Project acronym 2-3-AUT
Project Surfaces, 3-manifolds and automorphism groups
Researcher (PI) Nathalie Wahl
Host Institution (HI) KOBENHAVNS UNIVERSITET
Call Details Starting Grant (StG), PE1, ERC-2009-StG
Summary The scientific goal of the proposal is to answer central questions related to diffeomorphism groups of manifolds of dimension 2 and 3, and to their deformation invariant analogs, the mapping class groups. While the classification of surfaces has been known for more than a century, their automorphism groups have yet to be fully understood. Even less is known about diffeomorphisms of 3-manifolds despite much interest, and the objects here have only been classified recently, by the breakthrough work of Perelman on the Poincar\'e and geometrization conjectures. In dimension 2, I will focus on the relationship between mapping class groups and topological conformal field theories, with applications to Hochschild homology. In dimension 3, I propose to compute the stable homology of classifying spaces of diffeomorphism groups and mapping class groups, as well as study the homotopy type of the space of diffeomorphisms. I propose moreover to establish homological stability theorems in the wider context of automorphism groups and more general families of groups. The project combines breakthrough methods from homotopy theory with methods from differential and geometric topology. The research team will consist of 3 PhD students, and 4 postdocs, which I will lead.
Summary
The scientific goal of the proposal is to answer central questions related to diffeomorphism groups of manifolds of dimension 2 and 3, and to their deformation invariant analogs, the mapping class groups. While the classification of surfaces has been known for more than a century, their automorphism groups have yet to be fully understood. Even less is known about diffeomorphisms of 3-manifolds despite much interest, and the objects here have only been classified recently, by the breakthrough work of Perelman on the Poincar\'e and geometrization conjectures. In dimension 2, I will focus on the relationship between mapping class groups and topological conformal field theories, with applications to Hochschild homology. In dimension 3, I propose to compute the stable homology of classifying spaces of diffeomorphism groups and mapping class groups, as well as study the homotopy type of the space of diffeomorphisms. I propose moreover to establish homological stability theorems in the wider context of automorphism groups and more general families of groups. The project combines breakthrough methods from homotopy theory with methods from differential and geometric topology. The research team will consist of 3 PhD students, and 4 postdocs, which I will lead.
Max ERC Funding
724 992 €
Duration
Start date: 2009-11-01, End date: 2014-10-31
Project acronym 3S-BTMUC
Project Soft, Slimy, Sliding Interfaces: Biotribological Properties of Mucins and Mucus gels
Researcher (PI) Seunghwan Lee
Host Institution (HI) DANMARKS TEKNISKE UNIVERSITET
Call Details Starting Grant (StG), LS9, ERC-2010-StG_20091118
Summary Mucins are a family of high-molecular-weight glycoproteins and a major macromolecular constituent in slimy mucus gels that are covering the surface of internal biological tissues. A primary role of mucus gels in biological systems is known to be the protection and lubrication of underlying epithelial cell surfaces. This is intuitively well appreciated by both science community and the public, and yet detailed lubrication properties of mucins and mucus gels have remained largely unexplored to date. Detailed and systematic understanding of the lubrication mechanism of mucus gels is significant from many angles; firstly, lubricity of mucus gels is closely related with fundamental functions of various human organs, such as eye blinking, mastication in oral cavity, swallowing through esophagus, digestion in stomach, breathing through air way and respiratory organs, and thus often indicates the health state of those organs. Furthermore, for the application of various tissue-contacting devices or personal care products, e.g. catheters, endoscopes, and contact lenses, mucus gel layer is the first counter surface that comes into the mechanical and tribological contacts with them. Finally, remarkable lubricating performance by mucins and mucus gels in biological systems may provide many useful and possibly innovative hints in utilizing water as base lubricant for man-made engineering systems. This project thus proposes to carry out a 5 year research program focusing on exploring the lubricity of mucins and mucus gels by combining a broad range of experimental approaches in biology and tribology.
Summary
Mucins are a family of high-molecular-weight glycoproteins and a major macromolecular constituent in slimy mucus gels that are covering the surface of internal biological tissues. A primary role of mucus gels in biological systems is known to be the protection and lubrication of underlying epithelial cell surfaces. This is intuitively well appreciated by both science community and the public, and yet detailed lubrication properties of mucins and mucus gels have remained largely unexplored to date. Detailed and systematic understanding of the lubrication mechanism of mucus gels is significant from many angles; firstly, lubricity of mucus gels is closely related with fundamental functions of various human organs, such as eye blinking, mastication in oral cavity, swallowing through esophagus, digestion in stomach, breathing through air way and respiratory organs, and thus often indicates the health state of those organs. Furthermore, for the application of various tissue-contacting devices or personal care products, e.g. catheters, endoscopes, and contact lenses, mucus gel layer is the first counter surface that comes into the mechanical and tribological contacts with them. Finally, remarkable lubricating performance by mucins and mucus gels in biological systems may provide many useful and possibly innovative hints in utilizing water as base lubricant for man-made engineering systems. This project thus proposes to carry out a 5 year research program focusing on exploring the lubricity of mucins and mucus gels by combining a broad range of experimental approaches in biology and tribology.
Max ERC Funding
1 432 920 €
Duration
Start date: 2011-04-01, End date: 2016-03-31
Project acronym A-DATADRIVE-B
Project Advanced Data-Driven Black-box modelling
Researcher (PI) Johan Adelia K Suykens
Host Institution (HI) KATHOLIEKE UNIVERSITEIT LEUVEN
Call Details Advanced Grant (AdG), PE7, ERC-2011-ADG_20110209
Summary Making accurate predictions is a crucial factor in many systems (such as in modelling energy consumption, power load forecasting, traffic networks, process industry, environmental modelling, biomedicine, brain-machine interfaces) for cost savings, efficiency, health, safety and organizational purposes. In this proposal we aim at realizing a new generation of more advanced black-box modelling techniques for estimating predictive models from measured data. We will study different optimization modelling frameworks in order to obtain improved black-box modelling approaches. This will be done by specifying models through constrained optimization problems by studying different candidate core models (parametric models, support vector machines and kernel methods) together with additional sets of constraints and regularization mechanisms. Different candidate mathematical frameworks will be considered with models that possess primal and (Lagrange) dual model representations, functional analysis in reproducing kernel Hilbert spaces, operator splitting and optimization in Banach spaces. Several aspects that are relevant to black-box models will be studied including incorporation of prior knowledge, structured dynamical systems, tensorial data representations, interpretability and sparsity, and general purpose optimization algorithms. The methods should be suitable for handling larger data sets and high dimensional input spaces. The final goal is also to realize a next generation software tool (including symbolic generation of models and handling different supervised and unsupervised learning tasks, static and dynamic systems) that can be generically applied to data from different application areas. The proposal A-DATADRIVE-B aims at getting end-users connected to the more advanced methods through a user-friendly data-driven black-box modelling tool. The methods and tool will be tested in connection to several real-life applications.
Summary
Making accurate predictions is a crucial factor in many systems (such as in modelling energy consumption, power load forecasting, traffic networks, process industry, environmental modelling, biomedicine, brain-machine interfaces) for cost savings, efficiency, health, safety and organizational purposes. In this proposal we aim at realizing a new generation of more advanced black-box modelling techniques for estimating predictive models from measured data. We will study different optimization modelling frameworks in order to obtain improved black-box modelling approaches. This will be done by specifying models through constrained optimization problems by studying different candidate core models (parametric models, support vector machines and kernel methods) together with additional sets of constraints and regularization mechanisms. Different candidate mathematical frameworks will be considered with models that possess primal and (Lagrange) dual model representations, functional analysis in reproducing kernel Hilbert spaces, operator splitting and optimization in Banach spaces. Several aspects that are relevant to black-box models will be studied including incorporation of prior knowledge, structured dynamical systems, tensorial data representations, interpretability and sparsity, and general purpose optimization algorithms. The methods should be suitable for handling larger data sets and high dimensional input spaces. The final goal is also to realize a next generation software tool (including symbolic generation of models and handling different supervised and unsupervised learning tasks, static and dynamic systems) that can be generically applied to data from different application areas. The proposal A-DATADRIVE-B aims at getting end-users connected to the more advanced methods through a user-friendly data-driven black-box modelling tool. The methods and tool will be tested in connection to several real-life applications.
Max ERC Funding
2 485 800 €
Duration
Start date: 2012-04-01, End date: 2017-03-31
Project acronym ACCOPT
Project ACelerated COnvex OPTimization
Researcher (PI) Yurii NESTEROV
Host Institution (HI) UNIVERSITE CATHOLIQUE DE LOUVAIN
Call Details Advanced Grant (AdG), PE1, ERC-2017-ADG
Summary The amazing rate of progress in the computer technologies and telecommunications presents many new challenges for Optimization Theory. New problems are usually very big in size, very special in structure and possibly have a distributed data support. This makes them unsolvable by the standard optimization methods. In these situations, old theoretical models, based on the hidden Black-Box information, cannot work. New theoretical and algorithmic solutions are urgently needed. In this project we will concentrate on development of fast optimization methods for problems of big and very big size. All the new methods will be endowed with provable efficiency guarantees for large classes of optimization problems, arising in practical applications. Our main tool is the acceleration technique developed for the standard Black-Box methods as applied to smooth convex functions. However, we will have to adapt it to deal with different situations.
The first line of development will be based on the smoothing technique as applied to a non-smooth functions. We propose to substantially extend this approach to generate approximate solutions in relative scale. The second line of research will be related to applying acceleration techniques to the second-order methods minimizing functions with sparse Hessians. Finally, we aim to develop fast gradient methods for huge-scale problems. The size of these problems is so big that even the usual vector operations are extremely expensive. Thus, we propose to develop new methods with sublinear iteration costs. In our approach, the main source for achieving improvements will be the proper use of problem structure.
Our overall aim is to be able to solve in a routine way many important problems, which currently look unsolvable. Moreover, the theoretical development of Convex Optimization will reach the state, when there is no gap between theory and practice: the theoretically most efficient methods will definitely outperform any homebred heuristics.
Summary
The amazing rate of progress in the computer technologies and telecommunications presents many new challenges for Optimization Theory. New problems are usually very big in size, very special in structure and possibly have a distributed data support. This makes them unsolvable by the standard optimization methods. In these situations, old theoretical models, based on the hidden Black-Box information, cannot work. New theoretical and algorithmic solutions are urgently needed. In this project we will concentrate on development of fast optimization methods for problems of big and very big size. All the new methods will be endowed with provable efficiency guarantees for large classes of optimization problems, arising in practical applications. Our main tool is the acceleration technique developed for the standard Black-Box methods as applied to smooth convex functions. However, we will have to adapt it to deal with different situations.
The first line of development will be based on the smoothing technique as applied to a non-smooth functions. We propose to substantially extend this approach to generate approximate solutions in relative scale. The second line of research will be related to applying acceleration techniques to the second-order methods minimizing functions with sparse Hessians. Finally, we aim to develop fast gradient methods for huge-scale problems. The size of these problems is so big that even the usual vector operations are extremely expensive. Thus, we propose to develop new methods with sublinear iteration costs. In our approach, the main source for achieving improvements will be the proper use of problem structure.
Our overall aim is to be able to solve in a routine way many important problems, which currently look unsolvable. Moreover, the theoretical development of Convex Optimization will reach the state, when there is no gap between theory and practice: the theoretically most efficient methods will definitely outperform any homebred heuristics.
Max ERC Funding
2 090 038 €
Duration
Start date: 2018-09-01, End date: 2023-08-31
Project acronym AFRIVAL
Project African river basins: catchment-scale carbon fluxes and transformations
Researcher (PI) Steven Bouillon
Host Institution (HI) KATHOLIEKE UNIVERSITEIT LEUVEN
Call Details Starting Grant (StG), PE10, ERC-2009-StG
Summary This proposal wishes to fundamentally improve our understanding of the role of tropical freshwater ecosystems in carbon (C) cycling on the catchment scale. It uses an unprecedented combination of state-of-the-art proxies such as stable isotope, 14C and biomarker signatures to characterize organic matter, radiogenic isotope signatures to determine particle residence times, as well as field measurements of relevant biogeochemical processes. We focus on tropical systems since there is a striking lack of data on such systems, even though riverine C transport is thought to be disproportionately high in tropical areas. Furthermore, the presence of landscape-scale contrasts in vegetation (in particular, C3 vs. C4 plants) are an important asset in the use of stable isotopes as natural tracers of C cycling processes on this scale. Freshwater ecosystems are an important component in the global C cycle, and the primary link between terrestrial and marine ecosystems. Recent estimates indicate that ~2 Pg C y-1 (Pg=Petagram) enter freshwater systems, i.e., about twice the estimated global terrestrial C sink. More than half of this is thought to be remineralized before it reaches the coastal zone, and for the Amazon basin this has even been suggested to be ~90% of the lateral C inputs. The question how general these patterns are is a matter of debate, and assessing the mechanisms determining the degree of processing versus transport of organic carbon in lakes and river systems is critical to further constrain their role in the global C cycle. This proposal provides an interdisciplinary approach to describe and quantify catchment-scale C transport and cycling in tropical river basins. Besides conceptual and methodological advances, and a significant expansion of our dataset on C processes in such systems, new data gathered in this project are likely to provide exciting and novel hypotheses on the functioning of freshwater systems and their linkage to the terrestrial C budget.
Summary
This proposal wishes to fundamentally improve our understanding of the role of tropical freshwater ecosystems in carbon (C) cycling on the catchment scale. It uses an unprecedented combination of state-of-the-art proxies such as stable isotope, 14C and biomarker signatures to characterize organic matter, radiogenic isotope signatures to determine particle residence times, as well as field measurements of relevant biogeochemical processes. We focus on tropical systems since there is a striking lack of data on such systems, even though riverine C transport is thought to be disproportionately high in tropical areas. Furthermore, the presence of landscape-scale contrasts in vegetation (in particular, C3 vs. C4 plants) are an important asset in the use of stable isotopes as natural tracers of C cycling processes on this scale. Freshwater ecosystems are an important component in the global C cycle, and the primary link between terrestrial and marine ecosystems. Recent estimates indicate that ~2 Pg C y-1 (Pg=Petagram) enter freshwater systems, i.e., about twice the estimated global terrestrial C sink. More than half of this is thought to be remineralized before it reaches the coastal zone, and for the Amazon basin this has even been suggested to be ~90% of the lateral C inputs. The question how general these patterns are is a matter of debate, and assessing the mechanisms determining the degree of processing versus transport of organic carbon in lakes and river systems is critical to further constrain their role in the global C cycle. This proposal provides an interdisciplinary approach to describe and quantify catchment-scale C transport and cycling in tropical river basins. Besides conceptual and methodological advances, and a significant expansion of our dataset on C processes in such systems, new data gathered in this project are likely to provide exciting and novel hypotheses on the functioning of freshwater systems and their linkage to the terrestrial C budget.
Max ERC Funding
1 745 262 €
Duration
Start date: 2009-10-01, End date: 2014-09-30
Project acronym AMAIZE
Project Atlas of leaf growth regulatory networks in MAIZE
Researcher (PI) Dirk, Gustaaf Inzé
Host Institution (HI) VIB
Call Details Advanced Grant (AdG), LS9, ERC-2013-ADG
Summary "Understanding how organisms regulate size is one of the most fascinating open questions in biology. The aim of the AMAIZE project is to unravel how growth of maize leaves is controlled. Maize leaf development offers great opportunities to study the dynamics of growth regulatory networks, essentially because leaf development is a linear system with cell division at the leaf basis followed by cell expansion and maturation. Furthermore, the growth zone is relatively large allowing easy access of tissues at different positions. Four different perturbations of maize leaf size will be analyzed with cellular resolution: wild-type and plants having larger leaves (as a consequence of GA20OX1 overexpression), both grown under either well-watered or mild drought conditions. Firstly, a 3D cellular map of the growth zone of the fourth leaf will be made. RNA-SEQ of three different tissues (adaxial- and abaxial epidermis; mesophyll) obtained by laser dissection with an interval of 2.5 mm along the growth zone will allow for the analysis of the transcriptome with high resolution. Additionally, the composition of fifty selected growth regulatory protein complexes and DNA targets of transcription factors will be determined with an interval of 5 mm along the growth zone. Computational methods will be used to construct comprehensive integrative maps of the cellular and molecular processes occurring along the growth zone. Finally, selected regulatory nodes of the growth regulatory networks will be further functionally analyzed using a transactivation system in maize.
AMAIZE opens up new perspectives for the identification of optimal growth regulatory networks that can be selected for by advanced breeding or for which more robust variants (e.g. reduced susceptibility to drought) can be obtained through genetic engineering. The ability to improve the growth of maize and in analogy other cereals could have a high impact in providing food security"
Summary
"Understanding how organisms regulate size is one of the most fascinating open questions in biology. The aim of the AMAIZE project is to unravel how growth of maize leaves is controlled. Maize leaf development offers great opportunities to study the dynamics of growth regulatory networks, essentially because leaf development is a linear system with cell division at the leaf basis followed by cell expansion and maturation. Furthermore, the growth zone is relatively large allowing easy access of tissues at different positions. Four different perturbations of maize leaf size will be analyzed with cellular resolution: wild-type and plants having larger leaves (as a consequence of GA20OX1 overexpression), both grown under either well-watered or mild drought conditions. Firstly, a 3D cellular map of the growth zone of the fourth leaf will be made. RNA-SEQ of three different tissues (adaxial- and abaxial epidermis; mesophyll) obtained by laser dissection with an interval of 2.5 mm along the growth zone will allow for the analysis of the transcriptome with high resolution. Additionally, the composition of fifty selected growth regulatory protein complexes and DNA targets of transcription factors will be determined with an interval of 5 mm along the growth zone. Computational methods will be used to construct comprehensive integrative maps of the cellular and molecular processes occurring along the growth zone. Finally, selected regulatory nodes of the growth regulatory networks will be further functionally analyzed using a transactivation system in maize.
AMAIZE opens up new perspectives for the identification of optimal growth regulatory networks that can be selected for by advanced breeding or for which more robust variants (e.g. reduced susceptibility to drought) can be obtained through genetic engineering. The ability to improve the growth of maize and in analogy other cereals could have a high impact in providing food security"
Max ERC Funding
2 418 429 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
Project acronym ArtHep
Project Hepatocytes-Like Microreactors for Liver Tissue Engineering
Researcher (PI) Brigitte STADLER
Host Institution (HI) AARHUS UNIVERSITET
Call Details Consolidator Grant (CoG), LS9, ERC-2018-COG
Summary The global epidemics of obesity and diabetes type 2 lead to higher abundancy of medical conditions like non-alcoholic fatty liver disease causing an increase in liver failure and demand for liver transplants. The shortage of donor organs and the insufficient success in tissue engineering to ex vivo grow complex organs like the liver is a global medical challenge.
ArtHep targets the assembly of hepatic-like tissue, consisting of biological and synthetic entities, mimicking the core structure elements and key functions of the liver. ArtHep comprises an entirely new concept in liver regeneration with multi-angled core impact: i) cell mimics are expected to reduce the pressure to obtain donor cells, ii) the integrated biocatalytic subunits are destined to take over tasks of the damaged liver slowing down the progress of liver damage, and iii) the matching micro-environment in the bioprinted tissue is anticipated to facilitate the connection between the transplant and the liver.
Success criteria of ArtHep include engineering enzyme-mimics, which can perform core biocatalytic conversions similar to the liver, the assembly of biocatalytic active subunits and their encapsulation in cell-like carriers (microreactors), which have mechanical properties that match the liver tissue and that have a camouflaging coating to mimic the surface cues of liver tissue-relevant cells. Finally, matured bioprinted liver-lobules consisting of microreactors and live cells need to connect to liver tissue when transplanted into rats.
I am convinced that the ground-breaking research in ArtHep will contribute to the excellence of science in Europe while providing the game-changing foundation to counteract the ever increasing donor liver shortage. Further, consolidating my scientific efforts and moving them forward into unexplored dimensions in biomimicry for medical purposes, is a unique opportunity to advance my career.
Summary
The global epidemics of obesity and diabetes type 2 lead to higher abundancy of medical conditions like non-alcoholic fatty liver disease causing an increase in liver failure and demand for liver transplants. The shortage of donor organs and the insufficient success in tissue engineering to ex vivo grow complex organs like the liver is a global medical challenge.
ArtHep targets the assembly of hepatic-like tissue, consisting of biological and synthetic entities, mimicking the core structure elements and key functions of the liver. ArtHep comprises an entirely new concept in liver regeneration with multi-angled core impact: i) cell mimics are expected to reduce the pressure to obtain donor cells, ii) the integrated biocatalytic subunits are destined to take over tasks of the damaged liver slowing down the progress of liver damage, and iii) the matching micro-environment in the bioprinted tissue is anticipated to facilitate the connection between the transplant and the liver.
Success criteria of ArtHep include engineering enzyme-mimics, which can perform core biocatalytic conversions similar to the liver, the assembly of biocatalytic active subunits and their encapsulation in cell-like carriers (microreactors), which have mechanical properties that match the liver tissue and that have a camouflaging coating to mimic the surface cues of liver tissue-relevant cells. Finally, matured bioprinted liver-lobules consisting of microreactors and live cells need to connect to liver tissue when transplanted into rats.
I am convinced that the ground-breaking research in ArtHep will contribute to the excellence of science in Europe while providing the game-changing foundation to counteract the ever increasing donor liver shortage. Further, consolidating my scientific efforts and moving them forward into unexplored dimensions in biomimicry for medical purposes, is a unique opportunity to advance my career.
Max ERC Funding
1 992 289 €
Duration
Start date: 2019-05-01, End date: 2024-04-30
Project acronym ATTO
Project A new concept for ultra-high capacity wireless networks
Researcher (PI) Piet DEMEESTER
Host Institution (HI) UNIVERSITEIT GENT
Call Details Advanced Grant (AdG), PE7, ERC-2015-AdG
Summary The project will address the following key question:
How can we provide fibre-like connectivity to moving objects (robots, humans) with the following characteristics: very high dedicated bitrate of 100 Gb/s per object, very low latency of <10 μs, very high reliability of 99.999%, very high density of more than one object per m2 and this at low power consumption?
Achieving this would be groundbreaking and it requires a completely new and high-risk approach: applying close proximity wireless communications using low interference ultra-small cells (called “ATTO-cells”) integrated in floors and connected to antennas on the (parallel) floor-facing surface of ground moving objects. This makes it possible to obtain very high densities with very good channel conditions. The technological challenges involved are groundbreaking in mobile networking (overall architecture, handover with extremely low latencies), wireless subsystems (60 GHz substrate integrated waveguide-based distributed antenna systems connected to RF transceivers integrated in floors, low crosstalk between ATTO-cells) and optical interconnect subsystems (simple non-blocking optical coherent remote selection of ATTO-cells, transparent low power 100 Gb/s coherent optical / RF transceiver interconnection using analogue equalization and symbol interleaving to support 4x4 MIMO). By providing this unique communication infrastructure in high density settings, the ATTO concept will not only support the highly demanding future 5G services (UHD streaming, cloud computing and storage, augmented and virtual reality, a range of IoT services, etc.), but also even more demanding services, that are challenging our imagination such as mobile robot swarms or brain computer interfaces with PFlops computing capabilities.
This new concept for ultra-high capacity wireless networks will open up many more opportunities in reconfigurable robot factories, intelligent hospitals, flexible offices, dense public spaces, etc.
Summary
The project will address the following key question:
How can we provide fibre-like connectivity to moving objects (robots, humans) with the following characteristics: very high dedicated bitrate of 100 Gb/s per object, very low latency of <10 μs, very high reliability of 99.999%, very high density of more than one object per m2 and this at low power consumption?
Achieving this would be groundbreaking and it requires a completely new and high-risk approach: applying close proximity wireless communications using low interference ultra-small cells (called “ATTO-cells”) integrated in floors and connected to antennas on the (parallel) floor-facing surface of ground moving objects. This makes it possible to obtain very high densities with very good channel conditions. The technological challenges involved are groundbreaking in mobile networking (overall architecture, handover with extremely low latencies), wireless subsystems (60 GHz substrate integrated waveguide-based distributed antenna systems connected to RF transceivers integrated in floors, low crosstalk between ATTO-cells) and optical interconnect subsystems (simple non-blocking optical coherent remote selection of ATTO-cells, transparent low power 100 Gb/s coherent optical / RF transceiver interconnection using analogue equalization and symbol interleaving to support 4x4 MIMO). By providing this unique communication infrastructure in high density settings, the ATTO concept will not only support the highly demanding future 5G services (UHD streaming, cloud computing and storage, augmented and virtual reality, a range of IoT services, etc.), but also even more demanding services, that are challenging our imagination such as mobile robot swarms or brain computer interfaces with PFlops computing capabilities.
This new concept for ultra-high capacity wireless networks will open up many more opportunities in reconfigurable robot factories, intelligent hospitals, flexible offices, dense public spaces, etc.
Max ERC Funding
2 496 250 €
Duration
Start date: 2017-01-01, End date: 2021-12-31
Project acronym BIONICbacteria
Project Integrating a novel layer of synthetic biology tools in Pseudomonas, inspired by bacterial viruses
Researcher (PI) Rob LAVIGNE
Host Institution (HI) KATHOLIEKE UNIVERSITEIT LEUVEN
Call Details Consolidator Grant (CoG), LS9, ERC-2018-COG
Summary As nature’s first bioengineers, bacteriophages have evolved to modify, adapt and control their bacterial hosts through billions of years of interactions. Indeed, like modern synthetic biologists aspire to do, bacteriophages already evade bacterial silencing of their xenogeneic DNA, subvert host gene expression, and co-opt both the central and peripheral metabolisms of their hosts. Studying these key insights from a molecular systems biology perspective, inspired us to develop these evolutionary fully-adapted phage mechanisms as a next-level layer of synthetic biology tools. Thus, BIONICbacteria will provide conceptual novel synthetic biology tools that allow direct manipulation of specific protein activity, post-translational modifications, RNA stability, and metabolite concentrations.
The goal of BIONICbacteria is to pioneer an unconventional way to perform synthetic biology, tapping an unlimited source of novel phage tools genetic circuits and phage modulators. To achieve these goals, we will apply and develop state-of-the-art technologies in molecular microbiology and focus on three principal aims:
(1) To exploit new phage-encoded genetic circuits as synthetic biology parts and as intricate biotechnological chassis.
(2) To build synthetic phage modulators (SPMs) as novel payloads to directly impact the bacterial metabolism in a targeted manner.
(3) To create designer bacteria by integrating SPMs-containing circuits into bacterial strains as proof-of-concepts for applications in industrial fermentations and vaccine design.
This proposed “plug-in” approach of evolutionary-adapted synthetic modules, will allow us to domesticate Pseudomonas strains in radically new ways. By building proofs-of-concept for applications in industrial fermentations and vaccine development, we address key problem in these areas with potentially high-gain solutions for society and industry.
Summary
As nature’s first bioengineers, bacteriophages have evolved to modify, adapt and control their bacterial hosts through billions of years of interactions. Indeed, like modern synthetic biologists aspire to do, bacteriophages already evade bacterial silencing of their xenogeneic DNA, subvert host gene expression, and co-opt both the central and peripheral metabolisms of their hosts. Studying these key insights from a molecular systems biology perspective, inspired us to develop these evolutionary fully-adapted phage mechanisms as a next-level layer of synthetic biology tools. Thus, BIONICbacteria will provide conceptual novel synthetic biology tools that allow direct manipulation of specific protein activity, post-translational modifications, RNA stability, and metabolite concentrations.
The goal of BIONICbacteria is to pioneer an unconventional way to perform synthetic biology, tapping an unlimited source of novel phage tools genetic circuits and phage modulators. To achieve these goals, we will apply and develop state-of-the-art technologies in molecular microbiology and focus on three principal aims:
(1) To exploit new phage-encoded genetic circuits as synthetic biology parts and as intricate biotechnological chassis.
(2) To build synthetic phage modulators (SPMs) as novel payloads to directly impact the bacterial metabolism in a targeted manner.
(3) To create designer bacteria by integrating SPMs-containing circuits into bacterial strains as proof-of-concepts for applications in industrial fermentations and vaccine design.
This proposed “plug-in” approach of evolutionary-adapted synthetic modules, will allow us to domesticate Pseudomonas strains in radically new ways. By building proofs-of-concept for applications in industrial fermentations and vaccine development, we address key problem in these areas with potentially high-gain solutions for society and industry.
Max ERC Funding
1 998 750 €
Duration
Start date: 2019-09-01, End date: 2024-08-31
Project acronym BREEDIT
Project A NOVEL BREEDING STRATEGY USING MULTIPLEX GENOME EDITING IN MAIZE
Researcher (PI) Dirk INZE
Host Institution (HI) VIB
Call Details Advanced Grant (AdG), LS9, ERC-2018-ADG
Summary Feeding the growing world population under changing climate conditions poses an unprecedented challenge on global agriculture and our current pace to breed new high yielding crop varieties is too low to face the imminent threats on food security. This ERC project proposes a novel crossing scheme that allows for an expeditious evaluation of combinations of potential yield contributing alleles by unifying ‘classical’ breeding with gene-centric molecular biology. The acronym BREEDIT, a word fusion of breeding and editing, reflects the basic concept of combining breeding with multiplex genome editing of yield related genes. By introducing plants with distinct combinations of genome edited mutations in more than 80 known yield related genes into a crossing scheme, the combinatorial effect of these mutations on plant growth and yield will be evaluated. Subsequent rounds of crossings will increase the number of stacked gene-edits per plant, thus increasing the combinatorial complexity. Phenotypic evaluations throughout plant development will be done on our in-house automated image-analysis based phenotyping platform. The nature and frequency of Cas9-mediated mutations in the entire plant collection will be characterised by multiplex amplicon sequencing to follow the efficiency of CRISPR-cas9 genome editing and to identify the underlying combinations of genes that cause beneficial phenotypes (genetic gain). The obtained knowledge on yield regulatory networks can be directly implemented into current molecular breeding programs and the project will provide the basis to develop targeted breeding schemes implementing the optimal combinations of beneficial alleles into elite material.
BREEDIT will be a major step forward in integrating basic knowledge on genes with plant breeding and has the potential to provoke a paradigm shift in improving crop yield.
Summary
Feeding the growing world population under changing climate conditions poses an unprecedented challenge on global agriculture and our current pace to breed new high yielding crop varieties is too low to face the imminent threats on food security. This ERC project proposes a novel crossing scheme that allows for an expeditious evaluation of combinations of potential yield contributing alleles by unifying ‘classical’ breeding with gene-centric molecular biology. The acronym BREEDIT, a word fusion of breeding and editing, reflects the basic concept of combining breeding with multiplex genome editing of yield related genes. By introducing plants with distinct combinations of genome edited mutations in more than 80 known yield related genes into a crossing scheme, the combinatorial effect of these mutations on plant growth and yield will be evaluated. Subsequent rounds of crossings will increase the number of stacked gene-edits per plant, thus increasing the combinatorial complexity. Phenotypic evaluations throughout plant development will be done on our in-house automated image-analysis based phenotyping platform. The nature and frequency of Cas9-mediated mutations in the entire plant collection will be characterised by multiplex amplicon sequencing to follow the efficiency of CRISPR-cas9 genome editing and to identify the underlying combinations of genes that cause beneficial phenotypes (genetic gain). The obtained knowledge on yield regulatory networks can be directly implemented into current molecular breeding programs and the project will provide the basis to develop targeted breeding schemes implementing the optimal combinations of beneficial alleles into elite material.
BREEDIT will be a major step forward in integrating basic knowledge on genes with plant breeding and has the potential to provoke a paradigm shift in improving crop yield.
Max ERC Funding
2 474 790 €
Duration
Start date: 2019-09-01, End date: 2024-08-31
