Digital PCR






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Biomarkers Discovery & Circulating Nucleic Acids






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Advanced Molecular Diagnostics – 2






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Advanced Molecular Diagnostics – 1






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A Transcriptomic Approach To Ascertain Insights Into The Etiology Of Brown Trout Syndrome

Marc Young1, Jens-Eike Taeubert1, Juergen Geist2, Michael Pfaffl3, Ralph Kuehn1
1Unit of Molecular Zoology, Chair of Zoology, Department of Animal Science, Technische Universität München; 
2Aquatic Systems Biology Unit, Department of Ecology and Ecosystem Management, Technische Universität München; 
3Physiology Weihenstephan, Department of Animal Sciences, Centre of Life and Food Sciences, Technical University of Munich

Abstract
The brown trout syndrome (BTS) is an annually reoccurring disease that causes species-specific die-off of Salmo trutta in BTS-impacted pre-alpine rivers of Europe. Based on experimental evidence to date it is hypothesized that BTS is caused by a yet unidentified pathogen. To validate this working hypothesis, as well as to discern the type of pathogen likely to be responsible for BTS, gene expression analyses were conducted on Salmo trutta suffering from BTS in order to identify and investigate pathogen-specific immune responses during the progression of the disease. Salmo trutta obtained from a single source were held in flow-through tanks supplied with river water at two separate geographic locations (BTS-impacted river section / treatment group; Non-impacted river section / control group) along the same river for a duration of 98 days, with 3 individuals being sampled from each tank (treatment and control) in 7 day intervals (total 14 time points). In a first step, cDNA microarrays were employed in order to screen for regulated pathogen-specific immune responses. Spot identification, intensity quantification and quality control were carried out with the GenePix® Pro 6 software. Analysis of the microarray data were conducted using the open source R software package Linear Model for Microarray Data. Microarray data were background-subtracted using the Kooperberg model-based background correction function, normalized within arrays with the Loess method followed by normalization between arrays using the scale method. Linear models were fitted to the expression data and moderated t-statistics were computed using the empirical eBayes method. Features with a p-value ≤ 0.001 and log 2 -fold change ≥ 1 were deemed significant. The microarray analysis revealed that Salmo trutta suffering from BTS exhibit increased hepatic expression of important anti-viral genes. Subsequently in a second step relative gene expression for selected set of anti-viral genes were measured by RT-qPCR in order to construct more concise temporal gene expression patterns for anti-viral response genes in the liver of BTS-afflicted Salmo trutta over the course of the disease. The online Primer3 tool was used to design primers for selected anti-viral target genes as well as for three candidate reference genes. The web based comprehensive tool RefFinder identified Ubiquitin to be the most stable candidate reference gene. The ∆∆Ct method without efficiency correction as described by Pfaffl was used to determine the relative levels of mRNA expression for the anti-viral target genes normalized to the expression values of the reference gene Ubiquitin between treatment and control group for each time point. Both the microarray and the RT-qPCR analysis reveal that Salmo trutta suffering from BTS up-regulate different anti-viral genes throughout the progression of the BTS. Overall the results from the gene expression analyses suggest that BTS is caused by an unknown pathogenic virus.

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Challenges in Detection of Genetically Modified Organisms

Mojca Milavec, David Dobnik, Jana Žel
National Institute of Biology, Slovenia

Abstract
Genetically modified organisms (GMOs) are organisms in which the genetic material has been altered through the application of gene technology in a way that does not occur naturally through mating and/or natural recombination. There are considerable differences between countries in the adoption of this technology therefore labelling requirements have been set-up in many countries to facilitate international trade and to provide information to consumers. At present, quantitative real-time polymerase chain reaction (qPCR) is the most commonly accepted and used method for detection, identification and quantification of GMOs and considerable efforts have been invested in the understanding and critical evaluation of this technology. Nevertheless, there are challenges that should still be highlighted, such as inhibitors commonly present in different matrices, possible sequence mismatches, characteristics of taxon-specific genes and the quality of the reference materials, as these remain potential sources of measurement uncertainty. In addition, with steadily increasing number of GMOs developed and approved worldwide, the present qPCR methodology may no longer be fully suited to purpose. Several multiplex qPCR methods has already been developed and new approaches, such as digital PCR (dPCR), are being investigated.

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Transcriptomic Biomarkers in Food Safety: RNA Biomarkers against the abuse of growth promoters

Irmgard Riedmaier-Sprenzel, Melanie Spornraft, Michael, W. Pfaffl
TUM Physiology, Germany

Abstract
The use of growth promoting agents in animal husbandry is strictly forbidden the European Union. This ban is controlled within a strict control plan where residues of known growth promoting agents are identified using chromatographical methods in combination with mass spectrometry or may be screened by immuno assays. New designed xenobiotic agents or new modes of application, e.g. the administration of substance cocktails are not detectable with those methods. To ensure an efficient tracing of misused anabolic agents, new detection methods have to be developed. One promising way is to monitor the physiological effects of the given substances on the molecular level. The analysis of the transcriptome has already been shown to be a promising approach to detect the pharmacological action of a substance in different organs and matrices.
In a pilot study, RNA-Sequencing technology was used to screen for changes in the transcriptome of bovine liver caused by treatment with steroid hormones. Thereby a first biomarker pattern could be identified that enabled the separation of treated animals versus untreated animals using biostatistical clustering methods.
In order to test the drug dependence of such biomarkers, the identified biomarker candidates were validated in livers of veal calves treated with the b-agonist clenbuterol or another steroid hormone implant, respectively. Using the dynamic principal components analysis (PCA) algorithm, a biomarker signature could be detected that allowed the discrimination of treated and untreated individuals.
High throughput sequencing was also used to screen for additional biomarker candidates on mRNA and small RNA level in other target tissues. Those results indicate a high potential of transcriptomic biomarkers for the development of a new screening method that is independent of the given drug.

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Optimized library preparation for sequencing of whole bacterial genomes and low density microbiota by Illumina-based NGS

Mareike Wenning, Christopher Huptas, Manuela Schreiner, Siegfried Scherer
Lehrstuhl für Mikrobielle Ökologie, Zentralinstitut für Ernährungs- und Lebensmittelforschung, Technische Universität München

Abstract
Next-Generation Sequencing (NGS) technologies have paved the way for rapid and cost-efficient analyses of transcriptomes, microbiomes as well as de novo sequencing and re-sequencing of genomes. Library preparation is a crucial step in the generation of high quality data and may have a major impact on the success of data analysis and interpretability of data. Difficulties and improvements of two different sample preparation procedures are presented.
With the introduction of PCR-free library preparation procedures (LPPs) for de novo genome sequencing major improvements were made in comparison to the initial PCR containing LPPs, as PCR biases are largely reduced. In this study modified versions of the widely used Illumina TruSeq® DNA PCR-free library preparation protocol were developed that enable the generation of sequencing libraries with longer average insert sizes leading to substantial assembly improvements using SPAdes, which is currently one of the best performing assemblers with regard to bacterial de novo genome assembly. Through the introduced modifications, DNA quantitation by qPCR can be omitted and fewer reagents are consumed. Furthermore, the relationships between genomic GC content, average library insert size and sequencing quality were investigated.
For analyzing the biodiversity of microbiota, PCR is an indispensable step, as it is needed to amplify a fragment of the 16S rRNA gene, which is sequenced subsequently. Here, the extraction of DNA and use of adequate PCR conditions are of utmost importance. This is particularly true for microbial communities with low cell counts in difficult matrices. Raw milk microbiota are of high interest, but raw milk contains high fat and protein contents as well as high amounts of accompanying eukaryotic DNA originating from the cow’s somatic cells. We have developed a protocol for DNA extraction minimizing the content of somatic DNA and have performed different PCR strategies such as droplet digital PCR for analysing possible PCR bias. The data obtained show that DNA extraction out of low density communities requires substantial effort, but sequencing of such microbiota is possible.

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Comparison of Different RNA Sources to Examine the Lactating Bovine Mammary Gland Transcriptome using RNA-Sequencing

Angela Canovas1, Claudia Bevilacqua2, Gonzalo Rincon1, Pauline Brenaut2, Alma Islas-Trejo1, Russell C. Hovey1, Marion Boutinaud3, Caroline Morgenthaler2, Monica K. VanKlompenberg1, Juan F. Medrano1, Patrice D. Martin2
1Department of Animal Science, University of California-Davis, One Shields Avenue, Davis, 95616, CA, USA; 
2Institut National de la Recherche Agronomique, UMR 1313 Génétique animale et Biologie intégrative, F-78350 Jouy-en-Josas, France; 
3INRA, AGROCAMPUS OUEST, UMR1348 PEGASE, F-35590 Saint-Gilles, France

Abstract
The objective of the present study was to examine five different sources of RNA, namely mammary gland tissue (MGT), milk somatic cells (mSC), antibody-captured milk mammary epithelial cells (mMEC), milk fat globules (mFG) and laser microdissected mammary epithelial cells (LCMEC), to analyze the bovine mammary gland transcriptome, using RNA-Sequencing. Given the small amount of materials we started from, especially from mFG, mMEC and LCMEC, the five RNA preparations were amplified, using the Ribo-SPIA technology from the Ovation RNA-seq System (NuGEN, San Carlos, CA). Our results provide an objective assessment between invasive and non-invasive sampling methods to analyze and compare the transcriptome of mammary gland tissue and milk cells. This information is of value to choose the most appropriate sampling method for different research applications, to study specific physiological and health states during lactation. The simplest procedures to study the transcriptome associated with milk appears to be the isolation of total RNA directly from mSC or mFG from milk. Our results indicate that the mSC and mFG transcriptomes are representative of MGT and LCMEC, respectively, and can be used as effective and alternative samples to study mammary gland expression without the need to perform any tissue biopsy.

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RDML Consortium Meeting

Andreas Untergasser1,2
1University of Heidelberg, Germany; 
2On behalf of the RDML consortium

Abstract
RDML development is coordinated by the RDML consortium, a group of scientists, software developers and instrument manufacturers (http://www.rdml.org). The joined efforts resulted in improved versions 1.1 and 1.2. This consortium is not limited to its current members; it invites all interested parties to join the effort, by joining this RDML Consortium Meeting.

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