MicroRNA-mediated rescue of fear extinction memory by miR-144-3p in extinction-impaired mice

Background MicroRNA (miRNA)-mediated control of gene expression suggests that miRNAs are interesting targets and/or biomarkers in the treatment of anxiety- and trauma-related disorders, where often memory-associated gene expression is adversely affected. Methods The role of miRNAs in the rescue of impaired fear extinction was assessed using the 129S1/SvlmJ (S1) mouse model of impaired fear extinction. miRNA microarray analysis, reverse transcription polymerase chain reaction, fluorescent in situ hybridization, lentiviral overexpression, and Luciferase reporter assays were used to gain insight into the mechanisms underlying miRNA-mediated normalization of deficient fear extinction. Results Rescuing impaired fear extinction via dietary zinc restriction was associated with differential expression of miRNAs in the amygdala. One candidate, miR-144-3p, robustly expressed in the basolateral amygdala, showed specific extinction-induced, but not fear-induced, increased expression in both extinction-rescued S1 mice and extinction-intact C57BL/6 (BL6) mice. miR-144-3p upregulation and effects on subsequent behavioral adaption was assessed in S1 and BL6 mice. miR-144-3p overexpression in the basolateral amygdala rescued impaired fear extinction in S1 mice, led to enhanced fear extinction acquisition in BL6 mice, and furthermore protected against fear renewal in BL6 mice. miR-144-3p targets a number of genes implicated in the control of plasticity-associated signaling cascades, including Pten, Spred1, and Notch1. In functional interaction studies, we revealed that the miR-144-3p target, PTEN, colocalized with miR-144-3p in the basolateral amygdala and showed functional downregulation following successful fear extinction in S1 mice. Conclusions These findings identify a fundamental role of miR-144-3p in the rescue of impaired fear extinction and suggest this miRNA as a viable target in developing novel treatments for posttraumatic stress disorder and related disorders

Altered bile acid profile associates with cognitive impairment in Alzheimer's disease—An emerging role for gut microbiome

Introduction Increasing evidence suggests a role for the gut microbiome in central nervous system disorders and a specific role for the gut‐brain axis in neurodegeneration. Bile acids (BAs), products of cholesterol metabolism and clearance, are produced in the liver and are further metabolized by gut bacteria. They have major regulatory and signaling functions and seem dysregulated in Alzheimer's disease (AD). Methods Serum levels of 15 primary and secondary BAs and their conjugated forms were measured in 1464 subjects including 370 cognitively normal older adults, 284 with early mild cognitive impairment, 505 with late mild cognitive impairment, and 305 AD cases enrolled in the AD Neuroimaging Initiative. We assessed associations of BA profiles including selected ratios with diagnosis, cognition, and AD‐related genetic variants, adjusting for confounders and multiple testing. Results In AD compared to cognitively normal older adults, we observed significantly lower serum concentrations of a primary BA (cholic acid [CA]) and increased levels of the bacterially produced, secondary BA, deoxycholic acid, and its glycine and taurine conjugated forms. An increased ratio of deoxycholic acid:CA, which reflects 7α‐dehydroxylation of CA by gut bacteria, strongly associated with cognitive decline, a finding replicated in serum and brain samples in the Rush Religious Orders and Memory and Aging Project. Several genetic variants in immune response–related genes implicated in AD showed associations with BA profiles. Discussion We report for the first time an association between altered BA profile, genetic variants implicated in AD, and cognitive changes in disease using a large multicenter study. These findings warrant further investigation of gut dysbiosis and possible role of gut‐liver‐brain axis in the pathogenesis of AD

Identification of differentially expressed small non-coding RNAs as diagnostic markers in central nervous system disorders

Das Zentrale Nervensytem (ZNS) ist das komplexeste Organ im menschlichen Körper und exprimiert ungefähr 80% aller protein-kodierenden Gene. Die Regulation dieser Gene wird wiederum von einem weitaus komplexeren System an nicht protein-kodierenden RNAs (ncRNAs) übernommen. Die zumeist kurzen regulatorischen ncRNAs wurden mit verschiedenen Prozessen des ZNS in Verbindung gebracht und sind beispielsweise in der Regulation von Genexpression, epigenetischen Zustand, neuronaler Plastizität sowie in Alterungsprozessen im Gehirn involviert. Die meisten Studien haben sich im letzten Jahrzehnt auf eine mittlerweile sehr gut beschrieben Klasse von ncRNAs, den microRNAs (miRNAs) beschränkt. Hierzu gibt es mittlerweile zahlreiche etablierte bioinformatische und experimentelle Methoden. Andererseits gibt es kaum standardisierte Methoden zur Untersuchung weniger gut beschriebener bzw. gänzlich unbekannter ncRNAs, obwohl diese den Großteil der vorhandenen ncRNAs ausmachen. In dieser Dissertation wurden kurze regulatorische ncRNAs mit bioinformatischen Methoden identifiziert, welche im zentralen Nervensystem und des weiteren in neurodegenerativen Erkrankungen eine funktionelle Rolle einnehmen. Mittels differenzieller Expressionsanalyse wurden RNA-Seq Daten von embryonalen Stammzellen der Maus, neuronalen Vorläuferzellen und ausdifferenzierten neuronalen Zellen untersucht. Um möglichst alle ncRNAs zu identifizieren, welche in der neuronalen Entwicklung von Bedeutung sind wurden in weiterer Folge murine Hirn und Spinalganglien sequenziert und bioinformatisch selektiert. Basierend auf diesen Daten wurde ein neuro-spezifischer Microchip entwickelt, der zum Screening unterschiedlicher Expressionsmuster von ncRNAs in neurodegenerativen Erkrankungen verwendet werden kann. Der Vorteil gegenüber anderen Technologien ist dabei, dass kurze aber auch längere strukturierte ncRNAs auf ein und demselben Microchip untersucht werden können. Für die Generierung des Microchips wurde ein eigens dafür entwickeltes computer-unterstütztes Selektionsverfahren verwendet, welches Oligonukleotide anhand von Expressionsprofilen in den Sequenzierdaten auswählt. Zusätzlich wurden bioinformatisch vorhergesagte ncRNAs bei der Mikrochip Erstellung inkludiert, welche sich im Intron, in antisense Richtung zum Exon, oder in der Nähe von krankheitsassozierten protein-kodierenden Genen befinden. In einer während dieser Dissertation durchgeführten Studie wurden Expressionsprofile von drei neurodegenerativen murinen Modellen mittels Mikrochips untersucht. Die ersten zwei Modelle sind mit der Parkinson-Krankheit und Epilepsie assoziiert, dagegen weist das dritte Model patho-physiologische Merkmale der Alzheimer-Krankheit auf. Nach Auswertung der Ergebnisse konnten 119 unterschiedlich exprimierte ncRNAs identifiziert werden. Da zwei ncRNAs, welche im frühen Stadium der Alzheimer Krankheit unterschiedliche Expressionsmuster zeigten, im Liquor cerebrospinalis von Patienten detektiert werden konnten, ist deren Verwendung als Biomarker denkbar.The central nervous system (CNS) represents the most complex biological system in the human body, expressing about 80% of all protein-coding genes which are tightly regulated. Numerous reports have uncovered hidden layers of complexity by showing that non-protein-coding RNAs (ncRNAs) play keyroles in neural development, neural differentiation, neural plasticity and brain aging by regulating gene expression and epigenetic status. The majority of studies focused on microRNAs (miRNAs), for which several experimental, as well as computational analysis methods have been developed. However, much less attention has been paid to all other classes of small ncRNAs; from these, about 450,000 ncRNA transcripts have been predicted to be transcriped from the human genome which do not code for proteins, but may exert regulatory roles in gene expression. This work focused on the identification of small regulatory ncRNAs, involved in neuro-developmental disorders of the CNS. Therefore, novel ncRNAs were identified and preselected by differential expression analysis of RNA-Seq data from embryonic stem cells (ES cells) differentiated into neural cells. Following this study, RNA-Seq data from total mouse brain and murine dorsal root ganglia were bioinformatically analyzed, by employing a previously in-house developed computational pipeline, designated as APART and novel ncRNA candidates were predicted. Based on these data, a custom neuro-ncRNA microarray expression profiling platform was developed. For the design of the microarray, a computational pipeline was developed which selected oligonucleotides based on expression profiles in RNA-Seq data. In addition to the experimentally obtained data, computational ncRNA predictions were performed and added to the microarray which were located in introns, antisense to exons, or close to protein-coding genes associated with common CNS disorders. Expression profiling of two mouse models implicated in Epilepsy or Parkinsons disease, respectively, as well as in a mouse model mimicking patho-physiological aspects of Alzheimers disease, revealed 119 differentially expressed ncRNAs. Two of these could be detected experimentally in cerebral spine fluid (CSF) of human patients. Thereby, both ncRNAs showed differential expression in early stages of Alzheimers disease and thus might have the potential to serve as early diagnostic markers.Simon SchaffererAbweichender Titel laut Übersetzung der Verfasserin/des VerfassersEnth. u.a. 1 Veröff. d. Verf. aus den Jahren 2012 . - Zsfassung in dt. SpracheInnsbruck, Med. Univ., Diss., 2014OeBB(VLID)21644

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

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

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

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