Five years MIQE guidelines: The case of the Arabian countries

The quantitative real time polymerase chain reaction (qPCR) has become a key molecular enabling technology with an immense range of research, clinical, forensic as well as diagnostic applications. Its relatively moderate instrumentation and reagent requirements have led to its adoption by numerous laboratories, including those located in the Arabian world, where qPCR, which targets DNA, and reverse transcription qPCR (RT-qPCR), which targets RNA, are widely used for region-specific biotechnology, agricultural and human genetic studies. However, it has become increasingly apparent that there are significant problems with both the quality of qPCR-based data as well as the transparency of reporting. This realisation led to the publication of the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines in 2009 and their more widespread adoption in the last couple of years. An analysis of the performance of biomedical research in the Arabian world between 2001-2005 suggests that the Arabian world is producing fewer biomedical publications of lower quality than other Middle Eastern countries. Hence we have analysed specifically the quality of RT-qPCR-based peer-reviewed papers published since 2009 from Arabian researchers using a bespoke iOS/Android app developed by one of the authors. Our results show that compliance with 15 essential MIQE criteria was low (median of 40%, range 0-93%) and few details on RNA quality controls (22% compliance), assays design (12%), RT strategies (32%), amplification efficiencies (30%) and the normalisation process (3%). These data indicate that one of the reasons for the poor performance of Arabian world biomedical research may be the low standard of any supporting qPCR experiments and identify which aspects of qPCR experiments require significant improvements

A MIQE-Compliant Real-Time PCR Assay for Aspergillus Detection

PMCID: PMC3393739This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

RT-qPCR Diagnostics: The “Drosten” SARS-CoV-2 Assay Paradigm

The reverse transcription quantitative polymerase chain reaction (RT-qPCR) is an established tool for the diagnosis of RNA pathogens. Its potential for automation has caused it to be used as a presence/absence diagnostic tool even when RNA quantification is not required. This technology has been pushed to the forefront of public awareness by the COVID-19 pandemic, as its global application has enabled rapid and analytically sensitive mass testing, with the first assays targeting three viral genes published within days of the publication of the SARS-CoV-2 genomic sequence. One of those, targeting the RNA-dependent RNA polymerase gene, has been heavily criticised for supposed scientific flaws at the molecular and methodological level, and this criticism has been extrapolated to doubts about the validity of RT-qPCR for COVID-19 testing in general. We have analysed this assay in detail, and our findings reveal some limitations but also highlight the robustness of the RT-qPCR methodology for SARS-CoV-2 detection. Nevertheless, whilst our data show that some errors can be tolerated, it is always prudent to confirm that the primer and probe sequences complement their intended target, since, when errors do occur, they may result in a reduction in the analytical sensitivity. However, in this case, it is unlikely that a mismatch will result in poor specificity or a significant number of false-positive SARS-CoV-2 diagnoses, especially as this is routinely checked by diagnostic laboratories as part of their quality assurance

Analysis of Devonian Black Shales in Kentucky for Potential Carbon Dioxide Sequestration and Enhanced Natural Gas Production

Carbonaceous (black) Devonian gas shales underlie approximately two-thirds of Kentucky. In these shales, natural gas occurs in the intergranular and fracture porosity and is adsorbed on clay and kerogen surfaces. This is analogous to methane storage in coal beds, where CO2 is preferentially adsorbed, displacing methane. Black shales may similarly desorb methane in the presence of CO2. Drill cuttings from the Kentucky Geological Survey Well Sample and Core Library were sampled to determine both CO2 and CH4 adsorption isotherms. Sidewall core samples were acquired to investigate CO2 displacement of methane. An elemental capture spectroscopy log was acquired to investigate possible correlations between adsorption capacity and mineralogy. Average random vitrinite reflectance data range from 0.78 to 1.59 (upper oil to wet gas and condensate hydrocarbon maturity range). Total organic content determined from acid-washed samples ranges from 0.69 to 14 percent. CO2 adsorption capacities at 400 psi range from a low of 14 scf/ton in less organic-rich zones to more than 136 scf/ton in the more organic-rich zones. There is a direct linear correlation between measured total organic carbon content and the adsorptive capacity of the shale; CO2 adsorption capacity increases with increasing organic carbon content. Initial volumetric estimates based on these data indicate a CO2 sequestration capacity of as much as 28 billion tons total in the deeper and thicker parts of the Devonian shales in Kentucky. In the Big Sandy Gas Field area of eastern Kentucky, calculations using the net thickness of shale with 4 percent or greater total organic carbon, indicate that 6.8 billion tonnes of CO2 could be sequestered in the five county area. Discounting the uncertainties in reservoir volume and injection efficiency, these results indicate that the black shales of Kentucky are a potentially large geologic sink for CO2. Moreover, the extensive occurrence of gas shales in Paleozoic and Mesozoic basins across North America make them an attractive regional target for economic CO2 storage and enhanced natural gas production

TEMPRANILLO is a regulator of juvenility in plants

Many plants are incapable of flowering in inductive daylengths during the early juvenile vegetative phase (JVP). Arabidopsis mutants with reduced expression of TEMPRANILLO (TEM), a repressor of FLOWERING LOCUS T (FT) had a shorter JVP than wild-type plants. Reciprocal changes in mRNA expression of TEM and FT were observed in both Arabidopsis and antirrhinum, which correlated with the length of the JVP. FT expression was induced just prior to the end of the JVP and levels of TEM1 mRNA declined rapidly at the time when FT mRNA levels were shown to increase. TEM orthologs were isolated from antirrhinum (AmTEM) and olive (OeTEM) and were expressed most highly during their juvenile phase. AmTEM functionally complemented AtTEM1 in the tem1 mutant and over-expression of AmTEM prolonged the JVP through repression of FT and CONSTANS (CO). We propose that TEM may have a general role in regulating JVP in herbaceous and woody species

Impact of Reference Gene Selection for Target Gene Normalization on Experimental Outcome Using Real-Time qRT-PCR in Adipocytes

Background: With the current rise in obesity-related morbidities, real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) has become a widely used method for assessment of genes expressed and regulated by adipocytes. In order to measure accurate changes in relative gene expression and monitor intersample variability, normalization to endogenous control genes that do not change in relative expression is commonly used with qRT-PCR determinations. However, historical evidence has clearly demonstrated that the expression profiles of traditional control genes (e.g., b-actin, GAPDH, a-tubulin) are differentially regulated across multiple tissue types and experimental conditions. Methodology/Principal Findings: Therefore, we validated six commonly used endogenous control genes under diverse experimental conditions of inflammatory stress, oxidative stress, synchronous cell cycle progression and cellular differentiation in 3T3-L1 adipocytes using TaqMan qRT-PCR. Under each study condition, we further evaluated the impact of reference gene selection on experimental outcome using examples of target genes relevant to adipocyte function and differentiation. We demonstrate that multiple reference genes are regulated in a condition-specific manner that is not suitable for use in target gene normalization. Conclusion/Significance: Data are presented demonstrating that inappropriate reference gene selection can have profound influence on study conclusions ranging from divergent statistical outcome to inaccurate data interpretation of significan

Identification of genes for normalization of real-time RT-PCR data in breast carcinomas

<p>Abstract</p> <p>Background</p> <p>Quantitative real-time RT-PCR (RT-qPCR) has become a valuable molecular technique in basic and translational biomedical research, and is emerging as an equally valuable clinical tool. Correlation of inter-sample values requires data normalization, which can be accomplished by various means, the most common of which is normalization to internal, stably expressed, reference genes. Recently, such traditionally utilized reference genes as GAPDH and B2M have been found to be regulated in various circumstances in different tissues, emphasizing the need to identify genes independent of factors influencing the tissue, and that are stably expressed within the experimental milieu. In this study, we identified genes for normalization of RT-qPCR data for invasive breast cancer (IBC), with special emphasis on estrogen receptor positive (ER+) IBC, but also examined their applicability to ER- IBC, normal breast tissue and breast cancer cell lines.</p> <p>Methods</p> <p>The reference genes investigated by qRT-PCR were RPLP0, TBP, PUM1, ACTB, GUS-B, ABL1, GAPDH and B2M. Biopsies of 18 surgically-excised tissue specimens (11 ER+ IBCs, 4 ER- IBCs, 3 normal breast tissues) and 3 ER+ cell lines were examined and the data analyzed by descriptive statistics, geNorm and NormFinder. In addition, the expression of selected reference genes in laser capture microdissected ER+ IBC cells were compared with that of whole-tissue.</p> <p>Results</p> <p>A group of 3 genes, TBP, RPLP0 and PUM1, were identified for both the combined group of human tissue samples (ER+ and ER- IBC and normal breast tissue) and for the invasive cancer samples (ER+ and ER- IBC) by GeNorm, where NormFinder consistently identified PUM1 at the single best gene for all sample combinations.</p> <p>Conclusion</p> <p>The reference genes of choice when performing RT-qPCR on normal and malignant breast specimens should be either the collected group of 3 genes (TBP, RPLP0 and PUM1) employed as an average, or PUM1 as a single gene.</p

Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study

BACKGROUND: Quantitative molecular methods (QMMs) such as quantitative real-time polymerase chain reaction (q-PCR), reverse-transcriptase PCR (qRT-PCR) and quantitative nucleic acid sequence-based amplification (QT-NASBA) are increasingly used to estimate pathogen density in a variety of clinical and epidemiological contexts. These methods are often classified as semi-quantitative, yet estimates of reliability or sensitivity are seldom reported. Here, a statistical framework is developed for assessing the reliability (uncertainty) of pathogen densities estimated using QMMs and the associated diagnostic sensitivity. The method is illustrated with quantification of Plasmodium falciparum gametocytaemia by QT-NASBA. RESULTS: The reliability of pathogen (e.g. gametocyte) densities, and the accompanying diagnostic sensitivity, estimated by two contrasting statistical calibration techniques, are compared; a traditional method and a mixed model Bayesian approach. The latter accounts for statistical dependence of QMM assays run under identical laboratory protocols and permits structural modelling of experimental measurements, allowing precision to vary with pathogen density. Traditional calibration cannot account for inter-assay variability arising from imperfect QMMs and generates estimates of pathogen density that have poor reliability, are variable among assays and inaccurately reflect diagnostic sensitivity. The Bayesian mixed model approach assimilates information from replica QMM assays, improving reliability and inter-assay homogeneity, providing an accurate appraisal of quantitative and diagnostic performance. CONCLUSIONS: Bayesian mixed model statistical calibration supersedes traditional techniques in the context of QMM-derived estimates of pathogen density, offering the potential to improve substantially the depth and quality of clinical and epidemiological inference for a wide variety of pathogens