NaHCO3 and 25 mM D-glucose, bubbled with 95% O2 / 5% CO2. After recovery for 30 min at 37°C, slices were incubated with 0.5 mg/ml EZ-link-sulfo-NHS-SS-Biotin (Thermo, 21331) in ACSF for 30 min. The biotin solution was then removed, and the remaining unreacted biotin was quenched by the addition of 50 mM Tris solution (pH = 7.4) for 2 min. The slices were then washed with ice-cold PBS and lysed with RIPA buffer supplemented with protease inhibitors. Biotinylated proteins were separated from other proteins using streptavidin agarose beads (Thermo, 20349) overnight at 4°C. The agarose beads were then washed three times with RIPA buffer and 500× g, 2 min centrifuge. The biotinylated proteins were extracted with SDS-PAGE loading buffer and boiled for 3 min before western blot.

Transmission electron microscopy (TEM)

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Mice (P30) were transcranial perfused with saline and ice-cold fixative (4% PFA containing 0.1% glutaraldehyde), brains were removed and stored at 4 °C for 2.5 hr in fixative. Coronal slices containing hippocampus region (250 μm) were cut on a vibratome and kept in ice-cold fixative solution. Small blocks of tissue (1 mm2) from the CA1 region were excised under a microscope. The CA1 tissues were then rinsed for 6 times with 0.1 M PB and post-fixed in 1% OsO4 for 30 min, rinsed for three times with ddH2O and stained with 2% uranyl acetate for 30 min at room temperature. After dehydrating through a graded series of ethanol (50%, 70%, 90%, and 100%), the samples were embedded in an epoxy resin. Ultrathin sections (90 nm) were cut using an ultra-microtome (Leica), stained with lead citrate solution, and mounted on grids. EM images were captured at ×11,000 and ×68,000 magnification using a Tecnai transmission electron microscope (FEI, Hillsboro, OR). CA1 synapses were identified by the presence of a presynaptic bouton with at least two synaptic vesicles within a 50 nm distance from the cellular membrane facing the spine, a visible synaptic cleft, and PSD (Spano et al., 2019). Image J software was used to analyze the PSD length and PSD thickness.

Electrophysiology

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We used 1% barbital sodium to anesthetize mice and removed the brain of mice rapidly and placed it in ice-cold, high-sucrose cutting solution containing (in mM): 194 Sucrose, 30 NaCl, 4.5 KCl, 0.2 CaCl2, 2 MgCl2, 1.2 NaH2PO4, 26 NaHCO3, 10 Glucose. We cut slices coronally in the high-sucrose cutting solution with vibratome, and transferred the slices to an incubation chamber with artificial cerebrospinal fluid (ACSF) containing (in mM): 119 NaCl, 2.5 KCl, 2.5 CaCl2, 1.3 MgSO4, 1.0 NaH2PO4, 26.2 NaHCO3, 11 Glucose. Slices were incubated at 34 °C for 30 min and then transferred to 27 °C for at least 1 hr before recording. During recording, the slices were placed in a recording chamber constantly perfused with warmed ACSF (32 °C) and gassed continuously with 95% O2 and 5% CO2. Pipettes for Whole-cell recordings (3–5 MΩ) were filled with a solution containing (in mM): 115 CsMeSO4, 20 CsCl, 10 HEPES, 2.5 MgCl2, 4 Na-ATP, 0.4 Na2-GTP, 10 Na2phosphocreatine, 0.6 EGTA, 5 QX-314 (pH 7.2–7.4, osmolarity 290–310). Data were collected with a MultiClamp 700B amplifier and analyzed by pClamp10 software (Molecular Devices, Sunnyvale, USA). The initial access resistance was <25 MΩ and was monitored throughout each experiment. Data were discarded if the access resistance changed 20% during whole recording. Data were filtered at 2 kHz and digitized at 10 kHz.

For field excitatory postsynaptic potential recording, DG zone was cut down before recording to avoid the generation of epileptic wave. A concentric bipolar stimulating electrode was placed in the stratum radiatum to evoke EPSP and the recording electrode filled with ACSF was placed at 200–400 µm away from the stimulus electrode at the same region. Increasing stimulus intensity step by step to find the maximal response and then the baseline response was adjusted at 1/3 to 1/2 of the maximal response. After the steady baseline response was recorded for 30 min, a strain of 100 Hz-100 pulses high frequency stimulus (1× HFS) or four strains of 100 Hz-100 pulses high frequency stimulus applied with 5 min intervals (4× HFS) was delivered to induce LTP and a train of 2 Hz-900 pulses low-frequency stimulus was delivered to induce LTD. The induced post response was recorded for 1 hr (1× HFS) or 2 hr (4× HFS). The slope within 2ms at initial EPSP was calculated as the value for field EPSP. The magnitude of LTP and LTD was calculated based on the EPSP values 55–60 min (1× HFS) or 130–135 min (4× HFS) after the end of the induction protocol.

For whole-cell LTP recording, 100 µmol/L picrotoxin was added in recycling ACSF to block GABAR-mediated current. The stimulus electrode was placed in the stratum radiatum to evoke EPSC at 0.1 HZ and AMPAR-mediated current was recorded at –70 mV. After the steady baseline response was recorded for 5 min, the cell was held at 0 mV and received two strains of 100 Hz-100 pulses high frequency stimulus with 20 s intervals. And then the cell was held at –70 mV to record for 40 min. Here, the HFS must be given within 10 min of achieving the whole-cell recording to avoid ‘wash-out’ of LTP. The magnitude of LTP was calculated based on the EPSC values 35–40 min after the end of the induction protocol.

For NMDAR-mediated current and AMPAR-mediated current recording, 100 µmol/L picrotoxin was added in recycling ACSF to block GABAR-mediated current. AMPAR-mediated current was recorded at –70 mV. A mixed current for AMPAR-mediated current and NMDAR-mediated current was recorded at +40 mV. The current at 50ms after stimulus was counted for NMDAR-mediated current. The AMPAR/NMDAR ratio was calculated as the peak of the averaged AMPAR-mediated EPSC (30–40 consecutive events) at –70 mV divided by the averaged NMDAR-mediated EPSC (30–40 consecutive events).

Input-Output curves were established by plotting the EPSC amplitude against various intensities of the test pulse, ranging from 25 μA to 50 μA in 5 μA steps. NMDAR-mediated EPSCs were recorded in the presence of 20 μM CNQX and 100 μM picrotoxin and at +40 mV holding potential. AMPAR-mediated EPSCs were recorded in the presence of 50 μM AP5 and 100 μM picrotoxin and at –70 mV holding potential.

For mini excitatory synaptic transmission recording, 100 µmol/L picrotoxin and 1 µmol/L TTX was added into recycling ACSF to block GABA currents and sodium currents respectively. Recording was conducted at –70 mV. Chemical LTP (cLTP) was induced by treatment of hippocampus slices with glycine (200 μM) to activate NMDA receptors. Slices were treated with glycine in the Mg2+ free ACSF for 10 min, then transferred to the recording chamber with ACSF containing 1 μM tetrodotoxin, 100 μM picrotoxin for patch recordings. Mini analysis software was used to count the mini EPSCs.

Paired-pulse facilitation (PPF) was examined by paired stimulations at different intervals.

Behavioral experiments

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All behavioral experiments were performed with the age of 2- to 3-month-old male littermates. All animals were given at least 1 hr of habituation time before testing. KIF2C(WT) re-expression assay for behavioral tests used a doxycycline-induced viral expression system.

Open-field test

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The open-field test was used to evaluate the autonomous behavior, exploratory behavior, and tension of animals in a new environment. Through dynamic monitoring of exploratory behavior and spontaneous activity, it is often used to test basic exercise volume and anxiety level. The mice were put in an area of 40 cm× 40 cm × 40 cm box and exploring freely for 30 min using a video tracking system. Data were analyzed using ANY-maze software.

Y-maze

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The Y-maze was used to evaluate discriminative learning, short-term working memory and reference memory test. It is based on the innate curiosity of the rodents to explore an arm that has not been previously visited. The Y-shaped maze is composed of three equal-length arms (40 cm×9 cm × 16 cm). The angle between each two arms is 120 degrees. The inner arms and the bottom of the maze are painted dark gray. The mice were placed in the center of the maze and allowed to freely explore the three arms for 5 min. Take the animals’ four feet into the arm as the standard. One alternation would be recorded if all arms were entered successively at a time. The numbers of arm entries were recorded to evaluate the locomotion of animals in the Y-maze. Spontaneous alternation was calculated as total alternations/the number of maximum alternations (total arm entries-2). Error % was calculated as total errors/the number of maximum errors (total arm entries-2).

Elevated zero maze

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Elevated zero maze was used to investigate the animal’s anxiety state which was based on the animal’s exploring characteristics of the new environment and the fear of hanging open arms to form conflicting behaviors. The annular platform (60 cm in diameter, 5 cm track width) was evaluated 50 cm above the floor and divided equally into four quadrants. Two opposite quadrants were ‘open’ and others were surrounded by 16 cm high blue, opaque walls. The mice were randomly placed in closed quadrants and allowed to freely to explore for a period of 5 min using an overhead video tracking system. Dependent measures were: time in open quadrants, open entrances, number of head dips, number of stretch attendance postures (SAP) and number of four paws in open section.

Morris water maze

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Morris water maze is the most classic behavioral experiment that evaluates animal learning, memory, cognition, and space exploration ability. The water maze consists of a circular pool (radius 120 cm) filed with water containing nontoxic titanium pigment to make the platform invisible. Mice were trained to find the hidden platform (5 cm) and placed gently in different quadrants each time. The maximum searching period allotted was 60 s. If a mouse did not find the platform, it will be placed on the platform by the experimenter and remained for 10 s. Training was performed for five days and tested on the sixth day. For the training sessions, the time taken to find the platform, velocity, and distance traveled were recorded. For the test session, the platform was removed. The time spent in the four quadrants of the pool were recorded.

Self-grooming

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The mice were placed individually in a clean cage with fresh bedding. After 10-min habituation, mice were monitored with a camera and recorded for 10 min to score the spontaneous grooming behavior. Time of grooming was recorded.

Three-chambered social test

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Three-chamber social interaction test was carried out as described previously (Silverman et al., 2010). Briefly, two empty steel cylinders were respectively placed in the left and right rectangular. The test mice were individually placed in the center chamber for a 10-min habituation. Then the mice encountered a stranger C57BL /6 N mouse (S1) in the cage for 10 min. The social novelty test was then arranged and another stranger C57BL/6 N (S2) was placed in the cage and let the test mouse explored freely for 10 min. The close interaction time of the test mouse spent in each chamber was recorded. The ratio of (S1-E) to (S1+ E) was calculated as the preference index (S1-E), and the ratio of (S2-S1) to (S2+ S1) was measured as the preference index (S2-S1).

Cued fear conditioning

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Mice from each genotype were placed to the conditioning chamber for a 160-s habituation and then received three conditional stimulus (CS)- unconditional stimulus (US) trails inter-spaced by 40 s inter-trail intervals. They were given 60 s stimulus-free interval before returned to their home cage. The conditional stimulus comprised a 20 s discrete tone (80 dB, 2.8 kHz), which was followed by an unconditional stimulus at the last 2 s (US, 0.55 mA foot shock). To examine the condition response to the background contextual cues, the mice were placed back in the conditioning chamber for 6 min in the absence of the CS and US stimuli after training 24 hr, 7d. To examine the condition response to the CS, the mice were placed in a distinct and modified context and given a 6 min CS tone after training 48 hr, 8d. The context maintenance index is the ratio of (24hr-7d) to 24 hr freezing time, and the CS maintenance index is the ratio of (48hr-8d) to 48 hr freezing time. For all procedures, the animal freezing behaviors were monitored using a manufacturer’s software.

Prepulse inhibition (PPI) test

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PPI was performed as described previously (Maekawa et al., 2010). Briefly, in PPI test, prepulses (PP) were set at 70, 74, 78, and 82 dB, and pulse (P) was set at 120 dB. Percentage PPI was calculated as [(P amplitude – PP amplitude)/ P amplitude] × 100%.

Statistics

Data were analyzed using GraphPad Prism 8.0 (GraphPad Software, San Diego, CA), Excel 2017 (Microsoft, Seattle, WA), and Sigmaplot 12.0 (Systat Software, Erkrath, Germany). Data analyses were blind to experimental conditions until the data were integrated. Standard deviations for controls were calculated from the average of all control data. Statistical difference was determined using a Student’s t test or one-way ANOVA with Tukey’s post hoc tests or two-way ANOVA with Bonferroni correction. The accepted level of significance was p < 0.05. n represents the number of preparations, experimental repeats or cells as indicated in figure legends. Data are presented as mean ± SEM.

Appendix 1

Appendix 1—key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Strain, strain background (Mus musculus, male/female)C57BL/6Shanghai SLAC Laboratory Animal C.,Ltd
Strain, strain background (Mus musculus, male/female)kif2cflox/flox mouseModel Animal Research Center of Nanjing University
Strain, strain background (Mus musculus, male/female)NestinCre mouseZhejiang UniversityWang et al., 2019
Cell line (Homo-sapiens)HEK 293TATCCCRL-3216
Genetic reagent (virus)pAKD-CMV-bGlobin-mcherry-H1-shRNAObioTechnology
Genetic reagent (virus)pAAV-CMV-KIF2C-3FLAG-P2A-mNeonGreen-CW3SLObioTechnology
Genetic reagent (virus)pAAV-CMV-KIF2C(G491A)–3FLAG-P2A-mNeonGreen-CW3SLObioTechnology
Genetic reagent (virus)rAAV-TRE3G- KIF2C-3*Flag –2A-mCherry-WPRE-pABrainVTA
AntibodyAnti-KIF2C, (rabbit polyclonal)ProteintechCat# 12139–1-AP, RRID:AB_2877829IF (1:500), WB (1:500)
AntibodyAnti-PSD-95, (mouse monoclonal)AbcamCat# ab2723, RRID:AB_303248IF (1:1000) WB (1:1000)
AntibodyAnti-MAP2, (chicken polyclonal)AbcamCat# ab5392, RRID:AB_2138153IF (1:2000)
Antibodyanti-GFP (rabbit polyclonal)AbcamCat# ab6556, RRID:AB_305564IF (1:2000)
AntibodyAnti-α-tubulin, (rabbit monoclonal)AbcamCat# ab52866, RRID:AB_869989IF (1:1000)
AntibodyAnti-mCherry, (rabbit polyclonal)AbcamCat# ab167453, RRID:AB_2571870WB (1:2000)
AntibodyAnti-EB3, (rabbit monoclonal)AbcamCat# ab157217, RRID:AB_2890656WB (1:10,000)
AntibodyAnti-α-tubulin, tyrosinated, (rat monoclonal)MilliporeCat# MAB1864-I, RRID:AB_2890657IF (1:1000)
AntibodyAnti-synaptophysin, (mouse monoclonal)MilliporeCat# MAB368, RRID:AB_94947IF (1:1000) WB (1:2000)
AntibodyAnti-GAPDH, (mouse monoclonal)MilliporeCat# MAB374, RRID:AB_2107445WB (1:10,000)
AntibodyAnti-GluA1, (rabbit monoclonal)MilliporeCat# 04–855, RRID:AB_1977216WB (1:1000)
AntibodyAnti-GluA2, (mouse monoclonal)MilliporeCat# MAB397, RRID:AB_2113875WB (1:2000)
AntibodyAnti-GluN2A, (rabbit polyclonal)Cell Signaling TechnologyCat# 4205, RRID:AB_2112295WB (1:2000)
AntibodyAnti- GluN2B, (rabbit polyclonal)Cell Signaling TechnologyCat# 4207, RRID:AB_1264223WB (1:2000)
AntibodyAnti-GluN1, (rabbit polyclonal)Cell Signaling TechnologyCat# 5704, RRID:AB_1904067WB (1:2000)
AntibodyAnti-flotillin, (mouse monoclonal)BD BioscienceCat# 610820, RRID:AB_398139WB (1:1000)
AntibodyAnti-β-tubulin, a (mouse monoclonal)Santa CruzCat# sc-5274, RRID:AB_2288090WB (1:2000)
AntibodyAnti- bassoon, (mouse monoclonal)Enzo Life SciencesCat# ADI-VAM-PS003-F, RRID:AB_11181058IF (1:1000)
AntibodyAnti- N-cadherin, (rabbit polyclonal)Bioworld TechnologyCat# BS2224, RRID:AB_1664028WB (1:1000)
Chemical compound, drugCNQXSigma-AldrichCat# C239; CAS: 115066-14-320 μM
Chemical compound, drugAP-VSigma-AldrichCat# A8054; CAS: 79055-68-850 μM
Chemical compound, drugDoxycycline HyclateSelleckCat# S4163; CAS:24390-14-540 μg/ml
Chemical compound, drugGlycineSigma-AldrichCat# G8898; CAS:56-40-6200 μM
Chemical compound, drugbicucullineAbcamCat# ab120108; CAS: 40709-69-120 μM
Chemical compound, drugPicrotoxinSigma-AldrichCat# P1675; CAS: 124-87-8100 μM
Commercial assay or kitSYBR Green qPCR Master MixQIAGENCat# 204,057
Commercial assay or kitNissl staining KitBeyotimeCat# C0117
Commercial assay or kitFD Rapid GolgiStain KitFD NeuroTechnologiesCat# PK401
Commercial assay or kitBCA Protein Assay KitThermo FisherCat# 23,227
Software, algorithmGraphPad Prism (8.0)GraphPad Softwarehttps://www.graphpad.com/scientific-software/prism/RRID: SCR_002798
Software, algorithmImageJNational Institutes of Healthhttps://imagej.nih.gov/ij/RRID:SCR_003070
Software, algorithmANY-maze tracking softwareStoelting Cohttps://www.stoeltingco.com/anymaze.htmlRRID:SCR_014289
Software, algorithmPlusTipTrackerUTSouthwestern Medical Center Danuser Labhttps://www.utsouthwestern.edu/labs/danuser/software/
Software, algorithmSigmaplotsystatsoftwarehttp://www.systatsoftware.cn/RRID:SCR_003210
Software, algorithmMATLAB R2017bMathWorkshttps://se.mathworks.com/products/matlab.htmlRRID: SCR_001622
Sequence-based reagentKIF2C floxP _FThis paperPCR primersGGT CCA GCT CTT TAC TGA TGT GTT C
Sequence-based reagentKIF2C floxP _RThis paperPCR primersACA AAG CAA GTC CAG GTC CAA G
Sequence-based reagentNestin-Cre_FThis paperPCR primersTGC AAC GAG TGA TGA GGT TC
Sequence-based reagentNestin-Cre_RThis paperPCR primersGCT TGC ATG ATC TCC GGT AT
Sequence-based reagentkif2c_FThis paperPCR primersTGC CGT TGT TGA TGG TCA GTG
Sequence-based reagentkif2c_RThis paperPCR primersGGA GAC ACT TGC TGG GAA CAG
Sequence-based reagentshkif2c_FThis paperPCR primersTGG ATC GAA GGA GGT ACC AC
Sequence-based reagentshkif2c_RThis paperPCR primersCAC TGA CCA TCA ACA ACG GCA
Sequence-based reagentgapdh_FThis paperPCR primersAGG TCG GTG TGA ACG GAT TTG
Sequence-based reagentgapdh_RThis paperPCR primersTGT AGA CCA TGT AGT TGA GGT CA
Peptide, recombinant proteinBDNFSigma-AldrichCat# GF30150 ng/mL

Data availability

We have uploaded the source data files together with manuscript.

References

Decision letter

  1. Eunjoon Kim
    Reviewing Editor; Institute for Basic Science, Korea Advanced Institute of Science and Technology, Republic of Korea
  2. Anna Akhmanova
    Senior Editor; Utrecht University, Netherlands
  3. Yu-Tian Wang
    Reviewer

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

Decision letter after peer review:

Thank you for submitting your article "KIF2C regulates synaptic plasticity and cognition by mediating dynamic microtubule invasion of dendritic spines" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Anna Akhmanova as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Yu-Tian Wang (Reviewer #2).

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

Summary

The authors have provided data for the function of the microtubule depolymerizing kinesin, KIF2C/MCAK, in hippocampal neuron function, synaptic transmission, plasticity and mouse behavior. As such, many different techniques are used to determine the function of this protein. Previous work has implicated a similar family member, KIF2A, in axonal branching, however KIF2C appears to be functioning primarily in dendrites. This is an intriguing hypothesis and would provide important data for understanding the function of a microtubule depolymerase in nervous system function. Although copious amounts of data are shown and the manuscript is relatively clearly written, the authors oftentimes overinterpret the data and do not use the appropriate statistical tests and comparisons. The manuscript title and conclusions made in the Abstract and Discussion suggesting that the mechanism of KIF2C action is due to changes in microtubule invasion of dendritic spines is not substantiated. Because KIF2C conditional knock out neurons clearly have defects in microtubule dynamics throughout the dendritic shafts, many of the defects ascribed to microtubule invasion of spines are potentially indirect and may not be responsible for changes in synaptic transmission or behavior. More careful and appropriate analysis of their current data and additional experiments, specifically regarding the possibility of KIF2C leaving spines during synaptic activity and the dynamics of MT invasion of spines, would be needed to determine the mechanism of KIF2C action in dendrites. Thus, although interesting, the manuscript requires substantial revisions.

Essential revisions:

1. An important part of the proposed mechanism of KIF2C action relies on the data in 2H and I. The authors argue that KIF2C is leaving dendritic spines and concentrating in the dendritic shaft after cLTP treatment. However, only colocalization of PSD95 and KIF2C is quantified, and this quantification is a percentage. It is not clear to what the percentage refers – the % of spines where they are colocalized? How is colocalization determined? What is the cutoff? Even if all of these measures were indicated, much more rigorous quantification would have to be done to provide convincing evidence that KIF2C is leaving spines and concentrating in the dendrite shaft after cLTP (as the show in their model in Figure 8). Specifically, both fixed cell imaging of endogenous KIF2C in a much more rigorous fashion, taking into account spine volume changes and comparison with another protein known to leave spines after cLTP. Imaging GFP-KIF2C in individual spines before and after cLTP and showing a subsequent decrease in the spine and increase in the shaft would also provide more compelling data.

2. The authors overinterpret the data from Figure 6C. In this experiment they treated cells with BDNF, fixed the neurons and labeled them with an antibody to dynamic MTs (tyrosinated tubulin). They show that the percent of spines containing a MT increased with BDNF in WT neurons but not in controls. They also show that cKO neurons have slightly more spines containing MTs. This methodology is useful, in addition to live-cell imaging of EB3 entries into spines, but it is difficult to quantify MT invasions because tyrosinated tubulin is also cytoplasmic and spines can change sizes with treatment. Thus, it is difficult to determine which spines contain a MT vs. just increased volume of tyrosinated tubulin. Without live cell imaging of labeled EB3 or tubulin these data are not sufficient to make claims about MT invasion. Also, only live cell imaging would be able to differentiate increased invasion of MTs vs. increased retention of MTs in spines. It is unclear what is happening in the KIF2C cKO neurons. Thus, they can't claim in the discussion that "KIF2C deficiency also increased the frequency of MT invasion under basal conditions" (line 318).

3. In addition to the points made in #2 the fact that MT dynamics are affected in the dendrites suggests that changes in MT invasion of spines are indirect. KIF2C is clearly affecting MT dynamics throughout the neuron. Thus, one would expect changes in MT invasion of spines. Therefore, changes in synaptic transmission may have nothing to do with MT invasion of spines but rather they are due to changes in MT-based transport throughout the dendritic arbor.

Non-essential comments:

1. A major effect of KIF2C seems to be constraining the number of AMPARs in the postsynaptic membrane. However, its underlying mechanism remains uncharacterized – is it a result of inhibiting trafficking of the receptor to the synaptic site, its exocytosis into the plasma membrane, or destabilizing the receptor on the postsynaptic membrane? Can the authors provide any clarification on this?

2. Figure 2E:Is cLTP-induced increase in the spine width associated with an increase in the synaptic AMPARs and amplitude of mEPSCs? If so, would they also be blocked by shRNA?

3. Figure 3: N/A ratio changes may not indicate an increase in AMPAR-mediated synaptic transmission as it is not clear if NMDAR-mediated mEPSCs change or not. The authors should try to evaluate the changes in synaptic transmission by comparing the input-output curves between control and shRNA-treated neurons.

4. Figure 4: again, there should be a detailed analysis of the input-output curves in slices of WT and cKO mice. The individual traces on the left in 4E are not representative as the reduction of N/A ratio in cKO was not as obvious as shown in the bar graph on the right, and need to be changed. The impairment in LTP induced by a single HFS may not be sufficient. In order to further substantiate the impaired LTP, the authors should also attempt to maximize the LTP induced by 4xHFS.

5. Hippocampal re-expression of KIF2C rescues mEPSC, LTP, and behavioral phenotypes. These are nice sets of data suggesting KIF2C directly regulates the synaptic and behavioral phenotypes. However, I wonder whether the same KIF2C re-expression rescues baseline and BDNF-dependent MT invasion, which is an essential part of the conclusions together with synaptic phenotypes.

6. Biochemical work and ICC of hippocampal neurons suggests KIF2C is present postsynaptically, but it also colocalizes with Bassoon (Figure 1E). However, the authors discount the colocalization with a presynaptic label and only focus on the postsynaptic localization. A line scan is used to show colocalization, but this not sufficient. Colocalization analysis and Pearson's correlation coefficients should be computed to definitively show there is more colocalization with PSD95 than Bassoon.

7. Throughout Figure 6 and Figure 7 the authors use a KIF2C point mutant (G491A) that has been shown previously to have little MT depolymerization activity. However, they do not directly compare the point mutant to the WT KIF2C when they attempt to rescue the synaptic transmission phenotypes in the cKO mouse. Instead they compare each to a control and use a Student's t-test to indicate that the cKO + WT protein is significantly different than control, while the cKO + G491A is not. They need to compare cKO + WT directly to G491A and controls via ANOVA and show these two "rescues" are different. Moreover, addition of a WT control would be needed if they wanted to claim that the cKO + WT is the same as WT control (i.e. a full rescue).

8. In Figure 2 and 3 it is not clear why immunoblots are not used to show decreases in protein expression after knockdown. Only mRNA quantification is shown.

9. In Figure 2 KIF2C knockdown seems to have no effect on basal levels of spine density or spine head width. It is only after cLTP that significant differences are noted. However, in Figure 1D a Student's t-test is used, while in Figure 1E an ANOVA is used. Both of these graphs, as well as Figure 1G, should be analyzed with an ANOVA because more than two conditions are being compared. The minor differences (p<0.05) in Figure 1D and 1G are likely to be non-significant when analyzed with an ANOVA.

10. Bar graphs and scatter plots are used randomly throughout the paper. Scatter plots, or better yet SuperPlots (Lord et al., 2020, JCB, 219(6):e202001064), should be used throughout the paper.

11. The data in Figure 5E and F seem to be inconsistent. Both NMDAR and AMPAR appear to increase, although AMPAR to a greater extent than NMDARs, but the N/A ratio is significantly less in the cKO. Furthermore, only a p-value is provided. No statistical tests are mentioned.

12. In Figure 6B it is unclear why measurements of EB3 speed manually and using Tip Tracker software would result in such different growth speeds (EB3 speed vs. MT growth speed). The MT growth speeds are double the EB3 speeds. Shouldn't these be the same speeds?

13. In Figure 7C (lines 260-261) the authors claim the maintenance of fear memory is impaired in KIF2C cKO mice, however it appears that the maintenance is preserved – the two lines are parallel. Rather the fear memory is decreased throughout the periods of measurement. Also, these measures need to be analyzed with a repeated measures ANOVA, rather than a t-test.

14. Lines 320-21: The authors suggest that MTs bring AMPAR to the synapse. To my knowledge, this has not been shown here or elsewhere in the literature.

15. The model in Figure 8 is inaccurate. The authors want to show increased invasion of MTs into spines but show multiple simultaneous invasions. They never image MT dynamics in spines to show this.

16. The authors need to carefully review the writing contained within the manuscript, including the figure legends. The corresponding legend for Supplementary Information Figure S1 needs to be updated to reflect A-D as opposed to an abridged version A-B. Figure 4A includes "sgRNA" as opposed to "shRNA". Supplementary Information Figure S4 fails to mention B' in the legend and currently states "Number of strenching" as the title for the y-axis. There are also a number of confusing/distracting sentences within the body of the manuscript that need remedying.

17. In the description of Figure 2 (line 111), the authors state that spine morphology was examined at DIV 16-18 when the methods and figure legend state that this assessment occurred at DIV 18-20.

18. Line 135: Figure S1 is not referenced regarding the cultured neurons.

Reviewer #1:

This is a careful and thorough in vivo characterization of the synaptic function of the KIF2C protein using biochemical, cell biological, electrophysiological, mouse genetic, and behavioral analyses. The conclusions suggest that KIF2C regulates activity-dependent MT invasion, spine morphology, synaptic transmission, and synaptic plasticity. The rescue of synaptic and behavioral phenotypes by the use of KIF2C re-expression in the hippocampus is a key component of the manuscript. The overall conclusions are largely convincing and provide novel insights into the in vivo functions of KIF2C in the regulation of excitatory synaptic structure and function and cognitive behaviors.

Reviewer #2:

In this manuscript by Zhang et al., the authors report a set of exciting and novel data suggesting a critical role of KIF2C in AMPAR trafficking, synaptic plasticity and learning/memory related behaviours. This is a comprehensive study with clear logic and ample supporting data. Their results are of high quality and convincing.

Reviewer #3:

This manuscript is focused on how the kinesin protein KIF2C, a known microtubule depolymerizing protein, functions in hippocampal dendritic spine plasticity, cognition and behavior. The authors use many approaches, from electron microscopy to mouse behavioral analysis, to determine how KIF2C affects hippocampal neuron function. They suggest KIF2C plays a role in microtubule invasion of dendritic spines, which results in dendritic spine defects, deficits in synaptic transmission and behavior. Although interesting, some results are overinterpreted and not all conclusions are directly supported by the data that is presented.

The authors have provided data for the function of the microtubule depolymerizing kinesin, KIF2C/MCAK, in hippocampal neuron function, synaptic transmission, plasticity and mouse behavior. As such, many different techniques are used to determine the function of this protein. Previous work has implicated a similar family member, KIF2A, in axonal branching, however KIF2C appears to be functioning primarily in dendrites. This is an intriguing hypothesis and would provide important data for understanding the function of a microtubule depolymerase in nervous system function. Although copious amounts of data are shown and the manuscript is relatively clearly written, the authors oftentimes overinterpret the data and do not use the appropriate statistical tests and comparisons. The manuscript title and conclusions made in the Abstract and Discussion suggesting that the mechanism of KIF2C action is due to changes in microtubule invasion of dendritic spines is not substantiated. Because KIF2C conditional knock out neurons clearly have defects in microtubule dynamics throughout the dendritic shafts, many of the defects ascribed to microtubule invasion of spines are potentially indirect and may not be responsible for changes in synaptic transmission or behavior. More careful and appropriate analysis of their current data and additional experiments, specifically regarding the possibility of KIF2C leaving spines during synaptic activity and the dynamics of MT invasion of spines, would be needed to determine the mechanism of KIF2C action in dendrites.

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "KIF2C regulates synaptic plasticity and cognition in mice through dynamic microtubule depolymerization" for further consideration by eLife. Your revised article has been reviewed by 3 peer reviewers and the evaluation has been overseen by Anna Akhmanova as the Senior Editor.

The manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below:

Specifically, the authors need to provide details on the statistical methods used through the manuscript and the reasons why the authors could not perform the suggested live imaging experiments (see below for details).

Reviewer #1:

The authors have fully addressed my review comments. I do not have any remaining concerns.

Reviewer #2:

The authors have adequately addressed my concerns, and the manuscript can now be recommend for publication in the journal.

Reviewer #3:

The authors have taken the comments of the reviewers seriously and have responded with manuscript changes, additional experiments and moderated their interpretations of the data they present. These changes have strengthened the manuscript considerably. However, there are still a few points that the authors did not directly address.

In their response to Essential Revision #1 the authors quantified the distribution of KIF2C with regard to PSD-95 in different ways but the data in Figure 2H and I are still not very convincing. They didn't seem to make any measurements in the dendrite shaft to show that KIF2C was increasing in the shaft while decreasing in the spine. From these data it seems they can just conclude that KIF2C is not colocalizing as much with PSD-95 after cLTP. Additionally, they state that they tried overexpressing KIF2C but this caused damage to the neurons. However, in Figure 6E they show they expressed GFP-KIF2C in cKO neurons. Why could they not image these neurons live and quantify changes in KIF2C in the spine and shaft as requested?

The authors still used a Student t-test for Figure 2G and Figures 6F and G instead of ANOVA. Moreover, although they use ANOVA more appropriately in the revision, they have not indicated what post-tests they have run (Bonferroni, Tukey, etc.?) in their ANOVA analyses throughout the manuscript. These post-hoc tests should be included in the Methods and in the appropriate figure legends.

https://doi.org/10.7554/eLife.72483.sa1

Author response

Essential revisions:

1. An important part of the proposed mechanism of KIF2C action relies on the data in 2H and I. The authors argue that KIF2C is leaving dendritic spines and concentrating in the dendritic shaft after cLTP treatment. However, only colocalization of PSD95 and KIF2C is quantified, and this quantification is a percentage. It is not clear to what the percentage refers – the % of spines where they are colocalized? How is colocalization determined? What is the cutoff? Even if all of these measures were indicated, much more rigorous quantification would have to be done to provide convincing evidence that KIF2C is leaving spines and concentrating in the dendrite shaft after cLTP (as the show in their model in Figure 8). Specifically, both fixed cell imaging of endogenous KIF2C in a much more rigorous fashion, taking into account spine volume changes and comparison with another protein known to leave spines after cLTP. Imaging GFP-KIF2C in individual spines before and after cLTP and showing a subsequent decrease in the spine and increase in the shaft would also provide more compelling data.

We thank the reviewer for pointing this out. The colocalization refers to the percentage number of PSD-95-colocalized KIF2C puncta relative to total number of KIF2C puncta in dendritic protrusions. We totally agree with the reviewer that the increased PSD-95 puncta volume after cLTP would affect the result interpretating. We therefore dug into our data more carefully for more information and made more quantification. We have found that both the density or intensity (i.e., expression level/spine) of synaptic KIF2C was significantly reduced, percentage number of PSD-95-colocalized KIF2C puncta relative to total number of KIF2C puncta was reduced as well. Though the spines enlarged after cLTP, instead of increasing or unchanging, the percentage area of PSD-95-colocalized KIF2C relative to total KIF2C was decreased significantly, indicating that the spine volume change after cLTP was not the disturbing factor in our quantification. Taken together, we are confident that the imaging data did show the translocation of KIF2C out from spines after cLTP. The new data have been incorporated into Figure 2I together with corresponding descriptions in the main text (line 133-135).

The detailed quantification procedures have been incorporated into the Method section. Generally, fluorescence intensity was measured using region measurements function in MetaMorph. Single dendrites were selected randomly. Fixed threshold values were used to optimize highlighting of puncta in green (PSD-95) and red (KIF2C) channels and then applied to all images from the same experiment. For the colocalization quantification, the percentage area of KIF2C overlapping PSD-95 was performed using Measurement Colocalization function. For the quantification of synaptic KIF2C density and intensity, all the puncta on the green (PSD-95) channel were selected and used as a mask for red channel (KIF2C) overlapping to filter out the PSD-95-colocalized KIF2C puncta automatically, using the Process function, and Integrated Morphometric Analysis function was used to identify the puncta and measure their properties.

We have also overexpressed KIF2C in hippocampal neurons and checked its synaptic localization before or after cLTP treatment, according to the reviewer’s suggestion. However, we found that KIF2C overexpression impaired the postsynaptic structure largely, and neurons did not respond to cLTP stimulation. In fact, we found that KIF2C overexpression in WT neurons did more damage than in cKO neurons, as it could not be expressed for too long time in vitro or in vivo. Perhaps overloading of KIF2C in neurons would lead to an overactivated microtubule depolymerization. We suspect that KIF2C's expression in neuron needs to be in a precise balance in order to maintain normal physiological activity, with a mechanism that we have not understood yet.

2. The authors overinterpret the data from Figure 6C. In this experiment they treated cells with BDNF, fixed the neurons and labeled them with an antibody to dynamic MTs (tyrosinated tubulin). They show that the percent of spines containing a MT increased with BDNF in WT neurons but not in controls. They also show that cKO neurons have slightly more spines containing MTs. This methodology is useful, in addition to live-cell imaging of EB3 entries into spines, but it is difficult to quantify MT invasions because tyrosinated tubulin is also cytoplasmic and spines can change sizes with treatment. Thus, it is difficult to determine which spines contain a MT vs. just increased volume of tyrosinated tubulin. Without live cell imaging of labeled EB3 or tubulin these data are not sufficient to make claims about MT invasion. Also, only live cell imaging would be able to differentiate increased invasion of MTs vs. increased retention of MTs in spines. It is unclear what is happening in the KIF2C cKO neurons. Thus, they can't claim in the discussion that "KIF2C deficiency also increased the frequency of MT invasion under basal conditions" (line 318).

We thank the reviewer for the thoughtful analysis and for the suggestion. Our previous result did not provide direct evidence that KIF2C affects MT spine invasion. To just this question, we performed the live-imaging of EB3 and quantified the MT spine invasion events. Our result showed that without KIF2C, the MT invasion events in average each spine increased about 2 folds in an hour. We also provided a representative Kymograph and time-frame images showing a single MT invasion event. Therefore, we feel confident that KIF2C did affect MT invasion under basal condition. The new result has now been incorporated into Figure 6C together with corresponding descriptions in the main text (line 237-238).

3. In addition to the points made in #2 the fact that MT dynamics are affected in the dendrites suggests that changes in MT invasion of spines are indirect. KIF2C is clearly affecting MT dynamics throughout the neuron. Thus, one would expect changes in MT invasion of spines. Therefore, changes in synaptic transmission may have nothing to do with MT invasion of spines but rather they are due to changes in MT-based transport throughout the dendritic arbor.

We thank the reviewer for pointing this out. As our response for #2, we have seen the change in MT invasion by live imaging in cKO mice. We also agree with the reviewer that even though MT invasion of spines is affected, the defects in dendrites also count. Currently, we don’t have a clean and clear method to distinguish KIF2C’s function in dendrites or in spines. KIF2C’s translocation after cLTP induction would be a touch to its regulatory mechanism in spines, but currently we are unable to strip it out from dendritic factor. In order to avoid overinterpretation of the results, we have revised the inaccurate deduction in the article (line 39-42, 213-214, 265-267) as well as in the title, and made a discussion about this issue in the main text (line 335-338, 358-366, 367-388).

Non-essential comments:

1. A major effect of KIF2C seems to be constraining the number of AMPARs in the postsynaptic membrane. However, its underlying mechanism remains uncharacterized – is it a result of inhibiting trafficking of the receptor to the synaptic site, its exocytosis into the plasma membrane, or destabilizing the receptor on the postsynaptic membrane? Can the authors provide any clarification on this?

It is interesting to find out how KIF2C regulates surface expression of AMPA receptors. Our results suggest that KIF2C regulates microtubule depolymerization and stability in hippocampal neurons (Figure 6A). Microtubule-dependent trafficking has been typically associated with long-range transport along the dendrites, supporting the continuous supply and redistribution of AMPARs among synapses (1-4) (5, 6), which can also be regulated by neuronal activity (1, 7, 8). There has also been report showing microtubule dynamic stability regulates AMPARs postsynaptic localization and synaptic plasticity(9). We therefore speculate that KIF2C constrain AMPARs trafficking to the synaptic sites by microtubule depolymerization and stability. However, other possibilities are not excluded. This could be a very interesting topic for our follow up study.

2. Figure 2E:Is cLTP-induced increase in the spine width associated with an increase in the synaptic AMPARs and amplitude of mEPSCs? If so, would they also be blocked by shRNA?

It has been shown that cLTP induction is characterized by increases in the frequency and amplitude of spontaneous mEPSCs and elevation of CREB phosphorylation (10), altering the size and/or shape of the specialized postsynaptic compartment of the dendritic spine(11-13). Synaptic AMPARs recruitment is required for cLTP-induced spine expansion (13). Our data showed that knockdown of KIF2C blocked the cLTP-induced increase of dendritic spine width (Figure 2E), suggestion a change in synaptic AMPARs and mEPSC amplitude. To direct answer this question, we examined the mEPSCs before and after cLTP in KIF2C knockdown neurons, and found that shKIF2C blocked the cLTP-induced raise of synaptic AMPARs and mEPSCs amplitude. The new results were added in our revised manuscript (Figure 2—figure supplement 1E, F) (line 148-151).

3. Figure 3: N/A ratio changes may not indicate an increase in AMPAR-mediated synaptic transmission as it is not clear if NMDAR-mediated mEPSCs change or not. The authors should try to evaluate the changes in synaptic transmission by comparing the input-output curves between control and shRNA-treated neurons.

We thank the reviewer for the suggestion. In the revised manuscript, we examined the input-output curve of AMPA/NMDA receptor-mediated EPSCs in control and shKIF2C-treated neurons. We found that KIF2C knockdown alters the input-output curves of AMPA receptor but not that of NMDA receptor, indicating that KIF2C shRNA-caused EPSC amplitude alteration is AMPA receptor-mediated. The new result has now been incorporated into Figure 3D-E together with corresponding descriptions in the main text (line 159-163).

4. Figure 4: again, there should be a detailed analysis of the input-output curves in slices of WT and cKO mice. The individual traces on the left in 4E are not representative as the reduction of N/A ratio in cKO was not as obvious as shown in the bar graph on the right, and need to be changed. The impairment in LTP induced by a single HFS may not be sufficient. In order to further substantiate the impaired LTP, the authors should also attempt to maximize the LTP induced by 4xHFS.

We thank the reviewer for the suggestion. We examined the input-output curve of AMPA/NMDA receptor-mediated EPSCs in slices of WT and KIF2C cKO mice. Consistent with the shRNA knockdown result, KIF2C knockout alters the input-output curves of AMPA receptor but not that of NMDA receptor, indicating that KIF2C deficiency-caused EPSC amplitude alteration is AMPA receptor-mediated. The new result has now been incorporated into Figure 5D-E together with corresponding descriptions in the main text (line 200-202).

We suppose that the individual traces the review mentioned is on the left in Figure 5E instead of 4E. They have now been replaced by new ones (Figure 5C in the revised manuscript).

Moreover, we examined 4xHFS induced LTP between WT and cKO mice as the reviewer suggested. Similar as the 1xHFS induction, the LTP magnitude was also attenuated in cKO hippocampal slices even 2 hrs after LTP induction, indicating a long-term impairment of LTP in the cKO mice as well. The new result has now been incorporated into Figure 5H together with corresponding descriptions in the main text (line 208-210).

5. Hippocampal re-expression of KIF2C rescues mEPSC, LTP, and behavioral phenotypes. These are nice sets of data suggesting KIF2C directly regulates the synaptic and behavioral phenotypes. However, I wonder whether the same KIF2C re-expression rescues baseline and BDNF-dependent MT invasion, which is an essential part of the conclusions together with synaptic phenotypes.

We thank the reviewer for pointing this out. Following the suggestion, we over-expressed KIF2C in cKO neurons and examined the synaptic phenotypes carefully. We found that KIF2C re-expression was able to effectively rescue the baseline and BDNF-dependent MT invasion. The new result has now been incorporated into Figure 6E together with corresponding descriptions in the main text (line 243-247).

6. Biochemical work and ICC of hippocampal neurons suggests KIF2C is present postsynaptically, but it also colocalizes with Bassoon (Figure 1E). However, the authors discount the colocalization with a presynaptic label and only focus on the postsynaptic localization. A line scan is used to show colocalization, but this not sufficient. Colocalization analysis and Pearson's correlation coefficients should be computed to definitively show there is more colocalization with PSD95 than Bassoon.

We agree with the reviewer that KIF2C is localized both pre-synaptically and post-synaptically. The line scan result showed that KIF2C was colocalized with both PSD-95 and Bassoon. KIF2C must have played some roles in a pre-synaptic way. But in our electrophysiological experiments, we checked the paired-pulse ratios in hippocampus after KIF2C knockout and didn’t find any change (Figure 5B). Post-synaptic knockdown of KIF2C in CA1 neurons didn’t affect the paired-pulse ratios of CA3 neurons (Figure 3B). It is a hint that KIF2C may not be involved in the release probability. We didn’t perform the PDS-95 or Bassoon colocalization quantification because in our study we focused mainly on its function in post-synapse or dendrites. We found that the post-synaptic knockdown of KIF2C is sufficient to abolish the LTP in CA3-CA1 pathway (Figure 3F) and post-synaptic re-expression of KIF2C expression in CA1 could effectively rescue the LTP-defects in CA3-CA1 pathway (Figure 6G). Therefore, we think that at least KIF2C is an important post-synaptic regulator in neuron plasticity.

7. Throughout Figure 6 and Figure 7 the authors use a KIF2C point mutant (G491A) that has been shown previously to have little MT depolymerization activity. However, they do not directly compare the point mutant to the WT KIF2C when they attempt to rescue the synaptic transmission phenotypes in the cKO mouse. Instead they compare each to a control and use a Student's t-test to indicate that the cKO + WT protein is significantly different than control, while the cKO + G491A is not. They need to compare cKO + WT directly to G491A and controls via ANOVA and show these two "rescues" are different. Moreover, addition of a WT control would be needed if they wanted to claim that the cKO + WT is the same as WT control (i.e. a full rescue).

We thank the reviewer for the suggestion. In order to make our data more readable, we have compiled the data together and re-analyzed the result by one-way ANOVA. The results are consistent with previous ones and there was significant difference between WT and G491A rescue (Figure 6F-G, Figure 7F-H).

The re-expression of KIF2C in cKO mice was achieved via viral infection system, through which the expression level of KIF2C could be higher or lower than its endogenous level. Therefore, the phenotype readout of the “rescued mice” could be different to the WT mice. The aim of our rescue experiment was to prove the function of KIF2C in synaptic plasticity and cognition, and we did not claim “full rescue”. Moreover, according to our previous results, the expression level of KIF2C need to be finely tuned in neurons. Long-time overdosing of KIF2C affects synaptic plasticity or even cause deadly effect in neurons. In our study, we used doxycyline-induced expression to limit the duration and level of KIF2C expression. Even though, we did not speculate to reach a “full rescue” through viral-mediated overexpression but not the knockin approach. Therefore, we didn’t add the WT control in the rescue experiment.

8. In Figure 2 and 3 it is not clear why immunoblots are not used to show decreases in protein expression after knockdown. Only mRNA quantification is shown.

We have now added the immunoblot examination of KIF2C expression in Figure 2—figure supplement 1A, the result is consistent with the RT-PCR examination.

9. In Figure 2 KIF2C knockdown seems to have no effect on basal levels of spine density or spine head width. It is only after cLTP that significant differences are noted. However, in Figure 1D a Student's t-test is used, while in Figure 1E an ANOVA is used. Both of these graphs, as well as Figure 1G, should be analyzed with an ANOVA because more than two conditions are being compared. The minor differences (p<0.05) in Figure 1D and 1G are likely to be non-significant when analyzed with an ANOVA.

We suppose the panels the reviewer mentioned referred to those in Figure 2. We now have re-analyzed the data in Figure 2D by One-way ANOVA and the results are consistent. For Figure 2G, the bar chart we presented was misleading. What we actuary compared was the KIF2C expression level between the ECS and cLTP-treated groups in different fractions. We have now re-plotted the bar chart for clearer representation (Figure 2G).

10. Bar graphs and scatter plots are used randomly throughout the paper. Scatter plots, or better yet SuperPlots (Lord et al., 2020, JCB, 219(6):e202001064), should be used throughout the paper.

Thank you for pointing this out. We unified the chart format into scatter plot with bar graph in the revised manuscript.

11. The data in Figure 5E and F seem to be inconsistent. Both NMDAR and AMPAR appear to increase, although AMPAR to a greater extent than NMDARs, but the N/A ratio is significantly less in the cKO. Furthermore, only a p-value is provided. No statistical tests are mentioned.

We thank the reviewer for pointing this out. We think the immunoblotting and the electrophysiological approaches have different sensitivities and different experimental range so the results from the two experiments cannot be calculated and compared directly. To better address this question, we analyzed the input-output curve of AMPA/NMDA receptor-mediated EPSCs to better illustrate the changes of AMPARs and NMDARs in the patch clamp. KIF2C knockout alters the input-output curves of AMPA receptor but not that of NMDA receptor, indicating that KIF2C deficiency-caused EPSC amplitude alteration is AMPA receptor-mediated. The new result has now been incorporated into Figure 5D-E together with corresponding descriptions in the main text (line 200-202). We used Student’s t-test for statistical comparison.

12. In Figure 6B it is unclear why measurements of EB3 speed manually and using Tip Tracker software would result in such different growth speeds (EB3 speed vs. MT growth speed). The MT growth speeds are double the EB3 speeds. Shouldn't these be the same speeds?

We used EB3 to mark the +TIPs of MT and track the growing MT ends in live imaging. The EB3 speed we measured actually is the average velocity of EB3 moving (i.e., the displacement of EB3 divided by the time interval). As it cannot be measured by the software, we manually located EB3 at the beginning and at end of the live imaging and measured its displacement. The MT growth speed is the average forward moving speed of EB3. The software traced the moving of EB3 puncta and filters out the shrinking movement, calculates the average forward moving speed (i.e., total forward moving distances divided by the forward moving time). That’s why the MT growth speed is much higher than the EB3 speed. The detailed quantification procedures and parameters have been provided in the method section (Live-cell imaging and microtubule dynamics analysis, line 227-230, 510-527).

13. In Figure 7C (lines 260-261) the authors claim the maintenance of fear memory is impaired in KIF2C cKO mice, however it appears that the maintenance is preserved – the two lines are parallel. Rather the fear memory is decreased throughout the periods of measurement. Also, these measures need to be analyzed with a repeated measures ANOVA, rather than a t-test.

We thank the reviewer for the careful analysis. The freezing levels of WT and cKO mice did show similar decreasing tendencies. We re-checked the memory maintenance by calculating the percentage change of the freezing time between two consecutive times (i.e. (Freezing time24h- Freezing time7d)/ Freezing time24h to contextual cue and (Freezing time48h- Freezing time8d)/ Freezing time48h to conditioned stimulus) (Figure 7—figure supplement 1E) and there was no significant difference, showing the preserved maintenance of fear memory. We have corrected our mis-interpretation in the text (line 291-294).

Moreover, we have used RM ANOVA to analyze data in the revised submission, the result is consistent with our previous one.

14. Lines 320-21: The authors suggest that MTs bring AMPAR to the synapse. To my knowledge, this has not been shown here or elsewhere in the literature.

We thank the reviewer for pointing this out. We should draw our conclusions more carefully. We have now corrected the inappropriate description in the revised manuscript (line 355-359).

15. The model in Figure 8 is inaccurate. The authors want to show increased invasion of MTs into spines but show multiple simultaneous invasions. They never image MT dynamics in spines to show this.

We thank the reviewer for pointing this out. It is difficult to distinguish whether the increase in MT invasion frequency take place in the same spine or just the increase in invasion probability in a population of spines or both. By now, we cannot tell between the two possibilities, so we took down the schematic diagram.

16. The authors need to carefully review the writing contained within the manuscript, including the figure legends. The corresponding legend for Supplementary Information Figure S1 needs to be updated to reflect A-D as opposed to an abridged version A-B. Figure 4A includes "sgRNA" as opposed to "shRNA". Supplementary Information Figure S4 fails to mention B' in the legend and currently states "Number of strenching" as the title for the y-axis. There are also a number of confusing/distracting sentences within the body of the manuscript that need remedying.

We thank the reviewer for pointing this out. We have now revised the manuscript thoroughly and corrected the inappropriate wording or descriptions carefully.

17. In the description of Figure 2 (line 111), the authors state that spine morphology was examined at DIV 16-18 when the methods and figure legend state that this assessment occurred at DIV 18-20.

We are sorry for the mistake. We have now corrected the date.

18. Line 135: Figure S1 is not referenced regarding the cultured neurons.

We are sorry for the mistake. We had referenced Figure 2—figure supplement 1A but not the other panels in the text. We have now stated the other panels of Figure 2—figure supplement 1A in the corresponding part of the manuscript (line 120-123).

References:

1. F. J. Hoerndli et al., Kinesin-1 regulates synaptic strength by mediating the delivery, removal, and redistribution of AMPA receptors. Neuron 80, 1421-1437 (2013).

2. F. F. Heisler et al., GRIP1 interlinks N-cadherin and AMPA receptors at vesicles to promote combined cargo transport into dendrites. Proc Natl Acad Sci U S A 111, 5030-5035 (2014).

3. M. Setou et al., Glutamate-receptor-interacting protein GRIP1 directly steers kinesin to dendrites. Nature 417, 83-87 (2002).

4. C. C. Hoogenraad, A. D. Milstein, I. M. Ethell, M. Henkemeyer, M. Sheng, GRIP1 controls dendrite morphogenesis by regulating EphB receptor trafficking. Nat Neurosci 8, 906-915 (2005).

5. M. I. Monteiro et al., The kinesin-3 family motor KLP-4 regulates anterograde trafficking of GLR-1 glutamate receptors in the ventral nerve cord of Caenorhabditis elegans. Mol Biol Cell 23, 3647-3662 (2012).

6. H. Shin et al., Association of the kinesin motor KIF1A with the multimodular protein liprin-alpha. J Biol Chem 278, 11393-11401 (2003).

7. C. Maas et al., Synaptic activation modifies microtubules underlying transport of postsynaptic cargo. Proc Natl Acad Sci U S A 106, 8731-8736 (2009).

8. Y. Gutierrez et al., KIF13A drives AMPA receptor synaptic delivery for long-term potentiation via endosomal remodeling. J Cell Biol 220, (2021).

9. S. Uchida et al., Learning-induced and stathmin-dependent changes in microtubule stability are critical for memory and disrupted in ageing. Nat Commun 5, 4389 (2014).

10. A. Malgaroli, R. W. Tsien, Glutamate-induced long-term potentiation of the frequency of miniature synaptic currents in cultured hippocampal neurons. Nature 357, 134-139 (1992).

11. E. Fifkova, A possible mechanism of morphometric changes in dendritic spines induced by stimulation. Cell Mol Neurobiol 5, 47-63 (1985).

12. A. Vlachos et al., Synaptopodin regulates plasticity of dendritic spines in hippocampal neurons. J Neurosci 29, 1017-1033 (2009).

13. D. A. Fortin et al., Long-term potentiation-dependent spine enlargement requires synaptic Ca2+-permeable AMPA receptors recruited by CaM-kinase I. J Neurosci 30, 11565-11575 (2010).

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

The manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below:

Specifically, the authors need to provide details on the statistical methods used through the manuscript and the reasons why the authors could not perform the suggested live imaging experiments (see below for details).

Reviewer #3:

The authors have taken the comments of the reviewers seriously and have responded with manuscript changes, additional experiments and moderated their interpretations of the data they present. These changes have strengthened the manuscript considerably. However, there are still a few points that the authors did not directly address.

In their response to Essential Revision #1 the authors quantified the distribution of KIF2C with regard to PSD-95 in different ways but the data in Figure 2H and I are still not very convincing. They didn't seem to make any measurements in the dendrite shaft to show that KIF2C was increasing in the shaft while decreasing in the spine. From these data it seems they can just conclude that KIF2C is not colocalizing as much with PSD-95 after cLTP. Additionally, they state that they tried overexpressing KIF2C but this caused damage to the neurons. However, in Figure 6E they show they expressed GFP-KIF2C in cKO neurons. Why could they not image these neurons live and quantify changes in KIF2C in the spine and shaft as requested?

The authors still used a Student t-test for Figure 2G and Figures 6F and G instead of ANOVA. Moreover, although they use ANOVA more appropriately in the revision, they have not indicated what post-tests they have run (Bonferroni, Tukey, etc.?) in their ANOVA analyses throughout the manuscript. These post-hoc tests should be included in the Methods and in the appropriate figure legends.

We thank the reviewer for pointing this out. we have added the quantitative data of KIF2C level in dendritic shafts after cLTP stimulation and clearly see an increase of KIF2C expression in dendrites accompanying a reduction in spines (Figure 2I), corresponding text was added to describe this finding (Line 133-138, 581-582).

We had tested KIF2C overexpression in WT and cKO neurons and slices with biochemical and electrophysiological experiments in our pre-tests, and finally found that neurons survive far less in wild type than in cKO, which was less than four days for cKO neurons in in vivo experiments and less than two dasys in cultured cKO neurons. For our rescue experiments in cKO neurons, overexpression of KIF2C(WT) was controlled in a limited time, or else a highly expressed KIF2C level would be toxic to cKO neurons. However, we found that the lowly expressed KIF2C in healthy cKO neurons showed very weaker fluorescent signal which was too dim to be detected under microscope. We therefore think it’s not suitable for the suggested live-imaging experiment. That’s why we used GFP antibody to detect KIF2C expression in the rescue experiment (Figure 6E).

For Figure 6F, G, we have re-analyzed the data by one-way ANOVA and the results are consistent with previous ones (line 1224 and 1234, Figure 6F, G). We have also carefully looked into our data, and added post-hoc tests in the Methods (line 814-821) and in the appropriate figure legends. For Figure 2G, what we actuary compared was the KIF2C expression level between the ECS and cLTP-treated groups in each fraction. We have now re-plotted the bar chart for clearer representation (Figure 2G).

https://doi.org/10.7554/eLife.72483.sa2

Article and author information

Author details

  1. Rui Zheng

    1. Department of Neurobiology and Department of Rehabilitation of the Children’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
    2. NHC and CAMS Key Laboratory of Medical Neurobiology, Ministry of Education Frontier Science Center for Brain Research and Brain Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China
    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Writing – original draft
    Contributed equally with
    Yonglan Du
    Competing interests
    No competing interests declared
  2. Yonglan Du

    1. Department of Neurobiology and Department of Rehabilitation of the Children’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
    2. NHC and CAMS Key Laboratory of Medical Neurobiology, Ministry of Education Frontier Science Center for Brain Research and Brain Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China
    Contribution
    Data curation, Formal analysis, Investigation, Methodology, Software, Validation
    Contributed equally with
    Rui Zheng
    Competing interests
    No competing interests declared
  3. Xintai Wang

    NHC and CAMS Key Laboratory of Medical Neurobiology, Ministry of Education Frontier Science Center for Brain Research and Brain Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China
    Contribution
    Formal analysis, Funding acquisition, Methodology, Software, Validation
    Competing interests
    No competing interests declared
  4. Tailin Liao

    1. Department of Neurobiology and Department of Rehabilitation of the Children’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
    2. NHC and CAMS Key Laboratory of Medical Neurobiology, Ministry of Education Frontier Science Center for Brain Research and Brain Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China
    Contribution
    Formal analysis, Methodology, Validation
    Competing interests
    No competing interests declared
  5. Zhe Zhang

    1. Department of Neurobiology and Department of Rehabilitation of the Children’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
    2. NHC and CAMS Key Laboratory of Medical Neurobiology, Ministry of Education Frontier Science Center for Brain Research and Brain Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China
    Contribution
    Formal analysis, Validation
    Competing interests
    No competing interests declared
  6. Na Wang

    1. Department of Neurobiology and Department of Rehabilitation of the Children’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
    2. NHC and CAMS Key Laboratory of Medical Neurobiology, Ministry of Education Frontier Science Center for Brain Research and Brain Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China
    Contribution
    Conceptualization, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1438-1508
  7. Xiumao Li

    Department of Orthopedic Surgery, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
    Contribution
    Methodology, Validation
    Competing interests
    No competing interests declared
  8. Ying Shen

    Department of Physiology and Department of Neurology of First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
    Contribution
    Supervision, Validation, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7034-5328
  9. Lei Shi

    JNU-HKUST Joint Laboratory for Neuroscience and Innovative Drug Research, Jinan University, Guanzhou, China
    Contribution
    Validation, Visualization, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8695-3432
  10. Jianhong Luo

    1. Department of Neurobiology and Department of Rehabilitation of the Children’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
    2. NHC and CAMS Key Laboratory of Medical Neurobiology, Ministry of Education Frontier Science Center for Brain Research and Brain Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China
    Contribution
    Funding acquisition, Validation, Writing – review and editing
    For correspondence
    luojianhong@zju.edu.cn
    Competing interests
    No competing interests declared
  11. Jun Xia

    Division of Life Science and The Brain and Intelligence Research Institute, The Hong Kong University of Science and Technology, Hong Kong, China
    Contribution
    Validation, Writing – review and editing
    For correspondence
    jxia@ust.hk
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9308-2188
  12. Ziyi Wang

    Innovative Institute of Basic Medical Sciences of Zhejiang University (Yuhang), Hangzhou, China
    Contribution
    Data curation, Formal analysis, Methodology, Resources, Supervision, Validation, Writing – review and editing
    For correspondence
    mtray@qq.com
    Competing interests
    No competing interests declared
  13. Junyu Xu

    1. Department of Neurobiology and Department of Rehabilitation of the Children’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
    2. NHC and CAMS Key Laboratory of Medical Neurobiology, Ministry of Education Frontier Science Center for Brain Research and Brain Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China
    Contribution
    Conceptualization, Data curation, Formal analysis, Funding acquisition, Project administration, Resources, Software, Supervision, Validation, Writing – original draft, Writing – review and editing
    For correspondence
    junyu@zju.edu.cn
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1911-3553

Funding

National Natural Science Foundation of China (31970902)

  • Junyu Xu

National Natural Science Foundation of China (3192010300)

  • Jianhong Luo

National Natural Science Foundation of China (32000692)

  • Xintai Wang

National Natural Science Foundation of China (31871418)

  • Jianhong Luo

National Natural Science Foundation of China (81821091)

  • Jianhong Luo

Natural Science Foundation of Zhejiang Province (LD19H090002)

  • Jianhong Luo

Natural Science Foundation of Zhejiang Province (LR19H090001)

  • Junyu Xu

Special Project for Research and Development in Key areas of Guangdong Province (2019B030335001)

  • Junyu Xu

Research Grants Council of the Hong Kong SAR, China (16103520)

  • Jun Xia

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

Acknowledgements

We are grateful to research assistant Shuang-shuang Liu from the Core Facilities of Zhejiang University School of Medicine, Dr. San-hua Fang and research assistant Dao-hui Zhang from the Core Facilities of Zhejiang University Institute of Neuroscience, and research assistant Bei-bei Wang from the center of Cryo-Electron Microscopy of Zhejiang University for the operation of the instruments. We are grateful to Dr. Xiao-dong Wang and Xiao-Jun Wang from School of Brain Science and Brain Medicine of Zhejiang University for the guidance on statistical methods.

Ethics

All animal experiments were performed in accordance with the ethical guidelines of the Zhejiang University Animal Advisory Committee (2020-19500#), and were in complete compliance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals. All surgeries were performed under sodium pentobarbital anesthesia, and every effort was made to minimize suffering.

Senior Editor

  1. Anna Akhmanova, Utrecht University, Netherlands

Reviewing Editor

  1. Eunjoon Kim, Institute for Basic Science, Korea Advanced Institute of Science and Technology, Republic of Korea

Reviewer

  1. Yu-Tian Wang

Publication history

  1. Received: July 26, 2021
  2. Preprint posted: August 5, 2021 (view preprint)
  3. Accepted: February 1, 2022
  4. Version of Record published: February 9, 2022 (version 1)

Copyright

© 2022, Zheng 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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  1. Rui Zheng
  2. Yonglan Du
  3. Xintai Wang
  4. Tailin Liao
  5. Zhe Zhang
  6. Na Wang
  7. Xiumao Li
  8. Ying Shen
  9. Lei Shi
  10. Jianhong Luo
  11. Jun Xia
  12. Ziyi Wang
  13. Junyu Xu
(2022)
KIF2C regulates synaptic plasticity and cognition in mice through dynamic microtubule depolymerization
eLife 11:e72483.
https://doi.org/10.7554/eLife.72483

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    Funding: financial support for this work from a Vanier Canada Graduate Scholarship from the Canadian Institutes of Health Research (GIG), an Ontario Graduate Scholarship (SS), a Restracomp Research Fellowship provided by the Hospital for Sick Children (SS), an Institutional Research Chair in Neuroinformatics (MD), as well as a Natural Sciences and Engineering Research Council CREATE grant (MD).