Article

MicroRNAs can regulate human APP levels

Department of Bioscience & Biotechnology, Drexel University, Philadelphia, PA, USA. .
Molecular Neurodegeneration (Impact Factor: 5.29). 02/2008; 3:10. DOI: 10.1186/1750-1326-3-10
Source: PubMed

ABSTRACT A number of studies have shown that increased APP levels, resulting from either a genomic locus duplication or alteration in APP regulatory sequences, can lead to development of early-onset dementias, including Alzheimer's disease (AD). Therefore, understanding how APP levels are regulated could provide valuable insight into the genetic basis of AD and illuminate novel therapeutic avenues for AD. Here we test the hypothesis that APP protein levels can be regulated by miRNAs, evolutionarily conserved small noncoding RNA molecules that play an important role in regulating gene expression. Utilizing human cell lines, we demonstrate that miRNAs hsa-mir-106a and hsa-mir-520c bind to their predicted target sequences in the APP 3'UTR and negatively regulate reporter gene expression. Over-expression of these miRNAs, but not control miRNAs, results in translational repression of APP mRNA and significantly reduces APP protein levels. These results are the first to demonstrate that levels of human APP can be regulated by miRNAs.

0 Followers
 · 
142 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Early-onset, familial Alzheimer's disease (AD) is rare and may be attributed to disease-causinq mutations. By contrast, late onset, sporadic (non-Mendelian) AD is far more prevalent and reflects the interaction of multiple genetic and environmental risk factors, together with the disruption of epigenetic mechanisms controlling gene expression. Accordingly, abnormal patterns of histone acetylation and methylation, as well as anomalies in global and promoter-specific DNA methylation, have been documented in AD patients, together with a deregulation of noncoding RNA. In transgenic mouse models for AD, epigenetic dysfunction is likewise apparent in cerebral tissue, and it has been directly linked to cognitive and behavioral deficits in functional studies. Importantly, epigenetic deregulation interfaces with core pathophysiological processes underlying AD: excess production of Aβ42, aberrant post-translational modification of tau, deficient neurotoxic protein clearance, axonal-synaptic dysfunction, mitochondrial-dependent apoptosis, and cell cycle re-entry. Reciprocally, DNA methylation, histone marks and the levels of diverse species of microRNA are modulated by Aβ42, oxidative stress and neuroinflammation. In conclusion, epigenetic mechanisms are broadly deregulated in AD mainly upstream, but also downstream, of key pathophysiological processes. While some epigenetic shifts oppose the evolution of AD, most appear to drive its progression. Epigenetic changes are of irrefutable importance for AD, but they await further elucidation from the perspectives of pathogenesis, biomarkers and potential treatment.
    Dialogues in clinical neuroscience 09/2014; 16(3):373-93.
  • [Show abstract] [Hide abstract]
    ABSTRACT: RNA interference (RNAi) has changed the traditional model of gene regulation by revealing the existence of small regulatory RNA fragments, known as small RNAs (sRNAs), which influence gene expression at the transcriptional and post transcriptional level. The study of sRNAs is currently carried out as a joint effort in molecular biology, high throughput sequencing, bioinformatics analysis and biochemical studies. The book covers these aspects in its three parts: Basics (chapters 1 - 8), Methods (chapters 9 - 15) and Applications (chapters 16 - 21) in an attempt to present a snapshot of a dynamic and prolific field. The first part commences with an overview of the known classes of sRNAs in “Renaissance of the regulatory RNAs”. The junk DNA is reconsidered and further classified into several types of non-coding regulatory RNAs. The brief description of microRNAs, siRNA, piRNA, snoRNA forming the first chapter is smoothly continued in the second chapter “Diversity, overlap and relationships in the small RNA landscape”. Here further details on the biogenesis and mode of actions of sRNAs are presented next to an analysis of the evolutionary relationship between transposable elements and sRNAs. The third chapter explores yet another class of sRNAs, the small nucleolar RNAs (snoRNAs) and highlights high throughput sequencing and RNA protection experiments as methods to facilitate the understanding of their mode of action. The forth chapter focuses on sRNAs in prokaryotes and systematically presents the few known sRNAs in bacteria. Their biogenesis, mode of actions and evolutionary analysis are extended with their integration in regulatory circuits. sRNAs regulating gene expressions through complementary base pairing and sRNAs that bind small proteins are described in detail. Chapters 5, 7, 8 return to eukaryotes and present particular types of sRNA in animals (chapter 5), in neural differentiation and plasticity (chapter 7) and in cancer (chapter 8). In chapter 6 an in-depth description of long non-coding RNAs is presented together with comments on their natural selection. The second part of the book, “Methods”, focusses on the computational methods developed for the analysis of high throughput data sets. The first two chapters introduce two widely used high throughput methods, microarrays and deep sequencing, the first being described in the context of LNA/DNA microarrays and ribonucleoprotein libraries (RNP) and the latter in the context of protocols and tools for improving the quality of second generation sequencing. The preparation of immunoprecipitation libraries and technical aspects including capturing sRNA populations with different 5’ and 3’ ends, reduction of adapter dimers and cross mapping of miRNA variants are discussed in detail. Chapters 11 and 12 describe the identification of targets in bacteria (chapter 11) and eukaryotes using overexpression and knock-down methods as well as target validation for 3’ UTR sites using luciferase reporters (chapter 12). Chapter 13 presents the identification of lncRNAs using computational (like de novo prediction from genomic sequences) and experimental approaches (such as lncRNA specific microarray and RNA immunoprecipitation). Chapter 14 focuses on RNA based regulation in bacteria describing the anti-sense transcription as a main mode of action and the resulting sRNAs are presented as components of regulatory circuits. The methods part concludes with the in depth description of microregulators from stem cells (chapter 15). This chapter focusses on the better understood class of microRNAs which are, in this context, linked to significant epigenetic regulation. The third part of the book, “Applications”, focusses on sRNAs in biological systems. Chapter 16 presents the unique opportunity to silence cancer causing stem cells at a post transcriptional level using sRNAs. The authors also explore RNAi therapy against multi drug resistance genes in a state of art description of the field. Chapter 17 focusses on another aspect of stem cells and the role of microRNAs, microRNA mimics, microRNA antagonists, antisense RNA and siRNA on cell differentiation and regenerative medicine. This direction is continued in chapter 18 where the authors present the role of microRNAs in neurodegenerative diseases focussing on genomic scale analysis of conditions such as Alzheimer’s disease and other dementias. Next, chapter 19 comes as a summary and state of art of siRNA therapeutic design aimed at improving intracellular interactions with RNAi proteins. The section is concluded with two chapters on microRNAs. Chapter 20 focusses on artificial microRNAs and chapter 21 presents an overview of microRNAs involved in cancer. The book represents a valuable collection of articles that reflect the current knowledge in the RNAi field. It is useful for both biologists and bioinformaticians, researchers and students alike, and strengthens the links between molecular biology and bioinformatics.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Amyloid precursor protein (APP) and β-site amyloid precursor protein cleaving enzyme (BACE-1) play important roles in the generation of Alzheimer's disease (AD), a progressive neurodegenerative disorder. In the present study, microRNA (miR) microarray was used to analyze the miR expression profiles in the hippocampi from APP/PS1 transgenic and wild type mice. The miRs with significant alteration and putative targets on APP or BACE-1 were retrieved (miR-135a, -200b and -429). The deregulations of these miRs were confirmed in mice and further verified in AD patient samples by qPCR. Primary mouse hippocampal neurons, SH-SY5Y and HEK293 cells were used to study the function of miRs on APP and BACE-1. We found that miR-135a, which was downregulated significantly in hippocampi from APP/PS1 transgenic mice compared with the wild type control, directly interacted with the 3'-UTR of BACE-1 and repressed its expression and activity. On the other hand, miR-200b and -429, which were downregulated significantly in hippocampi from APP/PS1 transgenic mice compared with the wild type control, targeted the 3'-UTR of APP and repressed its expression. Furthermore, Aβ42 could downregulate miR-200b expression which may generate a vicious cycle resulted in accumulating Aβ42. The levels of miR-135a and -200b in the serum of DAT group were significantly lower than that of control groups (P<0.05). The serum miR-200b level of MCI group was higher than that of DAT group (P<0.05) and lower than that of control group (P<0.05). We also found decreased miR-135a and -200b levels in the cerebrospinal fluid of DAT group compared with the control group (P<0.05). In conclusion, these findings showed that miR-135a, -200b and -429 may take part in the progress of AD; miR-200b was of great potential as noninvasive and easily detected blood-based biomarkers of MCI and DAT patients.
    Brain Research 08/2014; 1583. DOI:10.1016/j.brainres.2014.04.026 · 2.83 Impact Factor