Indiana University-Purdue University Indianapolis (IUPUI) / Alzheimer’s disease (AD) is a neurodegenerative disease histopathologically characterized by the coexistence of amyloid plaques and neurofibrillary tangles, mainly consisting of amyloid β peptides hyperphosphorylated tau proteins, respectively. Multiple proteins and pathways are involved in the pathogenesis of AD, including Aβ precursor protein (APP), β-site APP-cleaving enzyme (BACE1), neprilysin, endothelin converting enzyme (ECE), repressor element-1 silencing transcription factor (REST), microtubule-associated protein tau, glycogen synthase kinase, and pro-inflammatory cytokines. However, how these proteins and pathways are dysregulated and converge in AD pathogenesis remains unclear. Genetic, epigenetic and environmental factors play important roles in disease progression. MicroRNAs (miRNAs), a group of small noncoding RNAs, are important epigenetic regulators that participate in AD development. We have identified three miRNAs capable of targeting several proteins in different AD-related pathways: miR-181-5p, miR-153-3p and miR-101-3p. We tested miR-181 activity with recombinant reporter gene- MME 3’-UTR constructs. All four miR-181-5p (miR-181a, miR-181b, miR-181c and miR-181d) sequences downregulated the reporter signal. Human differentiated neural cells were transfected with miR-181d-5p mimics. miR-181d-5p treatment significantly reduced MME mRNA levels, protein levels and enzyme activity. In addition, miR-181d-5p increased tau and phosphorylated tau levels proportionally. We further demonstrate that miR-153-3p reduced REST 3’-UTR activities, mRNA and protein levels in multiple human cell lines. Moreover, we show that miR-153-3p, by knocking down REST protein, induces apoptosis in HeLa cells but not differentiated neural cells. In addition, miR-153-3p regulates neuronal differentiation in neuronal stem cells, potentially via REST knockdown. We further found that miR-153 levels were correlated with a reduced likelihood of developing AD. Last, we demonstrated that miR-101-3p reduced ECE1 and GSK3β protein levels in multiple cell lines. miR-101-3p increased REST and pro-inflammatory cytokine secretion in microglia cells. In sum, we tested the hypothesis that miRNAs can serve as the master regulator of AD pathogenesis. / 2024-07-01

Vorhersagen von miRNA-Bindestellen enthalten oft einen hohen Prozentsatz an falsch positiven Ergebnissen (24-70%). Gleichzeitig ist es schwierig die biologischen Interaktionen von miRNAs und ihren Zieltranskripten auf experimentellem Wege und Genom weit zu messen. Daher wurde in der vorliegenden Arbeit die Frage beantwortet, ob ChIP-Sequenzierungsdaten, von denen es immer mehr gibt, verwendet werden können, um Vorhersagen von miRNA-Bindestellen zu filtern. Dabei wurde von einem Netzwerk aus miRNAs und Transkriptionsfaktoren gebraucht gemacht, die Zieltranskripte gemeinsam regulieren. Zunächst wurden verschiedene Methoden getestet, mit denen „Peaks“ aus der ChIP-Sequenzierung Zielgenen zugeordnet werden können. Zielgenlisten des transkriptionalen Repressors RE1-silencing transcription factor (REST/NRSF) wurden mithilfe von ChIP-Sequenzierungsdaten erzeugt. Ein Algorithmus zur Suche nach überrepräsentierten miRNA-Zielgenen in REST-Genlisten basierend auf Vorhersagen von TargetScanHuman wurde entwickelt und angewandt. Die detektierten „enrichment“-miRNAs waren Teil eines vielfältig regulierten REST-miRNA-Netzwerks. Mögliche Funktionen von miRNAs wurden vorgeschlagen und ihre Rolle im gemeinsamen Netzwerk mit REST und im damit gebildeten Netzwerkmotiv (Inkoherente Schleife zur Vorwärtskopplung Typ 2) wurde analysiert. Es stellte sich heraus, dass ein Filtern der Vorhersagen tatsächlich möglich ist, da Gene, die sowohl von REST als auch von einer oder mehreren „enrichment“-miRNAs reguliert werden, einen höheren Anteil an wahren miRNA-Transkript-Interaktionen haben. / Predictions of miRNA binding sites suffer from high false positive rates (24-70%) and measuring biological interactions of miRNAs and target transcripts on a genome wide scale remains challenging. In the thesis at hand the question was answered if the ever growing body of ChIP-sequencing data can be applied to filter miRNA target predictions by making use of the underlying regulatory network of miRNAs and transcription factors. First different methods for association of ChIP-sequencing peaks to target genes were tested. Target gene lists of the transcriptional repressor RE1-silencing transcription factor (REST/NRSF) were generated by means of ChIP-sequencing data. An enrichment analysis tool based on predictions from TargetScanHuman was developed and applied to find ‘enrichment’-miRNAs with over-represented targets in the REST gene lists. The detected miRNAs were shown to be part of a highly regulated REST-miRNA network. Possible functions could be assigned to them and their role in the regulatory network and special network motifs (incoherent feedforward loop of type 2) was analyzed. It turned out that miRNA target predictions of genes shared by enrichment-miRNAs and REST had a higher proportion of true positive associations than the TargetScanHuman background, thus the procedure made a filtering possible.