Specifications of qPCR based epigenetic immune cell quantification

OBJECTIVES

Immune monitoring is an important aspect in diagnostics and clinical trials for patients with compromised immune systems. Flow cytometry is the standard method for immune cell counting but faces limitations. Best practice guidelines are available, but lack of standardization complicates compliance with e.g., in vitro diagnostic regulations. Limited sample availability forces immune monitoring to predominantly use population-based reference intervals. Epigenetic qPCR has evolved as alternative with broad applicability and low logistical demands. Analytical performance specifications (APS) have been defined for qPCR in several regulated fields including testing of genetically modified organisms or vector-shedding.

METHODS

APS were characterized using five epigenetic qPCR-based assays quantifying CD3+, CD4+, CD8+ T, B and NK cells in light of regulatory requirements.

RESULTS

Epigenetic qPCR meets all specifications including bias, variability, linearity, ruggedness and sample stability as suggested by pertinent guidelines and regulations. The assays were subsequently applied to capillary blood from 25 normal donors over a 28-day period. Index of individuality (IoI) and reference change values were determined to evaluate potential diagnostic gains of individual reference intervals. Analysis of the IoI suggests benefits for individual over population-based references. Reference change values (RCVs) show that changes of approx. Fifty percent from prior measurement are suggestive for clinically relevant changes in any of the 5 cell types.

CONCLUSIONS

The demonstrated precision, long-term stability and obtained RCVs render epigenetic cell counting a promising tool for immune monitoring in clinical trials and diagnosis.

Prognostic model based on telomere-related genes predicts the risk of oral squamous cell carcinoma

BACKGROUND

This study investigated a potential prognostic model based on telomere-related genes (TRGs) for the clinical prediction of oral squamous cell carcinoma (OSCC).

METHODS

Gene expression data and associated clinical phenotypes were obtained from online databases. Differentially expressed (DE)-TRGs were identified between OSCC and normal samples, followed by protein-protein interaction and enrichment analyses. Subsequently, the prognostic genes explored based on the DE-TRGs and survival data were applied in the establishment of the current prognostic model, and an integrated analysis was performed between high- and low-risk groups using a prognostic model. The expression of certain prognostic genes identified in the present study was validated using qPCR analysis and/or western blot in OSCC cell lines and clinical samples.

RESULTS

169 DE-TRGs were identified between the OSCC samples and controls. DE-TRGs are mainly involved in functions such as hypoxia response and pathways such as the cell cycle. Eight TRGs (CCNB1, PDK4, PLOD2, RACGAP1, MET, PLK1, KPNA2, and CCNA2) associated with OSCC survival and prognosis were used to construct a prognostic model. qPCR analysis and western blot showed that most of the eight prognostic genes were consistent with the current bioinformatics results. Analysis of the high- and low-risk groups for OSCC determined by the prognostic model showed that the current prognostic model was reliable.

CONCLUSIONS

A novel prognostic model for OSCC was constructed by TRGs. PLOD2 and APLK1 may participate in the progression of OSCC via responses to hypoxia and cell cycle pathways, respectively. TRGs, including KPNA2 and CCNA2, may serve as novel prognostic biomarkers for OSCC.

Development and Evaluation of a Next-Generation Sequencing Panel for the Multiple Detection and Identification of Pathogens in Fermented Foods

These days, bacterial detection methods have some limitations in sensitivity, specificity, and multiple detection. To overcome these, novel detection and identification method is necessary to be developed. Recently, NGS panel method has been suggested to screen, detect, and even identify specific foodborne pathogens in one reaction. In this study, new NGS panel primer sets were developed to target 13 specific virulence factor genes from five types of pathogenic Escherichia coli, Listeria monocytogenes, and Salmonella enterica serovar Typhimurium, respectively. Evaluation of the primer sets using singleplex PCR, crosscheck PCR and multiplex PCR revealed high specificity and selectivity without interference of primers or genomic DNAs. Subsequent NGS panel analysis with six artificially contaminated food samples using those primer sets showed that all target genes were multi-detected in one reaction at 10⁸-10⁵ CFU of target strains. However, a few false-positive results were shown at 10⁶-10⁵ CFU. To validate this NGS panel analysis, three sets of qPCR analyses were independently performed with the same contaminated food samples, showing the similar specificity and selectivity for detection and identification. While this NGS panel still has some issues for detection and identification of specific foodborne pathogens, it has much more advantages, especially multiple detection and identification in one reaction, and it could be improved by further optimized NGS panel primer sets and even by application of a new real-time NGS sequencing technology. Therefore, this study suggests the efficiency and usability of NGS panel for rapid determination of origin strain in various foodborne outbreaks in one reaction.

Development of New PCR Assay with SYBR Green I for Detection of Mycoplasma, Acholeplasma, and Ureaplasma sp. in Cell Cultures

Mycoplasma, Acholeplasma, and Ureaplasma sp. are atypical bacteria responsible for in vitro cell culture contaminations that can warp the results. These bacteria also cause human and animal infections and may lead to chronic diseases. In developed polymerase chain reaction (PCR) in this study a quantitative PCR with SYBR Green I fluorochrome was applied to facilitate the Mycoplasma, Acholeplasma, and Ureaplasma sp. DNA detection and identification. Screening Test-1 v.1 (triplex qPCR) allowed for the detection of 11 species. Test-1 v.2 (three single qPCRs) pre-identified three subgroups, allowing for the reduction of using single qPCRs in Test-2 for species identification. The range of both tests was consistent with pharmacopeial requirements for microbial quality control of mammal cells and included detection of M. arginini, M. orale, M. hyorhinis, M. fermentans, M. genitalium, M. hominis, M. pneumoniae, M. salivarium, M. pirum, A. laidlawii, and U. urealyticum. Limit of detection values varied between 125–300 and 50–100 number of copies per milliliter in Test-1 and Test-2, respectively. Test-1 and Test-2 showed fully concordant results, allowed for time-saving detection and/or identification of selected species from Mycoplasma, Acholeplasma, and Ureaplasma in tested cell cultures.

Establishing high-accuracy biomarkers for colorectal cancer by comparing fecal microbiomes in patients with healthy families

Colorectal cancer (CRC) causes high morbidity and mortality worldwide, and noninvasive gut microbiome (GM) biomarkers are promising for early CRC diagnosis. However, the GM varies significantly based on ethnicity, diet and living environment, suggesting varied GM biomarker performance in different regions. We performed a metagenomic association analysis on stools from 52 patients and 55 corresponding healthy family members who lived together to identify GM biomarkers for CRC in Chongqing, China. The GM of patients differed significantly from that of healthy controls. A total of 22 microbial genes were included as screening biomarkers with high accuracy in additional 46 cases and 40 randomly selected healthy adults in Chongqing (area under the receive-operation curve (AUC) = 0.905, 95% CI 0.832-0.977). The classifier based on the identified 22 biomarkers also performed well in the cohort from Hong Kong (AUC = 0.811, 95% CI 0.715-0.907) and French (AUC = 0.859, 95% CI 0.773-0.944) populations. Quantitative PCR was applied for measuring three selected biomarkers in the classification of CRC patients in independent Chongqing population containing 30 cases and 30 controls and the best biomarker from Coprobacillus performed well with high AUC (0.930, 95% CI 0.904-0.955). This study revealed increased sensitivity and applicability of our GM biomarkers compared with previous biomarkers significantly promoting the early diagnosis of CRC.

Streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data

BACKGROUND

Genetically engineered mice (GEM) are essential tools for understanding gene function and disease modeling. Historically, gene targeting was first done in embryonic stem cells (ESCs) derived from the 129 family of inbred strains, leading to a mixed background or congenic mice when crossed with C57BL/6 mice. Depending on the number of backcrosses and breeding strategies, genomic segments from 129-derived ESCs can be introgressed into the C57BL/6 genome, establishing a unique genetic makeup that needs characterization in order to obtain valid conclusions from experiments using GEM lines. Currently, SNP genotyping is used to detect the extent of 129-derived ESC genome introgression into C57BL/6 recipients; however, it fails to detect novel/rare variants.

RESULTS

Here, we present a computational pipeline implemented in the Galaxy platform and in BASH/R script to determine genetic introgression of GEM using next generation sequencing data (NGS), such as whole genome sequencing (WGS), whole exome sequencing (WES) and RNA-Seq. The pipeline includes strategies to uncover variants linked to a targeted locus, genome-wide variant visualization, and the identification of potential modifier genes. Although these methods apply to congenic mice, they can also be used to describe variants fixed by genetic drift. As a proof of principle, we analyzed publicly available RNA-Seq data from five congenic knockout (KO) lines and our own RNA-Seq data from the Sall2 KO line. Additionally, we performed target validation using several genetics approaches.

CONCLUSIONS

We revealed the impact of the 129-derived ESC genome introgression on gene expression, predicted potential modifier genes, and identified potential phenotypic interference in KO lines. Our results demonstrate that our new approach is an effective method to determine genetic introgression of GEM.

Essential role of polymerases for assay performance - Impact of polymerase replacement in a well-established assay

The quantitative real-time polymerase chain reaction (qPCR) is one of the most commonly molecular methods used today. It is central to numerous assays that have since been developed and described around its optimization. The Listeria monocytogenes prfA qPCR assay has been studied in great detail and due to its comprehensive knowledge, excellent performance (sensitivity of one single copy), and internal amplification control, it represents a suitable test platform for qPCR examinations. In this study, we compared ten different polymerases (or ready-to-use mastermixes) as possible (economic) alternatives to our gold standard Platinum Taq polymerase. We sought to determine the reproducibility of these assays under modified conditions, which are realistic because published assays are frequently used with substituted polymerases. Surprisingly, there was no amplification at all with some of the tested polymerases, even although the internal amplification control worked well. Since adaptation of the thermal profile and of MgCl2 concentration could restore amplification, simple replacement of the polymerase can destroy a well-established assay leading up to >106-fold less analytical sensitivity. Further, validation using Poisson and PCR-Stop analyses revealed limits to some assay-polymerase combinations and emphasize the importance of validation.