How tech-savvy employees make the difference in core facilities: Recognizing core facility expertise with dedicated career tracks: Recognizing core facility expertise with dedicated career tracks.

Core facilities have a different mission than academic research labs. Accordingly, they require different career paths and structures.

Evaluation of quantitative miRNA expression platforms in the microRNA quality control (miRQC) study.

MicroRNAs are important negative regulators of protein-coding gene expression and have been studied intensively over the past years. Several measurement platforms have been developed to determine relative miRNA abundance in biological samples using different technologies such as small RNA sequencing, reverse transcription-quantitative PCR (RT-qPCR) and (microarray) hybridization. In this study, we systematically compared 12 commercially available platforms for analysis of microRNA expression. We measured an identical set of 20 standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples and synthetic spikes from microRNA family members with varying homology. We developed robust quality metrics to objectively assess platform performance in terms of reproducibility, sensitivity, accuracy, specificity and concordance of differential expression. The results indicate that each method has its strengths and weaknesses, which help to guide informed selection of a quantitative microRNA gene expression platform for particular study goals.

Target enrichment using parallel nanoliter quantitative PCR amplification.

BACKGROUND: Next generation targeted resequencing is replacing Sanger sequencing at high pace in routine genetic diagnosis. The need for well validated, high quality enrichment platforms to complement the bench-top next generation sequencing devices is high. RESULTS: We used the WaferGen Smartchip platform to perform highly parallelized PCR based target enrichment for a set of known cancer genes in a well characterized set of cancer cell lines from the NCI60 panel. Optimization of PCR assay design and cycling conditions resulted in a high enrichment efficiency. We provide proof of a high mutation rediscovery rate and have included technical replicates to enable SNP calling validation demonstrating the high reproducibility of our enrichment platform. CONCLUSIONS: Here we present our custom developed quantitative PCR based target enrichment platform. Using highly parallel nanoliter singleplex PCR reactions makes this a flexible and efficient platform. The high mutation validation rate shows this platform's promise as a targeted resequencing method for multi-gene routine sequencing diagnostics.

Evaluation of qPCR curve analysis methods for reliable biomarker discovery: bias, resolution, precision, and implications.

RNA transcripts such as mRNA or microRNA are frequently used as biomarkers to determine disease state or response to therapy. Reverse transcription (RT) in combination with quantitative PCR (qPCR) has become the method of choice to quantify small amounts of such RNA molecules. In parallel with the democratization of RT-qPCR and its increasing use in biomedical research or biomarker discovery, we witnessed a growth in the number of gene expression data analysis methods. Most of these methods are based on the principle that the position of the amplification curve with respect to the cycle-axis is a measure for the initial target quantity: the later the curve, the lower the target quantity. However, most methods differ in the mathematical algorithms used to determine this position, as well as in the way the efficiency of the PCR reaction (the fold increase of product per cycle) is determined and applied in the calculations. Moreover, there is dispute about whether the PCR efficiency is constant or continuously decreasing. Together this has lead to the development of different methods to analyze amplification curves. In published comparisons of these methods, available algorithms were typically applied in a restricted or outdated way, which does not do them justice. Therefore, we aimed at development of a framework for robust and unbiased assessment of curve analysis performance whereby various publicly available curve analysis methods were thoroughly compared using a previously published large clinical data set (Vermeulen et al., 2009) [11]. The original developers of these methods applied their algorithms and are co-author on this study. We assessed the curve analysis methods' impact on transcriptional biomarker identification in terms of expression level, statistical significance, and patient-classification accuracy. The concentration series per gene, together with data sets from unpublished technical performance experiments, were analyzed in order to assess the algorithms' precision, bias, and resolution. While large differences exist between methods when considering the technical performance experiments, most methods perform relatively well on the biomarker data. The data and the analysis results per method are made available to serve as benchmark for further development and evaluation of qPCR curve analysis methods (http://qPCRDataMethods.hfrc.nl).

Measurable impact of RNA quality on gene expression results from quantitative PCR.

Compromised RNA quality is suggested to lead to unreliable results in gene expression studies. Therefore, assessment of RNA integrity and purity is deemed essential prior to including samples in the analytical pipeline. This may be of particular importance when diagnostic, prognostic or therapeutic conclusions depend on such analyses. In this study, the comparative value of six RNA quality parameters was determined using a large panel of 740 primary tumour samples for which real-time quantitative PCR gene expression results were available. The tested parameters comprise of microfluidic capillary electrophoresis based 18S/28S rRNA ratio and RNA Quality Index value, HPRT1 5'-3' difference in quantification cycle (Cq) and HPRT1 3' Cq value based on a 5'/3' ratio mRNA integrity assay, the Cq value of expressed Alu repeat sequences and a normalization factor based on the mean expression level of four reference genes. Upon establishment of an innovative analytical framework to assess impact of RNA quality, we observed a measurable impact of RNA quality on the variation of the reference genes, on the significance of differential expression of prognostic marker genes between two cancer patient risk groups, and on risk classification performance using a multigene signature. This study forms the basis for further rational assessment of reverse transcription quantitative PCR based results in relation to RNA quality.

Unraveling the Molecular Basis of the Dystrophic Process in Limb-Girdle Muscular Dystrophy LGMD-R12 by Differential Gene Expression Profiles in Diseased and Healthy Muscles.

Limb-girdle muscular dystrophy R12 (LGMD-R12) is caused by two mutations in anoctamin-5 (ANO5). Our aim was to identify genes and pathways that underlie LGMD-R12 and explain differences in the molecular predisposition and susceptibility between three thigh muscles that are severely (semimembranosus), moderately (vastus lateralis) or mildly (rectus femoris) affected in this disease. We performed transcriptomics on these three muscles in 16 male LGMD-R12 patients and 15 age-matched male controls. Our results showed that LGMD-R12 dystrophic muscle is associated with the expression of genes indicative of fibroblast and adipocyte replacement, such as fibroadipogenic progenitors and immune cell infiltration, while muscle protein synthesis and metabolism were downregulated. Muscle degeneration was associated with an increase in genes involved in muscle injury and inflammation, and muscle repair/regeneration. Baseline differences between muscles in healthy individuals indicated that muscles that are the most affected by LGMD-R12 have the lowest expression of transcription factor networks involved in muscle (re)generation and satellite stem cell activation. Instead, they show relative high levels of fetal/embryonic myosins, all together indicating that muscles differ in their baseline regenerative potential. To conclude, we profiled the gene expression landscape in LGMD-R12, identified baseline differences in expression levels between differently affected muscles and characterized disease-associated changes.

How to do successful gene expression analysis using real-time PCR.

Reverse transcription quantitative PCR (RT-qPCR) is considered today as the gold standard for accurate, sensitive and fast measurement of gene expression. Unfortunately, what many users fail to appreciate is that numerous critical issues in the workflow need to be addressed before biologically meaningful and trustworthy conclusions can be drawn. Here, we review the entire workflow from the planning and preparation phase, over the actual real-time PCR cycling experiments to data-analysis and reporting steps. This process can be captured with the appropriate acronym PCR: plan/prepare, cycle and report. The key message is that quality assurance and quality control are essential throughout the entire RT-qPCR workflow; from living cells, over extraction of nucleic acids, storage, various enzymatic steps such as DNase treatment, reverse transcription and PCR amplification, to data-analysis and finally reporting.

External oligonucleotide standards enable cross laboratory comparison and exchange of real-time quantitative PCR data.

The quantitative polymerase chain reaction (qPCR) is widely utilized for gene expression analysis. However, the lack of robust strategies for cross laboratory data comparison hinders the ability to collaborate or perform large multicentre studies conducted at different sites. In this study we introduced and validated a workflow that employs universally applicable, quantifiable external oligonucleotide standards to address this question. Using the proposed standards and data-analysis procedure, we obtained a perfect concordance between expression values from eight different genes in 366 patient samples measured on three different qPCR instruments and matching software, reagents, plates and seals, demonstrating the power of this strategy to detect and correct inter-run variation and to enable exchange of data between different laboratories, even when not using the same qPCR platform.

Challenges in the Structural-Functional Characterization of Multidomain, Partially Disordered Proteins CBP and p300: Preparing Native Proteins and Developing Nanobody Tools.

The structural and functional characterization of large multidomain signaling proteins containing long disordered linker regions represents special methodological and conceptual challenges. These proteins show extreme structural heterogeneity and have complex posttranslational modification patterns, due to which traditional structural biology techniques provide results that are often difficult to interpret. As demonstrated through the example of two such multidomain proteins, CREB-binding protein (CBP) and its paralogue, p300, even the expression and purification of such proteins are compromised by their extreme proteolytic sensitivity and structural heterogeneity. In this chapter, we describe the effective expression of CBP and p300 in a eukaryotic host, Sf9 insect cells, followed by their tandem affinity purification based on two terminal tags to ensure their structural integrity. The major focus of this chapter is on the development of novel accessory tools, single-domain camelid antibodies (nanobodies), for structural-functional characterization. Specific nanobodies against full-length CBP and p300 can specifically target their different regions and can be used for their marking, labeling, and structural stabilization in a broad range of in vitro and in vivo studies. Here, we describe four high-affinity nanobodies binding to the KIX and the HAT domains, either mimicking known interacting partners or revealing new functionally relevant conformations. As immunization of llamas results in nanobody libraries with a great sequence variation, deep sequencing and interaction analysis with different regions of the proteins provide a novel approach toward developing a panel of specific nanobodies.

Long non-coding RNA expression profiling in the NCI60 cancer cell line panel using high-throughput RT-qPCR.

Long non-coding RNAs (lncRNAs) form a new class of RNA molecules implicated in various aspects of protein coding gene expression regulation. To study lncRNAs in cancer, we generated expression profiles for 1707 human lncRNAs in the NCI60 cancer cell line panel using a high-throughput nanowell RT-qPCR platform. We describe how qPCR assays were designed and validated and provide processed and normalized expression data for further analysis. Data quality is demonstrated by matching the lncRNA expression profiles with phenotypic and genomic characteristics of the cancer cell lines. This data set can be integrated with publicly available omics and pharmacological data sets to uncover novel associations between lncRNA expression and mRNA expression, miRNA expression, DNA copy number, protein coding gene mutation status or drug response.

Whole-genome RT-qPCR microRNA expression profiling.

MicroRNAs (miRNAs) are small noncoding RNA molecules that function as negative regulators of gene expression. They are essential components of virtually every biological process and deregulated miRNA expression has been reported in a multitude of human diseases including cancer. Owing to their small size (20-22 nucleotides), accurate quantification of miRNA expression is particularly challenging. In this chapter, we present different RT-qPCR technologies that enable whole genome miRNA expression quantification.

RNA pre-amplification enables large-scale RT-qPCR gene-expression studies on limiting sample amounts.

BACKGROUND: The quantitative polymerase chain reaction (qPCR) is a widely utilized method for gene-expression analysis. However, insufficient material often compromises large-scale gene-expression studies. The aim of this study is to evaluate an RNA pre-amplification method to produce micrograms of cDNA as input for qPCR. FINDINGS: The linear isothermal Ribo-SPIA pre-amplification method (WT-Ovation; NuGEN) was first evaluated by measuring the expression of 20 genes in RNA samples from six neuroblastoma cell lines and of 194 genes in two commercially available reference RNA samples before and after pre-amplification, and subsequently applied on a large panel of 738 RNA samples extracted from neuroblastoma tumours. All RNA samples were evaluated for RNA integrity and purity. Starting from 5 to 50 nanograms of total RNA the sample pre-amplification method was applied, generating approximately 5 microgams of cDNA, sufficient to measure more than 1000 target genes. The results obtained from this study show a constant yield of pre-amplified cDNA independent of the amount of input RNA; preservation of differential gene-expression after pre-amplification without introduction of substantial bias; no co-amplification of contaminating genomic DNA; no necessity to purify the pre-amplified material; and finally the importance of good RNA quality to enable pre-amplification. CONCLUSION: Application of this unbiased and easy to use sample pre-amplification technology offers great advantage to generate sufficient material for diagnostic and prognostic work-up and enables large-scale qPCR gene-expression studies using limited amounts of sample material.

Layer-by-layer coated digitally encoded microcarriers for quantification of proteins in serum and plasma.

The "layer-by-layer" (LbL) technology has been widely investigated for the coating of flat substrates and capsules with polyelectrolytes. In this study, LbL polyelectrolyte coatings applied at the surface of digitally encoded microcarriers were evaluated for the quantitative, sensitive, and simultaneous detection of proteins in complex biological samples like serum, plasma, and blood. LbL coated microcarriers were therefore coupled to capture antibodies, which were used as capture agents for the detection of tumor necrosis factor (TNF-alpha), P24, and follicle stimulating hormone (FSH). It was found that the LbL coatings did not disassemble upon incubating the microcarriers in serum and plasma. Also, nonspecific binding of target analytes to the LbL coating was not observed. We showed that the LbL coated microcarriers can reproducibly detect TNF-alpha, P24, and FSH down to the picogram per milliliter level, not only in buffer but also in serum and plasma samples. Microcarrier-to-microcarrier intratube variations were less then 30%, and interassay variations less than 8% were observed. This paper also shows evidence that the LbL coated digitally encoded microcarriers are ideally suited for assaying proteins in "whole" blood in microfluidic chips, which are of high interest for "point-of-care" diagnostics.

Multifunctional layer-by-layer coating of digitally encoded microparticles.

In the field of medical diagnostics there is a growing need for inexpensive, accurate, and quick "multiplexing" assays. By making use of encoded microparticles, such assays allow simultaneous determination of the presence of several analytes in a biological sample. The microparticles under investigation in this study are encoded by writing a digital dot or bar code in their central plane. This study evaluates to what extent a "multifunctional" coating can be applied around the digitally encoded microparticles by the layer-by-layer (LbL) technology. We show that a LbL coating containing CrO2 nanoparticles allows (a) an optimal (optical) readout of the dot and bar codes, (b) a perfect orientation of the microparticles, necessary to be able to read the code, and (c) an optimal coupling of capture probes to the surface of the microparticles.