Faculty Bibliography

Single-cell and single-population RNA sequencing (RNA-seq) is a rapidly evolving new field of intense investigation. Recent studies indicate unique transcriptomic profiles are derived based on the spatial localization of neurons within circuits and regions. Individual neuronal subtypes can have vastly different transcriptomic fingerprints, well beyond the basic excitatory neuron and inhibitory neuron designations. To study single-population gene expression profiles of spatially characterized neurons, we have developed a methodology combining laser capture microdissection (LCM), RNA purification of single populations of neurons, and subsequent library preparation for downstream applications, including RNA-seq. LCM provides the benefit of isolating single neurons characterized by morphology or via transmitter-identified and/or receptor immunoreactivity and enables spatial localization within the sample. We utilize unfixed human postmortem and mouse brain tissue that is frozen to preserve RNA quality in order to isolate the desired neurons of interest. Microisolated neurons are then pooled for RNA purification utilizing as few as 250 individual neurons from a tissue section, precluding extraneous nonspecific tissue contaminants. Library preparation is performed from picogram RNA quantities extracted from LCM-captured neurons. Single-population RNA-seq analysis demonstrates that microisolated neurons from both postmortem human and mouse brain tissues are viable for transcriptomic profiling, including differential gene expression assessment and bioinformatic pathway inquiry.

Extracellular vesicles (EVs) are small, lipid-bilayer-bound particles released by cells that can contain important bioactive molecules, including lipids, RNAs, and proteins. Once released in the extracellular environment, EVs can act as messengers locally as well as to distant tissues to coordinate tissue homeostasis and systemic responses. There is a growing interest in not only understanding the physiology of EVs as signaling particles but also leveraging them as minimally invasive diagnostic and prognostic biomarkers (e.g., they can be found in biofluids) and drug-delivery vehicles. On October 30-November 2, 2022, researchers in the EV field convened for the Keystone symposium "Exosomes, Microvesicles, and Other Extracellular Vesicles" to discuss developing standardized language and methodology, new data on the basic biology of EVs and potential clinical utility, as well as novel technologies to isolate and characterize EVs.

Cannabidiol (CBD), a non-euphoric component of cannabis, reduces seizures in multiple forms of pediatric epilepsies, but the mechanism(s) of anti-seizure action remain unclear. In one leading model, CBD acts at glutamatergic axon terminals, blocking the pro-excitatory actions of an endogenous membrane phospholipid, lysophosphatidylinositol (LPI), at the G-protein-coupled receptor GPR55. However, the impact of LPI-GPR55 signaling at inhibitory synapses and in epileptogenesis remains underexplored. We found that LPI transiently increased hippocampal CA3-CA1 excitatory presynaptic release probability and evoked synaptic strength in WT mice, while attenuating inhibitory postsynaptic strength by decreasing GABA_ARγ₂ and gephyrin puncta. LPI effects at excitatory and inhibitory synapses were eliminated by CBD pre-treatment and absent after GPR55 deletion. Acute pentylenetrazole-induced seizures elevated GPR55 and LPI levels, and chronic lithium-pilocarpine-induced epileptogenesis potentiated LPI's pro-excitatory effects. We propose that CBD exerts potential anti-seizure effects by blocking LPI's synaptic effects and dampening hyperexcitability.

Diseases are manifestations of complex changes in protein-protein interaction (PPI) networks whereby stressors, genetic, environmental, and combinations thereof, alter molecular interactions and perturb the individual from the level of cells and tissues to the entire organism. Targeting stressor-induced dysfunctions in PPI networks has therefore become a promising but technically challenging frontier in therapeutics discovery. This opinion provides a new framework based upon disrupting epichaperomes - pathological entities that enable dysfunctional rewiring of PPI networks - as a mechanism to revert context-specific PPI network dysfunction to a normative state. We speculate on the implications of recent research in this area for a precision medicine approach to detecting and treating complex diseases, including cancer and neurodegenerative disorders.

Cocaine, an addictive psychostimulant, has a broad mechanism of action, including the induction of a wide range of alterations in brain metabolism and mitochondrial homeostasis. Our group recently identified a subpopulation of non-microvesicular, non-exosomal extracellular vesicles of mitochondrial origin (mitovesicles) and developed a method to isolate mitovesicles from brain parenchyma. We hypothesised that the generation and secretion of mitovesicles is affected by mitochondrial abnormalities induced by chronic cocaine exposure. Mitovesicles from the brain extracellular space of cocaine-administered mice were enlarged and more numerous when compared to controls, supporting a model in which mitovesicle biogenesis is enhanced in the presence of mitochondrial alterations. This interrelationship was confirmed in vitro. Moreover, cocaine affected mitovesicle protein composition, causing a functional alteration in mitovesicle ATP production capacity. These data suggest that mitovesicles are previously unidentified players in the biology of cocaine addiction and that target therapies to fine-tune brain mitovesicle functionality may be beneficial to mitigate the effects of chronic cocaine exposure.

Neurofilament and tau proteins are neuron-specific cytoskeletal proteins that are enriched in axons, regulated by many of the same protein kinases, interact physically, and are the principal constituents of neurofibrillary lesions in major adult-onset dementias. Both proteins share functions related to the modulation of stability and functions of the microtubule network in axons, axonal transport and scaffolding of organelles, long-term synaptic potentiation, and learning and memory. Expression of these proteins is regulated not only at the transcriptional level but also through posttranscriptional control of pre-mRNA splicing, mRNA stability, transport, localization, local translation and degradation. Current evidence suggests that posttranscriptional determinants of their levels are usually regulated by RNA-binding proteins and microRNAs primarily through 3'-untranslated regions of neurofilament and tau mRNAs. Dysregulations of neurofilament and tau expression caused by mutations or pathologies of RNA-binding proteins such as TDP43, FUS and microRNAs are increasingly recognized in association with varied neurological disorders. In this review, we summarize the current understanding of posttranscriptional control of neurofilament and tau by examining the posttranscriptional regulation of neurofilament and tau by RNA-binding proteins and microRNAs implicated in health and diseases.

OBJECTIVE:To test the hypothesis that high frequency oscillations (HFOs) between 250 and 500Hz occur in mouse models of Alzheimer's disease (AD) and thus are not unique to epilepsy. METHODS:Experiments were conducted in three mouse models of AD: Tg2576 mice that simulate a form of familial AD, presenilin 2 knock-out (PS2KO) mice, and the Ts65Dn model of Down's syndrome. We recorded HFOs using wideband (0.1-500Hz, 2kHz) intra-hippocampal and cortical surface EEG at 1month until 24months-old during wakefulness, slow wave sleep (SWS) and rapid eye movement (REM) sleep. Interictal spikes (IIS) and seizures were also analyzed for the possible presence of HFOs. Comparisons were made to the intra-hippocampal kainic acid and pilocarpine models of epilepsy. RESULTS:We describe for the first time that hippocampal and cortical HFOs are a new EEG abnormality in AD mouse models. HFOs occurred in all transgenic mice but no controls. They were also detectable as early as 1month of age and prior to amyloid-β plaque neuropathology. HFOs were most frequent during SWS (vs. REM or wakefulness). Notably, HFOs in the AD and epilepsy models were indistinguishable in both spectral frequency and duration. HFOs also occurred during IIS and seizures in the AD models, although with altered spectral properties compared to isolated HFOs. SIGNIFICANCE/CONCLUSIONS:Our data demonstrate that HFOs, an epilepsy biomarker with high translational value, are not unique to epilepsy and thus not disease specific. Our findings also strengthen the idea of hyperexcitability in AD and its significant overlap with epilepsy. HFOs in AD mouse models may serve as an EEG biomarker which is detectable from the scalp and thus amenable to non-invasive detection in people at risk for AD.

Linear regression is one of the most used statistical techniques in neuroscience, including the study of the neuropathology of Alzheimer's disease (AD) dementia. However, the practical utility of this approach is often limited because dependent variables are often highly skewed and fail to meet the assumption of normality. Applying linear regression analyses to highly skewed datasets can generate imprecise results, which lead to erroneous estimates derived from statistical models. Furthermore, the presence of outliers can introduce unwanted bias, which affect estimates derived from linear regression models. Although a variety of data transformations can be utilized to mitigate these problems, these approaches are also associated with various caveats. By contrast, a robust regression approach does not impose distributional assumptions on data allowing for results to be interpreted in a similar manner to that derived using a linear regression analysis. Here, we demonstrate the utility of applying robust regression to the analysis of data derived from studies of human brain neurodegeneration where the error distribution of a dependent variable does not meet the assumption of normality. We show that the application of a robust regression approach to two independent published human clinical neuropathologic data sets provides reliable estimates of associations. We also demonstrate that results from a linear regression analysis can be biased if the dependent variable is significantly skewed, further indicating robust regression as a suitable alternate approach.

Human apolipoprotein E (APOE) is the greatest determinant of genetic risk for memory deficits and Alzheimer's disease (AD). While APOE4 drives memory loss and high AD risk, APOE2 leads to healthy brain aging and reduced AD risk compared to the common APOE3 variant. We examined brain APOE protein levels in humanized mice homozygous for these alleles and found baseline levels to be age- and isoform-dependent: APOE2 levels were greater than APOE3, which were greater than APOE4. Despite the understanding that APOE lipoparticles do not traverse the blood-brain barrier, we show that brain APOE levels are responsive to dietary fat intake. Challenging mice for 6 months on a Western diet high in fat and cholesterol increased APOE protein levels in an allele-dependent fashion with a much greater increase within blood plasma than within the brain. In the brain, APOE2 levels responded most to the Western diet challenge, increasing by 20 % to 30 %. While increased lipoparticles are generally deleterious in the periphery, we propose that higher brain APOE2 levels may represent a readily available pool of beneficial lipid particles for neurons.