Project acronym AMDROMA
Project Algorithmic and Mechanism Design Research in Online MArkets
Researcher (PI) Stefano LEONARDI
Host Institution (HI) UNIVERSITA DEGLI STUDI DI ROMA LA SAPIENZA
Country Italy
Call Details Advanced Grant (AdG), PE6, ERC-2017-ADG
Summary Online markets currently form an important share of the global economy. The Internet hosts classical markets (real-estate, stocks, e-commerce) as well allowing new markets with previously unknown features (web-based advertisement, viral marketing, digital goods, crowdsourcing, sharing economy). Algorithms play a central role in many decision processes involved in online markets. For example, algorithms run electronic auctions, trade stocks, adjusts prices dynamically, and harvest big data to provide economic information. Thus, it is of paramount importance to understand the algorithmic and mechanism design foundations of online markets.
The algorithmic research issues that we consider involve algorithmic mechanism design, online and approximation algorithms, modelling uncertainty in online market design, and large-scale data analysisonline and approximation algorithms, large-scale optimization and data mining. The aim of this research project is to combine these fields to consider research questions that are central for today's Internet economy. We plan to apply these techniques so as to solve fundamental algorithmic problems motivated by web-basedInternet advertisement, Internet market designsharing economy, and crowdsourcingonline labour marketplaces. While my planned research is focussedcentered on foundational work with rigorous design and analysis of in algorithms and mechanismsic design and analysis, it will also include as an important component empirical validation on large-scale real-life datasets.
Summary
Online markets currently form an important share of the global economy. The Internet hosts classical markets (real-estate, stocks, e-commerce) as well allowing new markets with previously unknown features (web-based advertisement, viral marketing, digital goods, crowdsourcing, sharing economy). Algorithms play a central role in many decision processes involved in online markets. For example, algorithms run electronic auctions, trade stocks, adjusts prices dynamically, and harvest big data to provide economic information. Thus, it is of paramount importance to understand the algorithmic and mechanism design foundations of online markets.
The algorithmic research issues that we consider involve algorithmic mechanism design, online and approximation algorithms, modelling uncertainty in online market design, and large-scale data analysisonline and approximation algorithms, large-scale optimization and data mining. The aim of this research project is to combine these fields to consider research questions that are central for today's Internet economy. We plan to apply these techniques so as to solve fundamental algorithmic problems motivated by web-basedInternet advertisement, Internet market designsharing economy, and crowdsourcingonline labour marketplaces. While my planned research is focussedcentered on foundational work with rigorous design and analysis of in algorithms and mechanismsic design and analysis, it will also include as an important component empirical validation on large-scale real-life datasets.
Max ERC Funding
1 780 150 €
Duration
Start date: 2018-07-01, End date: 2023-06-30
Project acronym BACKUP
Project Unveiling the relationship between brain connectivity and function by integrated photonics
Researcher (PI) Lorenzo PAVESI
Host Institution (HI) UNIVERSITA DEGLI STUDI DI TRENTO
Country Italy
Call Details Advanced Grant (AdG), PE7, ERC-2017-ADG
Summary I will address the fundamental question of which is the role of neuron activity and plasticity in information elaboration and storage in the brain. I, together with an interdisciplinary team, will develop a hybrid neuro-morphic computing platform. Integrated photonic circuits will be interfaced to both electronic circuits and neuronal circuits (in vitro experiments) to emulate brain functions and develop schemes able to supplement (backup) neuronal functions. The photonic network is based on massive reconfigurable matrices of nonlinear nodes formed by microring resonators, which enter in regime of self-pulsing and chaos by positive optical feedback. These networks resemble human brain. I will push this analogy further by interfacing the photonic network with neurons making hybrid network. By using optogenetics, I will control the synaptic strengthen-ing and the neuron activity. Deep learning algorithms will model the biological network functionality, initial-ly within a separate artificial network and, then, in an integrated hybrid artificial-biological network.
My project aims at:
1. Developing a photonic integrated reservoir-computing network (RCN);
2. Developing dynamic memories in photonic integrated circuits using RCN;
3. Developing hybrid interfaces between a neuronal network and a photonic integrated circuit;
4. Developing a hybrid electronic, photonic and biological network that computes jointly;
5. Addressing neuronal network activity by photonic RCN to simulate in vitro memory storage and retrieval;
6. Elaborating the signal from RCN and neuronal circuits in order to cope with plastic changes in pathologi-cal brain conditions such as amnesia and epilepsy.
The long-term vision is that hybrid neuromorphic photonic networks will (a) clarify the way brain thinks, (b) compute beyond von Neumann, and (c) control and supplement specific neuronal functions.
Summary
I will address the fundamental question of which is the role of neuron activity and plasticity in information elaboration and storage in the brain. I, together with an interdisciplinary team, will develop a hybrid neuro-morphic computing platform. Integrated photonic circuits will be interfaced to both electronic circuits and neuronal circuits (in vitro experiments) to emulate brain functions and develop schemes able to supplement (backup) neuronal functions. The photonic network is based on massive reconfigurable matrices of nonlinear nodes formed by microring resonators, which enter in regime of self-pulsing and chaos by positive optical feedback. These networks resemble human brain. I will push this analogy further by interfacing the photonic network with neurons making hybrid network. By using optogenetics, I will control the synaptic strengthen-ing and the neuron activity. Deep learning algorithms will model the biological network functionality, initial-ly within a separate artificial network and, then, in an integrated hybrid artificial-biological network.
My project aims at:
1. Developing a photonic integrated reservoir-computing network (RCN);
2. Developing dynamic memories in photonic integrated circuits using RCN;
3. Developing hybrid interfaces between a neuronal network and a photonic integrated circuit;
4. Developing a hybrid electronic, photonic and biological network that computes jointly;
5. Addressing neuronal network activity by photonic RCN to simulate in vitro memory storage and retrieval;
6. Elaborating the signal from RCN and neuronal circuits in order to cope with plastic changes in pathologi-cal brain conditions such as amnesia and epilepsy.
The long-term vision is that hybrid neuromorphic photonic networks will (a) clarify the way brain thinks, (b) compute beyond von Neumann, and (c) control and supplement specific neuronal functions.
Max ERC Funding
2 499 825 €
Duration
Start date: 2018-11-01, End date: 2023-10-31
Project acronym CARDIOEPIGEN
Project Epigenetics and microRNAs in Myocardial Function and Disease
Researcher (PI) Gianluigi Condorelli
Host Institution (HI) HUMANITAS MIRASOLE SPA
Country Italy
Call Details Advanced Grant (AdG), LS4, ERC-2011-ADG_20110310
Summary Heart failure (HF) is the ultimate outcome of many cardiovascular diseases. Re-expression of fetal genes in the adult heart contributes to development of HF. Two mechanisms involved in the control of gene expression are epigenetics and microRNAs (miRs). We propose a project on epigenetic and miR-mediated mechanisms leading to HF.
Epigenetics refers to heritable modification of DNA and histones that does not modify the genetic code. Depending on the type of modification and on the site affected, these chemical changes up- or down-regulate transcription of specific genes. Despite it being a major player in gene regulation, epigenetics has been only partly investigated in HF. miRs are regulatory RNAs that target mRNAs for inhibition. Dysregulation of the cardiac miR signature occurs in HF. miR expression may itself be under epigenetic control, constituting a miR-epigenetic regulatory network. To our knowledge, this possibility has not been studied yet.
Our specific hypothesis is that the profile of DNA/histone methylation and the cross-talk between epigenetic enzymes and miRs have fundamental roles in defining the characteristics of cells during cardiac development and that the dysregulation of these processes determines the deleterious nature of the stressed heart’s gene programme. We will test this first through a genome-wide study of DNA/histone methylation to generate maps of the main methylation modifications occurring in the genome of cardiac cells treated with a pro-hypertrophy regulator and of a HF model. We will then investigate the role of epigenetic enzymes deemed important in HF, through the generation and study of knockout mice models. Finally, we will test the possible therapeutic potential of modulating epigenetic genes.
We hope to further understand the pathological mechanisms leading to HF and to generate data instrumental to the development of diagnostic and therapeutic strategies for this disease.
Summary
Heart failure (HF) is the ultimate outcome of many cardiovascular diseases. Re-expression of fetal genes in the adult heart contributes to development of HF. Two mechanisms involved in the control of gene expression are epigenetics and microRNAs (miRs). We propose a project on epigenetic and miR-mediated mechanisms leading to HF.
Epigenetics refers to heritable modification of DNA and histones that does not modify the genetic code. Depending on the type of modification and on the site affected, these chemical changes up- or down-regulate transcription of specific genes. Despite it being a major player in gene regulation, epigenetics has been only partly investigated in HF. miRs are regulatory RNAs that target mRNAs for inhibition. Dysregulation of the cardiac miR signature occurs in HF. miR expression may itself be under epigenetic control, constituting a miR-epigenetic regulatory network. To our knowledge, this possibility has not been studied yet.
Our specific hypothesis is that the profile of DNA/histone methylation and the cross-talk between epigenetic enzymes and miRs have fundamental roles in defining the characteristics of cells during cardiac development and that the dysregulation of these processes determines the deleterious nature of the stressed heart’s gene programme. We will test this first through a genome-wide study of DNA/histone methylation to generate maps of the main methylation modifications occurring in the genome of cardiac cells treated with a pro-hypertrophy regulator and of a HF model. We will then investigate the role of epigenetic enzymes deemed important in HF, through the generation and study of knockout mice models. Finally, we will test the possible therapeutic potential of modulating epigenetic genes.
We hope to further understand the pathological mechanisms leading to HF and to generate data instrumental to the development of diagnostic and therapeutic strategies for this disease.
Max ERC Funding
2 500 000 €
Duration
Start date: 2012-10-01, End date: 2018-09-30
Project acronym CLEAR
Project Modulating cellular clearance to cure human disease
Researcher (PI) Andrea Ballabio
Host Institution (HI) FONDAZIONE TELETHON
Country Italy
Call Details Advanced Grant (AdG), LS2, ERC-2009-AdG
Summary Cellular clearance is a fundamental process required by all cells in all species. Important physiological processes, such as aging, and pathological mechanisms, such as neurodegeneration, are strictly dependent on cellular clearance. In eukaryotes, most of the cellular clearing processes occur in a specialized organelle, the lysosome. This project is based on a recent discovery, made in our laboratory, of a gene network, which we have named CLEAR, that controls lysosomal biogenesis and function and regulates cellular clearance. The specific goals of the project are: 1) the comprehensive characterization of the mechanisms underlying the CLEAR network, 2) the thorough understanding of CLEAR physiological function at the cellular and organism levels, 3) the development of strategies and tools to modulate cellular clearance, and 4) the implementation of proof-of-principle therapeutic studies based on the activation of the CLEAR network in murine models of human lysosomal storage disorders and of neurodegenerative diseases, such as Alzheimers s and Huntington s diseases. A combination of genomics, bioinformatics, systems biology, chemical genomics, cell biology, and mouse genetics approaches will be used to achieve these goals. Our goal is to develop tools to modulate cellular clearance and to use such tools to develop therapies to cure human disease. The potential medical relevance of this project is very high, particularly in the field of neurodegenerative disease. Therapies that prevent, ameliorate or delay neurodegeneration in these diseases would have a huge impact on human health.
Summary
Cellular clearance is a fundamental process required by all cells in all species. Important physiological processes, such as aging, and pathological mechanisms, such as neurodegeneration, are strictly dependent on cellular clearance. In eukaryotes, most of the cellular clearing processes occur in a specialized organelle, the lysosome. This project is based on a recent discovery, made in our laboratory, of a gene network, which we have named CLEAR, that controls lysosomal biogenesis and function and regulates cellular clearance. The specific goals of the project are: 1) the comprehensive characterization of the mechanisms underlying the CLEAR network, 2) the thorough understanding of CLEAR physiological function at the cellular and organism levels, 3) the development of strategies and tools to modulate cellular clearance, and 4) the implementation of proof-of-principle therapeutic studies based on the activation of the CLEAR network in murine models of human lysosomal storage disorders and of neurodegenerative diseases, such as Alzheimers s and Huntington s diseases. A combination of genomics, bioinformatics, systems biology, chemical genomics, cell biology, and mouse genetics approaches will be used to achieve these goals. Our goal is to develop tools to modulate cellular clearance and to use such tools to develop therapies to cure human disease. The potential medical relevance of this project is very high, particularly in the field of neurodegenerative disease. Therapies that prevent, ameliorate or delay neurodegeneration in these diseases would have a huge impact on human health.
Max ERC Funding
2 100 000 €
Duration
Start date: 2010-03-01, End date: 2015-02-28
Project acronym COGSYSTEMS
Project Understanding actions and intentions of others
Researcher (PI) Giacomo Rizzolatti
Host Institution (HI) UNIVERSITA DEGLI STUDI DI PARMA
Country Italy
Call Details Advanced Grant (AdG), LS5, ERC-2009-AdG
Summary How do we understand the actions and intentions of others? Hereby we intend to address this issue by using a multidisciplinary approach. Our project is subdivided into four parts. In the first part we investigate the neural organization of monkey area F5, an area deeply involved in motor act understanding. By using a new set of electrodes we will describe the columnar organization of the area F5, establish the temporal relationships between the activity of F5 mirror and motor neurons, and correlate the activity of mirror neurons coding the observed motor acts in peripersonal and extrapersonal space with the activity of motor neurons in the same cortical column. In the second part we will assess the neural mechanism underlying the understanding of the intention of complex actions , i.e. actions formed by a sequence of two (or more) individual actions. The focus will be on the neurons located in ventrolateral prefrontal cortex, an area involved in the organization of high-order motor behavior. The rational of the experiment is that, while the organization of single actions and the understanding of intention behind them is function of parietal neurons, that of complex actions relies on the activity of the prefrontal lobe. In the third and fourth parts of the project we will delimit the cortical areas involved in understanding the goal (the what) and the intention (the why) of the observed actions in individuals with typical development (TD) and in children with autism and will establish the time relation between these two processes. Our hypothesis is that the chained organization of intentional motor acts is impaired in children with autism and this impairment prevents them from organizing normally their actions and from understanding others intentions.
Summary
How do we understand the actions and intentions of others? Hereby we intend to address this issue by using a multidisciplinary approach. Our project is subdivided into four parts. In the first part we investigate the neural organization of monkey area F5, an area deeply involved in motor act understanding. By using a new set of electrodes we will describe the columnar organization of the area F5, establish the temporal relationships between the activity of F5 mirror and motor neurons, and correlate the activity of mirror neurons coding the observed motor acts in peripersonal and extrapersonal space with the activity of motor neurons in the same cortical column. In the second part we will assess the neural mechanism underlying the understanding of the intention of complex actions , i.e. actions formed by a sequence of two (or more) individual actions. The focus will be on the neurons located in ventrolateral prefrontal cortex, an area involved in the organization of high-order motor behavior. The rational of the experiment is that, while the organization of single actions and the understanding of intention behind them is function of parietal neurons, that of complex actions relies on the activity of the prefrontal lobe. In the third and fourth parts of the project we will delimit the cortical areas involved in understanding the goal (the what) and the intention (the why) of the observed actions in individuals with typical development (TD) and in children with autism and will establish the time relation between these two processes. Our hypothesis is that the chained organization of intentional motor acts is impaired in children with autism and this impairment prevents them from organizing normally their actions and from understanding others intentions.
Max ERC Funding
1 992 000 €
Duration
Start date: 2010-05-01, End date: 2015-04-30
Project acronym CONCEPT
Project Construction of Perception from Touch Signals
Researcher (PI) Mathew Diamond
Host Institution (HI) SCUOLA INTERNAZIONALE SUPERIORE DI STUDI AVANZATI DI TRIESTE
Country Italy
Call Details Advanced Grant (AdG), LS5, ERC-2011-ADG_20110310
Summary Our sensory systems gather stimuli as elemental physical features yet we perceive a world made up of familiar objects, not wavelengths or vibrations. Perception occurs when the neuronal representation of physical parameters is transformed into the neuronal representation of meaningful objects. How does this recoding occur? An ideal platform for the inquiry is the rat whisker sensory system: it produces fast and accurate judgments of complex stimuli, yet can be broken down into accessible neuronal mechanisms. CONCEPT will examine the process that begins with whisker motion and ends with perception of the contacted object. Understanding the general principles for the construction of perception will help explain why we experience the world as we do.
The main hypothesis is that graded neuronal representations at early processing stages are “fractured” to generate discrete object representations at late processing stages. Of particular interest is the emergence of object representations as the meaning of new stimuli is acquired.
We will collect multi-site single-unit and local field potential signals simultaneously with precise behavioral indices, and will interpret data through advanced computational methods. We will begin by quantifying whisker motion as rats discriminate texture, thus defining the raw material on which the brain operates. Next, we will characterize the transformation of texture along an intracortical stream from sensory areas (where we expect that neurons encode whisker kinematics) to frontal and rhinal areas (where we expect that neurons encode objects extracted from the graded physical continuum) and hippocampus (where we expect that neurons encode objects in conjunction with context). We will test candidate processing schemes by manipulating perception on single trials using optogenetic methods.
Summary
Our sensory systems gather stimuli as elemental physical features yet we perceive a world made up of familiar objects, not wavelengths or vibrations. Perception occurs when the neuronal representation of physical parameters is transformed into the neuronal representation of meaningful objects. How does this recoding occur? An ideal platform for the inquiry is the rat whisker sensory system: it produces fast and accurate judgments of complex stimuli, yet can be broken down into accessible neuronal mechanisms. CONCEPT will examine the process that begins with whisker motion and ends with perception of the contacted object. Understanding the general principles for the construction of perception will help explain why we experience the world as we do.
The main hypothesis is that graded neuronal representations at early processing stages are “fractured” to generate discrete object representations at late processing stages. Of particular interest is the emergence of object representations as the meaning of new stimuli is acquired.
We will collect multi-site single-unit and local field potential signals simultaneously with precise behavioral indices, and will interpret data through advanced computational methods. We will begin by quantifying whisker motion as rats discriminate texture, thus defining the raw material on which the brain operates. Next, we will characterize the transformation of texture along an intracortical stream from sensory areas (where we expect that neurons encode whisker kinematics) to frontal and rhinal areas (where we expect that neurons encode objects extracted from the graded physical continuum) and hippocampus (where we expect that neurons encode objects in conjunction with context). We will test candidate processing schemes by manipulating perception on single trials using optogenetic methods.
Max ERC Funding
2 500 000 €
Duration
Start date: 2012-06-01, End date: 2018-05-31
Project acronym DDRNA
Project A novel direct role of non coding RNA in DNA damage response activation
Researcher (PI) Fabrizio D'adda Di Fagagna
Host Institution (HI) IFOM FONDAZIONE ISTITUTO FIRC DI ONCOLOGIA MOLECOLARE
Country Italy
Call Details Advanced Grant (AdG), LS1, ERC-2012-ADG_20120314
Summary DNA, if damaged, cannot be replaced. If not replaceable, it must be repaired. The so-called “DNA damage response” (DDR) is a coordinate set of evolutionary conserved events that arrest the cell-cycle (DNA damage checkpoint function) in proliferating cells and attempts DNA repair. Until DNA damage has not been repaired in full, cell proliferation is not resumed in normal cells.
DNA damage is a physiological event. Ageing and cancer are both associated with DNA damage accumulation. In the past, we contribute to better understand the mechanisms and the consequences of DNA damage generation and DDR activation in both settings.
We have recently identified a completely hitherto undiscovered level of control of DDR activation, so far considered a proteinaceous only signaling cascade. We have discovered that short RNA species are detectable at DNA damage sites and are necessary for DDR activation at DNA lesions. These RNA species are generated by an evolutionary-conserved RNA processing machinery. However, they serve purposes never reported before.
We believe that our findings change radically our understanding of DDR modulation in mammals and disclose a fertile unspoilt ground for exciting investigations.
Summary
DNA, if damaged, cannot be replaced. If not replaceable, it must be repaired. The so-called “DNA damage response” (DDR) is a coordinate set of evolutionary conserved events that arrest the cell-cycle (DNA damage checkpoint function) in proliferating cells and attempts DNA repair. Until DNA damage has not been repaired in full, cell proliferation is not resumed in normal cells.
DNA damage is a physiological event. Ageing and cancer are both associated with DNA damage accumulation. In the past, we contribute to better understand the mechanisms and the consequences of DNA damage generation and DDR activation in both settings.
We have recently identified a completely hitherto undiscovered level of control of DDR activation, so far considered a proteinaceous only signaling cascade. We have discovered that short RNA species are detectable at DNA damage sites and are necessary for DDR activation at DNA lesions. These RNA species are generated by an evolutionary-conserved RNA processing machinery. However, they serve purposes never reported before.
We believe that our findings change radically our understanding of DDR modulation in mammals and disclose a fertile unspoilt ground for exciting investigations.
Max ERC Funding
2 329 200 €
Duration
Start date: 2013-06-01, End date: 2018-05-31
Project acronym DEPTH
Project DEsigning new Paths in The differentiation Hyperspace
Researcher (PI) Giovanni Cesareni
Host Institution (HI) UNIVERSITA DEGLI STUDI DI ROMA TOR VERGATA
Country Italy
Call Details Advanced Grant (AdG), LS2, ERC-2012-ADG_20120314
Summary The adult human organism contains heterogeneous reservoirs of pluripotent stem cells characterized by a diversified differentiation potential. Understanding their biology at a system level would advance our ability to selectively activate and control their differentiation potential. Aside from the basic implications this would represent a substantial progress in regenerative medicine by providing a rational framework for using small molecules to control cell trans-determination and reprogramming.
Here we propose a combined experimental and modelling approach to assemble a predictive model of mesoderm stem cell differentiation. Different cell states are identified by a vector in the differentiation hyperspace, the coordinates of the vector being the activation levels of a large number of nodes of a logic model linking the cell signalling network to the transcription regulatory network.
The premise of this proposal is that differentiation is equivalent to rewiring the cell regulatory network as a consequence of induced perturbation of the gene expression program. This process can be rationally controlled by perturbing specific nodes of the signalling network that in turn control transcription factor activation. We will develop this novel strategy using the mesoangioblast ex vivo differentiation system. Mesoangioblasts are one of the many different types of mesoderm stem/progenitor cells that exhibit myogenic potential. Ex vivo, they readily differentiate into striated muscle. However, under appropriate conditions they can also differentiate, into smooth muscle and adipocytes, albeit less efficiently. We will start by assembling, training and optimizing different predictive models for the undifferentiated mesoangioblast. Next by a combination of experiments and modelling approaches we will learn how, by perturbing the signalling models with different inhibitors and activators we can rewire the cell networks to induce trans-determination or reprogramming.
Summary
The adult human organism contains heterogeneous reservoirs of pluripotent stem cells characterized by a diversified differentiation potential. Understanding their biology at a system level would advance our ability to selectively activate and control their differentiation potential. Aside from the basic implications this would represent a substantial progress in regenerative medicine by providing a rational framework for using small molecules to control cell trans-determination and reprogramming.
Here we propose a combined experimental and modelling approach to assemble a predictive model of mesoderm stem cell differentiation. Different cell states are identified by a vector in the differentiation hyperspace, the coordinates of the vector being the activation levels of a large number of nodes of a logic model linking the cell signalling network to the transcription regulatory network.
The premise of this proposal is that differentiation is equivalent to rewiring the cell regulatory network as a consequence of induced perturbation of the gene expression program. This process can be rationally controlled by perturbing specific nodes of the signalling network that in turn control transcription factor activation. We will develop this novel strategy using the mesoangioblast ex vivo differentiation system. Mesoangioblasts are one of the many different types of mesoderm stem/progenitor cells that exhibit myogenic potential. Ex vivo, they readily differentiate into striated muscle. However, under appropriate conditions they can also differentiate, into smooth muscle and adipocytes, albeit less efficiently. We will start by assembling, training and optimizing different predictive models for the undifferentiated mesoangioblast. Next by a combination of experiments and modelling approaches we will learn how, by perturbing the signalling models with different inhibitors and activators we can rewire the cell networks to induce trans-determination or reprogramming.
Max ERC Funding
2 639 804 €
Duration
Start date: 2013-04-01, End date: 2018-09-30
Project acronym FUEL-PATH
Project Exploiting the saccharification potential of pathogenic microorganisms to improve biofuel production from plants
Researcher (PI) Felice Cervone
Host Institution (HI) UNIVERSITA DEGLI STUDI DI ROMA LA SAPIENZA
Country Italy
Call Details Advanced Grant (AdG), LS9, ERC-2008-AdG
Summary "FUEL-PATH aims at providing new knowledge on plant cell wall and innovative biotechnological solutions for biomass utilization. A key process for biomass utilization is the initial degradation of cell walls into fermentable sugars (saccharification); this is hindered by the wall recalcitrance to hydrolysis. We propose to improve the plant saccharification characteristics by mimicking a strategy successfully used by phytopathogenic microorganisms. These produce pectic enzymes before other cell wall-degrading enzymes (CWDEs) to weaken the linkages between the wall components and favour the maceration of the plant tissue. Homogalacturonan (HGA), a major component of pectin, is synthesized in a methylated form and is de-esterified in the wall by methylesterases (PMEs). De-esterified HGA interacts with calcium to form ""egg-box"" structures, which are critical for maintaining the integrity of the entire wall. We propose to improve saccharification by expression in plants of microbial polygalacturonases (PGs) hydrolizing HGA. Plants expressing a fungal PG have reduced levels of HGA and enhanced saccharification (unpublished preliminary data). Since PG activity in pianta affects normal growth, a technology of enzyme control through the use of specific protein inhibitors will be developed. A second strategy to be adopted for weakening the ""egg-box"" is the overexpression of PME inhibitors. This may cause not only an increased degradability but also an enhanced biomass production. FUEL-PATH will provide detailed information on the structure, function and construction of tailor-made enzymes and inhibitors suitable for the saccharification process. FUEL-PATH will also address the relationship between pectin composition and developmental responses mediated by hormones in PG-expressing plants. A genetic screen will be performed to isolate genes involved growth defects and increased cell wall degradability and these will be characterized for a possible biotechnological use."
Summary
"FUEL-PATH aims at providing new knowledge on plant cell wall and innovative biotechnological solutions for biomass utilization. A key process for biomass utilization is the initial degradation of cell walls into fermentable sugars (saccharification); this is hindered by the wall recalcitrance to hydrolysis. We propose to improve the plant saccharification characteristics by mimicking a strategy successfully used by phytopathogenic microorganisms. These produce pectic enzymes before other cell wall-degrading enzymes (CWDEs) to weaken the linkages between the wall components and favour the maceration of the plant tissue. Homogalacturonan (HGA), a major component of pectin, is synthesized in a methylated form and is de-esterified in the wall by methylesterases (PMEs). De-esterified HGA interacts with calcium to form ""egg-box"" structures, which are critical for maintaining the integrity of the entire wall. We propose to improve saccharification by expression in plants of microbial polygalacturonases (PGs) hydrolizing HGA. Plants expressing a fungal PG have reduced levels of HGA and enhanced saccharification (unpublished preliminary data). Since PG activity in pianta affects normal growth, a technology of enzyme control through the use of specific protein inhibitors will be developed. A second strategy to be adopted for weakening the ""egg-box"" is the overexpression of PME inhibitors. This may cause not only an increased degradability but also an enhanced biomass production. FUEL-PATH will provide detailed information on the structure, function and construction of tailor-made enzymes and inhibitors suitable for the saccharification process. FUEL-PATH will also address the relationship between pectin composition and developmental responses mediated by hormones in PG-expressing plants. A genetic screen will be performed to isolate genes involved growth defects and increased cell wall degradability and these will be characterized for a possible biotechnological use."
Max ERC Funding
2 099 600 €
Duration
Start date: 2009-01-01, End date: 2014-06-30
Project acronym GeCo
Project Data-Driven Genomic Computing
Researcher (PI) stefano CERI
Host Institution (HI) POLITECNICO DI MILANO
Country Italy
Call Details Advanced Grant (AdG), PE6, ERC-2015-AdG
Summary Next-generation sequencing technology has dramatically reduced the cost and time of reading the DNA. Huge investments are targeted to sequencing the DNA of large populations, and repositories of well-curated sequence data are being collected. Answers to fundamental biomedical problems are hidden in these data, e.g. how cancer arises, how driving mutations occur, how much cancer is dependent on environment. But genomic computing has not comparatively evolved. Bioinformatics has been driven by specific needs and distracted from a foundational approach; hundreds of methods solve individual problems, but miss the broad perspective.
The objective of GeCo is to rethink genomic computing through the lens of basic data management. We will first design the data model, using few general abstractions that guarantee interoperability between existing data formats. Next, we will design a new-generation query language inspired by classic relational algebra and extended with orthogonal, domain-specific abstractions for genomics. Query processing will trace metadata and computation steps, opening doors to the seamless integration of descriptive statistics and high-level data analysis (e.g., DNA region clustering and extraction of regulatory networks).
Genomic computing is a “big data” problem, therefore we will also achieve computational efficiency by using parallel computing on both clusters and public clouds; the choice of a suitable data model and of computational abstractions will boost performance in a principled way. The resulting technology will be applicable to individual and federated repositories, and will be exploited for providing integrated access to curated data, made available by large consortia, through user-friendly search services. Our most far-fetching vision is to move towards an Internet of Genomes exploiting data indexing and crawling. The PI’s background in distributed data, data modelling, query processing and search will drive a radical paradigm shift.
Summary
Next-generation sequencing technology has dramatically reduced the cost and time of reading the DNA. Huge investments are targeted to sequencing the DNA of large populations, and repositories of well-curated sequence data are being collected. Answers to fundamental biomedical problems are hidden in these data, e.g. how cancer arises, how driving mutations occur, how much cancer is dependent on environment. But genomic computing has not comparatively evolved. Bioinformatics has been driven by specific needs and distracted from a foundational approach; hundreds of methods solve individual problems, but miss the broad perspective.
The objective of GeCo is to rethink genomic computing through the lens of basic data management. We will first design the data model, using few general abstractions that guarantee interoperability between existing data formats. Next, we will design a new-generation query language inspired by classic relational algebra and extended with orthogonal, domain-specific abstractions for genomics. Query processing will trace metadata and computation steps, opening doors to the seamless integration of descriptive statistics and high-level data analysis (e.g., DNA region clustering and extraction of regulatory networks).
Genomic computing is a “big data” problem, therefore we will also achieve computational efficiency by using parallel computing on both clusters and public clouds; the choice of a suitable data model and of computational abstractions will boost performance in a principled way. The resulting technology will be applicable to individual and federated repositories, and will be exploited for providing integrated access to curated data, made available by large consortia, through user-friendly search services. Our most far-fetching vision is to move towards an Internet of Genomes exploiting data indexing and crawling. The PI’s background in distributed data, data modelling, query processing and search will drive a radical paradigm shift.
Max ERC Funding
2 500 000 €
Duration
Start date: 2016-09-01, End date: 2021-08-31