Diese Studie wurde unterstützt durch einen Zuschuss von der CLL Global Research Foundation unterstützt. Die University of Texas MD Anderson Cancer Center wird zum Teil durch die National Institutes of Health durch ein Cancer Center Support-Grant (P30CA16672) unterstützt.

1. Identifizieren Transkriptionsfaktor-Bindungsstellen in dem Promoter von microRNA Gene, Data Mining-Ansatz <ol><li> Verwenden Sie die University of California Santa Cruz (UCSC) Genom-Browser Chromatinimmunpräzipitation (CHIP) Sequenzierungsdaten als Teil der Encyclopedia of DNA Elements (ENCODE) Projekt erzeugt zu extrahieren. <ol><li> Öffnen Sie die Tabelle Browser im UCSC Genom-Browser. </li><li> Verwenden Sie die folgenden Spezifikationen, die Tabelle zu extrahieren: Clade: (Säugetiere), Genom: (Mensch), Montage: (Feb2009 (GRch37 / hg18)), Gruppe: (Verordnung), Schiene (TxnFactorChIP), Tabelle: (weEncoderesTFbsCo7steredv3), Region : (Genome), Ausgabeformat (alle aus ausgewählten Tabelle Gene). </li><li> Speichern Sie die Ausgabe von 1.1.2 als TXT-Datei und in eine Tabelle. </li><li> Sortieren und Filtern für den Transkriptionsfaktor von Interesse (zB STAT2). </li></ol></li><li> Verwenden Sie die Liste von microRNA Vermittler auf Basis von H3K4me3 Epigenetik Signatur verfügbar bei Baeer et al. 9 </sup&gt;. Kopieren Sie diese Liste in eine .txt-Datei. </li><li> Zur Anpassung nach Koordinaten auf dem menschlichen Genom, zeichnen sie die Daten von 1.1 und 1.2 (zB Bindung von STAT3 auf mutmaßliche microRNA - Promotoren) und bestimmen Sie die mittlere Bindungsaffinität mit dem Code in C geschrieben scharf wie in ergänzenden skizzierte Codierung Datei 1. </li></ol> 2. Verwenden Sie shRNA Down-Regulierung der Expression eines Transkriptionsfaktors von Interesse <ol><li> Platte 1.5 x 10 6 Zellen von humanen embryonalen 293 - Nierenzelllinie in 10 cm Platte bei etwa 50% Konfluenz (DMEM mit 10% FBS). </li><li> Transfizieren Zellen von humanen embryonalen 293-Nierenzelllinie mit 5 ug grüne Fluoreszenz-Protein (GFP) Lentivirus shRNA enthält gerichtet an den Transkriptionsfaktor von Interesse und mit 5 ug Verpackungsvektoren Transfektionsreagenz für adhärente Zellen unter Verwendung von dem Protokoll des Herstellers entsprechend. </li><li> Als Kontrolle mit den Zellen aus 293 menschlichen embryonalen Nierenzelllinie zu transfizierenverwürfelten shRNA und die Verpackungsvektoren dem Protokoll des Herstellers entsprechend. </li><li> Halten Sie Transfektionsgemisch auf Zellen für 16 Stunden (bei ​​37 ° C, CO 2 Inkubator), dann wird ein neues Medium 10% DMEM - Medium mit 10% FBS auf 10 ml geändert werden . </li><li> Warten Sie 48 Stunden nach der Transfektion Zentrifugation der Zellkultur (300 × g, 5 min) und sammeln infektiösen Überstand. Filtriere den Überstand durch ein 0,45 &amp; mgr; m-Spritzenfilter (25 mm tensidfrei Celluloseacetat-Membran), um alle schwebenden Zellen zu entfernen. </li><li> Konzentrieren Sie den Überstand und sammeln die Lentiviren ein Ultrazentrifugalmühle Filtervorrichtung mit Schwellenwert von 100 kDa. Spin bei 950 xg für 30 - 60 min, bis das Volumen hat Konzentrats auf weniger als 250 &amp; mgr; l. Lagern Sie das konzentrierte Virus bei -80 ° C. </li><li> Transfizieren der Zellen mit der lentivirus. Entfernen Sie gefrorene Lentiviren von -80 ° C Gefrierschrank und tauen auf Raumtemperatur. Übertragen Sie 100 ul Virusüberstand in ein frisches 1,5 ml Mikrozentrifugenröhrchen. <ol><li> Bring das Volumen in dem Rohr zu 1 ml mit reduziertem Serum-Medium auf. In Hexadimethrinbromid zu 1 ml Virussuspension für die endgültige Konzentration von 10 ng / ml, vorsichtig mischen und lassen Sie die Mischung für 5 Minuten stehen. </li></ol></li><li> Zentrifuge 5 x 10 6 Zellen für jede Transduktion und sanft das Zellpellet in 0,5 ml Medium , das Virus resuspendieren. Lassen Sie die Zellen für 4 im Inkubator bleiben - 24 Stunden, dann wurden 0,5 ml Medium in einer Endkonzentration von 10% FBS mit 20% FBS hinzufügen. </li><li> Warten Sie 48 bis 72 Stunden und färben die Zellen mit Propidiumiodid (PI) und grün fluoreszierendem Protein (GFP) gemäß den Anweisungen des Herstellers. Schützen Sie die Zellen , die aus Licht und mit einem FACS - Sorter die Raten der GFP + / PI zu messen - Zellen. Da PI Flecken nur tote Zelle, ist diese Rate eine Schätzung der Transfektionseffizienz in lebenden Zellen. </li><li> Sortieren Sie die positive Zellpopulation auf GFP - Expression (GFP +) durch FACS - Sorter wie zuvor 10 beschrieben. </li><li> Verwenden Western Immun Blotting wie zuvor beschrieben 10 die Pegel eines Transkriptionsfaktors von Interesse vor und nach der Infektion der Zellen von Interesse (zB CLL - Zellen) mit den benannten shRNA zu bestimmen. </li></ol> 3. Bestimmen Sie die Expression von microRNA Transkriptom in Zellen, die mit Transcription Factor-shRNA <ol><li> Isolieren RNA Kommerzielle Kits nach Herstellerprotokoll. </li><li> Beschriften Sie die RNA und hybridisieren es zu microRNA Microarray - 11. </li><li> Bestimmen Sie die differentiell exprimierte microRNA in Zellen , die mit Transkriptionsfaktor-shRNA oder mit leerem Vektor Kontrollen 5. </li><li> Überprüfen Sie die Microarray - Ergebnisse für die meisten differentiell exprimierten microRNAs unter Verwendung von Echtzeit - PCR - 5. </li></ol> 4. Bestimmen Sie die Überlappung zwischen den Bioinformatik und der shRNA-Ansatz in der Transkriptionsfaktor abhängige Transkriptom beschreiben <ol><li> detHermelin die erwarteten und beobachteten Verhältnisse von microRNA Gene , die Transkriptionsfaktor - Bindungsstellen in ihren Promotoren und wurden downregulated in Transkriptionsfaktor-shRNA transfizierten Zellen beherbergen, gehen Sie wie folgt vor : <ol><li> Beziehen Sie das Verhältnis von Genen, die den Transkriptionsfaktor von Interesse an ihrem Promotor / Gesamt microRNA aus der Liste erzeugt in 1.3 Hafen. Diese Liste ist das erwartete Verhältnis (zB microRNA Gene mit STAT3 - Bindungsstellen / Gesamt microRNA Gene getestet = 0,25). </li><li> Bestimmen Sie die Anzahl von Genen , die in Transkriptionsfaktor-shRNA transfizierten Zellen aus der Liste in 3.3 erzeugt downregulated wurden und hat Transkriptionsfaktor von Interesse Bindungsstellen aus der Liste in 1.3 erzeugt. Diese Nummer / Gesamtzahl der nach unten reguliert Gene ist das beobachtete Verhältnis (zB microRNA Gene mit STAT3 sites / Gesamtzahl der downregulated microRNAs = 0,6 Bindung). </li></ol></li&gt; <li> Verwenden χ2 Statistik zeigt den beobachteten und erwarteten Verhältnisse zu vergleichen, die oben erzeugt wurden, und zu bestimmen, ob die Liste von Genen, die in Transkriptionsfaktor-shRNA transfizierten Zellen herunterreguliert wurden in ihrem Promotor mit Transkriptionsfaktor-Bindungsstellen angereichert sind. </li></ol>

<ol>
	<li>Bentwich, I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+of+hundreds+of+conserved+and+nonconserved+human+microRNAs.">Identification of hundreds of conserved and nonconserved human microRNAs.</a> Nat Genet. 37, 766-770 (2005).</li><li>Hata, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Functions+of+microRNAs+in+cardiovascular+biology+and+disease.">Functions of microRNAs in cardiovascular biology and disease.</a> Annu Rev Physiol. 75, 69-93 (2013).</li><li>Bartel, D. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNAs:+target+recognition+and+regulatory+functions.">MicroRNAs: target recognition and regulatory functions.</a> Cell. 136, 215-233 (2009).</li><li>Piriyapongsa, J., Jordan, I. K., Conley, A. B., Ronan, T., Smalheiser, N. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transcription+factor+binding+sites+are+highly+enriched+within+microRNA+precursor+sequences.">Transcription factor binding sites are highly enriched within microRNA precursor sequences.</a> Biol Direct. 6, 61 (2011).</li><li>Rozovski, U., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Signal+transducer+and+activator+of+transcription+(STAT)-3+regulates+microRNA+gene+expression+in+chronic+lymphocytic+leukemia+cells.">Signal transducer and activator of transcription (STAT)-3 regulates microRNA gene expression in chronic lymphocytic leukemia cells.</a> Mol Cancer. 12, 50 (2013).</li><li>Turner, M. J., Slack, F. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transcriptional+control+of+microRNA+expression+in+C.+elegans:+promoting+better+understanding.">Transcriptional control of microRNA expression in C. elegans: promoting better understanding.</a> RNA Biol. 6, 49-53 (2009).</li><li>Cui, Q., Yu, Z., Pan, Y., Purisima, E. O., Wang, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNAs+preferentially+target+the+genes+with+high+transcriptional+regulation+complexity.">MicroRNAs preferentially target the genes with high transcriptional regulation complexity.</a> Biochem Biophys Res Commun. 352, 733-738 (2007).</li><li>Yamakuchi, M., Lowenstein, C. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MiR-34,+SIRT1+and+p53:+the+feedback+loop.">MiR-34, SIRT1 and p53: the feedback loop.</a> Cell Cycle. 8, 712-715 (2009).</li><li>Baer, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Extensive+promoter+DNA+hypermethylation+and+hypomethylation+is+associated+with+aberrant+microRNA+expression+in+chronic+lymphocytic+leukemia.">Extensive promoter DNA hypermethylation and hypomethylation is associated with aberrant microRNA expression in chronic lymphocytic leukemia.</a> Cancer Res. 72, 3775-3785 (2012).</li><li>Hazan-Halevy, I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=STAT3+is+constitutively+phosphorylated+on+serine+727+residues,+binds+DNA,+and+activates+transcription+in+CLL+cells.">STAT3 is constitutively phosphorylated on serine 727 residues, binds DNA, and activates transcription in CLL cells.</a> Blood. 115, 2852-2863 (2010).</li><li>Melo, S. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+TARBP2+mutation+in+human+cancer+impairs+microRNA+processing+and+DICER1+function.">A TARBP2 mutation in human cancer impairs microRNA processing and DICER1 function.</a> Nat Genet. 41, 365-370 (2009).</li><li>Akira, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Functional+roles+of+STAT+family+proteins:+lessons+from+knockout+mice.">Functional roles of STAT family proteins: lessons from knockout mice.</a> Stem Cells. 17, 138-146 (1999).</li><li>Frank, D. A., Mahajan, S., Ritz, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=B+lymphocytes+from+patients+with+chronic+lymphocytic+leukemia+contain+signal+transducer+and+activator+of+transcription+(STAT)+1+and+STAT3+constitutively+phosphorylated+on+serine+residues.">B lymphocytes from patients with chronic lymphocytic leukemia contain signal transducer and activator of transcription (STAT) 1 and STAT3 constitutively phosphorylated on serine residues.</a> J Clin Invest. 100, 3140-3148 (1997).</li><li>Calin, G. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNA+profiling+reveals+distinct+signatures+in+B+cell+chronic+lymphocytic+leukemias.">MicroRNA profiling reveals distinct signatures in B cell chronic lymphocytic leukemias.</a> Proc Natl Acad Sci U S A. 101, 11755-11760 (2004).</li><li>Consortium, E. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+user's+guide+to+the+encyclopedia+of+DNA+elements+(ENCODE).">A user's guide to the encyclopedia of DNA elements (ENCODE).</a> PLoS biology. 9, e1001046 (2011).</li><li>Miranda, K. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+pattern-based+method+for+the+identification+of+MicroRNA+binding+sites+and+their+corresponding+heteroduplexes.">A pattern-based method for the identification of MicroRNA binding sites and their corresponding heteroduplexes.</a> Cell. 126, 1203-1217 (2006).</li><li>Consortium, E. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+integrated+encyclopedia+of+DNA+elements+in+the+human+genome.">An integrated encyclopedia of DNA elements in the human genome.</a> Nature. 489, 57-74 (2012).</li><li>Lau, J. C., Hanel, M. L., Wevrick, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tissue-specific+and+imprinted+epigenetic+modifications+of+the+human+NDN+gene.">Tissue-specific and imprinted epigenetic modifications of the human NDN gene.</a> Nucl Acids Res. 32, 3376-3382 (2004).</li><li>Corcoran, D. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Features+of+mammalian+microRNA+promoters+emerge+from+polymerase+II+chromatin+immunoprecipitation+data.">Features of mammalian microRNA promoters emerge from polymerase II chromatin immunoprecipitation data.</a> PLoS One. 4, e5279 (2009).</li><li>Bhattacharyya, M., Feuerbach, L., Bhadra, T., Lengauer, T., Bandyopadhyay, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNA+transcription+start+site+prediction+with+multi-objective+feature+selection.">MicroRNA transcription start site prediction with multi-objective feature selection.</a> Stat Appl Genet Mol Biol. 11, (2012).</li></ol>

The authors declare no competing financial interests.

Der Mechanismus der RNA-Polymerase II- abhängige Transkription von Protein-codierenden Genen zugrunde liegenden wurde ausgiebig untersucht. Während diese Elemente nur 1% ausmachen - 2% des menschlichen Genoms, Beweise aus dem ENCODE - Projekt legen nahe , dass mehr als 80% des menschlichen Genoms 17 Transkription unterzogen werden kann und was reguliert die Transkription der nicht-kodierenden DNA - Elemente , bleibt weitgehend unbekannt 6 . Mehrere Studien, die zeigte...

MicroRNAs sind endogene kleine, nicht kodierende regulatorische RNAs, die typischerweise als negative Regulatoren der mRNA-Expression auf der posttranskritionelle Ebene funktionieren. Etwa 1000 nicht-codierende 20 bis 25 Nucleotide langen mikroRNAs im menschlichen Genom zu finden sind 1,2. MicroRNAs regulieren die Genexpression durch kanonische Basenpaarungen zwischen dem Keimsequenz des mikroRNA und sein komplementärer seed Übereinstimmung Sequenz, die üblicherweise am 3&#39;-untranslatierten Region (UTR) der Ziel-mRNAs befindet. Zusammenfassend regulieren mikroRNAs mehr als 30% der Protein - codierenden Gene 3, aber nur wenig über die Transkription von DNA von mikroRNAs bekannt. Es wurde vorgeschlagen, dass die Regulation der Transkription MikroRNA , die der mRNA 4,5 ähnlich ist. Insbesondere ähnlich wie seine Aktivität Transkription von Protein - kodierenden Gene bei der Förderung, sind Transkriptionsfaktoren gedacht 6 Transkription von microRNAs zu aktivieren. Der Transkriptionsfaktor-microRNA Zusammenspiel wurde als Modulator Faktor der Genexpression 7, berichtet und kann auch Feedback- und Feedforward - Schleifen bilden. Zum Beispiel Yamakuchi et al. Berichteten von einer Rückkopplungsschleife , in der p53 die Expression von microRNA34a induziert, die wiederum Translation des p53 - Repressor SIRT hemmt und dadurch Erhöhung p53 Aktivität 8. Während spezifische Beispiele von Transkriptionsfaktor-abhängige Expression von microRNAs berichtet worden, die eine anerkannte Methode, um Informationen darüber, wie ein Transkriptionsfaktor von Interesse reguliert die Expression des microRNA-Transkriptom bietet fehlt. Der Zweck des Protokolls hier vorgeschlagen ist, eine eingehende Beschreibung der Transkriptionsfaktor-abhängige Regulation der microRNA-Transkriptom zu liefern. öffentlich verfügbaren Daten, Bioinformatik-Tools Durch die Kombination und Microarray-Technologie, die Forscher, die diesen Algorithmus folgen zu erfassen wäre in der Lage zu einer genomischen Maßstab, wie jederTranskriptionsfaktor in jedem Zelltyp von Interesse reguliert die Expression des microRNA-Transkriptom und ein mutmaßliches Beitrag des Transkriptionsfaktors-mRNA bei der Regulierung der microRNA Ausdruck zu erkunden.

<table><tbody><tr><td>Lipofectamin 2000</td><td>Life Technologies</td><td>11668027</td><td></td></tr><tr><td>0.45 &amp;micro;m syringe filter</td><td>Thermo Scientific (Nalgene)</td><td>190-2545</td><td></td></tr><tr><td>Amicon ultracentrifugal filter device with threshold of 100&amp;nbsp;kDa</td><td>Merck Millipore</td><td></td><td></td></tr><tr><td>Polybrene</td><td>Merck Millipore</td><td>TR-1003-G</td><td></td></tr><tr><td>TRIzol reagent</td><td>Life Tachnologies (Invitrogen)</td><td>15596-026</td><td></td></tr><tr><td>293 Cell line human</td><td>Sigma-Aldrich</td><td>85120602</td><td></td></tr></tbody></table>

describing a transcription factor dependent regulation of the microrna transcriptome

Während die Transkriptionsregulation der Protein-kodierenden Gene ausgiebig untersucht wurde, ist nur wenig bekannt darüber, wie Transkriptionsfaktoren in der Transkription von nicht-kodierenden RNAs beteiligt sind, insbesondere von Mikro-RNAs. Hier schlagen wir eine Strategie, um die potentielle Rolle des Transkriptionsfaktors zu studieren an der Transkription von microRNAs regulieren öffentlich verfügbaren Daten, Rechenressourcen und hohem Durchsatz Daten. Wir verwenden die epigenetischen Signatur H3K4me3 zu microRNA Promotoren und Chromatinimmunpräzipitation (Chip-) -sequencing Daten aus dem ENCODE-Projekt identifizieren zu microRNA Promotoren zu identifizieren, die mit Transkriptionsfaktor-Bindungsstellen angereichert sind. Durch Transfektion von Zellen von Interesse mit shRNA einen Transkriptionsfaktor von Interesse und Aussetzen der Zellen an microRNA Array Targeting untersuchen wir die Wirkung dieses Transkriptionsfaktors auf der microRNA Transkriptom. Als anschauliches Beispiel verwenden wir unsere Studie über die Wirkung von STAT3 auf der microRNA Transkriptom der chronischen lymphocytic Leukämie (CLL) Zellen.

STAT3 ist ein Transkriptionsfaktor , der typischerweise die Transkription von Genen induziert , die anti apoptotischen und proliferative Wirkungen 12. Ob STAT3 wirken sich auch auf die nicht-kodierende RNA Transkriptom derzeit nicht bekannt ist. In allen CLL - Zellen ist STAT3 konstitutiv phosphoryliert an Serin 707 Reste 10,13. Phosphoserin STAT3 Shuttles zum Kern, bindet an DNA und aktiviert Gene bekannt 10 durch Tyrosin pSTAT3 in anderen Zelltypen akti...

Watch this Scientific Journal Video about Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome at JoVE.com

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome

Herein we propose a strategy to study the effect of a transcription factor of interest on the microRNA transcriptome using publically available data, computational resources and high throughput data from microRNA arrays after transfecting cells with small hairpin (sh)RNA targeting a transcription factor of interest.

Beschreiben ein Transkriptionsfaktor abhängige Regulation der MicroRNA Transkriptom

While the transcription regulation of protein coding genes was extensively studied, little is known on how transcription factors are involved in ...

describing-transcription-factor-dependent-regulation-microrna

Research

JoVE Journal

Bioengineering

8.3K Aufrufe.  Rabin Medical Center. Herein we propose a strategy to study the effect of a transcription factor of interest on the microRNA transcriptome using publically available data, computational resources and high throughput data from microRNA arrays after transfecting cells with small hairpin (sh)RNA targeting a transcription factor of interest. 

Serie: Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs

MicroRNAs (miRNAs) are a class of small noncoding RNAs that post-transcriptionally regulate cellular gene expression. MiRNAs bind to the 3&#39; untranslated region (UTR) of target mRNA to inhibit protein translation or in some instances cause mRNA degradation. The binding of the miRNA to the 3&#39; UTR of the target mRNA is mediated by a 2&#8211;8 nucleotide seed sequence at the 5&#39; end of miRNA. While the role of miRNAs as cellular regulatory molecules is well established, identification of the target mRNAs with functional relevance remains a challenge. Bioinformatic tools have been employed to predict sequences within the 3&#39; UTR of mRNAs as potential targets for miRNA binding. These tools have also been utilized to determine the evolutionary conservation of such sequences among related species in an attempt to predict functional role. However, these computational methods often generate false positive results and are limited to predicting canonical interaction between miRNA and mRNA. Therefore, experimental procedures that measure direct binding of miRNA to its mRNA target are necessary to establish functional interaction. In this report, we describe a sensitive method for validating direct interaction between the cellular miRNA miR-125b and the 3&#39; UTR of PARP-1 mRNA. We elaborate a protocol in which synthetic biotinylated-miRNA mimics were transfected into mammalian cells and the miRNA-mRNA complex in the cellular lysate was pulled down with streptavidin-coated magnetic beads. Finally, the target mRNA in the pulled-down nucleic acid complex was quantified using a qPCR-based strategy.

This report describes a fast and reliable method for validating mRNA targets of cellular miRNAs. The method uses synthetic biotinylated Locked Nucleic Acid (LNA)-based miRNA mimics to capture target mRNA. Subsequently, streptavidin-coated magnetic beads are employed to pulldown the target mRNA for quantification by qPCR polymerase chain reaction.

Biotin-basierte Pulldown Assay, Validate mRNA Ziele der zellulären miRNAs

MicroRNAs (miRNAs) are a class of small noncoding RNAs that post-transcriptionally regulate cellular gene expression. MiRNAs bind to the 3&#39; ...

Forschung

Genetik

A Reporter Assay to Analyze Intronic microRNA Maturation in Mammalian Cells

MicroRNAs (miRNAs) are short RNA molecules that are widespread in eukaryotes. Most miRNAs are transcribed from introns, and their maturation involves different RNA-binding proteins in the nucleus. Mature miRNAs frequently mediate gene silencing, and this has become an important tool for comprehending post-transcriptional events. Besides that, it can be explored as a promising methodology for gene therapies. However, there is currently a lack of direct methods for assessing miRNA expression in mammalian cell cultures. Here, we describe an efficient and simple method that aids in determining miRNA biogenesis and maturation through confirmation of its interaction with target sequences. Also, this system allows the separation of exogenous miRNA maturation from its endogenous activity using a doxycycline-inducible promoter capable of controlling primary miRNA (pri-miRNA) transcription with high efficiency and low cost. This tool also allows modulation with RNA-binding proteins in a separate plasmid. In addition to its use with a variety of different miRNAs and their respective targets, it can be adapted to different cell lines, provided these are amenable to transfection.

We developed an intronic microRNA biogenesis reporter assay to be used in cells in vitro with four plasmids: one with intronic miRNA, one with the target, one to overexpress a regulatory protein, and one for Renilla luciferase. The miRNA was processed and could control luciferase expression by binding to the target sequence.

Ein Reporter-Assay zur Analyse der intronischen microRNA-Reifung in Säugetierzellen

MicroRNAs (miRNAs) are short RNA molecules that are widespread in eukaryotes. Most miRNAs are transcribed from introns, and their maturation involves ...

Krebsforschung

MicroRNA-based Regulation of Picornavirus Tropism

Cell-specific restriction of viral replication without concomitant attenuation can benefit vaccine development, gene therapy, oncolytic virotherapy, and understanding the biological properties of viruses. There are several mechanisms for regulating viral tropism, however they tend to be virus class specific and many result in virus attenuation. Additionally, many viruses, including picornaviruses, exhibit size constraints that do not allow for incorporation of large amounts of foreign genetic material required for some targeting methods. MicroRNAs are short, non-coding RNAs that regulate gene expression in eukaryotic cells by binding complementary target sequences in messenger RNAs, preventing their translation or accelerating their degradation. Different cells exhibit distinct microRNA signatures and many microRNAs serve as biomarkers. These differential expression patterns can be exploited for restricting gene expression in cells that express specific microRNAs while maintaining expression in cells that do not. In regards to regulating viral tropism, sequences complementary to specific microRNAs are incorporated into the viral genome, generally in the 3' non-coding regions, targeting them for destruction in the presence of the cognate microRNAs thus preventing viral gene expression and/or replication. MicroRNA-targeting is a technique that theoretically can be applied to all viral vectors without altering the potency of the virus in the absence of the corresponding microRNAs. Here we describe experimental methods associated with generating a microRNA-targeted picornavirus and evaluating the efficacy and specificity of that targeting in vitro. This protocol is designed for a rapidly replicating virus with a lytic replication cycle, however, modification of the time points analyzed and the specific virus titration readouts used will aid in the adaptation of this protocol to many different viruses.

We describe here a method for regulating picornavirus tropism by incorporating sequences complementary to specific microRNAs into the viral genome. This protocol can be adapted to all different classes of viruses with modifications based upon the length and nature of their life cycle.

MicroRNA-basierten Regulation der Picornavirus Tropism

Cell-specific restriction of viral replication without concomitant attenuation can benefit vaccine development, gene therapy, oncolytic virotherapy, and ...

Immunologie und Infektion

Genome-wide Screen for miRNA Targets Using the MISSION Target ID Library

The Target ID Library is designed to assist in discovery and identification of microRNA (miRNA) targets. The Target ID Library is a plasmid-based, genome-wide cDNA library cloned into the 3'UTR downstream from the dual-selection fusion protein, thymidine kinase-zeocin (TKzeo). The first round of selection is for stable transformants, followed with introduction of a miRNA of interest, and finally, selecting for cDNAs containing the miRNA's target. Selected cDNAs are identified by sequencing (see Figure 1-3 for Target ID Library Workflow and details).
To ensure broad coverage of the human transcriptome, Target ID Library cDNAs were generated via oligo-dT priming using a pool of total RNA prepared from multiple human tissues and cell lines. Resulting cDNA range from 0.5 to 4 kb, with an average size of 1.2 kb, and were cloned into the p3&#900;TKzeo dual-selection plasmid (see Figure 4 for plasmid map). The gene targets represented in the library can be found on the Sigma-Aldrich webpage. Results from Illumina sequencing (Table 3), show that the library includes 16,922 of the 21,518 unique genes in UCSC RefGene (79%), or 14,000 genes with 10 or more reads (66%).

The Target ID Library is a plasmid-based, genome-wide collection of cloned cDNA used to identify miRNA targets. Here we demonstrate its use and application.

Genomweiten Screen für miRNA-Targets mit dem Missionsziel ID-Bibliothek

The Target ID Library is designed to assist in discovery and identification of microRNA (miRNA) targets. The Target ID Library is a plasmid-based, ...

Biologie

Identifying Targets of Human microRNAs with the LightSwitch Luciferase Assay System using 3'UTR-reporter Constructs and a microRNA Mimic in Adherent Cells

MicroRNAs (miRNAs) are important regulators of gene expression and play a role in many biological processes. More than 700 human miRNAs have been identified so far with each having up to hundreds of unique target mRNAs. Computational tools, expression and proteomics assays, and chromatin-immunoprecipitation-based techniques provide important clues for identifying mRNAs that are direct targets of a particular miRNA. In addition, 3'UTR-reporter assays have become an important component of thorough miRNA target studies because they provide functional evidence for and quantitate the effects of specific miRNA-3'UTR interactions in a cell-based system. To enable more researchers to leverage 3'UTR-reporter assays and to support the scale-up of such assays to high-throughput levels, we have created a genome-wide collection of human 3'UTR luciferase reporters in the highly-optimized LightSwitch Luciferase Assay System. The system also includes synthetic miRNA target reporter constructs for use as positive controls, various endogenous 3'UTR reporter constructs, and a series of standardized experimental protocols.
Here we describe a method for co-transfection of individual 3'UTR-reporter constructs along with a miRNA mimic that is efficient, reproducible, and amenable to high-throughput analysis.

MicroRNAs (miRNAs) are important regulators of gene expression and have been shown to play a role in numerous biological processes. To better understand miRNA-UTR interactions, we have created a genome-wide collection of 3 UTR luciferase reporters paired with a novel luciferase gene and assay reagent, the LightSwitch system.

Identifizierung von Zielen für Menschenrechte microRNAs mit dem LightSwitch Luciferase Assay System mit 3&#39;UTR-Reporter-Konstrukte und eine microRNA Mimic in adhärenter Zellen

MicroRNAs (miRNAs) are important regulators of gene expression and play a role in many biological processes.  More than 700 human miRNAs have been ...

Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay

Luminescent Identification of Functional Elements in 3&#8217;UTRs (3&#8217;LIFE) allows the rapid identification of targets of specific miRNAs within an array of hundreds of queried 3&#8217;UTRs. Target identification is based on the dual-luciferase assay, which detects binding at the mRNA level by measuring translational output, giving a functional readout of miRNA targeting. 3&#8217;LIFE uses non-proprietary buffers and reagents, and publically available reporter libraries, making genome-wide screens feasible and cost-effective. 3&#8217;LIFE can be performed either in a standard lab setting or scaled up using liquid handling robots and other high-throughput instrumentation. We illustrate the approach using a dataset of human 3&#8217;UTRs cloned in 96-well plates, and two test miRNAs, let-7c and miR-10b. We demonstrate how to perform DNA preparation, transfection, cell culture and luciferase assays in 96-well format, and provide tools for data analysis. In conclusion 3&#39;LIFE is highly reproducible, rapid, systematic, and identifies high confidence targets.

Luminescent identification of functional elements in 3&#8217; untranslated regions (3&#8217;UTRs) (3&#8217;LIFE) is a technique to identify functional regulation in 3&#8217;UTRs by miRNAs or other regulatory factors. This protocol utilizes high-throughput methodology such as 96-well transfection and luciferase assays to screen hundreds of putative interactions for functional repression.

Nachweis von miRNA Targets in Hochdurchsatz-Verwendung des 3&#39;LIFE Assay

Luminescent Identification of Functional Elements in 3&#8217;UTRs (3&#8217;LIFE) allows the rapid identification of targets of specific miRNAs within an ...

The Ago2-miRNA-co-IP Assay to Study TGF- &#946;1  Mediated Recruitment of miRNA to the RISC in CFBE Cells

Micro(mi)RNAs are short, non-coding RNAs that mediate the RNA interference (RNAi) by post-transcriptional mechanisms. Specific miRNAs are recruited to the cytoplasmic RNA induced silencing complex (RISC). Argonaute2 (Ago2), an essential component of RISC, facilitates binding of miRNA to the target-site on mRNA, followed by cleaving the miRNA-mRNA duplex with its endonuclease activity. RNAi is mediated by a specific pool of miRNAs recruited to RISC, and thus is referred to as the functional pool. The cellular levels of many miRNAs are affected by the cytokine Transforming Growth Factor-&#946;1 (TGF-&#946;1). However, little is known about whether the TGF-&#946;1 affects the functional pools of these miRNAs. The Ago2-miRNA-co-IP assay, discussed in this manuscript, is designed to examine effects of TGF-&#946;1 on the recruitment of miRNAs to RISC and it helps to determine whether changes in the cellular miRNA levels correlate with changes in the RISC-associated, functional pools. The general principles of the assay are as follows. Cultured cells treated with TGF-&#946;1 or vehicle control are lysed and the endogenous Ago2 is immunoprecipitated with immobilized anti-Ago2 antibody, and the active miRNAs complexed with Ago2 are isolated with a RISC immunoprecipitation (RIP) assay kit. The miRNAs are identified with quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR) using miRNA-specific stem-looped primers during reverse transcription, followed by PCR using miRNA-specific forward and reverse primers, and TaqMan hydrolysis probes.

Here, we describe the Ago2-miRNA-co-IP assay designed to quantify an active pool of specific miRNAs induced by TGF-&#946;1 in human bronchial epithelial CFBE41o- cells. This assay provides functional information on the recruitment of miRNA to the RNA induced silencing complex, quantified by qRT-PCR using specific miRNA primers and TaqMan hydrolysis probes.

Micro(mi)RNAs are short, non-coding RNAs that mediate the RNA interference (RNAi) by post-transcriptional mechanisms. Specific miRNAs are recruited to the ...

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis

MicroRNAs (miRNAs) have emerged as important cellular regulators (tumor suppressors, pro-oncogenic factors) of cancer and metastasis. Most published studies focus on a single miRNA when characterizing the role of small RNAs in cancer. However, ~30%&#160;of human miRNA genes are organized in clustered units that are often co-expressed, indicating a complex and coordinated system of noncoding RNA regulation. A clearer understating of how clustered miRNA networks function cooperatively to regulate tumor growth, cancer aggressiveness, and drug resistance is required before translating noncoding small RNAs to the clinic.
The use of a high-throughput clustered regularly interspaced short palindromic repeats (CRISPR)-mediated gene editing procedure has been employed to study the oncogenic role of a genomic cluster of seven miRNA genes located within a locus spanning ~35,000 bp in length in the context of prostate cancer. For this approach, human cancer cell lines were infected with a lentivirus vector for doxycycline (DOX)-inducible Cas9 nuclease grown in DOX-containing medium for 48 h. The cells were subsequently co-transfected with synthetic trans-activating CRISPR RNA (tracrRNA) complexed with genomic site-specific CRISPR RNA (crRNA) oligonucleotides to allow the rapid generation of cancer cell lines carrying the entire miRNA cluster deletion and individual or combination miRNA gene cluster deletions within a single experiment.
The advantages of this high-throughput gene editing system are the ability to avoid time-consuming DNA vector subcloning, the flexibility in transfecting cells with unique guide RNA combinations in a 24-well format, and the lower-cost PCR genotyping using crude cell lysates. Studies using this streamlined approach promise to uncover functional redundancies and synergistic/antagonistic interactions between miRNA cluster members, which will aid in characterizing the complex small noncoding RNA networks involved in human disease and better inform future therapeutic design.

This protocol describes a high-throughput clustered regularly interspaced short palindromic repeats (CRISPR) gene editing workflow for microRNA cluster network analysis that allows the rapid generation of a panel of genetically modified cell lines carrying unique miRNA cluster member deletion combinations as large as 35 kb within a single experiment.

CRISPR-Gen-Editing-Tool für die MicroRNA-Cluster-Netzwerkanalyse

MicroRNAs (miRNAs) have emerged as important cellular regulators (tumor suppressors, pro-oncogenic factors) of cancer and metastasis. Most published ...

Regulation of Expression Occurs at Multiple Steps

Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a protein. This happens through mRNA splicing, which involves the removal of non-coding regions and merging of the coding ones. mRNA processing can also be used as a regulatory mechanism through variation in splicing patterns such as skipping of certain exons, alternative splicing, and inclusion of introns.&#160;
The addition of a poly-A tail at the 3&#8217; end and a 5&#8217; cap to produce the mature mRNA are also regulatory points during RNA processing. Regulation occurs through variation in the polyadenylation signal, which determines where the poly-A tail will be added onto the mRNA.&#160; In some cases, more than one poly-A signal is present at the 3&#8217; end which will change the length of the 3&#8217; untranslated region, but the final protein product will be the same. However, the stability and the translation potential the variants mRNA may differ, which can alter the amount of protein produced. In other cases, an additional poly-A signal is present on the intron or exon within the gene sequence which may lead to variation in splicing sites for polyadenylation and result in different proteins from the same strand of pre-mRNA.The addition of the 5&#8217; cap, which is made up of methylated guanosine, is regulated by two mechanisms.&#160; One involves the regulation of the methyltransferases that add the methyl group to the guanosine, and the other is through regulation of the cellular signaling pathways that lead to methylation.
Next, the mature mRNA needs to be transported from the nucleus to the cytoplasm through nuclear pore complexes (NPCs) to be translated. This is regulated by the mRNA to forming a complex, known as the ribonucleoparticle, with RNA binding proteins. NPCs only allow mRNAs that are in the complex to pass into the cytoplasm. Once an mRNA enters the cytoplasm for translation, it can either be targetted individually or as a part of a group through specific regulations, or it can undergo a common regulation with all other mRNAs in the cytoplasm. In specific regulation, particular trans-acting elements, like proteins and different types of RNAs, regulate transcription. In general regulation, the proteins involved in the translation machinery are activated or inhibited, which in turn affects the translation of all transcripts. The most common translational regulatory mechanism is the modification of the translation initiation factor.
Gene expression can also be regulated through post-translational modifications, where an enzyme-catalyzed reversible modification can alter the function of a protein. A common post-translational modification is phosphorylation, which is carried out by enzymes known as kinases. Dephosphorylation of proteins, on the other hand, is carried out by proteins known as phosphatases. Phosphorylation of a protein can result in its activation or deactivation and alter its function.

Regulation of Expression during Transcription and Translation

Die Regulation der Expression erfolgt in mehreren Schritten

Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the ...

Lehre

JoVE Core

Molekularbiologie

Unit 1

Genexpression

SCHLÜSSELBEGRIFFE UND KONZEPTE

Regulation of Expression at Multiple Steps

The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors&#8212;these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5&#39; capping, splicing, and the addition of a 3&#39; poly-A tail, forming the mature mRNA. Only those mature mRNAs that associate with RNA-binding proteins (RBPs) forming ribonucleoprotein particles are prevented from degradation and are selectively transported out of the nucleus for protein synthesis. mRNAs that do not associate with RBPs are not transported out of the nucleus and hence not translated into proteins. Alternatively, if a mature mRNA binds a complementary microRNA, it undergoes degradation, thereby inhibiting protein synthesis.
However, once the mRNA is translated, the newly synthesized protein undergoes modification that affects its activity. For example, adding functional groups, such as methyl groups, phosphate, or acetyl groups, may activate or inactivate the protein. In contrast, adding multiple ubiquitin proteins to a substrate protein marks them for degradation. Thus, ubiquitination regulates protein stability and its functional activity.

Regulierung der Expression in mehreren Schritten

The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. ...

Beschreiben ein Transkriptionsfaktor abhängige Regulation der MicroRNA Transkriptom

Zusammenfassung

Weitere Videos entdecken

Kapitel in diesem Video