Latest SCI publications
AQUASAFE: Establishing water safety monitoring for tomorrow – genetic faecal marker diagnostics for detection and tracking of contamination
Research project (§ 26 & § 27)
Duration : 2017-09-01 - 2019-08-31
Molecular faecal pollution diagnostics, based on the detection of genetic faecal microbial source tracking (MST) markers, is about to revolutionise water quality testing. Such applications have been mainly focusing within the fields of recreational water quality monitoring, shellfish production, and maximum daily load monitoring. Scientific knowledge on the application of genetic faecal MST marker diagnostics, to support drinking water supply management and water safety planning, is hardly available yet. The proposed translational research project is going to establish the basic scientific knowledge needed to apply and further develop cutting edge genetic faecal marker diagnostics for quality testing to support water safety plans of drinking water supplies of tomorrow. Genetic faecal MST markers are supposed to extend current monitoring practices based on standard faecal indicator bacteria (SFIB) E. coli and enterococci in order to identify potential contamination sources for elimination or minimisation, and, to bridge the gap between traditional faecal pollution monitoring and microbial risk assessment. However, molecular diagnostics with adequate faecal-source specificity and faecal –source sensitivity is considered a key prerequisite for these applications. A new tiered application strategy for drinking water resources monitoring, based on the combination of bacterial and mitochondrial genetic faecal MST markers, is proposed. The new strategy will systematically be evaluated by means of relevant faecal pollution sources, representative water resources in Lower Austria, and important disinfection processes. To enable comparisons to traditional methods investigations will be complemented by SFIB and total cell count analysis. Chemical markers will be evaluated to support genetic MST diagnostics. The topic “Intelligent Indication Systems and Diagnostics” has been defined as prioritised research area within the recent FTI strategy (Programme for Research, Technology & Innovation for Lower Austria). The submitted research proposal is thus directly contributing to the adopted FTI strategy. The translational research project will stimulate sustainable collaborations between the Karl Landsteiner University, the well-established Center for Analytic Chemistry at IFA Tulln and the Interuniversity Cooperation Centre for Water and Health, a research centre to pioneer cutting edge water quality research. Furthermore, the project will directly collaborate with EVN Wasser GesmbH, the leading Lower Austrian drinking water supplier. The project will thus directly establish links between cutting edge water research and activities of a leading drinking water supplier to support the realization of water safety management of the future. Joint collaboration between these excellent partners in research and management will contribute to a further establishment of Lower Austria as a leading region in the water sector within the Danube and Central European Region.
Research project (§ 26 & § 27)
Duration : 2017-01-01 - 2019-12-31
Fungi are responsible for the production of many natural products as a result of the use of various biosynthetic gene clusters and pathways. Although numerous of these products are nowadays widely exploited by the biotech and pharmaceutical industry, two main challenges limit the access to new compounds: i) the inability to cultivate diverse producers of natural products in the laboratory and, ii) the fact that a majority of secondary metabolite biosynthesis gene clusters are silent under standard laboratory conditions. To overcome this obstacle, the current project makes use of fungal strains, which are deficient in the gene encoding the recently discovered transcription factor Xylanase promoter binding protein 1 (Xpp1). Xpp1 can be found in various fungi and is functioning as a pleiotropic regulator of secondary metabolism and is involved in the synthesis of small biomolecules. Based on these findings the major aims of the curent project, which is coordinated by Prof. Mach from the Vienna University of Technology is to i) elucidate the regulon of Xpp1 in Trichoderma reesei ii) to analyze the regulatory function of Xpp1 in other other biotechnologically and agriculturally relevant fungal species iii) investigate the molecular mechanisms behind Xpp1 exerting it regulatory function in secondary metabolism Our group will contribute to the project by stable isotope based metabolomics approaches, the untargeted screening of novel fungal secondary metabolites and the annotation of their chemical structure.
Research project (§ 26 & § 27)
Duration : 2016-10-01 - 2018-09-30
Untargeted metabolomics research is the study of the highly complex inventory of low-molecular-weight compounds in biological systems. Currently, some of the still unsolved challenges in untargeted metabolomics research are the automated, computer-aided processing and interpretation of the acquired raw analytical data, which consists of the mass-to-charge ratio (m/z) and retention time (RT) for each detected metabolite. Based on our successful strategy to use SIL to advance the field of LC-HRMS based untargeted metabolomics, the proposed work will focus on the development of cutting-edge strategies and novel software solutions for enhanced metabolomics research. The following issues shall be addressed: A) combination of different labeling experiments for comprehensive metabolite annotation, B) the simultaneous use of more than one labeling isotope at once to support more complex experimental setups as well as C) the detection of non-standard isotope patterns from more than one tracer compound incorporated into a single biotransformation product. The presented 2-years research proposal has the following five major goals: 1. Development of a novel data processing algorithm for the detection of very low abundant metabolites that are currently misinterpreted as noise by most data processing tools 2. Development of a method and software tool for multi-element labeling experiments to improve global metabolite detection and annotation 3. Development of a software tool for the detection of multi-element and multi-tracer biotransformation products 4. Implementation of a curated metabolite database and the use of metabolic networking for untargeted metabolite identification 5. Application of the developed software tools and workflows to untargeted metabolomics experiments, ad-hoc custom data processing solutions and dissemination of scientific results