The emerging technique of microfluidic digital PCR (dPCR) offers a unique approach to real-time quantitative PCR for measuring nucleic acids that may be particularly suited for low-level detection. In this study, we evaluated the quantitative capabilities of dPCR when measuring small amounts (<200 copies) of DNA and investigated parameters influencing technical performance. We used various DNA templates, matrixes, and assays to evaluate the precision, sensitivity and reproducibility of dPCR, and demonstrate that this technique can be highly reproducible when performed at different times and when different primer sets are targeting the same molecule. dPCR exhibited good analytical sensitivity and was reproducible outside the range recommended by the instrument manufacturer; detecting 16 estimated targets with high precision. The inclusion of carrier had no effect on this estimated quantity, but did improve measurement precision. We report disagreement when using dPCR to measure different template types and when comparing the estimated quantities by dPCR and UV spectrophotometry. Finally, we also demonstrate that preamplification can impose a significant measurement bias. These findings provide an independent assessment of low copy molecular measurement using dPCR and underline important factors for consideration in dPCR experimental design.
Digital PCR (dPCR) is being increasingly used for the quantification of sequence variations, including single nucleotide polymorphisms (SNPs), due to its high accuracy and precision in comparison with techniques such as quantitative PCR (qPCR) and melt curve analysis. To develop and evaluate dPCR for SNP detection using DNA, RNA, and clinical samples, an influenza virus model of resistance to oseltamivir (Tamiflu) was used. First, this study was able to recognize and reduce off-target amplification in dPCR quantification, thereby enabling technical sensitivities down to 0.1% SNP abundance at a range of template concentrations, a 50-fold improvement on the qPCR assay used routinely in the clinic. Second, a method was developed for determining the false-positive rate (background) signal. Finally, comparison of dPCR with qPCR results on clinical samples demonstrated the potential impact dPCR could have on clinical research and patient management by earlier (trace) detection of rare drug-resistant sequence variants. Ultimately this could reduce the quantity of ineffective drugs taken and facilitate early switching to alternative medication when available. In the short term such methods could advance our understanding of microbial dynamics and therapeutic responses in a range of infectious diseases such as HIV, viral hepatitis, and tuberculosis. Furthermore, the findings presented here are directly relevant to other diagnostic areas, such as the detection of rare SNPs in malignancy, monitoring of graft rejection, and fetal screening.
This work validates dPCR as an SI-traceable reference measurement procedure based on enumeration and demonstrates how it can be applied for assignment of copy number concentration and fractional abundance values to DNA reference materials in an aqueous solution. High-accuracy measurements using dPCR will support the implementation and traceable standardization of molecular diagnostic procedures needed for advancements in precision medicine.
Sample quality is of major importance when conducting molecular analysis of nucleic acids, and factors such as degradation, presence of impurities, and enzymatic inhibitors may have a significant impact on the quality of data. Issues of quality assessment become more important as the increased use of biobanking means that whole blood samples are being stored for longer periods. A range of commercially available kits/methods have been specifically developed for extraction of high quality nucleic acids from a variety of clinical samples, including blood, but there is limited information on how best to quality assess the extracts to determine their fitness for purpose in specific downstream applications. In this study, we have performed nucleic acid extractions from stored blood using a number of different methods. The resulting extracts were analyzed by a panel of quantity and quality metrics including UV spectrophotometry, PicoGreen fluorescence, electrophoresis, and a PCR approach. To evaluate the relevance of different metrics, DNA samples were subsequently assessed for their performance in real time PCR and microarray experiments. Our findings demonstrate that the most suitable extraction technique and quality assessment approach depends on the required downstream analytical method.
Authentication of pasta is currently determined using molecular biology-based techniques focusing on DNA as the target analyte. Whilst proven to be effective, these approaches can be criticised as being destructive, time consuming, and requiring specialist instrument training. Advances in the field of multispectral imaging (MSI) and hyperspectral imaging (HSI) have facilitated the development of compact imaging platforms with the capability to rapidly differentiate a range of materials (inclusive of grains and seeds) based on surface colour, texture and chemical composition. This preliminary investigation evaluated the applicability of spectral imaging for identification and quantitation of durum wheat grain samples in relation to pasta authenticity. MSI and HSI were capable of rapidly distinguishing between durum wheat and adulterant common wheat cultivars and assigning percentage adulteration levels characterised by low biases and good repeatability estimates. The results demonstrated the potential for spectral imaging based seed/grain adulteration testing to augment existing standard molecular approaches for food authenticity testing.
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