MicroRNAs are post-transcriptional regulators of gene expression, crucial for neuronal differentiation, survival, and activity. Age-related dysregulation of microRNA biogenesis increases neuronal vulnerability to cellular stress and may contribute to the development and progression of neurodegenerative diseases. All major neurodegenerative disorders are also associated with oxidative stress, which is widely recognized as a potential target for protective therapies. Albeit often considered separately, microRNA networks and oxidative stress are inextricably entwined in neurodegenerative processes. Oxidative stress affects expression levels of multiple microRNAs and, conversely, microRNAs regulate many genes involved in an oxidative stress response. Both oxidative stress and microRNA regulatory networks also influence other processes linked to neurodegeneration, such as mitochondrial dysfunction, deregulation of proteostasis, and increased neuroinflammation, which ultimately lead to neuronal death. Modulating the levels of a relatively small number of microRNAs may therefore alleviate pathological oxidative damage and have neuroprotective activity. Here, we review the role of individual microRNAs in oxidative stress and related pathways in four neurodegenerative conditions: Alzheimer’s (AD), Parkinson’s (PD), Huntington’s (HD) disease, and amyotrophic lateral sclerosis (ALS). We also discuss the problems associated with the use of oversimplified cellular models and highlight perspectives of studying microRNA regulation and oxidative stress in human stem cell-derived neurons.

Unbiased estimates of neuron numbers within substantia nigra are crucial for experimental Parkinson's disease models and gene-function studies. Unbiased stereological counting techniques with optical fractionation are successfully implemented, but are extremely laborious and time-consuming. The development of neural networks and deep learning has opened a new way to teach computers to count neurons. Implementation of a programming paradigm enables a computer to learn from the data and development of an automated cell counting method. The advantages of computerized counting are reproducibility, elimination of human error and fast high-capacity analysis. We implemented whole-slide digital imaging and deep convolutional neural networks (CNN) to count substantia nigra dopamine neurons. We compared the results of the developed method against independent manual counting by human observers and validated the CNN algorithm against previously published data in rats and mice, where tyrosine hydroxylase (TH)-immunoreactive neurons were counted using unbiased stereology. The developed CNN algorithm and fully cloud-embedded Aiforia™ platform provide robust and fast analysis of dopamine neurons in rat and mouse substantia nigra.

Parkinson's disease (PD) is an age‐related neurodegenerative disorder characterized by motor symptoms such as tremor, slowness of movement, rigidity, and postural instability, as well as non‐motor features like sleep disturbances, loss of ability to smell, depression, constipation, and pain. Motor symptoms are caused by depletion of dopamine in the striatum due to the progressive loss of dopamine neurons in the substantia nigra pars compacta. Approximately 10% of PD cases are familial arising from genetic mutations in α‐synuclein, LRRK2, DJ‐1, PINK1, parkin, and several other proteins. The majority of PD cases are, however, idiopathic, i.e., having no clear etiology. PD is characterized by progressive accumulation of insoluble inclusions, known as Lewy bodies, mostly composed of α‐synuclein and membrane components. The cause of PD is currently attributed to cellular proteostasis deregulation and mitochondrial dysfunction, which are likely interdependent. In addition, neuroinflammation is present in brains of PD patients, but whether it is the cause or consequence of neurodegeneration remains to be studied. Rodents do not develop PD or PD‐like motor symptoms spontaneously; however, neurotoxins, genetic mutations, viral vector‐mediated transgene expression and, recently, injections of misfolded α‐synuclein have been successfully utilized to model certain aspects of the disease. Here, we critically review the advantages and drawbacks of rodent PD models and discuss approaches to advance pre‐clinical PD research towards successful disease‐modifying therapy. © 2020 The Authors.

Glial cell line-derived neurotrophic factor (GDNF) is one of the most studied neurotrophic factors. GDNF has two splice isoforms, full-length pre-α-pro-GDNF (α-GDNF) and pre-β-pro-GDNF (β-GDNF), which has a 26 amino acid deletion in the pro-region. Thus far, studies have focused solely on the α-GDNF isoform, and nothing is known about the in vivo effects of the shorter β-GDNF variant. Here we compare for the first time the effects of overexpressed α-GDNF and β-GDNF in non-lesioned rat striatum and the partial 6-hydroxydopamine lesion model of Parkinson's disease. GDNF isoforms were overexpressed with their native pre-pro-sequences in the striatum using an adeno-associated virus (AAV) vector, and the effects on motor performance and dopaminergic phenotype of the nigrostriatal pathway were assessed. In the non-lesioned striatum, both isoforms increased the density of dopamine transporter-positive fibers at 3 weeks after viral vector delivery. Although both isoforms increased the activity of the animals in cylinder assay, only α-GDNF enhanced the use of contralateral paw. Four weeks later, the striatal tyrosine hydroxylase (TH)-immunoreactivity was decreased in both α-GDNF and β-GDNF treated animals. In the neuroprotection assay, both GDNF splice isoforms increased the number of TH-immunoreactive cells in the substantia nigra but did not promote behavioral recovery based on amphetamine-induced rotation or cylinder assays. Thus, the shorter GDNF isoform, β-GDNF, and the full-length α-isoform have comparable neuroprotective efficacy on dopamine neurons of the nigrostriatal circuitry.

The cytomegalovirus (CMV) immediate early promoter has been extensively developed and exploited for transgene expression in vitro and in vivo , including human clinical trials. The CMV promoter has long been considered a stable, constitutive, and ubiquitous promoter for transgene expression. Using two different CMV-based promoters, we found an increase in CMV-driven transgene expression in the rodent brain and in primary neuronal cultures in response to methamphetamine, glutamate, kainic acid, and activation of G protein-coupled receptor signaling using designer receptors exclusively activated by designer drugs (DREADDs). In contrast, promoters derived from human synapsin 1 (hSYN1) gene or elongation factor 1α (EF1α) did not exhibit altered transgene expression in response to the same neuronal stimulations. Overall, our results suggest that the long-standing assertion that the CMV promoter confers constitutive expression in neurons should be reevaluated, and future studies should empirically determine the activity of the CMV promoter in a given application.

The endoplasmic reticulum (ER) is a multipurpose organelle comprising dynamic structural subdomains, such as ER sheets and tubules, serving to maintain protein, calcium, and lipid homeostasis. In neurons, the single ER is compartmentalized with a careful segregation of the structural subdomains in somatic and neurite (axodendritic) regions. The distribution and arrangement of these ER subdomains varies between different neuronal types. Mutations in ER membrane shaping proteins and morphological changes in the ER are associated with various neurodegenerative diseases implying significance of ER morphology in maintaining neuronal integrity. Specific neurons, such as the highly arborized dopaminergic neurons, are prone to stress and neurodegeneration. Differences in morphology and functionality of ER between the neurons may account for their varied sensitivity to stress and neurodegenerative changes. In this review, we explore the neuronal ER and discuss its distinct morphological attributes and specific functions. We hypothesize that morphological heterogeneity of the ER in neurons is an important factor that accounts for their selective susceptibility to neurodegeneration.

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