基于通用荧光标签的microRNA芯片检测平台

microRNA（miRNA）是一类生物内源性非编码小RNA分子,在细胞的生长、发育、增殖和细胞凋亡中具有重要的调控作用,并且与癌症的发生息息相关. miRNA表达谱是miRNA研究中的一个关键环节,使用芯片技术分析miRNA表达谱通常要求对miRNA样品进行耗时耗力的荧光标记,并且常规的芯片技术难以精确识别高度同源的miRNAs分子. 为了解决以上问题,本实验室建立了一个被命名为SHUT（Stacking-hybridized Universal Tag）的新型非标记miRNA芯片分析方法. 本文通过分别使用两步杂交法、一步杂交法对SHUT平台的miRNAs特异性检测进行优化. 研究结果表明,SHUT平台在48℃下杂交18 h,除了let-7b和P-let-7c,let-7c和P-let-7a分别存在超过32.5%和83.3%的假阳性信号之外,其它交叉杂交信号都低于10%,具有较好的特异性. 在该杂交条件下,靶标分子let-7d的最低检测浓度为20 fmol/L,并且在20 fmol/L至200 pmol/L之间具有较好的线性关系.     

Optimization and clinical validation of a pathogen detection microarray

DNA microarrays used as 'genomic sensors' have great potential in clinical diagnostics. Biases inherent in random PCR-amplification, cross-hybridization effects, and inadequate microarray analysis, however, limit detection sensitivity and specificity. Here, we have studied the relationships between viral amplification efficiency, hybridization signal, and target-probe annealing specificity using a customized microarray platform. Novel features of this platform include the development of a robust algorithm that accurately predicts PCR bias during DNA amplification and can be used to improve PCR primer design, as well as a powerful statistical concept for inferring pathogen identity from probe recognition signatures. Compared to real-time PCR, the microarray platform identified pathogens with 94% accuracy (76% sensitivity and 100% specificity) in a panel of 36 patient specimens. Our findings show that microarrays can be used for the robust and accurate diagnosis of pathogens, and further substantiate the use of microarray technology in clinical diagnostics.     

Rapid microRNA (miRNA) detection and classification via surface-enhanced Raman spectroscopy (SERS)

microRNAs (miRNA) are recognized as regulators of gene expression during development and cell differentiation as well as biomarkers of disease. Development of rapid and sensitive miRNA profiling methods is essential for evaluating the pattern of miRNA expression that varies across normal and diseased states. The ability to identify miRNA expression patterns is limited to cumbersome assays that often lack sensitivity and specificity to distinguish between different miRNA families and members. We evaluated a surface-enhanced Raman scattering (SERS) platform for detection and classification of miRNAs. The strength of the SERS-based sensor is its sensitivity to detect extremely low levels of analyte and specificity to provide the molecular fingerprint of the analyte. We show that the SERS spectra of related and unrelated miRNAs can be detected in near-real time, that detection is sequence dependent, and that SERS spectra can be used to classify miRNA patterns with high accuracy.     

Locked nucleic acid-based in situ detection of microRNAs in mouse tissue sections

Here we describe a method for sensitive and specific histological detection of microRNAs (miRNAs) by in situ hybridization. The protocol focuses on the use of locked nucleic acids (LNAs), which are bi-cyclic RNA analogs that allow a significant increase in the hybridization temperature and thereby an enhanced stringency for short probes as required for miRNA detection. The protocol is optimized for cryosections in order to study the spatial and temporal expression of miRNAs with high sensitivity and resolution. We detail how to construct probes, set up and conduct an LNA in situ hybridization experiment. In addition, we discuss alternative colorimetric strategies that can be used to effectively detect and visualize miRNAs including double staining with other markers. Setting up and conducting the in situ experiment is estimated to take approximately 1 week, assuming that all the component parts are readily available.     

The use of miRNA microarrays for the analysis of cancer samples with global miRNA decrease

Recent studies have established that mutations or deletions in microRNA (miRNA) processing enzymes resulting in a global decrease of miRNA expression are frequent across cancers and can be associated with a poorer prognosis. While very popular in miRNA profiling studies, it remains unclear whether miRNA microarrays are suited or not to accurately detecting global miRNA decreases seen in cancers. In this work, we analyzed the miRNA profiles of samples with global miRNA decreases using Affymetrix miRNA microarrays following the inducible genetic deletion of Dicer1. Surprisingly, up to a third of deregulated miRNAs identified upon Dicer1 depletion were found to be up-regulated following standard robust multichip average (RMA) background correction and quantile normalization, indicative of normalization bias. Our comparisons of five preprocess steps performed at the probe level demonstrated that the use of cyclic loess relying on non-miRNA small RNAs present on the Affymetrix platform significantly improved specificity and sensitivity of detection of decreased miRNAs. These findings were validated in samples from patients with prostate cancer, where conjugation of robust normal-exponential background correction with cyclic loess normalization and array weights correctly identified the greatest number of decreased miRNAs, and the lowest amount of false-positive up-regulated miRNAs. These findings highlight the importance of miRNA microarray normalization for the detection of miRNAs that are truly differentially expressed and suggest that the use of cyclic loess based on non-miRNA small RNAs can help to improve the sensitivity and specificity of miRNA profiling in cancer samples with global miRNA decrease.     

Identification of a 4-microRNA signature for clear cell renal cell carcinoma metastasis and prognosis

Renal cell carcinoma (RCC) metastasis portends a poor prognosis and cannot be reliably predicted. Early determination of the metastatic potential of RCC may help guide proper treatment. We analyzed microRNA (miRNA) expression in clear cell RCC (ccRCC) for the purpose of developing a miRNA expression signature to determine the risk of metastasis and prognosis. We used the microarray technology to profile miRNA expression of 78 benign kidney and ccRCC samples. Using 28 localized and metastatic ccRCC specimens as the training cohort and the univariate logistic regression and risk score methods, we developed a miRNA signature model in which the expression levels of miR-10b, miR-139-5p, miR-130b and miR-199b-5p were used to determine the status of ccRCC metastasis. We validated the signature in an independent 40-sample testing cohort of different stages of primary ccRCCs using the microarray data. Within the testing cohort patients who had at least 5 years follow-up if no metastasis developed, the signature showed a high sensitivity and specificity. The risk status was proven to be associated with the cancer-specific survival. Using the most stably expressed miRNA among benign and tumorous kidney tissue as the internal reference for normalization, we successfully converted his signature to be a quantitative PCR (qPCR)-based assay, which showed the same high sensitivity and specificity. The 4-miRNA is associated with ccRCC metastasis and prognosis. The signature is ready for and will benefit from further large clinical cohort validation and has the potential for clinical application.     

植物病毒检测芯片的杂交条件优化

利用芯片点样仪将5种侵染马铃薯的病毒/类病毒(苜蓿花叶病毒、黄瓜花叶病毒、黄瓜花叶病毒-卫星病毒、马铃薯病毒Y、马铃薯块茎纺锤状类病毒)的保守区寡核苷酸(Oligonucleotide,oligo)探针和PCR探针点样于玻片,并以植物18S rRNA作为内参照制成基因芯片。研究探针浓度、杂交时间、杂交温度以及点样液对芯片杂交的影响,并验证优化后病毒检测芯片的特异性。结果表明,寡核苷酸探针浓度介于5-20 ?mol/L之间对杂交信号强度影响不大,PCR探针浓度与杂交信号强度间呈线性关系;在45℃杂交4 h时,芯片的杂交信号最强,且该条件下进行杂交对两种探针芯片的影响趋势一致;点样液中以DMSO的杂交效果最好。经过整体条件优化后的两种探针芯片在杂交检测上具有较高的特异性,适于检测植物病毒。     

Expression profiling of microRNA using oligo DNA arrays

After 12 years from its first application, microarray technology has become the reference technique to monitor gene expression of thousands of genes in the same experiment. In the past few years an increasing amount of evidence showed the importance of non-coding RNA (ncRNA) in different human diseases. The microRNAs (miRNAs) are one of the groups of ncRNA. They are small RNA fragments, 19-25 nucleotides long, with a main regulatory function on both protein coding genes and non-coding RNAs. The application of microarray platforms applied to miRNA profiling determined their deregulation in virtually all human diseases that have been studied. We previously developed a custom miRNA microarray platform, and here we describe the protocol we used to work with it including the oligo design strategy, the microarray printing protocol, the target-probe hybridization and the signal detection.     

应用多重标记引物增强寡核苷酸芯片的荧光信号强度

寡核苷酸芯片技术是一种高通量发掘和采集生物信息的强大技术平台,目前已广泛应用于生物科学领域 . 为改善寡核苷酸芯片的分析性能,对影响芯片杂交结果的因素,如片基表面的化学处理、探针的长度、间隔臂的长度、杂交条件等,进行了深入的研究和优化 . 对寡核苷酸芯片而言,仍有待解决的问题是如何产生更强的荧光信号来改善其检测灵敏度 . 利用两种类型的多个荧光分子标记的引物,来增强二维寡核苷酸芯片平面上的荧光信号强度 . 两种引物分别命名为：多标记线性引物和多标记分支引物 . 通过增加标记在目标 DNA 片段上的荧光分子数,可以显著增强寡核苷酸芯片上相应捕获探针的信号强度 . 实验表明,使用多标记引物能将所用的寡核苷酸微阵列的检测限 ( 以能够检测的最低模板量计算 ) 降低至单荧光标记引物的 1/100 以下,多重标记技术是一种有效增强微型化探针矩阵检测灵敏度的信号放大方法 .     

Target labelling for the detection and profiling of microRNAs expressed in CNS tissue using microarrays

Background  

MicroRNAs (miRNA) are a novel class of small, non-coding, gene regulatory RNA molecules that have diverse roles in a variety of eukaryotic biological processes. High-throughput detection and differential expression analysis of these molecules, by microarray technology, may contribute to a greater understanding of the many biological events regulated by these molecules. In this investigation we compared two different methodologies for the preparation of labelled miRNAs from mouse CNS tissue for microarray analysis. Labelled miRNAs were prepared either by a procedure involving linear amplification of miRNAs (labelled-aRNA) or using a direct labelling strategy (labelled-cDNA) and analysed using a custom miRNA microarray platform. Our aim was to develop a rapid, sensitive methodology to profile miRNAs that could be adapted for use on limited amounts of tissue.     

Multiple Sclerosis: MicroRNA Expression Profiles Accurately Differentiate Patients with Relapsing-Remitting Disease from Healthy Controls

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system, which is heterogenous with respect to clinical manifestations and response to therapy. Identification of biomarkers appears desirable for an improved diagnosis of MS as well as for monitoring of disease activity and treatment response. MicroRNAs (miRNAs) are short non-coding RNAs, which have been shown to have the potential to serve as biomarkers for different human diseases, most notably cancer. Here, we analyzed the expression profiles of 866 human miRNAs. In detail, we investigated the miRNA expression in blood cells of 20 patients with relapsing-remitting MS (RRMS) and 19 healthy controls using a human miRNA microarray and the Geniom Real Time Analyzer (GRTA) platform. We identified 165 miRNAs that were significantly up- or downregulated in patients with RRMS as compared to healthy controls. The best single miRNA marker, hsa-miR-145, allowed discriminating MS from controls with a specificity of 89.5%, a sensitivity of 90.0%, and an accuracy of 89.7%. A set of 48 miRNAs that was evaluated by radial basis function kernel support vector machines and 10-fold cross validation yielded a specificity of 95%, a sensitivity of 97.6%, and an accuracy of 96.3%. While 43 of the 165 miRNAs deregulated in patients with MS have previously been related to other human diseases, the remaining 122 miRNAs are so far exclusively associated with MS. The implications of our study are twofold. The miRNA expression profiles in blood cells may serve as a biomarker for MS, and deregulation of miRNA expression may play a role in the pathogenesis of MS.     

A single-molecule method for the quantitation of microRNA gene expression

MicroRNAs (miRNA) are short endogenous noncoding RNA molecules that regulate fundamental cellular processes such as cell differentiation, cell proliferation and apoptosis through modulation of gene expression. Critical to understanding the role of miRNAs in this regulation is a method to rapidly and accurately quantitate miRNA gene expression. Existing methods lack sensitivity, specificity and typically require upfront enrichment, ligation and/or amplification steps. The Direct miRNA assay hybridizes two spectrally distinguishable fluorescent locked nucleic acid (LNA)-DNA oligonucleotide probes to the miRNA of interest, and then tagged molecules are directly counted on a single-molecule detection instrument. In this study, we show the assay is sensitive to femtomolar concentrations of miRNA (500 fM), has a three-log linear dynamic range and is capable of distinguishing among miRNA family members. Using this technology, we quantified expression of 45 human miRNAs within 16 different tissues, yielding a quantitative differential expression profile that correlates and expands upon published results.