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Session Chair: Michael W Pfaffl, Technical University of Munich, Germany
Location:HS 14 ZHG -- Lecture Hall 14
Towards a Universal Diagnostic Test for Infection Using Rapid Nanopore Metagenomics
Quadram Insitute Bioscience, United Kingdom
The rise in antimicrobial resistance (AMR) is predicted to cause 10 million deaths per year by 2050 unless steps are taken to prevent this looming crisis. Microbiological culture is the gold standard for the diagnosis of bacterial/fungal pathogens and antimicrobial resistance and takes 48 hours or longer. Hence, antibiotic prescriptions are rarely based on a definitive diagnosis and patients often receive inappropriate treatment. Rapid diagnostic tools are urgently required to guide appropriate antimicrobial therapy, thereby improving patient outcomes and slowing the development of AMR. In this talk, I will discuss the application of sequencing technology for the diagnosis of infection, focusing on rapid (~6hr) nanopore sequencing based clinical metagenomics.
MRNA As A Forensic Target - A Bridge Too Far?
Stephen Andrew Bustin
Anglia Ruskin University, United Kingdom
Individual human tissues are distinguished by distinctive RNA expression profiles, with the expression of many RNAs restricted to certain cell types only. Reverse transcription polymerase chain reaction (RT-PCR)-based assays are widely used in research and diagnostic applications to exploit this tissue-specificity for the identification of unique or aberrant cells. This feature has also led to an extensive evaluation of their potential to identify RNA transcripts that will reliably, sensitively and definitively identify tissues of origin in forensic casework applications. An analysis of the literature published by forensic scientists highlights a divergence of methodologies, protocols, reagents and interpretative models for forensic RNA studies. Disconcertingly, it also suggests the widespread application of protocols that are optimised for the analysis of DNA but are inappropriate for reliable RNA detection as well as the use of non-human and non-tissue-specific markers. Since the interpretation of RT-PCR-based results is dependent on the properties of the RNA as well as the variable characteristics of RT-PCR, this has serious consequences with regards to the robustness, consistency and reliability of any conclusions. A consensus on the most appropriate approach for reliable, accurate and meaningful RNA investigation as a forensic tool remains to be established.
HTPathwaySeq, a Novel Application for High-throughput RNA Sequencing Based Pathway Phenotyping
Pieter Mestdagh, Tom Maes, Manuel Luypaert, Nele Nys, Gert Van Peer, Ariane De Ganck, Carolina Fierro, Jan Hellemans, Jo Vandesompele
Different technologies support researchers in probing the transcriptome. The choice among these technologies is guided in part by the balance between the amount of data one wishes to obtain for a given sample and the number of samples being tested. Typically, these parameters are inversely correlated. At the opposite ends of this spectrum, deep RNA sequencing and qPCR yield in depth data for tens of samples starting at a total cost of at least 300€/sample or very directed information for thousands of samples at a cost below 10€ per sample, respectively. We here present HTPathwaySeq, a technology situated in the middle of this spectrum, tailored towards researchers looking for maximal molecular insights for their in vitrostudies.
At a cost below 100 EUR/sample, HTPathwaySeq processes 384 cell lysates with RNA seq to generate expression data analyzed at pathway level. Our data shows that shallow sequencing of crude cell lysates reproducibly detects over 5000 genes with at least 10 reads. Subsampling of deep sequencing datasets demonstrated that differential pathway analysis is largely unaffected when reducing the number of genes to this level. Consequently, reliable pathway insights can be obtained at high throughput and relatively low cost while not being limited to a predefined set of genes or pathways. In cell perturbation screenings (small molecules, RNAi, antisense or CRISPR), HTPathwaySeq can provide in depth information on the mode of action underlying the induced cellular phenotypes as well as molecular similarity scores to identify those perturbations acting similar to a reference condition or via shared molecular mechanisms. We will show results from a lead compound dose response study, illustrating the potential of HTPathwaySeq.
Expression Data Integration: Advancing Immuno-Oncology Target Discovery
Frank Staubli, Jana Sponarova, Stefan Bleuler, Philip Zimmermann
Nebion AG, Switzerland
Although genome-wide RNA expression analysis has become a routine tool in biomedical research, extracting valuable biological insight from thousands of published studies and underlying data remains a major challenge for two main reasons: the heterogeneity in annotations and technology, and the unreliable quality levels.
GENEVESTIGATOR is an analysis tool and database, containing manually curated gene expression data from public studies, making use of controlled vocabularies for several biological dimensions such as tissues, genotypes, diseases and treatments. To avoid bias in the results a strict quality control ensures to only integrate high quality samples and experiments into the database.
In this example study, we used GENEVESTIGATOR for 1. indication finding, 2. novel target predictions and 3. target validation for cancer immunotherapy as follows:
Profiled the expression of selected immune checkpoint surface molecules across hundreds of tumors and subtypes to indicate which cancer types could be suitable for similar immunotherapies.
Identified novel target genes that are co-regulated with known immune checkpoint targets across immune-oncology studies, for insights to which immunological pathways are affected.
Compared spatial expression profiles of targets, to validate their combinative advantage.
These studies show how GENEVESTIGATOR can effectively take advantage of the world’s high-quality expression data, and help identifying new targets and characterize expression patterns of targets across cancers.