Robert G. Wither

Daily Rhythmic Behaviors and Thermoregulatory Patterns Are Disrupted in Adult Female MeCP2-Deficient Mice

Mutations in the X-linked gene encoding Methyl-CpG-binding protein 2 (MECP2) have been associated with neurodevelopmental and neuropsychiatric disorders including Rett Syndrome, X-linked mental retardation syndrome, severe neonatal encephalopathy, and Angelman syndrome. Although alterations in the performance of MeCP2-deficient mice in specific behavioral tasks have been documented, it remains unclear whether or not MeCP2 dysfunction affects patterns of periodic behavioral and electroencephalographic (EEG) activity. The aim of the current study was therefore to determine whether a deficiency in MeCP2 is sufficient to alter the normal daily rhythmic patterns of core body temperature, gross motor activity and cortical delta power. To address this, we monitored individual wild-type and MeCP2-deficient mice in their home cage environment via telemetric recording over 24 hour cycles. Our results show that the normal daily rhythmic behavioral patterning of cortical delta wave activity, core body temperature and mobility are disrupted in one-year old female MeCP2-deficient mice. Moreover, female MeCP2-deficient mice display diminished overall motor activity, lower average core body temperature, and significantly greater body temperature fluctuation than wild-type mice in their home-cage environment. Finally, we show that the epileptiform discharge activity in female MeCP2-deficient mice is more predominant during times of behavioral activity compared to inactivity. Collectively, these results indicate that MeCP2 deficiency is sufficient to disrupt the normal patterning of daily biological rhythmic activities.

Differential expression of sirtuin family members in the developing, adult, and aged rat brain.

The sirtuins are NAD+-dependent protein deacetylases and/or ADP-ribosyltransferases that play roles in metabolic homeostasis, stress response and potentially aging. This enzyme family resides in different subcellular compartments, and acts on a number of different targets in the nucleus, cytoplasm and in the mitochondria. Despite their recognized ability to regulate metabolic processes, the roles played by specific sirtuins in the brain—the most energy demanding tissue in the body—remains less well investigated and understood. In the present study, we examined the regional mRNA and protein expression patterns of individual sirtuin family members in the developing, adult, and aged rat brain. Our results show that while each sirtuin is expressed in the brain at each of these different stages, they display unique spatial and temporal expression patterns within the brain. Further, for specific members of the family, the protein expression profile did not coincide with their respective mRNA expression profile. Moreover, using primary cultures enriched for neurons and astrocytes respectively, we found that specific sirtuin members display preferential neural lineage expression. Collectively, these results provide the first composite illustration that sirtuin family members display differential expression patterns in the brain, and provide evidence that specific sirtuins could potentially be targeted to achieve cell-type selective effects within the brain.

Rescue of behavioral and EEG deficits in male and female Mecp2-deficient mice by delayed Mecp2 gene reactivation

Mutations of the X-linked gene encoding methyl CpG binding protein type 2 (MECP2) are the predominant cause of Rett syndrome, a severe neurodevelopmental condition that affects primarily females. Previous studies have shown that major phenotypic deficits arising from MeCP2-deficiency may be reversible, as the delayed reactivation of the Mecp2 gene in Mecp2-deficient mice improved aspects of their Rett-like phenotype. While encouraging for prospective gene replacement treatments, it remains unclear whether additional Rett syndrome co-morbidities recapitulated in Mecp2-deficient mice will be similarly responsive to the delayed reintroduction of functional Mecp2. Here, we show that the delayed reactivation of Mecp2 in both male and female Mecp2-deficient mice rescues established deficits in motor and anxiety-like behavior, epileptiform activity, cortical and hippocampal electroencephalogram patterning and thermoregulation. These findings indicate that neural circuitry deficits arising from the deficiency in Mecp2 are not engrained, and provide further evidence that delayed restoration of Mecp2 function can improve a wide spectrum of the Rett-like deficits recapitulated by Mecp2-deficient mice.

Regional MeCP2 expression levels in the female MeCP2-deficient mouse brain correlate with specific behavioral impairments

Using female MeCP2-deficient mice as a model, we tested whether MeCP2 expression levels would parallel one another in different regions of the brain and spinal cord, and/or whether the levels of MeCP2 protein in these specific neural regions would correlate with the degree of behavioral impairment seen in individual subjects. Our results show that MeCP2 protein levels are not uniform across different regions of the mosaic brain, and that the relative MeCP2 levels in one region did not necessarily predict its expression levels in other regions of the same mouse. Correlational analysis between region-specific MeCP2 expression levels and the degree of impairment exhibited by mice in specific behavioral tests revealed significant associations. Cortical MeCP2 expression was significantly correlated with general symptomatic severity and daily EEG delta power patterning. Hippocampal MeCP2 expression was significantly correlated with exploratory activity behaviors, anxiety-like behaviors, and epileptiform discharge rates, whereas cerebellar and spinal cord MeCP2 expression levels correlated only with daily EEG delta power patterning. Collectively, our results show that MeCP2 protein expression in female MeCP2-deficient mice is not uniform throughout specific brain regions, and indicate that specific behavioral deficits in these mice may correlate with the region-specific expression levels of the functional MeCP2 allele.

Selective preservation of MeCP2 in catecholaminergic cells is sufficient to improve the behavioral phenotype of male and female Mecp2-deficient mice

Rett syndrome (RTT) is a neurodevelopmental disorder caused primarily by mutations of the X-linked MECP2 gene. Although the loss of MeCP2 function affects many neural systems, impairments of catecholaminergic function have been hypothesized to underlie several of the cardinal behavioral deficits of RTT patients and Mecp2-deficient mice. Although recent Mecp2 reactivation studies indicate that RTT may be a reversible condition, it remains unclear whether specifically preserving Mecp2 function within a specific system will be sufficient to convey beneficial effects. Here, we test whether the selective preservation of Mecp2 within catecholaminergic cells will improve the phenotype of Mecp2-deficient mice. Our results show that this targeted preservation of Mecp2 significantly improves the lifespan, phenotypic severity and cortical epileptiform discharge activity of both male and female Mecp2-deficient mice. Further, we found that the catecholaminergic preservation of Mecp2 also improves the ambulatory rate, rearing activity, motor coordination, anxiety and nest-building performances of Mecp2-deficient mice of each gender. Interestingly, our results also revealed a gender-specific improvement, as specific cortical and hippocampal electroencephalographic abnormalities were significantly improved in male, but not female, rescue mice. Collectively, these results support the role of the catecholaminergic system in the pathogenesis of RTT and provide proof-of-principle that restoring MeCP2 function within this specific system could represent a treatment strategy for RTT.

Characterization of seizure-like events recorded in vivo in a mouse model of Rett syndrome

Rett syndrome is a neurodevelopmental disorder caused by mutations in the X-linked gene encoding methyl-CpG-binding protein 2 (MECP2). Spontaneous recurrent discharge episodes are displayed in Rett-related seizures as in other types of epilepsies. The aim of this paper is to investigate the seizure-like event (SLE) and inter-SLE states in a female MeCP2-deficient mouse model of Rett syndrome and compare them to those found in other spontaneous recurrent epilepsy models. The study was performed on a small population of female MeCP2-deficient mice using telemetric local field potential (LFP) recordings over a 24 h period. Durations of SLEs and inter-SLEs were extracted using a rule-based automated SLE detection system for both daytime and nighttime, as well as high and low power levels of the delta frequency range (0.5-4 Hz) of the recorded LFPs. The results suggest SLE occurrences are not influenced by circadian rhythms, but had a significantly greater association with delta power. Investigating inter-SLE and SLE states by fitting duration histograms to the gamma distribution showed that SLE initiation and termination were associated with random and deterministic mechanisms, respectively. These findings when compared to reported studies on epilepsy suggest that Rett-related seizures share many similarities with absence epilepsy.

Characterization of HFOs in short and long duration discharges recorded from in-vivo MeCP2-deficient mice.

Mutations in the X-linked gene encoding methyl CpG-binding protein 2 (MeCP2) have been linked to a neurodevelopmental disorder known as Rett syndrome. The disorder is associated with a number of symptoms, of which epileptic seizures are common. In this study we examined the presence of high frequency oscillations (HFOs) and their interactions with low frequency oscillations (LFOs) during epileptiform-like discharges using intracranial electroencephalogram (iEEG) recordings from male and female Mecp2-deficient mice. The study compared differences in mean HFO power levels normalized to baseline along with LFO-HFO modulation observed in short and long duration discharges. Short duration discharges, common to both male and female Mecp2-deficient mice, showed a decrease in mean HFO power levels compared to baseline levels. During the short duration discharges the theta (7-9 Hz) LFOs were found to modulate fast ripple (350-500 Hz) HFOs predominantly in the female Mecp2-deficient mice. Long duration discharges, predominantly observed in male Mecp2-deficient mice, were found to have elevated mean power levels in the ripple (80-200 Hz) and fast ripple (350-500 Hz) frequency ranges when compared to baseline. During the long duration discharges a lower frequency range theta LFO (4-6 Hz) modulated both the ripple (80-200 Hz) and fast ripple (350-500 Hz) HFOs. These findings suggest that the long duration discharges observed in male Mecp2-deficient mice share biomarkers indicative of seizure-like activity.

Low frequency-modulated high frequency oscillations in seizure-like events recorded from in-vivo MeCP2-deficient mice

Rett syndrome is a neurodevelopmental condition caused by mutations in the gene encoding methyl CpG-binding protein 2 (MeCP2). Seizures are often associated with Rett syndrome and can be observed in intracranial electroencephalogram (iEEG) recordings. To date most studies have focused on the low frequencies oscillations (LFOs), however recent findings in epilepsy studies link high frequency oscillations (HFOs) with epileptogenesis. In this study, we examine the presence of HFOs in the male and female MeCP2-deficient mouse models of Rett syndrome and their interaction with the LFOs present during seizure-like events (SLEs). Our findings indicate that HFOs (200-600 Hz) are present during the SLEs and in addition, we reveal strong phase-amplitude coupling between LFOs (6-10 Hz) and HFOs (200-600 Hz) during female SLEs in the MeCP2-deficient mouse model.

EEG analysis for estimation of duration and inter-event intervals of seizure-like events recorded in vivo from mice

Rett syndrome is a neurodevelopmental disorder of the brain that affects females more often than males. Its cause is linked to the mutations within the gene encoding methyl CpG-binding protein 2 (MeCP2). Presently, there is little information regarding how the loss of MeCP2 affects brain activity. It has been documented that during awake but immobile state, the MeCP2 deficient mice exhibit spontaneous, rhythmic electroencephalogram (EEG) seizure-like events (SLEs) in the range of 6–9 Hz. In this study, we analyze the cortical EEG activity in female MeCP2-deficient mice over 24 hour recordings. Characterizing the SLE and inter-SLE durations by fitting to a gamma distribution we show similarity to previous in vivo epilepsy studies. These results suggest that the SLE and inter-SLE dynamics differ. More precisely, the SLE terminations appear to be a result of time-dependent mechanisms, whereas the inter-SLEs are a result of a random process.

Prediction of antiepileptic drug treatment outcomes using machine learning

OBJECTIVE Antiepileptic drug (AED) treatments produce inconsistent outcomes, often necessitating patients to go through several drug trials until a successful treatment can be found. This study proposes the use of machine learning techniques to predict epilepsy treatment outcomes of commonly used AEDs. APPROACH Machine learning algorithms were trained and evaluated using features obtained from intracranial electroencephalogram (iEEG) recordings of the epileptiform discharges observed in Mecp2-deficient mouse model of the Rett Syndrome. Previous work have linked the presence of cross-frequency coupling (I CFC) of the delta (2-5 Hz) rhythm with the fast ripple (400-600 Hz) rhythm in epileptiform discharges. Using the I CFC to label post-treatment outcomes we compared support vector machines (SVMs) and random forest (RF) machine learning classifiers for providing likelihood scores of successful treatment outcomes. MAIN RESULTS (a) There was heterogeneity in AED treatment outcomes, (b) machine learning techniques could be used to rank the efficacy of AEDs by estimating likelihood scores for successful treatment outcome, (c) I CFC features yielded the most effective a priori identification of appropriate AED treatment, and (d) both classifiers performed comparably. SIGNIFICANCE Machine learning approaches yielded predictions of successful drug treatment outcomes which in turn could reduce the burdens of drug trials and lead to substantial improvements in patient quality of life.