Biomolecular Detection and Quantification最新文献

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.

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 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.

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.

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 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(N₀), where N₀ is the initial number of target molecules. The location of C_q for the unknown on this line then yields its N₀. 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. 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(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.

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.

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.