Detection of Saccharopolyspora rectivirgula by quantitative Real-Time PCR

The thermophilic actinomycete species Saccharopolyspora rectivirgula has been associated with the exogen allergic alveolitis (EAA). EAA is caused by the inhalation of high amounts of airborne spores that can be found for example in environments of agricultural production, compost facilities, mushroom cultivation rooms, or rooms with technical air moistening. Because of the medical relevance of S. rectivirgula, a reliable detection system is needed. Therefore, a quantitative real-time polymerase chain reaction (qPCR) primer system was designed, targeting the 16S rRNA gene of the type strain S. rectivirgula DSM 43747T and six other S. rectivirgula reference strains. Our investigation showed that S. rectivirgula presumably own four operons of the 16S rRNA gene, which has to be considered for estimation of cell equivalents. Furthermore, the DNA recovery efficiency from these strains was tested in combination with bioaerosol or material sample as well as the influence of non-target DNA to the recovery rate. Results showed a recovery DNA efficiency of 7–55%. The recovery rate of DNA in a mixture with non-target DNA resulted in ~87%. In summary, a high amplification efficiency using real-time PCR was found, for which estimated concentrations revealed cell numbers of 2.7 × 105 cells m-3 in bioaerosol and 2.8 × 106 cells g-1 fw-1 in material samples from a duck house. The specificity of the new developed quantification system was shown by generation of two clone libraries from bioarosol samples, from a duck house, and from a composting plant. Totally, the results clearly show the specificity and practicability of the established qPCR assay for detection of S. rectivirgula

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

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

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