Real-time PCR Data Analysis Research Articles

Production of Chimeric Acidic α-Amylase by the Recombinant Pichia pastoris and Its Applications

Recombinant chimeric α-amylase (Ba-Gt-amy) has been produced extracellularly in Pichia pastoris under AOX promoter. Clones of P. pastoris with multiple gene copies have been generated by multiple transformations and post-transformational vector amplification, which led to 10.7-fold enhancement in α-amylase titre as compared to a clone with a copy of the gene. The recombinant P. pastoris integrated eight copies of Ba-Gt-amy in the genome of P. pastoris, as revealed by real time PCR data analysis. Heterologous protein expression as well as mRNA level of Ba-Gt-amy was higher in multi-copy clone than that with single copy. The pure Ba-Gt-amy expressed in P. pastoris is a glycoprotein of 75 kDa, which is optimally active at pH 4.0 and 60°C with T1/2 of 40 min at 70°C. The Kinetic parameters and end product analysis suggested that glycosylation has no effect on catalytic properties of Ba-Gt-amy. The enzyme saccharifies soluble as well as raw starches efficiently and generates maltose and maltooligosaccharides, thus, useful in baking and sugar syrup industries. The strategy for generating multi-copy clones is being reported for the first time, which could be useful in enhancing the production of other recombinant proteins.

Increased ZAP70 Is Involved in Dry Skin Pruritus in Aged Mice.

Dry skin pruritus is common in the elderly. Recent reports show that T-cell signal path is involved in dry skin pruritus. Zeta-chain-associated protein kinase 70 (ZAP70), as a T-cell receptor, may induce interleukin 2 (IL-2) secretion and promote nerve growth factor (NGF) secretion in skin. This study aimed to detect the alteration of ZAP70 in a mice model with dry skin pruritus. The C57BL mice with 5 months and 22 months were used as experimental animal. Following a 5-day period of treatment of back with a mixture of acetone-diethyl-ether-water (AEW), mice exhibited a significant increase in spontaneous scratching behavior directed to the treated back compared to control animals in which back was similarly treated with water only (W). After AEW process, spontaneous scratching in 22-month AEW mice was increased compared to 5-month AEW mice. Western blot and real-time quantitative PCR data analysis showed that ZAP70 expression was significantly increased in 22-month AEW mice compared with 5-month AEW mice. ELISA data showed that secretions of IL-2 and NGF in 22-month AEW mice were higher than 5-month AEW mice. Our results indicate that increased ZAP70 is involved in dry skin in elderly pruritus. Increased secretion of IL-2 and NGF may induce dry skin itch.

Diagnostics of Tree Diseases Caused by Phytophthora austrocedri Species.

We present methods for the detection and quantification of four Phytophthora species which are pathogenic on trees; Phytophthora ramorum, Phytophthora kernoviae, Phytophthora lateralis, and Phytophthora austrocedri. Nucleic acid extraction methods are presented for phloem tissue from trees, soil, and pure cultures on agar plates. Real-time PCR methods are presented and include primer and probe sets for each species, general advice on real-time PCR setup and data analysis. A method for sequence-based identification, useful for pure cultures, is also included.

Identification of suitable reference genes for hepatic microRNA quantitation

BackgroundMicroRNAs (miRNAs) are short (~22 nt) endogenous RNAs that play important roles in regulating expression of a wide variety of genes involved in different cellular processes. Alterations in microRNA expression patterns have been associated with a number of human diseases. Accurate quantitation of microRNA levels is important for their use as biomarkers and in determining their functions. Real time PCR is the gold standard and the most frequently used technique for miRNA quantitation. Real time PCR data analysis includes normalizing the amplification data to suitable endogenous control/s to ensure that microRNA quantitation is not affected by the variability that is potentially introduced at different experimental steps. U6 (RNU6A) and RNU6B are two commonly used endogenous controls in microRNA quantitation. The present study was designed to investigate inter-individual variability and gender differences in hepatic microRNA expression as well as to identify the best endogenous control/s that could be used for normalization of real-time expression data in liver samples.MethodsWe used Taqman based real time PCR to quantitate hepatic expression levels of 22 microRNAs along with U6 and RNU6B in 50 human livers samples (25 M, 25 F). To identify the best endogenous controls for use in data analysis, we evaluated the amplified candidates for their stability (least variability) in expression using two commonly used software programs: Normfinder and GeNormplus,ResultsBoth Normfinder and GeNormplus identified U6 to be among the least stable of all the candidates analyzed, and RNU6B was also not among the top genes in stability. mir-152 and mir-23b were identified to be the two most stable candidates by both Normfinder and GeNormplus in our analysis, and were used as endogenous controls for normalization of hepatic miRNA levels.ConclusionMeasurements of microRNA stability indicate that U6 and RNU6B are not suitable for use as endogenous controls for normalizing microRNA relative quantitation data in hepatic tissue, and their use can led to possibly erroneous conclusions.

Gene Expression Signatures of Peripheral Blood Mononuclear Cells during the Early Post-Transplant Period in Patients Developing Cardiac Allograft Vasculopathy

Background. Cardiac allograft vasculopathy (CAV) is a major cause of graft loss and death after heart transplantation. Currently, no diagnostic methods are available during the early post-transplant period to accurately identify patients at risk of CAV. We hypothesized that PBMC gene expression profiles (GEP) can identify patients at risk of CAV. Methods. We retrospectively analyzed a limited set of whole-genome PBMC microarrays from 10 post-transplant patients who did (n = 3) or did not (n = 7) develop advanced grade CAV during their long-term follow-up. We used significance analysis of microarrays to identify differentially expressed genes and High-Throughput GoMiner to assess gene ontology (GO) categories. We corroborated our findings by retrospective analysis of PBMC real-time PCR data from 33 patients. Results. Over 300 genes were differentially expressed (FDR < 5%), and 18 GO-categories including “macrophage activation”, “Interleukin-6 pathway”, “NF-KappaB cascade”, and “response to virus” were enriched by these genes (FDR < 5%). Out of 8 transcripts available for RT-PCR analysis, we confirmed 6 transcripts (75.0%) including FPRL1, S100A9, CXCL10, PRO1073, and MMP9 (P < .05). Conclusion. Our pilot data suggest that GEP of PBMC may become a valuable tool in the evaluation of patients at risk of CAV. Larger prospectively designed studies are needed to corroborate our hypothesis.

HTqPCR: high-throughput analysis and visualization of quantitative real-time PCR data in R

Motivation: Quantitative real-time polymerase chain reaction (qPCR) is routinely used for RNA expression profiling, validation of microarray hybridization data and clinical diagnostic assays. Although numerous statistical tools are available in the public domain for the analysis of microarray experiments, this is not the case for qPCR. Proprietary software is typically provided by instrument manufacturers, but these solutions are not amenable to the tandem analysis of multiple assays. This is problematic when an experiment involves more than a simple comparison between a control and treatment sample, or when many qPCR datasets are to be analyzed in a high-throughput facility.Results: We have developed HTqPCR, a package for the R statistical computing environment, to enable the processing and analysis of qPCR data across multiple conditions and replicates.Availability: HTqPCR and user documentation can be obtained through Bioconductor or at http://www.ebi.ac.uk/bertone/software.Contact: bertone@ebi.ac.uk

QPCR: Application for real-time PCR data management and analysis

BackgroundSince its introduction quantitative real-time polymerase chain reaction (qPCR) has become the standard method for quantification of gene expression. Its high sensitivity, large dynamic range, and accuracy led to the development of numerous applications with an increasing number of samples to be analyzed. Data analysis consists of a number of steps, which have to be carried out in several different applications. Currently, no single tool is available which incorporates storage, management, and multiple methods covering the complete analysis pipeline.ResultsQPCR is a versatile web-based Java application that allows to store, manage, and analyze data from relative quantification qPCR experiments. It comprises a parser to import generated data from qPCR instruments and includes a variety of analysis methods to calculate cycle-threshold and amplification efficiency values. The analysis pipeline includes technical and biological replicate handling, incorporation of sample or gene specific efficiency, normalization using single or multiple reference genes, inter-run calibration, and fold change calculation. Moreover, the application supports assessment of error propagation throughout all analysis steps and allows conducting statistical tests on biological replicates. Results can be visualized in customizable charts and exported for further investigation.ConclusionWe have developed a web-based system designed to enhance and facilitate the analysis of qPCR experiments. It covers the complete analysis workflow combining parsing, analysis, and generation of charts into one single application. The system is freely available at

Promotion of BACE1 mRNA Alternative Splicing Reduces Amyloid β-Peptide Production

Production of the amyloid beta-peptide (Abeta) via sequential proteolytic cleavage of the amyloid precursor protein by beta- and gamma-secretases is strongly implicated in the pathogenesis of Alzheimer disease. The beta-secretase that executes the first cleavage event is a transmembrane aspartyl protease known as beta-site amyloid precursor protein-cleaving enzyme 1 (BACE1). BACE1 pre-mRNA is alternatively spliced through the use of alternative splice sites in exons 3 and 4, although the significance of these splicing events is unclear. Here, we quantitatively measured relative levels of BACE1 transcripts and identified a novel splice variant of BACE1. We found a subtle but significant difference in BACE1 splicing between brain and pancreas, indicating the cellular environment can affect BACE1 alternative splicing. Furthermore, we have shown that BACE1 proteins translated from alternatively spliced transcripts have dramatically reduced beta-secretase activity and promotion of BACE1 alternative splicing reduces Abeta production. These findings illustrate the importance of BACE1 alternative splicing in affecting the level of Abeta produced in cells and suggest that targeting regulation of BACE1 alternative splicing is a potential therapeutic strategy for lowering beta-secretase activity.

A new method for robust quantitative and qualitative analysis of real-time PCR

An automated data analysis method for real-time PCR needs to exhibit robustness to the factors that routinely impact the measurement and analysis of real-time PCR data. Robust analysis is paramount to providing the same interpretation for results regardless of the skill of the operator performing or reviewing the work. We present a new method for analysis of real-time PCR data, the maxRatio method, which identifies a consistent point within or very near the exponential region of the PCR signal without requiring user intervention. Compared to other analytical techniques that generate only a cycle number, maxRatio generates several measurements of amplification including cycle numbers and relative measures of amplification efficiency and curve shape. By using these values, the maxRatio method can make highly reliable reactive/nonreactive determination along with quantitative evaluation. Application of the maxRatio method to the analysis of quantitative and qualitative real-time PCR assays is shown along with examples of method robustness to, and detection of, amplification response anomalies.

Highly accurate sigmoidal fitting of real-time PCR data by introducing a parameter for asymmetry

BackgroundFitting four-parameter sigmoidal models is one of the methods established in the analysis of quantitative real-time PCR (qPCR) data. We had observed that these models are not optimal in the fitting outcome due to the inherent constraint of symmetry around the point of inflection. Thus, we found it necessary to employ a mathematical algorithm that circumvents this problem and which utilizes an additional parameter for accommodating asymmetrical structures in sigmoidal qPCR data.ResultsThe four-parameter models were compared to their five-parameter counterparts by means of nested F-tests based on the residual variance, thus acquiring a statistical measure for higher performance. For nearly all qPCR data we examined, five-parameter models resulted in a significantly better fit. Furthermore, accuracy and precision for the estimation of efficiencies and calculation of quantitative ratios were assessed with four independent dilution datasets and compared to the most commonly used quantification methods. It could be shown that the five-parameter model exhibits an accuracy and precision more similar to the non-sigmoidal quantification methods.ConclusionThe five-parameter sigmoidal models outperform the established four-parameter model with high statistical significance. The estimation of essential PCR parameters such as PCR efficiency, threshold cycles and initial template fluorescence is more robust and has smaller variance. The model is implemented in the qpcR package for the freely available statistical R environment. The package can be downloaded from the author's homepage.

Cross‐platform comparisons of algorithms for calculating real‐time PCR amplification efficiencies

The analysis of real‐time PCR data has become the focus of mathematical modeling to increase quantification precision and accuracy. Methods include: (1) the slope‐derived efficiency calculation from the standard curve method using Ct values determined either from (a) the fit‐point method or (b) the second derivative maximum (SDM) of a four parametric logistic model; or (2) the single amplification plot methods to compute efficiencies from individual PCR kinetic curves using comprehensive algorithms such as (a) mid‐point regression (Data Analysis for Real‐time PCR or DART‐PCR), (b) the window‐of‐linearity algorithm (LinReg) or (c) noise‐resistant iterative nonlinear regression (Real‐time PCR Miner). We directly compared these methods on three commonly used real‐time PCR instruments (BioRad iCycler iQ™, Stratagene Mx3005P™ and ABI 7500 Fast PCR System). SYBR‐Green® based RT2 Profiler™PCR Arrays from SuperArray Bioscience were used with serially diluted DNA templates and the amplification efficiency for each PCR assay was computed. This study demonstrates that Real‐time PCR Miner provides the best precision in efficiency estimation independent of the PCR instrument, while the precisions for other methods are platform‐dependent. Accounting for amplification efficiencies in fold‐change calculations may increase the precision of gene expression measurements using real time PCR.

Statistical methods for efficiency adjusted real‐time PCR quantification

The statistical treatment for hypothesis testing using real-time PCR data is a challenge for quantification of gene expression. One has to consider two key factors in precise statistical analysis of real-time PCR data: a well-defined statistical model and the integration of amplification efficiency (AE) into the model. Previous publications in real-time PCR data analysis often fall short in integrating the AE into the model. Novel, user-friendly, and universal AE-integrated statistical methods were developed for real-time PCR data analysis with four goals. First, we addressed the definition of AE, introduced the concept of efficiency-adjusted Delta Delta Ct, and developed a general mathematical method for its calculation. Second, we developed several linear combination approaches for the estimation of efficiency adjusted Delta Delta Ct and statistical significance for hypothesis testing based on different mathematical formulae and experimental designs. Statistical methods were also adopted to estimate the AE and its equivalence among the samples. A weighted Delta Delta Ct method was introduced to analyze the data with multiple internal controls. Third, we implemented the linear models with SAS programs and analyzed a set of data for each model. In order to allow other researchers to use and compare different approaches, SAS programs are included in the Supporting Information. Fourth, the results from analysis of different statistical models were compared and discussed. Our results underline the differences between the efficiency adjusted Delta Delta Ct methods and previously published methods, thereby better identifying and controlling the source of errors introduced by real-time PCR data analysis.

Recirculating Immunomagnetic Separation and Optimal Enrichment Conditions for Enhanced Detection and Recovery of Low Levels of Escherichia coli O157:H7 from Fresh Leafy Produce and Surface Water

The objective of this study was to develop a rapid, simple method for enhanced detection and isolation of low levels of Escherichia coli O157:H7 from leafy produce and surface water using recirculating immunomagnetic separation (RIMS) coupled with real-time PCR and a standard culture method. The optimal enrichment conditions for the method also were determined. Analysis of real-time PCR data (CT values) suggested that incubation of lettuce and spinach leaves rather than rinsates provides better enrichment of E. coli O157:H7. Enrichment of lettuce or spinach leaves at 42°C for 5 h provided better detection than enrichment at 37°C. Extended incubation of surface water for 20 h at 42°C did not improve the detection. The optimized enrichment conditions were also employed with modified Moore swabs, which were used to sample flowing water sites. Positive isolation rates and real-time PCR results indicated an increased recovery of E. coli O157:H7 from all samples following the application of RIMS. Under these conditions, the method provided detection and/or isolation of E. coli O157:H7 at levels as low as 0.07 CFU/g of lettuce, 0.1 CFU/g of spinach, 6 CFU/100 ml of surface water, and 9 CFU per modified Moore swab. During a 6-month field study, modified Moore swabs yielded high isolation rates when deployed in natural watershed sites. The method used in this study was effective for monitoring E. coli O157:H7 in the farm environment, during postharvest processing, and in foodborne outbreak investigations.

QBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data

qBase, a free program for the management and automated analysis of qPCR data, is described

Relative quantification of mRNA: comparison of methods currently used for real-time PCR data analysis

BackgroundFluorescent data obtained from real-time PCR must be processed by some method of data analysis to obtain the relative quantity of target mRNA. The method chosen for data analysis can strongly influence results of the quantification.ResultsTo compare the performance of six techniques which are currently used for analysing fluorescent data in real-time PCR relative quantification, we quantified four cytokine transcripts (IL-1β, IL-6 TNF-α, and GM-CSF) in an in vivo model of colonic inflammation. Accuracy of the methods was tested by quantification on samples with known relative amounts of target mRNAs. Reproducibility of the methods was estimated by the determination of the intra-assay and inter-assay variability. Cytokine expression normalized to the expression of three reference genes (ACTB, HPRT, SDHA) was then determined using the six methods for data analysis. The best results were obtained with the relative standard curve method, comparative Ct method and with DART-PCR, LinRegPCR and Liu & Saint exponential methods when average amplification efficiency was used. The use of individual amplification efficiencies in DART-PCR, LinRegPCR and Liu & Saint exponential methods significantly impaired the results. The sigmoid curve-fitting (SCF) method produced medium performance; the results indicate that the use of appropriate type of fluorescence data and in some instances manual selection of the number of amplification cycles included in the analysis is necessary when the SCF method is applied. We also compared amplification efficiencies (E) and found that although the E values determined by different methods of analysis were not identical, all the methods were capable to identify two genes whose E values significantly differed from other genes.ConclusionOur results show that all the tested methods can provide quantitative values reflecting the amounts of measured mRNA in samples, but they differ in their accuracy and reproducibility. Selection of the appropriate method can also depend on the design of a particular experiment. The advantages and disadvantages of the methods in different applications are discussed.

Evaluation of quantification methods for real-time PCR minor groove binding hybridization probe assays

Real-time PCR data analysis for quantification has been the subject of many studies aimed at the identification of new and improved quantification methods. Several analysis methods have been proposed as superior alternatives to the common variations of the threshold crossing method. Notably, sigmoidal and exponential curve fit methods have been proposed. However, these studies have primarily analyzed real-time PCR with intercalating dyes such as SYBR Green. Clinical real-time PCR assays, in contrast, often employ fluorescent probes whose real-time amplification fluorescence curves differ from those of intercalating dyes. In the current study, we compared four analysis methods related to recent literature: two versions of the threshold crossing method, a second derivative maximum method, and a sigmoidal curve fit method. These methods were applied to a clinically relevant real-time human herpes virus type 6 (HHV6) PCR assay that used a minor groove binding (MGB) Eclipse hybridization probe as well as an Epstein–Barr virus (EBV) PCR assay that used an MGB Pleiades hybridization probe. We found that the crossing threshold method yielded more precise results when analyzing the HHV6 assay, which was characterized by lower signal/noise and less developed amplification curve plateaus. In contrast, the EBV assay, characterized by greater signal/noise and amplification curves with plateau regions similar to those observed with intercalating dyes, gave results with statistically similar precision by all four analysis methods.

Quantitative real-time RT-PCR data analysis: current concepts and the novel “gene expression’s C T difference” formula

For quantification of gene-specific mRNA, quantitative real-time RT-PCR has become one of the most frequently used methods over the last few years. This article focuses on the issue of real-time PCR data analysis and its mathematical background, offering a general concept for efficient, fast and precise data analysis superior to the commonly used comparative CT (DeltaDeltaCT) and the standard curve method, as it considers individual amplification efficiencies for every PCR. This concept is based on a novel formula for the calculation of relative gene expression ratios, termed GED (Gene Expression's CT Difference) formula. Prerequisites for this formula, such as real-time PCR kinetics, the concept of PCR efficiency and its determination, are discussed. Additionally, this article offers some technical considerations and information on statistical analysis of real-time PCR data.

Novel methods of quantitative real-time PCR data analysis in a murine Helicobacter pylori vaccine model

Monitoring of Helicobacter pylori in the stomach is important to assess the efficacy of new vaccines against the pathogen. To realise the full potential of quantitative real-time PCR (q-PCR), this technology has to offer accurate and easy models of post-PCR data analysis. In this work, we used a variety of absolute and relative approaches of q-PCR data analysis to monitor the H. pylori infection in the stomach of immunized mice. Relative quantification was performed with Ct-based methods, with the DART program, and with two methods based on the mathematical analysis of raw fluorescence kinetics, the LinReg program and the Sigmoidal Curve Fitting Method. The different calculation methods were validated in mice immunized with cell lysates of Lactococcus lactis expressing the H. pylori urease subunit B in combination with cholera toxin. The H. pylori load was found to be reduced in immunized mice by a factor of 50–144, depending on the calculation method employed. We found that relative quantification using DART, LinReg and Sigmoidal Curve Fitting methods generated similar results (infection ratios of 54–58) with absolute quantification results (54–65). Results were very different to those using relative quantification Ct-based methods without a correction for PCR efficiency (ratio of 92–144) and with results based on conventional culture method (ratio of 34). Overall, this study demonstrates that q-PCR associated with a relative quantification analysis is a powerful tool for the monitoring of microorganisms in tissue. It could be used as an alternative to standard curve approach especially for the investigation of microbial load in vaccine models.

Evaluation of absolute quantitation by nonlinear regression in probe-based real-time PCR

BackgroundIn real-time PCR data analysis, the cycle threshold (CT) method is currently the gold standard. This method is based on an assumption of equal PCR efficiency in all reactions, and precision may suffer if this condition is not met. Nonlinear regression analysis (NLR) or curve fitting has therefore been suggested as an alternative to the cycle threshold method for absolute quantitation. The advantages of NLR are that the individual sample efficiency is simulated by the model and that absolute quantitation is possible without a standard curve, releasing reaction wells for unknown samples. However, the calculation method has not been evaluated systematically and has not previously been applied to a TaqMan platform. Aim: To develop and evaluate an automated NLR algorithm capable of generating batch production regression analysis.ResultsTotal RNA samples extracted from human gastric mucosa were reverse transcribed and analysed for TNFA, IL18 and ACTB by TaqMan real-time PCR. Fluorescence data were analysed by the regular CT method with a standard curve, and by NLR with a positive control for conversion of fluorescence intensity to copy number, and for this purpose an automated algorithm was written in SPSS syntax. Eleven separate regression models were tested, and the output data was subjected to Altman-Bland analysis. The Altman-Bland analysis showed that the best regression model yielded quantitative data with an intra-assay variation of 58% vs. 24% for the CT derived copy numbers, and with a mean inter-method deviation of × 0.8.ConclusionNLR can be automated for batch production analysis, but the CT method is more precise for absolute quantitation in the present setting. The observed inter-method deviation is an indication that assessment of the fluorescence conversion factor used in the regression method can be improved. However, the versatility depends on the level of precision required, and in some settings the increased cost effectiveness of NLR may justify the lower precision.

Statistical analysis of real-time PCR data.

BackgroundEven though real-time PCR has been broadly applied in biomedical sciences, data processing procedures for the analysis of quantitative real-time PCR are still lacking; specifically in the realm of appropriate statistical treatment. Confidence interval and statistical significance considerations are not explicit in many of the current data analysis approaches. Based on the standard curve method and other useful data analysis methods, we present and compare four statistical approaches and models for the analysis of real-time PCR data.ResultsIn the first approach, a multiple regression analysis model was developed to derive ΔΔCt from estimation of interaction of gene and treatment effects. In the second approach, an ANCOVA (analysis of covariance) model was proposed, and the ΔΔCt can be derived from analysis of effects of variables. The other two models involve calculation ΔCt followed by a two group t-test and non-parametric analogous Wilcoxon test. SAS programs were developed for all four models and data output for analysis of a sample set are presented. In addition, a data quality control model was developed and implemented using SAS.ConclusionPractical statistical solutions with SAS programs were developed for real-time PCR data and a sample dataset was analyzed with the SAS programs. The analysis using the various models and programs yielded similar results. Data quality control and analysis procedures presented here provide statistical elements for the estimation of the relative expression of genes using real-time PCR.