Data-driven normalization strategies for high-throughput quantitative RT-PCR

Associations between telomere length, glucocorticoid receptor gene DNA methylation, volume of stress-related brain structures, and academic performance in middle-school-age children

Background

The biological embedding theory posits that early life experiences can lead to enduring physiological and molecular changes impacting various life outcomes, notably academic performance. Studying previously revealed and objective biomarkers of early life stress exposure, such as telomere length (TL), glucocorticoid receptor gene DNA methylation (DNAme), and the volume of brain structures involved in the regulation of HPA axis functioning (the hippocampus, the amygdala, and the medial prefrontal cortex), in relation to academic performance is crucial. This approach provides an objective measure that surpasses the limitations of self-reported early life adversity and reveals potential molecular and neurological targets for interventions to enhance academic outcomes.

Methods

The participants were 52 children of Mexican or Central American origin aged 11.6-15.6 years. DNA methylation levels and TL were analyzed in three cell sources: saliva, whole blood, and T cells derived from whole blood.

Results

Overall, the concordance across three systems of stress-related biomarkers (TL, DNAme, and the brain) was observed to some extent, although it was less pronounced than we expected; no consistency in different cell sources was revealed. Each of the academic domains that we studied was characterized by a unique and distinct complex of associations with biomarkers, both in terms of the type of biomarker, the directionality of the observed effects, and the cell source of biomarkers. Furthermore, there were biomarker-by-sex interaction effects in predicting academic performance measures.

Conclusions

Assessed in an understudied youth sample, these preliminary data present new essential evidence for a deepened understanding of the biological mechanisms behind associations between exposure to early life stress and academic performance.

Normalizing real-time PCR results in routine testing

Normalization, the process of controlling for normal variation in sampling and testing, can be achieved in real-time PCR assays by converting sample quantification cycles (Cqs) to "efficiency standardized Cqs" (ECqs). We calculated ECqs as E-ΔCq, where E is amplification efficiency and ΔCq is the difference between sample and reference standard Cqs. To apply this approach to a commercial porcine reproductive and respiratory syndrome virus (PRRSV) RT-qPCR assay, we created reference standards by rehydrating and then diluting (1 × 10-4) a PRRSV modified-live vaccine (PRRS MLV; Ingelvac) with serum or oral fluid (OF) to match the sample matrix to be tested. Sample ECqs were calculated using the mean E and reference standard Cq calculated from the 4 reference standards on each plate. Serum (n = 132) and OF (n = 130) samples were collected from each of 12 pigs vaccinated with a PRRSV MLV from -7 to 42 d post-vaccination, tested, and sample Cqs converted to ECqs. Mean plate Es were 1.75-2.6 for serum and 1.7-2.3 for OF. Mean plate reference standard Cqs were 29.1-31.3 for serum and 29.2-31.5 for OFs. Receiver operating characteristic analysis calculated the area under the curve for serum and OF sample ECqs as 0.999 (95% CI: 0.997, 1.000) and 0.947 (0.890, 1.000), respectively. For serum, diagnostic sensitivity and specificity of the commercial PRRSV RT-qPCR assay were estimated as 97.9% and 100% at an ECq cutoff ≥ 0.20, and for OF, 82.6% and 100%, respectively, at an ECq cutoff ≥ 0.45.

Stochastic epithelial-mesenchymal transitions diversify non-cancerous lung cell behaviours

Epithelial-mesenchymal plasticity (EMP) is a hallmark of cancer. By enabling cells to shift between different morphological and functional states, EMP promotes invasion, metastasis and therapy resistance. We report that near-diploid non-cancerous human epithelial lung cells spontaneously shift along the EMP spectrum without genetic changes. Strikingly, more than half of single cell-derived clones adopt a mesenchymal morphology. We independently characterise epithelial-like and mesenchymal-like clones. Mesenchymal clones lose epithelial markers, display larger cell aspect ratios and lower motility, with mostly unaltered proliferation rates. Stemness marker expression and metabolic rewiring diverge independently of phenotypes. In 3D culture, more epithelial clones become mesenchymal-like. Thus, non-cancerous epithelial cells may acquire cancer metastasis-associated features prior to genetic alterations and cancerous transformation.

Data-driven identification of total RNA expression genes for estimation of RNA abundance in heterogeneous cell types highlighted in brain tissue

We define and identify a new class of control genes for next-generation sequencing called total RNA expression genes (TREGs), which correlate with total RNA abundance in cell types of different sizes and transcriptional activity. We provide a data-driven method to identify TREGs from single-cell RNA sequencing data, allowing the estimation of total amount of RNA when restricted to quantifying a limited number of genes. We demonstrate our method in postmortem human brain using multiplex single-molecule fluorescent in situ hybridization and compare candidate TREGs against classic housekeeping genes. We identify AKT3 as a top TREG across five brain regions.

miRNome expression analysis in canine diffuse large B-cell lymphoma

Introduction

Lymphoma is a common canine cancer with translational relevance to human disease. Diffuse large B-cell lymphoma (DLBCL) is the most frequent subtype, contributing to almost fifty percent of clinically recognized lymphoma cases. Identifying new biomarkers capable of early diagnosis and monitoring DLBCL is crucial for enhancing remission rates. This research seeks to advance our knowledge of the molecular biology of DLBCL by analyzing the expression of microRNAs, which regulate gene expression by negatively impacting gene expression via targeted RNA degradation or translational repression. The stability and accessibility of microRNAs make them appropriate biomarkers for the diagnosis, prognosis, and monitoring of diseases.

Methods

We extracted and sequenced microRNAs from ten fresh-frozen lymph node tissue samples (six DLBCL and four non-neoplastic).

Results

Small RNA sequencing data analysis revealed 35 differently expressed miRNAs (DEMs) compared to controls. RT-qPCR confirmed that 23/35 DEMs in DLBCL were significantly upregulated (n = 14) or downregulated (n = 9). Statistical significance was determined by comparing each miRNA's average expression fold-change (2-Cq) between the DLCBL and healthy groups by applying the unpaired parametric Welch's 2-sample t-test and false discovery rate (FDR). The predicted target genes of the DEMs were mainly enriched in the PI3K-Akt-MAPK pathway.

Discussion

Our data point to the potential value of miRNA signatures as diagnostic biomarkers and serve as a guideline for subsequent experimental studies to determine the targets and functions of these altered miRNAs in canine DLBCL.

Evaluation in a porcine wound model and long-term clinical assessment of an autologous heterogeneous skin construct used to close full-thickness wounds

Acute and chronic wounds involving deeper layers of the skin are often not adequately healed by dressings alone and require therapies such as skin grafting, skin substitutes, or growth factors. Here we report the development of an autologous heterogeneous skin construct (AHSC) that aids wound closure. AHSC is manufactured from a piece of healthy full-thickness skin. The manufacturing process creates multicellular segments, which contain endogenous skin cell populations present within hair follicles. These segments are physically optimized for engraftment within the wound bed. The ability of AHSC to facilitate closure of full thickness wounds of the skin was evaluated in a swine model and clinically in 4 patients with wounds of different etiologies. Transcriptional analysis demonstrated high concordance of gene expression between AHSC and native tissues for extracellular matrix and stem cell gene expression panels. Swine wounds demonstrated complete wound epithelialization and mature stable skin by 4 months, with hair follicle development in AHSC-treated wounds evident by 15 weeks. Biomechanical, histomorphological, and compositional analysis of the resultant swine and human skin wound biopsies demonstrated the presence of epidermal and dermal architecture with follicular and glandular structures that are similar to native skin. These data suggest that treatment with AHSC can facilitate wound closure.

Serum miRNA modulations indicate changes in retinal morphology

Background

Age-related macular degeneration (AMD) is the leading cause of vision loss in the developed world and the detection of its onset and progression are based on retinal morphological assessments. MicroRNA (miRNA) have been explored extensively as biomarkers for a range of neurological diseases including AMD, however differences in experimental design and the complexity of human biology have resulted in little overlap between studies. Using preclinical animal models and clinical samples, this study employs a novel approach to determine a serum signature of AMD progression.

Methods

Serum miRNAs were extracted from mice exposed to photo-oxidative damage (PD; 0, 1, 3 and 5 days), and clinical samples from patients diagnosed with reticular pseudodrusen or atrophic AMD. The expression of ~800 miRNAs was measured using OpenArray™, and differential abundance from controls was determined using the HTqPCR R package followed by pathway analysis with DAVID. MiRNA expression changes were compared against quantifiable retinal histological indicators. Finally, the overlap of miRNA changes observed in the mouse model and human patient samples was investigated.

Results

Differential miRNA abundance was identified at all PD time-points and in clinical samples. Importantly, these were associated with inflammatory pathways and histological changes in the retina. Further, we were able to align findings in the mouse serum to those of clinical patients.

Conclusion

In conclusion, serum miRNAs are a valid tool as diagnostics for the early detection of retinal degeneration, as they reflect key changes in retinal health. The combination of pre-clinical animal models and human patient samples led to the identification of a preliminary serum miRNA signature for AMD. This study is an important platform for the future development of a diagnostic serum miRNA panel for the early detection of retinal degeneration.

Reference gene validation for the relative quantification of cannabinoid receptor expression in human odontoblasts via quantitative polymerase chain reaction

Objective

The aim of this study was to identify and validate the reference genes in cultured human odontoblasts to quantify their cannabinoid receptor transcripts.

Methods

The most stably transcribed genes in cultured human odontoblast cells were identified using the RefGenes tool and were selected for real-time polymerase chain reaction (PCR) amplification. Human odontoblast cells were differentiated from mesenchymal stem cells using a transforming growth factor-β-supplemented differentiation medium, and total RNA was purified. Reverse transcription-quantitative PCR and relative quantification analyses were performed using the Schefe's method. The relative expression dataset was analyzed to select the most stable genes.

Results

The analysis showed that the transcripts of cholinergic receptor nicotinic beta 2 subunit, LIM homeobox transcription factor 1 beta, and family with sequence similarity 223 member B presented the lowest standard deviation (SD) in expression (SD: 0.2, 0.17, and 0.16, respectively). These genes showed similar expression levels as the target genes (cannabinoid receptors). Significant differences were found in the relative expression levels of cannabinoid receptors using the selected genes compared to those calculated using beta actin transcripts as references (p < 0.05).

Conclusions

The strategy reported here for searching and verifying new reference genes will aid in the accurate and reliable expression of cannabinoid receptors in human odontoblast cells.

qPCRtools: An R package for qPCR data processing and visualization

In biological research, qPCR is a technique that is frequently used to measure gene expression levels. The calculation of gene amplification efficiency is a critical step in the processing of qPCR data since it helps to decide which method to employ to compute gene expression levels. Here, we introduce the R package qPCRtools, which enables users to analyze the efficiency of gene amplification. Additionally, this software can determine gene expression levels using one of three approaches: the conventional curve-based method, the 2−ΔΔCt method, and the SATQPCR method. The qPCRtools package produces a table with the statistical data of each method as well as a figure with a box or bar plot illustrating the results. The R package qPCRtools is freely available at CRAN (https://CRAN.R-project.org/package=qPCRtools) or GitHub (https://github.com/lixiang117423/qPCRtools/tree/main/CRAN/qPCRtools).

Comparison of Data Normalization Strategies for Array-Based MicroRNA Profiling Experiments and Identification and Validation of Circulating MicroRNAs as Endogenous Controls in Hypertension

Introduction: MicroRNAs are small noncoding RNAs with potential regulatory roles in hypertension and drug response. The presence of many of these RNAs in biofluids has spurred investigation into their role as possible biomarkers for use in precision approaches to healthcare. One of the major challenges in clinical translation of circulating miRNA biomarkers is the limited replication across studies due to lack of standards for data normalization techniques for array-based approaches and a lack of consensus on an endogenous control normalizer for qPCR-based candidate miRNA profiling studies.

Methods: We conducted genome-wide profiling of 754 miRNAs in baseline plasma of 36 European American individuals with uncomplicated hypertension selected from the PEAR clinical trial, who had been untreated for hypertension for at least one month prior to sample collection. After appropriate quality control with amplification score and missingness filters, we tested different normalization strategies such as normalization with global mean of imputed and unimputed data, mean of restricted set of miRNAs, quantile normalization, and endogenous control miRNA normalization to identify the method that best reduces the technical/experimental variability in the data. We identified best endogenous control candidates with expression pattern closest to the mean miRNA expression in the sample, as well as by assessing their stability using a combination of NormFinder, geNorm, Best Keeper and Delta Ct algorithms under the Reffinder software. The suitability of the four best endogenous controls was validated in 50 hypertensive African Americans from the same trial with reverse-transcription–qPCR and by evaluating their stability ranking in that cohort.

Results: Among the compared normalization strategies, quantile normalization and global mean normalization performed better than others in terms of reducing the standard deviation of miRNAs across samples in the array-based data. Among the four strongest candidate miRNAs from our selection process (miR-223-3p, 19b, 106a, and 126-5p), miR-223-3p and miR-126-5p were consistently expressed with the best stability ranking in the validation cohort. Furthermore, the combination of miR-223-3p and 126-5p showed better stability ranking when compared to single miRNAs.

Conclusion: We identified quantile normalization followed by global mean normalization to be the best methods in reducing the variance in the data. We identified the combination of miR-223-3p and 126-5p as potential endogenous control in studies of hypertension.

Differential Expression of Serum Extracellular Vesicle miRNAs in Multiple Sclerosis: Disease-Stage Specificity and Relevance to Pathophysiology

Multiple sclerosis (MS) is a chronic inflammatory autoimmune disease of the central nervous system (CNS). Its first clinical presentation (clinically isolated syndrome, CIS) is often followed by the development of relapsing–remitting MS (RRMS). The periphery-to-CNS transmission of inflammatory molecules is a major pathophysiological pathway in MS. This could include signalling via extracellular vesicle (EV) microRNAs (miRNAs). In this study, we investigated the serum EV miRNome in CIS and RRMS patients and matched controls, with the aims to identify MS stage-specific differentially expressed miRNAs and investigate their biomarker potential and pathophysiological relevance. miRNA sequencing was conducted on serum EVs from CIS-remission, RRMS-relapse, and viral inflammatory CNS disorder patients, as well as from healthy and hospitalized controls. Differential expression analysis was conducted, followed by predictive power and target-pathway analysis. A moderate number of dysregulated serum EV miRNAs were identified in CIS-remission and RRMS-relapse patients, especially relative to healthy controls. Some of these miRNAs were also differentially expressed between the two MS stages and had biomarker potential for patient-control and CIS–RRMS separations. For the mRNA targets of the RRMS-relapse-specific EV miRNAs, biological processes inherent to MS pathophysiology were identified using in silico analysis. Study findings demonstrate that specific serum EV miRNAs have MS stage-specific biomarker potential and contribute to the identification of potential targets for novel, efficacious therapies.

Evidence for Effects of Extracellular Vesicles on Physical, Inflammatory, Transcriptome and Reward Behaviour Status in Mice

Immune-inflammatory activation impacts extracellular vesicles (EVs), including their miRNA cargo. There is evidence for changes in the EV miRNome in inflammation-associated neuropsychiatric disorders. This mouse study investigated: (1) effects of systemic lipopolysaccharide (LPS) and chronic social stress (CSS) on plasma EV miRNome; and (2) physiological, transcriptional, and behavioural effects of peripheral or central delivered LPS-activated EVs in recipient mice. LPS or CSS effects on the plasma EV miRNome were assessed by using microRNA sequencing. Recipient mice received plasma EVs isolated from LPS-treated or SAL-treated donor mice or vehicle only, either intravenously or into the nucleus accumbens (NAc), on three consecutive days. Bodyweight, spleen or NAc transcriptome and reward (sucrose) motivation were assessed. LPS and CSS increased the expression of 122 and decreased expression of 20 plasma EV miRNAs, respectively. Peripheral LPS-EVs reduced bodyweight, and both LPS-EVs and SAL-EVs increased spleen expression of immune-relevant genes. NAc-infused LPS-EVs increased the expression of 10 immune-inflammatory genes. Whereas motivation increased similarly across test days in all groups, the effect of test days was more pronounced in mice that received peripheral or central LPS-EVs compared with other groups. This study provides causal evidence that increased EV levels impact physiological and behavioural processes and are of potential relevance to neuropsychiatric disorders.

Predicting clinical events using Bayesian multivariate linear mixed models with application to scleroderma

BACKGROUND

Scleroderma is a serious chronic autoimmune disease in which a patient's disease state manifests in several irregularly spaced longitudinal measures of lung, heart, skin, and other organ systems. Threshold crossings of pulmonary and cardiac measures indicate potentially life-threatening key clinical events including interstitial lung disease (ILD), cardiomyopathy, and pulmonary hypertension (PH). The statistical challenge is to accurately and precisely predict these events by using all of the clinical history for the patient at hand and for a reference population of patients.

METHODS

We use a Bayesian mixed model approach to simultaneously characterize each individual's future trajectories for several biomarkers. We estimate this model using a large population of patients from the Johns Hopkins Scleroderma Center Research Registry. The joint probabilities of critical lung and heart events are then calculated as a byproduct of the mixed model.

RESULTS

The performance of this approach is substantially better than standard, more common alternatives. In order to predict an individual's risks in a clinical setting, we also develop a cross-validated, sequential prediction (CVSP) algorithm. As additional data are observed during a patient's visit, the algorithm sequentially produces updated predictions for the future longitudinal trajectories and for ILD, cardiomyopathy, and PH. The updated prediction distributions with little additional computing, for example within an electronic health record (EHR).

CONCLUSIONS

This method that generates real-time personalized risk estimates has been implemented within the electronic health record system for clinical testing. To our knowledge, this work represents the first approach to compute personalized risk estimates for multiple scleroderma complications.

A novel wastewater-based epidemiology indexing method predicts SARS-CoV-2 disease prevalence across treatment facilities in metropolitan and regional populations

There is a need for wastewater based epidemiological (WBE) methods that integrate multiple, variously sized surveillance sites across geographic areas. We developed a novel indexing method, Melvin's Index, that provides a normalized and standardized metric of wastewater pathogen load for qPCR assays that is resilient to surveillance site variation. To demonstrate the utility of Melvin's Index, we used qRT-PCR to measure SARS-CoV-2 genomic RNA levels in influent wastewater from 19 municipal wastewater treatment facilities (WWTF's) of varying sizes and served populations across the state of Minnesota during the Summer of 2020. SARS-CoV-2 RNA was detected at each WWTF during the 20-week sampling period at a mean concentration of 8.5 × 104 genome copies/L (range 3.2 × 102-1.2 × 109 genome copies/L). Lag analysis of trends in Melvin's Index values and clinical COVID-19 cases showed that increases in indexed wastewater SARS-CoV-2 levels precede new clinical cases by 15-17 days at the statewide level and by up to 25 days at the regional/county level. Melvin's Index is a reliable WBE method and can be applied to both WWTFs that serve a wide range of population sizes and to large regions that are served by multiple WWTFs.

Bifidobacterium breve Exopolysaccharide Blocks Dendritic Cell Maturation and Activation of CD4+ T Cells

Exopolysaccharide (EPS) is a bacterial extracellular carbohydrate moiety which has been associated with immunomodulatory activity and host protective effects of several gut commensal bacteria. Bifidobacterium breve are early colonizers of the human gastrointestinal tract (GIT) but the role of EPS in mediating their effects on the host has not been investigated for many strains. Here, we characterized EPS production by a panel of human B. breve isolates and investigated the effect of EPS status on host immune responses using human and murine cell culture-based assay systems. We report that B. breve EPS production is heterogenous across strains and that immune responses in human THP-1 monocytes are strain-specific, but not EPS status-specific. Using wild type and isogenic EPS deficient mutants of B. breve strains UCC2003 and JCM7017 we show that EPS had strain-specific divergent effects on cytokine responses from murine bone marrow derived macrophages (BMDMs) and dendritic cells (BMDCs). The B. breve UCC2003 EPS negative (EPS^–) strain increased expression of cytokine genes (Tnfa, Il6, Il12a, and Il23a) relative to untreated BMDCs and BMDCs treated with wild type strain. B. breve UCC2003 and JCM7017 EPS^– strains increased expression of dendritic cell (DC) activation and maturation marker genes (Cd80, Cd83, and Cd86) relative to untreated BMDCs. Consistent with this, BMDCs co-cultured with B. breve UCC2003 and JCM7017 EPS^– strains engineered to express OVA antigen activated OVA-specific OT-II CD4⁺ T-cells in a co-culture antigen-presentation assay while EPS proficient strains did not. Collectively, these data indicate that B. breve EPS proficient strains use EPS to prevent maturation of DCs and activation of antigen specific CD4⁺ T cells responses to B. breve. This study identifies a new immunomodulatory role for B. breve EPS and suggests it may be important for immune evasion of adaptive immunity by B. breve and contribute to host-microbe mutualism.

Reference Gene Selection for RT-qPCR Analysis in Maize Kernels Inoculated with Aspergillus flavus

Resistance against infection by the fungus Aspergillus flavus Link in commercial maize (Zea mays L.) is the topic of many studies, but few studies have investigated the effects of A. flavus infection on gene expression levels in ear kernels. A crucial component of gene expression profiling by RT-qPCR is having a reliable set of reference genes that show relatively constant expression across the treatments and phenotypes under study. Currently, however, there is no published information on reference genes suitable for measuring changes in kernel gene expression levels after infection with A. flavus. Thus, in this study, six candidate reference genes (ACT1, β-Tub2, eIF4A2, TATA, EFIα, and GAPDH) were evaluated and ranked according to their expression stability. The genes were amplified from first-strand cDNA samples synthesized from kernels of two susceptible and two resistant maize lines that were either inoculated with A. flavus or water or not inoculated. Three software packages were used to calculate and rank the stability of expression for these genesgeNorm, NormFinder, and BestKeeper. The analysis revealed that the most stable genes to normalize expression levels from maize kernels responding to A. flavus inoculation and wounding were ACT1, EFIα, and eIF4A2.

Carotid sinus nerve stimulation attenuates alveolar bone loss and inflammation in experimental periodontitis

Baroreceptor and chemoreceptor reflexes modulate inflammatory responses. However, whether these reflexes attenuate periodontal diseases has been poorly examined. Thus, the present study determined the effects of electrical activation of the carotid sinus nerve (CSN) in rats with periodontitis. We hypothesized that activation of the baro and chemoreflexes attenuates alveolar bone loss and the associated inflammatory processes. Electrodes were implanted around the CSN, and bilateral ligation of the first mandibular molar was performed to, respectively, stimulate the CNS and induce periodontitis. The CSN was stimulated daily for 10 min, during nine days, in unanesthetized animals. On the eighth day, a catheter was inserted into the left femoral artery and, in the next day, the arterial pressure was recorded. Effectiveness of the CNS electrical stimulation was confirmed by hypotensive responses, which was followed by the collection of a blood sample, gingival tissue, and jaw. Long-term (9 days) electrical stimulation of the CSN attenuated bone loss and the histological damage around the first molar. In addition, the CSN stimulation also reduced the gingival and plasma pro-inflammatory cytokines induced by periodontitis. Thus, CSN stimulation has a protective effect on the development of periodontal disease mitigating alveolar bone loss and inflammatory processes.

Evaluation of a modified method of extraction, purification, and characterization of lipopolysaccharide (O antigen) from Salmonella Typhimurium

Background and Aim:

Lipopolysaccharide (LPS) is an integral part of the outer cell membrane complex of Gram-negative bacteria. It plays an important role in the induction and stimulation of the immune system. Various LPS purification protocols have been developed. However, analysis of their efficacy is limited by contamination during downstream applications or the public health hazard of LPS. The aim of this study was to evaluate a modified method for extracting LPS as well as assess the purity of the extracted LPS by high-performance liquid chromatography (HPLC) analysis. Further, we evaluated its immunopotentiating function by measuring the relative RNA expression levels of splenic immune-related genes such as interleukin 1β (IL-1β) and interferon-γ (IFN-γ), after intramuscular injection of increasing concentrations of the extracted LPS in specific pathogen-free (SPF) chick.

Materials and Methods:

Isolation, identification, and serotyping of Salmonella Typhimurium were performed using chicken flocks. We then performed molecular typing of Salmonella isolates using conventional polymerase chain reaction (PCR). A new protocol for purification of LPS from Salmonella isolate (S. Typhimurium) was conducted. HPLC analysis of the extracted LPS in the current study was compared to existing methods. An in vivo study was performed to evaluate the ability of LPS to induce an immune response by measuring relative IFN-γ and IL-1β gene expression after injecting increasing concentrations of the extracted LPS into SPF chicks.

Results:

Isolation and serotyping revealed that Salmonella enterica was of the serovar Typhimurium. Confirmation was conducted by molecular typing through conventional PCR. Fractionation of the LPS extract by HPLC revealed a high degree of purity comparable with standard commercial LPS. These results demonstrate the high purity of extracted LPS based on our modified method using propanol and sodium hydroxide mixture. Intramuscular injection of the extracted LPS in 22 day-old SPF chicks, compared to the negative control, revealed significant upregulation of IFN-γ and slight downregulation of IL-1β.

Conclusion:

The new modified method can be used for high purity LPS extraction and demonstrates effective immunopotentiating activity.

Transcriptomics in Toxicogenomics, Part II: Preprocessing and Differential Expression Analysis for High Quality Data

Preprocessing of transcriptomics data plays a pivotal role in the development of toxicogenomics-driven tools for chemical toxicity assessment. The generation and exploitation of large volumes of molecular profiles, following an appropriate experimental design, allows the employment of toxicogenomics (TGx) approaches for a thorough characterisation of the mechanism of action (MOA) of different compounds. To date, a plethora of data preprocessing methodologies have been suggested. However, in most cases, building the optimal analytical workflow is not straightforward. A careful selection of the right tools must be carried out, since it will affect the downstream analyses and modelling approaches. Transcriptomics data preprocessing spans across multiple steps such as quality check, filtering, normalization, batch effect detection and correction. Currently, there is a lack of standard guidelines for data preprocessing in the TGx field. Defining the optimal tools and procedures to be employed in the transcriptomics data preprocessing will lead to the generation of homogeneous and unbiased data, allowing the development of more reliable, robust and accurate predictive models. In this review, we outline methods for the preprocessing of three main transcriptomic technologies including microarray, bulk RNA-Sequencing (RNA-Seq), and single cell RNA-Sequencing (scRNA-Seq). Moreover, we discuss the most common methods for the identification of differentially expressed genes and to perform a functional enrichment analysis. This review is the second part of a three-article series on Transcriptomics in Toxicogenomics.

Multi-Omics Characterization of the Spontaneous Mesenchymal-Epithelial Transition in the PMC42 Breast Cancer Cell Lines

Epithelial–mesenchymal plasticity (EMP), encompassing epithelial–mesenchymal transition (EMT) and mesenchymal–epithelial transition (MET), are considered critical events for cancer metastasis. We investigated chromosomal heterogeneity and chromosomal instability (CIN) profiles of two sister PMC42 breast cancer (BC) cell lines to assess the relationship between their karyotypes and EMP phenotypic plasticity. Karyotyping by GTG banding and exome sequencing were aligned with SWATH quantitative proteomics and existing RNA-sequencing data from the two PMC42 cell lines; the mesenchymal, parental PMC42-ET cell line and the spontaneously epithelially shifted PMC42-LA daughter cell line. These morphologically distinct PMC42 cell lines were also compared with five other BC cell lines (MDA-MB-231, SUM-159, T47D, MCF-7 and MDA-MB-468) for their expression of EMP and cell surface markers, and stemness and metabolic profiles. The findings suggest that the epithelially shifted cell line has a significantly altered ploidy of chromosomes 3 and 13, which is reflected in their transcriptomic and proteomic expression profiles. Loss of the TGFβR2 gene from chromosome 3 in the epithelial daughter cell line inhibits its EMT induction by TGF-β stimulus. Thus, integrative ‘omics’ characterization established that the PMC42 system is a relevant MET model and provides insights into the regulation of phenotypic plasticity in breast cancer.

Plasma miRNAs Display Limited Potential as Diagnostic Tools for Endometriosis

CONTEXT

Despite extensive searches for novel noninvasive diagnostics, laparoscopy remains the reference test for endometriosis. Circulating miRNAs are purported endometriosis biomarkers; however, the miRNA species and their diagnostic accuracy differ between studies and have not been validated in independent cohorts.

OBJECTIVE

Identify endometriosis-specific plasma miRNAs and determine their diagnostic test accuracy.

SETTING

Two university-based, public hospitals and a private gynecology practice in Australia.

DESIGN AND PARTICIPANTS

Four phases: (i) Explorative phase. Plasma miRNA menstrual cycle fluctuations were evaluated in women with endometriosis and asymptomatic controls (n = 16). (ii) Biomarker discovery. Endometriosis-specific plasma miRNAs were identified in (a) women with endometriosis and asymptomatic controls (n = 16) and (b) women with and without surgically defined endometriosis (n = 20). (iii) Biomarker selection. Plasma miRNAs with the best diagnostic potential for endometriosis were selected in a surgically defined selection cohort (n = 78). (iv) Biomarker validation. The diagnostic test accuracy of these miRNAs was calculated in an independent, surgically defined validation cohort (n = 119).

RESULTS

Forty-nine miRNAs were differentially expressed in women with endometriosis. Nine maintained dysregulation in the selection cohort, but only three (miR-155, miR574-3p and miR139-3p) did so in the validation cohort. Combined, these three miRNAs demonstrated a sensitivity and specificity of 83% and 51%, respectively.

CONCLUSION

Plasma miRNAs demonstrated modest sensitivity and specificity as diagnostic tests or triage tools for endometriosis. Other groups' findings were not replicated and accorded poorly with our results. Circulating miRNAs demonstrate diagnostic potential, but stringent, standardized methodological approaches are required for the development of a clinically applicable tool.

Comparative and functional analysis of plasma membrane-derived extracellular vesicles from obese vs. nonobese women

BACKGROUND

Membrane-derived extracellular vesicles (EVs) are released to the circulation by cells found in adipose tissue, transferring microRNAs (miRNAs) that may mediate the adaptive response of recipient cells. This study investigated plasma EVs from obese vs. nonobese women and their functional impact in adipocytes.

METHODS

Plasma EVs were isolated by differential centrifugation. Concentration and size were examined by nanoparticle tracking analysis (NanoSight). RNA was purified from plasma and plasma EVs of 45 women (47 ± 12 years, 58% of obesity) and profiles of mature miRNAs were assessed. Functional analyses were performed in human adipocytes.

FINDINGS

Smaller plasma EVs were found in obese when compared to nonobese women. Positive associations were identified between circulating EVs numbers and parameters of impaired glucose tolerance. Almost 40% of plasma cell-free miRNAs were also found in isolated plasma EVs, defined as Ct values < 37 in ≥75% of samples. BMI together with parameters of insulin resistance were major contributors to EVs-contained miRNA patterns. Treatments of cultured human adipocytes with EVs from obese women led to a significant reduction of genes involved in lipid biosynthesis, while increasing the expression of IRS1 (12.3%, p = 0.002).

INTERPRETATION

Size, concentration and the miRNA cargo of plasma EVs are associated with obesity and parameters of insulin resistance. Plasma EVs may mediate intercellular communication relevant to metabolism in adipocytes.

Factors governing extracellular DNA degradation dynamics in soil

We examined the impacts of soil moisture, temperature, agricultural management and habitat type on the degradation dynamics of eDNA in soils. Synthetic eDNA was added to soil microcosms, and its disappearance over time was measured using both high-throughput sequencing and qPCR. The synthetic eDNA was degraded rapidly, but a small fraction remained detectable throughout the experiments (39-80 days). The eDNA degradation rate was positively correlated with moisture and temperature, but negatively correlated with soil organic carbon content. End-point stabilization of eDNA was highest at low moisture and temperature, but exhibited no relationship with soil organic carbon. Tilled soils had higher rates of degradation and less stabilization than no-till soils. Among different habitats we observed that forest soils had the slowest degradation rate, and meadow soils had the greatest stabilization of eDNA. While eDNA was detectable by qPCR in all treatments across all time-points, it became inconsistently detectable with high-throughput gene sequencing in less than 1 week. We conclude that eDNA degradation and stabilization dynamics vary with moisture, temperature and habitat characteristics, that small amounts of eDNA may persist in soils indefinitely, and that the ability of persistent eDNA to impact microbial community estimates depends on method sensitivity and experimental objectives.

Normalization strategies differently affect circulating miRNA profile associated with the training status

MicroRNAs are fine regulators of the whole-body adaptive response but their use as biomarkers is limited by the lack of standardized pre- and post-analytical procedures. This work aimed to compare different normalization approaches for RT-qPCR data analyses, in order to identify the most reliable and reproducible method to analyze circulating miRNA expression profiles in sedentary and highly-trained subjects. As the physically active status is known to affect miRNA expression, they could be effective biomarkers of the homeostatic response. Following RNA extraction from plasma, a panel of 179 miRNAs was assayed by RT-qPCR and quantified by applying different normalization strategies based on endogenous miRNAs and exogenous oligonucleotides. hsa-miR-320d was found as the most appropriate reference miRNA in reducing the technical variability among the experimental replicates and, hence, in highlighting the inter-cohorts differences. Our data showed an association between the physically active status and specific skeletal muscle- and bone-associated circulating miRNAs profiles, revealing that established epigenetic modifications affect the baseline physiological status of these tissues. Since different normalization strategies led to different outputs, in order to avoid misleading interpretation of data, we remark the importance of the accurate choice of the most reliable normalization method in every experimental setting.

Genome-Wide Association Study of Circadian Behavior in Drosophila melanogaster

Circadian rhythms influence physiological processes from sleep–wake cycles to body temperature and are controlled by highly conserved cycling molecules. Although the mechanistic basis of the circadian clock has been known for decades, the extent to which circadian rhythms vary in nature and the underlying genetic basis for that variation is not well understood. We measured circadian period (Ʈ) and rhythmicity index in the Drosophila Genetic Reference Panel (DGRP) and observed extensive genetic variation in both. Seven DGRP lines had sexually dimorphic arrhythmicity and one line had an exceptionally long Ʈ. Genome-wide analyses identified 584 polymorphisms in 268 genes. We observed differences among transcripts for nine genes predicted to interact among themselves and canonical clock genes in the long period line and a control. Mutations/RNAi knockdown targeting these genes also affected circadian behavior. Our observations reveal that complex genetic interactions influence high levels of variation in circadian phenotypes.

Irreversible effects of trichloroethylene on the gut microbial community and gut-associated immune responses in autoimmune-prone mice

The developing immune system is particularly sensitive to immunotoxicants. This study assessed trichloroethylene (TCE)-induced effects on the gut microbiome and cytokine production during the development in mice. Mice were exposed to TCE (0.05 or 500 μg/mL) at the levels that approximate to environmental or occupational exposure, respectively. Mice were subjected to a continuous developmental exposure to these doses encompassing gestation, lactation and continuing directly in the drinking water postnatally for 154 days (PND154) or PND259. To observe persistence of the effect TCE was removed from the drinking water in a subset of mice on PND154 and were provided regular drinking water until the study terminus (PND259). Abundance of total tissue-associated bacteria reduced only in mice exposed to TCE until PND259. The ratio of Firmicutes/Bacteroidetes did not alter during this continuos exposure; however, cessation of high-dose TCE at PND154 resulted in the increased abundance Bacteroidetes at PND259. Furthermore, high-dose TCE exposure until PND259 resulted in a lower abundance of the genera Bacteroides and Lactobaccilus and increased abundance of genus Bifidobactrium and bacterial family Enterobacteriaceae. TCE exposure until PND154 showed significant changes in the production of interleukin-33; that might play a dual role in maintaining the balance and homeostasis between commensal microbiota and mucosal health. At PND259, interleukin-3, granulocyte-macrophage colony-stimulating factor and Eotaxin were altered in both, the continuous exposure and cessation groups, whereas only a cessation group had a higher level of KC that may facilitate infiltration of neutrophils. The irreversible effects of TCE after a period of exposure cessation suggested a unique programming and potential toxicity of TCE even at the environmental level exposure.

A Study on Effect of Oxaliplatin in MicroRNA Expression in Human Colon Cancer

Colorectal cancer is a commonly diagnosed malignancy and also the major cause of death worldwide. Chemotherapy is the primary therapy for advanced colorectal cancer. Although oxaliplatin has potential effect in colorectal cancer therapy, the molecular mechanisms involved in its cytotoxic effects are not well elucidated. This study outlines the regulatory effects of oxaliplatin on miRNAs expression in colon cancer cells and correlates it with the changing microRNA expression with p53 and p73 expression status in cells. HCT116^p53+/+ and HCT116^p53-/- cells were exposed to oxaliplatin, and the cellular viability was determined by XTT. p73 was knocked down using siRNA and the tumor cells were then treated with oxaliplatin. The expression profile of 384 miRNAs was determined by TaqMan® human miRNA array and calculated by the ∆∆C_t method. Cellular viability was found to decrease after the treatment with oxaliplatin in a dose-dependent manner. The wild-type p53 cells were found to be more sensitive than the null-p53 derivatives. A selective set of miRNAs were either up-regulated or down-regulated in response to the oxaliplatin treatment with a presumable role of p53 and p73 proteins. The miRNAs expression is known to influence the pharmacodynamic mechanisms of oxaliplatin and these effects have been observed to be regulated by p53 and p73. Our results may therefore provide more evidence for identifying a suitable biomarker for the diagnosis of colon cancer.

Leukocyte Dynamics Influence Reference Gene Stability in Whole Blood: Data-Driven qRT-PCR Normalization Is a Robust Alternative for Measurement of Transcriptional Biomarkers

Background

The use of reference genes for normalization of whole blood qRT-PCR data may be problematic in conditions such as stroke which induce alterations in white blood cell differential. In this study, we assessed the influence of stroke on the stability of commonly employed reference genes, and we evaluated data-driven normalization as an alternative.

Methods

Peripheral whole blood was sampled from 33 stroke patients and 29 controls, and qRT-PCR was used to measure the expression levels of 10 target genes whose transcripts are known stroke biomarkers. Target gene expression levels were normalized via those of 2 frequently cited reference genes (ACTB and B2M) as well as with the NORMA-Gene data-driven normalization algorithm.

Results

Whole blood expression levels of reference genes were significantly altered in stroke patients relative to controls. In comparison to normalization via reference genes, NORMA-Gene produced more robust target gene expression data in terms of differential expression dynamics, variance properties, and diagnostic performance.

Conclusions

Our findings suggest that whole blood expression levels of commonly used reference genes may be sensitive to changes in white blood cell differential, and that data-driven qRT-PCR normalization approaches offer a powerful alternative.

Selection of reference genes suitable for normalization of qPCR data under abiotic stresses in bioenergy crop Arundo donax L

Suitable reference gene selection in qRT-PCR is a key pre-requisite to produce reliable data in gene expression analyses. In this study, novel primers for six commonly used reference genes (AC1, TLF, Act2, TUB α, EF-1α and GAPDH) plus two new candidates (pDUF221 and RPN6) were designed and comparatively tested for expression stability under abiotic stresses (osmotic, heavy metal and heat shock) in shoot, root and their combination of Arundo donax L., a raising non-food energy crop. Expression stability rankings from the most to the least stable gene in each condition and in two tissues (young shoots and roots) were generated with geNorm, NormFinder and BestKeeper programs. All programs provided similar rankings and, strikingly, in most cases identified one of the new candidates, RPN6, as the most suitable reference gene. This novel set of reliable references allows to choose either the best combination of reference genes across multiple stress/organ conditions or to select condition-specific genes that can improve the quality of qRT-PCR analysis. This work provides a solid basis for the functional characterization of A. donax, by enabling accurate quantification of the transcriptional responsiveness under a series of common stress conditions of any gene of interest in this promising biomass/bioenergy species.

RNA-sequence data normalization through in silico prediction of reference genes: the bacterial response to DNA damage as case study

Background

Measuring how gene expression changes in the course of an experiment assesses how an organism responds on a molecular level. Sequencing of RNA molecules, and their subsequent quantification, aims to assess global gene expression changes on the RNA level (transcriptome). While advances in high-throughput RNA-sequencing (RNA-seq) technologies allow for inexpensive data generation, accurate post-processing and normalization across samples is required to eliminate any systematic noise introduced by the biochemical and/or technical processes. Existing methods thus either normalize on selected known reference genes that are invariant in expression across the experiment, assume that the majority of genes are invariant, or that the effects of up- and down-regulated genes cancel each other out during the normalization.

Results

Here, we present a novel method, moose², which predicts invariant genes in silico through a dynamic programming (DP) scheme and applies a quadratic normalization based on this subset. The method allows for specifying a set of known or experimentally validated invariant genes, which guides the DP. We experimentally verified the predictions of this method in the bacterium Escherichia coli, and show how moose² is able to (i) estimate the expression value distances between RNA-seq samples, (ii) reduce the variation of expression values across all samples, and (iii) to subsequently reveal new functional groups of genes during the late stages of DNA damage. We further applied the method to three eukaryotic data sets, on which its performance compares favourably to other methods. The software is implemented in C++ and is publicly available from http://grabherr.github.io/moose2/.

Conclusions

The proposed RNA-seq normalization method, moose², is a valuable alternative to existing methods, with two major advantages: (i) in silico prediction of invariant genes provides a list of potential reference genes for downstream analyses, and (ii) non-linear artefacts in RNA-seq data are handled adequately to minimize variations between replicates.

Electronic supplementary material

The online version of this article (10.1186/s13040-017-0150-8) contains supplementary material, which is available to authorized users.

MicroRNA profile analysis in the liver fibrotic tissues of chronic hepatitis B patients

OBJECTIVE

We aimed to identify the features of microRNA (miRNA) at different fibrotic stages in patients with hepatitis B virus (HBV)-related liver fibrosis.

METHODS

Liver tissues were collected from 40 chronic hepatitis B (CHB) patients at fibrotic stages S0-4. Microarrays of miRNAs and genomic informatics analysis were performed.

RESULTS

In total, 105 miRNAs were differentially expressed in fibrotic tissues (S1-4 groups) compared with no fibrotic tissues (S0 group; P < 0.05). Combined with three classifications, 17 differential miRNAs were found to be closely related to fibrotic stages (over twofold change and P < 0.05). Five miRNAs had a signature that correlated with serum biochemical parameters and liver inflammatory grades. The receiver operating characteristic (ROC) curve showed that six miRNAs performed excellently in the diagnosis of liver fibrosis, with the area under the ROC curve (AUROC) over 0.8; among them hsa-miR-214-3p had the highest AUROC (0.867). Gene ontology functions of differential miRNAs mainly involved in the cellular and developmental processes, localization, biological regulation, binding, transcriptional regulator and organelle. We also found that 23 novel signaling pathways were dysregulated in the liver fibrosis.

CONCLUSIONS

MiRNA profile signature, including 17 differential miRNAs and 23 dysregulated signaling pathways, was associated with liver fibrosis. Hepatic inflammatory grades were correlated with the differential miRNA. Some miRNAs can be used for the diagnosis of liver fibrosis.

Radiation and SN38 treatments modulate the expression of microRNAs, cytokines and chemokines in colon cancer cells in a p53-directed manner

Aberrant expression of miRNAs, cytokines and chemokines are involved in pathogenesis of colon cancer. However, the expression of p53 mediated miRNAs, cyto- and chemokines after radiation and SN38 treatment in colon cancer remains elusive. Here, human colon cancer cells, HCT116 with wild-type, heterozygous and a functionally null p53, were treated by radiation and SN38. The expression of 384 miRNAs was determined by using the TaqMan® miRNA array, and the expression of cyto- and chemokines was analyzed by Meso-Scale-Discovery instrument. Up- or down-regulations of miRNAs after radiation and SN38 treatments were largely dependent on p53 status of the cells. Cytokines, IL-6, TNF-α, IL-1β, Il-4, IL-10, VEGF, and chemokines, IL-8, MIP-1α were increased, and IFN-γ expression was decreased after radiation, whereas, IL-6, IFN-γ, TNF-α, IL-1β, Il-4, IL-10, IL-8 were decreased, and VEGF and MIP-1α were increased after SN38 treatment. Bioinformatic analysis pointed out that the highly up-regulated miRNAs, let-7f-5p, miR-455-3p, miR-98, miR-155-5p and the down-regulated miRNAs, miR-1, miR-127-5p, miR-142-5p, miR-202-5p were associated with colon cancer pathways and correlated with cyto- or chemokine expression. These miRNAs have the potential for use in colon cancer therapy as they are related to p53, pro- or anti-inflammatory cyto- or chemokines after the radiation and SN38 treatment.

Sperm microRNA Content Is Altered in a Mouse Model of Male Obesity, but the Same Suite of microRNAs Are Not Altered in Offspring's Sperm

The prevalence of obesity is increasing worldwide and has tripled in men of reproductive age since the 1970s. Concerningly, obesity is not only comorbid with other chronic diseases, but there is mounting evidence that it increases the non-communicable disease load in their children (eg mortality, obesity, autism). Animal studies have demonstrated that paternal obesity increases the risk of metabolic (eg glucose metabolism defects, obesity) and reproductive disorders in offspring. Epigenetic changes within sperm are clear mechanistic candidates that are associated with both changes to the father’s environment and offspring phenotype. Specifically there is emerging evidence that a father’s sperm microRNA content both responds to paternal environmental cues and alters the gene expression profile and subsequent development of the early embryo. We used a mouse model of high fat diet (HFD) induced obesity to investigate whether male obesity could modulate sperm microRNA content. We also investigated whether this alteration to a father’s sperm microRNA content lead to a similar change in the sperm of male offspring. Our investigations were initially guided by a Taqman PCR array, which indicated the differential abundance of 28 sperm borne microRNAs in HFD mice. qPCR confirmation in a much larger cohort of founder males demonstrated that 13 of these microRNAs were differentially abundant (11 up-regulated; 2 down-regulated) due to HFD feeding. Despite metabolic and reproductive phenotypes also being observed in grand-offspring fathered via the male offspring lineage, there was no evidence that any of the 13 microRNAs were also dysregulated in male offspring sperm. This was presumably due to the variation seen within both groups of offspring and suggests other mechanisms might act between offspring and grand-offspring. Thus 13 sperm borne microRNAs are modulated by a father’s HFD and the presumed transfer of this altered microRNA payload to the embryo at fertilisation potentially acts to alter the embryonic molecular makeup post-fertilisation, altering its growth trajectory, ultimately affecting adult offspring phenotype and may contribute to paternal programming.

Quantitative real-time PCR normalization for gene expression studies in the plant pathogenic fungi Lasiodiplodia theobromae

Lasiodiplodia theobromae is a highly virulent plant pathogen. It has been suggested that heat stress increases its virulence. The aim of this work was to evaluate, compare, and recommend normalization strategies for gene expression analysis of the fungus growing with grapevine wood under heat stress. Using RT-qPCR-derived data, reference gene stability was evaluated through geNorm, NormFinder and Bestkeeper applications. Based on the geometric mean using the ranking position obtained for each independent analysis, genes were ranked from least to most stable as follows: glyceraldehyde-3-phosphate dehydrogenase (GAPDH), actin (ACT), β-tubulin (TUB) and elongation factor-1α (EF1α). Using RNAseq-derived data based on the calculated tagwise dispersion these genes were ordered by increasing stability as follows: GAPDH, ACT, TUB, and EF1α. The correlation between RNAseq and RTqPCR results was used as criteria to identify the best RT-qPCR normalization approach. The gene TUB is recommended as the best option for normalization among the commonly used reference genes, but alternative fungal reference genes are also suggested.

Extracellular vesicle microRNAs: biomarker discovery in various diseases based on RT-qPCR

In recent years, biomarker discovery based on extracellular microRNAs (miRNAs), especially exosome miRNAs, has drawn wide attention. While exosome isolation and identification technologies are increasingly sophisticated, the preanalytical process of exosome miRNAs seems to be no longer a crucial problem. Though next-generation sequencing, microarray and digital PCR have been recommended as good downstream analytical platforms for exosome miRNA quantification, they are still more constrained in clinical utility compared with RT-qPCR method at present. In this review, we will trace back to the origin and summarize current studies of biomarker discovery based on extracellular vesicle miRNAs, and provide an overview and latest developments of RT-qPCR-based data normalization, in order to further assist the development of translational medicine.

Differential Expression of Inflammation-Related Genes in Children with Down Syndrome

OBJECTIVE

The aim of the study was to investigate the expression patterns of a specific set of genes involved in the inflammation process in children with Down Syndrome (DS) and children without the syndrome (control group) to identify differences that may be related to the immune abnormalities observed in DS individuals.

METHOD

RNA samples were obtained from peripheral blood, and gene expression was quantified using the TaqMan® Array Plate Human Inflammation Kit, which facilitated the investigation into 92 inflammation-related genes and four reference genes using real-time polymerase chain reaction (qPCR).

RESULTS

Twenty genes showed differential expression in children with DS; 12 were overexpressed (PLA2G2D, CACNA1D, ALOX12, VCAM1, ICAM1, PLCD1, ADRB1, HTR3A, PDE4C, CASP1, PLA2G5, and PLCB4), and eight were underexpressed (LTA4H, BDKRB1, ADRB2, CD40LG, ITGAM, TNFRSF1B, ITGB1, and TBXAS1). After statistically correcting for the false discovery rate, only the genes BDKRB1 and LTA4H showed differential expression, and both were underexpressed within the DS group.

CONCLUSION

DS children showed differential expression of inflammation-related genes that were not located on chromosome 21 compared with children without DS. The BDKRB1 and LTA4H genes may differentiate the case and control groups based on the inflammatory response, which plays an important role in DS pathogenesis.

Evaluation of two real-time polymerase chain reaction assays for Porcine epidemic diarrhea virus (PEDV) to assess PEDV transmission in growing pigs

In April 2013, a Porcine epidemic diarrhea virus (PEDV) epidemic began in the United States. As part of the response, real-time reverse transcription polymerase chain reaction (RT-PCR) assays to detect PEDV were developed by several veterinary diagnostic laboratories. Our study evaluated RT-PCR PEDV assays that detect the N gene (gN) and S gene (gS) for their ability to detect PEDV infection and the transmission potential of pigs experimentally exposed to PEDV. Detection limits and quantification cycle (Cq) values of real-time RT-PCR were assayed for PEDV samples and positive controls for both gN and gS. The limit of detection for the gN assay was 10(-6) (mean Cq: 39.82 ± 0.30) and 10(-5) (mean Cq: 39.39 ± 0.72) for the gS assay with PEDV strain USA/Colorado/2013. Following recommended guidelines, rectal swabs (n = 1,064) were tested; 354 samples were positive by gN assay and 349 samples were positive by gS assay (Cq ≤ 34.99), 710 samples were negative by gN assay and 715 were negative by gS assay (Cq > 34.99) of which 355 and 344 were "undetermined" (i.e., undetected within a threshold of 40 RT-PCR cycles, by gN and gS assays, respectively). The coefficient of variation (intra-assay variation) ranged from 0.00% to 2.65% and interassay variation had an average of 2.75%. PEDV could be detected in rectal swabs from all pigs for ~2 weeks postinfection at which time the prevalence began to decrease until all pigs were RT-PCR negative by 5 weeks postinfection. Our study demonstrated that RT-PCR assays functioned well to detect PEDV and that the gN assay was slightly better.

With Reference to Reference Genes: A Systematic Review of Endogenous Controls in Gene Expression Studies

The choice of reference genes that are stably expressed amongst treatment groups is a crucial step in real-time quantitative PCR gene expression studies. Recent guidelines have specified that a minimum of two validated reference genes should be used for normalisation. However, a quantitative review of the literature showed that the average number of reference genes used across all studies was 1.2. Thus, the vast majority of studies continue to use a single gene, with β-actin (ACTB) and/or glyceraldehyde 3-phosphate dehydrogenase (GAPDH) being commonly selected in studies of vertebrate gene expression. Few studies (15%) tested a panel of potential reference genes for stability of expression before using them to normalise data. Amongst studies specifically testing reference gene stability, few found ACTB or GAPDH to be optimal, whereby these genes were significantly less likely to be chosen when larger panels of potential reference genes were screened. Fewer reference genes were tested for stability in non-model organisms, presumably owing to a dearth of available primers in less well characterised species. Furthermore, the experimental conditions under which real-time quantitative PCR analyses were conducted had a large influence on the choice of reference genes, whereby different studies of rat brain tissue showed different reference genes to be the most stable. These results highlight the importance of validating the choice of normalising reference genes before conducting gene expression studies.

LEMming: A Linear Error Model to Normalize Parallel Quantitative Real-Time PCR (qPCR) Data as an Alternative to Reference Gene Based Methods

BACKGROUND

Gene expression analysis is an essential part of biological and medical investigations. Quantitative real-time PCR (qPCR) is characterized with excellent sensitivity, dynamic range, reproducibility and is still regarded to be the gold standard for quantifying transcripts abundance. Parallelization of qPCR such as by microfluidic Taqman Fluidigm Biomark Platform enables evaluation of multiple transcripts in samples treated under various conditions. Despite advanced technologies, correct evaluation of the measurements remains challenging. Most widely used methods for evaluating or calculating gene expression data include geNorm and ΔΔCt, respectively. They rely on one or several stable reference genes (RGs) for normalization, thus potentially causing biased results. We therefore applied multivariable regression with a tailored error model to overcome the necessity of stable RGs.

RESULTS

We developed a RG independent data normalization approach based on a tailored linear error model for parallel qPCR data, called LEMming. It uses the assumption that the mean Ct values within samples of similarly treated groups are equal. Performance of LEMming was evaluated in three data sets with different stability patterns of RGs and compared to the results of geNorm normalization. Data set 1 showed that both methods gave similar results if stable RGs are available. Data set 2 included RGs which are stable according to geNorm criteria, but became differentially expressed in normalized data evaluated by a t-test. geNorm-normalized data showed an effect of a shifted mean per gene per condition whereas LEMming-normalized data did not. Comparing the decrease of standard deviation from raw data to geNorm and to LEMming, the latter was superior. In data set 3 according to geNorm calculated average expression stability and pairwise variation, stable RGs were available, but t-tests of raw data contradicted this. Normalization with RGs resulted in distorted data contradicting literature, while LEMming normalized data did not.

CONCLUSIONS

If RGs are coexpressed but are not independent of the experimental conditions the stability criteria based on inter- and intragroup variation fail. The linear error model developed, LEMming, overcomes the dependency of using RGs for parallel qPCR measurements, besides resolving biases of both technical and biological nature in qPCR. However, to distinguish systematic errors per treated group from a global treatment effect an additional measurement is needed. Quantification of total cDNA content per sample helps to identify systematic errors.

Analysis of the differential expression of circulating microRNAs during the progression of hepatic fibrosis in patients with chronic hepatitis B virus infection

Considering the limitations of liver biopsy, reliable non‑invasive serum biomarkers of liver fibrosis are required for early diagnosis. The present study analyzed the expression profile of circulating micro (mi)RNAs during the development and progression of hepatic fibrosis in patients with chronic hepatitis B virus (HBV) infection, aiming to identify novel earlier diagnostic biomarkers. Fresh plasma samples were collected from 50 patients diagnosed with chronic HBV infection and hepatic fibrosis. These patients were classified into five groups (S0, S1, S2, S3 and S4; n=10 per group) based on Scheuer's staging criteria. The differential expression of the circulating miRNAs was determined by performing miRNA microarray hybridization. Finally, the target genes of the miRNAs were predicted and classified using gene ontology analysis. A total of 140 miRNAs were detected in the S1‑S4 patient groups, and their expression levels were >2‑fold higher compared with those in the S0 group. The numbers of miRNAs differentially expressed in the S1‑S4 patient groups were 48, 97, 84 and 56, respectively, with 12 miRNAs differentially expressed at all stages, 10 of which were upregulated and two of which were downregulated. The target genes of the miRNAs identified were found to be involved in 100 signal transduction pathways, the majority of which affected hepatic fibrosis via the TGF‑/Smad, Wnt, MAPK, Jak/STAT and VEGF pathways. The differential expression levels of miRNAs were closely associated with the staging of hepatic fibrosis. The results of the present study provide evidence to facilitate the development and application of non‑invasive biomarkers for earlier diagnosis of hepatic fibrosis.

Normalization of circulating microRNA expression data obtained by quantitative real-time RT-PCR

The high-throughput analysis of microRNAs (miRNAs) circulating within the blood of healthy and diseased individuals is an active area of biomarker research. Whereas quantitative real-time reverse transcription polymerase chain reaction (qPCR)-based methods are widely used, it is yet unresolved how the data should be normalized. Here, we show that a combination of different algorithms results in the identification of candidate reference miRNAs that can be exploited as normalizers, in both discovery and validation phases. Using the methodology considered here, we identify normalizers that are able to reduce nonbiological variation in the data and we present several case studies, to illustrate the relevance in the context of physiological or pathological scenarios. In conclusion, the discovery of stable reference miRNAs from high-throughput studies allows appropriate normalization of focused qPCR assays.

Simple regression for correcting ΔCt bias in RT-qPCR low-density array data normalization

BACKGROUND

Reverse transcription quantitative PCR (RT-qPCR) is considered the gold standard for quantifying relative gene expression. Normalization of RT-qPCR data is commonly achieved by subtracting the Ct values of the internal reference genes from the Ct values of the target genes to obtain ΔCt. ΔCt values are then used to derive ΔΔCt when compared to a control group or to conduct further statistical analysis.

RESULTS

We examined two rheumatoid arthritis RT-qPCR low density array datasets and found that this normalization method introduces substantial bias due to differences in PCR amplification efficiency among genes. This bias results in undesirable correlations between target genes and reference genes, which affect the estimation of fold changes and the tests for differentially expressed genes. Similar biases were also found in multiple public mRNA and miRNA RT-qPCR array datasets we analysed. We propose to regress the Ct values of the target genes onto those of the reference genes to obtain regression coefficients, which are then used to adjust the reference gene Ct values before calculating ΔCt.

CONCLUSIONS

The per-gene regression method effectively removes the ΔCt bias. This method can be applied to both low density RT-qPCR arrays and individual RT-qPCR assays.

Association of mitochondrial DNA levels with frailty and all-cause mortality

Mitochondrial function is altered with age and variants in mitochondrial DNA (mtDNA) modulate risk for several age-related disease states. However, the association of mtDNA copy number, a readily available marker which reflects mitochondrial depletion, energy reserves, and oxidative stress, on aging and mortality in the general population has not been addressed. To assess the association between mtDNA copy number and two primary outcomes--prevalent frailty and all-cause mortality--we utilize data from participants who were from two multicenter, multiethnic, community-based, prospective studies--the Cardiovascular Health Study (CHS) (1989-2006) and the Atherosclerosis Risk in Communities (ARIC) study (1987-2013). A total of 4892 participants (43.3% men) from CHS and 11,509 participants (44.9% men) from ARIC self-identifying as white or black were included in the analysis. mtDNA copy number, the trait of interest, was measured using a qPCR-based method in CHS and an array-based method in ARIC from DNA isolated from whole blood in participants from both cohorts. In race-stratified meta-analyses, we observe a significant inverse association of mtDNA copy number with age and higher mtDNA copy number in women relative to men. Lower mtDNA copy number was also significantly associated with prevalent frailty in white participants from CHS (OR 0.91, 95% CI 0.85-0.97). Additionally, mtDNA copy number was a strong independent predictor of all-cause mortality in an age- and sex-adjusted, race-stratified analysis of 16,401 participants from both cohorts with a pooled hazard ratio of 1.47 (95% CI 1.33-1.62) for the lowest quintile of mtDNA copy number relative to the highest quintile. Key messages: Mitochondrial DNA (mtDNA) copy number is associated with age and sex. Lower mtDNA copy number is also associated with prevalent frailty. mtDNA copy number is a significant predictor of all-cause mortality in a multiethnic population.

A survey of tools for the analysis of quantitative PCR (qPCR) data

Real-time quantitative polymerase-chain-reaction (qPCR) is a standard technique in most laboratories used for various applications in basic research. Analysis of qPCR data is a crucial part of the entire experiment, which has led to the development of a plethora of methods. The released tools either cover specific parts of the workflow or provide complete analysis solutions. Here, we surveyed 27 open-access software packages and tools for the analysis of qPCR data. The survey includes 8 Microsoft Windows, 5 web-based, 9 R-based and 5 tools from other platforms. Reviewed packages and tools support the analysis of different qPCR applications, such as RNA quantification, DNA methylation, genotyping, identification of copy number variations, and digital PCR. We report an overview of the functionality, features and specific requirements of the individual software tools, such as data exchange formats, availability of a graphical user interface, included procedures for graphical data presentation, and offered statistical methods. In addition, we provide an overview about quantification strategies, and report various applications of qPCR. Our comprehensive survey showed that most tools use their own file format and only a fraction of the currently existing tools support the standardized data exchange format RDML. To allow a more streamlined and comparable analysis of qPCR data, more vendors and tools need to adapt the standardized format to encourage the exchange of data between instrument software, analysis tools, and researchers.

Data Pre-Processing for Label-Free Multiple Reaction Monitoring (MRM) Experiments

Multiple Reaction Monitoring (MRM) conducted on a triple quadrupole mass spectrometer allows researchers to quantify the expression levels of a set of target proteins. Each protein is often characterized by several unique peptides that can be detected by monitoring predetermined fragment ions, called transitions, for each peptide. Concatenating large numbers of MRM transitions into a single assay enables simultaneous quantification of hundreds of peptides and proteins. In recognition of the important role that MRM can play in hypothesis-driven research and its increasing impact on clinical proteomics, targeted proteomics such as MRM was recently selected as the Nature Method of the Year. However, there are many challenges in MRM applications, especially data pre‑processing where many steps still rely on manual inspection of each observation in practice. In this paper, we discuss an analysis pipeline to automate MRM data pre‑processing. This pipeline includes data quality assessment across replicated samples, outlier detection, identification of inaccurate transitions, and data normalization. We demonstrate the utility of our pipeline through its applications to several real MRM data sets.

MicroRNA-146a regulates human foetal femur derived skeletal stem cell differentiation by down-regulating SMAD2 and SMAD3

MicroRNAs (miRs) play a pivotal role in a variety of biological processes including stem cell differentiation and function. Human foetal femur derived skeletal stem cells (SSCs) display enhanced proliferation and multipotential capacity indicating excellent potential as candidates for tissue engineering applications. This study has examined the expression and role of miRs in human foetal femur derived SSC differentiation along chondrogenic and osteogenic lineages. Cells isolated from the epiphyseal region of the foetal femur expressed higher levels of genes associated with chondrogenesis while cells from the foetal femur diaphyseal region expressed higher levels of genes associated with osteogenic differentiation. In addition to the difference in osteogenic and chondrogenic gene expression, epiphyseal and diaphyseal cells displayed distinct miRs expression profiles. miR-146a was found to be expressed by human foetal femur diaphyseal cells at a significantly enhanced level compared to epiphyseal populations and was predicted to target various components of the TGF-β pathway. Examination of miR-146a function in foetal femur cells confirmed regulation of protein translation of SMAD2 and SMAD3, important TGF-β and activin ligands signal transducers following transient overexpression in epiphyseal cells. The down-regulation of SMAD2 and SMAD3 following overexpression of miR-146a resulted in an up-regulation of the osteogenesis related gene RUNX2 and down-regulation of the chondrogenesis related gene SOX9. The current findings indicate miR-146a plays an important role in skeletogenesis through attenuation of SMAD2 and SMAD3 function and provide further insight into the role of miRs in human skeletal stem cell differentiation modulation with implications therein for bone reparation.

NqA: an R-based algorithm for the normalization and analysis of microRNA quantitative real-time polymerase chain reaction data

In this note, we propose an R function named NqA (Normalization qPCR Array, where qPCR is quantitative real-time polymerase chain reaction) suitable for the identification of a set of microRNAs (miRNAs) to be used for data normalization in view of subsequent validation studies with qPCR data. NqA is available through the website of the Fondazione IRCCS Istituto Nazionale dei Tumori of Milan (http://www.istitutotumori.mi.it/modules.php?name=Content&pa=showpage&pid=812) with a dedicated user's guide. We applied our function on a qPCR dataset downloaded from the Gene Expression Omnibus (GEO) database. Results show that NqA provides a functional subset of reference miRNAs and a set of promising significantly modulated miRNAs for subsequent validation studies.