An Antisense Oligonucleotide Leads to Suppressed Transcription of Hdac2 and Long-Term Memory Enhancement.

Knockout of the memory suppressor gene histone deacetylase 2 (Hdac2) in mice elicits cognitive enhancement, and drugs that block HDAC2 have potential as therapeutics for disorders affecting memory. Currently available HDAC2 catalytic activity inhibitors are not fully isoform specific and have short half-lives. Antisense oligonucleotides (ASOs) are drugs that elicit extremely long-lasting, specific inhibition through base pairing with RNA targets. We utilized an ASO to reduce Hdac2 messenger RNA (mRNA) in mice and determined its longevity, specificity, and mechanism of repression. A single injection of the Hdac2-targeted ASO in the central nervous system produced persistent reduction in HDAC2 protein and Hdac2 mRNA levels for 16 weeks. It enhanced object location memory for 8 weeks. RNA sequencing (RNA-seq) analysis of brain tissues revealed that the repression was specific to Hdac2 relative to related Hdac isoforms, and Hdac2 reduction caused alterations in the expression of genes involved in extracellular signal-regulated kinase (ERK) and memory-associated immune signaling pathways. Hdac2-targeted ASOs also suppress a nonpolyadenylated Hdac2 regulatory RNA and elicit direct transcriptional suppression of the Hdac2 gene through stalling RNA polymerase II. These findings identify transcriptional suppression of the target gene as a novel mechanism of action of ASOs.

Cognition-Enhancing Vagus Nerve Stimulation Alters the Epigenetic Landscape.

Vagus nerve stimulation (VNS) has been shown to enhance learning and memory, yet the mechanisms behind these enhancements are unknown. Here, we present evidence that epigenetic modulation underlies VNS-induced improvements in cognition. We show that VNS enhances novelty preference (NP); alters the hippocampal, cortical, and blood epigenetic transcriptomes; and epigenetically modulates neuronal plasticity and stress-response signaling genes in male Sprague Dawley rats. Brain-behavior analysis revealed structure-specific relationships between NP test performance (NPTP) and epigenetic alterations. In the hippocampus, NPTP correlated with decreased histone deacetylase 11 (HDAC11), a transcriptional repressor enriched in CA1 cells important for memory consolidation. In the cortex, the immediate early gene (IEG) ARC was increased in VNS rats and correlated with transcription of plasticity genes and epigenetic regulators, including HDAC3. For rats engaged in NPTP, ARC correlated with performance. Interestingly, blood ARC transcripts decreased in VNS rats performing NPTP, but increased in VNS-only rats. Because DNA double-strand breaks (DSBs) facilitate transcription of IEGs, we investigated phosphorylated H2A.X (γH2A.X), a histone modification known to colocalize with DSBs. In agreement with reduced cortical stress-response transcription factor NF-κB1, chromatin immunoprecipitation revealed reduced γH2A.X in the ARC promoter. Surprisingly, VNS did not significantly reduce transcription of cortical or hippocampal proinflammatory cytokines. However, TNFRSF11B (osteoprotegerin) correlated with NPTP as well as plasticity, stress-response signaling, and epigenetic regulation transcripts in both hippocampus and cortex. Together, our findings provide the first evidence that VNS induces widespread changes in the cognitive epigenetic landscape and specifically affects epigenetic modulators associated with NPTP, stress-response signaling, memory consolidation, and cortical neural remodeling.SIGNIFICANCE STATEMENT Recent studies have implicated vagus nerve stimulation (VNS) in enhanced learning and memory. However, whereas epigenetic modifications are known to play an important role in memory, the particular mechanisms involved in VNS-enhanced cognition are unknown. In this study, we examined brain and behavior changes in VNS and sham rats performing a multiday novelty preference (NP) task. We found that VNS activated specific histone modifications and DNA methylation changes at important stress-response signaling and plasticity genes. Both cortical and hippocampal plasticity changes were predictive of NP test performance. Our results reveal important epigenetic alterations associated with VNS cognitive improvements, as well as new potential pharmacological targets for enhancing cortical and hippocampal plasticity.

Stimulation of Cortico-Subthalamic Projections Amplifies Resting Motor Circuit Activity and Leads to Increased Locomotion in Dopamine-Depleted Mice.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) improves motor function in patients with Parkinson's disease (PD). STN-DBS enables similar improved motor function, including increased movement speed (reduced bradykinesia), in the 6-OHDA dopamine-depletion mouse model of PD. Previous analyses of electrophysiological recordings from STN and motor cortex (M1) have explored signaling changes that correspond to PD and amelioration of PD symptoms. The most common results show an increase in beta frequency power during 'off' states and a reduction in beta during 'on' states. Surprisingly, however, few studies have analyzed whole signal measures of amplitude and coherence during stimulation in freely moving subjects. In previous work by the author, specific transfection of layer five motor cortex projections to the STN revealed an axonal network with collaterals reaching to multiple non-dopaminergic subcortical areas of the brain. The large excitatory shift that stimulation of this axonal network could potentially induce inspired the current study's hypothesis that amplification of excitatory signaling occurs during stimulation of cortico-subthalamic projections. The results show that, in awake mice, (1) the root-mean-square amplitudes of STN and M1 local field potentials (LFPs) are significantly decreased ipsilateral to chronic unilateral 6-OHDA lesions, (2) stimulation of cortico-subthalamic projections increases the amplitude of M1- and STN-LFPs, and 3) M1-LFP amplitude correlates strongly with locomotion speed in lesioned mice. Together, these findings demonstrate that bradykinesia-reducing stimulation of cortico-subthalamic projections amplifies both cortical and subcortical motor circuit activity in unilaterally dopamine-depleted mice. Most PD treatments are focused on increasing dopamine in the dorsal striatum. However, in this study, stimulation of layer five cortico-subthalamic glutamatergic axons that do not directly project to dopaminergic neurons increased movement and amplified cortico-subthalamic excitatory signaling in dopamine-depleted mice. The correlation between M1-LFP amplitude and locomotion speed observed in these mice points to a role for upregulated hyperdirect pathway excitatory signaling in bradykinesia amelioration. In addition to providing insight into the elusive mechanisms of DBS, these motor circuit amplification relationships suggest that specific manipulation of NMDA, AMPA, and/or metabotropic glutamate receptors in the hyperdirect pathway may be beneficial for upregulating signaling and movement in PD.

Optogenetic stimulation of cortico-subthalamic projections is sufficient to ameliorate bradykinesia in 6-ohda lesioned mice.

Electrical deep brain stimulation (DBS) of the subthalamic nucleus (STN) is effective for ameliorating the motor symptoms of Parkinson's disease (PD) including bradykinesia. The STN receives its main excitatory input from cortex; however, the contribution of cortico-subthalamic projection neurons to the effects of DBS remains unclear. To isolate the consequences of stimulating layer 5 primary motor cortex (M1) projections to the STN, we used a dual virus transfection technique to selectively express opsins in these neurons in mice made parkinsonian by unilateral nigrostriatal 6-OHDA lesioning. AAVs containing WGA-Cre constructs were injected in the STN to retrogradely place Cre in STN afferents, while AAVs containing Cre-dependent ultrafast hChR2(E123T/T159C)-EYFP opsin constructs were injected in M1 layer 5, producing specific opsin expression in M1-STN projections. Under unstimulated conditions, lesioned mice showed bradykinesia and hypokinesia (decreased movement), along with electrophysiological changes similar to those observed in PD patients. Specifically, low frequency power (theta, alpha, low beta) was increased and gamma power was decreased, while M1/STN coherence and STN phase-amplitude-coupling (PAC) were increased. Optogenetic stimulation (100-130Hz) of STN afferents in these mice ameliorated bradykinesia and hypokinesia and brought the neural dynamics closer to the non-parkinsonian state by reducing theta and alpha and increasing gamma power in M1, decreasing STN PAC, and reducing theta band coherence. Histological examination of the EYFP expression revealed that, in addition to orthodromic and antidromic effects, stimulation of cortico-subthalamic neurons may cause wide-spread increased glutamatergic activity due to collaterals that project to areas of the thalamus and other brain regions.

Phase-amplitude coupling, an indication of bursting in parkinsonism, is masked by periodic pulses.

Interactions between neural oscillations in the brain have been observed in many structures including the hippocampus, amygdala, motor cortex, and basal ganglia. In this study, one popular approach for quantifying oscillation interactions was considered: phase-amplitude coupling. The goals of the study were to use simulations to examine potential causes of elevated phase-amplitude coupling in parkinsonism, to compare simulated parkinsonian signals with recorded local field potentials from animal models of parkinsonism, to investigate possible relationships between increased bursting in parkinsonian single cells and elevated phase-amplitude coupling, and to uncover potential noise and artifact effects. First, a cell model that integrates incremental input currents and fires at realistic voltage thresholds was modified to allow control of stochastic parameters related to firing and burst rates. Next, the input currents and distribution of integration times were set to reproduce firing patterns consistent with those from parkinsonian subthalamic nucleus cells. Then, local field potentials were synthesized from the output of multiple simulated cells with varying degrees of synchronization and compared with subthalamic nucleus recordings from animal models of parkinsonism. The results showed that phase-amplitude coupling can provide important information about underlying neural activity. In particular, signals synthesized from synchronized bursting neurons showed increased oscillatory interactions similar to those observed in parkinsonian animals. Additionally, changes in bursting parameters such as the intraburst rate, the mean interburst period, and the amount of synchronization between neurons influenced the phase-amplitude coupling in predictable ways. Finally, simulation results revealed that small periodic signals can have a surprisingly large masking effect on phase-amplitude coupling.

Sleep stage classification with cross frequency coupling.

Sleep is a key requirement for an individual's health, though currently the options to study sleep rely largely on manual visual classification methods. In this paper we propose a new scheme for automated offline classification based upon cross-frequency-coupling (CFC) and compare it to the traditional band power estimation and the more recent preferential frequency band information estimation. All three approaches allowed sleep stage classification and provided whole-night visualization of sleep stages. Surprisingly, the simple average power in band classification achieved better overall performance than either the preferential frequency band information estimation or the CFC approach. However, combined classification with both average power and CFC features showed improved classification over either approach used singly.

Parkinsonism-related features of neuronal discharge in primates.

Parkinson's disease is known to be associated with abnormal electrical spiking activities of basal ganglia neurons, including changes in firing rate, bursting activities and oscillatory firing patterns and changes in entropy. We explored the relative importance of these measures through optimal feature selection and discrimination analysis methods. We identified key characteristics of basal ganglia activity that predicted whether the neurons were recorded in the normal or parkinsonian state. Starting with 29 features extracted from the spike timing of neurons recorded in normal and parkinsonian monkeys in the internal or external segment of the globus pallidus or the subthalamic nucleus (STN), we used a method that incorporates a support vector machine algorithm to find feature combinations that optimally discriminate between the normal and parkinsonian states. Our results demonstrate that the discrimination power of combinations of specific features is higher than that of single features, or of all features combined, and that the most discriminative feature sets differ substantially between basal ganglia structures. Each nucleus or class of neurons in the basal ganglia may react differently to the parkinsonian condition, and the features used to describe this state should be adapted to the neuron type under study. The feature that was overall most predictive of the parkinsonian state in our data set was a high STN intraburst frequency. Interestingly, this feature was not correlated with parameters describing oscillatory firing properties in recordings made in the normal condition but was significantly correlated with spectral power in specific frequency bands in recordings from the parkinsonian state (specifically with power in the 8-13 Hz band).

Canonical Correlation to Estimate the Degree of Parkinsonism from Local Field Potential and Electroencephalographic Signals.

In this study, modulation index (MI) features derived from local field potential (LFP) recordings in the subthalamic nucleus (STN) and electroencephalographic recordings (EEGs) from the primary motor cortex are shown to correlate with both the overall motor impairment and motor subscores in a monkey model of parkinsonism. The MI features used are measures of phase-amplitude cross frequency coupling (CFC) between frequency sub-bands. We used complex wavelet transforms to extract six spectral sub-bands within the 3-60 Hz range from LFP and EEG signals. Using the method of canonical correlation, we show that weighted combinations of the MI features in LFP or EEG signals correlate significantly with individual and composite scores on a scale for parkinsonian disability.

Development of an automatic quantification method for cancer tissue microarray study.

Clinical Histopathology is based on the analysis of immunohistochemistry (IHC) stained tissue images. Selection of antibodies for detecting the presence, type, and grade of cancerous tissue has a great influence on the diagnostic potential of IHC tests. Automated evaluation methods for tissue microarrays applied to many combinations of antibody and tissue type can speed development of new clinical assays. We present an automatic method that successfully quantifies stain intensity, fraction of cells stained and sub-cellular location of staining in tissue microarray images. The method combines an opponent color preprocessor and a novel statistical approach for identifying brown and blue staining, followed by multilevel morphological processing. We verify the capability of our method by comparing the results to manually annotated image databases. We also demonstrate cross-tissue robustness using two clinical case study data.