Absolute Copy Number from the Statistics of the Quantification Cycle in Replicate Quantitative Polymerase Chain Reaction Experiments

Reducing Bias and Quantifying Uncertainty in Fluorescence Produced by PCR

We present a new approach for relating nucleic-acid content to fluorescence in a real-time Polymerase Chain Reaction (PCR) assay. By coupling a two-type branching process for PCR with a fluorescence analog of Beer's Law, the approach reduces bias and quantifies uncertainty in fluorescence. As the two-type branching process distinguishes between complementary strands of DNA, it allows for a stoichiometric description of reactions between fluorescent probes and DNA and can capture the initial conditions encountered in assays targeting RNA. Analysis of the expected copy-number identifies additional dynamics that occur at short times (or, equivalently, low cycle numbers), while investigation of the variance reveals the contributions from liquid volume transfer, imperfect amplification, and strand-specific amplification (i.e., if one strand is synthesized more efficiently than its complement). Linking the branching process to fluorescence by the Beer's Law analog allows for an a priori description of background fluorescence. It also enables uncertainty quantification (UQ) in fluorescence which, in turn, leads to analytical relationships between amplification efficiency (probability) and limit of detection. This work sets the stage for UQ-PCR, where both the input copy-number and its uncertainty are quantified from fluorescence kinetics.

Magnetic Bead Processing Enables Sensitive Ligation-Based Detection of HIV Drug Resistance Mutations

HIV develops single nucleotide polymorphisms (SNPs), some of which lead to drug resistance mutations (DRMs) that prevent therapeutic viral suppression. Genomic sequencing enables healthcare professionals to select effective combination antiretroviral therapy (ART) to achieve and maintain viral suppression. However, sequencing technologies, which are resource-intensive, are limited in their availability. This report describes the first step toward a highly specific ligation-based SNP discrimination method with endpoint PCR detection, which is more suitable for resource-limited clinics. The approach is based on magnetic bead processing to maximize reaction product transfer and minimize the carryover of incompatible buffer for three consecutive enzymatic reactions─reverse transcription (RT), oligonucleotide ligation assay (OLA), and PCR. The method improved PCR detection following RT → OLA by 8.06 cycles (∼250-fold) compared to direct pipette processing and detected between 103 and 104 RNA copies per reaction. In studies with synthesized nucleic acids based on the well-studied HIV mutation, K103N, the assay successfully differentiated between wild-type and mutant for RNA targets with high specificity. With further development, this design provides a pathway for SNP detection with more accessible PCR instrumentation and is a step toward a self-contained processing approach that incorporates the SNP specificity of the ligation reaction for more effective clinical management of DRMs in resource-constrained settings.

Considerations for Group Testing: A Practical Approach for the Clinical Laboratory

Group testing, also known as pooled sample testing, was first proposed by Robert Dorfman in 1943. While sample pooling has been widely practiced in blood-banking, it is traditionally seen as anathema for clinical laboratories. However, the ongoing COVID-19 pandemic has re-ignited interest for group testing among clinical laboratories to mitigate supply shortages. We propose five criteria to assess the suitability of an analyte for pooled sample testing in general and outline a practical approach that a clinical laboratory may use to implement pooled testing for SARS-CoV-2 PCR testing. The five criteria we propose are: (1) the analyte concentrations in the diseased persons should be at least one order of magnitude (10 times) higher than in healthy persons; (2) sample dilution should not overly reduce clinical sensitivity; (3) the current prevalence must be sufficiently low for the number of samples pooled for the specific protocol; (4) there is no requirement for a fast turnaround time; and (5) there is an imperative need for resource rationing to maximise public health outcomes. The five key steps we suggest for a successful implementation are: (1) determination of when pooling takes place (pre-pre analytical, pre-analytical, analytical); (2) validation of the pooling protocol; (3) ensuring an adequate infrastructure and archival system; (4) configuration of the laboratory information system; and (5) staff training. While pool testing is not a panacea to overcome reagent shortage, it may allow broader access to testing but at the cost of reduction in sensitivity and increased turnaround time.

qPCR data analysis: Better results through iconoclasm

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 (C_q ) are fitted to a straight-line function of log(N ₀), where N ₀ is the initial number of target molecules. The location of C_q for the unknown on this line then yields its N ₀. The most widely used definition for C_q 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 (C_r ) avoid this problem. We describe improved methods for estimating these and other C_q markers and their standard errors, from a nonlinear algorithm that fits growth profiles to a 4-parameter log-logistic function plus a baseline function. Further, by examining six multidilution, multireplicate qPCR data sets, we find that nonlinear expressions are often preferred statistically for the dependence of C_q on log(N ₀). This means that the amplification efficiency E depends on N ₀, 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 N ₀. 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.

Savitzky-Golay smoothing and differentiation for polymerase chain reaction quantification

In quantitative PCR (qPCR), replicates can minimize the impact of intra-assay variation; however, inter-assay variations must be minimized to obtain a robust quantification method. The method proposed in this study uses Savitzky-Golay smoothing and differentiation (SGSD) to identify a derivative-maximum-based cycle of quantification. It does not rely on curve modeling, as is the case with many existing techniques. PCR fluorescence data sets challenged for inter-assay variations (different thermocycler units, different reagents batches, different operators, different standard curves, and different labs) were used for the evaluation. The algorithm was compared with a four-parameter logistic model (4PLM) method, the C_y0 method, and the threshold method. The SGSD method compared favourably with all methods in terms of inter-assay variation. SGSD was statistically different from the 4PLM (P = 0.03), C_y0 (P = 0.05), and threshold (P = 0.004) methods on relative error comparison basis. For intra-assay variations, SGSD outperformed the threshold method (P = 0.005) and equalled the 4PLM and C_y0 methods (P > 0.05) on relative error basis. Our results demonstrate that the SGSD method could potentially be an alternative to sigmoid modeling based methods (4PLM and C_y0) when PCR data are challenged for inter-assay variations.

Methods to determine limit of detection and limit of quantification in quantitative real-time PCR (qPCR)

Quantitative Real-Time Polymerase Chain Reaction, better known as qPCR, is the most sensitive and specific technique we have for the detection of nucleic acids. Even though it has been around for more than 30 years and is preferred in research applications, it has yet to win broad acceptance in routine practice. This requires a means to unambiguously assess the performance of specific qPCR analyses. Here we present methods to determine the limit of detection (LoD) and the limit of quantification (LoQ) as applicable to qPCR. These are based on standard statistical methods as recommended by regulatory bodies adapted to qPCR and complemented with a novel approach to estimate the precision of LoD.

Adaptive PCR Based on Hybridization Sensing of Mirror-Image l-DNA

Polymerase chain reaction (PCR) is dependent on two key hybridization events during each cycle of amplification, primer annealing and product melting. To ensure that these hybridization events occur, current PCR approaches rely on temperature set points and reaction contents that are optimized and maintained using rigid thermal cycling programs and stringent sample preparation procedures. This report describes a fundamentally simpler and more robust PCR design that dynamically controls thermal cycling by more directly monitoring the two key hybridization events during the reaction. This is achieved by optically sensing the annealing and melting of mirror-image l-DNA analogs of the reaction's primers and targets. Because the properties of l-DNA enantiomers parallel those of natural d-DNAs, the l-DNA reagents indicate the cycling conditions required for effective primer annealing and product melting during each cycle without interfering with the reaction. This hybridization-sensing approach adapts in real time to variations in reaction contents and conditions that impact primer annealing and product melting and eliminates the requirement for thermal calibrations and cycling programs. Adaptive PCR is demonstrated to amplify DNA targets with high efficiency and specificity under both controlled conditions and conditions that are known to cause traditional PCR to fail. The advantages of this approach promise to make PCR-based nucleic acid analysis simpler, more robust, and more accessible outside of well-controlled laboratory settings.

System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation

Real-time quantitative polymerase chain reaction (qPCR) data are found to display periodic patterns in the fluorescence intensity as a function of sample number for fixed cycle number. This behavior is seen for technical replicate datasets recorded on several different commercial instruments; it occurs in the baseline region and typically increases with increasing cycle number in the growth and plateau regions. Autocorrelation analysis reveals periodicities of 12 for 96-well systems and 24 for a 384-well system, indicating a correlation with block architecture. Passive dye experiments show that the effect may be from optical detector bias. Importantly, the signal periodicity manifests as periodicity in quantification cycle (C_q) values when these are estimated by the widely applied fixed threshold approach, but not when scale-insensitive markers like first- and second-derivative maxima are used. Accordingly, any scale variability in the growth curves will lead to bias in constant-threshold-based C_qs, making it mandatory that workers should either use scale-insensitive C_qs or normalize their growth curves to constant amplitude before applying the constant threshold method.

Advances in digital polymerase chain reaction (dPCR) and its emerging biomedical applications

Since the invention of polymerase chain reaction (PCR) in 1985, PCR has played a significant role in molecular diagnostics for genetic diseases, pathogens, oncogenes and forensic identification. In the past three decades, PCR has evolved from end-point PCR, through real-time PCR, to its current version, which is the absolute quantitive digital PCR (dPCR). In this review, we first discuss the principles of all key steps of dPCR, i.e., sample dispersion, amplification, and quantification, covering commercialized apparatuses and other devices still under lab development. We highlight the advantages and disadvantages of different technologies based on these steps, and discuss the emerging biomedical applications of dPCR. Finally, we provide a glimpse of the existing challenges and future perspectives for dPCR.

Isolation and gene expression analysis of single potential human spermatogonial stem cells

STUDY HYPOTHESIS

It is possible to isolate pure populations of single potential human spermatogonial stem cells without somatic contamination for down-stream applications, for example cell culture and gene expression analysis.

STUDY FINDING

We isolated pure populations of single potential human spermatogonial stem cells (hSSC) without contaminating somatic cells and analyzed gene expression of these cells via single-cell real-time RT-PCR.

WHAT IS KNOWN ALREADY

The isolation of a pure hSSC fraction could enable clinical applications such as fertility preservation for prepubertal boys and in vitro-spermatogenesis. By utilizing largely nonspecific markers for the isolation of spermatogonia (SPG) and hSSC, previously published cell selection methods are not able to deliver pure target cell populations without contamination by testicular somatic cells. However, uniform cell populations free of somatic cells are necessary to guarantee defined growth conditions in cell culture experiments and to prevent unintended stem cell differentiation. Fibroblast growth factor receptor 3 (FGFR3) is a cell surface protein of human undifferentiated A-type SPG and a promising candidate marker for hSSC. It is exclusively expressed in small, non-proliferating subgroups of this spermatogonial cell type together with the pluripotency-associated protein and spermatogonial nuclear marker undifferentiated embryonic cell transcription factor 1 (UTF1).

STUDY DESIGN, SAMPLES/MATERIALS, METHODS

We specifically selected the FGFR3-positive spermatogonial subpopulation from two 30 mg biopsies per patient from a total of 37 patients with full spermatogenesis and three patients with meiotic arrest. We then employed cell selection with magnetic beads in combination with a fluorescence-activated cell sorter antibody directed against human FGFR3 to tag and visually identify human FGFR3-positive spermatogonia. Positively selected and bead-labeled cells were subsequently picked with a micromanipulator. Analysis of the isolated cells was carried out by single-cell real-time RT-PCR, real-time RT-PCR, immunocytochemistry and live/dead staining.

MAIN RESULTS AND THE ROLE OF CHANCE

Single-cell real-time RT-PCR and real-time RT-PCR of pooled cells indicate that bead-labeled single cells express FGFR3 with high heterogeneity at the mRNA level, while bead-unlabeled cells lack FGFR3 mRNA. Furthermore, isolated cells exhibit strong immunocytochemical staining for the stem cell factor UTF1 and are viable.

LIMITATIONS, REASONS FOR CAUTION

The cell population isolated in this study has to be tested for their potential stem cell characteristics via xenotransplantation. Due to the small amount of the isolated cells, propagation by cell culture will be essential. Other potential hSSC without FGFR3 surface expression will not be captured with the provided experimental design.

WIDER IMPLICATIONS OF THE FINDINGS

The technical approach as developed in this work could encourage the scientific community to test other established or novel hSSC markers on single SPG that present with potential stem cell-like features.

STUDY FUNDING AND COMPETING INTERESTS

The project was funded by the DFG Research Unit FOR1041 Germ cell potential (SCH 587/3-2) and DFG grants to K.v.K. (KO 4769/2-1) and A.-N.S. (SP 721/4-1). The authors declare no competing interests.

Novel electrochemical redox-active species: one-step synthesis of polyaniline derivative-Au/Pd and its application for multiplexed immunoassay

Electrochemical redox-active species play crucial role in electrochemically multiplexed immunoassays. A one-pot method for synthesizing four kinds of new electrochemical redox-active species was reported using HAuCl4 and Na2PdCl4 as dual oxidating agents and aniline derivatives as monomers. The synthesized polyaniline derivative-Au/Pd composites, namely poly(N-methyl-o-benzenediamine)-Au/Pd, poly(N-phenyl-o-phenylenediamine)-Au/Pd, poly(N-phenyl-p-phenylenediamine)-Au/Pd and poly(3,3',5,5'-tetramethylbenzidine)-Au/Pd, exhibited electrochemical redox activity at -0.65 V, -0.3 V, 0.12 V, and 0.5 V, respectively. Meanwhile, these composites showed high H2O2 electrocatalytic activity because of the presence of Au/Pd. The as-prepared composites were used as electrochemical immunoprobes in simultaneous detection of four tumor biomarkers (carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA199), carbohydrate antigen 72-4 (CA724), and alpha fetoprotein (AFP)). This immunoassay shed light on potential applications in simultaneous gastric cancer (related biomarkers: CEA, CA199, CA724) and liver cancer diagnosis (related biomarkers: CEA, CA199, AFP). The present strategy to the synthesize redox species could be easily extended to other polymers such as polypyrrole derivatives and polythiophene derivatives. This would be of great significance in the electrochemical detection of more analytes.

Quantitative large scale gene expression profiling from human stem cell culture micro samples using multiplex pre-amplification

Transcriptional profiling is a powerful tool to study biological mechanisms during stem cell differentiation and reprogramming. Genome-wide methods like microarrays or next generation sequencing are expensive, time consuming, and require special equipment and bioinformatics expertise. Quantitative RT-PCR remains one of today's most widely accepted and used methods for analyzing gene expression in biological samples. However, limitations in the amount of starting materials often hinder the quantity and quality of information that could be obtained from a given sample. Here, we present a fast 4-step workflow allowing direct, column-free RNA isolation from limited human pluripotent stem cell (hPSC) cultures that is directly compatible with subsequent reverse transcription, target specific multiplex pre-amplification, and standard SYBR-Green quantitative PCR (qPCR) analysis. The workflow delivers excellent correlations in normalized gene-expression data obtained from different samples of hPSCs over a wide range of cell numbers (500-50,000 cells). We demonstrate accurate and unbiased target gene quantification in limiting stem cell cultures which allows for monitoring embryoid body differentiation and induced pluripotent stem cell (iPSC) reprogramming. This method highlights a rapid and cost effective screening process, allowing reduction of culture formats and increase of processing throughputs for various stem cell applications.