TY - JOUR
AU - Tian,, Di
AB - Abstract Sleep abnormalities are common among children with neurodevelopmental disorders. The human chr16p11.2 microdeletion is associated with a range of neurological and neurobehavioral abnormalities. Previous studies of a mouse model of human chr16p11.2 microdeletion (chr16p11.2df/+) have demonstrated pathophysiological changes at the synapses in the hippocampus and striatum; however, the impact of this genetic abnormality on system level brain functions, such as sleep and neural oscillation, has not been adequately investigated. Here, we show that chr16p11.2df/+ mice have altered sleep architecture, with increased wake time and reduced time in rapid eye movement (REM) and non-REM (NREM) sleep. Importantly, several measurements of REM sleep are significantly changed in deletion mice. The REM bout number and the bout number ratio of REM to NREM are decreased in mutant mice, suggesting a deficit in REM-NREM transition. The average REM bout duration is shorter in mutant mice, indicating a defect in REM maintenance. In addition, whole-cell patch clamp recording of the ventrolateral periaqueductal gray (vlPAG)-projecting gamma-aminobutyric acid (GABA)ergic neurons in the lateral paragigantocellular nucleus of ventral medulla of mutant mice reveal that these neurons, which are important for NREM–REM transition and REM maintenance, have hyperpolarized resting membrane potential and increased membrane resistance. These changes in intrinsic membrane properties suggest that these projection-specific neurons of mutant mice are less excitable, and thereby may play a role in deficient NREM–REM transition and REM maintenance. Furthermore, mutant mice exhibit changes in neural oscillation involving multiple frequency classes in several vigilance states. The most significant alterations occur in the theta frequency during wake and REM sleep. chr16p11.2 microdeletion, REM sleep, neural oscillation, theta rhythm, vlPAG, LPGi, GABAergic neurons Statement of Significance Our current study has uncovered altered REM sleep in a mouse model of human chr16p11.2 microdeletion, one of the most common CNVs associated with a range of neurodevelopmental disorders. We not only demonstrate that the alterations are caused by deficient NREM–REM transition and REM maintenance, but also identify a potential cellular and circuit mechanism. Specifically, we show that the intrinsic membrane excitability in vlPAG-projecting LPGi GABAergic neurons is reduced. Furthermore, REM-associated theta oscillation is attenuated. Given the postulated functions of REM sleep and theta oscillation in memory consolidation and synaptic homeostasis, our findings are potentially relevant to understanding the role of sleep dysfunction in a wide range of neurobehavioral phenotypes and to informing effective interventions in individuals with chr16p11.2 microdeletion. Introduction Sleep disorders are common among patients with neurodevelopmental disorders (NDDs), such as autism spectrum disorders (ASDs) [1, 2], Asperger’s syndrome [3, 4], attention deficit hyperactivity disorders (ADHDs) [5, 6], intellectual disability (ID) [7–10], and schizophrenia [11–13]. The most frequent sleep-related presentations in these patients are delayed sleep onset, shortened total sleep, sleep fragmentation, day-time sleepiness, reduced or increased rapid eye movement (REM) sleep [7, 14–16], REM sleep behavioral disorder [2, 13, 17–19], and periodic limb movement syndrome (PLMS) [15]. Polysomnography recordings have reported poor differentiation of sleep stage [7, 20, 21], and changes in neural oscillation patterns and regional coherence [22–25]. Such sleep disorders can adversely affect patients’ daily activities and exacerbate the core symptoms of neurodevelopmental and neuropsychiatric disorders [26–29]. The human chr16p11.2 microdeletion is one of the most common chromosome copy number variations (CNVs) associated with NDDs [30–37]. The most common neurobehavioral presentations associated with chr16p11.2 deletion are language deficits, ID, ASDs, anxiety, ADHD, and epilepsy [34–37]. Although sleep abnormalities have been anecdotally reported, no comprehensive characterization of sleep phenotypes in individuals with chr16p11.2 microdeletion has been published. Given that sleep disturbance can be subtle and can go unreported in the face of larger clinical concerns, but that they can greatly exacerbate the severity of other symptoms, it is important to investigate the extent that specific genetic alternations are associated with sleep disorders. Several studies on mouse models of chr16p11.2 microdeletion have demonstrated impairments in synaptic transmission and local circuit function in the hippocampus [38, 39] and striatum [40]. However, the role and mechanism by which the chr16p11.2 microdeletion produces system level abnormalities in mice, specifically alterations in sleep and neural oscillations has not been adequately addressed in detail. In this study, we investigated wake and sleep architectures as well as oscillation patterns in a mouse model of human chr16p11.2 microdeletion. Polysomnographic recording revealed reduced total, non-REM (NREM), and REM sleep, decreased number of REM bouts, and shortened REM epoch duration in heterozygous deletion mice. In addition, mutant mice displayed significant alterations in oscillation patterns, involving several frequency classes in different vigilance states. Lastly, patch clamp recording from vlPAG-projecting gamma-aminobutyric acid (GABA)ergic neurons in lateral paragigantocellular (LPGi) nucleus in the ventral medulla revealed altered intrinsic membrane properties, suggesting that changes in membrane excitability in these neurons, which are critical for REM sleep regulation, may potentially be one of the mechanisms of REM sleep deficit in chr16p11.2df/+ mice. Materials and Methods Animals Mice carrying a deletion of the syntenic region of human chr16p11.2 (chr16p11.2df/+ mice) [41] have been previously analyzed and reported [38, 39, 41–44]. Mice used in this study have been backcrossed onto the congenic C57BL/6N (Charles River Laboratories) background for more than 20 generations. Wildtype and heterozygous deletion mice were generated by breeding wildtype females with mutant male mice. Both wildtype and mutant mice were group-housed and kept on a 12:12 h light:dark cycle with unrestricted access to food and water. Gad2-IRES-Cre mice (B6N.Cg-Gad2tm2(cre)Zjh/J) on a congenic C57BL/6N background were obtained from Jackson Laboratory (stock 019022). All experimental procedures were approved by the Institutional Animal Care and Use Committee at the Children’s Hospital Los Angeles and conformed to NIH guidelines. All experimenters were blind to the genotypes in all experiments and during data analysis. Surgery for polysomnographic recording Male mice (6–7 weeks old) were anesthetized with 3% isoflurane under a flow rate of 3 L/min for 3 min. After eye ointment was applied and the scalp was shaved, isoflurane was maintained at 2% at a flow rate of 1 L/min for the remaining procedure. A small amount of normal saline solution containing 1% lidocaine and 0.1% epinephrine was injected under the scalp and a small area of scalp was excised to expose the skull. The soft tissue overlying the skull was removed and the skull was cleaned with 70% ethanol. Three stainless steel micro screws (0.6 mm in diameter) were inserted into the skull with the tips in the epidural space. Two screws were placed over the frontal cortex (1.0 mm anterior to Bregma and 1.0 mm lateral to the midline), and the third was over the parietal cortex (2.5 mm posterior to Bregma and 2.0 mm lateral to the midline). The left fontal screw was used as ground (Figure 1A). The differential of the signals measured at the right frontal and left parietal cortex were used for EEG (electroencephalogram) analysis. The screws were secured using cyanoacrylate glue and connected to a headmount (Pinnacle Technology, KS; #8402-SS) via silver wires. Two stainless steel wires, which were built into the headmount by the manufacturer, were inserted into the trapezius muscle for electromyographic recording. Dental cement was applied to the skull to form a protective cap for the surgical field, micro screws, and headmount. Post-surgical mice were given analgesics for 3 days and monitored for any signs of infection and discomfort. Figure 1. View largeDownload slide Schematic diagram of the electrode configuration, setup of polysomnography, and representative traces of EEG and EMG, and hypnograms. (A) Schematic diagram showing the positions of EEG miniscrews (highlighted in yellow) and EMG electrodes (represented by wires). (B) Photographs showing a mouse under polysomnographic recording during the day and night. (C) Representative traces of wake EEG and EMG as well as power spectral plot of EEG. Notice the low amplitude EEG and flat power spectral plot. (D) Representative traces of NREM EEG and EMG as well as power spectral plot of EEG. Notice the relatively high amplitude EEG and a prominent peak in the delta frequency (0.5–4 Hz) on the power spectral plot. (E) Representative traces of REM EEG and EMG as well as power spectral plot of EEG. Notice the low amplitude EEG and a prominent peak in the theta frequency (6–9 Hz) on the power spectral plot. The EEG and EMG traces between two adjacent vertical lines are 4 s in duration. The spectral plots shown in C, D, and E are derived from the EEG in the shaded epochs. The three vigilance and sleep states, that is, wake, NREM, and REM, are color coded for clarity. (F) Representative hypnograms of wildtype and mutant mice. Figure 1. View largeDownload slide Schematic diagram of the electrode configuration, setup of polysomnography, and representative traces of EEG and EMG, and hypnograms. (A) Schematic diagram showing the positions of EEG miniscrews (highlighted in yellow) and EMG electrodes (represented by wires). (B) Photographs showing a mouse under polysomnographic recording during the day and night. (C) Representative traces of wake EEG and EMG as well as power spectral plot of EEG. Notice the low amplitude EEG and flat power spectral plot. (D) Representative traces of NREM EEG and EMG as well as power spectral plot of EEG. Notice the relatively high amplitude EEG and a prominent peak in the delta frequency (0.5–4 Hz) on the power spectral plot. (E) Representative traces of REM EEG and EMG as well as power spectral plot of EEG. Notice the low amplitude EEG and a prominent peak in the theta frequency (6–9 Hz) on the power spectral plot. The EEG and EMG traces between two adjacent vertical lines are 4 s in duration. The spectral plots shown in C, D, and E are derived from the EEG in the shaded epochs. The three vigilance and sleep states, that is, wake, NREM, and REM, are color coded for clarity. (F) Representative hypnograms of wildtype and mutant mice. Polysomnographic recording Two to three weeks after surgery, mice were habituated for 5 days to custom-built circular cages (polypropylene, 30 cm diameter and 25 cm height) (Figure 1B) placed inside sound-attenuated boxes (48″ x 48″ x 48″) located in a dedicated sleep recording room. Next, preamplifiers (Pinnacle Technology, KS; 8406-SL) were connected to the headmount, and mice were habituated for an additional 5 days before recording was initiated. Recording was performed for at least three consecutive days. EEG signals were bandpass-filtered between 0.5 Hz and 200 Hz, and sampled at 400 Hz. EMG signals were likewise filtered between 0.5 Hz and 200 Hz, and sampled at 400 Hz. Sleep stage analysis Recordings from two consecutive days were scored for sleep stage analysis and we report the average values for each parameter across the 2 days. Sleep stages were first scored by “Sirenia Sleep Pro” software using “threshold scoring” function (Pinnacle Technology) and further verified manually by two experimenters. A consensus on scoring was reached for each animal before further analysis proceeded. Four-second window epochs were chosen for all sleep scoring and oscillation analysis (Figure 1C–E). The oscillation frequency classes reported in our study were delta (0.5–4 Hz), theta (6–9 Hz), alpha (9–12 Hz), beta (12–30 Hz), and gamma (30–59 Hz). The wake state was classified by high activity EMG and asynchronized low amplitude EEG (Figure 1C). NREM sleep was classified by EMG of low to absent activity, and EEG power spectra with high delta and low theta (Figure 1D). REM sleep was classified by the absence of EMG activity, and EEG power spectra with high theta and low delta (Figure 1E). The post-scoring data were further analyzed for sleep architecture and oscillation pattern analysis. One wildtype mouse that was used for sleep architecture analysis was excluded from power analysis due to an increased number of artifacts during wakefulness. Retrograde labeling of LPGi neurons with Cholera Toxin Subunit B Alexa FluorTM 488 conjugate Retrograde labeling was performed on wildtype and mutant mice carrying the Gad2-IRES-Cre allele, so that neurons that were recorded by patch clamp (see below) could be verified to be GABAergic. Retrograde labeling of LPGi neurons was achieved by injecting Cholera Toxin Subunit B conjugated with Alexa Fluor 488 (CTB-488, ThermoFisher Scientific, Cat# C22841) into the ventrolateral periaqueductal gray (vlPAG) of P23–P25 male wildtype and mutant littermates. Seventy-five nanoliters of 5% CTB-488, diluted in 1× phosphate buffered saline (PBS), was injected bilaterally into vlPAG (1.0 mm posterior to Lambda, 0.5 mm lateral, and 2.1 mm deep) at a rate of 75 nL/min. After injecting the designated volume, flow was stopped, and the injection needle was held at the injection site for additional 2 min before being withdrawn slowly out of the brain. Postsurgical mice were given analgesics for 3 days and monitored for any signs of infection and discomfort. Patch clamp recording After 6–10 days of recovery from surgery, whole-cell patch clamp recordings were performed on CTB-488 labeled LPGi neurons. Mice were euthanized by rapid decapitation and the brains were immediately submerged in ice-cold high sucrose dissection buffer (HSDB) for 1 min. Two-hundred-micron coronal sections were cut on a Leica VT1000 S vibratome in ice-cold HSDB, incubated in NMDG recovery buffer (NRB) at 30°C for 15 min, then transferred to artificial cerebrospinal fluid (aCSF) at 25°C. Slices were further recovered at room temperature for 1 h before recording. During the recording, slices were continuously perfused with oxygenated aCSF at a flow rate of 2 mL/min and at 25°C, and then viewed using both infrared differential interference contrast (IR-DIC) and fluorescent imaging. The LPGi neurons located within ventral medulla selected for whole-cell patching were identified by the presence of CTB-488 visualized by superimposing the fluorescent and IR-DIC images. HSDB was composed of (in mM): 87 NaCl, 75 sucrose, 2.5 KCl, 1.2 NaH2PO4, 30 NaHCO3, 25 glucose, 20 HEPES, 5 Na-ascorbate, 3 Na-pyruvate, 2 thiourea, 10 MgSO4, and 0.5 CaCl2. NRB was composed of (in mM): 92 NMDG, 92 HCl, 2.5 KCl, 1.2 NaH2PO4, 30 NaHCO3, 25 glucose, 20 HEPES, 5 Na-ascorbate, 3 Na-pyruvate, 2 thiourea, 10 MgSO4, and 0.5 CaCl2. aCSF was composed of (in mM): 119 NaCl, 2.5 KCl, 1 MgCl2, 2 CaCl2, 26 NaHCO3, 1.23 NaH2PO4, and 10 glucose. All buffers used in dissection, recovery, and recording were supplemented with a mixture of 95% O2 and 5% CO2 to maintain the pH at 7.4. All recordings were performed in aCSF at 25°C with a Multiclamp 700B microelectrode amplifier (Molecular Device, Sunnyvale, CA). Signals were low-pass filtered at a frequency of 1k Hz and digitized at 10k Hz using Digidata 1440A amplifier and Clampex 10.7 software (Molecular Device). Series resistance was monitored continuously during recording and experiments were discarded if the measurement changed by >15%. All internal solutions (resistance 4–7 MΩ; pH 7.2–7.4; osmolarity 290–300 mOsm) used in this study contained 80 µM Alexa-Fluor 594 hydrazide and 6.7 mM biocytin for visualization during recording and postrecording staining, respectively. All data were analyzed using Minianalysis (version 6.0.3, Synaptosoft, Inc.) or Clampfit software (version 10.7, Molecular Device). Current clamp recording was performed to measure the resting membrane potential (RMP) as previously described [39, 45]. Specifically, after obtaining a gigaseal, the membrane was carefully broken to avoid a leaking current larger than 50 pA. The membrane potentials were recorded for 10 min and the measurements during the last 5 min were used to calculate the RMP. The electrodes were filled with (in mM) 131 K-gluconate, 20 KCl, 8 NaCl, 10 HEPES, 2 EGTA, 2 NaATP, and 0.3 NaGTP. To measure membrane resistance (Rm), series resistance (Rs), and membrane capacitance (Cm), neurons were recorded for 15 min, and the measurements during the last 5 min were analyzed. Neurons were discarded if the values of these three measurements fluctuated more than 15% from the average values across the 15 min of recording. The electrodes were filled with (in mM) 131 K-gluconate, 20 KCl, 8 NaCl, 10 HEPES, 2 EGTA, 2 NaATP, and 0.3 NaGTP. To determine the current–voltage (I-V) curve, membrane current at 11 voltage steps (−100, −80, −60, −40, −20, 0, 20, 40, 60, 80, 100 mV) were measured. Specifically, neurons were held at each step for 400 ms. The initial peak current for the entire step and the average current for the last 100 ms were analyzed. The voltage step cycle was repeated twice for each neuron and the current measurements for each step were averaged and used for data analysis. The electrodes were filled with (in mM) 131 K-gluconate, 20 KCl, 8 NaCl, 10 HEPES, 2 EGTA, 2 NaATP, and 0.3 NaGTP. Postrecording staining The purpose of postrecording staining was to determine whether the recorded neurons were GABAergic. Biocytin, which diffused into the neurons from the internal solution during patch recording, was detected by Avidin D conjugated with 7-amino-4-methylcoumarin-3-acetic acid (AMCA) (AMCA Avidin D). An antibody against Cre-recombinase (Cre) was used to detect GABAergic neurons. Specifically, tissue slices were fixed in freshly prepared 4% PFA diluted in 1× PBS for 30 min immediately after recording. They were transferred to 1× PBS and stored at 4°C until staining. Dual staining for biocytin and Cre was performed on all slices containing patched neurons. All procedures were performed at room temperature unless otherwise specified. Slices were first washed with 1× PBS supplemented with 3% Triton X (PBST) for three times with 5 min each; they were incubated in 1× PBST + 5% normal donkey serum for 1 h; they were then incubated with AMCA Avidin D (dilution: 1/200; Vector Laboratories, Cat# A-2008) and monoclonal rabbit anti-Cre antibody (dilution: 1/200; Synaptic System, Cat# 257003) at 4°C. After overnight incubation, slices were washed in 1× PBST for three times with 5 min each; they were then incubated with donkey anti-rabbit secondary antibody conjugated with Alexa Fluor 594 (dilution: 1/200; Jackson ImmunoResearch, Cat# 611-585-215). After 2 h, slices were washed in 1× PBST for three times with 5 min each, 1× PBS for two times with 5 min each, and mounted on slides with Fluoromount-G mounting media without DAPI (SouthernBiotech, Cat# 0100-01). Statistical analysis Statistical analyses were performed using Statistical Analysis System (SAS) software (version 9.4) and GraphPad (version 6). Multivariate analysis of variance (MANOVA) was used to analyze wake, sleep, NREM, and REM time during the day and night, as well as for REM/total sleep ratio, and REM/NREM ratio (Figure 2A–F). Student’s t-test (unpaired, two-tailed) was used for analyzing the same parameters as above over the 24-h time period (Figure 2A–F). Two-way analysis of variance (two-way ANOVA) with post hoc Bonferroni correction was used for the 12 × 2-h binned sleep state analysis (Figure 2G–J). MANOVA was used for bout number and duration analyses during the day and night (Figure 3A–H). Student’s t-test (unpaired, two-tailed) was used for bout number and duration analyses over the 24-h period (Figure 3A–H). Two-way ANOVA with post hoc Bonferroni correction was used for analyzing the distribution of bout duration of NREM (Figure 4A–D) and REM (Figure 4E–H) sleep. Student’s t-test (unpaired, two-tailed) was used to analyze the RMP, membrane resistance, and membrane capacitance (Figure 5I–K), as well as for the IV-curves (Figure 5M and N). Mann–Whitney U-test was used to analyze the relative powers in frequency class (Figure 6A–F). Mann–Whitney U-test was used to analyze the relative powers in frequency class (Figure 6A–F). Two-way ANOVA with post hoc Bonferroni correction was used to analyze the relative powers in 1 Hz frequency bins (Figure 6G–L). All data are presented as the average ± SEM (standard error of the mean). Figure 2. View largeDownload slide Reduced NREM and REM sleep, and increased arousal in mutant mice. Mutant mice exhibited increased awake time (A), reduced total sleep time (B), reduced NREM sleep time (C), and reduced REM sleep time (D). The ratios of REM to total sleep time (E) and REM to NREM sleep time (F) are reduced in mutant mice. Time courses of wake (G), total sleep (H), NREM sleep (I), and REM sleep (J). Data are presented as mean ± SEM. Wildtype, n = 10. Mutant, n = 9. Statistical significance is determined by MANOVA (day and night in panels A–F), two-tailed, unpaired Student’s t-test (24 h in panels A–F), and two-way ANOVA with post hoc Bonferroni correction (panels G–J). *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Figure 2. View largeDownload slide Reduced NREM and REM sleep, and increased arousal in mutant mice. Mutant mice exhibited increased awake time (A), reduced total sleep time (B), reduced NREM sleep time (C), and reduced REM sleep time (D). The ratios of REM to total sleep time (E) and REM to NREM sleep time (F) are reduced in mutant mice. Time courses of wake (G), total sleep (H), NREM sleep (I), and REM sleep (J). Data are presented as mean ± SEM. Wildtype, n = 10. Mutant, n = 9. Statistical significance is determined by MANOVA (day and night in panels A–F), two-tailed, unpaired Student’s t-test (24 h in panels A–F), and two-way ANOVA with post hoc Bonferroni correction (panels G–J). *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Figure 3. View largeDownload slide Bout analysis of wake, REM, and NREM sleep. Bout numbers of wake (A), NREM sleep (B), and REM sleep (C). (D) REM/NREM bout ratio. Bout durations of wake (E), total sleep (F), NREM sleep (G), and REM sleep (H). Data are presented as mean ± SEM. Wildtype, n = 10. Mutant, n = 9. Statistical significance is determined by two-tailed, unpaired Student’s t-test (24 h in panels A–H), and MANOVA (day and night in panels A–H). ns: not significant. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Figure 3. View largeDownload slide Bout analysis of wake, REM, and NREM sleep. Bout numbers of wake (A), NREM sleep (B), and REM sleep (C). (D) REM/NREM bout ratio. Bout durations of wake (E), total sleep (F), NREM sleep (G), and REM sleep (H). Data are presented as mean ± SEM. Wildtype, n = 10. Mutant, n = 9. Statistical significance is determined by two-tailed, unpaired Student’s t-test (24 h in panels A–H), and MANOVA (day and night in panels A–H). ns: not significant. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Figure 4. View largeDownload slide The distribution plot of REM and NREM bout duration. Distributions of NREM bout number (A and C) and normalized NREM percentage (B and D) as a function of NREM duration during the day (A and B) and night (C and D). Distributions of REM bout number (E and G) and normalized REM percentage (F and H) as a function of REM duration during the day (E and F) and night (G and H). Please note that the shortest NREM and REM duration bins are 16–32 s. Data are presented as mean ± SEM. Wildtype, n = 10. Mutant, n = 9. Statistical significance is determined by two-way ANOVA with post hoc Bonferroni correction. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Figure 4. View largeDownload slide The distribution plot of REM and NREM bout duration. Distributions of NREM bout number (A and C) and normalized NREM percentage (B and D) as a function of NREM duration during the day (A and B) and night (C and D). Distributions of REM bout number (E and G) and normalized REM percentage (F and H) as a function of REM duration during the day (E and F) and night (G and H). Please note that the shortest NREM and REM duration bins are 16–32 s. Data are presented as mean ± SEM. Wildtype, n = 10. Mutant, n = 9. Statistical significance is determined by two-way ANOVA with post hoc Bonferroni correction. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Figure 5. View largeDownload slide Intrinsic membrane properties and current–voltage (I–V) relationship of vlPAG-projecting GABAergic neurons in LPGi of ventral medulla. (A) Schematic diagram highlighting the ventral lateral periaqueductal gray (vlPAG). (B) A representative fluorescent image showing bilateral vlPAG injected with CTB-488. (C) Schematic diagram of medulla demonstrating LPGi in ventral medulla (reference needed). Laterodorsal tegmental nucleus (LDT) and dorsal raphe nucleus (DRN) are shown as reference. (D) A representative fluorescent image illustrating unilateral LPGi labeled with retrograde CTB-488. The gigantocellular reticular nucleus (Gi), inferior olivary (IO) nucleus, and the nucleus of ambiguus (Amb) are shown for reference. (E) A representative fluorescent image showing a CTB-488 labeled LPGi neuron under patch clamp recording. (F) Post-recording detection of a patched neuron (filled with biocytin via patch pipette) with AMCA-conjugated avidin D. Notice that well-circumscribed contour of the neuron in contrast to irregular background staining. (G) Post-recording verification of Cre expression in the same patched neuron as in (F). Notice that multiple neurons are immunoreactive for Cre. (H) A merged image of (F) and (G). Colocalization of AMCA signal and Cre expression confirmed that the patched neuron is indeed GABAergic. (I) Resting membrane potential (RMP) is mildly reduced in mutant LPGi neurons. (J) Membrane resistance (Rm) is increased in mutant LPGi neurons. (K) Membrane capacitance (Cm) is indistinguishable between wildtype and mutant LPGi neurons. (L) Representative traces of current-voltage relationship in wildtype and mutant LPGi neurons. Both peak (denoted by arrows) and steady-state responses (the last 100 ms denoted by horizontal bars) are subjected to analysis. No statistical differences are present between wildtype and mutant LPGi neurons in peak current (M) and steady state (N) current responses. Schematic diagrams in panels A and C are from Paxinos and Frankin [46]. Arrows and insets in (E) to (H) denote and highlight a patched neuron. Scale bars are 200 microns in (A) to (D), and 30 microns in (E) to (H). Eighteen neurons from 6 wildtype mice and 15 neurons from 5 mutant mice were analyzed. Statistical significance was determined by two-tailed, unpaired Student’s t-test. ns: not significant, *p < 0.05, ***p < 0.001. Figure 5. View largeDownload slide Intrinsic membrane properties and current–voltage (I–V) relationship of vlPAG-projecting GABAergic neurons in LPGi of ventral medulla. (A) Schematic diagram highlighting the ventral lateral periaqueductal gray (vlPAG). (B) A representative fluorescent image showing bilateral vlPAG injected with CTB-488. (C) Schematic diagram of medulla demonstrating LPGi in ventral medulla (reference needed). Laterodorsal tegmental nucleus (LDT) and dorsal raphe nucleus (DRN) are shown as reference. (D) A representative fluorescent image illustrating unilateral LPGi labeled with retrograde CTB-488. The gigantocellular reticular nucleus (Gi), inferior olivary (IO) nucleus, and the nucleus of ambiguus (Amb) are shown for reference. (E) A representative fluorescent image showing a CTB-488 labeled LPGi neuron under patch clamp recording. (F) Post-recording detection of a patched neuron (filled with biocytin via patch pipette) with AMCA-conjugated avidin D. Notice that well-circumscribed contour of the neuron in contrast to irregular background staining. (G) Post-recording verification of Cre expression in the same patched neuron as in (F). Notice that multiple neurons are immunoreactive for Cre. (H) A merged image of (F) and (G). Colocalization of AMCA signal and Cre expression confirmed that the patched neuron is indeed GABAergic. (I) Resting membrane potential (RMP) is mildly reduced in mutant LPGi neurons. (J) Membrane resistance (Rm) is increased in mutant LPGi neurons. (K) Membrane capacitance (Cm) is indistinguishable between wildtype and mutant LPGi neurons. (L) Representative traces of current-voltage relationship in wildtype and mutant LPGi neurons. Both peak (denoted by arrows) and steady-state responses (the last 100 ms denoted by horizontal bars) are subjected to analysis. No statistical differences are present between wildtype and mutant LPGi neurons in peak current (M) and steady state (N) current responses. Schematic diagrams in panels A and C are from Paxinos and Frankin [46]. Arrows and insets in (E) to (H) denote and highlight a patched neuron. Scale bars are 200 microns in (A) to (D), and 30 microns in (E) to (H). Eighteen neurons from 6 wildtype mice and 15 neurons from 5 mutant mice were analyzed. Statistical significance was determined by two-tailed, unpaired Student’s t-test. ns: not significant, *p < 0.05, ***p < 0.001. Figure 6. View largeDownload slide Power spectral analysis. Normalized day-time spectral analysis of oscillation classes during wake (A), NREM (B), and REM sleep (C). Normalized nighttime spectral analysis of oscillation classes during wake (D), NREM (E), and REM sleep (F). Normalized day-time spectral analysis of 1 Hz bin during wake (G), NREM (H), and REM sleep (I). Normalized nighttime spectral analysis of 1 Hz bin during wake (J), NREM (K), and REM sleep (L). The oscillation frequencies are defined as delta (0.5–4 Hz), theta (6–9 Hz), alpha (9–12 Hz), beta (12–30 Hz), and gamma (30–59 Hz). Data are presented as mean ± SEM. Wildtype, n = 9. Mutant, n = 9. Statistical significance is determined by Mann–Whitney test (panels A–F), and two-way ANOVA with post hoc Bonferroni correction (panels G–L). ns: not significant. *p < 0.05, **p < 0.01, ***p < 0.001. Figure 6. View largeDownload slide Power spectral analysis. Normalized day-time spectral analysis of oscillation classes during wake (A), NREM (B), and REM sleep (C). Normalized nighttime spectral analysis of oscillation classes during wake (D), NREM (E), and REM sleep (F). Normalized day-time spectral analysis of 1 Hz bin during wake (G), NREM (H), and REM sleep (I). Normalized nighttime spectral analysis of 1 Hz bin during wake (J), NREM (K), and REM sleep (L). The oscillation frequencies are defined as delta (0.5–4 Hz), theta (6–9 Hz), alpha (9–12 Hz), beta (12–30 Hz), and gamma (30–59 Hz). Data are presented as mean ± SEM. Wildtype, n = 9. Mutant, n = 9. Statistical significance is determined by Mann–Whitney test (panels A–F), and two-way ANOVA with post hoc Bonferroni correction (panels G–L). ns: not significant. *p < 0.05, **p < 0.01, ***p < 0.001. Results Reduced NREM and REM sleep in mutant mice We first determined the amount of time wildtype and mutant mice spent in wake and sleep (total sleep) and in NREM and REM sleep. During the day, mutant mice showed a reduction in total, NREM, and REM sleep (Figure 2B–D), and a concurrent increase in total wakefulness (Figure 2A). During the night, these differences were more pronounced (Figure 2A–D), and were also noted for the full 24-h recordings (Figure 2A–D). We also calculated the percentages of REM sleep relative to total (Figure 2E) and to NREM sleep (Figure 2F) and found both were significantly lower in deletion mice compared with the wildtype, indicating that not only is there shortening of REM sleep in absolute value (Figure 2A–D), but also in relative values. We further examined the time-course of the wake and sleep states in 2-h intervals to identify the time window(s) in which mutant mice differed from wildtype mice. As shown in Figure 2G–J, mutant mice had a trend of having longer wake time, shorter total sleep, and shorter NREM sleep for most of the daytime windows (Figure 2G–I). Although no time-segment of NREM was statistically significant between wildtype and mutant mice, the differences across the daytime accumulatively contributed to the shortening of the daytime total NREM (Figure 2C). In contrast, most of the nighttime windows showed statistically significant differences between wildtype and mutant mice in wake, total sleep, and NREM (Figure 2G–I). More significantly, the REM sleep was shorter in mutant mice for most of the time segments across the 24-h recording period (Figure 2J). Impaired NREM to REM transition and REM sleep maintenance in mutant mice The significant reduction in REM sleep time seen in mutant mice could be due to a decrease in the number of REM episodes (bout number) and/or duration of each REM episode (bout duration). To differentiate these two possibilities, we quantified bout number and bout duration for mutant and wildtype mice for each type of wake/sleep state. As shown in Figure 3, during the day, mutant mice were indistinguishable from wildtype mice in the number of wake, total sleep (which is equivalent to the number of wake bouts), and NREM sleep bouts (Figure 3A and B), but showed a reduced number of REM bouts (Figure 3C) and lower REM/NREM bout number ratios (Figure 3D). During the night, mutant mice displayed reduced wake, total, NREM, and REM sleep bout numbers, and REM/NREM bout number ratios (Figure 3A–D). In addition, mutant mice showed increased wake bout duration (Figure 3E) and reduced REM bout duration (Figure 3H) at daytime, during nighttime, and across the entire 24-h recording. In contrast to REM sleep, deletion mice were statistically indistinguishable from wildtype mice in total sleep bout duration (Figure 3F) and NREM bout duration (Figure 3G). It is worth mentioning that the significantly increased nighttime wake bout duration (Figure 3E) was largely due to the presence of multiple episodes of wakefulness with long duration at night, particularly during the first half of the night (Figures 1F and 2G). The bout analysis shed some light on the sources of shortened NREM and REM sleep as previously shown in Figure 2C and D, respectively. Specifically, the reduced nighttime NREM bout number (Figure 3B), in the presence of normal NREM bout duration (Figure 3G) in mutant mice, contributed to a significantly reduced total nighttime NREM sleep (Figure 2C). In addition, the reduced REM bout number (Figure 3C) and REM bout duration in mutant mice (Figure 3H) contributed to the markedly reduced REM sleep during both day and night (Figure 2D). We next analyzed the distribution of NREM bout duration in wildtype and mutant mice. The NREM bout distribution was plotted on a scale of 32-s bins using both the absolute (Figure 4A and C) and relative values (Figure 4B and D). The only exception was the first bin, which was set as 16–32 s. The relative value for each bin was calculated by dividing the number of episodes of a given bin by the total number of NREM bouts during the day (Figure 4B) or night (Figure 4D). As shown in Figure 4A–D, during the day, the mutant mice showed a mild increase in the absolute number and percentage of bouts of 16–32 s duration. Although the significance of mild increases in the number and percentage of 16–32 s duration bouts in mutant mice is unclear, we noticed that in our recording NREM episodes of 16–32 second duration were mostly observed at the wake-NREM transition. This may suggest a deficit in wake-NREM transition in mutant mice. In contrast to daytime, the absolute numbers of NREM episodes were markedly lower in multiple bout durations in mutant mice (Figure 4C). This result was consistent with a lower total NREM bout number at night for mutant mice (Figure 3B). In contrast to the relative NREM distribution of daytime (Figure 4B), there was no difference in the relative nighttime NREM distribution between wildtype and mutant mice (Figure 4D). To more precisely characterize REM duration, we analyzed the distribution of REM bout duration in wildtype and mutant mice in 16-s intervals. We plotted the REM bout distribution on a scale of 16-s long bins using both absolute and relative values with the relative values. The first bin of REM duration was set as 16–32 s because any REM episode shorter than 16 s could not be reliably identified in our recording. As shown in Figure 4E–H, deletion mice differed from the wildtype during both the day and night. During the day, mutant mice had an increased number and percentage of REM bouts of relatively short duration (e.g. 16–32 s and 32–48 s; Figure 4E and F); and decreased REM bouts of relatively long duration (e.g. ≥112 s; Figure 4E and F). At night, mutant mice showed decreased number of REM bouts in multiple bins compared with wildtype mice (Figure 4G), and an increased percentage of REM bouts only in the bin of the shortest duration (16–32 s; Figure 4H). REM sleep is divided into the initiation and maintenance phase [47–50]. Because NREM episode is followed by either a REM or a wake episode, the ratio of the number of REM to NREM episodes is regarded as an index of NREM to REM initiation [47, 48]. As shown in Figure 3D, this ratio was mildly reduced in mutant mice compared with the wildtype, indicating that a larger fraction of NREM episodes were not converted into REM sleep in mutant mice. This result suggests that NREM to REM transition, hence the initiation of REM, is impaired in mutant mice. Furthermore, deletion mice showed an increased number and percentage of short REM bouts while exhibiting a tendency of decreased long REM bouts (Figure 4E and F), suggesting that the maintenance of REM sleep is also impaired in mutant mice during the day. Altered intrinsic membrane properties in mutant vlPAG-projecting GABAergic LPGi neurons Several studies have suggested that the vlPAG-projecting GABAergic neurons in LPGi play an important role in REM sleep regulation. For example, optogenetic stimulation of these neurons increases REM sleep by increasing the probability of NREM–REM transition and the REM duration [48]. Additionally, their firing activity correlates with both the initiation and maintenance phases of REM sleep [49]. We speculated that impaired initiation and maintenance of REM in mutant mice could result from impaired excitability of these projection-specific GABAergic neurons in LPGi. Since the intrinsic membrane properties are critical for neuronal excitability, we conducted patch clamp recording to investigate the pertinent biophysical parameters. We retrogradely labeled the vlPAG-projecting LPGi neurons by injecting CTB-488 into vlPAG (Figure 5A and B) and determined the intrinsic membrane properties of green fluorescent neurons in LPGi (Figure 5C–E). Postrecording staining confirmed that all patched neurons were immunoreactive for Cre-recombinase, thus confirming that they were GABAergic neurons (Figure 5F–H). As shown in Figure 4I, the mutant neurons showed a mild reduction in RMP (Figure 5I) and a significant elevation in membrane resistance (Figure 5J). Membrane capacitance (Figure 5K) was indistinguishable between wildtype and mutant LPGi neurons. Next, we applied a step-protocol to determine the current–voltage (I-V) relationship (Figure 5L–N). Both the peak current, representing the responses of voltage-gated ion channels and ionotropic receptors with fast kinetics, and the steady state current, representing ligand-gated channels and metabotropic receptors with slow kinetics, were quantified (Figure 5L). The mutant and wildtype LPGi neurons were indistinguishable in peak (Figure 5M) and steady state current (Figure 5N) at all voltage steps. These results suggest that both the quantities and types of fast-responding ion channels (or receptors) and the slow-responding ligand-gated channels (or metabotropic receptors) [51, 52] were unaltered in mutant vlPAG-projecting GABAergic LPGi neurons. Taken together, the above studies revealed a small reduction in RMP and mildly increased membrane resistance in mutant vlPAG-projecting GABAergic LPGi neurons. Although these changes were individually small in magnitude, in combination they lead to decreased excitability of the mutant LPGi neurons and potentially resulting in impaired REM sleep initiation and maintenance. Altered oscillation pattern in mutant mice Different vigilance and sleep states are characterized by distinctive EEG features and power spectra patterns. The changes in sleep structure described above in mutant mice prompted us to investigate the oscillation patterns using power spectrum analysis. Different vigilance and sleep states are characterized by distinctive neural oscillation patterns observed in EEG recording. The changes in sleep structure described above in mutant mice led us to investigate the oscillation patterns using power spectrum analysis. Fast Fourier transform was performed using SleepPro software (Pinnacle Technology) on each 4-s segment of EEG and the power for each 1-Hz bin (between 0 and 59 Hz) within the 4-s segment was calculated. The derived power data were further grouped and analyzed based on oscillation classes and vigilance states. Here, we present the normalized power data based on the vigilance state in combination with either oscillation frequency classes (Figure 5A–F) or the distribution of power in 1-Hz windows (Figure 6G–L). As shown in Figure 6, during the day, mutant mice showed reduced theta oscillation during wakefulness, lower delta oscillation during NREM sleep, and significantly decreased theta as well as increased beta oscillations during REM sleep (Figure 6A–C). During the night, mutant mice displayed reduced theta during wakefulness, and lower theta as well as increased delta during REM sleep (Figure 6D–F). The mutant mice showed no changes in any of the frequency classes during NREM sleep at night. To verify and better characterize the frequency classes where mutant mice showed changes in oscillation patterns, we examined the spectral plot continuously between 0 and 59 Hz (Figure 6G–L). The results closely matched those from frequency class analysis in the delta (Day-NREM, Night-REM), theta (Day-Wake, Day-REM, Night-Wake, and Night-REM) oscillation ranges. It was noted that three bins in Night-NREM (Figure 6K) (1–2, 2–3, and 3–4 Hz) showed differences between mutant and wildtype mice; however, since the difference between the two genotypes in 1–2 Hz bin (wildtype > mutant) was in the opposite direction to that of 2–3 and 3–4 Hz bin (wildtype < mutant), the overall delta oscillation of night-NREM was not changed in mutant mice (Figure 6E). Taken together, our power analysis demonstrated aberrations in neural oscillation in multiple frequency classes in several wake and sleep states. The most prominent findings were changes in theta oscillation in both wake and REM sleep at both day and night, suggesting that the neural circuits involved in theta oscillation were abnormal in mutant mice. Discussion In this study, we determined the impact of chr16p11.2 microdeletion on sleep and neural oscillation in an engineered mouse model for this syndrome. Polysomnographic recording of the mutant mice demonstrated reduced total, NREM, and REM sleep during both day and night. The mutant mice also showed decreased NREM to REM bout number ratio and reduced bout duration, indicated that both initiation and maintenance of REM sleep were impaired. In addition, whole-cell patch clamp recording of the vlPAG-projecting GABAergic neurons in the LPGi nucleus, aimed to probe the cellular and circuit mechanism of REM sleep deficit, revealed hyperpolarized RMP and increased membrane resistance in mutant mice. Furthermore, power spectral analysis demonstrated alterations in neural oscillation in multiple frequency classes in mutant mice. The most prominent abnormality was in the theta frequency during wake and REM sleep. Below we will discuss the major findings of our study in the context of the current understanding of sleep regulation and neural oscillation. Although detailed mechanisms are far from being clear, many studies have indicated that wake and sleep are regulated by highly orchestrated activities among multiple brain regions and neuronal populations [50, 53, 54]. The wake state is associated with activation of the thalamocortical system, which is driven by both the ascending reticular activation system in the brainstem, basal forebrain, and hypothalamus. NREM sleep coincides with silencing of the wake-promoting neurons, decreased activity of the ascending reticular and orexin systems, and activation of the vlPAG NREM-on GABAergic neurons. In addition, studies using immunohistochemistry for c-Fos expression, in vivo recording in behaving animals, and optogenetic manipulations, have strongly suggested that activation of ventrolateral preoptic (VLPO) neurons are important in induction and maintenance of NREM sleep [50]. A number of studies have identified a number of structures and neurons that are involved in REM regulation. They include the lateral hypothalamic neurons that produce melanin-concentrating hormone (MCH) [47, 55–57], glutamatergic neurons in the sublaterodorsal nucleus (SLD) of the pons [49, 58–60], and GABAergic neurons in the LPGi nucleus of ventral medulla oblongata [48, 49, 58, 61]. It is worth emphasizing the mechanisms of transitions between difference vigilant and sleep state are still poorly understood. Reduction in daytime NREM sleep and slow-wave oscillation in the delta range NREM sleep has been proposed to be involved in memory consolidation and synaptic homeostasis. NREM-associated memory processing likely depend on a highly coordinated interplay between thalamus-originated cortical slow-wave oscillation and hippocampal sharp waves and ripples [62]. For example, hippocampal memory replay predominantly occurs during NREM sleep [63]. A number of studies have shown slow-wave oscillation in the delta range during NREM may provide an “up-state” in the cortex for the transfer of memory traces “carried” by hippocampal sharp waves and ripples [62, 64–67]. One line of evidence to support the role of slow-wave oscillation in sleep-dependent memory formation and consolidation is from a study using trans-cranial direct current stimulations (tDCS). It is shown that increasing the duration and intensity of slow-wave oscillation during NREM by tDCS augments recall of declarative memories, whereas suppressing slow-wave oscillation strongly suppresses retention of declarative memories [68]. Further, slow-wave oscillation during NREM has been shown to coordinate the flow of information between distributed brain regions, and determines spike-timing dependent synaptic plasticity by synchronizing cycles of excitability among these brain regions [69–71]. Lastly, NREM sleep has been proposed to regulate homeostasis of cortical neuronal firing rate and thus facilitates various forms of synaptic plasticity [71, 72]. Our study demonstrated mild reductions in NREM sleep time and in the power of slow-wave oscillation in mutant mice. Although these changes are small, in light of the aforementioned studies demonstrating the potential roles of NREM and its associated slow-wave oscillation in memory consolidation, neuronal homeostasis, and synaptic plasticity, the coexistence of both abnormalities may affect these basic neuronal functions and processes. It is noted that the magnitude of NREM reduction was different between the daytime and nighttime in mutant mice and the nighttime was more significantly affected (Figure 2C). The analysis of the distributions NREM bout duration revealed an increase in bouts of the shortest duration (16–32 s) in the daytime in mutant mice (Figure 4A and B), suggesting a mild impairment in wake-NREM transition (please also refer to the Results section). During the nighttime, the number and percentage of NREM of the 16–32 s bin were similar between the two genotypes (Figure 4C and D). Instead, mutant mice had a much lower total number of bouts (Figure 3B) affecting many of the duration bins (Figure 4C). This significant reduction in the bout number indicated that mutant mice were less likely to enter NREM sleep at night compared with the wildtype. Interestingly, our unpublished results of the open field test, conducted at low light at night, showed increased locomotor activities in mutant mice. This suggests that nighttime hyperactivity could be a cause for significantly reduced nighttime NREM sleep in mutant mice. Reduced REM sleep time REM sleep is associated with the activation of lateral hypothalamic MCH neurons, glutamatergic SLD neurons, and LPGi GABAergic in ventral medulla, and tightly coordinated silencing of wake-promoting neurons in the basal forebrain, lateral hypothalamus, and brainstem [50, 53, 54]. Immunohistochemical, chemogenetic, and optogenetic studies have demonstrated that several brainstem nuclei may play critical roles in NREM–REM transition and REM maintenance. For example, the REM-off GABAergic neurons in vlPAG have been shown to control the NREM–REM transition by inhibiting glutamatergic REM-on neurons in SLD, and these SLD neurons activate REM-on GABAergic neurons in the LPGi [60, 73]. In addition, the REM-on GABAergic neurons in LPGi project to vlPAG and inhibit the firing of the vlPAG GABAergic NREM-on neurons during REM sleep [48]. Silencing of their activity correlates with reactivation of vlPAG GABAergic REM-off neurons and concurrent REM-wake transition [49]. Our study demonstrates significantly reduced REM sleep in mutant mice during both day and night. Several parameters indicate that the initiation and maintenance of REM is impaired in deletion mice. First, the number of REM bouts and REM/NREM bout ratios are lower in mutant mice. Second, mutant mice have an increased number of short REM episodes. Third, the number of bouts with long REM duration is significantly lower in mutant mice. Based on the aforementioned circuit mechanisms of REM sleep regulation, it is conceivable that shortening of REM in mutant mice may result from the “weakening” of REM-on neurons, and/or the “strengthening” of wake-promoting systems distributed in multiple brain regions. It is worth mentioning that a reduced REM time during the day and night may be the direct result of decreased NREM. This is particularly true for the nighttime when mutant mice show a more significant reduction in NREM than during daytime (Figure 2C). Nevertheless, the reduction of REM is disproportionate to that of NREM, measured by both time (Figure 2F) and bout ratio (Figure 3D) for both the daytime and nighttime. Therefore, the shortened NREM can only partially explain reduced REM (particularly for the nighttime), and some primary deficits in REM regulation, that is intrinsic to REM and independent of NREM sleep, also exist. Indeed, the alternations in the intrinsic membrane properties of the LPGi GABAergic neurons could be one of the potential deficits (please see below). Altered intrinsic membrane properties in vlPAG-projecting GABAergic LPGi neurons Neuronal excitability is highly dependent on intrinsic membrane properties, including RMP and membrane resistance. Both parameters influence the summation effects of excitatory and inhibitory postsynaptic currents, the conductance and open probability of channels and receptors on the cell membrane, and the degree of shunting inhibition received from neighboring synapses [45, 74–78]. Our patch clamp recordings reveal a decreased RMP and an increased membrane resistance in mutant vlPAG-projecting GABAergic LPGi neurons. These observations suggest that the mutant neurons have reduced excitability. Since activation of these projection specific GABAergic neurons in LPGi has been shown to be critical for REM initiation and maintenance [48, 49], a reduction in their excitability is likely to contribute to reduced frequency (bout number) and duration (bout duration) of REM sleep in mutant mice. To prove this hypothesis, future studies designed to increase the excitability of the vlPAG-projecting GABAergic neurons in LPGi (such as using pharmacogenetic approaches), followed by sleep analysis of mutant mice are needed. In addition, we acknowledge that the aberrations of vlPAG-projecting GABAergic LPGi neurons may not the only cause for altered REM sleep in mutant mice. It has been shown that other REM-on centers, such as MCH and SLD, also contain GABAergic neurons which project to vlPAG GABAergic neurons [59, 61, 73, 79, 80]. Changes in the intrinsic membrane properties and synaptic transmission of these additional REM-on neurons in mutant mice are also possible. Furthermore, it is possible that the wake-promoting brain regions are hyperactive in mutant mice, and thus maybe “prematurely” terminating REM and causing impaired REM maintenance. Future in vitro and in vivo studies of the pertinent brain regions and neuronal subpopulations involved in REM regulation will likely shed light on the comprehensive cellular and circuit mechanisms for abnormal REM sleep in mutant mice. Reduced REM-associated theta oscillation In addition to reduced REM sleep time, mutant mice also showed significant reductions in REM associated theta oscillation during both day and night. Theta oscillation during REM sleep can be recorded from multiple brain regions in rodents including the hippocampus, entorhinal cortex, amygdala, supramammillary nuclei of the hypothalamus, and retrosplenial cortex [81, 82]. The reciprocal loop between the medioseptal (MS) region and the hippocampus has been proposed to be important for theta rhythm [81–83]. MS GABAergic neurons drive hippocampal theta oscillation thus functioning as “rhythm generators” or “pace-makers.” The frequency and power of hippocampal REM theta are determined by MS GABAergic neurons, the hippocampus, and entorhinal cortex [81, 82, 84]. In our study, theta oscillation recorded from the parietal cortex during REM and wakefulness reflects the activity of the hippocampus. The peak frequencies of theta rhythm were indistinguishable between wildtype and mutant mice, suggesting that the “rhythm generator” function of MS GABAergic neurons in driving theta oscillation in the hippocampus is intact in mutant mice. In contrast, mutant mice showed significantly reduced theta power. Two possibilities may account for this phenotype. First, the “current generator” function of MS GABAergic neurons is impaired in mutant mice, despite their normal function as “rhythm generator.” Studies have shown that selective lesion and/or optogenetic silencing of MS GABAergic neurons greatly reduce hippocampal theta power [85, 86]. It is thus conceivable that a reduction in the activity of MS GABAergic neurons, at either the ensemble or individual cellular level, contributes to attenuated theta power. The reduced MS GABAergic activity could be due to anatomic and/or functional changes in mutant mice. Second, the source of theta oscillation, that is the hippocampus, could be abnormal in mutant mice. Specifically, the degree of synchronization and intrinsic properties of hippocampal neurons, as well as the local inhibitory network is aberrant in deletion mice. It is known that hippocampal theta rhythm is generated by synchronized synaptic activity in a continuous layer of neurons in CA3/CA1/subiculum, and theta power is determined by the degree of synchronization, the strength of synaptic input, and the tuning properties of inhibitory neurons [81]. Therefore, it is reasonable to speculate that some or all of these factors are abnormal and lead to an attenuated theta power in mutant mice. Consistent with this idea, our recent study demonstrated electrophysiological changes affecting hippocampal functions in mutant mice [39], including increased excitability and elevated excitation to inhibition (E/I) ratio in the absence of significant changes in inhibition in synapses onto the CA1 neurons [39]. It is conceivable that increased excitability and E/I ratio decreases synchronization among CA1 neurons, thus reducing theta power in mutant mice. Furthermore, we speculate that additional aberrations in hippocampal neurons that affect synaptic inputs and synchronization are likely present in mutant mice. Future in vivo characterization of the hippocampus will likely provide cellular and circuit mechanisms for altered theta oscillation in mutant mice. What is the functional implication of altered theta oscillation in mutant mice? Hippocampal theta rhythm during REM sleep has been proposed to be involved consolidation of spatial memory and memory with strong emotion component [87, 88]. A study by Boyce et al. [86] demonstrated that theta activity during REM sleep was required for memory consolidation in novel object place recognition and contextual fear conditioning [86]. Optogenetic silencing of MS GABAergic neurons during REM sleep selectively reduced hippocampal theta oscillation (without affecting other parameters of REM sleep) and resulted in impaired performance in object place recognition and contextual fear conditioning. Intriguingly, impaired contextual fear conditioning was reported in chr16p11.2 deletion mice [38]. In light of our current study, which revealed reduced theta oscillation in mutant mice, we hypothesize that reduction in theta rhythm may contribute to impaired conditional fear memory in chr16p11.2 mice. As mentioned previously, one tantalizing possibility is that impairment in MS GABAergic neurons as current generator may be a contributing factor. Future studies of the MS GABAergic neurons and their functions in mutant mice are needed to investigate this possibility. Reduction in wake-associated theta oscillation Interestingly, in addition to a reduction in REM theta, a decrease in theta rhythm also occurs in deletion mice during wakefulness. It has been shown awake theta rhythm occurs during active exploration, sniffing, whisking, and rearing [70, 89]. Theta rhythm recorded during explorative locomotion is generated in the hippocampus and is critical for spatial encoding and memory [88, 90–92]. The cellular and physiological mechanisms are similar to those during REM sleep, although they differ in properties such as theta-gamma coherence and phase relationship between theta rhythm and CA1 firing [93–95]. Our study did not simultaneously assess behavioral states and theta oscillation; therefore, it could not determine the behavioral correlate of reduced theta power. Given the importance of theta rhythm in spatial encoding and memory, it would be interesting to evaluate hippocampal theta oscillation in various spatial learning tasks, such as Barnes maze test, in mutant mice. The impact of chr16p11.2 microdeletion on sleep was first reported by Horev et al. [41]. Heterozygous deletion mice show increased diurnal and nocturnal activity, as well as disturbances in dark-light transitions [41]. A recent study by Angelakos et al. demonstrated male-specific sleep phenotypes in chr16p11.2 deletion mice on a C57BL/6J and 129S1/SvlmJ hybrid background, including increased 24-h wakefulness, decreased 24-h NREM sleep, and increased number of long-duration wake bouts [44]. In addition, mutant male mice showed increased alpha oscillation during the wake state [44]. Consistent with the findings from Angelakos et al., our study, conducted on mice of a congenic C57BL/6N background, showed increased 24-h wake time and reduced 24-h NREM sleep. However, our results and conclusions differ from those of the previous report. First, our study demonstrated that mutant mice had a significant NREM shortening during both daytime and nighttime (Figure 2C and I); in contrast, the previous study did not find these differences. Second, our study revealed marked REM sleep abnormalities in mutant mice on all measurements, including total time, percentage, distribution (Figure 2D, E, and J), and bout characteristics (Figures 3C, D, and H and 4E–H), whereas Angelakos et al. reported normal REM sleep in mutant mice. Third, our study revealed abnormal neural oscillation in multiple frequency ranges during wakefulness, NREM, and REM. Among them, the most significant was reduced theta oscillation in wake and REM sleep. In contrast, the only abnormality reported in male mice in the previous study was increased power in alpha frequency during wakefulness. It is reasonable to speculate that the differences between these two studies may reflect the influence of the genetic background on sleep and neural oscillation. In addition, the laboratory environments where these two studies are conducted might also have affected the outcomes. In summary, the current study uncovered a series of sleep and sleep-related perturbations in a mouse model of the human chr16p11.2 microdeletion. We speculate that these phenotypes may arise from altered functions of the circuits regulating sleep, arousal, and rhythmic activity of the brain. Given the postulated functions of sleep in memory consolidation and synaptic homeostasis in both rodents and human, the abnormalities observed in this mouse model of the human chr16p11.2 microdeletion may have significant clinical implications. Sleep studies of patients with chr16p11.2 microdeletion are needed to confirm and expand our observations. The results can be highly relevant to understanding the potential role of sleep dysfunction in a wide range of neurobehavioral phenotypes and to inform effective treatments in individuals with chr16p11.2 microdeletion. Acknowledgments DT conceived the research, designed the experiments, performed surgeries, conducted sleep recording, scored EEG, analyzed data, and wrote the article. HCL designed the experiments, performed patch clamp, analyzed data, and co-wrote the article. HP scored EEG, analyzed the data, and co-wrote the article. AAM provided chr16p11.2df/+ mice and edited the article. We sincerely thank Dr Allison T. Knoll for critically reading the article. We also thank the Translational Biomedical Imaging Laboratory (TBIL) of CHLA for the technical support. Funding This study was supported by a Research Career Development Award from The Saban Research Institute of CHLA (8030-RRI007513 to DT) and by the Simons Foundation Autism Research Initiative (SFARI to AAM and DT). Conflict of interest statement. None declared. References 1. Wiggs L , et al. Sleep patterns and sleep disorders in children with autistic spectrum disorders: insights using parent report and actigraphy . 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TI - Altered sleep architecture, rapid eye movement sleep, and neural oscillation in a mouse model of human chromosome 16p11.2 microdeletion
JF - SLEEP
DO - 10.1093/sleep/zsy253
DA - 2018-12-12
UR - https://www.deepdyve.com/lp/oxford-university-press/altered-sleep-architecture-rapid-eye-movement-sleep-and-neural-kdttmpwuTj
SP - 1
VL - Advance Article
IS - 
DP - DeepDyve
ER -