Project acronym DYNACLOCK
Project Dynamic protein-DNA interactomes and circadian transcription regulatory networks in mammals
Researcher (PI) Felix Naef
Host Institution (HI) ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE
Call Details Starting Grant (StG), LS2, ERC-2010-StG_20091118
Summary The aim of this project is to understand the dynamics of protein-DNA interactomes underlying circadian oscillators in mammals, and how these shape circadian transcriptional output programs. Specifically our goal is to solve a fundamental issue in circadian biology: the phase specificity problem underlying circadian gene expression. We have taken a challenging and original multi-disciplinary approach in which molecular biology experiments will be tightly interlinked with computational analyses and biophysical modeling. The approach will generate time resolved protein-DNA interactomes in mouse liver for several key circadian repressors at unprecedented resolution. These experiments will be complemented with chromosome conformation capture (3C) experiments to monitor how looping interactions and 3D genome structure rearrange during the circadian cycle, which will inform on how circadian transcription networks use long-range gene regulatory mechanisms. Novel computational algorithms based on biophysical principles will be developed and implemented to optimally analyze interactome and 3C datasets. For the latter, statistical models from polymer physics will be used to reconstruct the chromatin networks and interaction maps from the 3C data. At the detailed level of individual cells, we will investigate transcription bursts, and how those are involved in the control of circadian gene expression. In particular we will exploit high temporal resolution bioluminescence reporters using a biophysical model of transcription coupled with a Hidden Markov Model (HMM). Through our innovative approach, we expect that the data generated and state-of-the-art analyses performed will lead novel insight into the role and mechanics of circadian transcription in controlling circadian outputs in mammals.
Summary
The aim of this project is to understand the dynamics of protein-DNA interactomes underlying circadian oscillators in mammals, and how these shape circadian transcriptional output programs. Specifically our goal is to solve a fundamental issue in circadian biology: the phase specificity problem underlying circadian gene expression. We have taken a challenging and original multi-disciplinary approach in which molecular biology experiments will be tightly interlinked with computational analyses and biophysical modeling. The approach will generate time resolved protein-DNA interactomes in mouse liver for several key circadian repressors at unprecedented resolution. These experiments will be complemented with chromosome conformation capture (3C) experiments to monitor how looping interactions and 3D genome structure rearrange during the circadian cycle, which will inform on how circadian transcription networks use long-range gene regulatory mechanisms. Novel computational algorithms based on biophysical principles will be developed and implemented to optimally analyze interactome and 3C datasets. For the latter, statistical models from polymer physics will be used to reconstruct the chromatin networks and interaction maps from the 3C data. At the detailed level of individual cells, we will investigate transcription bursts, and how those are involved in the control of circadian gene expression. In particular we will exploit high temporal resolution bioluminescence reporters using a biophysical model of transcription coupled with a Hidden Markov Model (HMM). Through our innovative approach, we expect that the data generated and state-of-the-art analyses performed will lead novel insight into the role and mechanics of circadian transcription in controlling circadian outputs in mammals.
Max ERC Funding
1 500 000 €
Duration
Start date: 2011-03-01, End date: 2016-02-29
Project acronym ECMETABOLISM
Project Targeting endothelial metabolism: a novel anti-angiogenic therapy
Researcher (PI) Peter Frans Martha Carmeliet
Host Institution (HI) VIB
Call Details Advanced Grant (AdG), LS2, ERC-2010-AdG_20100317
Summary Current anti-angiogenesis based anti-tumor therapy relies on starving tumors by blocking their vascular supply via inhibition of growth factors. However, limitations such as resistance and toxicity, mandate conceptually distinct approaches. We will explore an entirely novel and long-overlooked strategy to discover additional anti-angiogenic candidates, based on the following innovative concept: ¿rather than STARVING TUMORS BY BLOCKING THEIR VASCULAR SUPPLY, we intend TO STARVE BLOOD VESSELS BY BLOCKING THEIR METABOLIC ENERGY SUPPLY¿, so that new vessels cannot form and nourish the growing tumor. This project is a completely new research avenue in our group, but we expect that it will offer refreshing long-term research and translational opportunities for the field.
Because so little is known on endothelial cell (EC) metabolism, we will (i) via a multi-disciplinary systems-biology approach of transcriptomics, proteomics, computational network modeling, metabolomics and flux-omics, draw an endothelio-metabolic map in angiogenesis. This will allow us to identify metabolic regulators of angiogenesis, which will be further validated and characterized in (ii) loss and gain-of-function studies in various angiogenesis models in vitro and (iii) in vivo in zebrafish (knockdown; zinc finger nuclease mediated knockout), providing prescreen data to select the most promising candidates. (iv) EC-specific down-regulation (miR RNAi) or knockout studies of selected candidates in mice will confirm their relevance for angiogenic phenotypes in a preclinical model; and ultimately (v) a translational study evaluating EC metabolism-targeted anti-angiogenic strategies (pharmacological inhibitors, antibodies, small molecular compounds) will be performed in tumor models in the mouse.
Summary
Current anti-angiogenesis based anti-tumor therapy relies on starving tumors by blocking their vascular supply via inhibition of growth factors. However, limitations such as resistance and toxicity, mandate conceptually distinct approaches. We will explore an entirely novel and long-overlooked strategy to discover additional anti-angiogenic candidates, based on the following innovative concept: ¿rather than STARVING TUMORS BY BLOCKING THEIR VASCULAR SUPPLY, we intend TO STARVE BLOOD VESSELS BY BLOCKING THEIR METABOLIC ENERGY SUPPLY¿, so that new vessels cannot form and nourish the growing tumor. This project is a completely new research avenue in our group, but we expect that it will offer refreshing long-term research and translational opportunities for the field.
Because so little is known on endothelial cell (EC) metabolism, we will (i) via a multi-disciplinary systems-biology approach of transcriptomics, proteomics, computational network modeling, metabolomics and flux-omics, draw an endothelio-metabolic map in angiogenesis. This will allow us to identify metabolic regulators of angiogenesis, which will be further validated and characterized in (ii) loss and gain-of-function studies in various angiogenesis models in vitro and (iii) in vivo in zebrafish (knockdown; zinc finger nuclease mediated knockout), providing prescreen data to select the most promising candidates. (iv) EC-specific down-regulation (miR RNAi) or knockout studies of selected candidates in mice will confirm their relevance for angiogenic phenotypes in a preclinical model; and ultimately (v) a translational study evaluating EC metabolism-targeted anti-angiogenic strategies (pharmacological inhibitors, antibodies, small molecular compounds) will be performed in tumor models in the mouse.
Max ERC Funding
2 365 224 €
Duration
Start date: 2011-05-01, End date: 2016-04-30
Project acronym POPRNASEQ
Project Population transcriptional genomics in humans using high throughput sequencing
Researcher (PI) Emmanouil Dermitzakis
Host Institution (HI) UNIVERSITE DE GENEVE
Call Details Starting Grant (StG), LS2, ERC-2010-StG_20091118
Summary Gene expression is one of the marks of cellular state and function. The relative abundance of transcripts defines and is a result of the differentiation status of a cell. Interrogation of gene expression levels and patterns in the human and other genomes can be informative about perturbations from the average pattern due to external stimuli or internal factors such as genetic variants. Gene expression profiles have been extensively used to assess developmental processes, pathways contributing to cell differentiation, and predicting the outcome of disease status.
Understanding the effects of genetic variation in basic cellular processes such as gene expression is key to the dissection of the genetic contributions to whole organism phenotypes.
We propose to interrogate the transcriptome of primary fibroblasts, primary T-cells and EBV-transformed B-cell (lymphoblastoid cell lines or LCLs) from umbilical cords of 200 individuals of European descent using next generation sequencing (mRNAseq). A subset will also be interrogated for transcriptionally engaged RNA polymerases (GROseq) and protein abundance. These data will be analyzed for the detection of eQTLs and other genetic effects associated with variation in alternative splicing and other properties of the transcripts and dissection of the genetic effects from primary transcription to protein and their tissue specific effects. These data will be integrated with genome-wide association studies and other efforts to dissect the genetic basis of complex traits and diseases in humans. In addition, we will develop bioinformatic models to understand the fine scale regulatory signals that are responsible for the regulatory patterns observed and how sequence variants have an effect on them.
Summary
Gene expression is one of the marks of cellular state and function. The relative abundance of transcripts defines and is a result of the differentiation status of a cell. Interrogation of gene expression levels and patterns in the human and other genomes can be informative about perturbations from the average pattern due to external stimuli or internal factors such as genetic variants. Gene expression profiles have been extensively used to assess developmental processes, pathways contributing to cell differentiation, and predicting the outcome of disease status.
Understanding the effects of genetic variation in basic cellular processes such as gene expression is key to the dissection of the genetic contributions to whole organism phenotypes.
We propose to interrogate the transcriptome of primary fibroblasts, primary T-cells and EBV-transformed B-cell (lymphoblastoid cell lines or LCLs) from umbilical cords of 200 individuals of European descent using next generation sequencing (mRNAseq). A subset will also be interrogated for transcriptionally engaged RNA polymerases (GROseq) and protein abundance. These data will be analyzed for the detection of eQTLs and other genetic effects associated with variation in alternative splicing and other properties of the transcripts and dissection of the genetic effects from primary transcription to protein and their tissue specific effects. These data will be integrated with genome-wide association studies and other efforts to dissect the genetic basis of complex traits and diseases in humans. In addition, we will develop bioinformatic models to understand the fine scale regulatory signals that are responsible for the regulatory patterns observed and how sequence variants have an effect on them.
Max ERC Funding
1 500 000 €
Duration
Start date: 2011-05-01, End date: 2016-04-30
Project acronym PROKRNA
Project Prokaryotic RNomics: Unravelling the RNA-mediated regulatory layers
Researcher (PI) Rotem Sorek
Host Institution (HI) WEIZMANN INSTITUTE OF SCIENCE
Call Details Starting Grant (StG), LS2, ERC-2010-StG_20091118
Summary Pioneering studies from the recent year, including those published by the PI of this proposal, are revolutionizing our perception of prokaryotic transcriptomes, and reveal unexpected regulatory complexity. Two central concepts are arising: the unanticipated abundance of cis-antisense RNAs overlapping protein coding genes, and alternative transcripts resulting from a dynamic behaviour of operon structures (where genes can be included or excluded from a polycistronic transcript in response to environmental cues). Understanding these phenomena holds a great potential for our ability to decipher how bacteria regulate their complex life styles and pathogenic behaviours, but their dynamics, regulatory roles, and effects on combinatorially increasing the regulatory capacity of the genome are completely unknown.
The primary objectives of this proposed research are: i) to understand the extent, regulatory roles, and evolutionary consequences of cis-antisense
RNAs in prokaryotes; ii) to understand the regulatory code, combinatorial effects and dynamics of alternative operon structures; and, in parallel iii) to develop a unified framework for comparative prokaryotic transcriptomics.
Our strategy is based on a combination of deep sequencing technologies, computational modelling and data analyses, systems biology
approaches, and focused molecular biology experiments. We will identify the extent and the impact of these RNA-based regulatory layers in representative pathogenic and non-pathogenic species across the prokaryotic tree of life, study their functional and evolutionary consequences, and break the regulatory code controlling them. Our planned research has the potential of producing
methodological and conceptual breakthroughs in the emerging field of prokaryotic transcriptomics.
Summary
Pioneering studies from the recent year, including those published by the PI of this proposal, are revolutionizing our perception of prokaryotic transcriptomes, and reveal unexpected regulatory complexity. Two central concepts are arising: the unanticipated abundance of cis-antisense RNAs overlapping protein coding genes, and alternative transcripts resulting from a dynamic behaviour of operon structures (where genes can be included or excluded from a polycistronic transcript in response to environmental cues). Understanding these phenomena holds a great potential for our ability to decipher how bacteria regulate their complex life styles and pathogenic behaviours, but their dynamics, regulatory roles, and effects on combinatorially increasing the regulatory capacity of the genome are completely unknown.
The primary objectives of this proposed research are: i) to understand the extent, regulatory roles, and evolutionary consequences of cis-antisense
RNAs in prokaryotes; ii) to understand the regulatory code, combinatorial effects and dynamics of alternative operon structures; and, in parallel iii) to develop a unified framework for comparative prokaryotic transcriptomics.
Our strategy is based on a combination of deep sequencing technologies, computational modelling and data analyses, systems biology
approaches, and focused molecular biology experiments. We will identify the extent and the impact of these RNA-based regulatory layers in representative pathogenic and non-pathogenic species across the prokaryotic tree of life, study their functional and evolutionary consequences, and break the regulatory code controlling them. Our planned research has the potential of producing
methodological and conceptual breakthroughs in the emerging field of prokaryotic transcriptomics.
Max ERC Funding
1 499 540 €
Duration
Start date: 2011-01-01, End date: 2016-06-30
Project acronym SYMPAC
Project Synthetic metabolic pathways for carbon fixation
Researcher (PI) Ron Milo
Host Institution (HI) WEIZMANN INSTITUTE OF SCIENCE
Call Details Starting Grant (StG), LS2, ERC-2010-StG_20091118
Summary Carbon fixation is the main pathway for storing energy and accumulating biomass in the living world. It is also the principal reason for humanity s utilization of land and water. Under human cultivation, carbon fixation significantly limits growth. Hence increasing carbon fixation rate is of major importance towards agricultural and energetic sustainability.
Are there limits on the rate of such central metabolic pathways? Attempts to improve the rate of Rubisco, the key enzyme in the Calvin-Benson cycle, have achieved very limited success. In this proposal we try to overcome this bottleneck by systematically exploring the space of carbon fixation pathways that can be assembled from all ~4000 metabolic enzymes known in nature. We computationally compare all possible pathways based on kinetics, energetics and topology. Our initial analysis suggests a new family of synthetic carbon fixation pathways utilizing the most effective carboxylating enzyme, PEPC. We propose to experimentally test these cycles in the most genetically tractable context by constructing an E. coli strain that will depend on carbon fixation as its sole carbon input. Energy will be supplied by compounds that cannot be used as carbon source. Initially, we will devise an autotrophic E. coli strain to use the Calvin-Benson Cycle; in the next stage, we will implement the most promising synthetic cycles. Systematic in vivo comparison will guide the future implementation in natural photosynthetic organisms.
At the basic science level, this proposal revisits and challenges our understanding of central carbon metabolism and growth. Concomitantly, it is an evolutionary experiment on integration of a biological novelty. It will serve as a model for significantly adapting a central metabolic pathway.
Summary
Carbon fixation is the main pathway for storing energy and accumulating biomass in the living world. It is also the principal reason for humanity s utilization of land and water. Under human cultivation, carbon fixation significantly limits growth. Hence increasing carbon fixation rate is of major importance towards agricultural and energetic sustainability.
Are there limits on the rate of such central metabolic pathways? Attempts to improve the rate of Rubisco, the key enzyme in the Calvin-Benson cycle, have achieved very limited success. In this proposal we try to overcome this bottleneck by systematically exploring the space of carbon fixation pathways that can be assembled from all ~4000 metabolic enzymes known in nature. We computationally compare all possible pathways based on kinetics, energetics and topology. Our initial analysis suggests a new family of synthetic carbon fixation pathways utilizing the most effective carboxylating enzyme, PEPC. We propose to experimentally test these cycles in the most genetically tractable context by constructing an E. coli strain that will depend on carbon fixation as its sole carbon input. Energy will be supplied by compounds that cannot be used as carbon source. Initially, we will devise an autotrophic E. coli strain to use the Calvin-Benson Cycle; in the next stage, we will implement the most promising synthetic cycles. Systematic in vivo comparison will guide the future implementation in natural photosynthetic organisms.
At the basic science level, this proposal revisits and challenges our understanding of central carbon metabolism and growth. Concomitantly, it is an evolutionary experiment on integration of a biological novelty. It will serve as a model for significantly adapting a central metabolic pathway.
Max ERC Funding
1 498 792 €
Duration
Start date: 2011-01-01, End date: 2015-12-31
