Simulation of between repeat variability in real time PCR reactions

While many decisions rely on real time quantitative PCR (qPCR) analysis few attempts have hitherto been made to quantify bounds of precision accounting for the various sources of variation involved in the measurement process. Besides influences of more obvious factors such as camera noise and pipetting variation, changing efficiencies within and between reactions affect PCR results to a degree which is not fully recognized. Here, we develop a statistical framework that models measurement error and other sources of variation as they contribute to fluorescence observations during the amplification process and to derived parameter estimates. Evaluation of reproducibility is then based on simulations capable of generating realistic variation patterns. To this end, we start from a relatively simple statistical model for the evolution of efficiency in a single PCR reaction and introduce additional error components, one at a time, to arrive at stochastic data generation capable of simulating the variation patterns witnessed in repeated reactions (technical repeats). Most of the variation in C-q values was adequately captured by the statistical model in terms of foreseen components. To recreate the dispersion of the repeats' plateau levels while keeping the other aspects of the PCR curves within realistic bounds, additional sources of reagent consumption (side reactions) enter into the model. Once an adequate data generating model is available, simulations can serve to evaluate various aspects of PCR under the assumptions of the model and beyond

Enhanced analysis of real-time PCR data by using a variable efficiency model : FPK-PCR

Current methodology in real-time Polymerase chain reaction (PCR) analysis performs well provided PCR efficiency remains constant over reactions. Yet, small changes in efficiency can lead to large quantification errors. Particularly in biological samples, the possible presence of inhibitors forms a challenge. We present a new approach to single reaction efficiency calculation, called Full Process Kinetics-PCR (FPK-PCR). It combines a kinetically more realistic model with flexible adaptation to the full range of data. By reconstructing the entire chain of cycle efficiencies, rather than restricting the focus on a 'window of application', one extracts additional information and loses a level of arbitrariness. The maximal efficiency estimates returned by the model are comparable in accuracy and precision to both the golden standard of serial dilution and other single reaction efficiency methods. The cycle-to-cycle changes in efficiency, as described by the FPK-PCR procedure, stay considerably closer to the data than those from other S-shaped models. The assessment of individual cycle efficiencies returns more information than other single efficiency methods. It allows in-depth interpretation of real-time PCR data and reconstruction of the fluorescence data, providing quality control. Finally, by implementing a global efficiency model, reproducibility is improved as the selection of a window of application is avoided

Syndromic surveillance and pathogen detection using multiplex assays for respiratory infections in small ruminants

Background Several bacterial and viruses can infect the respiratory tract of small ruminants causing similar clinical signs. The differential diagnosis of respiratory diseases in small ruminants can be achieved using multi-plex assays for an accurate identification of the causative agents. Objective The present study was aimed at developing molecular multiplex as-says using different methods, such as real time PCR and micro fluidics bead-based technology, applicable for the syndromic surveillance of respiratory infection in small ruminants. The targeted infections were those caused by Capripoxviruses (CaPVs), Peste-des-petits ru-minants' virus (PPRV), Parapoxvirus, Mycoplasma Capricolum subsp. Capripneumoniae (MCCP) and Pasteurella multocida (PM). An inter-nal control was included in order to determine the quality of sam-ples being tested. Methodology Primers and probes were designed for the conserved regions of the genomes of all the targeted pathogens. The probes for real time PCR were labelled with compatible fluorescent dyes and quenchers, whereas for microfluidics bead based method, primers and probes were biotinylated, phosphorylated and C12 amino-modified accor-dingly. Total nucleic acid extraction procedures were evaluated to extract both DNA or RNA. The amplification protocols were opti-mized and the procedures were validated for the amplification of the above-mentioned pathogens in a single test (or tube). Results A one-step multiplex real time PCR method was developed to ampli-fy four targets, CaPVs, PPRV, MCCP and PM in order to accommodate real time PCR platforms from different manufacturers and reduce complexity in performing the assay. This real time PCR method was highly specific and sensitive in detecting the targeted pathogens as well as co-coinfections. Out of 314 samples tested from different African countries, 80 samples were positive for PPRV, 50 for PM, 2 for CaPV and 8 were mixed infections of PPRV and PM. The same patho-gens were included, and the panel was expanded with Parapoxvirus, an internal control, and tested in microfluidics bead-based method. The validated microfluidics bead-based method displayed a similar analytical sensitivity and specificity to the real time PCR based assay. Conclusion The real time PCR method is being implemented in routine diag-nostics and surveillance of different veterinary laboratories in Africa and Asia for differential diagnosis of PPR. Microfluidics bead-based assays will extend the scope by allowing the screening of more pathogens. These two multiplex approaches facilitate the syndromic surveillance of respiratory infection in small ruminants in regions where several pathogens with similar clinical symptoms are present

A MIQE-Compliant Real-Time PCR Assay for Aspergillus Detection

PMCID: PMC3393739This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Detection of Tumor Cell-Specific mRNA in the Peripheral Blood of Patients with Breast Cancer-Evaluation of Several Markers with Real-Time Reverse Transcription-PCR

It is widely known that cells from epithelial tumors, e. g., breast cancer, detach from their primary tissue and enter blood circulation. We show that the presence of circulating tumor cells (CTCs) in samples of patients with primary and metastatic breast cancer can be detected with an array of selected tumor-marker-genes by reverse transcription real-time PCR. The focus of the presented work is on detecting differences in gene expression between healthy individuals and adjuvant and metastatic breast cancer patients, not an accurate quantification of these differences. Therefore, total RNA was isolated from blood samples of healthy donors and patients with primary or metastatic breast cancer after enrichment of mononuclear cells by density gradient centrifugation. After reverse transcription real-time PCR was carried out with a set of marker genes (BCSP, CK8, Her2, MGL, CK18, CK19). B2M and GAPDH were used as reference genes. Blood samples from patients with metastatic disease revealed increased cytokine gene levels in comparison to normal blood samples. Detection of a single gene was not sufficient to detect CTCs by reverse transcription real-time PCR. Markers used here were selected based on a recent study detecting cancer cells on different protein levels. The combination of such a marker array leads to higher and more specific discovery rates, predominantly in metastatic patients. Identification of CTCs by PCR methods may lead to better diagnosis and prognosis and could help to choose an adequate therapy