Project acronym 20SInhibitor
Project Selective 20S proteasome inhibition for multiple myeloma therapy
Researcher (PI) Michal SHARON
Host Institution (HI) WEIZMANN INSTITUTE OF SCIENCE
Call Details Proof of Concept (PoC), ERC-2018-PoC
Summary Multiple myeloma (MM) is a cancer of plasma cells, that is incurable, and the second most common form of blood cancer. Proteasome inhibitors (PIs) are considered a mainstay in the treatment of MM and mantle cell lymphoma (MCL). Current drugs, based on PIs however, target the chymotrypsin-like activity of the 20S proteasome, and inhibit the activities of both the 20S and 26S proteasomes. Thus, it is possible that selective drug intervention specifically inhibiting only the 20S proteasomes will reduce toxicity, and minimize the deleterious side effects of the current therapeutic regimens.
Our preliminary work revealed a family of 20S proteasome inhibitors, which we termed Catalytic Core Regulators (CCRs) that selectively target the 20S proteasome rather than the 26S complex. Based on sequence motif and structural elements of the CCRs we have designed an artificial protein that is capable of inhibiting the 20S proteasome. We anticipate that these findings will lead to the design of synthetic proteins, peptides or peptidomimetic compounds targeting cancer cells more specifically. This specificity will pose the compounds in an attractive light for using them in various therapeutic applications.
What is exciting from the commercialization perspective, is that pharmaceutical research has switched to revisit the use of peptides as therapeutics. Pharmaceutical companies have seen the development of peptides as a promising direction to lower their risk position. Overall, peptide therapeutics have a 20% chance of receiving regulatory approval, a probability that is 50% higher than that for the approval of small molecules, which form the basis of so called traditional drugs.
In the project, we will carry out actions, which will equip us with the sufficient IP protection strategy, business strategy, industry networks and initial contacts for taking the innovation out from the laboratory to next phase in developing therapy first for MM and MCL later on.
Summary
Multiple myeloma (MM) is a cancer of plasma cells, that is incurable, and the second most common form of blood cancer. Proteasome inhibitors (PIs) are considered a mainstay in the treatment of MM and mantle cell lymphoma (MCL). Current drugs, based on PIs however, target the chymotrypsin-like activity of the 20S proteasome, and inhibit the activities of both the 20S and 26S proteasomes. Thus, it is possible that selective drug intervention specifically inhibiting only the 20S proteasomes will reduce toxicity, and minimize the deleterious side effects of the current therapeutic regimens.
Our preliminary work revealed a family of 20S proteasome inhibitors, which we termed Catalytic Core Regulators (CCRs) that selectively target the 20S proteasome rather than the 26S complex. Based on sequence motif and structural elements of the CCRs we have designed an artificial protein that is capable of inhibiting the 20S proteasome. We anticipate that these findings will lead to the design of synthetic proteins, peptides or peptidomimetic compounds targeting cancer cells more specifically. This specificity will pose the compounds in an attractive light for using them in various therapeutic applications.
What is exciting from the commercialization perspective, is that pharmaceutical research has switched to revisit the use of peptides as therapeutics. Pharmaceutical companies have seen the development of peptides as a promising direction to lower their risk position. Overall, peptide therapeutics have a 20% chance of receiving regulatory approval, a probability that is 50% higher than that for the approval of small molecules, which form the basis of so called traditional drugs.
In the project, we will carry out actions, which will equip us with the sufficient IP protection strategy, business strategy, industry networks and initial contacts for taking the innovation out from the laboratory to next phase in developing therapy first for MM and MCL later on.
Max ERC Funding
150 000 €
Duration
Start date: 2019-04-01, End date: 2020-09-30
Project acronym 3D-nanoMorph
Project Label-free 3D morphological nanoscopy for studying sub-cellular dynamics in live cancer cells with high spatio-temporal resolution
Researcher (PI) Krishna AGARWAL
Host Institution (HI) UNIVERSITETET I TROMSOE - NORGES ARKTISKE UNIVERSITET
Call Details Starting Grant (StG), PE7, ERC-2018-STG
Summary Label-free optical nanoscopy, free from photobleaching and photochemical toxicity of fluorescence labels and yielding 3D morphological resolution of <50 nm, is the future of live cell imaging. 3D-nanoMorph breaks the diffraction barrier and shifts the paradigm in label-free nanoscopy, providing isotropic 3D resolution of <50 nm. To achieve this, 3D-nanoMorph performs non-linear inverse scattering for the first time in nanoscopy and decodes scattering between sub-cellular structures (organelles).
3D-nanoMorph innovatively devises complementary roles of light measurement system and computational nanoscopy algorithm. A novel illumination system and a novel light collection system together enable measurement of only the most relevant intensity component and create a fresh perspective about label-free measurements. A new computational nanoscopy approach employs non-linear inverse scattering. Harnessing non-linear inverse scattering for resolution enhancement in nanoscopy opens new possibilities in label-free 3D nanoscopy.
I will apply 3D-nanoMorph to study organelle degradation (autophagy) in live cancer cells over extended duration with high spatial and temporal resolution, presently limited by the lack of high-resolution label-free 3D morphological nanoscopy. Successful 3D mapping of nanoscale biological process of autophagy will open new avenues for cancer treatment and showcase 3D-nanoMorph for wider applications.
My cross-disciplinary expertise of 14 years spanning inverse problems, electromagnetism, optical microscopy, integrated optics and live cell nanoscopy paves path for successful implementation of 3D-nanoMorph.
Summary
Label-free optical nanoscopy, free from photobleaching and photochemical toxicity of fluorescence labels and yielding 3D morphological resolution of <50 nm, is the future of live cell imaging. 3D-nanoMorph breaks the diffraction barrier and shifts the paradigm in label-free nanoscopy, providing isotropic 3D resolution of <50 nm. To achieve this, 3D-nanoMorph performs non-linear inverse scattering for the first time in nanoscopy and decodes scattering between sub-cellular structures (organelles).
3D-nanoMorph innovatively devises complementary roles of light measurement system and computational nanoscopy algorithm. A novel illumination system and a novel light collection system together enable measurement of only the most relevant intensity component and create a fresh perspective about label-free measurements. A new computational nanoscopy approach employs non-linear inverse scattering. Harnessing non-linear inverse scattering for resolution enhancement in nanoscopy opens new possibilities in label-free 3D nanoscopy.
I will apply 3D-nanoMorph to study organelle degradation (autophagy) in live cancer cells over extended duration with high spatial and temporal resolution, presently limited by the lack of high-resolution label-free 3D morphological nanoscopy. Successful 3D mapping of nanoscale biological process of autophagy will open new avenues for cancer treatment and showcase 3D-nanoMorph for wider applications.
My cross-disciplinary expertise of 14 years spanning inverse problems, electromagnetism, optical microscopy, integrated optics and live cell nanoscopy paves path for successful implementation of 3D-nanoMorph.
Max ERC Funding
1 499 999 €
Duration
Start date: 2019-07-01, End date: 2024-06-30
Project acronym 3DBrainStrom
Project Brain metastases: Deciphering tumor-stroma interactions in three dimensions for the rational design of nanomedicines
Researcher (PI) Ronit Satchi Fainaro
Host Institution (HI) TEL AVIV UNIVERSITY
Call Details Advanced Grant (AdG), LS7, ERC-2018-ADG
Summary Brain metastases represent a major therapeutic challenge. Despite significant breakthroughs in targeted therapies, survival rates of patients with brain metastases remain poor. Nowadays, discovery, development and evaluation of new therapies are performed on human cancer cells grown in 2D on rigid plastic plates followed by in vivo testing in immunodeficient mice. These experimental settings are lacking and constitute a fundamental hurdle for the translation of preclinical discoveries into clinical practice. We propose to establish 3D-printed models of brain metastases (Aim 1), which include brain extracellular matrix, stroma and serum containing immune cells flowing in functional tumor vessels. Our unique models better capture the clinical physio-mechanical tissue properties, signaling pathways, hemodynamics and drug responsiveness. Using our 3D-printed models, we aim to develop two new fronts for identifying novel clinically-relevant molecular drivers (Aim 2) followed by the development of precision nanomedicines (Aim 3). We will exploit our vast experience in anticancer nanomedicines to design three therapeutic approaches that target various cellular compartments involved in brain metastases: 1) Prevention of brain metastatic colonization using targeted nano-vaccines, which elicit antitumor immune response; 2) Intervention of tumor-brain stroma cells crosstalk when brain micrometastases establish; 3) Regression of macrometastatic disease by selectively targeting tumor cells. These approaches will materialize using our libraries of polymeric nanocarriers that selectively accumulate in tumors.
This project will result in a paradigm shift by generating new preclinical cancer models that will bridge the translational gap in cancer therapeutics. The insights and tumor-stroma-targeted nanomedicines developed here will pave the way for prediction of patient outcome, revolutionizing our perception of tumor modelling and consequently the way we prevent and treat cancer.
Summary
Brain metastases represent a major therapeutic challenge. Despite significant breakthroughs in targeted therapies, survival rates of patients with brain metastases remain poor. Nowadays, discovery, development and evaluation of new therapies are performed on human cancer cells grown in 2D on rigid plastic plates followed by in vivo testing in immunodeficient mice. These experimental settings are lacking and constitute a fundamental hurdle for the translation of preclinical discoveries into clinical practice. We propose to establish 3D-printed models of brain metastases (Aim 1), which include brain extracellular matrix, stroma and serum containing immune cells flowing in functional tumor vessels. Our unique models better capture the clinical physio-mechanical tissue properties, signaling pathways, hemodynamics and drug responsiveness. Using our 3D-printed models, we aim to develop two new fronts for identifying novel clinically-relevant molecular drivers (Aim 2) followed by the development of precision nanomedicines (Aim 3). We will exploit our vast experience in anticancer nanomedicines to design three therapeutic approaches that target various cellular compartments involved in brain metastases: 1) Prevention of brain metastatic colonization using targeted nano-vaccines, which elicit antitumor immune response; 2) Intervention of tumor-brain stroma cells crosstalk when brain micrometastases establish; 3) Regression of macrometastatic disease by selectively targeting tumor cells. These approaches will materialize using our libraries of polymeric nanocarriers that selectively accumulate in tumors.
This project will result in a paradigm shift by generating new preclinical cancer models that will bridge the translational gap in cancer therapeutics. The insights and tumor-stroma-targeted nanomedicines developed here will pave the way for prediction of patient outcome, revolutionizing our perception of tumor modelling and consequently the way we prevent and treat cancer.
Max ERC Funding
2 353 125 €
Duration
Start date: 2019-04-01, End date: 2024-03-31
Project acronym 4DPHOTON
Project Beyond Light Imaging: High-Rate Single-Photon Detection in Four Dimensions
Researcher (PI) Massimiliano FIORINI
Host Institution (HI) ISTITUTO NAZIONALE DI FISICA NUCLEARE
Call Details Consolidator Grant (CoG), PE2, ERC-2018-COG
Summary Goal of the 4DPHOTON project is the development and construction of a photon imaging detector with unprecedented performance. The proposed device will be capable of detecting fluxes of single-photons up to one billion photons per second, over areas of several square centimetres, and will measure - for each photon - position and time simultaneously with resolutions better than ten microns and few tens of picoseconds, respectively. These figures of merit will open many important applications allowing significant advances in particle physics, life sciences or other emerging fields where excellent timing and position resolutions are simultaneously required.
Our goal will be achieved thanks to the use of an application-specific integrated circuit in 65 nm complementary metal-oxide-semiconductor (CMOS) technology, that will deliver a timing resolution of few tens of picoseconds at the pixel level, over few hundred thousand individually-active pixel channels, allowing very high rates of photons to be detected, and the corresponding information digitized and transferred to a processing unit.
As a result of the 4DPHOTON project we will remove the constraints that many light imaging applications have due to the lack of precise single-photon information on four dimensions (4D): the three spatial coordinates and time simultaneously. In particular, we will prove the performance of this detector in the field of particle physics, performing the reconstruction of Cherenkov photon rings with a timing resolution of ten picoseconds. With its excellent granularity, timing resolution, rate capability and compactness, this detector will represent a new paradigm for the realisation of future Ring Imaging Cherenkov detectors, capable of achieving high efficiency particle identification in environments with very high particle multiplicities, exploiting time-association of the photon hits.
Summary
Goal of the 4DPHOTON project is the development and construction of a photon imaging detector with unprecedented performance. The proposed device will be capable of detecting fluxes of single-photons up to one billion photons per second, over areas of several square centimetres, and will measure - for each photon - position and time simultaneously with resolutions better than ten microns and few tens of picoseconds, respectively. These figures of merit will open many important applications allowing significant advances in particle physics, life sciences or other emerging fields where excellent timing and position resolutions are simultaneously required.
Our goal will be achieved thanks to the use of an application-specific integrated circuit in 65 nm complementary metal-oxide-semiconductor (CMOS) technology, that will deliver a timing resolution of few tens of picoseconds at the pixel level, over few hundred thousand individually-active pixel channels, allowing very high rates of photons to be detected, and the corresponding information digitized and transferred to a processing unit.
As a result of the 4DPHOTON project we will remove the constraints that many light imaging applications have due to the lack of precise single-photon information on four dimensions (4D): the three spatial coordinates and time simultaneously. In particular, we will prove the performance of this detector in the field of particle physics, performing the reconstruction of Cherenkov photon rings with a timing resolution of ten picoseconds. With its excellent granularity, timing resolution, rate capability and compactness, this detector will represent a new paradigm for the realisation of future Ring Imaging Cherenkov detectors, capable of achieving high efficiency particle identification in environments with very high particle multiplicities, exploiting time-association of the photon hits.
Max ERC Funding
1 975 000 €
Duration
Start date: 2019-12-01, End date: 2024-11-30
Project acronym 5D-NanoTrack
Project Five-Dimensional Localization Microscopy for Sub-Cellular Dynamics
Researcher (PI) Yoav SHECHTMAN
Host Institution (HI) TECHNION - ISRAEL INSTITUTE OF TECHNOLOGY
Call Details Starting Grant (StG), PE7, ERC-2018-STG
Summary The sub-cellular processes that control the most critical aspects of life occur in three-dimensions (3D), and are intrinsically dynamic. While super-resolution microscopy has revolutionized cellular imaging in recent years, our current capability to observe the dynamics of life on the nanoscale is still extremely limited, due to inherent trade-offs between spatial, temporal and spectral resolution using existing approaches.
We propose to develop and demonstrate an optical microscopy methodology that would enable live sub-cellular observation in unprecedented detail. Making use of multicolor 3D point-spread-function (PSF) engineering, a technique I have recently developed, we will be able to simultaneously track multiple markers inside live cells, at high speed and in five-dimensions (3D, time, and color).
Multicolor 3D PSF engineering holds the potential of being a uniquely powerful method for 5D tracking. However, it is not yet applicable to live-cell imaging, due to significant bottlenecks in optical engineering and signal processing, which we plan to overcome in this project. Importantly, we will also demonstrate the efficacy of our method using a challenging biological application: real-time visualization of chromatin dynamics - the spatiotemporal organization of DNA. This is a highly suitable problem due to its fundamental importance, its role in a variety of cellular processes, and the lack of appropriate tools for studying it.
The project is divided into 3 aims:
1. Technology development: diffractive-element design for multicolor 3D PSFs.
2. System design: volumetric tracking of dense emitters.
3. Live-cell measurements: chromatin dynamics.
Looking ahead, here we create the imaging tools that pave the way towards the holy grail of chromatin visualization: dynamic observation of the 3D positions of the ~3 billion DNA base-pairs in a live human cell. Beyond that, our results will be applicable to numerous 3D micro/nanoscale tracking applications.
Summary
The sub-cellular processes that control the most critical aspects of life occur in three-dimensions (3D), and are intrinsically dynamic. While super-resolution microscopy has revolutionized cellular imaging in recent years, our current capability to observe the dynamics of life on the nanoscale is still extremely limited, due to inherent trade-offs between spatial, temporal and spectral resolution using existing approaches.
We propose to develop and demonstrate an optical microscopy methodology that would enable live sub-cellular observation in unprecedented detail. Making use of multicolor 3D point-spread-function (PSF) engineering, a technique I have recently developed, we will be able to simultaneously track multiple markers inside live cells, at high speed and in five-dimensions (3D, time, and color).
Multicolor 3D PSF engineering holds the potential of being a uniquely powerful method for 5D tracking. However, it is not yet applicable to live-cell imaging, due to significant bottlenecks in optical engineering and signal processing, which we plan to overcome in this project. Importantly, we will also demonstrate the efficacy of our method using a challenging biological application: real-time visualization of chromatin dynamics - the spatiotemporal organization of DNA. This is a highly suitable problem due to its fundamental importance, its role in a variety of cellular processes, and the lack of appropriate tools for studying it.
The project is divided into 3 aims:
1. Technology development: diffractive-element design for multicolor 3D PSFs.
2. System design: volumetric tracking of dense emitters.
3. Live-cell measurements: chromatin dynamics.
Looking ahead, here we create the imaging tools that pave the way towards the holy grail of chromatin visualization: dynamic observation of the 3D positions of the ~3 billion DNA base-pairs in a live human cell. Beyond that, our results will be applicable to numerous 3D micro/nanoscale tracking applications.
Max ERC Funding
1 802 500 €
Duration
Start date: 2018-11-01, End date: 2023-10-31
Project acronym ADIMMUNE
Project Decoding interactions between adipose tissue immune cells, metabolic function, and the intestinal microbiome in obesity
Researcher (PI) Eran Elinav
Host Institution (HI) WEIZMANN INSTITUTE OF SCIENCE
Call Details Consolidator Grant (CoG), LS6, ERC-2018-COG
Summary Obesity and its metabolic co-morbidities have given rise to a rapidly expanding ‘metabolic syndrome’ pandemic affecting
hundreds of millions of individuals worldwide. The integrative genetic and environmental causes of the obesity pandemic
remain elusive. White adipose tissue (WAT)-resident immune cells have recently been highlighted as important factors
contributing to metabolic complications. However, a comprehensive understanding of the regulatory circuits governing their
function and the cell type-specific mechanisms by which they contribute to the development of metabolic syndrome is
lacking. Likewise, the gut microbiome has been suggested as a critical regulator of obesity, but the bacterial species and
metabolites that influence WAT inflammation are entirely unknown.
We propose to use our recently developed high-throughput genomic and gnotobiotic tools, integrated with CRISPR-mediated interrogation of gene function, microbial culturomics, and in-vivo metabolic analysis in newly generated mouse models, in order to achieve a new level of molecular understanding of how WAT immune cells integrate environmental cues into their crosstalk with organismal metabolism, and to explore the microbial contributions to the molecular etiology of WAT inflammation in the pathogenesis of diet-induced obesity. Specifically, we aim to (a) decipher the global regulatory landscape and interaction networks of WAT hematopoietic cells at the single-cell level, (b) identify new mediators of WAT immune cell contributions to metabolic homeostasis, and (c) decode how host-microbiome communication shapes the development of WAT inflammation and obesity.
Unraveling the principles of WAT immune cell regulation and their amenability to change by host-microbiota interactions
may lead to a conceptual leap forward in our understanding of metabolic physiology and disease. Concomitantly, it may
generate a platform for microbiome-based personalized therapy against obesity and its complications.
Summary
Obesity and its metabolic co-morbidities have given rise to a rapidly expanding ‘metabolic syndrome’ pandemic affecting
hundreds of millions of individuals worldwide. The integrative genetic and environmental causes of the obesity pandemic
remain elusive. White adipose tissue (WAT)-resident immune cells have recently been highlighted as important factors
contributing to metabolic complications. However, a comprehensive understanding of the regulatory circuits governing their
function and the cell type-specific mechanisms by which they contribute to the development of metabolic syndrome is
lacking. Likewise, the gut microbiome has been suggested as a critical regulator of obesity, but the bacterial species and
metabolites that influence WAT inflammation are entirely unknown.
We propose to use our recently developed high-throughput genomic and gnotobiotic tools, integrated with CRISPR-mediated interrogation of gene function, microbial culturomics, and in-vivo metabolic analysis in newly generated mouse models, in order to achieve a new level of molecular understanding of how WAT immune cells integrate environmental cues into their crosstalk with organismal metabolism, and to explore the microbial contributions to the molecular etiology of WAT inflammation in the pathogenesis of diet-induced obesity. Specifically, we aim to (a) decipher the global regulatory landscape and interaction networks of WAT hematopoietic cells at the single-cell level, (b) identify new mediators of WAT immune cell contributions to metabolic homeostasis, and (c) decode how host-microbiome communication shapes the development of WAT inflammation and obesity.
Unraveling the principles of WAT immune cell regulation and their amenability to change by host-microbiota interactions
may lead to a conceptual leap forward in our understanding of metabolic physiology and disease. Concomitantly, it may
generate a platform for microbiome-based personalized therapy against obesity and its complications.
Max ERC Funding
2 000 000 €
Duration
Start date: 2019-03-01, End date: 2024-02-29
Project acronym AFDMATS
Project Anton Francesco Doni – Multimedia Archive Texts and Sources
Researcher (PI) Giovanna Rizzarelli
Host Institution (HI) SCUOLA NORMALE SUPERIORE
Call Details Starting Grant (StG), SH4, ERC-2007-StG
Summary This project aims at creating a multimedia archive of the printed works of Anton Francesco Doni, who was not only an author but also a typographer, a publisher and a member of the Giolito and Marcolini’s editorial staff. The analysis of Doni’s work may be a good way to investigate appropriation, text rewriting and image reusing practices which are typical of several authors of the 16th Century, as clearly shown by the critics in the last decades. This project intends to bring to light the wide range of impulses from which Doni’s texts are generated, with a great emphasis on the figurative aspect. The encoding of these texts will be carried out using the TEI (Text Encoding Initiative) guidelines, which will enable any single text to interact with a range of intertextual references both at a local level (inside the same text) and at a macrostructural level (references to other texts by Doni or to other authors). The elements that will emerge from the textual encoding concern: A) The use of images Real images: the complex relation between Doni’s writing and the xylographies available in Marcolini’s printing-house or belonging to other collections. Mental images: the remarkable presence of verbal images, as descriptions, ekphràseis, figurative visions, dreams and iconographic allusions not accompanied by illustrations, but related to a recognizable visual repertoire or to real images that will be reproduced. B) The use of sources A parallel archive of the texts most used by Doni will be created. Digital anastatic reproductions of the 16th-Century editions known by Doni will be provided whenever available. The various forms of intertextuality will be divided into the following typologies: allusions; citations; rewritings; plagiarisms; self-quotations. Finally, the different forms of narrative (tales, short stories, anecdotes, lyrics) and the different idiomatic expressions (proverbial forms and wellerisms) will also be encoded.
Summary
This project aims at creating a multimedia archive of the printed works of Anton Francesco Doni, who was not only an author but also a typographer, a publisher and a member of the Giolito and Marcolini’s editorial staff. The analysis of Doni’s work may be a good way to investigate appropriation, text rewriting and image reusing practices which are typical of several authors of the 16th Century, as clearly shown by the critics in the last decades. This project intends to bring to light the wide range of impulses from which Doni’s texts are generated, with a great emphasis on the figurative aspect. The encoding of these texts will be carried out using the TEI (Text Encoding Initiative) guidelines, which will enable any single text to interact with a range of intertextual references both at a local level (inside the same text) and at a macrostructural level (references to other texts by Doni or to other authors). The elements that will emerge from the textual encoding concern: A) The use of images Real images: the complex relation between Doni’s writing and the xylographies available in Marcolini’s printing-house or belonging to other collections. Mental images: the remarkable presence of verbal images, as descriptions, ekphràseis, figurative visions, dreams and iconographic allusions not accompanied by illustrations, but related to a recognizable visual repertoire or to real images that will be reproduced. B) The use of sources A parallel archive of the texts most used by Doni will be created. Digital anastatic reproductions of the 16th-Century editions known by Doni will be provided whenever available. The various forms of intertextuality will be divided into the following typologies: allusions; citations; rewritings; plagiarisms; self-quotations. Finally, the different forms of narrative (tales, short stories, anecdotes, lyrics) and the different idiomatic expressions (proverbial forms and wellerisms) will also be encoded.
Max ERC Funding
559 200 €
Duration
Start date: 2008-08-01, End date: 2012-07-31
Project acronym AGALT
Project Asymptotic Geometric Analysis and Learning Theory
Researcher (PI) Shahar Mendelson
Host Institution (HI) TECHNION - ISRAEL INSTITUTE OF TECHNOLOGY
Call Details Starting Grant (StG), PE1, ERC-2007-StG
Summary In a typical learning problem one tries to approximate an unknown function by a function from a given class using random data, sampled according to an unknown measure. In this project we will be interested in parameters that govern the complexity of a learning problem. It turns out that this complexity is determined by the geometry of certain sets in high dimension that are connected to the given class (random coordinate projections of the class). Thus, one has to understand the structure of these sets as a function of the dimension - which is given by the cardinality of the random sample. The resulting analysis leads to many theoretical questions in Asymptotic Geometric Analysis, Probability (most notably, Empirical Processes Theory) and Combinatorics, which are of independent interest beyond the application to Learning Theory. Our main goal is to describe the role of various complexity parameters involved in a learning problem, to analyze the connections between them and to investigate the way they determine the geometry of the relevant high dimensional sets. Some of the questions we intend to tackle are well known open problems and making progress towards their solution will have a significant theoretical impact. Moreover, this project should lead to a more complete theory of learning and is likely to have some practical impact, for example, in the design of more efficient learning algorithms.
Summary
In a typical learning problem one tries to approximate an unknown function by a function from a given class using random data, sampled according to an unknown measure. In this project we will be interested in parameters that govern the complexity of a learning problem. It turns out that this complexity is determined by the geometry of certain sets in high dimension that are connected to the given class (random coordinate projections of the class). Thus, one has to understand the structure of these sets as a function of the dimension - which is given by the cardinality of the random sample. The resulting analysis leads to many theoretical questions in Asymptotic Geometric Analysis, Probability (most notably, Empirical Processes Theory) and Combinatorics, which are of independent interest beyond the application to Learning Theory. Our main goal is to describe the role of various complexity parameters involved in a learning problem, to analyze the connections between them and to investigate the way they determine the geometry of the relevant high dimensional sets. Some of the questions we intend to tackle are well known open problems and making progress towards their solution will have a significant theoretical impact. Moreover, this project should lead to a more complete theory of learning and is likely to have some practical impact, for example, in the design of more efficient learning algorithms.
Max ERC Funding
750 000 €
Duration
Start date: 2009-03-01, End date: 2014-02-28
Project acronym AGENSI
Project A Genetic View into Past Sea Ice Variability in the Arctic
Researcher (PI) Stijn DE SCHEPPER
Host Institution (HI) NORCE NORWEGIAN RESEARCH CENTRE AS
Call Details Consolidator Grant (CoG), PE10, ERC-2018-COG
Summary Arctic sea ice decline is the exponent of the rapidly transforming Arctic climate. The ensuing local and global implications can be understood by studying past climate transitions, yet few methods are available to examine past Arctic sea ice cover, severely restricting our understanding of sea ice in the climate system. The decline in Arctic sea ice cover is a ‘canary in the coalmine’ for the state of our climate, and if greenhouse gas emissions remain unchecked, summer sea ice loss may pass a critical threshold that could drastically transform the Arctic. Because historical observations are limited, it is crucial to have reliable proxies for assessing natural sea ice variability, its stability and sensitivity to climate forcing on different time scales. Current proxies address aspects of sea ice variability, but are limited due to a selective fossil record, preservation effects, regional applicability, or being semi-quantitative. With such restraints on our knowledge about natural variations and drivers, major uncertainties about the future remain.
I propose to develop and apply a novel sea ice proxy that exploits genetic information stored in marine sediments, sedimentary ancient DNA (sedaDNA). This innovation uses the genetic signature of phytoplankton communities from surface waters and sea ice as it gets stored in sediments. This wealth of information has not been explored before for reconstructing sea ice conditions. Preliminary results from my cross-disciplinary team indicate that our unconventional approach can provide a detailed, qualitative account of past sea ice ecosystems and quantitative estimates of sea ice parameters. I will address fundamental questions about past Arctic sea ice variability on different timescales, information essential to provide a framework upon which to assess the ecological and socio-economic consequences of a changing Arctic. This new proxy is not limited to sea ice research and can transform the field of paleoceanography.
Summary
Arctic sea ice decline is the exponent of the rapidly transforming Arctic climate. The ensuing local and global implications can be understood by studying past climate transitions, yet few methods are available to examine past Arctic sea ice cover, severely restricting our understanding of sea ice in the climate system. The decline in Arctic sea ice cover is a ‘canary in the coalmine’ for the state of our climate, and if greenhouse gas emissions remain unchecked, summer sea ice loss may pass a critical threshold that could drastically transform the Arctic. Because historical observations are limited, it is crucial to have reliable proxies for assessing natural sea ice variability, its stability and sensitivity to climate forcing on different time scales. Current proxies address aspects of sea ice variability, but are limited due to a selective fossil record, preservation effects, regional applicability, or being semi-quantitative. With such restraints on our knowledge about natural variations and drivers, major uncertainties about the future remain.
I propose to develop and apply a novel sea ice proxy that exploits genetic information stored in marine sediments, sedimentary ancient DNA (sedaDNA). This innovation uses the genetic signature of phytoplankton communities from surface waters and sea ice as it gets stored in sediments. This wealth of information has not been explored before for reconstructing sea ice conditions. Preliminary results from my cross-disciplinary team indicate that our unconventional approach can provide a detailed, qualitative account of past sea ice ecosystems and quantitative estimates of sea ice parameters. I will address fundamental questions about past Arctic sea ice variability on different timescales, information essential to provide a framework upon which to assess the ecological and socio-economic consequences of a changing Arctic. This new proxy is not limited to sea ice research and can transform the field of paleoceanography.
Max ERC Funding
2 615 858 €
Duration
Start date: 2019-08-01, End date: 2024-07-31
Project acronym Agglomerates
Project Infinite Protein Self-Assembly in Health and Disease
Researcher (PI) Emmanuel Doram LEVY
Host Institution (HI) WEIZMANN INSTITUTE OF SCIENCE
Call Details Consolidator Grant (CoG), LS2, ERC-2018-COG
Summary Understanding how proteins respond to mutations is of paramount importance to biology and disease. While protein stability and misfolding have been instrumental in rationalizing the impact of mutations, we recently discovered that an alternative route is also frequent, where mutations at the surface of symmetric proteins trigger novel self-interactions that lead to infinite self-assembly. This mechanism can be involved in disease, as in sickle-cell anemia, but may also serve in adaptation. Importantly, it differs fundamentally from aggregation, because misfolding does not drive it. Thus, we term it “agglomeration”. The ease with which agglomeration can occur, even by single point mutations, shifts the paradigm of how quickly new protein assemblies can emerge, both in health and disease. This prompts us to determine the basic principles of protein agglomeration and explore its implications in cell physiology and human disease.
We propose an interdisciplinary research program bridging atomic and cellular scales to explore agglomeration in three aims: (i) Map the landscape of protein agglomeration in response to mutation in endogenous yeast proteins; (ii) Characterize how yeast physiology impacts agglomeration by changes in gene expression or cell state, and, conversely, how protein agglomerates impact yeast fitness. (iii) Analyze agglomeration in relation to human disease via two approaches. First, by predicting single nucleotide polymorphisms that trigger agglomeration, prioritizing them using knowledge from Aims 1 & 2, and characterizing them experimentally. Second, by providing a proof-of-concept that agglomeration can be exploited in drug design, whereby drugs induce its formation, like mutations can do.
Overall, through this research, we aim to establish agglomeration as a paradigm for protein assembly, with implications for our understanding of evolution, physiology, and disease.
Summary
Understanding how proteins respond to mutations is of paramount importance to biology and disease. While protein stability and misfolding have been instrumental in rationalizing the impact of mutations, we recently discovered that an alternative route is also frequent, where mutations at the surface of symmetric proteins trigger novel self-interactions that lead to infinite self-assembly. This mechanism can be involved in disease, as in sickle-cell anemia, but may also serve in adaptation. Importantly, it differs fundamentally from aggregation, because misfolding does not drive it. Thus, we term it “agglomeration”. The ease with which agglomeration can occur, even by single point mutations, shifts the paradigm of how quickly new protein assemblies can emerge, both in health and disease. This prompts us to determine the basic principles of protein agglomeration and explore its implications in cell physiology and human disease.
We propose an interdisciplinary research program bridging atomic and cellular scales to explore agglomeration in three aims: (i) Map the landscape of protein agglomeration in response to mutation in endogenous yeast proteins; (ii) Characterize how yeast physiology impacts agglomeration by changes in gene expression or cell state, and, conversely, how protein agglomerates impact yeast fitness. (iii) Analyze agglomeration in relation to human disease via two approaches. First, by predicting single nucleotide polymorphisms that trigger agglomeration, prioritizing them using knowledge from Aims 1 & 2, and characterizing them experimentally. Second, by providing a proof-of-concept that agglomeration can be exploited in drug design, whereby drugs induce its formation, like mutations can do.
Overall, through this research, we aim to establish agglomeration as a paradigm for protein assembly, with implications for our understanding of evolution, physiology, and disease.
Max ERC Funding
2 574 819 €
Duration
Start date: 2019-04-01, End date: 2024-03-31
