Assessment of RT-qPCR normalization strategies for accurate quantification of extracellular microRNAs in murine serum.
ABSTRACT: Extracellular microRNAs (miRNAs) are under investigation as minimally-invasive biomarkers for a wide range of disease conditions. We have recently shown in a mouse model of the progressive muscle-wasting condition Duchenne muscular dystrophy (DMD) that a set of highly elevated serum miRNAs reflects the regenerative status of muscle. These miRNAs are promising biomarkers for monitoring DMD disease progression and the response to experimental therapies. The gold standard miRNA detection methodology is Reverse Transcriptase-quantitative Polymerase Chain Reaction (RT-qPCR), which typically exhibits high sensitivity and wide dynamic range. Accurate determination of miRNA levels is affected by RT-qPCR normalization method and therefore selection of the optimal strategy is of critical importance. Serum miRNA abundance was measured by RT-qPCR array in 14 week old mice, and by individual RT-qPCR assays in a time course experiment spanning 48 weeks. Here we utilize these two datasets to assess the validity of three miRNA normalization strategies (a) normalization to the average of all Cq values from array experiments, (b) normalization to a stably expressed endogenous reference miRNA, and (c) normalization to an external spike-in synthetic oligonucleotide. Normalization approaches based on endogenous control miRNAs result in an under-estimation of miRNA levels by a factor of ?2. An increase in total RNA and total miRNA was observed in dystrophic serum which may account for this systematic bias. We conclude that the optimal strategy for this model system is to normalize to a synthetic spike-in control oligonucleotide.
Project description:Biomarkers are critically important for disease diagnosis and monitoring. In particular, close monitoring of disease evolution is eminently required for the evaluation of therapeutic treatments. Classical monitoring methods in muscular dystrophies are largely based on histological and molecular analyses of muscle biopsies. Such biopsies are invasive and therefore difficult to obtain. The serum protein creatine kinase is a useful biomarker, which is however not specific for a given pathology and correlates poorly with the severity or course of the muscular pathology. The aim of the present study was the systematic evaluation of serum microRNAs (miRNAs) as biomarkers in striated muscle pathologies. Mouse models for five striated muscle pathologies were investigated: Duchenne muscular dystrophy (DMD), limb-girdle muscular dystrophy type 2D (LGMD2D), limb-girdle muscular dystrophy type 2C (LGMD2C), Emery-Dreifuss muscular dystrophy (EDMD) and hypertrophic cardiomyopathy (HCM). Two-step RT-qPCR methodology was elaborated, using two different RT-qPCR miRNA quantification technologies. We identified miRNA modulation in the serum of all the five mouse models. The most highly dysregulated serum miRNAs were found to be commonly upregulated in DMD, LGMD2D and LGMD2C mouse models, which all exhibit massive destruction of striated muscle tissues. Some of these miRNAs were down rather than upregulated in the EDMD mice, a model without massive myofiber destruction. The dysregulated miRNAs identified in the HCM model were different, with the exception of one dysregulated miRNA common to all pathologies. Importantly, a specific and distinctive circulating miRNA profile was identified for each studied pathological mouse model. The differential expression of a few dysregulated miRNAs in the DMD mice was further evaluated in DMD patients, providing new candidates of circulating miRNA biomarkers for DMD.
Project description:Circulating microRNAs (ci-miRNAs) in blood have emerged as promising diagnostic, prognostic and predictive biomarkers in cancer. Many clinical studies currently incorporate studies that assess ci-miRNAs. Validation of the clinical significance of candidate biomarker miRNAs has proven to be difficult, potentially resulting from vast discrepancies in the detection methodology as well as biological variability. In the current study, the influence of several methodological factors on ci-miRNA detection was evaluated as well as short-term biological variability in patients with head and neck cancer. RNA was isolated from 124 serum and plasma samples originating from patients with head and neck cancer and healthy volunteers. The miRNA levels were measured using RT-qPCR and the influence of pre-analytical factors, different normalization strategies and temporal reproducibility was assessed. RNA carriers improved ci-miRNA detection in serum and plasma specimens. A prolonged pre-processing time correlated with an increased hemolytic index in serum samples only. Hemolysis differentially affected the detection of individual miRNAs. Optimal normalization was achieved using the averaged detection values of spike-in cel-miR-39-3p and endogenous miR-16-5p. Comparing biological replicates from patients with head and neck cancer, the intra-individual miRNA levels were relatively stable (average interval 7 days). Differences in the ci-miRNA detection methodology and limitations of currently used technologies can greatly affect the results and may explain inconsistent outcomes between studies. Prior to the implementation of ci-miRNAs as useful clinical biomarkers, further advances in the standardization of the detection methodology and reduction of technical variability are needed.
Project description:BACKGROUND/OBJECTIVE: Reverse transcription quantitative real-time PCR (RT-qPCR) is widely used in microRNA (miRNA) expression studies on cancer. To compensate for the analytical variability produced by the multiple steps of the method, relative quantification of the measured miRNAs is required, which is based on normalization to endogenous reference genes. No study has been performed so far on reference miRNAs for normalization of miRNA expression in urothelial carcinoma. The aim of this study was to identify suitable reference miRNAs for miRNA expression studies by RT-qPCR in urothelial carcinoma. METHODS: Candidate reference miRNAs were selected from 24 urothelial carcinoma and normal bladder tissue samples by miRNA microarrays. The usefulness of these candidate reference miRNAs together with the commonly for normalization purposes used small nuclear RNAs RNU6B, RNU48, and Z30 were thereafter validated by RT-qPCR in 58 tissue samples and analyzed by the algorithms geNorm, NormFinder, and BestKeeper. PRINCIPAL FINDINGS: Based on the miRNA microarray data, a total of 16 miRNAs were identified as putative reference genes. After validation by RT-qPCR, miR-101, miR-125a-5p, miR-148b, miR-151-5p, miR-181a, miR-181b, miR-29c, miR-324-3p, miR-424, miR-874, RNU6B, RNU48, and Z30 were used for geNorm, NormFinder, and BestKeeper analyses that gave different combinations of recommended reference genes for normalization. CONCLUSIONS: The present study provided the first systematic analysis for identifying suitable reference miRNAs for miRNA expression studies of urothelial carcinoma by RT-qPCR. Different combinations of reference genes resulted in reliable expression data for both strongly and less strongly altered miRNAs. Notably, RNU6B, which is the most frequently used reference gene for miRNA studies, gave inaccurate normalization. The combination of four (miR-101, miR-125a-5p, miR-148b, and miR-151-5p) or three (miR-148b, miR-181b, and miR-874,) reference miRNAs is recommended for normalization.
Project description:MicroRNAs (miRNAs) have critical functions in various biological processes. MiRNA profiling is an important tool for the identification of differentially expressed miRNAs in normal cellular and disease processes. A technical challenge remains for high-throughput miRNA expression analysis as the number of miRNAs continues to increase with in silico prediction and experimental verification. Our study critically evaluated the performance of a novel miRNA expression profiling approach, quantitative RT-PCR array (qPCR-array), compared to miRNA detection with oligonucleotide microchip (microarray).High reproducibility with qPCR-array was demonstrated by comparing replicate results from the same RNA sample. Pre-amplification of the miRNA cDNA improved sensitivity of the qPCR-array and increased the number of detectable miRNAs. Furthermore, the relative expression levels of miRNAs were maintained after pre-amplification. When the performance of qPCR-array and microarrays were compared using different aliquots of the same RNA, a low correlation between the two methods (r=-0.443) indicated considerable variability between the two assay platforms. Higher variation between replicates was observed in miRNAs with low expression in both assays. Finally, a higher false positive rate of differential miRNA expression was observed using the microarray compared to the qPCR-array.Our studies demonstrated high reproducibility of TaqMan qPCR-array. Comparison between different reverse transcription reactions and qPCR-arrays performed on different days indicated that reverse transcription reactions did not introduce significant variation in the results. The use of cDNA pre-amplification increased the sensitivity of miRNA detection. Although there was variability associated with pre-amplification in low abundance miRNAs, the latter did not involve any systemic bias in the estimation of miRNA expression. Comparison between microarray and qPCR-array indicated superior sensitivity and specificity of qPCR-array.
Project description:Plant microRNAs are small non-coding, endogenic RNA molecule (containing 20-24 nucleotides) produced from miRNA precursors (pri-miRNA and pre-miRNA). Evidence suggests that up and down regulation of the miRNA targets the mRNA genes involved in resistance against biotic and abiotic stresses. Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is a powerful technique to analyze variations in mRNA levels. Normalizing the data using reference genes is essential for the analysis of reliable RT-qPCR data. In this study, two groups of candidate reference mRNAs and miRNAs in soybean leaves and roots treated with various abiotic stresses (PEG-simulated drought, salinity, alkalinity, salinity+alkalinity, and abscisic acid) were analyzed by RT-qPCR. We analyzed the most appropriate reference mRNA/miRNAs using the geNorm, NormFinder, and BestKeeper algorithms. According to the results, Act and EF1b were the most suitable reference mRNAs in leaf and root samples, for mRNA and miRNA precursor data normalization. The most suitable reference miRNAs found in leaf and root samples were 166a and 167a for mature miRNA data normalization. Hence the best combinations of reference mRNAs for mRNA and miRNA precursor data normalization were EF1a + Act or EF1b + Act in leaf samples, and EF1a + EF1b or 60s + EF1b in root samples. For mature miRNA data normalization, the most suitable combinations of reference miRNAs were 166a + 167d in leaf samples, and 171a + 156a or 167a + 171a in root samples. We identified potential reference mRNA/miRNAs for accurate RT-qPCR data normalization for mature miRNA, miRNA precursors, and their targeted mRNAs. Our results promote miRNA-based studies on soybean plants exposed to abiotic stress conditions.
Project description:<h4>Background</h4>Normalization is critical for accurate gene expression analysis. A significant challenge in the quantitation of gene expression from biofluids samples is the inability to quantify RNA concentration prior to analysis, underscoring the need for robust normalization tools for this sample type. In this investigation, we evaluated various methods of normalization to determine the optimal approach for quantifying microRNA (miRNA) expression from biofluids and tissue samples when using the TaqMan® Megaplex™ high-throughput RT-qPCR platform with low RNA inputs.<h4>Findings</h4>We compared seven normalization methods in the analysis of variation of miRNA expression from biofluid and tissue samples. We developed a novel variant of the common mean-centering normalization strategy, herein referred to as mean-centering restricted (MCR) normalization, which is adapted to the TaqMan Megaplex RT-qPCR platform, but is likely applicable to other high-throughput RT-qPCR-based platforms. Our results indicate that MCR normalization performs comparable to or better than both standard mean-centering and other normalization methods. We also propose an extension of this method to be used when migrating biomarker signatures from Megaplex to singleplex RT-qPCR platforms, based on the identification of a small number of normalizer miRNAs that closely track the mean of expressed miRNAs.<h4>Conclusions</h4>We developed the MCR method for normalizing miRNA expression from biofluids samples when using the TaqMan Megaplex RT-qPCR platform. Our results suggest that normalization based on the mean of all fully observed (fully detected) miRNAs minimizes technical variance in normalized expression values, and that a small number of normalizer miRNAs can be selected when migrating from Megaplex to singleplex assays. In our study, we find that normalization methods that focus on a restricted set of miRNAs tend to perform better than methods that focus on all miRNAs, including those with non-determined (missing) values. This methodology will likely be most relevant for studies in which a significant number of miRNAs are not detected.
Project description:Caerulein-induced acute pancreatitis accelerates the progression of pancreatic intraepithelial neoplasia (PanIN) lesions in a pancreas-specific KrasG12D mouse model. The purpose of this study was to explore whether serum microRNAs (miRNAs) can serve as sensitive biomarkers to detect occult PanIN in the setting of acute pancreatitis. Serum miRNA profiles were quantified by an array-based method and normalized by both Variance Stabilization Normalization (VSN) and invariant methods. Individual miRNAs were validated by TaqMan real-time PCR with synthetic spike-in C. elegans miRNAs as external controls. Serum miRNA profiles distinguished KrasG12D mice with pancreatitis from wild-type mice without pancreatitis, but failed to differentiate KrasG12D mice with pancreatitis from wild-type mice with pancreatitis. Most individual miRNAs that increased in KrasG12D mice with pancreatitis were not significantly different between KrasG12D mice without pancreatitis and wild-type mice without pancreatitis. Mechanistically, Gene Set Enrichment Analysis (GSEA) of the mRNA array data and immunohistochemical assays showed that caerulein-induced acute pancreatitis involved acinar cell loss and immune cell infiltration, which might contribute to serum miRNA profile changes. This study highlighted the challenges in using sensitive serum miRNA biomarker screening for the early detection of pancreatic malignancies during acute pancreatitis.
Project description:Altered levels of circulating extracellular miRNA in plasma and serum have shown promise as non-invasive biomarkers of disease. However, unlike the assessment of cellular miRNA levels for which there are accepted housekeeping genes, analogous reference controls for normalization of circulating miRNA are lacking. Here, we provide an approach to identify and validate circulating miRNA reference controls on a de novo basis, and demonstrate the advantages of these customized internal controls in different disease settings. Importantly, these internal controls overcome key limitations of external spike-in controls.Using a global RT-qPCR screen of 1066 miRNAs in plasma from pulmonary hypertension patients (PAH) and healthy subjects as a case example, we identified a large pool of initial candidate miRNAs that were systematically ranked according to their plasma level stability using a predefined algorithm. The performance of the top candidates was validated against multiple comparators, and in a second independent cohort of PAH and control subjects. The broader utility of this approach was demonstrated in a completely different disease setting with 372 miRNAs screened in plasma from septic shock patients and healthy controls.Normalization of data with specific internal reference controls significantly reduced the overall variation in circulating miRNA levels between subjects (relative to raw data), provided a more balanced distribution of up- and down-regulated miRNAs, replicated the results obtained by the benchmark geometric averaging of all detected miRNAs, and outperformed the commonly used external spike-in strategy.We demonstrate the feasibility of identifying circulating reference controls that can reduce extraneous technical variations, and improve the assessment of disease-related changes in plasma miRNA levels. This study provides a novel conceptual framework that addresses a critical and previously unmet need if circulating miRNAs are to advance as reliable diagnostic tools in medicine.
Project description:MicroRNAs regulate gene expression at the post-transcriptional level. Differential expression of miRNAs can potentially be used as biomarkers for early diagnosis and prediction for outcomes. Failure in validation of miRNA profiles is often caused by variations in experimental parameters. In this study, the performance of five extraction kits and three RT-qPCR systems were evaluated using BioMark high-throughput platform and the effects of different experimental parameters on circulating miRNA levels were determined. Differences in the performance of extraction kits as well as varying accuracy, sensitivity and reproducibility in qPCR systems were observed. Normalisation of RT-qPCR data to spike-in controls can reduce extraction bias. However, the extent of correlation for different qPCR systems varies in different assays. At different time points, there was no significant fold change in eight of the plasma miRNAs that we evaluated. Higher level of miRNAs was detected in plasma as compared to serum of the same cohort. In summary, we demonstrated that high-throughput RT-qPCR with pre-amplification step had increased sensitivity and can be achieved with accuracy and high reproducibility through stringent experimental controls. The information provided here is useful for planning biomarker validation studies involving circulating miRNAs.
Project description:Optimal endogenous controls enable reliable normalization of microRNA (miRNA) expression in reverse-transcription quantitative PCR (RT-qPCR). This is particularly important when miRNAs are considered as candidate diagnostic or prognostic biomarkers. Universal endogenous controls are lacking, thus candidate normalizers must be evaluated individually for each experiment. Here we present a strategy that we applied to the identification of optimal control miRNAs for RT-qPCR profiling of miRNA expression in T-cell acute lymphoblastic leukemia (T-ALL) and in normal cells of T-lineage. First, using NormFinder for an iterative analysis of miRNA stability in our miRNA-seq data, we established the number of control miRNAs to be used in RT-qPCR. Then, we identified optimal control miRNAs by a comprehensive analysis of miRNA stability in miRNA-seq data and in RT-qPCR by analysis of RT-qPCR amplification efficiency and expression across a variety of T-lineage samples and T-ALL cell line culture conditions. We then showed the utility of the combination of three miRNAs as endogenous normalizers (hsa-miR-16-5p, hsa-miR-25-3p, and hsa-let-7a-5p). These miRNAs might serve as first-line candidate endogenous controls for RT-qPCR analysis of miRNAs in different types of T-lineage samples: T-ALL patient samples, T-ALL cell lines, normal immature thymocytes, and mature T-lymphocytes. The strategy we present is universal and can be transferred to other RT-qPCR experiments.