doi:10.1182/blood-2010-09-299719
香柏树Prepublished online March 17, 2011;2011 117: 5189-5197
Jing-fei Dong and Paul F. Bray Chen, G. Stanley McKnight, José A. López, Linghai Yang, Ying Jin, Molly S. Bray, Suzanne M. Leal, Srikanth Nagalla, Chad Shaw, Xianguo Kong, Altaf A. Kondkar, Leonard C. Edelstein, Lin Ma, Junmei
reactivity
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PLATELETS AND THROMBOPOIESIS
Platelet microRNA-mRNA coexpression profiles correlate with
platelet reactivity
Srikanth Nagalla,1Chad Shaw,2,3Xianguo Kong,1Altaf A.Kondkar,1Leonard C.Edelstein,1Lin Ma,1Junmei Chen,4
G.Stanley McKnight,5Jo´A.Lo´pez,4Linghai Yang,5Ying Jin,1Molly S.Bray,6Suzanne M.Leal,2,3
鲸的英文
Jing-fei Dong,7and Paul F.Bray1
1Thomas Jefferson University,Cardeza Foundation for Hematologic Rearch,and the Department of Medicine,Jefferson Medical College,Philadelphia,PA; 2Department of Molecular and Human Genetics,Baylor College of Medicine,Houston,TX;3Department of Statistics,Rice University,Houston,TX;4Puget Sound Blood Center,Seattle,WA;5Department of Pharmacology,University of Washington,Seattle,WA;6Departments of Epidemiology and Genetics, University of Alabama at Birmingham,Birmingham,AL;and7Department of Medicine,Baylor College of Medicine,Houston,TX
MicroRNAs(miRNAs)regulate cell physi-ology by altering protein expression,but the biology of platelet miRNAs is largely unexplored.We tested whether platelet miRNA levels were associated with
plate-let reactivity by genome-wide profiling using platelet RNA from19healthy sub-jects.We found that human platelets ex-press284miRNAs.Unsupervid hierar-chical clustering of miRNA profiles resulted in2groups of subjects that appeared to cluster by platelet aggrega-tion phenotypes.Seventy-four miRNAs were differentially expresd(DE)be-
tween subjects grouped according to
platelet aggregation to epinephrine,a sub-
t of which predicted the platelet reactiv-
ity respon.Using whole genome mRNA
expression data on the same subjects,
we computationally generated a high-
priority list of miRNA-mRNA pairs in which
工龄工资怎么算the DE platelet miRNAs had binding sites
in3-untranslated regions of DE mRNAs,
and the levels were negatively correlated.
Three miRNA-mRNA pairs(miR-200b:
PRKAR2B,miR-495:KLHL5,and miR-107:
CLOCK)were lected from this list,and
all3miRNAs knocked down protein ex-
pression from the target mRNA.Reduced
activation from platelets lacking
PRKAR2B supported thefindings.In
summary,(1)platelet miRNAs are able to
repress expression of platelet proteins,
(2)miRNA profiles are associated with
and may predict platelet reactivity,and
(3)bioinformatic approaches can suc-
cessfully identify functional miRNAs in
platelets.(Blood.2011;117(19):5189-5197)
Introduction
On rupture of atherosclerotic plaques,some persons form occlusive platelet thrombi whereas other persons repair the wound without occluding the vesl.The extreme interindividual variation in platelet reactivity probably contributes to the variation in both risk and clinical outcome of ischemic vascular dia becau platelet hyper-reactivity has prospectively been shown to be a risk for recurrent coronary syndromes.1Although heritability strongly influences the interindividual variation in platelet reactivity,2-4 there is a lack of understanding of the responsible genetic and molecular mechanisms.To understand better the basis for human platelet function,it is critical to define the genes that are expresd in the tissue of interest.We have previously ud platelet RNA expression
analys from platelets of differing reactivity to identify differentially expresd(DE)platelet transcripts and proteins.5 During the cour of our studies,we found that a DE platelet microRNA(miRNA)altered the expression of V AMP8,a critical component of platelet granule exocytosis.miRNAs are small (ϳ22nucleotides)noncoding RNAs that function post-transcrip-tionally in regulating gene expression by inducing mRNA degrada-tion or translation inhibition,generally by targeting the 3Ј-untranslated region(UTR)of mRNAs.6miRNAs were initially identified as regulators of genes involved in development but have since been shown to affect a broad range of normal physiologic process,including hematopoietic lineage commitment,as well as pathologic conditions.7,8More than1000miRNAs have been identified,which are estimated to regulate most(Ͼ60%)coding genes.9The cellular impact of most miRNA-mRNA interactions is afine-tuning of protein output,and not a major repression of expression.10Importantly,as little as a20%reduction in miRNA levels can produce a dia phenotype.11
Recent data demonstrate a role for miRNAs in both normal and diad human megakaryocytopoiesis.8,12-17Although we and others have obrved miRNAs in platelets,15,18-23their biology is largely unexplored.We are unaware of a prior unbiad,genome-wide miRNA profiling study that has attempted to establish associations with platelet phenotypes.Becau we had
previously obtained platelet mRNA profile data on a cohort of healthy subjects with marked variability in platelet responsiveness,we had a unique opportunity to test for(1)associations between miRNA profiles and platelet reactivity and(2)relationships between DE miRNAs and target DE mRNAs.The experimental and bioinformatic approaches identified a refined and highly suggestive t of candidate DE miRNA-mRNA pairs.We report the validation of this approach by miR-mediated knockdown of protein in cells,thus providing new insights into platelet physiology and into the molecular mechanisms affecting differential megakaryocyte/ platelet gene regulation.
Submitted September9,2010;accepted February15,2011.Prepublished online as Blood First Edition paper,March17,2011;DOI10.1182/blood-2010-09-299719.
The online version of this article contains a data supplement.The publication costs of this article were defrayed in part by page charge payment.Therefore,and solely to indicate this fact,this article is hereby marked‘‘advertiment’’in accordance with18USC ction1734.
©2011by The American Society of Hematology
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Methods
Subjects
The study was approved by the institutional review boards of Thomas
Jefferson University and Baylor College of Medicine,and informed connt was obtained from all participants in accordance with the Declaration of Helsinki.The original cohort of healthy subjects,the sample collection,and methods of platelet phenotyping have been described previously.24From this cohort,29subjects were recalled for phlebotomy for the platelet RNA expression study.After completion of the mRNA profiling,5sufficient RNA remained for miRNA profiling on 19subjects.LDP and RNA preparations
Blood was drawn into acid citrate dextro (85mM trisodium citrate,78mM citric acid,111mM gluco)
and centrifuged at 180g for 10minutes.Ethylenediaminetetraacetic acid was added to the platelet-rich plasma (PRP)at a final concentration of 2mM.Platelets were pelleted at 1000g for 10minutes and resuspended in 3mL Beads buffer (0.8%NaCl,0.02%KCl,0.144%Na 2HPO 4,0.024%KH 2PO4,0.5%bovine rum albumin,and 2mM ethylenediaminetetraacetic acid).A total of 40L of human CD45MicroBeads reagent (Miltenyi Biotec)was added and incubated at room temperature for 45minutes with gentle mixing.Leukocyte-depleted plate-lets (LDPs)were collected as the negative fraction flow-through using magnetic paration columns (Miltenyi Biotec).This protocol yielded a purity of less than 1leukocyte per 5million platelets.RNA extraction from LDPs and megakaryocytic cell lines (HEL and Meg-01)was performed with TRIzol (Invitrogen).miRNA array profiling
大调和小调的区别The quality of the total RNA was verified by an Agilent 2100Bioanalyzer profile.Approximately 350ng of total RNA from each sample and the reference RNA were labeled with Hy3and Hy5fluorescent labels,respectively,and hybridized to the miRCURY LNAarray,V ersion 11.0(Exiqon),which contains more than 900capture probes targeting all human miRNAs registered in the miRBASE Version 13.0at the Sanger Institute following the procedure described by the manufacturer (Exiqon).After hybridization,the microarray slides were scanned and image analysis carried out using ImaGene Version 8.0software (BioDiscovery).The quantified signals were background corrected and normalize
d using the global LOWESS (LOcally WEighted Scatterplot Smoothing)regression algorithm.All miRNA micro-array data have been deposited in the Gene Expression Omnibus under accession number GSE27917.
Bioinformatic analysis of miRNA levels
Traditional log2-ratio analysis was ud for consideration of 2-color microarray data.25,26The u of log 2-ratios provides a more reliable analysis across a large number of heterogeneous microarray oligonucleotide probes by integrating a pair of hybridization signals within each oligonucleotide feature:one value for the test sample and one for a reference control.The ratio value cancels out intensity variations between the oligos that are driven by hybridization energetic properties of the probe quences,yet the ratio values retain the relative abundance differences between the test and reference samples.25-27Becau all samples are compared with a common reference,the log 2-ratios rve to more reliably reprent the differences in miRNA abundance between the test samples across the large number of features on the array.
短裤用英语怎么说The log 2-ratios were ud to perform a cluster analysis on the samples,and a rank correlation dendrogram with a mean join rule between clusters was computed to reprent the similarity of the
miRNA profiles.We also performed a 2-sample unequal variances t test to identify the DE miRNAs between groups with differing platelet reactivity.To visualize the miRNA log 2-ratio values for the t of potentially DE miRNAs between the platelet respon groups,we ud the heatmap method,which provides a
2-dimensional visual reprentation of the relative expression values for many miRNAs across all persons in our study.Biomarker predictions
We analyzed the log2-ratio miRNA values as explanatory data to predict the quantitative epinephrine respon phenotype of each subject.To avoid overfitting,we first lected a subt of the miRNAs that had the strongest individual correlations with the epinephrine respon phenotype bad on linear regression analysis.We performed our predictive analysis with variable numbers of miRNAs from as few as 2to more than 10.We found that 7miRNAs performed best in our analysis,by optimally balancing model richness with the danger of overfitting and loss of ability to generalize to new obrvations.This analysis determined the best predictor miRNAs among all miRNAs identified in the 2-sample t test differential expression analysis.We then performed multiple linear regression predic-tion using cross-validation with the 7miRNAs ud together to predict respon.To ensure this analysis was robust,we cho a cross-validation approach where each subject was in turn removed f
rom the model estimation step and then their platelet phenotype respon was predicted using the model fit (regression coefficients)determined by the analysis of the other subjects.
mRNA-miRNA correlation analysis
To refine the number of functional studies for candidate DE miRNAs,we developed a strategy bad on the predicted negative correlation between levels of functional miRNAs and the level of an authentic mRNA target.Raw mRNA expression data were extracted on the samples from our prior platelet mRNA profiling study.5We then ud the miRNA-mRNA target predictions made available in the September 2008relea of miRANDA target prediction (www.microrna/microrna/home.do).For each mRNA-miRNA pair where (1)the mRNA was predicted to be expresd,5(2)the miRNA had obrvable expression in all 19samples,and (3)the miRanda target prediction score was greater than 150,we computed a simple linear regression slope statistic and the associated P value.In addition,we computed 2-sample T-statistics to compare mRNA expression values between the high and low platelet reactivity groups.In situations where multiple mRNA probes were prent for a single gene,we considered the probe with the strongest mRNA-miRNA absolute correlation.Asss miRNA knockdown of target gene products
The megakaryocytic cell line Meg-01and HCT116-Dicer-KO 2(HCT-DK)cells were ud for miRNA transfection experiments.The HCT-DK cells (kindly provided by Dr Renato Barga,Department of Cancer Biology,Thomas Jefferson University)express a mutant DICER1that has the exon 5helica domain disrupted but has an intact RNa III domain,resulting in reduced (but not abnt)RNa activity and,hence,reduced amounts of mature miRNAs.28This system allows a more clear asssment of exogenous miRNA effects.Cells were transfected with 40to 80nM final concentration of specific or negative control pre-miR miRNA ds-oligo precursors (Ambion).Meg-01and HCT-DK cells were transfected by electroporation using Nucleofactor II (Amaxa)and DharmaFECT 4(Dhar-macon RNA Technologies),respectively,and were harvested 48to 72hours later for protein analysis.The pre-miR-miRNA precursor molecule-negative control #1(Ambion)ud in the experiments has a random quence that has no known human mRNA target.Proteins were parated by reduced gradient (4%-20%)sodium dodecyl sulfate–polyacrylamide gel electrophoresis,transferred to membranes,and immunoblotted with poly-clonal antibodies specific for CLOCK,KLHL5,and PRKAR2B (Abcam).Protein quantification was performed using LI-COR Odysy Western blot analysis.
Asssment of miRNA binding to 3-UTRs using reporter gene assays
The locations of candidate miRNA binding sites in the 3Ј-UTR of candidate mRNAs were identified using miRanda,and the corresponding regions of the genome were polymera chain reaction amplified from genomic
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DNA and cloned directionally into the3Ј-UTR of the enhanced green fluorescent protein(EGFP)gene in the pEGFP-C1vector(BD Biosci-ences).The reporter gene constructs were verified by quencing to contain the3Ј-UTRs of PRKAR2B(nt1794-2032),KLHL5(nt955-1198), and CLOCK(nt1-643)(nucleotide positions are numbered starting at the first position of the3Ј-UTR of the mRNA).Reporter constructs were cotransfected with the candidate pre-miR miRNA ds-oligo precursors (Ambion)into HCT-DK cells and assd for GFP expression by immunoblotting.GFP ex
pression was normalized to␣-tubulin. Functional asssment of the type IIregulatory subunit of cAMP-dependent PKA
All mou protocols were approved by the Animal Care and U Committee of University of Washington(Seattle,WA).Platelet lysates were prepared from PRP and immunoblotted for PRKAR2B.Citrated whole blood from wild-type C57Bl/6mice and mice null for Prkar2b29was diluted25-fold with Tyrode-N-2-hydroxyethylpiperazine-NЈ-2-ethanesulfonic acid buffer (140mM NaCl,2.7mM KCl,12mM NaHCO3,0.46mM NaH2PO3,5.5mM gluco,10mM N-2-hydroxyethylpiperazine-NЈ-2-ethanesulfonic acid, pH7.4),incubated with epinephrine(Bio/Data),or PAR4activation peptide (PAR4AP;NH2-GYPGQV-CONH2;Abgent),or both,at room temperature for30minutes in the prence of10g/mLfluorescein isothiocyanate-
conjugated rat anti–mou CD62P antibody(P-lectin antibody; BD Biosciences).The samples were thenfixed with1%paraformaldehyde and analyzed byflow cytometry.Platelet meanfluorescence intensity was quantified byflow cytometry and analyzed by multifactor analysis of variance using explanatory variables for agonist dosage,genotype,and animal effects.
Results
miRNA expression profiling
Platelets were categorized as hyper-reactive(nϭ13)or hyporeac-tive(nϭ6)bad on the maximal aggregation respon to1.5M epinephrine(mean83.1%vs21%,respectively,PϽ.001)and 4M ADP(mean85.3%vs55.7%,respectively,PϽ.001).There was no significant difference between the hyper-reactive and hyporeactive subjects forfibrinogen or von Willebrand factor levels(not shown).Becau PRP prepared by standard density centrifugation is contaminated with leukocytes(1leukocyte per 10000-100000platelets),and becau leukocytes contain10000to 100000times as much RNA as do platelets,30,31LDP RNA was ud for miRNA expression profiling.We found that284miRNAs (ofϾ900screened)were expresd in all19LDP RNA samples. The15highest expresd miRNAs are listed in Table1.Supple-mental Table1(available on the Blood Web site;e the Supple-mental Materials link at the top of the online article)provides all 284platelet miRNAs by expression level.
返璞归真的意思是什么We computed a rank correlation dendrogram using the284miRNAs to reprent the similarity of the samples independent of platelet functional respon(Figure1A).A group structure emerged in the unsupervid dendrogram analysis,indicating2groups of samples according to patterns of miRNA expression.We then considered the individual platelet reactivity and found that the phenotypes par
tially coincided with the2groups defined by miRNA levels.
A cond analysis was performed in which74miRNAs were identified as differentially expresd between the hyper-reactive and hyporeactive groups(PϽ.05).The heatmap in Figure1
B reprents the41miRNAs(listed in supplemental Table2)that best parated the hyperreactive from hyporeactive platelet samples. Table1lists the15miRNAs showing the greatest differential expression.Prediction analysis
The results prompted us to consider whether a smaller t of platelet mRNAs could be identified that might have predictive value for platelet reactivity.As few as7of the differentially expresd miRNAs(miR-19b,miR-34b,miR-190,miR-320a,miR-320b,miR-320c,and miR-320d)identified a strong correlation (Spearman rank correlationϭ0.71,Pϭ.0006801)between the true epinephrine respon and the predicted respon from the cross-validated regression analysis(Figure2).This prediction analysis suggests that miRNA expression log2-ratios may be a quantitative predictor of the platelet aggregation respon. Platelet-megakaryocytic cell line miRNA correlations
Biologic studies in megakaryocytic cell lines are often ud as surrogates for human megakaryocytes,which are difficult to obtain in large numbers.We profiled miRNAs from HEL and Me
g-01 cells and found a correlation between normal human platelets and both HEL cells(rϭ0.595,PϽ2.2ϫ10Ϫ16)and Meg-01cells (rϭ0.58,PϽ2.2ϫ10Ϫ16;Figure3).
miRNA-mRNA correlations
The role of a DE mRNA can usually be studied by testing the known or predicted function of the corresponding protein.The situation is very different for a candidate DE miRNA becau miRNAs target many mRNAs.Using in silico techniques,we determined that the median number of distinct predicted gene targets per human miRNA is307(rangeϭ12for hsa-miR-126 [minimum]to1417for hsa-miR-590–3p[maximum]).Thus,the t of all theoretically possible miRNA-mRNA pairs to consider is quite large.When we considered only the platelet-expresd miRNAs and mRNAs,the number of unique pairs with a good alignment score was reduced to29821(supplemental Figure1,filtering strategy),an impractical number to test functionally. Furthermore,such in silico predictions often lead to fal-positive findings that cannot be validated in living cell experiments. Therefore,we sought to divine linkages between miRNAs and mRNA to prioritize which miRNAs would be tested functionally.
We developed a bioinformatics approach to identify DE platelet miRNAs that have binding sites in3Ј-UTRs of DE platelet mRNAs.Our strategy was bad on the assumption that any Table1.Highest expresd15miRNAs ud in the dendogram and
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platelet miRNA that caus mRNA degradation by directly binding to the 3Ј-UTR of the mRNA will result in a negative correlation for the miRNA-mRNA pair in the 19subjects in our study.We cho miRNA-mRNA pairs that met 3criteria:(1)DE miRNA between hyper-reactive and hyporeactive platelets (P Ͻ.05),(2)DE mRNA between hyperreactive and hyporeactive platelets (P Ͻ.05),and (3)a negative correlation in the slopes of the DE miRNA and mRNA.This stringent filtering reduced the number of candidate miRNA-mRNA pairs to 12among 6platelet expresd genes (PRKAR2B,KLHL5,CLOCK,WIPF1,CEP27,and ALPP ;Table 2)
Platelet expresd miRNAs knockdown platelet expresd targets
To validate this genomic and bioinformatics approach as a means of identifying functional platelet miRNAs,3pairs were lected from Table 2for testing in cells.This lection was bad on (1)biologic plausibility of a role for the mRNA in platelets (PRKAR2B,KLHL5,and CLOCK )and (2)an mRNA-miRNA correlation slope of less than Ϫ1.Figure 4shows the anticorrelation of expression patterns for the 3lected pairs (miR-200b:PRKAR2B,miR-495:KLHL5,and miR-107:CLOCK ).(Although W1P1has known function in platelets,it was not chon becau the negative slope of the miRNA-mRNA correlation was less than for PRKAR2B,KLHL5,and CLOCK.)
First,miRNAs were transfected into cells that express the target protein.We obrved that miR-200b induced a 21%knockdown of PRKAR2B (P ϭ.04,Figure 5A);miR-495induced an 18%knockdown of KLHL5(P ϭ.07,Figure 5B);and miR-107induced a 37%knockdown of CLOCK (P ϭ.002,Figure 5C).Subquently,to test whether the miRNA of interest directly targeted the 3Ј-UTR of the candidate mRNA,cotransfection experiments were performed using reporter gene constructs engi-neered to contain the candidate mRNA 3Ј-UTR.As shown in Figure 5D-F,miR-200b ,miR-495,and miR-107directly targeted and represd expression through the 3Ј-UTR of PRKAR2B (50%reduction;P ϭ.004),KLHL5(23%reduction;P ϭ.04),and CLOCK (50%reduction;P ϭ.04),respectively.
The regulatory subunit of PKA is required for normal platelet activation
We next tested whether our approach had identified genes that control platelet reactivity.Most studies on the functionality of cyclic adenosine monophosphate (cAMP)–dependent protein kina A (PKA)in platelets have assd the phosphorylating activity of the catalytic subunit.32Although the regulatory subunit (encoded by PRKAR2B )is thought to control PKA activity,33there are no inhibitors of the regulatory subunit,and we are unaware of
work that directly tests its function in platelets.Using mice rendered null for Prkar2b 29,we confirmed the abnce of protein in platelets (Figure 6A).Compared with wild-type platelets,we found that platelets lacking PRKAR2B expresd similar levels of P-lectin under resting conditions (not shown).Epinephrine alone has little or no ability to induce mou aggregation but markedly enhances PAR4-mediated platelet aggregation.34Using a subthreshold concentration of PAR4AP,we obrved that increas-ing concentrations of epinephrine substantially incread platelet activation (Figure 6B).Notably,and compared with wild-type platelets,Prkar2b Ϫ/Ϫplatelets had reduced activation (P ϭ.0008).The functional experiments provide strong support to our strat-egy for identifying functional miRNAs in platelets.
Discussion
The importance of noncoding RNAs has become increasingly appreciated over the past decade.6miRNA has been the most studied of the small RNAs,but relatively little is known about the role of miRNAs in megakaryocyte/platelet biology.In this study,we focud on the potential role of platelet miRNAs as both
a
Figure 2.Platelet reactivity predicted by differentially expresd miRNAs.Cross-validation analysis using 7miRNAs (miR-19b,miR-34b,miR-190,miR-320a,miR-320b,miR-320c ,and miR-320d )was able to predict the true epinephrine respon in hyper-reactive (red)and hyporeactive (blue)platelets (r ϭ0.71,P ϭ.0006801).See “Biomarker predictions”for criteria ud to lect the
miRNAs.
Figure 1.Platelet microRNA profiling in 19healthy
subjects.(A)Unsupervid hierarchical clustering of miRNA expression profiles.The dendrogram was gener-ated with 284miRBa miRNAs that were expresd in the platelets of all 19subjects included in the study.The dendrogram reprents a Euclidean distance dendro-gram of the median-centered log ratio values for the 19samples.Two major clusters are identified,which tend to differentiate between platelets of differing reactiv-ity to epinephrine.(B)Heatmap with miRNAs that were differentially expresd between the 2platelet reactivity groups using a 2-sample unequal variances t test.Each row in the heatmap indicates the log-ratio intensity data of 1DE miRNA across the 19subjects.
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