Albert Kriegner

Methylation of ribosomal RNA by NSUN5 is a conserved mechanism modulating organismal lifespan

Several pathways modulating longevity and stress resistance converge on translation by targeting ribosomal proteins or initiation factors, but whether this involves modifications of ribosomal RNA is unclear. Here, we show that reduced levels of the conserved RNA methyltransferase NSUN5 increase the lifespan and stress resistance in yeast, worms and flies. Rcm1, the yeast homologue of NSUN5, methylates C2278 within a conserved region of 25S rRNA. Loss of Rcm1 alters the structural conformation of the ribosome in close proximity to C2278, as well as translational fidelity, and favours recruitment of a distinct subset of oxidative stress-responsive mRNAs into polysomes. Thus, rather than merely being a static molecular machine executing translation, the ribosome exhibits functional diversity by modification of just a single rRNA nucleotide, resulting in an alteration of organismal physiological behaviour, and linking rRNA-mediated translational regulation to modulation of lifespan, and differential stress response.

Identification of human pathogens isolated from blood using microarray hybridisation and signal pattern recognition

BackgroundPathogen identification in clinical routine is based on the cultivation of microbes with subsequent morphological and physiological characterisation lasting at least 24 hours. However, early and accurate identification is a crucial requisite for fast and optimally targeted antimicrobial treatment. Molecular biology based techniques allow fast identification, however discrimination of very closely related species remains still difficult.ResultsA molecular approach is presented for the rapid identification of pathogens combining PCR amplification with microarray detection. The DNA chip comprises oligonucleotide capture probes for 25 different pathogens including Gram positive cocci, the most frequently encountered genera of Enterobacteriaceae, non-fermenter and clinical relevant Candida species. The observed detection limits varied from 10 cells (e.g. E. coli) to 105 cells (S. aureus) per mL artificially spiked blood. Thus the current low sensitivity for some species still represents a barrier for clinical application. Successful discrimination of closely related species was achieved by a signal pattern recognition approach based on the k-nearest-neighbour method. A prototype software providing this statistical evaluation was developed, allowing correct identification in 100 % of the cases at the genus and in 96.7 % at the species level (n = 241).ConclusionThe newly developed molecular assay can be carried out within 6 hours in a research laboratory from pathogen isolation to species identification. From our results we conclude that DNA microarrays can be a useful tool for rapid identification of closely related pathogens particularly when the protocols are adapted to the special clinical scenarios.

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.

Monitoring of technical variation in quantitative high-throughput datasets.

High-dimensional datasets can be confounded by variation from technical sources, such as batches. Undetected batch effects can have severe consequences for the validity of a studys conclusion(s). We evaluate high-throughput RNAseq and miRNAseq as well as DNA methylation and gene expression microarray datasets, mainly from the Cancer Genome Atlas (TCGA) project, in respect to technical and biological annotations. We observe technical bias in these datasets and discuss corrective interventions. We then suggest a general procedure to control study design, detect technical bias using linear regression of principal components, correct for batch effects, and re-evaluate principal components. This procedure is implemented in the R package swamp, and as graphical user interface software. In conclusion, high-throughput platforms that generate continuous measurements are sensitive to various forms of technical bias. For such data, monitoring of technical variation is an important analysis step.

Characterization of the drugged human genome

Human drug targets are a part of our genome of special relevance to human disease. However, the number and nature of drug target genes has not yet been conclusively assessed. We analyzed involvement in biochemical functions, biological processes and pathways, with chromosome, cellular and tissue distribution of the 392 human drug targets collected in DrugBank. Comparison with the whole human genome reveals their scarcely diverse characteristics, largely dominated by rhodopsin-like 7 transmembrane receptors involved in the neuroactive ligand-receptor interaction pathway and located in the plasma membrane. Drug target genes are frequently expressed in multiple tissues, suggesting drug application in distinct disease classes. Intersections with other clinically relevant gene sets, such as the Mendelian disorder-linked genes and various molecular cancer signatures, are discussed.

The Influence of Gender, Age, and RET Polymorphisms on C-Cell Hyperplasia and Medullary Thyroid Carcinoma

BACKGROUND RET germline mutations predispose to the development of hereditary medullary thyroid carcinoma (hMTC). Several single nucleotide polymorphisms (SNPs) are described associated with sporadic MTC (sMTC). However, the findings regarding their influence on the clinical course and biological behavior of this disorder are discordant. To clarify the contradictory findings, we studied the association of certain SNPs considering age, gender, and histopathology in a large Austrian cohort with C-cell hyperplasia (CCH) and MTC. METHODS Genotyping of SNPs located in RET codons 691, 769, 836, and 904 from 199 patients with MTC and CCH (basal calcitonin > 10 pg/mL, pentagastrin stimulated > 100 pg/mL) was performed, and the results were analyzed considering gender, age at diagnosis, and histopathology. RESULTS No significant difference of SNP frequencies was found in the study patients versus normal controls. In sMTC and sporadic CCH (sCCH) no significant association of SNP frequency with the age at diagnosis was found. In patients with sporadic C-cell disease (sCCH and sMTC), 3.7 times more males than females suffered synchronously from papillary or follicular thyroid cancer (20/97 [20.6%] males; 3/54 [5.6%] females; p = 0.02). sCCH was revealed more frequently in males (89/97, 91.7%) than in females (27/54, 50%; p = 10(-8)). In contrast to males, the ratio of CCH to total C-cell disease was significantly higher in females with hereditary (26/32, 81%) compared to those with sporadic disease (27/54, 50%; p = 0.006). CONCLUSIONS In this study RET SNPs had no clinical impact on the development of sporadic C-cell disease when the age of diagnosis or gender is considered. C-cell disease seems to predispose males to the development of papillary and follicular thyroid cancer. In addition, at least in females with CCH RET germline mutation, screening is recommended even if the family history is negative for MTC.

DNA methylation testing and marker validation using PCR: diagnostic applications.

DNA methylation provides a fundamental epigenetic mechanism to establish and promote cell-specific gene-expression patterns, which are inherited by subsequent cell generations. Thus, the epigenome determines the differentiation into a cell lineage but can also program cells to become abnormal or malignant. In humans, different germline and somatic diseases have been linked to faulty DNA methylation. In this article, we will discuss the available PCR-based technologies to assess differences in DNA methylation levels mainly affecting 5-methylcytosine in the CpG dinucleotide context in hereditary syndromal and somatic pathological conditions. We will discuss some of the current diagnostic applications and provide an outlook on how DNA methylation-based biomarkers might provide novel tools for diagnosis, prognosis or patient stratification for diseases such as cancer.

RGG: A general GUI Framework for R scripts

BackgroundR is the leading open source statistics software with a vast number of biostatistical and bioinformatical analysis packages. To exploit the advantages of R, extensive scripting/programming skills are required.ResultsWe have developed a software tool called R GUI Generator (RGG) which enables the easy generation of Graphical User Interfaces (GUIs) for the programming language R by adding a few Extensible Markup Language (XML) – tags. RGG consists of an XML-based GUI definition language and a Java-based GUI engine. GUIs are generated in runtime from defined GUI tags that are embedded into the R script. User-GUI input is returned to the R code and replaces the XML-tags. RGG files can be developed using any text editor. The current version of RGG is available as a stand-alone software (RGGRunner) and as a plug-in for JGR.ConclusionRGG is a general GUI framework for R that has the potential to introduce R statistics (R packages, built-in functions and scripts) to users with limited programming skills and helps to bridge the gap between R developers and GUI-dependent users. RGG aims to abstract the GUI development from individual GUI toolkits by using an XML-based GUI definition language. Thus RGG can be easily integrated in any software. The RGG project further includes the development of a web-based repository for RGG-GUIs. RGG is an open source project licensed under the Lesser General Public License (LGPL) and can be downloaded freely at http://rgg.r-forge.r-project.org

MSP-HTPrimer: a high-throughput primer design tool to improve assay design for DNA methylation analysis in epigenetics

BackgroundBisulfite (BS) conversion-based and methylation-sensitive restriction enzyme (MSRE)-based PCR methods have been the most commonly used techniques for locus-specific DNA methylation analysis. However, both methods have advantages and limitations. Thus, an integrated approach would be extremely useful to quantify the DNA methylation status successfully with great sensitivity and specificity. Designing specific and optimized primers for target regions is the most critical and challenging step in obtaining the adequate DNA methylation results using PCR-based methods. Currently, no integrated, optimized, and high-throughput methylation-specific primer design software methods are available for both BS- and MSRE-based methods. Therefore an integrated, powerful, and easy-to-use methylation-specific primer design pipeline with great accuracy and success rate will be very useful.ResultsWe have developed a new web-based pipeline, called MSP-HTPrimer, to design primers pairs for MSP, BSP, pyrosequencing, COBRA, and MSRE assays on both genomic strands. First, our pipeline converts all target sequences into bisulfite-treated templates for both forward and reverse strand and designs all possible primer pairs, followed by filtering for single nucleotide polymorphisms (SNPs) and known repeat regions. Next, each primer pairs are annotated with the upstream and downstream RefSeq genes, CpG island, and cut sites (for COBRA and MSRE). Finally, MSP-HTPrimer selects specific primers from both strands based on custom and user-defined hierarchical selection criteria. MSP-HTPrimer produces a primer pair summary output table in TXT and HTML format for display and UCSC custom tracks for resulting primer pairs in GTF format.ConclusionsMSP-HTPrimer is an integrated, web-based, and high-throughput pipeline and has no limitation on the number and size of target sequences and designs MSP, BSP, pyrosequencing, COBRA, and MSRE assays. It is the only pipeline, which automatically designs primers on both genomic strands to increase the success rate. It is a standalone web-based pipeline, which is fully configured within a virtual machine and thus can be readily used without any configuration. We have experimentally validated primer pairs designed by our pipeline and shown a very high success rate of primer pairs: out of 66 BSP primer pairs, 63 were successfully validated without any further optimization step and using the same qPCR conditions. The MSP-HTPrimer pipeline is freely available from http://sourceforge.net/p/msp-htprimer.

ClinQC: a tool for quality control and cleaning of Sanger and NGS data in clinical research

BackgroundTraditional Sanger sequencing has been used as a gold standard method for genetic testing in clinic to perform single gene test, which has been a cumbersome and expensive method to test several genes in heterogeneous disease such as cancer. With the advent of Next Generation Sequencing technologies, which produce data on unprecedented speed in a cost effective manner have overcome the limitation of Sanger sequencing. Therefore, for the efficient and affordable genetic testing, Next Generation Sequencing has been used as a complementary method with Sanger sequencing for disease causing mutation identification and confirmation in clinical research. However, in order to identify the potential disease causing mutations with great sensitivity and specificity it is essential to ensure high quality sequencing data. Therefore, integrated software tools are lacking which can analyze Sanger and NGS data together and eliminate platform specific sequencing errors, low quality reads and support the analysis of several sample/patients data set in a single run.ResultsWe have developed ClinQC, a flexible and user-friendly pipeline for format conversion, quality control, trimming and filtering of raw sequencing data generated from Sanger sequencing and three NGS sequencing platforms including Illumina, 454 and Ion Torrent. First, ClinQC convert input read files from their native formats to a common FASTQ format and remove adapters, and PCR primers. Next, it split bar-coded samples, filter duplicates, contamination and low quality sequences and generates a QC report. ClinQC output high quality reads in FASTQ format with Sanger quality encoding, which can be directly used in down-stream analysis. It can analyze hundreds of sample/patients data in a single run and generate unified output files for both Sanger and NGS sequencing data. Our tool is expected to be very useful for quality control and format conversion of Sanger and NGS data to facilitate improved downstream analysis and mutation screening.ConclusionsClinQC is a powerful and easy to handle pipeline for quality control and trimming in clinical research. ClinQC is written in Python with multiprocessing capability, run on all major operating systems and is available at https://sourceforge.net/projects/clinqc.