Klemen Zupancic1, Misa Korva2, Tatjana Avsic Zupanc2, Urska Cepin3, Manca Pirc3, Laura Simdon4 Matjaz Hren 1,3,*,
1 SCINOTE, LLC, USA
2 Institute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Slovenia
3 BioSistemika, d.o.o., Slovenia
4 Gilson, Inc., USA
Automation has significantly improved human diagnostics in the developed world by increasing patient throughput and decreasing diagnostic variability caused by human interaction. The outbreak and expansion of Zika virus (ZIKV) has increased the need for rapid and reliable diagnostics in the early stages of infection and for virus quantification in clinical studies. Real time PCR (qPCR) has been found to be the most sensitive, specific and rapid detection system for ZIKV detection.
Our study addressed automation of qPCR plate setup for ZIKV detection and quantification which includes management of sam- ples, preparation of sample dilutions, preparation of master mix and their application to the qPCR plate. This was compared to manual qPCR setup which was performed by an experienced lab diagnostician.
In this study samples were tested from five human patients with suspicion on ZIKV infection that were sent for routine diagnostics of ZIKV to the Institute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Slovenia (IMI). RNA was iso- lated from different tissues or fluids including fetus brain, blood, semen, plasma, or urine. Additionally, for an absolute quantifica- tion study, six different ZIKV strains maintained in cell culture lines were analysed. Necessary controls were included in every step of the process. The same samples were used for manual and auto- mated qPCR experiments on the same day.
The automated setup included management of samples in sciNote Open Source Electronic Lab Notebook while sample dilu- tions, master mix preparation and qPCR plate setup was done by using Gilson qPCR Assistant with PIPETMAX® 268 automated pipet- ting workstation (PIPETMAX®).
Analysis of the qPCR data revealed that the accuracy of perfor- mance of automated qPCR plate setup was comparable to manual setup done by a very experienced lab diagnostician while the speed of the setup was improved by automating the sample import, sam- ple dilutions and qPCR plate setup.
Incorporating an automation platform into the diagnostic pro- tocol allows for accurate standard dilution and assay setup with a significant increase in throughput compared to manual processing. Moreover, integration of data management software with an automation system further increases the throughput and reduces the possibility of user error. More importantly, data management software, such as sciNote, enables full traceability of samples and results which is critical for accuracy in human diagnostics.
Jan M. Ruijter 1, *, Maurice W.J. de Ronde2, Antoni Bayes Genis3, Yigal Pinto4, Sara-Joan Pinto 2
1 Anatomy, Embryology and Physiology, Academic Medical Center, Amsterdam, the Netherlands
2 Vascular Medicine & Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, Amsterdam, the Netherlands
3 Heart Failure Unit, Germans Trias i Pujol Hospital, Universitat Autònoma, Barcelona, Spain
4 Experimental Cardiology, Academic Medical Center, Amsterdam, the Netherlands
In the analysis of qPCR data, the criterion for reproducibility between replicate reactions is set to 0.5 cycles; when the Cq values of replicates differ more than 0.5, the results are often discarded. The idea is that this rule-of-thumb should be enforced to protect against the inclusion of technical variation in the analysis of the qPCR results. However, a technical pipetting error of 15% is required to reach a 0.5 cycles difference. Smaller technical errors are already unacceptably large but would go unnoticed and be tolerated. On the other hand, at high Cq values the sampling error that occurs when pipetting a low number of target molecules into the PCR plate is governed by the Poisson distribution. To calculate the magnitude of this sampling error for different Cq values, we started with the assumption that for a PCR efficiency of about 1.8, an input of 10 copies of target leads to a Cq value of about 35 when the primer and amplicon concentration become similar. The observed Cq value will depend on the actual PCR efficiency, the monitoring chemistry, the (pre-) processing of the fluorescence data and the way the Cq value is determined. When the PCR reaction reaches the quantification threshold the general kinetic equation can be written as
Nq = NEqC (1) which with the above assumption is equal to
Nq = 10E35 (2)
This equality provides us with an equation to estimate the target input from the observed Cq value and PCR efficiency:
Nq = 10E35-C (3) q
Using the relationship between Poisson and Chi2 distributions the 95% confidence interval of N is then given by:
0.5 20.025;2N ≤ N ≤ 0.5 20.975;2N+2 (4)
For each Cq and PCR efficiency value we can thus calculate a number of copies with Eq. (3), the sampling error range with Eq. (4) and then, with the inverse of Eq. (1), the expected range of Cq values due to unavoidable sampling variation. This range increases with higher Cq values (less target) and easily leads to a replicate variation above 0.5 cycles. Discarding such discordant replicates will lead to bias and loss of power in the analysis. For a dataset that resulted from the qPCR measurement of 12 miRNA targets in 834 patients with a total of 20,016 reactions, the strict application of the rule that the Cq values of replicates should be within 0.5 cycles led to rejection of 7752 (39%) measurements. When the unavoidable Cq range, calculated as described above, is used to determine which Cq difference between replicates should lead to the decision that the replicate discordance is still acceptable, the number of reac- tions that should be discarded decreases to 1414 (7%). Not only less reactions are discarded, also the distribution of Cq values changes showing that strict application of the Cq < 0.5 cycle rule has led to bias in the results of the qPCR experiment. A decision to exclude replicate reactions based on the expected sampling error avoids this bias, prevents unwanted loss of data and therefore increases the statistical power.
Real-time fluorescence-dependent quantitative PCR, with or without a preceding reverse transcription (RT) step, has long been embraced as a valuable and valid means for quantifying nucleic acids. Its results are widely used to report molecular biomarkers of disease, quantify changes to RNA levels in cells or biopsies and iden- tify the tissue of origin from deposits on forensic samples. Clearly, qPCR has an important and effective use for detecting pathogens, SNPs or other DNA-associated applications. However, this accep- tance for RNA is remarkable, given the numerous reports that have emerged over the last twenty years or so that should cast significant doubts on how reliable RT-qPCR data really are. Whilst RT-qPCR can undoubtedly be used to distinguish fairly large differences or changes in nucleic acid levels, the majority of conclusions are based on results that report small changes that are neither robust nor con- sistent. This raises the far-reaching question of whether it is time to abandon RT-qPCR as a method for quantifying RNAs and replace it with more accurate and less error-prone digital PCR technology.
Lukas Valihrach 1, Peter Androvic1, Julie Elling2, Robert Sjoback2, Mikael Kubista1,2
1 Institute of Biotechnology AS CR, Czech Republic
2 TATAA Biocenter AB, Sweden
MicroRNAs are a class of small non-coding RNAs that serve as important regulators of gene expression at the posttranscriptional level. MiRNAs are stable in body fluids and pose great potential to serve as biomarkers. Here, we present a highly specific, sensi- tive and cost-effective system to quantify miRNA expression based on two-step RT-qPCR with SYBR-green detection chemistry called Two-tailed RT-qPCR. It takes advantage of novel, target-specific primers for reverse transcription composed of two hemiprobes complementary to two different parts of the targeted miRNA, connected by a hairpin structure. The introduction of a second probe ensures high sensitivity and enables discrimination of highly homologous miRNAs irrespectively of the position of the mis- matched nucleotide. Two-tailed RT-qPCR has a dynamic range of 8 logs and a sensitivity sufficient to detect down to a hun- dred of target miRNA molecules. It is capable to capture the full isomiR repertoire, leading to accurate representation of the com- plete miRNA content in a sample. The reverse transcription step can be multiplexed and the miRNA profiles measured with Two-tailed RT-qPCR show excellent correlation with the industry standard TaqMan miRNA assays (R2 = 0.985). Moreover, Two-tailed RT-qPCR allows for rapid testing with a total analysis time of less than 2.5 hours.
For some time now, Bioline has offered an extensive list of indi- vidual human miRNAs, using the proprietary algorithm developed by MiRXES to maximize miRNA detection sensitivity, while mini- mizing non-specific interactions. The versatility of the assay design system has now allowed us to extend the range to include all the 27,000 miRNA listed on miRBase, providing plant and animal miRNA assays. The resulting real-time PCR assays enable detec- tion of extremely low levels of miRNA with high specificity using a SYBR® Green detection chemistry, allowing the discrimination between closely related miRNA sequences. All EPIK miRNA Select Assays have been validated using synthetic miRNA templates and human assays have also been validated against total RNA. Typically the assays detect as few as 100 copies of template per RT reaction with excellent assay efficiency and linearity. We will also dis- cuss the appropriate uses of positive controls to normalize results between assays and between experiments, and how the EPIK RNA Spike-In controls can be used to build an accurate picture of the relative concentration of miRNA in a sample. These controls can be particularly effective in addressing complex biological problems such as the abundance of miRNA in exosomes from human blood.
RNA revolution has turned non-coding RNAs (ncRNAs) from dark-matter into a biological research hotspot. ncRNA families, such as microRNAs (miRNAs) and more recently, long non cod- ing RNAs (lncRNAs) are being researched for physiological and pathological implications. The role of miRNAs in development and diseasehas been widely reported during the past few years.
During the talk tools from the DIANA suite of miRNA analysis (microrna.gr) will be presented that can be used as basic step for the identification of miRNA biomarkers.
Such tools and databases include miRNA target prediction (DIANA micro-T) and annotation (TarBase, LNCBase), pathway analy- sis (DIANA–mirPath), regulation of microRNAs (miRGEN) and the use of RNAseq data for the identification of key regulatory components (miRNA and/or Transcription factors) based on two investigated stages (DIANA- mirExTra). The DIANA suite is widely used with more than 100,000 unique users per year from all over the world.
One of the major challenges towards an improved treatment of human diseases is the identification of appropriate prognostic and diagnostic markers. During the past decade, microRNA (miRNA) activity has been associated with the control of a wide range of cel- lular processes. Importantly, it has been shown that dysfunctional expression of specific miRNAs is associated with the development of a variety of diseases in human. However, the inherent difficul- ties associated to the collection of diseased material from patients has severely limited the investigation of cellular miRNAs as source for disease-related biomarker. Remarkably, the discovery of popu- lations of cell-free miRNAs circulating in the blood of healthy as well as diseased individuals, have raised the possibility to iden- tify specific signature reflecting clinical manifestation of diseases. Although two different sub-populations of circulating miRNAs exist, we will specifically focus on the clinical utility, isolation, and detection of extracellular vesicles-associated miRNAs. Extra- cellular vesicles (EVs) are a heterogeneous group of nano-sized particles, which play a key role in inter-cellular communication and signaling. EVs are secreted by most, if not all, cell types composing the organism. Compelling evidences indicate that both the quan- titative and qualitative composition of EVs may correlate with the diseased state of the patient. However, application of experimental protocols to the clinical setting is a challenge, requiring the estab- lishment of easy to use, affordable and robust methodologies. Here, implementation of experimental pipelines required for the isola- tion and analysis of EVs and EVs-associated miRNAs from patients’ serum in the context of diagnostic laboratories will be presented and discussed.
For RNA to fulfil its essential function within the cellular environment, numerous chemical modifications have evolved to sculpt its physical and functional interactions. Although more than hundred types of RNA modifications have built the descriptive foundation of what is referred to as the epitranscriptome, their mode of action remains largely unknown. I will present our results on the function of chemical RNA modifications at the intersection of small RNA silencing pathways and general RNA metabolism.
Uridylation of RNA species represents an emerging theme in post-transcriptional gene regulation. In the microRNA pathway, such modifications regulate small RNA biogenesis and stability in plants, worms, and mammals. We identified the first RNA- specific uridylytransferase that is required for the majority of 3′ end modifications of microRNAs in Drosophila and predominantly tar- gets precursor hairpins. Uridylation modulates the characteristic two-nucleotide 3′ overhang of microRNA hairpins, which regu- lates processing by Dicer and destabilizes RNA hairpins. Tailor preferentially uridylates mirtron hairpins, thereby impeding the production of non-canonical microRNAs. Mirtron selectivity is explained by primary sequence specificity of Tailor, selecting substrates ending with a 3′ guanosine. In contrast to mirtrons, con- served Drosophila precursor microRNAs are significantly depleted in 3′ guanosine, thereby escaping regulatory uridylation. Our data support the hypothesis that evolutionary adaptation to Tailor-directed uridylation shapes the nucleotide composition of precursor microRNA 3′ ends. Hence, hairpin uridylation may serve as a barrier for the de novo creation of microRNAs in Drosophila. Our data also provide an atlas of post-transcriptional modifications in small RNAs and their precursors in flies, providing a framework for understanding the epitranscriptomic regulation of small RNA biogenesis and function.
We could also show that uridylation in flies triggers the pro- cessive 3′-to-5′ exoribonucleolytic decay via the ribonuclease II/R enzyme CG16940, a homolog of the human Perlman syn- drome exoribonuclease Dis3l2. Together with the TUTase Tailor, dmDis3l2 forms a stable cytoplasmic uridylation-triggered RNA processing (TRUMP) complex, that functionally cooperates in the degradation of structured RNAs in vitro, providing a molecular explanation for the inhibition of mirtron maturation in flies. RNA- immunoprecipitation and high-throughput sequencing reveals a variety of TRUMP complex substrates, including long non-coding RNA, such as rRNA, the essential RNase MRP and the signal recogni- tion particle RNA 7SL. Together with high-throughput biochemical characterization of dmDis3l2 and bacterial RNase R our results imply a conserved molecular function of RNase II/R enzymes as ‘readers’ of destabilizing post-transcriptional marks–uridylation in eukaryotes and adenylation in prokaryotes–that play important roles in non-coding RNA surveillance.
Benedikt Kirchner, Ming Wu, Dominik Buschmann, Michael W. Pfaffl*,
Animal Physiology & Immunology, TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany
Recent studies have proven that microvesicles are a valuable source of biomarkers in a number of physiological and pathophy- siological states. The molecular content of exosomes (and other vesicles) and their miRNA cargo in particular can act as a unique ‘biomarker signature’ and help identifying releasing cells and their circumstances.
While knowledge of the extensive target repertoire of individual miRNAs greatly expanded our understanding of miRNA functions, the high resolution down to single nucleotide alterations enabled by small-RNA sequencing technologies added an entire new layer of complexity by detecting a great abundance of miRNA isoforms. These isomiRs show significant sequence and length heterogeneity, generated by base exchanges from the canonical sequence, and/or additions and/or deletions at the 3′ or 5′ end. The quantified isomiRs can change the mRNA targeting behaviour, either subtly through supplementary or complementary binding at the 3′ end, or drasti- cally by altering the seed sequence at the 5′ end. By taking these target gene shifts into account and using a consensus of predicted genes that reflects actual miRNA sequence distribution and binding efficiencies, the accuracy of predicted pathways and related dis- eases is greatly improved. To realize this approach we implement these ideas in a ‘bioinformatical pipeline’ which analyses the small RNA sequencing read data files in a fully automatic way.
The assessment of mRNA targets can help discern the phys- iological relevance of identified miRNA biomarkers and even uncover novel relationships. We apply this ‘analysis pipeline’ to discover new integrative mRNA/miRNA regulation pattern in agri- veterinary research and to predict new ‘miR biomarker signatures’ in human clinical diagnostics.
Until recently, it was believed that only a small fraction of the genome contained relevant information, used by the cell to pro- duce proteins. The majority was referred to as ‘junk DNA’ with no obvious function throughout life. The introduction of mas- sively parallel RNA-sequencing technology has drastically changed that view. Today, there’s ample evidence demonstrating that the majority of the genome is transcribed, producing non-coding RNA (ncRNA) transcripts that differ in size, shape, expression and func- tion. The bulk of the non-coding transcriptome consists of so-called long non-coding RNAs (lncRNAs). These lncRNAs are character- ized by an exquisite tissue-specificity of lncRNAs which makes them extremely attractive as targets for therapeutic intervention or biomarkers for disease diagnosis and treatment response moni- toring.