Tingting Lou’s research while affiliated with University of Tsukuba and other places

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Publications (3)


Cdkl5 KO mice recapitulate sleep disturbances observed in CDD patients. (A–D) Hourly time (A), total time (B), numbers of episodes (C), and mean durations of episodes (D) of wakefulness, NREMS, and REMS in young WT (n = 13) and Cdkl5 KO mice (n = 13). Time points are double-plotted to facilitate visual detection of daily variation. ZT, Zeitgeber time. (E–H) Hourly time (E), total time (F), numbers of episodes (G), and mean durations of episodes (H) of wakefulness, NREMS, and REMS in aged WT (n = 12) and Cdkl5 KO mice (n = 10). Time points are double-plotted to facilitate visual detection of daily variation. (I) Number of transitions between wakefulness, NREMS, and REMS per 24 h in young (up) and aged (down) WT and KO mice. Arrows show the direction of transitions, and numbers show the average frequency of transitions. (J) Mean NREMS latency in young (up) and aged (down) WT and KO mice. (K) Mean REMS latency in young (up) and aged (down) WT and KO mice. Data are the mean ± SEM. Two-way repeated measures ANOVA with Sidak’s test (A,E,I) and unpaired t-test (B–D,F–H,J,K). * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001. ns, not significant.
Cdkl5 KO mice exhibit altered baseline EEG activity. (A,B) Mean NREMS delta power in every hour (A) and per 6 h block (B) in young WT (n = 13) and Cdkl5 KO mice (n = 13). (C,D) Mean NREMS delta power in every hour (C) and per 6 h block (D) in aged WT (n = 11) and Cdkl5 KO mice (n = 9). (E–J) EEG power spectra and frequency bands during wakefulness (E,F), NREMS (G,H), and REMS (I,J) in young WT and KO mice. (K–P) EEG power spectra and frequency bands during wakefulness (K,L), NREMS (M,N), and REMS (O,P) in aged WT and KO mice. (Q–V) EEG frequency band ratios during wakefulness, NREMS, and REMS in young (Q–S) and aged (T–V) WT and KO mice. Data are the mean ± SEM. Two-way repeated measures ANOVA with Sidak’s test (A–P) and unpaired t-test (Q–V). * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001. ns, not significant.
Loss of CDKL5 does not exacerbate the rate of age-associated changes in sleep behavior and EEG spectra in mice. (A,B) Hourly time in wakefulness, NREMS, and REMS in WT (young, n = 13; aged, n = 12) (A) and Cdkl5 KO (young, n = 13; aged, n = 10) (B) mice. (C,D) Total time in wakefulness, NREMS, and REMS in WT (young, n = 13; aged, n = 12) (C) and Cdkl5 KO (young, n = 13; aged, n = 10) (D) mice. (E) Normalized time, episode number, and episode duration in wakefulness, NREMS, and REMS of aged WT and KO mice. Normalized values were calculated as [(aged-young average)/young average]% in 24 h. (F,G) EEG power spectra during wakefulness, NREMS, and REMS in WT (young, n = 13; aged, n = 11) (F) and KO (young, n = 13; aged, n = 9) (G) mice. (H–M) EEG frequency bands during wakefulness, NREMS, and REMS in WT (H,J,L) and KO (I,K,M) mice. (N) Normalized EEG frequency band powers in NREMS, REMS, and wakefulness of aged WT and KO mice. Normalized values were calculated as [(aged-young average)/young average]% in 24 h. Data are mean ± SEM. Two-way repeated measures ANOVA with Sidak’s test (A,B, F–M) and unpaired t-test (C–E,N). * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001. ns, not significant.
Cdkl5 KO mice exhibited a normal homeostatic sleep response and circadian rhythm. (A,B) Hourly NREMS time of young (WT, n = 13; KO, n = 13) (A) and aged (WT, n = 12; KO, n = 10) (B) WT and Cdkl5 KO mice before (baseline, BL) and after sleep deprivation (SD). (C,D) Amount of NREMS in young (C) and aged (D) WT and KO mice during 20 h recovery period and time-matched baseline period. (E,F) Time course of cumulative NREMS gain in young (E) and aged (F) WT and KO mice across 20 h recovery period. (G) Hourly NREMS delta power density of young WT and KO mice before and after sleep deprivation. (H,I) Normalized hourly (H) and mean (I) NREM delta power of young WT and KO mice during 20 h recovery period after sleep deprivation. (J) Hourly NREMS delta power density of aged WT and KO mice before and after sleep deprivation. (K,L) Normalized hourly (K) and mean (L) NREM delta power of aged WT and KO mice during 20 h recovery period after sleep deprivation. (M) Sleep latency after sleep deprivation in young (up) and aged (down) WT and KO mice. (N,P) Representative double-plotted actograms of an aged WT (N) and KO (O) mice under LD and DD conditions. (P) Average circadian free-running periods in DD in aged WT (n = 12) and KO (n =14) mice. Data are the mean ± SEM. Two-way repeated measures ANOVA with Sidak’s test (A,B,E,F,H,K), paired t-test (C–D), and unpaired t-test (I,L,M,P). * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001. ns, not significant.
Selective loss of CDKL5 in glutamatergic neurons results in sleep disturbances. (A–D) Hourly time (A), total time (B), numbers of episodes (C), and mean durations of episodes (D) of wakefulness, NREMS, and REMS in WT (n = 7) and Vglut2-cKO mice (n = 9). Time points are double-plotted to facilitate visual detection of daily variation. (E) Number of transitions between wakefulness, NREMS, and REMS per 24 h in WT and Vglut2-cKO mice. (F,G) Mean NREMS (F) and REMS (G) latency in WT (n = 9) and Vglut2-cKO (n = 9) mice. (H,K) Hourly time (H), total time (I), numbers of episodes (J), and mean durations of episodes (K) of wakefulness, NREMS, and REMS in WT (n = 9) and Vgat-cKO mice (n = 9). Time points are double-plotted to facilitate visual detection of daily variation. (L) Number of transitions between wakefulness, NREMS, and REMS per 24 h in WT and Vgat-cKO mice. (M,N) Mean NREMS (M) and REMS (N) latency in WT (n = 9) and Vgat-cKO (n = 9) mice. Data are the mean ± SEM. Two-way repeated measures ANOVA with Sidak’s test (A,E,H,L) and unpaired t-test (B–D,F,G,I–K,M,N). * p < 0.05; ** p < 0.01; *** p < 0.001; ns, not significant.

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Cdkl5 Knockout Mice Recapitulate Sleep Phenotypes of CDKL5 Deficient Disorder
  • Article
  • Full-text available

April 2025

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17 Reads

Liqin Cao

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Xin Zhang

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Tingting Lou

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[...]

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Cyclin-dependent kinase-like 5 (CDKL5) deficiency disorder (CDD) is an X-linked rare neurodevelopmental disorder associated with severe sleep disturbances. However, little is known about the mechanisms underlying sleep disturbances in CDD patients. Here, we employed the electroencephalogram (EEG) recording to characterize sleep–wake behaviors and EEG activity in male CDKL5-deficient mice. We found that young adult and middle-aged Cdkl5 knockout (KO) mice recapitulated sleep phenotypes in patients with CDD, including difficulties in initiating and maintaining sleep, reduction in total sleep time, and frequent night awakenings. Cdkl5 KO mice exhibited pre-sleep arousal, but normal circadian rhythm and homeostatic sleep response. Conditional knockout (cKO) of Cdkl5 in glutamatergic neurons resulted in reduced sleep time and difficulty in sleep maintenance. Further, the rate of age-associated decline in sleep and EEG activity in Cdkl5 KO mice was comparable to that of wild-type littermates. Together, these results confirm a causative role for CDKL5 deficiency in sleep disturbances observed in CDD patients and establish an animal model for translational research of sleep treatment in CDD. Moreover, our results provide valuable information for developing therapeutic strategies and identifying sleep and EEG parameters as potential biomarkers for facilitating preclinical and clinical trials in CDD.

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Hyper-Activation of mPFC Underlies Specific Traumatic Stress-Induced Sleep–Wake EEG Disturbances

August 2020

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450 Reads

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14 Citations

Sleep disturbances have been recognized as a core symptom of post-traumatic stress disorders (PTSD). However, the neural basis of PTSD-related sleep disturbances remains unclear. It has been challenging to establish the causality link between a specific brain region and traumatic stress-induced sleep abnormalities. Here, we found that single prolonged stress (SPS) could induce acute changes in sleep/wake duration as well as short- and long-term electroencephalogram (EEG) alterations in the isogenic mouse model. Moreover, the medial prefrontal cortex (mPFC) showed persistent high number of c-fos expressing neurons, of which more than 95% are excitatory neurons, during and immediately after SPS. Chemogenetic inhibition of the prelimbic region of mPFC during SPS could specifically reverse the SPS-induced acute suppression of delta power (1–4 Hz EEG) of non-rapid-eye-movement sleep (NREMS) as well as most of long-term EEG abnormalities. These findings suggest a causality link between hyper-activation of mPFC neurons and traumatic stress-induced specific sleep–wake EEG disturbances.


Quantitative phosphoproteomic analysis of the molecular substrates of sleep need

June 2018

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1,009 Reads

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211 Citations

Nature

Sleep and wake have global effects on brain physiology, from molecular changes1-4 and neuronal activities to synaptic plasticity3-7. Sleep-wake homeostasis is maintained by the generation of a sleep need that accumulates during waking and dissipates during sleep8-11. Here we investigate the molecular basis of sleep need using quantitative phosphoproteomic analysis of the sleep-deprived and Sleepy mouse models of increased sleep need. Sleep deprivation induces cumulative phosphorylation of the brain proteome, which dissipates during sleep. Sleepy mice, owing to a gain-of-function mutation in the Sik3 gene 12 , have a constitutively high sleep need despite increased sleep amount. The brain proteome of these mice exhibits hyperphosphorylation, similar to that seen in the brain of sleep-deprived mice. Comparison of the two models identifies 80 mostly synaptic sleep-need-index phosphoproteins (SNIPPs), in which phosphorylation states closely parallel changes of sleep need. SLEEPY, the mutant SIK3 protein, preferentially associates with and phosphorylates SNIPPs. Inhibition of SIK3 activity reduces phosphorylation of SNIPPs and slow wave activity during non-rapid-eye-movement sleep, the best known measurable index of sleep need, in both Sleepy mice and sleep-deprived wild-type mice. Our results suggest that phosphorylation of SNIPPs accumulates and dissipates in relation to sleep need, and therefore SNIPP phosphorylation is a molecular signature of sleep need. Whereas waking encodes memories by potentiating synapses, sleep consolidates memories and restores synaptic homeostasis by globally downscaling excitatory synapses4-6. Thus, the phosphorylation-dephosphorylation cycle of SNIPPs may represent a major regulatory mechanism that underlies both synaptic homeostasis and sleep-wake homeostasis.

Citations (2)


... Power ratios of theta/delta, alpha/delta, beta/delta, alpha/theta, beta/theta, and beta/alpha were calculated. For hourly NREMS delta power density analysis after sleep deprivation, values of delta power for each hour after sleep deprivation were normalized to the baseline average NREMS delta power from ZT8 to ZT11, which is at the end of the major rest period [78,79]. Epochs containing recording artefacts were included in the sleep-wake state totals and architecture analysis but excluded from spectral analysis. ...

Reference:

Cdkl5 Knockout Mice Recapitulate Sleep Phenotypes of CDKL5 Deficient Disorder
Hyper-Activation of mPFC Underlies Specific Traumatic Stress-Induced Sleep–Wake EEG Disturbances

... Next, we incorporated the spontaneous sleep-wake cycle into our network models. Previous phosphoproteomic studies suggested that phosphorylation of several synaptic proteins is associated with sleep needs [26][27][28]. The sleep needs increase during wakefulness and decreases with the onset of sleep. ...

Quantitative phosphoproteomic analysis of the molecular substrates of sleep need

Nature