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Validation of Collection and Extraction Methods of Saliva for Use in Biomarker Research
Sarah Hurst, Research Assistant Professor, South College School of Pharmacy
Regarding personalized medicine, there is increasing interest in biomarker research as these specific genes and/or proteins can be used to identify people who are at risk of a disease years before symptoms appear. Therefore, one of the most important goals is to develop and validate biomarkers that can detect and identify diseases early. Moreover, the use of saliva collection to investigate biomarkers is growing in popularity as this method is inexpensive, non-invasive, and easy to process. As this process is relatively new and still not widely utilized, we tested two methods of saliva collection using different collection vessels and well as multiple RNA, DNA, and protein extraction kits/techniques. Based on the sample collected (n=12), we conclude that there were significant differences in the quality of RNA based on collection tube and kit used. When we tested differences in the methods, tubes and kits, there were no significant differences in DNA quantity and quality. Furthermore, we did see significant differences in the quantity and quality of protein based on the collection method, tube, and technique employed. All of our results support the use of saliva collection as a means to investigate biomarkers for identifying individuals at risk of developing future diseases.
Development of a handheld MDx & DNA sequencing device and the Internet of Life
Maggie Love, Chief Scientific Officer & co-founder, QuantuMDx Group Limited
Despite dramatic advances in the fields of DNA sequencing & MDx, capillary electrophoresis (CE) is still routinely used for targeted sequencing and costly PCR devices remain the work-horse of the MDx laboratory. QuantuMDx is developing a mobile, handheld DNA sequencing device for infectious disease and some PGx applications. We expect to roll these devices out throughout resource limited areas and networking the disease data in real-time, enabling a real-time epidemiology platform we call 'The Internet of Life'™.
The device specifications were informed by two years in Cape Town observing the obstacles faced by mobile TB & HIV clinics, and proprietary sample preparation, amplification and sequencing technologies have been developed based on co-founder Jonathan O’Halloran’s inventions in his garage lab. QuantuMDx has now grown to over 40 people, with a research base in Newcastle, UK and offices in USA and Singapore. The technology is in an alpha format and a handheld beta device will be available for trials in 2014.
Biomarkers derived from high-throughput data: how can Systems Biology help? malaria vaccines case study
Teresa Sardon, Head of Analytical Services, Anaxomics
Finding biomarker panels offers many potential solutions, which increase with the number of considered molecules. It is not only computationally intensive, but also frequently a challenging task, as most of the found combinations lack generalization power, i.e. they cannot be used as only biomarkers at the conditions which they are meant to specifically signal. In order to tackle this problem, Anaxomics applied its systems biology-based technology, named Therapeutic Performance Mapping System (TPMS), to develop an innovative approach in the frame of SysMalVac [1], a European-level project researching markers of immunity to malaria. TPMS creates mathematical models that simulate human physiology by integrating biological, pharmacological and medical information into the human interactome, using known stimulus-response pairs to train the models [2]. TPMS was used to identify biomarkers associated with a particular physiological state, analysing two malaria vaccines in order to design a tool able to predict whether a person will be protected from malaria after vaccination and to identify a biomarker signature indicative of this protection. Immunological read-outs and transcriptomic results from both trials and experimental data from non-human primates were used to build the TPMS mathematical models, which served to identify a preliminarily generalizing biomarker panel, currently being validated.
Proteomic Approaches for the Discovery, Detection and Quantitation of Novel Liver Fibrosis Biomarkers
Bevin Gangadharan, Research Associate, University of Oxford
Two-dimensional gel electrophoresis (2-DE) is often used to separate plasma or serum proteins in an attempt to identify novel disease biomarkers. A major problem with this approach is the presence of high abundant plasma/serum proteins which limit the detection of low abundance features. We show how we have used two novel proteomic approaches to identify new liver fibrosis biomarkers. Plasma samples from patients were analysed using 2-DE over a narrow pH 3-5.6 range, a range outside the pH of highly abundant albumin, transferrin and immunoglobulins. This is the first time the pH 3-5.6 range has been used to separate plasma by 2-DE and was found to be beneficial for biomarker discovery. In addition, we show how in-solution isoelectric focusing followed by SDS-PAGE is beneficial for identifying basic, high molecular weight protein biomarkers.
Immunoassays are currently used to detect and quantify biomarkers in the clinic. However, such assays can have several disadvantages such as the inability to detect degraded proteins if the antibody epitope is not intact, non-specific interactions giving rise to false positives, limited antibody availability and often these assays are time consuming. We have developed a fast, sensitive and robust antibody-free method to detect and quantify liver fibrosis biomarkers in human plasma/serum which overcomes all these disadvantages. Our method can detect any protein biomarker even if antibodies are unavailable and involves the use of a mass spectrometer with either selected reaction monitoring (SRM) or parallel reaction monitoring (PRM) to detect tryptic peptides and their fragments and so it does not matter if a protein is degraded. Unlike immunoassays which are restricted on the number of biomarkers due to antibody cost, our method can successfully detect and quantify more than 50 biomarkers in a single 30 minute run. We propose to use this approach as a potential diagnostic tool to aid clinicians in determining the stage of liver fibrosis as well as in the quantitation of protein biomarkers for other diseases.
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