Toll-like receptor 4 deficiency facilitates α-synuclein propagation and neurodegeneration in a mouse model of prodromal Parkinson's disease

The evidence linking innate immunity mechanisms and neurodegenerative diseases is growing, but the specific mechanisms are incompletely understood. Experimental data suggest that microglial TLR4 mediates the uptake and clearance of α-synuclein also termed synucleinophagy. The accumulation of misfolded α-synuclein throughout the brain is central to Parkinson's disease (PD). The distribution and progression of the pathology is often attributed to the propagation of α-synuclein. Here, we apply a classical α-synuclein propagation model of prodromal PD in wild type and TLR4 deficient mice to study the role of TLR4 in the progression of the disease. Our data suggest that TLR4 deficiency facilitates the α-synuclein seed spreading associated with reduced lysosomal activity of microglia. Three months after seed inoculation, more pronounced proteinase K-resistant α-synuclein inclusion pathology is observed in mice with TLR4 deficiency. The facilitated propagation of α-synuclein is associated with early loss of dopamine transporter (DAT) signal in the striatum and loss of dopaminergic neurons in substantia nigra pars compacta of TLR4 deficient mice. These new results support TLR4 signaling as a putative target for disease modification to slow the progression of PD and related disorders

Signal transduction through tyrosine-phosphorylated C-terminal fragments of amyloid precursor protein via an enhanced interaction with Shc/Grb2 adaptor proteins in reactive astrocytes of Alzheimer's disease brain.

The proteolytic processing of amyloid precursor protein (APP) through the formation of membrane-bound C-terminal fragments (CTFs) and of soluble beta-amyloid peptides likely influences the development of Alzheimer's disease (AD). We show that in human brain a subset of CTFs are tyrosine-phosphorylated and form stable complexes with the adaptor protein ShcA. Grb2 is also part of these complexes, which are present in higher amounts in AD than in control brains. ShcA immunoreactivity is also greatly enhanced in patients with AD and occurs at reactive astrocytes surrounding cerebral vessels and amyloid plaques. A higher amount of phospho-ERK1,2, likely as result of the ShcA activation, is present in AD brains. In vitro experiments show that the ShcA-CTFs interaction is strictly confined to glial cells when treated with thrombin, which is a well known ShcA and ERK1,2 activator and a regulator of APP cleavage. In untreated cells ShcA does not interact with either APP or CTFs, although they are normally generated. Altogether these data suggest that CTFs are implicated in cell signaling via Shc transduction machinery, likely influencing MAPK activity and glial reaction in AD patients

Additional file 1: of Toll-like receptor 4 stimulation with monophosphoryl lipid A ameliorates motor deficits and nigral neurodegeneration triggered by extraneuronal Îą-synucleinopathy

Supplementary Table - Density of GCIs in the striatum and cerebellum. (DOCX 14 kb

Changes in the miRNA-mRNA Regulatory Network Precede Motor Symptoms in a Mouse Model of Multiple System Atrophy: Clinical Implications.

Multiple system atrophy (MSA) is a fatal rapidly progressive α-synucleinopathy, characterized by α-synuclein accumulation in oligodendrocytes. It is accepted that the pathological α-synuclein accumulation in the brain of MSA patients plays a leading role in the disease process, but little is known about the events in the early stages of the disease. In this study we aimed to define potential roles of the miRNA-mRNA regulatory network in the early pre-motor stages of the disease, i.e., downstream of α-synuclein accumulation in oligodendroglia, as assessed in a transgenic mouse model of MSA. We investigated the expression patterns of miRNAs and their mRNA targets in substantia nigra (SN) and striatum, two brain regions that undergo neurodegeneration at a later stage in the MSA model, by microarray and RNA-seq analysis, respectively. Analysis was performed at a time point when α-synuclein accumulation was already present in oligodendrocytes at neuropathological examination, but no neuronal loss nor deficits of motor function had yet occurred. Our data provide a first evidence for the leading role of gene dysregulation associated with deficits in immune and inflammatory responses in the very early, non-symptomatic disease stages of MSA. While dysfunctional homeostasis and oxidative stress were prominent in SN in the early stages of MSA, in striatum differential gene expression in the non-symptomatic phase was linked to oligodendroglial dysfunction, disturbed protein handling, lipid metabolism, transmembrane transport and altered cell death control, respectively. A large number of putative miRNA-mRNAs interaction partners were identified in relation to the control of these processes in the MSA model. Our results support the role of early changes in the miRNA-mRNA regulatory network in the pathogenesis of MSA preceding the clinical onset of the disease. The findings thus contribute to understanding the disease process and are likely to pave the way towards identifying disease biomarkers for early diagnosis of MSA

Changes in the miRNA-mRNA Regulatory Network Precede Motor Symptoms in a Mouse Model of Multiple System Atrophy: Clinical Implications - Fig 7

<p><b>Deregulated miRNA-mRNA regulatory network in the striatum of MSA mice in pre-motor stage of disease:</b> Modules “Protein handling” (A) and “Metabolism” (B). Differentially expressed miRNAs with predicted negatively correlated differentially expressed mRNA targets assigned to the indicated GO-terms (light blue rectangles) are visualized by employing Cytoscape (version 3.2.1). Round nodes designate mRNA and triangle nodes miRNA. Node size is proportional to its degree. Fold change (log₂ transformed) for each node is ranging from -0.75 (red) to 1 (green). The shade of blue color of the interaction arrows indicates the degree (range -1.00–0.00) of negative correlation between miRNA-mRNA target 3’ UTR interaction. Interaction arrow thickness is proportional to the number of algorithms predicting the miRNA-mRNA target 3’ UTR interaction, ranging from one to four.</p

Motor analysis of MSA versus age-matched control mice.

<p>Motor analysis of MSA versus age-matched control mice.</p

Neuropathological and behavioral characterization of a mouse model of a pre-motor stage of MSA.

<p>(A) Human α-synuclein overexpression in MSA transgenic mice resulted in α-synuclein accumulation in oligodendrocytes (arrows) detectable both in substantia nigra and striatum. (B) No dopaminergic neuronal loss was identified in the pre-motor stage in substantia nigra of MSA mice (n = 6) as compared to controls (n = 4) by stereological determination of the number of tyrosine hydroxylase (TH)-immunoreactrive (IR) neurons. (C) No GABAergic medium spiny neurons loss was identified in the pre-motor stage in striatum of MSA mice (n = 6) as compared to controls (n = 4) by stereological determination of the number of DARPP-32-IR neurons. (D) Iba-1-IR was used to determine the number and activation status of microglia (type A, B, C, and D [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150705#pone.0150705.ref029" target="_blank">29</a>]) in MSA (n = 3) and control mice (n = 3). No significant differences were detected between the groups with predominant representation of type A resting microglia in both substantia nigra and striatum. (E) GFAP-immunohistochemistry was used to determine the level of astroglial activation in MSA (n = 5) and control mice (n = 3) in substantia nigra and striatum. No significant differences were identified between the groups. Statistical analysis of the neuropathological data to compare control and transgenic MSA mice was done by t-test analysis with GraphPad Prism 5.03 software. Statistical significance was set at p<0.05. Data are presented as mean ± SEM. (F) TUNEL staining detected no cell death in SN and striatum of PM3 MSA mice. As a positive control we applied aged PM12 MSA mice (an age when detectable neuronal loss is recorded) that demonstrated positive TUNEL staining.</p

Deregulated miRNA-mRNA regulatory network to “Immune system process” in MSA mice in disease pre-motor stage.

<p>Differentially expressed miRNAs with predicted negatively correlated differentially expressed mRNA targets are visualized by employing Cytoscape (version 3.2.1). Round nodes show mRNA and triangle nodes miRNA. Node size is proportional to its degree. Fold change (log₂ transformed) for each node is ranging from red (negative) to green (positive). Interaction arrow thickness is proportional to the number of algorithms predicting the miRNA-mRNA target 3’ UTR interaction, ranging from one to four. Differential expression of genes, in striatum and SN, such as <i>Anln</i>, <i>Car2</i>, <i>Cd59a</i>, <i>Hba-a1</i> and <i>Rps17</i>, is visualized by color corresponding to the mean fold change (exact values can be found in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150705#pone.0150705.s007" target="_blank">S2</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150705#pone.0150705.s008" target="_blank">S3</a> Tables).</p

Differential expression of miRNAs in a mouse model of pre-motor stage MSA.

<p>(A) Heatmap shows expression changes of miRNAs of striatum (left) and SN (right). miRNAs with statistically significant (adjusted p<0.1) changes are indicated by a red line on the side. Gray boxes designate miRNAs with expression signals below background. The color gradient shows positive and negative log₂-transformed fold changes in orange and blue color, respectively. (B) Fold change and adjusted p-value of the miRNAs of the mir-467 family. (C) Venn diagram illustrates the overlap of differentially expressed miRNAs between SN and striatum in MSA mice. Differential expression analysis was performed by calculating a linear model for each miRNA according to the guidelines for simple dye swap experiments [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150705#pone.0150705.ref039" target="_blank">39</a>]. Duplicated spots were considered in the linear model fit. This model was then employed to obtain test statistics by the empirical Bayes method providing stable estimations for the sample variance of a small number of arrays [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150705#pone.0150705.ref044" target="_blank">44</a>]. All differentially expressed miRNAs with an adjusted p-value < 0.1 after multiple testing corrections as proposed by Benjamini and Hochberg were considered statistically significant [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150705#pone.0150705.ref038" target="_blank">38</a>].</p