In November 2013, the ERA-Net ERASysAPP launched its first joint transnational call on «Transforming Systems Biology Knowledge into Applications» which aimed to encourage scientists from different countries and disciplines to collaborate and share resources across national borders.
The call focused mainly on application-oriented research approaches to tackle major scientific and societal challenges. The proposals covered a wide spectrum of topics within the area of Life Sciences and Biotechnology, from research in biological processes in animals, plants and microorganisms to health related aspects.
32 eligible proposals, involving 196 partners from 15 countries were submitted. The proposals were assessed in a one-step peer-review process involving internationally renowned experts. The top 7 proposals comprising more than 46 research groups from 10 countries were chosen to receive funding.
The projects encompass a broad range of topics, e.g. environmentally friendly techniques to meet the increasing worldwide demand for metals from sulphide ores, Viral replication with a view to obtain universal antivirals less prone to develop resistance and combined experimental and modelling approaches that exploit genome-scale models to identify global cancer-specific alterations.
List of funded projects:
|Mark Dopson||Linnaeus University||Sweden|
|Wolfgang Sand||University of Duisburg-Essen||Germany|
|Paul Wilmes||University of Luxembourg||Luxembourg|
|Igor Pivkin||Università della Svizzera italiana||Switzerland|
|Ansgar Poetsch||Ruhr University Bochum||Germany|
|Mikael Kubista||TATAA Biocenter AB, Göteborg||Sweden|
|Kjärstin Hagman Boström||Linnaeus University||Sweden|
Biomining is a biotechnological process carried out in many parts of the world that exploits acid loving microorganisms to extract metals from sulphide minerals. One industrial biomining method is called ‘heap bioleaching’ where typically copper containing minerals are piled into very large heaps, acid and microorganisms are added to the top and the soluble metal is collected at the heap base. The role of the different types of microbes in the process is to speed up metal solubilisation by oxidising ferrous iron to ferric and removing sulphur compounds that can accumulate on the mineral surface. Metals are most efficiently released from sulphide ores if the microorganisms form a thin layer, termed a ‘biofilm’, on the mineral surface. A crucial stage in bioleaching is how efficiently the microbes attach to the mineral. This project will test how rapidly a biofilm is formed and copper is released from the mineral by different combinations of microorganisms and the order that they are added. Data on the biological processes the microorganisms carry out will be used in computer modelling to suggest the best combination and order in which to add the different types of microbes. This in turn will increase the efficiency of industrial bioleaching by reducing the time between when a heap is built and when the first metals are collected.
|Kiran Raosaheb Patil||European Molecular Biology Laboratory, Heidelberg||Germany|
|Uwe Sauer||Institute of Molecular Systems Biology, ETH Zurich||Switzerland|
|Ivica Letunic||Biobyte solutions GmbH, Heidelberg||Germany|
|Bas Teusink||VU University Amsterdam||The Netherlands|
|André Kelkkanen||Chalmers University of Technology, Gothenburg||Sweden|
|Rute Neves||Chr-Hansen A/S||Denmark|
|KjärsJens Nielsen||Chalmers University of Technology, Gothenburg||Sweden|
Microbial communities are ubiquitously found in nature, from soil to the human gut, and have direct implications for the environment, human health and biotechnology. Our understanding of the structure and function of these communities, however, has remained poor due to the lack of tools for discovering inter-species interactions. To address this gap, the SysMilk project will develop new experimental and computational technologies for microbial community analysis. The new technologies will be developed and tested by using kefir, a natural fermented milk drink, as a model system. The SysMilk consortium includes four top academic research institutes, a small-scale company and a large industry that is leading the sector of fermented milk products. This multi-disciplinary constellation will enable efficient transfer of the SysMilk technology to the dairy products industry, facilitating the design of customized yogurt starter cultures.
|Lars Kaderali||Technische Universität Dresden||Germany|
|Marco Binder||German Cancer Research Center, Heidelberg||Germany|
|Eric Snijder||Leiden University Medical Center||The Netherlands|
|Frank Van Kuppeveld||Utrecht University||The Netherlands|
|Ralf Bartenschlager||University of Heidelberg||Germany|
|Niko Beerenwinkel||ETH Zurich, Basel||Switzerland|
|Antreas Afantitis||NovaMechanics Ltd., Nicosia||Cyprus|
|Jörg Rauch||technology transfer heidelberg GmbH||Germany|
SysVirDrug is a translational project, aiming to establish a strategy for the development of true “antivirotics”– drugs that, analogously to antibiotics (which are effective only against bacterial infection), can be used to treat viral infections caused by a whole group of different viruses. SysVirDrug focuses on positive-strand RNA viruses, a broad class of viruses that extends from every-day infections such as the common cold to life-threatening diseases such as hepatitis C, dengue fever and SARS. SysVirDrug brings together world leading virological groups with computational and mathematical experts, with the aim to identify most efficient drug targets with broad antiviral efficacy. As viruses make extensive use of host mechanisms for their own benefit, SysVirDrug focuses on host cell processes as targets for antiviral treatment. The consortium can build on large-scale screening experiments that have been conducted by the partner laboratories, using RNA interference. These experiments identify host processes that are hijacked by specific viruses during the infection. Such processes are potential targets for “antiviotic” drug design, if they are targets of a whole group of different viruses. The SysVirDrug consortium uses a combination of wetlab experiments, sophisticated bioinformatics approaches and mathematical and computational modelling to identify most efficient, broadly active anti-viral targets or combinations of targets, and strategies to interfere with these target mechanisms to treat the infection. Chemoinformatics approaches are then used to identify suitable drug molecules targeting the identified host cell processes, which are subsequently tested and – if successful – will be commercialized with the help of a technology transfer partner.
|Trygve Brautaset||terials and Chemistry, Trondheim||Norway|
|Julia Vorholt||ETH Zürich||Switzerland|
|Volker Wendisch||Bielefeld University||Germany|
|Jean-Charles Portais||INSA Toulouse||France|
|Nils Spidsøe||SINVENT AS||Norway|
Genetically engineered bacteria are widely used as cell factories for production of special, fine, bulk, and fuel chemicals. Industrial biotechnology mainly uses sugars and molasses as carbon source, and these raw materials are derived from plants demanding cultivable land which is more and more needed for human nutrition. Methanol is abundant and regarded as alternative highly attractive non-feed raw material in microbial bioprocesses. Methylotrophy, the ability of certain specialized bacteria to use methanol as carbon source for growth, bears the potential to build value from methanol through production of value-added chemicals. A systems-level understanding of bacteria is a prerequisite for their rational engineering and efficient use as cell factories in industrial biotechnology. The MetApp project goal is to gain systems-level understanding of evolutionary alternatives of bacterial methylotrophy to deduce and experimentally evaluate strategies for methanol-based production of sought-after chemicals.
|Ursula Klingmüller||German Cancer Research Center (DKFZ), Heidelberg||Germany|
|Jens Nielsen||Chalmers University of Technology||Sweden|
|Frank Bruggeman||VU University Amsterdam||The Netherlands|
|Daniel Seehofer||Charité University Medicine Berlin||Germany|
|Jens Timmer||University of Freiburg||Germany|
|Steven Tan||TTO VU University Amsterdam||The Netherlands|
|Iwan De Esch||Griffin Discoveries BV||The Netherlands|
Uncontrolled proliferation in cancer results from synergistic adaptations in metabolism and signalling. However, due to the complexity, coupling mechanisms between metabolism and signalling are difficult to assess and it remains to be clarified how they give rise to cooperative enhancement. As a proof of concept, we focus on liver cancer, and propose a combined experimental and modelling approach that exploits both, comprehensive genome-scale models to identify global, cancer-specific alterations as well as a more detailed integrative model that links glycolysis and signalling. We will develop standard operating procedures for combined quantitative studies of metabolism and signal transduction in healthy and cancer cells, elucidate alterations in signalling and gene expression causing glycolytic adaptations and predict cancer-cell selective drug combinations using mathematical modelling of healthy and cancer cells. The proposed approach will act as a model study for systems biology approaches to integrate metabolism and signalling in oncology and will open new avenues for the treatment of liver cancer.
|Eivind Almaas||Norwegian University of Science and Technology||Norway|
|Jonas Warringer||University of Gothenburg||Sweden|
|Kiran Patil||European Molecular Biology Laboratory||Germany|
|Albert Mas||Universitat Rovira i Virgili||Spain|
Industrial scale wine production is hampered by wine yeasts’ ability to fully use available nutrients in grape must. This leaves compounds in the wine that may reduce its quality, or that allow unwanted microorganisms to grow and produce foul tasting or unhealthy by-products. The economic losses associated with this problem are substantial. Starting from wine yeasts currently used by the industry, we will produce non-GMO wine yeasts with improved performance through a combination of laboratory work and computer modelling. We will test the best performing wine yeasts in actual wine production. Our approach will serve as a proof of concept for a new paradigm to improve properties of microorganisms of industrial importance in a fast, cheap and GMO-free manner.
|Maria von Korff||Heinrich Heine University, Düsseldorf||Germany|
|Christoforos Hadjicostis||University of Cyprus||Cyprus|
|Lennart Ljung||Linköping University||Sweden|
|Monika Spiller||Syngenta Seeds GmbH||Germany|
|Clemens Ostrowicz||University of Luxembourg||Luxembourg|
|Sigmar Lampe||University of Luxembourg||Luxembourg|
The circadian clock is an internal timing system that allows plants to predict daily and seasonal changes in light and temperature and thus to adapt photosynthesis, growth, and development to external conditions. The core oscillator is well understood in the model plant Arabidopsis, however, relatively little is known about the dynamic effects of the clock on agronomic behaviour of crop plants. We therefore propose to model the circadian clock of the important crop barley and its effects on the transcriptome, metabolome and phenotypic performance. To this end, we have adapted tools from the fields of Control Systems and Machine Learning to learn how species in complex networks regulate each other and how these regulations vary in response to genetic or environmental changes. Understanding the circadian clock of the model crop barley and its effects on important agronomic traits may have great impact on precision breeding of barley and related cereals.