Project acronym CharFL
Project Characterizing the fitness landscape on population and global scales
Researcher (PI) Fyodor Kondrashov
Host Institution (HI) INSTITUTE OF SCIENCE AND TECHNOLOGY AUSTRIA
Call Details Consolidator Grant (CoG), LS2, ERC-2017-COG
Summary The fitness landscape, the representation of how the genotype manifests at the phenotypic (fitness) levels, may be among the most useful concepts in biology with impact on diverse fields, including quantitative genetics, emergence of pathogen resistance, synthetic biology and protein engineering. While progress in characterizing fitness landscapes has been made, three directions of research in the field remain virtually unexplored: the nature of the genotype to phenotype of standing variation (variation found in a natural population), the shape of the fitness landscape encompassing many genotypes and the modelling of complex genetic interactions in protein sequences.
The current proposal is designed to advance the study of fitness landscapes in these three directions using large-scale genomic experiments and experimental data from a model protein and theoretical work. The study of the fitness landscape of standing variation is aimed at the resolution of an outstanding question in quantitative genetics: the extent to which epistasis, non-additive genetic interactions, is shaping the phenotype. The second aim of characterizing the global fitness landscape will give us an understanding of how evolution proceeds along long evolutionary timescales, which can be directly applied to protein engineering and synthetic biology for the design of novel phenotypes. Finally, the third aim of modelling complex interactions will improve our ability to predict phenotypes from genotypes, such as the prediction of human disease mutations. In summary, the proposed study presents an opportunity to provide a unifying understanding of how phenotypes are shaped through genetic interactions. The consolidation of our empirical and theoretical work on different scales of the genotype to phenotype relationship will provide empirical data and novel context for several fields of biology.
Summary
The fitness landscape, the representation of how the genotype manifests at the phenotypic (fitness) levels, may be among the most useful concepts in biology with impact on diverse fields, including quantitative genetics, emergence of pathogen resistance, synthetic biology and protein engineering. While progress in characterizing fitness landscapes has been made, three directions of research in the field remain virtually unexplored: the nature of the genotype to phenotype of standing variation (variation found in a natural population), the shape of the fitness landscape encompassing many genotypes and the modelling of complex genetic interactions in protein sequences.
The current proposal is designed to advance the study of fitness landscapes in these three directions using large-scale genomic experiments and experimental data from a model protein and theoretical work. The study of the fitness landscape of standing variation is aimed at the resolution of an outstanding question in quantitative genetics: the extent to which epistasis, non-additive genetic interactions, is shaping the phenotype. The second aim of characterizing the global fitness landscape will give us an understanding of how evolution proceeds along long evolutionary timescales, which can be directly applied to protein engineering and synthetic biology for the design of novel phenotypes. Finally, the third aim of modelling complex interactions will improve our ability to predict phenotypes from genotypes, such as the prediction of human disease mutations. In summary, the proposed study presents an opportunity to provide a unifying understanding of how phenotypes are shaped through genetic interactions. The consolidation of our empirical and theoretical work on different scales of the genotype to phenotype relationship will provide empirical data and novel context for several fields of biology.
Max ERC Funding
1 998 280 €
Duration
Start date: 2019-01-01, End date: 2023-12-31
Project acronym Demos
Project Design Principles of Branching Morphogenesis
Researcher (PI) Claude-Edouard, Bernard Hannezo
Host Institution (HI) INSTITUTE OF SCIENCE AND TECHNOLOGY AUSTRIA
Call Details Starting Grant (StG), LS2, ERC-2019-STG
Summary Branching morphogenesis, the process by which branched organs such as the lung, prostate, kidney or mammary gland are generated, is a paradigmatic example of complex developmental processes bridging multiple scales. The mechanisms through which given molecular signals and cellular behaviours give rise to a robust organ structure remains a fundamental and open question, for which theoretical methods are needed. Our experience in modelling cytoskeletal mechanics, stem cell dynamics and branching processes puts us in a unique position to tackle this fascinating problem, by combining systems biology and biophysical approaches at multiple scales. In particular, we will focus on:
1. Understanding how stochastic rules lead to robust morphogenetic outputs at the organ scale, and which constraints and optimal design principles they impose on physiological function.
2. Characterizing at the cellular scale the bi-directional feedbacks coordinating fate choices of stem/progenitor cells and niche signals during the extensive remodelling events that branching morphogenesis entails.
3. Developing at the subcellular and cellular scale an integrated mechanochemical theory of pattern formation in branched organs, to understand the coordination of mechanical forces and chemical signals defining their global structure.
Towards these goals, we will combine analytical and numerical tools with data analysis methods, to reach a quantitative understanding of the emergent mechanisms driving branching morphogenesis. We will challenge our theoretical predictions with published datasets available for different organs, as well as design specific experimental tests in collaboration with experimental biology groups. This will allow us to compare and contrast different systems, and extract generic classes of design principles of organogenesis across length scales. With this, we expect to generate novel insights of broad relevance for the fields of systems, computational and developmental biology.
Summary
Branching morphogenesis, the process by which branched organs such as the lung, prostate, kidney or mammary gland are generated, is a paradigmatic example of complex developmental processes bridging multiple scales. The mechanisms through which given molecular signals and cellular behaviours give rise to a robust organ structure remains a fundamental and open question, for which theoretical methods are needed. Our experience in modelling cytoskeletal mechanics, stem cell dynamics and branching processes puts us in a unique position to tackle this fascinating problem, by combining systems biology and biophysical approaches at multiple scales. In particular, we will focus on:
1. Understanding how stochastic rules lead to robust morphogenetic outputs at the organ scale, and which constraints and optimal design principles they impose on physiological function.
2. Characterizing at the cellular scale the bi-directional feedbacks coordinating fate choices of stem/progenitor cells and niche signals during the extensive remodelling events that branching morphogenesis entails.
3. Developing at the subcellular and cellular scale an integrated mechanochemical theory of pattern formation in branched organs, to understand the coordination of mechanical forces and chemical signals defining their global structure.
Towards these goals, we will combine analytical and numerical tools with data analysis methods, to reach a quantitative understanding of the emergent mechanisms driving branching morphogenesis. We will challenge our theoretical predictions with published datasets available for different organs, as well as design specific experimental tests in collaboration with experimental biology groups. This will allow us to compare and contrast different systems, and extract generic classes of design principles of organogenesis across length scales. With this, we expect to generate novel insights of broad relevance for the fields of systems, computational and developmental biology.
Max ERC Funding
1 452 604 €
Duration
Start date: 2020-07-01, End date: 2025-06-30
Project acronym EASTFE3
Project Efficient and accurate simulation techniques for free energies, enthalpies and entropies
Researcher (PI) Bernard Christiaan Oostenbrink
Host Institution (HI) UNIVERSITAET FUER BODENKULTUR WIEN
Call Details Starting Grant (StG), LS2, ERC-2010-StG_20091118
Summary Computational, structure-based, drug design offers insight at an atomic resolution, which is commonly not attainable by experimental means. Detailed calculations on protein-ligand interactions help to rationalize and predict experimental findings. Accurate and efficient calculations of binding free energies is essential in this respect. In addition, knowledge concerning the enthalpic and entropic contributions are highly relevant to determine novel drug design strategies and to understand the underlying principles of ligand binding.
Currently available methods to address ligand affinity either do not include all relevant contributions to the binding free energy, or are too computationally demanding to be applied straightforwardly. In addition, calculations on enthalpy and entropy for drug design purposes are very rare, due to the difficulty in calculating these accurately. This proposal describes the research that leads the way to new, standard applications to be used in drug design processes in academia and industry. Furthermore, we propose to investigate the enthalpic and entropic contributions to ligand binding. We define a ligand-surroundings enthalpy and entropy, which conveys more information than the experimentally accessible enthalpy and entropy of ligand binding.
In support of this research, we will develop new enhanced sampling techniques which not only render the above calculations practically feasible, but which will also find their application in related research questions such as the protein folding problem or the elucidation of protein-protein interactions.
The methods described are highly relevant for the pharmaceutical industry, where currently available computational approaches are insufficient to answer the questions of todays drug discovery programmes.
Summary
Computational, structure-based, drug design offers insight at an atomic resolution, which is commonly not attainable by experimental means. Detailed calculations on protein-ligand interactions help to rationalize and predict experimental findings. Accurate and efficient calculations of binding free energies is essential in this respect. In addition, knowledge concerning the enthalpic and entropic contributions are highly relevant to determine novel drug design strategies and to understand the underlying principles of ligand binding.
Currently available methods to address ligand affinity either do not include all relevant contributions to the binding free energy, or are too computationally demanding to be applied straightforwardly. In addition, calculations on enthalpy and entropy for drug design purposes are very rare, due to the difficulty in calculating these accurately. This proposal describes the research that leads the way to new, standard applications to be used in drug design processes in academia and industry. Furthermore, we propose to investigate the enthalpic and entropic contributions to ligand binding. We define a ligand-surroundings enthalpy and entropy, which conveys more information than the experimentally accessible enthalpy and entropy of ligand binding.
In support of this research, we will develop new enhanced sampling techniques which not only render the above calculations practically feasible, but which will also find their application in related research questions such as the protein folding problem or the elucidation of protein-protein interactions.
The methods described are highly relevant for the pharmaceutical industry, where currently available computational approaches are insufficient to answer the questions of todays drug discovery programmes.
Max ERC Funding
1 485 615 €
Duration
Start date: 2011-01-01, End date: 2015-12-31
Project acronym EFFECTOMICS
Project EFFECTOMICS- elucidating the toolbox of
biotrophic pathogens
Researcher (PI) Armin Djamei
Host Institution (HI) GREGOR MENDEL INSTITUT FUR MOLEKULARE PFLANZENBIOLOGIE GMBH
Call Details Starting Grant (StG), LS2, ERC-2013-StG
Summary "Our existence as human beings is based on plants and their products. Worldwide, crops are threatened by pests including biotrophic fungi. Therefore, it is of vital interest to develop new strategies to reduce crop losses and to improve crop plants for the growing world population. Biotrophic plant pathogens employ small secreted molecules, so-called effectors, to overcome plant defence systems and to establish biotrophy. The rapid increase in available genome sequences of biotrophic pathogens and in transcriptomic datasets of their biotrophic stages allow us to identify putative secreted proteinaceous effectors by bioinformatic means. However, our insight into the functions of these effectors is still very limited. In this proposal, the PI´s extensive experience on both the plant host side and the fungal pathogen side of the biotrophic interaction is exploited to develop a workflow for functional, partially robotic-based screens to fill this gap. The combination of screen-deduced functional information with the analysis of effector localisation and specific host interactors will provide the basis for formulating starting hypotheses of effector function. These will then be tested in individual case studies, employing the well established Ustilago maydis-Zea mays as well as the new Ustilago bromivora-Brachypodium distachyon model systems. The project will be conducted at the Max Planck Institute (MPI) for Terrestrial Microbiology in a highly stimulating scientific environment. Linking the dramatic morphological changes and underlying molecular events during biotrophy on the host side to the action of subsets or even single effector proteins will allow the creation of a synthetic effectome. The deep functional understanding of the manipulative toolbox of biotrophs has the potential to facilitate transgenic crop development and will open a new era in the development of sustainable antifungal plant protection strategies."
Summary
"Our existence as human beings is based on plants and their products. Worldwide, crops are threatened by pests including biotrophic fungi. Therefore, it is of vital interest to develop new strategies to reduce crop losses and to improve crop plants for the growing world population. Biotrophic plant pathogens employ small secreted molecules, so-called effectors, to overcome plant defence systems and to establish biotrophy. The rapid increase in available genome sequences of biotrophic pathogens and in transcriptomic datasets of their biotrophic stages allow us to identify putative secreted proteinaceous effectors by bioinformatic means. However, our insight into the functions of these effectors is still very limited. In this proposal, the PI´s extensive experience on both the plant host side and the fungal pathogen side of the biotrophic interaction is exploited to develop a workflow for functional, partially robotic-based screens to fill this gap. The combination of screen-deduced functional information with the analysis of effector localisation and specific host interactors will provide the basis for formulating starting hypotheses of effector function. These will then be tested in individual case studies, employing the well established Ustilago maydis-Zea mays as well as the new Ustilago bromivora-Brachypodium distachyon model systems. The project will be conducted at the Max Planck Institute (MPI) for Terrestrial Microbiology in a highly stimulating scientific environment. Linking the dramatic morphological changes and underlying molecular events during biotrophy on the host side to the action of subsets or even single effector proteins will allow the creation of a synthetic effectome. The deep functional understanding of the manipulative toolbox of biotrophs has the potential to facilitate transgenic crop development and will open a new era in the development of sustainable antifungal plant protection strategies."
Max ERC Funding
1 446 316 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
Project acronym EINME
Project Systematic investigation of epistasis in molecular evolution
Researcher (PI) Fyodor Kondrashov
Host Institution (HI) INSTITUTE OF SCIENCE AND TECHNOLOGY AUSTRIA
Call Details Starting Grant (StG), LS2, ERC-2013-StG
Summary Why does a mutation have a deleterious effect when it occurs in one species but shows no apparent consequences on the phenotype when it occurs in another species? What are some of possible explanations on the molecular basis of this phenomenon? Are the computational predictions of the extent of this phenomenon in nature accurate? The present project aims to take a swing at answering, at least partially, these basic questions of epistasis in molecular evolution. Within our work we plan to address these issues using computational approaches, systematic fitness assays of engineered orthologous genotypes and experimental functional assays of specific cases of epistasis identified by evolutionary analysis. By tackling these goals and utilising this array of approaches the projects aims to create a synthesis between theory and experimentation under the confines of a single laboratory that will allow us to study this phenomenon in a systematic fashion on the interface of different fields and methodologies.
Summary
Why does a mutation have a deleterious effect when it occurs in one species but shows no apparent consequences on the phenotype when it occurs in another species? What are some of possible explanations on the molecular basis of this phenomenon? Are the computational predictions of the extent of this phenomenon in nature accurate? The present project aims to take a swing at answering, at least partially, these basic questions of epistasis in molecular evolution. Within our work we plan to address these issues using computational approaches, systematic fitness assays of engineered orthologous genotypes and experimental functional assays of specific cases of epistasis identified by evolutionary analysis. By tackling these goals and utilising this array of approaches the projects aims to create a synthesis between theory and experimentation under the confines of a single laboratory that will allow us to study this phenomenon in a systematic fashion on the interface of different fields and methodologies.
Max ERC Funding
1 461 576 €
Duration
Start date: 2014-01-01, End date: 2018-12-31
Project acronym Enhancer ID
Project Identification and functional characterization of mammalian enhancers and transcriptional co-factors during cellular signaling and cell fate transitions
Researcher (PI) Alexander Stark
Host Institution (HI) FORSCHUNGSINSTITUT FUR MOLEKULARE PATHOLOGIE GESELLSCHAFT MBH
Call Details Consolidator Grant (CoG), LS2, ERC-2014-CoG
Summary A major goal in biology is to understand how gene regulatory information is encoded by the human genome and how it defines different gene expression programs and cell types. Enhancers are genomic elements that control transcription, yet despite their importance, only a minority of enhancers are known and functionally characterized. In particular, their activity changes during cellular signalling or cell type transitions are largely elusive. Furthermore, fundamental questions about transcriptional co-factors have remained unanswered even though they regulate enhancer activities and have become attractive therapeutic targets, e.g. for cancer treatment.
Here, I propose a functional genomics approach in mammalian cells with three specific objectives: First, we will identify and functionally characterize transcriptional enhancers in selected human and mouse cells using the recently developed quantitative enhancer activity assay STARR-seq. Second, we will determine enhancer activity changes quantitatively during steroid hormone signalling, cell differentiation, and malignant transformation to reveal enhancers that are important for these processes. Third, we will systematically dissect the functional relationship of enhancers and transcriptional co-factors.
This proposal uses emerging in-house technology to address fundamental questions in enhancer biology and complement the genome-wide profiling of gene expression and chromatin states (e.g. by ENCODE). We will gain insights into the genomic organization of active enhancers and reveal chromatin or sequence features associated with dynamic activity changes. I also expect that we will be able to define co-factor requirements for enhancer function and reveal if different types of enhancers exist. Given our expertise in experimental and computational approaches and STARR-seq, I anticipate that we reach our aims and make major contributions to the understanding of gene regulation in mammals.
Summary
A major goal in biology is to understand how gene regulatory information is encoded by the human genome and how it defines different gene expression programs and cell types. Enhancers are genomic elements that control transcription, yet despite their importance, only a minority of enhancers are known and functionally characterized. In particular, their activity changes during cellular signalling or cell type transitions are largely elusive. Furthermore, fundamental questions about transcriptional co-factors have remained unanswered even though they regulate enhancer activities and have become attractive therapeutic targets, e.g. for cancer treatment.
Here, I propose a functional genomics approach in mammalian cells with three specific objectives: First, we will identify and functionally characterize transcriptional enhancers in selected human and mouse cells using the recently developed quantitative enhancer activity assay STARR-seq. Second, we will determine enhancer activity changes quantitatively during steroid hormone signalling, cell differentiation, and malignant transformation to reveal enhancers that are important for these processes. Third, we will systematically dissect the functional relationship of enhancers and transcriptional co-factors.
This proposal uses emerging in-house technology to address fundamental questions in enhancer biology and complement the genome-wide profiling of gene expression and chromatin states (e.g. by ENCODE). We will gain insights into the genomic organization of active enhancers and reveal chromatin or sequence features associated with dynamic activity changes. I also expect that we will be able to define co-factor requirements for enhancer function and reveal if different types of enhancers exist. Given our expertise in experimental and computational approaches and STARR-seq, I anticipate that we reach our aims and make major contributions to the understanding of gene regulation in mammals.
Max ERC Funding
1 999 906 €
Duration
Start date: 2015-09-01, End date: 2021-07-31
Project acronym EpigenomeProgramming
Project An experimental and bioinformatic toolbox for functional epigenomics and its application to epigenetically making and breaking a cancer cell
Researcher (PI) Christoph Bock
Host Institution (HI) CEMM - FORSCHUNGSZENTRUM FUER MOLEKULARE MEDIZIN GMBH
Call Details Starting Grant (StG), LS2, ERC-2015-STG
Summary Epigenetic alterations can be detected in all cancers and in essentially every patient. Despite their prevalence, the concrete functional roles of these alterations are not well understood, for two reasons: First, cancer samples tend to carry many correlated epigenetic alterations, making it difficult to statistically distinguish relevant driver events from those that co-occur for other reasons. Second, we lack tools for targeted epigenome editing that could be used to validate biological function in perturbation and rescue experiments.
The proposed project strives to overcome these limitations through experimental and bioinformatic methods development, with the ambition of making and breaking cancer cells in vitro by introducing defined sets of epigenetic alterations. We will focus on leukemia as our “model cancer” (given its low mutation rate, frequent defects in epigenetic regulators, and availability of excellent functional assays), but the concepts and methods are general. In Aim 1, we will generate epigenome profiles for a human knockout cell collection comprising 100 epigenetic regulators and use the data to functionally annotate thousands of epigenetic alterations observed in large cancer datasets. In Aim 2, we will develop an experimental toolbox for epigenome programming using epigenetic drugs, CRISPR-assisted recruitment of epigenetic modifiers for locus-specific editing, and cell-derived guide RNA libraries for epigenome copying. Finally, in Aim 3 we will explore epigenome programming (methods from Aim 2) of candidate driver events (predictions from Aim 1) with the ultimate goal of converting cancer cells into non-cancer cells and vice versa.
In summary, this project will establish a broadly applicable methodology and toolbox for dissecting the functional roles of epigenetic alterations in cancer. Moreover, successful creation of a cancer that is driven purely by epigenetic alterations could challenge our understanding of cancer as a genetic disease.
Summary
Epigenetic alterations can be detected in all cancers and in essentially every patient. Despite their prevalence, the concrete functional roles of these alterations are not well understood, for two reasons: First, cancer samples tend to carry many correlated epigenetic alterations, making it difficult to statistically distinguish relevant driver events from those that co-occur for other reasons. Second, we lack tools for targeted epigenome editing that could be used to validate biological function in perturbation and rescue experiments.
The proposed project strives to overcome these limitations through experimental and bioinformatic methods development, with the ambition of making and breaking cancer cells in vitro by introducing defined sets of epigenetic alterations. We will focus on leukemia as our “model cancer” (given its low mutation rate, frequent defects in epigenetic regulators, and availability of excellent functional assays), but the concepts and methods are general. In Aim 1, we will generate epigenome profiles for a human knockout cell collection comprising 100 epigenetic regulators and use the data to functionally annotate thousands of epigenetic alterations observed in large cancer datasets. In Aim 2, we will develop an experimental toolbox for epigenome programming using epigenetic drugs, CRISPR-assisted recruitment of epigenetic modifiers for locus-specific editing, and cell-derived guide RNA libraries for epigenome copying. Finally, in Aim 3 we will explore epigenome programming (methods from Aim 2) of candidate driver events (predictions from Aim 1) with the ultimate goal of converting cancer cells into non-cancer cells and vice versa.
In summary, this project will establish a broadly applicable methodology and toolbox for dissecting the functional roles of epigenetic alterations in cancer. Moreover, successful creation of a cancer that is driven purely by epigenetic alterations could challenge our understanding of cancer as a genetic disease.
Max ERC Funding
1 281 205 €
Duration
Start date: 2016-12-01, End date: 2021-11-30
Project acronym GameofGates
Project Solute carrier proteins as the gates managing chemical access to cells
Researcher (PI) Giulio SUPERTI-FURGA
Host Institution (HI) CEMM - FORSCHUNGSZENTRUM FUER MOLEKULARE MEDIZIN GMBH
Call Details Advanced Grant (AdG), LS2, ERC-2015-AdG
Summary Chemical exchange between cells and their environment occurs at cellular membranes, the interface where biology meets chemistry. Studying mechanisms of drug resistance, I realized that SoLute Carrier proteins (SLCs), not only represent the major class of small molecule transporters, but that they are encoded by one of the most neglected group of human genes. I identified a case where an SLC controls the activity of mTOR, suggesting that other SLCs may be involved in signalling. This formed the basis for the GameofGates project proposal. The name refers to SLCs as a metaphor for cellular gates coordinating access to resources following game rules that are largely unknown but worth learning, as the acquired knowledge could impact our understanding of cellular physiology and open avenues for innovative treatment of human diseases.
GameofGates (GoG) plans the investigation of SLC function by comprehensively and deeply charting the genetic and protein interaction landscape of SLCs in a human cell line, while monitoring fitness, drug sensitivity and metabolic state. GoG aims at functionally de-orphanize many SLCs by assessing hundreds of thousands of genetic interactions as well as thousands protein and drug interactions. I hypothesize that SLC action is linked to signalling pathways and plays an important role in integration of metabolism and cell regulation for successful homeostasis. I propose that whole circuits of SLCs may be linked to particular nutrient auxotrophy states and that knowledge of these dependencies could instruct assessment of vulnerabilities in cancer cells. In turn, these could be pharmacologically exploited using existing or future drugs. Overall, GoG should position enough pieces into functional and regulatory networks in the SLC puzzle game to facilitate future work and motivate the community to embrace investigation of SLCs as conveyers of metabolic and chemical integration of cell biology with physiology and, in a wider scope, ecology.
Summary
Chemical exchange between cells and their environment occurs at cellular membranes, the interface where biology meets chemistry. Studying mechanisms of drug resistance, I realized that SoLute Carrier proteins (SLCs), not only represent the major class of small molecule transporters, but that they are encoded by one of the most neglected group of human genes. I identified a case where an SLC controls the activity of mTOR, suggesting that other SLCs may be involved in signalling. This formed the basis for the GameofGates project proposal. The name refers to SLCs as a metaphor for cellular gates coordinating access to resources following game rules that are largely unknown but worth learning, as the acquired knowledge could impact our understanding of cellular physiology and open avenues for innovative treatment of human diseases.
GameofGates (GoG) plans the investigation of SLC function by comprehensively and deeply charting the genetic and protein interaction landscape of SLCs in a human cell line, while monitoring fitness, drug sensitivity and metabolic state. GoG aims at functionally de-orphanize many SLCs by assessing hundreds of thousands of genetic interactions as well as thousands protein and drug interactions. I hypothesize that SLC action is linked to signalling pathways and plays an important role in integration of metabolism and cell regulation for successful homeostasis. I propose that whole circuits of SLCs may be linked to particular nutrient auxotrophy states and that knowledge of these dependencies could instruct assessment of vulnerabilities in cancer cells. In turn, these could be pharmacologically exploited using existing or future drugs. Overall, GoG should position enough pieces into functional and regulatory networks in the SLC puzzle game to facilitate future work and motivate the community to embrace investigation of SLCs as conveyers of metabolic and chemical integration of cell biology with physiology and, in a wider scope, ecology.
Max ERC Funding
2 389 782 €
Duration
Start date: 2016-10-01, End date: 2021-09-30
Project acronym I-FIVE
Project Interferon-focused Innate Immunity Interactome and Inhibitome
Researcher (PI) Giulio Gino Maria Superti Furga
Host Institution (HI) CEMM - FORSCHUNGSZENTRUM FUER MOLEKULARE MEDIZIN GMBH
Call Details Advanced Grant (AdG), LS2, ERC-2009-AdG
Summary After a decade of development in model organisms and later in mammalian cells, mass spectrometry-based functional proteomics approaches have come of age and are ready to enable a systematic study of the innate immune system. We propose to cross the large-scale proteomics and innate immunity disciplines to obtain a functionally annotated map of the molecular machinery involved in viral recognition and leading to the hallmark interferon response, through a three-pronged approach: 1. Map the interactome of innate immunity proteins in macrophages to establish the network of components leading to interferon production; 2. Chart the interactions of molecular patterns, mostly nucleic acids, to identify the receptors and sensors at the non-self/self interface; 3. Study viral pathogenicity factors as molecular jammers of the anti-viral response and elucidate their mode of action to uncover critical nodes (inhibitome). Datasets are integrated and released at regular intervals with embargoed windows allowing a network of collaborators/own laboratory to do in-depth validation. New components at data intersections will be tested through loss-of-function experiments and standardized read-outs for the interferon pathway as well as genetic association with autoimmune diseases. Because of its unbiased/large scope and its cross-validating approaches, wherein the newly mapped circuitry is modeled, challenged by inducers and perturbed by viral agents, i-FIVE has the potential to promote a systems-level understanding of the interferon branch of molecular innate immunity. This insight may in turn create medical opportunities for the treatment of autoimmune disorders, septic shoc, arthritis as well as in boosting anti-viral responses.
Summary
After a decade of development in model organisms and later in mammalian cells, mass spectrometry-based functional proteomics approaches have come of age and are ready to enable a systematic study of the innate immune system. We propose to cross the large-scale proteomics and innate immunity disciplines to obtain a functionally annotated map of the molecular machinery involved in viral recognition and leading to the hallmark interferon response, through a three-pronged approach: 1. Map the interactome of innate immunity proteins in macrophages to establish the network of components leading to interferon production; 2. Chart the interactions of molecular patterns, mostly nucleic acids, to identify the receptors and sensors at the non-self/self interface; 3. Study viral pathogenicity factors as molecular jammers of the anti-viral response and elucidate their mode of action to uncover critical nodes (inhibitome). Datasets are integrated and released at regular intervals with embargoed windows allowing a network of collaborators/own laboratory to do in-depth validation. New components at data intersections will be tested through loss-of-function experiments and standardized read-outs for the interferon pathway as well as genetic association with autoimmune diseases. Because of its unbiased/large scope and its cross-validating approaches, wherein the newly mapped circuitry is modeled, challenged by inducers and perturbed by viral agents, i-FIVE has the potential to promote a systems-level understanding of the interferon branch of molecular innate immunity. This insight may in turn create medical opportunities for the treatment of autoimmune disorders, septic shoc, arthritis as well as in boosting anti-viral responses.
Max ERC Funding
1 974 022 €
Duration
Start date: 2010-04-01, End date: 2015-03-31
Project acronym MAXMAP
Project Developing maximum-resolution genotype-phenotype maps using whole-genome polymorphism data
Researcher (PI) Lars Magnus Henrik Nordborg
Host Institution (HI) GREGOR MENDEL INSTITUT FUR MOLEKULARE PFLANZENBIOLOGIE GMBH
Call Details Advanced Grant (AdG), LS2, ERC-2010-AdG_20100317
Summary Although pioneered by human geneticists as a potential solution to the challenging problem of finding the genetic basis of common human diseases, genome-wide association studies (GWAS) have, owing to advances in genotyping and sequencing technology, become an obvious general approach for studying the genetics of natural variation. They are particularly useful when inbred lines are available because once these lines have been genotyped they can be phenotyped multiple times, making it possible (as well as extremely cost-effective) to study many different traits in many different environments, while replicating the phenotypic measurements to reduce environmental noise. Here we propose to continue our groundbreaking GWAS work in the model plant Arabidopsis thaliana. We will explore the limits of the approach, moving beyond marker-trait linkage disequilibrium to full sequence information. We will carry out GWAS of important life-history traits using over 1000 inbred A. thaliana lines for which nearly complete sequence information is available. The GWAS will be complemented by linkage mapping in F2 crosses to eliminate confounding linkage disequilibrium, associations will be verified experimentally, and confirmed causal polymorphisms will be added to the model in an iterative manner in order to create an increasingly refined genotype-phenotype map.
Summary
Although pioneered by human geneticists as a potential solution to the challenging problem of finding the genetic basis of common human diseases, genome-wide association studies (GWAS) have, owing to advances in genotyping and sequencing technology, become an obvious general approach for studying the genetics of natural variation. They are particularly useful when inbred lines are available because once these lines have been genotyped they can be phenotyped multiple times, making it possible (as well as extremely cost-effective) to study many different traits in many different environments, while replicating the phenotypic measurements to reduce environmental noise. Here we propose to continue our groundbreaking GWAS work in the model plant Arabidopsis thaliana. We will explore the limits of the approach, moving beyond marker-trait linkage disequilibrium to full sequence information. We will carry out GWAS of important life-history traits using over 1000 inbred A. thaliana lines for which nearly complete sequence information is available. The GWAS will be complemented by linkage mapping in F2 crosses to eliminate confounding linkage disequilibrium, associations will be verified experimentally, and confirmed causal polymorphisms will be added to the model in an iterative manner in order to create an increasingly refined genotype-phenotype map.
Max ERC Funding
2 183 956 €
Duration
Start date: 2011-05-01, End date: 2016-04-30