Project acronym CELLDOCTOR
Project Quantitative understanding of a living system and its engineering as a cellular organelle
Researcher (PI) Luis Serrano
Host Institution (HI) FUNDACIO CENTRE DE REGULACIO GENOMICA
Call Details Advanced Grant (AdG), LS2, ERC-2008-AdG
Summary The idea of harnessing living organisms for treating human diseases is not new but, so far, the majority of the living vectors used in human therapy are viruses which have the disadvantage of the limited number of genes and networks that can contain. Bacteria allow the cloning of complex networks and the possibility of making a large plethora of compounds, naturally or through careful redesign. One of the main limitations for the use of bacteria to treat human diseases is their complexity, the existence of a cell wall that difficult the communication with the target cells, the lack of control over its growth and the immune response that will elicit on its target. Ideally one would like to have a very small bacterium (of a mitochondria size), with no cell wall, which could be grown in Vitro, be genetically manipulated, for which we will have enough data to allow a complete understanding of its behaviour and which could live as a human cell parasite. Such a microorganism could in principle be used as a living vector in which genes of interests, or networks producing organic molecules of medical relevance, could be introduced under in Vitro conditions and then inoculated on extracted human cells or in the organism, and then become a new organelle in the host. Then, it could produce and secrete into the host proteins which will be needed to correct a genetic disease, or drugs needed by the patient. To do that, we need to understand in excruciating detail the Biology of the target bacterium and how to interface with the host cell cycle (Systems biology aspect). Then we need to have engineering tools (network design, protein design, simulations) to modify the target bacterium to behave like an organelle once inside the cell (Synthetic biology aspect). M.pneumoniae could be such a bacterium. It is one of the smallest free-living bacterium known (680 genes), has no cell wall, can be cultivated in Vitro, can be genetically manipulated and can enter inside human cells.
Summary
The idea of harnessing living organisms for treating human diseases is not new but, so far, the majority of the living vectors used in human therapy are viruses which have the disadvantage of the limited number of genes and networks that can contain. Bacteria allow the cloning of complex networks and the possibility of making a large plethora of compounds, naturally or through careful redesign. One of the main limitations for the use of bacteria to treat human diseases is their complexity, the existence of a cell wall that difficult the communication with the target cells, the lack of control over its growth and the immune response that will elicit on its target. Ideally one would like to have a very small bacterium (of a mitochondria size), with no cell wall, which could be grown in Vitro, be genetically manipulated, for which we will have enough data to allow a complete understanding of its behaviour and which could live as a human cell parasite. Such a microorganism could in principle be used as a living vector in which genes of interests, or networks producing organic molecules of medical relevance, could be introduced under in Vitro conditions and then inoculated on extracted human cells or in the organism, and then become a new organelle in the host. Then, it could produce and secrete into the host proteins which will be needed to correct a genetic disease, or drugs needed by the patient. To do that, we need to understand in excruciating detail the Biology of the target bacterium and how to interface with the host cell cycle (Systems biology aspect). Then we need to have engineering tools (network design, protein design, simulations) to modify the target bacterium to behave like an organelle once inside the cell (Synthetic biology aspect). M.pneumoniae could be such a bacterium. It is one of the smallest free-living bacterium known (680 genes), has no cell wall, can be cultivated in Vitro, can be genetically manipulated and can enter inside human cells.
Max ERC Funding
2 400 000 €
Duration
Start date: 2009-03-01, End date: 2015-02-28
Project acronym LIQUIDMASS
Project High throughput mass spectrometry of single proteins in liquid environment
Researcher (PI) Montserrat Calleja Gomez
Host Institution (HI) AGENCIA ESTATAL CONSEJO SUPERIOR DEINVESTIGACIONES CIENTIFICAS
Call Details Consolidator Grant (CoG), PE4, ERC-2015-CoG
Summary Although mass spectrometry has brought about major advancements in proteomics in the last decade, protein mass spectrometers still have important limitations. One fundamental limitation is that they require sample ionization, desorption into the gas phase and fragmentation, clearly leading to protein denaturation. Since relevant protein complexes are unstable or transient, their characterization in its native state and physiological environment remains an unexplored route towards the full understanding of protein function and protein interactions. This problem has only been targeted to date through theoretical approaches or low throughput experimental techniques, such as atomic force spectroscopy, optical tweezers or FRET. A high throughput characterization technology capable of addressing single proteins in its native state would have a large impact in proteomics. The goal of LIQUIDMASS is to develop a high throughput spectrometric technique addressing single proteins from complex samples while in physiological conditions. LIQUIDMASS also proposes a new concept for protein spectrometry, by characterizing not only the mass, but also the hydrodynamic radius, geometry and stiffness of single proteins. This multiparameter approach will serve to open up new routes to understand protein structure-function relations by providing insight into the fast conformational changes that occur in liquids. In order to attain these goals, I propose to integrate nanomechanical resonators, nano-optics and nanofluidics. The disruptive approach proposed will bring about new knowledge about protein interactions and protein conformation that is elusive today. The enabling technologies aimed at the LIQUIDMASS will increase our understanding of protein misfolding related diseases, such as Alzheimer’s or diabetes, as well as bring closer a full understanding of the human interactome, contributing to the advancement of the proteomics field.
Summary
Although mass spectrometry has brought about major advancements in proteomics in the last decade, protein mass spectrometers still have important limitations. One fundamental limitation is that they require sample ionization, desorption into the gas phase and fragmentation, clearly leading to protein denaturation. Since relevant protein complexes are unstable or transient, their characterization in its native state and physiological environment remains an unexplored route towards the full understanding of protein function and protein interactions. This problem has only been targeted to date through theoretical approaches or low throughput experimental techniques, such as atomic force spectroscopy, optical tweezers or FRET. A high throughput characterization technology capable of addressing single proteins in its native state would have a large impact in proteomics. The goal of LIQUIDMASS is to develop a high throughput spectrometric technique addressing single proteins from complex samples while in physiological conditions. LIQUIDMASS also proposes a new concept for protein spectrometry, by characterizing not only the mass, but also the hydrodynamic radius, geometry and stiffness of single proteins. This multiparameter approach will serve to open up new routes to understand protein structure-function relations by providing insight into the fast conformational changes that occur in liquids. In order to attain these goals, I propose to integrate nanomechanical resonators, nano-optics and nanofluidics. The disruptive approach proposed will bring about new knowledge about protein interactions and protein conformation that is elusive today. The enabling technologies aimed at the LIQUIDMASS will increase our understanding of protein misfolding related diseases, such as Alzheimer’s or diabetes, as well as bring closer a full understanding of the human interactome, contributing to the advancement of the proteomics field.
Max ERC Funding
2 470 283 €
Duration
Start date: 2016-11-01, End date: 2021-10-31
Project acronym NetMoDEzyme
Project Network models for the computational design of proficient enzymes
Researcher (PI) Silvia Osuna Oliveras
Host Institution (HI) UNIVERSITAT DE GIRONA
Call Details Starting Grant (StG), PE4, ERC-2015-STG
Summary Billions of years of evolution have made enzymes superb catalysts capable of accelerating reactions by several orders of magnitude. The underlying physical principles of their extraordinary catalytic power still remains highly debated, which makes the alteration of natural enzyme activities towards synthetically useful targets a tremendous challenge for modern chemical biology. The routine design of enzymes will, however, have large socio-economic benefits, as because of the enzymatic advantages the production costs of many drugs will be reduced and will allow industries to use environmentally friendly alternatives. The goal of this project is to make the routine design of proficient enzymes possible. Current computational and experimental approaches are able to confer natural enzymes new functionalities but are economically unviable and the catalytic efficiencies lag far behind their natural counterparts. The groundbreaking nature of NetMoDEzyme relies on the application of network models to reduce the complexity of the enzyme design paradigm and completely reformulate previous computational design approaches. The new protocol proposed accurately characterizes the enzyme conformational dynamics and customizes the included mutations by exploiting the correlated movement of the enzyme active site residues with distal regions. The guidelines for mutation are withdrawn from the costly directed evolution experimental technique, and the most proficient enzymes are easily identified via chemoinformatic models. The new strategy will be applied to develop proficient enzymes for the synthesis of enantiomerically pure β-blocker drugs for treating cardiovascular problems at a reduced cost. The experimental assays of our computational predictions will finally elucidate the potential of this genuinely new approach for mimicking Nature’s rules of evolution.
Summary
Billions of years of evolution have made enzymes superb catalysts capable of accelerating reactions by several orders of magnitude. The underlying physical principles of their extraordinary catalytic power still remains highly debated, which makes the alteration of natural enzyme activities towards synthetically useful targets a tremendous challenge for modern chemical biology. The routine design of enzymes will, however, have large socio-economic benefits, as because of the enzymatic advantages the production costs of many drugs will be reduced and will allow industries to use environmentally friendly alternatives. The goal of this project is to make the routine design of proficient enzymes possible. Current computational and experimental approaches are able to confer natural enzymes new functionalities but are economically unviable and the catalytic efficiencies lag far behind their natural counterparts. The groundbreaking nature of NetMoDEzyme relies on the application of network models to reduce the complexity of the enzyme design paradigm and completely reformulate previous computational design approaches. The new protocol proposed accurately characterizes the enzyme conformational dynamics and customizes the included mutations by exploiting the correlated movement of the enzyme active site residues with distal regions. The guidelines for mutation are withdrawn from the costly directed evolution experimental technique, and the most proficient enzymes are easily identified via chemoinformatic models. The new strategy will be applied to develop proficient enzymes for the synthesis of enantiomerically pure β-blocker drugs for treating cardiovascular problems at a reduced cost. The experimental assays of our computational predictions will finally elucidate the potential of this genuinely new approach for mimicking Nature’s rules of evolution.
Max ERC Funding
1 445 588 €
Duration
Start date: 2016-05-01, End date: 2021-04-30
Project acronym NONCODRIVERS
Project Finding noncoding cancer drivers
Researcher (PI) Nuria Lopez Bigas
Host Institution (HI) FUNDACIO INSTITUT DE RECERCA BIOMEDICA (IRB BARCELONA)
Call Details Consolidator Grant (CoG), LS2, ERC-2015-CoG
Summary Finding the mutations, genes and pathways directly involved in cancer is of paramount importance to understand the mechanisms of tumour development and devise therapeutic strategies to overcome the disease. Due to their role in cancer development and maintenance, the proteins encoded by cancer genes are candidate therapeutic targets. Indeed, in recent years we have witnessed the development of successful cancer-targeting therapies to counteract the effect of driver mutations. Although the coding part of the human genome has now largely been explored in the search for cancer driver mutations in most frequent cancer types, the extent of involvement of noncoding mutations in cancer development remains a mystery. The main challenges faced are: 1) the functional role of most noncoding regions is unknown, and 2) tumours often have thousands of somatic mutations, so that distinguishing cancer driver mutations from bystanders is like finding the proverbial needle in a haystack. To overcome these two challenges I propose to analyse the pattern of somatic mutations across thousands of tumours in noncoding regions to identify signals of positive selection. These signals are an indication that mutations in the region have been positively selected during tumour evolution and are thus directly involved in the tumour phenotype. The large scale analysis proposed here will allow us to create a catalogue of noncoding elements involved in different types of cancer upon mutations. We will study in detail a selected set of driver elements to uncover their specific function and role in the tumourigenic process. Furthermore, we will explore possibilities of counteracting their driver effect with targeted drugs. The results of this project may boost our understanding of the biological role of noncoding regions, help to unravel novel molecular causes of cancer and provide novel targeted therapeutic opportunities for cancer patients.
Summary
Finding the mutations, genes and pathways directly involved in cancer is of paramount importance to understand the mechanisms of tumour development and devise therapeutic strategies to overcome the disease. Due to their role in cancer development and maintenance, the proteins encoded by cancer genes are candidate therapeutic targets. Indeed, in recent years we have witnessed the development of successful cancer-targeting therapies to counteract the effect of driver mutations. Although the coding part of the human genome has now largely been explored in the search for cancer driver mutations in most frequent cancer types, the extent of involvement of noncoding mutations in cancer development remains a mystery. The main challenges faced are: 1) the functional role of most noncoding regions is unknown, and 2) tumours often have thousands of somatic mutations, so that distinguishing cancer driver mutations from bystanders is like finding the proverbial needle in a haystack. To overcome these two challenges I propose to analyse the pattern of somatic mutations across thousands of tumours in noncoding regions to identify signals of positive selection. These signals are an indication that mutations in the region have been positively selected during tumour evolution and are thus directly involved in the tumour phenotype. The large scale analysis proposed here will allow us to create a catalogue of noncoding elements involved in different types of cancer upon mutations. We will study in detail a selected set of driver elements to uncover their specific function and role in the tumourigenic process. Furthermore, we will explore possibilities of counteracting their driver effect with targeted drugs. The results of this project may boost our understanding of the biological role of noncoding regions, help to unravel novel molecular causes of cancer and provide novel targeted therapeutic opportunities for cancer patients.
Max ERC Funding
1 995 829 €
Duration
Start date: 2016-12-01, End date: 2021-11-30
