Despite the wide-spread use of the polymerase chain reaction (PCR) in various life-science applications, the causes of arrested amplicon generation in late cycles have not been confidently identified. This so-called plateau phase has been attributed to depletion or thermal break-down of primers or nucleotides, thermal inactivation of the DNA polymerase, and product accumulation resulting in competition between primer annealing and product re-hybridization as well as blocking of DNA polymerase by double-stranded amplicons. In the current study, we experimentally investigate the proposed limiting factors of PCR product formation. By applying robust and validated qPCR assays, we elucidate the impact of adding non-target and target amplicons to the reactions, mimicking the high amount of products in late PCR cycles. Further, the impact of increased primer concentrations and thermal stability of reagents are explored. Our results show that high amounts of non-target amplicons inhibit amplification by binding to the DNA polymerase, but that this effect is counteracted by addition of more DNA polymerase or prolonged annealing/extension times. Adding high amounts of target amplicons that also act as templates in the reaction is far less inhibitory to amplification, although a decrease in amplification rate is seen. When primer concentrations are increased, both amplification rates and end-product yields are elevated. Taken together, our results suggest that the main cause of PCR plateau formation is primer depletion and not product accumulation or degradation of reagents. We stress that a PCR plateau caused by primer depletion is assay-dependent, i.e. dependent on the primer design and primer characteristics such as the probability of primer-dimer formation. Our findings contribute to an improved understanding of the major parameters controlling the PCR dynamics at later cycles and the limitations of continued product formation, which in the end can facilitate PCR optimization.
An increasing number of studies demonstrate the potential use of cell-free DNA (cfDNA) as a surrogate marker for multiple indications in cancer, including diagnosis, prognosis, and monitoring. However, harnessing the full potential of cfDNA requires (i) the optimization and standardization of preanalytical steps, (ii) refinement of current analysis strategies, and, perhaps most importantly, (iii) significant improvements in our understanding of its origin, physical properties, and dynamics in circulation. The latter knowledge is crucial for interpreting the associations between changes in the baseline characteristics of cfDNA and the clinical manifestations of cancer. In this review we explore recent advancements and highlight the current gaps in our knowledge concerning each point of contact between cfDNA analysis and the different stages of cancer management.
Small extracellular vesicles (EVs) are 50–200 nm sized mediators in intercellular communication that reflect both physiological and pathophysiological changes of their parental cells. Thus, EVs hold great potential for biomarker detection. However, reliable purification methods for the downstream screening of the microRNA (miRNA) cargo carried within urinary EVs by small RNA sequencing have yet to be established. To address this knowledge gap, RNA extracted from human urinary EVs obtained by five different urinary EV purification methods (spin column chromatography, immunoaffinity, membrane affinity, precipitation and ultracentrifugation combined with density gradient) was analyzed by small RNA sequencing. Urinary EVs were further characterized by nanoparticle tracking analysis, Western blot analysis and transmission electron microscopy. Comprehensive EV characterization established significant method-dependent differences in size and concentration as well as variances in protein composition of isolated vesicles. Even though all purification methods captured enough total RNA to allow small RNA sequencing, method-dependent differences were also observed with respect to library sizes, mapping distributions, number of miRNA reads and diversity of transcripts. Whereas EVs obtained by immunoaffinity yielded the purest subset of small EVs, highly comparable with results attained by ultracentrifugation combined with density gradient, precipitation and membrane affinity, sample purification by spin column chromatography indicated a tendency to isolate different subtypes of small EVs, which might also carry a distinct subset of miRNAs. Based on our results, different EV purification methods seem to preferentially isolate different subtypes of EVs with varying efficiencies. As a consequence, sequencing experiments and resulting miRNA profiles were also affected. Hence, the selection of a specific EV isolation method has to satisfy the respective research question and should be well considered. In strict adherence with the MISEV (minimal information for studies of extracellular vesicles) guidelines, the importance of a combined evaluation of biophysical and proteomic EV characteristics alongside transcriptomic results was clearly demonstrated in this present study.
Genetically modified alfalfa is authorized for cultivation in several countries since 2005. On the other hand, cultivation in or export to the European Union is not allowed and thus neither certified reference material nor official event-specific detection methods are available. Therefore, based on patent sequence information, event-specific real-time PCR detection methods targeting the junction sequence of the alfalfa genome and the transgenic insert of the respective events J101, J163 and KK179 were developed. Newly developed plasmids were used as reference material for assay optimization and in-house validation. Plasmid standards were quantified using digital droplet PCR and LOD95%, PCR efficiency, robustness and specificity of the assays were determined using real-time PCR. A LOD95% of 10 copies per PCR reaction was observed and PCR efficiencies of 95–97 % were achieved. Different real-time PCR instruments and PCR conditions were applied to test for robustness of the assays using DNA at a concentration of 30 copies per μL for each gm alfalfa event. All replicates were positive independent of the instrument or the PCR condition. DNA from certified reference material of different genetically modified crops as well as reference materials of the three events was used to experimentally test for specificity. No unspecific amplification signal was observed for any of the assays. Validation results were in line with the “Minimum Performance Requirements for Analytical Methods of GMO Testing” of the European Network of GMO Laboratories. Furthermore, an inter-laboratory comparison study was conducted to show the transferability and applicability of the methods and to verify the assay performance parameters.
[This corrects the article DOI: 10.1016/j.bdq.2015.10.001.].
Non-coding RNAs were established in the last decade as a new valuable biomarker class for human diseases. Specifically, circular RNAs (circRNAs) were only recently discovered as a new large group of non-coding RNAs that, due to their circular configuration, are metabolically more stable compared to their linear counterparts and therefore highly suitable for biomarker use. Based on high-throughput sequencing, the catalogs of endogenous circRNAs with disease relevance and correlation continue to grow steadily. As a consequence, circRNAs emerged as novel and attractive biomarkers, indicated by numerous recent publications. Here we would like to stress the need of essential quality criteria for validation and characterization of circular RNAs. In addition to high-throughput sequencing, classical biochemical methods are essential and should be applied for the characterization of this special class of RNAs, in particular to convincingly confirm their circularity.
[This corrects the article DOI: 10.1016/j.bdq.2018.12.003.].
Over the last few decades, there has been a decline in Northern bobwhite quail (Colinus virginianus) throughout their native range. While there are various factors that may be influencing this decline, it is suggested that parasites should be taken into consideration as a potential contributor in the Rolling Plains Ecoregion. High prevalence of the eyeworm (Oxyspirura petrowi) and caecal worm (Aulonocephalus pennula) in bobwhite of this region, coupled with a continuous decline, creates a need to assess infection through alternative methods for regional surveillance. Previous studies have developed a qPCR method and mobile research laboratory as an option for nonlethal procedures. However, there is still a need for standardization of these techniques. Therefore, this study builds on previous protocols to develop an application that considers factors that may influence qPCR results. In this study, cloacal swabs are collected from bobwhite in three locations throughout the Rolling Plains and scaled based on amount of feces present on the swab. This data is compared to qPCR standards as a limit of quantification for both eyeworm and caecal worm to define parasitic infection levels. Binary logistic regressions confirm that the probability of detection increases for both eyeworm (Odds Ratio: 2.3738; 95% Confidence Interval: [1.7804, 3.1649]) and caecal worm (Odds Ratio: 2.8516; 95% Confidence Interval: [2.2235, 3.6570]) as swab score increases. Infection levels for eyeworm and caecal worm are based on the generated cycle threshold value averages of qPCR standards. Based on the results of this study, this method can be applied in the mobile research laboratory to quantitatively assess regional parasitic infection in bobwhite throughout the Rolling Plains.
The standard approach for quantitative estimation of genetic materials with qPCR is calibration with known concentrations for the target substance, in which estimates of the quantification cycle (Cq) are fitted to a straight-line function of log(N0), where N0 is the initial number of target molecules. The location of Cq for the unknown on this line then yields its N0. The most widely used definition for Cq is an absolute threshold that falls in the early growth cycles. This usage is flawed as commonly implemented: threshold set very close to the baseline level, which is estimated separately, from designated "baseline cycles." The absolute threshold is especially poor for dealing with the scale variability often observed for growth profiles. Scale-independent markers, like the first derivative maximum (FDM) and a relative threshold (Cr) avoid this problem. We describe improved methods for estimating these and other Cq markers and their standard errors, from a nonlinear algorithm that fits growth profiles to a 4-parameter log-logistic function plus a baseline function. By examining six multidilution, multireplicate qPCR data sets, we find that nonlinear expressions are often preferred statistically for the dependence of Cq on log(N0). This means that the amplification efficiency E depends on N0, in violation of another tenet of qPCR analysis. Neglect of calibration nonlinearity leads to biased estimates of the unknown. By logic, E estimates from calibration fitting pertain to the earliest baseline cycles, not the early growth cycles used to estimate E from growth profiles for single reactions. This raises concern about the use of the latter in lengthy extrapolations to estimate N0. Finally, we observe that replicate ensemble standard deviations greatly exceed predictions, implying that much better results can be achieved from qPCR through better experimental procedures, which likely include reducing pipette volume uncertainty.
mRNA is a critical biomolecule involved in the manifestation of the genetic code into functional protein molecules. Its critical role in the central dogma has made it a key target in many studies to determine biomarkers and drug targets for numerous diseases. Currently, there is a growing body of evidence to suggest that RNA molecules around the size of full-length mRNA transcripts can be assayed in the supernatant of human urine and urinary extracellular mRNA could provide information about transcription in cells of urogenital tissues. However, the optimal means of normalizing these signals is unclear. In this paper, we describe relevant first principles as well as research findings from our lab and other labs toward normalization of urinary extracellular mRNA.
The kinetic requirements of quantitative PCR were experimentally dissected into the stages of DNA denaturation, primer annealing, and polymerase extension. The temperature/time conditions for 2 stages were kept optimal, while the other was limited until the amplification efficiency decreased as measured by an increase in quantification cycle (Cq). Extension was studied in a commercial capillary LightCycler®. Using a rapid deletion mutant of Taq (KlenTaq™), about 1 s was required for every 70 bp of product length. To study annealing and denaturation times of <1 s, a custom “extreme” PCR instrument with 3 temperatures was used along with increased primer and polymerase concentrations. Actual sample temperatures and times were measured rather than programmed or predicted. For denaturation, 200–500 ms above the denaturation threshold was necessary for maximal efficiency. For annealing, 300-1000 ms below the annealing threshold was required. Temperature thresholds were set at 98% primer annealing or PCR product denaturation as determined experimentally by melting curves. Progressing from rapid cycle PCR to extreme PCR decreased cycling times by 10–60 fold. If temperatures are controlled accurately and flexibility in reagents is allowed, PCR of short products can be performed in less than 15 s. We also put PCR in context to other emerging methods and consider its relevance to the evolution of molecular diagnostics.
Direct detection of single stained DNA fragments in flow is a very sensitive method for nucleic acid detection which does not need any amplification process. We have developed an instrument for direct counting and sizing of single DNA fragments (single or double stranded DNA) in flow with integrated sample volume measurement for concentration determination. As the method is a potential reference method for DNA quantification, processes affecting the measurement uncertainty are of major interest. Additionally, comparison of this method to the orthogonal method of digital PCR is useful with the restriction of low specificity of the direct detection method. In this study, we analysed raw detector signals and the sizing performance for target identification and the effect of coincidence detection concerning concentration measurements. We present data of purified artificial DNA samples measured with the home-built setup. Main emphasis was to develop an improved data analysis method to gain insight into and carefully correct for coincident detection of DNA fragments and for estimation of the amount of fragment dimers.
The analysis of HIV-1 sequences has helped understand the viral molecular epidemiology, monitor the development of antiretroviral drug resistance, and design candidate vaccines. The introduction of single genome amplification (SGA) has been a major advancement in the field, allowing for the characterization of multiple sequences per patient while preserving linkage among polymorphisms in the same viral genome copy. Sequencing of SGA amplicons is performed by capillary Sanger sequencing, which presents low throughput, requires a high amount of template, and is highly sensitive to template/primer mismatching. In order to meet the increasing demand for HIV-1 SGA amplicon sequencing, we have developed a platform based on benchtop next-generation sequencing (NGS) (IonTorrent) accompanied by a bioinformatics pipeline capable of running on computer resources commonly available at research laboratories. During assay validation, the NGS-based sequencing of 10 HIV-1 env SGA amplicons was fully concordant with Sanger sequencing. The field test was conducted on plasma samples from 10 US Navy and Marine service members with recent HIV-1 infection (sampling interval: 2005-2010; plasma viral load: 5,884-194,984 copies/ml). The NGS analysis of 101 SGA amplicons (median: 10 amplicons/individual) showed within-individual viral sequence profiles expected in individuals at this disease stage, including individuals with highly homogeneous quasispecies, individuals with two highly homogeneous viral lineages, and individuals with heterogeneous viral populations. In a scalability assessment using the Ion Chef automated system, 41/43 tested env SGA amplicons (95%) multiplexed on a single Ion 318 chip showed consistent gene-wide coverage >50×. With lower sample requirements and higher throughput, this approach is suitable to support the increasing demand for high-quality and cost-effective HIV-1 sequences in fields such as molecular epidemiology, and development of preventive and therapeutic strategies.
Circulating cell-free tumor DNA (ctDNA) is a promising biomarker in cancer. Ultrasensitive technologies enable detection of low (< 0.1%) mutant allele frequencies, a pre-requisite to fully utilize the potential of ctDNA in cancer diagnostics. In addition, the entire liquid biopsy workflow needs to be carefully optimized to enable reliable ctDNA analysis. Here, we discuss important considerations for ctDNA detection in plasma. We show how each experimental step can easily be evaluated using simple quantitative PCR assays, including detection of cellular DNA contamination and PCR inhibition. Furthermore, ctDNA assay performance is also demonstrated to be affected by both DNA fragmentation and target sequence. Finally, we show that quantitative PCR is useful to estimate the required sequencing depth and to monitor DNA losses throughout the workflow. The use of quality control assays enables the development of robust and standardized workflows that facilitate the implementation of ctDNA analysis into clinical routine.
The RNA-to-cDNA conversion step in transcriptomics experiments is widely recognised as inefficient and variable, casting doubt on the ability to do quantitative transcriptomics analyses. Multiple studies have focused on ways to optimise this process, resulting in contradictory recommendations. Here we explore the problem of reverse transcription efficiency using digital PCR and the RT method's impact on subsequent data analysis. Using synthetic RNA standards, an example experiment is presented, outlining a method to (1) determine relevant efficiency and variability values and then to (2) incorporate this information into downstream analyses as a way to improve the accuracy of quantitative transcriptomics experiments.
OBJECTIVES:Detection of genomic alterations in diseases can be achieved with current molecular technologies. However, the molecules extracted from formalin-fixed, paraffin-embedded (FFPE) bio-samples are often limited possibly due to DNA fragmentation and crosslinking caused by the sample fixation and processing. The study objective was to design a droplet digital PCR (ddPCR) assay to assess the quality and quantity of DNA derived from various DNA extraction conditions on FFPE samples.METHODS:We used 10 μm-thick sections from 5 FFPE oral tumoral blocks, each consisting of 10-15 sections. The protocol variables tested included: 1) tissue staining; 2) duration and 3) temperature of post-digestion heat treatment; and 4) DNA extraction method. DNA quantity was assessed using the NanoDrop 2000 (Thermo Fisher Scientific, USA), the Qubit fluorometer (Thermo Fisher Scientific, USA), and a ddPCR-based assay. DNA quality was assessed using a ddPCR assay for the degree of fragmentation and the effectiveness of removing crosslinks with varying guanine-cytosine (GC)-content.RESULTS:Deparaffinization with xylene helped to increase the DNA yield. Tissue staining (methyl green staining, pH 6) prior to microdissection, comparing to no staining, caused additional DNA fragmentation. Compared to column-based method, DNA extracted with phenol chloroform and ethanol precipitation increased the degree of fragmentation and lowered the yield of amplifiable DNA. The cross-linking derived from GC-contents may not be the only factor impacting on the DNA quality.CONCLUSIONS:Samples undergoing different pre-treatment conditions prior to extraction can impact the yield of amplifiable DNA. Our ddPCR assay can be used to assess for both DNA quantity and quality.
The quantitative real-time polymerase chain reaction (qPCR) is one of the most commonly molecular methods used today. It is central to numerous assays that have since been developed and described around its optimization. The Listeria monocytogenes prfA qPCR assay has been studied in great detail and due to its comprehensive knowledge, excellent performance (sensitivity of one single copy), and internal amplification control, it represents a suitable test platform for qPCR examinations. In this study, we compared ten different polymerases (or ready-to-use mastermixes) as possible (economic) alternatives to our gold standard Platinum Taq polymerase. We sought to determine the reproducibility of these assays under modified conditions, which are realistic because published assays are frequently used with substituted polymerases. Surprisingly, there was no amplification at all with some of the tested polymerases, even although the internal amplification control worked well. Since adaptation of the thermal profile and of MgCl2 concentration could restore amplification, simple replacement of the polymerase can destroy a well-established assay leading up to >106-fold less analytical sensitivity. Further, validation using Poisson and PCR-Stop analyses revealed limits to some assay-polymerase combinations and emphasize the importance of validation.
Amplification curves from quantitative Real-Time PCR experiments typically exhibit a sigmoidal shape. They can roughly be divided into a ground or baseline phase, an exponential amplification phase, a linear phase and finally a plateau phase, where in the latter, the PCR product concentration no longer increases. Nevertheless, in some cases the plateau phase displays a negative trend, e.g. in hydrolysis probe assays. This cycle-to-cycle fluorescence decrease is commonly referred to in the literature as the hook effect. Other detection chemistries also exhibit this negative trend, however the underlying molecular mechanisms are different. In this study we present two approaches to automatically detect hook effect-like curvatures based on linear (hookreg) and nonlinear regression (hookregNL). As the hook effect is typical for qPCR data, both algorithms can be employed for the automated identification of regular structured qPCR curves. Therefore, our algorithms streamline quality control, but can also be used for assay optimization or machine learning.
