Biomolecular Detection and Quantification最新文献

Aims

We describe the development and interlaboratory study of modified Saccharomyces cerevisiae as a candidate material to evaluate a full detection workflow including DNA extraction and quantitative polymerase chain reaction (qPCR).

Methods and results

S. cerevisiae NE095 was prepared by stable insertion of DNA sequence External RNA Control Consortium-00095 into S. cerevisiae BY4739 to convey selectivity. For the interlaboratory study, a binomial regression model was used to select three cell concentrations, high (4 × 10⁷ cells ml⁻¹), intermediate (4 × 10⁵ cells ml⁻¹) and low (4 × 10³ cells ml⁻¹), and the number of samples per concentration. Seven participants, including potential end users, had combined rates of positive qPCR detection (quantification cycle <37) of 100%, 40%, and 0% for high, intermediate, and low concentrations, respectively.

Conclusions

The NE095 strain was successfully detected by all participants, with the high concentration indicating a potential target concentration for a reference material.

Significance and impact of the study

The engineered yeast has potential to support measurement assurance for the analytical process of qPCR, encompassing the method, equipment, and operator, to increase confidence in results and better inform decision-making in areas of applied microbiology. This material can also support process assessment for other DNA-based detection technologies.

Primer and probe sequence designs are among the most critical input factors in real-time polymerase chain reaction (PCR) assay optimization. In this study, we present the use of statistical design of experiments (DOE) approach as a general guideline for probe optimization and more specifically focus on design optimization of label-free hydrolysis probes that are designated as mediator probes (MPs), which are used in reverse transcription MP PCR (RT-MP PCR). The effect of three input factors on assay performance was investigated: distance between primer and mediator probe cleavage site; dimer stability of MP and target sequence (influenza B virus); and dimer stability of the mediator and universal reporter (UR). The results indicated that the latter dimer stability had the greatest influence on assay performance, with RT-MP PCR efficiency increased by up to 10% with changes to this input factor. With an optimal design configuration, a detection limit of 3–14 target copies/10 μl reaction could be achieved. This improved detection limit was confirmed for another UR design and for a second target sequence, human metapneumovirus, with 7–11 copies/10 μl reaction detected in an optimum case. The DOE approach for improving oligonucleotide designs for real-time PCR not only produces excellent results but may also reduce the number of experiments that need to be performed, thus reducing costs and experimental times.

Beak and feather disease is caused by Circovirus, which affects actively growing beak and feather cells of avian species. The disease affects mainly young birds while older birds may overcome the disease with few lasting effects. Due to lack of treatment, the only way to control the disease is through hygiene and early diagnosis. As a diagnostic tool, we have established a Taqman probe based real-time PCR assay to detect the presence of the viral genome in psittacine birds in UAE and reported the incidence of circovirus in different species of psittacine birds. The sensitivity of our assay was found to be very high with detection limit of up to 3.5 fg of DNA in the sample. The mean prevalence of circovirus was found to be 58.33% in African Grey Parrots, 34.42% in Cockatoos, 31.8% in amazon parrots and 25.53% in Macaws.

The Taqman assay is a quick, reliable and sensitive detection method that has been instrumental in identifying this disease that was not previously reported in the region.

Integrity of the mRNA in clinical samples has major impact on the quality of measured expression levels. This is independent of the measurement technique being next generation sequencing (NGS), Quantitative real-time PCR (qPCR) or microarray profiling. If mRNA is highly degraded or damaged, measured data will be very unreliable and the whole study is likely a waste of time and money. It is therefore common strategy to test the quality of RNA in samples before conducting large and costly studies. Most methods today to assess the quality of RNA are ignorant to the nature of the RNA and, therefore, reflect the integrity of ribosomal RNA, which is the dominant species, rather than of mRNAs, microRNAs and long non-coding RNAs, which usually are the species of interest. Here, we present a novel molecular approach to assess the quality of the targeted RNA species by measuring the differential amplification (ΔAmp) of an Endogenous RNase Resistant (ERR) marker relative to a reference gene, optionally combined with the measurement of two amplicons of different lengths. The combination reveals any mRNA degradation caused by ribonucleases as well as physical, chemical or UV damage. ΔAmp has superior sensitivity to common microfluidic electrophoretic methods, senses the integrity of the actual targeted RNA species, and allows for a smoother and more cost efficient workflow.

PCR is a well-understood and established laboratory technique often used in molecular diagnostics. Huge experience has been accumulated over the last years regarding the design of PCR assays and their set-up, including in-depth troubleshooting to obtain the optimal PCR assay for each purpose. Here we report a PCR troubleshooting that came up with a surprising result never observed before. With this report we hope to sensitize the reader to this peculiar problem and to save troubleshooting efforts in similar situations, especially in time-critical and ambitious diagnostic settings.

We developed a novel PCR-based pre-amplification (PreAmp) technology that can increase the abundance of over 350 target genes one million-fold. To assess potential bias introduced by PreAmp we utilized ERCC RNA reference standards, a model system that quantifies measurement error in RNA analysis. We assessed three types of bias: amplification bias, dynamic range bias and fold-change bias. We show that our PreAmp workflow introduces only minimal amplification and fold-change bias under stringent conditions. We do detect dynamic range bias if a target gene is highly abundant and PreAmp occurred for 16 or more PCR cycles; however, this type of bias is easily correctable. To assess PreAmp bias in a gene expression profiling experiment, we analyzed a panel of genes that are regulated during differentiation using the NTera2 stem cell model system. We find that results generated using PreAmp are similar to results obtained using standard qPCR (without the pre-amplification step). Importantly, PreAmp maintains patterns of gene expression changes across samples; the same biological insights would be derived from a PreAmp experiment as with a standard gene expression profiling experiment. We conclude that our PreAmp technology can facilitate analysis of extremely limited samples in gene expression quantification experiments.

The advent of next-generation sequencing technologies had a profound impact on molecular diagnostics. PCR is a popular method for target enrichment of disease gene panels. Using our proprietary primer-design pipeline, primerXL, we have created almost one million assays covering over 98% of the human exome. Here we describe the assay specification and both in silico and wet-lab validation of a selected set of 2294 assays using both next-generation sequencing and Sanger sequencing. Using a universal PCR protocol without optimization, these assays result in high coverage uniformity and limited non-specific coverage. In addition, data indicates a positive correlation between the predictive in silico specificity score and the amount of assay non-specific coverage.

The precision and reliability of quantitative nucleic acid analysis depends on the quality of the sample analyzed and the integrity of the nucleic acids. The integrity of RNA is currently primarily assessed by the analysis of ribosomal RNA, which is the by far dominant species. The extrapolation of these results to mRNAs and microRNAs, which are structurally quite different, is questionable. Here we show that ribosomal and some nucleolar and mitochondrial RNAs, are highly resistant to naturally occurring post-mortem degradation, while mRNAs, although showing substantial internal variability, are generally much more prone to nucleolytic degradation. In contrast, all types of RNA show the same sensitivity to heat. Using qPCR assays targeting different regions of mRNA molecules, we find no support for 5′ or 3′ preferentiality upon post-mortem degradation.

The purpose of the study was to explore the feasibility of a protocol for the isolation and molecular characterization of single circulating tumor cells (CTCs) from cancer patients using a single-cell next generation sequencing (NGS) approach.

To reach this goal we used as a model an artificial sample obtained by spiking a breast cancer cell line (MDA-MB-231) into the blood of a healthy donor.

Tumor cells were enriched and enumerated by CellSearch^® and subsequently isolated by DEPArray™ to obtain single or pooled pure samples to be submitted to the analysis of the mutational status of multiple genes involved in cancer.

Upon whole genome amplification, samples were analysed by NGS on the Ion Torrent PGM™ system (Life Technologies) using the Ion AmpliSeq™ Cancer Hotspot Panel v2 (Life Technologies), designed to investigate genomic “hot spot” regions of 50 oncogenes and tumor suppressor genes.

We successfully sequenced five single cells, a pool of 5 cells and DNA from a cellular pellet of the same cell line with a mean depth of the sequencing reaction ranging from 1581 to 3479 reads.

We found 27 sequence variants in 18 genes, 15 of which already reported in the COSMIC or dbSNP databases. We confirmed the presence of two somatic mutations, in the BRAF and TP53 gene, which had been already reported for this cells line, but also found new mutations and single nucleotide polymorphisms. Three variants were common to all the analysed samples, while 18 were present only in a single cell suggesting a high heterogeneity within the same cell line.

This paper presents an optimized workflow for the molecular characterization of multiple genes in single cells by NGS. The described pipeline can be easily transferred to the study of single CTCs from oncologic patients.

Background

Clinical implementation of Next-Generation Sequencing (NGS) is challenged by poor control for stochastic sampling, library preparation biases and qualitative sequencing error. To address these challenges we developed and tested two hypotheses.

Methods

Hypothesis 1: Analytical variation in quantification is predicted by stochastic sampling effects at input of (a) amplifiable nucleic acid target molecules into the library preparation, (b) amplicons from library into sequencer, or (c) both. We derived equations using Monte Carlo simulation to predict assay coefficient of variation (CV) based on these three working models and tested them against NGS data from specimens with well characterized molecule inputs and sequence counts prepared using competitive multiplex-PCR amplicon-based NGS library preparation method comprising synthetic internal standards (IS). Hypothesis 2: Frequencies of technically-derived qualitative sequencing errors (i.e., base substitution, insertion and deletion) observed at each base position in each target native template (NT) are concordant with those observed in respective competitive synthetic IS present in the same reaction. We measured error frequencies at each base position within amplicons from each of 30 target NT, then tested whether they correspond to those within the 30 respective IS.

Results

For hypothesis 1, the Monte Carlo model derived from both sampling events best predicted CV and explained 74% of observed assay variance. For hypothesis 2, observed frequency and type of sequence variation at each base position within each IS was concordant with that observed in respective NTs (R² = 0.93).

Conclusion

In targeted NGS, synthetic competitive IS control for stochastic sampling at input of both target into library preparation and of target library product into sequencer, and control for qualitative errors generated during library preparation and sequencing. These controls enable accurate clinical diagnostic reporting of confidence limits and limit of detection for copy number measurement, and of frequency for each actionable mutation.