Project acronym ADHESWITCHES
Project Adhesion switches in cancer and development: from in vivo to synthetic biology
Researcher (PI) Mari Johanna Ivaska
Host Institution (HI) TURUN YLIOPISTO
Call Details Consolidator Grant (CoG), LS3, ERC-2013-CoG
Summary Integrins are transmembrane cell adhesion receptors controlling cell proliferation and migration. Our objective is to gain fundamentally novel mechanistic insight into the emerging new roles of integrins in cancer and to generate a road map of integrin dependent pathways critical in mammary gland development and integrin signalling thus opening new targets for therapeutic interventions. We will combine an in vivo based translational approach with cell and molecular biological studies aiming to identify entirely novel concepts in integrin function using cutting edge techniques and synthetic-biology tools.
The specific objectives are:
1) Integrin inactivation in branching morphogenesis and cancer invasion. Integrins regulate mammary gland development and cancer invasion but the role of integrin inactivating proteins in these processes is currently completely unknown. We will investigate this using genetically modified mice, ex-vivo organoid models and human tissues with the aim to identify beneficial combinational treatments against cancer invasion.
2) Endosomal adhesomes – cross-talk between integrin activity and integrin “inside-in signaling”. We hypothesize that endocytosed active integrins engage in specialized endosomal signaling that governs cell survival especially in cancer. RNAi cell arrays, super-resolution STED imaging and endosomal proteomics will be used to investigate integrin signaling in endosomes.
3) Spatio-temporal co-ordination of adhesion and endocytosis. Several cytosolic proteins compete for integrin binding to regulate activation, endocytosis and recycling. Photoactivatable protein-traps and predefined matrix micropatterns will be employed to mechanistically dissect the spatio-temporal dynamics and hierarchy of their recruitment.
We will employ innovative and unconventional techniques to address three major unanswered questions in the field and significantly advance our understanding of integrin function in development and cancer.
Summary
Integrins are transmembrane cell adhesion receptors controlling cell proliferation and migration. Our objective is to gain fundamentally novel mechanistic insight into the emerging new roles of integrins in cancer and to generate a road map of integrin dependent pathways critical in mammary gland development and integrin signalling thus opening new targets for therapeutic interventions. We will combine an in vivo based translational approach with cell and molecular biological studies aiming to identify entirely novel concepts in integrin function using cutting edge techniques and synthetic-biology tools.
The specific objectives are:
1) Integrin inactivation in branching morphogenesis and cancer invasion. Integrins regulate mammary gland development and cancer invasion but the role of integrin inactivating proteins in these processes is currently completely unknown. We will investigate this using genetically modified mice, ex-vivo organoid models and human tissues with the aim to identify beneficial combinational treatments against cancer invasion.
2) Endosomal adhesomes – cross-talk between integrin activity and integrin “inside-in signaling”. We hypothesize that endocytosed active integrins engage in specialized endosomal signaling that governs cell survival especially in cancer. RNAi cell arrays, super-resolution STED imaging and endosomal proteomics will be used to investigate integrin signaling in endosomes.
3) Spatio-temporal co-ordination of adhesion and endocytosis. Several cytosolic proteins compete for integrin binding to regulate activation, endocytosis and recycling. Photoactivatable protein-traps and predefined matrix micropatterns will be employed to mechanistically dissect the spatio-temporal dynamics and hierarchy of their recruitment.
We will employ innovative and unconventional techniques to address three major unanswered questions in the field and significantly advance our understanding of integrin function in development and cancer.
Max ERC Funding
1 887 910 €
Duration
Start date: 2014-05-01, End date: 2019-04-30
Project acronym Age Asymmetry
Project Age-Selective Segregation of Organelles
Researcher (PI) Pekka Aleksi Katajisto
Host Institution (HI) HELSINGIN YLIOPISTO
Call Details Starting Grant (StG), LS3, ERC-2015-STG
Summary Our tissues are constantly renewed by stem cells. Over time, stem cells accumulate cellular damage that will compromise renewal and results in aging. As stem cells can divide asymmetrically, segregation of harmful factors to the differentiating daughter cell could be one possible mechanism for slowing damage accumulation in the stem cell. However, current evidence for such mechanisms comes mainly from analogous findings in yeast, and studies have concentrated only on few types of cellular damage.
I hypothesize that the chronological age of a subcellular component is a proxy for all the damage it has sustained. In order to secure regeneration, mammalian stem cells may therefore specifically sort old cellular material asymmetrically. To study this, I have developed a novel strategy and tools to address the age-selective segregation of any protein in stem cell division. Using this approach, I have already discovered that stem-like cells of the human mammary epithelium indeed apportion chronologically old mitochondria asymmetrically in cell division, and enrich old mitochondria to the differentiating daughter cell. We will investigate the mechanisms underlying this novel phenomenon, and its relevance for mammalian aging.
We will first identify how old and young mitochondria differ, and how stem cells recognize them to facilitate the asymmetric segregation. Next, we will analyze the extent of asymmetric age-selective segregation by targeting several other subcellular compartments in a stem cell division. Finally, we will determine whether the discovered age-selective segregation is a general property of stem cell in vivo, and it's functional relevance for maintenance of stem cells and tissue regeneration. Our discoveries may open new possibilities to target aging associated functional decline by induction of asymmetric age-selective organelle segregation.
Summary
Our tissues are constantly renewed by stem cells. Over time, stem cells accumulate cellular damage that will compromise renewal and results in aging. As stem cells can divide asymmetrically, segregation of harmful factors to the differentiating daughter cell could be one possible mechanism for slowing damage accumulation in the stem cell. However, current evidence for such mechanisms comes mainly from analogous findings in yeast, and studies have concentrated only on few types of cellular damage.
I hypothesize that the chronological age of a subcellular component is a proxy for all the damage it has sustained. In order to secure regeneration, mammalian stem cells may therefore specifically sort old cellular material asymmetrically. To study this, I have developed a novel strategy and tools to address the age-selective segregation of any protein in stem cell division. Using this approach, I have already discovered that stem-like cells of the human mammary epithelium indeed apportion chronologically old mitochondria asymmetrically in cell division, and enrich old mitochondria to the differentiating daughter cell. We will investigate the mechanisms underlying this novel phenomenon, and its relevance for mammalian aging.
We will first identify how old and young mitochondria differ, and how stem cells recognize them to facilitate the asymmetric segregation. Next, we will analyze the extent of asymmetric age-selective segregation by targeting several other subcellular compartments in a stem cell division. Finally, we will determine whether the discovered age-selective segregation is a general property of stem cell in vivo, and it's functional relevance for maintenance of stem cells and tissue regeneration. Our discoveries may open new possibilities to target aging associated functional decline by induction of asymmetric age-selective organelle segregation.
Max ERC Funding
1 500 000 €
Duration
Start date: 2016-05-01, End date: 2021-04-30
Project acronym Agglomerates
Project Infinite Protein Self-Assembly in Health and Disease
Researcher (PI) Emmanuel Doram LEVY
Host Institution (HI) WEIZMANN INSTITUTE OF SCIENCE
Call Details Consolidator Grant (CoG), LS2, ERC-2018-COG
Summary Understanding how proteins respond to mutations is of paramount importance to biology and disease. While protein stability and misfolding have been instrumental in rationalizing the impact of mutations, we recently discovered that an alternative route is also frequent, where mutations at the surface of symmetric proteins trigger novel self-interactions that lead to infinite self-assembly. This mechanism can be involved in disease, as in sickle-cell anemia, but may also serve in adaptation. Importantly, it differs fundamentally from aggregation, because misfolding does not drive it. Thus, we term it “agglomeration”. The ease with which agglomeration can occur, even by single point mutations, shifts the paradigm of how quickly new protein assemblies can emerge, both in health and disease. This prompts us to determine the basic principles of protein agglomeration and explore its implications in cell physiology and human disease.
We propose an interdisciplinary research program bridging atomic and cellular scales to explore agglomeration in three aims: (i) Map the landscape of protein agglomeration in response to mutation in endogenous yeast proteins; (ii) Characterize how yeast physiology impacts agglomeration by changes in gene expression or cell state, and, conversely, how protein agglomerates impact yeast fitness. (iii) Analyze agglomeration in relation to human disease via two approaches. First, by predicting single nucleotide polymorphisms that trigger agglomeration, prioritizing them using knowledge from Aims 1 & 2, and characterizing them experimentally. Second, by providing a proof-of-concept that agglomeration can be exploited in drug design, whereby drugs induce its formation, like mutations can do.
Overall, through this research, we aim to establish agglomeration as a paradigm for protein assembly, with implications for our understanding of evolution, physiology, and disease.
Summary
Understanding how proteins respond to mutations is of paramount importance to biology and disease. While protein stability and misfolding have been instrumental in rationalizing the impact of mutations, we recently discovered that an alternative route is also frequent, where mutations at the surface of symmetric proteins trigger novel self-interactions that lead to infinite self-assembly. This mechanism can be involved in disease, as in sickle-cell anemia, but may also serve in adaptation. Importantly, it differs fundamentally from aggregation, because misfolding does not drive it. Thus, we term it “agglomeration”. The ease with which agglomeration can occur, even by single point mutations, shifts the paradigm of how quickly new protein assemblies can emerge, both in health and disease. This prompts us to determine the basic principles of protein agglomeration and explore its implications in cell physiology and human disease.
We propose an interdisciplinary research program bridging atomic and cellular scales to explore agglomeration in three aims: (i) Map the landscape of protein agglomeration in response to mutation in endogenous yeast proteins; (ii) Characterize how yeast physiology impacts agglomeration by changes in gene expression or cell state, and, conversely, how protein agglomerates impact yeast fitness. (iii) Analyze agglomeration in relation to human disease via two approaches. First, by predicting single nucleotide polymorphisms that trigger agglomeration, prioritizing them using knowledge from Aims 1 & 2, and characterizing them experimentally. Second, by providing a proof-of-concept that agglomeration can be exploited in drug design, whereby drugs induce its formation, like mutations can do.
Overall, through this research, we aim to establish agglomeration as a paradigm for protein assembly, with implications for our understanding of evolution, physiology, and disease.
Max ERC Funding
2 574 819 €
Duration
Start date: 2019-04-01, End date: 2024-03-31
Project acronym ALGOCom
Project Novel Algorithmic Techniques through the Lens of Combinatorics
Researcher (PI) Parinya Chalermsook
Host Institution (HI) AALTO KORKEAKOULUSAATIO SR
Call Details Starting Grant (StG), PE6, ERC-2017-STG
Summary Real-world optimization problems pose major challenges to algorithmic research. For instance, (i) many important problems are believed to be intractable (i.e. NP-hard) and (ii) with the growth of data size, modern applications often require a decision making under {\em incomplete and dynamically changing input data}. After several decades of research, central problems in these domains have remained poorly understood (e.g. Is there an asymptotically most efficient binary search trees?) Existing algorithmic techniques either reach their limitation or are inherently tailored to special cases.
This project attempts to untangle this gap in the state of the art and seeks new interplay across multiple areas of algorithms, such as approximation algorithms, online algorithms, fixed-parameter tractable (FPT) algorithms, exponential time algorithms, and data structures. We propose new directions from the {\em structural perspectives} that connect the aforementioned algorithmic problems to basic questions in combinatorics.
Our approaches fall into one of the three broad schemes: (i) new structural theory, (ii) intermediate problems, and (iii) transfer of techniques. These directions partially build on the PI's successes in resolving more than ten classical problems in this context.
Resolving the proposed problems will likely revolutionize our understanding about algorithms and data structures and potentially unify techniques in multiple algorithmic regimes. Any progress is, in fact, already a significant contribution to the algorithms community. We suggest concrete intermediate goals that are of independent interest and have lower risks, so they are suitable for Ph.D students.
Summary
Real-world optimization problems pose major challenges to algorithmic research. For instance, (i) many important problems are believed to be intractable (i.e. NP-hard) and (ii) with the growth of data size, modern applications often require a decision making under {\em incomplete and dynamically changing input data}. After several decades of research, central problems in these domains have remained poorly understood (e.g. Is there an asymptotically most efficient binary search trees?) Existing algorithmic techniques either reach their limitation or are inherently tailored to special cases.
This project attempts to untangle this gap in the state of the art and seeks new interplay across multiple areas of algorithms, such as approximation algorithms, online algorithms, fixed-parameter tractable (FPT) algorithms, exponential time algorithms, and data structures. We propose new directions from the {\em structural perspectives} that connect the aforementioned algorithmic problems to basic questions in combinatorics.
Our approaches fall into one of the three broad schemes: (i) new structural theory, (ii) intermediate problems, and (iii) transfer of techniques. These directions partially build on the PI's successes in resolving more than ten classical problems in this context.
Resolving the proposed problems will likely revolutionize our understanding about algorithms and data structures and potentially unify techniques in multiple algorithmic regimes. Any progress is, in fact, already a significant contribution to the algorithms community. We suggest concrete intermediate goals that are of independent interest and have lower risks, so they are suitable for Ph.D students.
Max ERC Funding
1 411 258 €
Duration
Start date: 2018-02-01, End date: 2023-01-31
Project acronym AMD
Project Algorithmic Mechanism Design: Beyond Truthful Mechanisms
Researcher (PI) Michal Feldman
Host Institution (HI) TEL AVIV UNIVERSITY
Call Details Starting Grant (StG), PE6, ERC-2013-StG
Summary "The first decade of Algorithmic Mechanism Design (AMD) concentrated, very successfully, on the design of truthful mechanisms for the allocation of resources among agents with private preferences.
Truthful mechanisms are ones that incentivize rational users to report their preferences truthfully.
Truthfulness, however, for all its theoretical appeal, suffers from several inherent limitations, mainly its high communication and computation complexities.
It is not surprising, therefore, that practical applications forego truthfulness and use simpler mechanisms instead.
Simplicity in itself, however, is not sufficient, as any meaningful mechanism should also have some notion of fairness; otherwise agents will stop using it over time.
In this project I plan to develop an innovative AMD theoretical framework that will go beyond truthfulness and focus instead on the natural themes of simplicity and fairness, in addition to computational tractability.
One of my primary goals will be the design of simple and fair poly-time mechanisms that perform at near optimal levels with respect to important economic objectives such as social welfare and revenue.
To this end, I will work toward providing precise definitions of simplicity and fairness and quantifying the effects of these restrictions on the performance levels that can be obtained.
A major challenge in the evaluation of non-truthful mechanisms is defining a reasonable behavior model that will enable their evaluation.
The success of this project could have a broad impact on Europe and beyond, as it would guide the design of natural mechanisms for markets of tens of billions of dollars in revenue, such as online advertising, or sales of wireless frequencies.
The timing of this project is ideal, as the AMD field is now sufficiently mature to lead to a breakthrough and at the same time young enough to be receptive to new approaches and themes."
Summary
"The first decade of Algorithmic Mechanism Design (AMD) concentrated, very successfully, on the design of truthful mechanisms for the allocation of resources among agents with private preferences.
Truthful mechanisms are ones that incentivize rational users to report their preferences truthfully.
Truthfulness, however, for all its theoretical appeal, suffers from several inherent limitations, mainly its high communication and computation complexities.
It is not surprising, therefore, that practical applications forego truthfulness and use simpler mechanisms instead.
Simplicity in itself, however, is not sufficient, as any meaningful mechanism should also have some notion of fairness; otherwise agents will stop using it over time.
In this project I plan to develop an innovative AMD theoretical framework that will go beyond truthfulness and focus instead on the natural themes of simplicity and fairness, in addition to computational tractability.
One of my primary goals will be the design of simple and fair poly-time mechanisms that perform at near optimal levels with respect to important economic objectives such as social welfare and revenue.
To this end, I will work toward providing precise definitions of simplicity and fairness and quantifying the effects of these restrictions on the performance levels that can be obtained.
A major challenge in the evaluation of non-truthful mechanisms is defining a reasonable behavior model that will enable their evaluation.
The success of this project could have a broad impact on Europe and beyond, as it would guide the design of natural mechanisms for markets of tens of billions of dollars in revenue, such as online advertising, or sales of wireless frequencies.
The timing of this project is ideal, as the AMD field is now sufficiently mature to lead to a breakthrough and at the same time young enough to be receptive to new approaches and themes."
Max ERC Funding
1 394 600 €
Duration
Start date: 2013-11-01, End date: 2018-10-31
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
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 ANOREP
Project Targeting the reproductive biology of the malaria mosquito Anopheles gambiae: from laboratory studies to field applications
Researcher (PI) Flaminia Catteruccia
Host Institution (HI) UNIVERSITA DEGLI STUDI DI PERUGIA
Call Details Starting Grant (StG), LS2, ERC-2010-StG_20091118
Summary Anopheles gambiae mosquitoes are the major vectors of malaria, a disease with devastating consequences for
human health. Novel methods for controlling the natural vector populations are urgently needed, given the
evolution of insecticide resistance in mosquitoes and the lack of novel insecticidals. Understanding the
processes at the bases of mosquito biology may help to roll back malaria. In this proposal, we will target
mosquito reproduction, a major determinant of the An. gambiae vectorial capacity. This will be achieved at
two levels: (i) fundamental research, to provide a deeper knowledge of the processes regulating reproduction
in this species, and (ii) applied research, to identify novel targets and to develop innovative approaches for
the control of natural populations. We will focus our analysis on three major players of mosquito
reproduction: male accessory glands (MAGs), sperm, and spermatheca, in both laboratory and field settings.
We will then translate this information into the identification of inhibitors of mosquito fertility. The
experimental activities will be divided across three objectives. In Objective 1, we will unravel the role of the
MAGs in shaping mosquito fertility and behaviour, by performing a combination of transcriptional and
functional studies that will reveal the multifaceted activities of these tissues. In Objective 2 we will instead
focus on the identification of the male and female factors responsible for sperm viability and function.
Results obtained in both objectives will be validated in field mosquitoes. In Objective 3, we will perform
screens aimed at the identification of inhibitors of mosquito reproductive success. This study will reveal as
yet unknown molecular mechanisms underlying reproductive success in mosquitoes, considerably increasing
our knowledge beyond the state-of-the-art and critically contributing with innovative tools and ideas to the
fight against malaria.
Summary
Anopheles gambiae mosquitoes are the major vectors of malaria, a disease with devastating consequences for
human health. Novel methods for controlling the natural vector populations are urgently needed, given the
evolution of insecticide resistance in mosquitoes and the lack of novel insecticidals. Understanding the
processes at the bases of mosquito biology may help to roll back malaria. In this proposal, we will target
mosquito reproduction, a major determinant of the An. gambiae vectorial capacity. This will be achieved at
two levels: (i) fundamental research, to provide a deeper knowledge of the processes regulating reproduction
in this species, and (ii) applied research, to identify novel targets and to develop innovative approaches for
the control of natural populations. We will focus our analysis on three major players of mosquito
reproduction: male accessory glands (MAGs), sperm, and spermatheca, in both laboratory and field settings.
We will then translate this information into the identification of inhibitors of mosquito fertility. The
experimental activities will be divided across three objectives. In Objective 1, we will unravel the role of the
MAGs in shaping mosquito fertility and behaviour, by performing a combination of transcriptional and
functional studies that will reveal the multifaceted activities of these tissues. In Objective 2 we will instead
focus on the identification of the male and female factors responsible for sperm viability and function.
Results obtained in both objectives will be validated in field mosquitoes. In Objective 3, we will perform
screens aimed at the identification of inhibitors of mosquito reproductive success. This study will reveal as
yet unknown molecular mechanisms underlying reproductive success in mosquitoes, considerably increasing
our knowledge beyond the state-of-the-art and critically contributing with innovative tools and ideas to the
fight against malaria.
Max ERC Funding
1 500 000 €
Duration
Start date: 2011-01-01, End date: 2015-12-31
Project acronym BACTERIAL SPORES
Project Investigating the Nature of Bacterial Spores
Researcher (PI) Sigal Ben-Yehuda
Host Institution (HI) THE HEBREW UNIVERSITY OF JERUSALEM
Call Details Starting Grant (StG), LS3, ERC-2007-StG
Summary When triggered by nutrient limitation, the Gram-positive bacterium Bacillus subtilis and its relatives enter a pathway of cellular differentiation culminating in the formation of a dormant cell type called a spore, the most resilient cell type known. Bacterial spores can survive for long periods of time and are able to endure extremes of heat, radiation and chemical assault. Remarkably, dormant spores can rapidly convert back to actively growing cells by a process called germination. Consequently, spore forming bacteria, including dangerous pathogens, (such as C. botulinum and B. anthracis) are highly resistant to antibacterial treatments and difficult to eradicate. Despite significant advances in our understanding of the process of spore formation, little is known about the nature of the mature spore. It is unrevealed how dormancy is maintained within the spore and how it is ceased, as the organization and the dynamics of the spore macromolecules remain obscure. The unusual biochemical and biophysical characteristics of the dormant spore make it a challenging biological system to investigate using conventional methods, and thus set the need to develop innovative approaches to study spore biology. We propose to explore the nature of spores by using B. subtilis as a primary experimental system. We intend to: (1) define the architecture of the spore chromosome, (2) track the complexity and fate of mRNA and protein molecules during sporulation, dormancy and germination, (3) revisit the basic notion of the spore dormancy (is it metabolically inert?), (4) compare the characteristics of bacilli spores from diverse ecophysiological groups, (5) investigate the features of spores belonging to distant bacterial genera, (6) generate an integrative database that categorizes the molecular features of spores. Our study will provide original insights and introduce novel concepts to the field of spore biology and may help devise innovative ways to combat spore forming pathogens.
Summary
When triggered by nutrient limitation, the Gram-positive bacterium Bacillus subtilis and its relatives enter a pathway of cellular differentiation culminating in the formation of a dormant cell type called a spore, the most resilient cell type known. Bacterial spores can survive for long periods of time and are able to endure extremes of heat, radiation and chemical assault. Remarkably, dormant spores can rapidly convert back to actively growing cells by a process called germination. Consequently, spore forming bacteria, including dangerous pathogens, (such as C. botulinum and B. anthracis) are highly resistant to antibacterial treatments and difficult to eradicate. Despite significant advances in our understanding of the process of spore formation, little is known about the nature of the mature spore. It is unrevealed how dormancy is maintained within the spore and how it is ceased, as the organization and the dynamics of the spore macromolecules remain obscure. The unusual biochemical and biophysical characteristics of the dormant spore make it a challenging biological system to investigate using conventional methods, and thus set the need to develop innovative approaches to study spore biology. We propose to explore the nature of spores by using B. subtilis as a primary experimental system. We intend to: (1) define the architecture of the spore chromosome, (2) track the complexity and fate of mRNA and protein molecules during sporulation, dormancy and germination, (3) revisit the basic notion of the spore dormancy (is it metabolically inert?), (4) compare the characteristics of bacilli spores from diverse ecophysiological groups, (5) investigate the features of spores belonging to distant bacterial genera, (6) generate an integrative database that categorizes the molecular features of spores. Our study will provide original insights and introduce novel concepts to the field of spore biology and may help devise innovative ways to combat spore forming pathogens.
Max ERC Funding
1 630 000 €
Duration
Start date: 2008-10-01, End date: 2013-09-30
Project acronym BANDWIDTH
Project The cost of limited communication bandwidth in distributed computing
Researcher (PI) Keren CENSOR-HILLEL
Host Institution (HI) TECHNION - ISRAEL INSTITUTE OF TECHNOLOGY
Call Details Starting Grant (StG), PE6, ERC-2017-STG
Summary Distributed systems underlie many modern technologies, a prime example being the Internet. The ever-increasing abundance of distributed systems necessitates their design and usage to be backed by strong theoretical foundations.
A major challenge that distributed systems face is the lack of a central authority, which brings many aspects of uncertainty into the environment, in the form of unknown network topology or unpredictable dynamic behavior. A practical restriction of distributed systems, which is at the heart of this proposal, is the limited bandwidth available for communication between the network components.
A central family of distributed tasks is that of local tasks, which are informally described as tasks which are possible to solve by sending information through only a relatively small number of hops. A cornerstone example is the need to break symmetry and provide a better utilization of resources, which can be obtained by the task of producing a valid coloring of the nodes given some small number of colors. Amazingly, there are still huge gaps between the known upper and lower bounds for the complexity of many local tasks. This holds even if one allows powerful assumptions of unlimited bandwidth. While some known algorithms indeed use small messages, the complexity gaps are even larger compared to the unlimited bandwidth case. This is not a mere coincidence, and in fact the existing theoretical infrastructure is provably incapable of
giving stronger lower bounds for many local tasks under limited bandwidth.
This proposal zooms in on this crucial blind spot in the current literature on the theory of distributed computing, namely, the study of local tasks under limited bandwidth. The goal of this research is to produce fast algorithms for fundamental distributed local tasks under restricted bandwidth, as well as understand their limitations by providing lower bounds.
Summary
Distributed systems underlie many modern technologies, a prime example being the Internet. The ever-increasing abundance of distributed systems necessitates their design and usage to be backed by strong theoretical foundations.
A major challenge that distributed systems face is the lack of a central authority, which brings many aspects of uncertainty into the environment, in the form of unknown network topology or unpredictable dynamic behavior. A practical restriction of distributed systems, which is at the heart of this proposal, is the limited bandwidth available for communication between the network components.
A central family of distributed tasks is that of local tasks, which are informally described as tasks which are possible to solve by sending information through only a relatively small number of hops. A cornerstone example is the need to break symmetry and provide a better utilization of resources, which can be obtained by the task of producing a valid coloring of the nodes given some small number of colors. Amazingly, there are still huge gaps between the known upper and lower bounds for the complexity of many local tasks. This holds even if one allows powerful assumptions of unlimited bandwidth. While some known algorithms indeed use small messages, the complexity gaps are even larger compared to the unlimited bandwidth case. This is not a mere coincidence, and in fact the existing theoretical infrastructure is provably incapable of
giving stronger lower bounds for many local tasks under limited bandwidth.
This proposal zooms in on this crucial blind spot in the current literature on the theory of distributed computing, namely, the study of local tasks under limited bandwidth. The goal of this research is to produce fast algorithms for fundamental distributed local tasks under restricted bandwidth, as well as understand their limitations by providing lower bounds.
Max ERC Funding
1 486 480 €
Duration
Start date: 2018-06-01, End date: 2023-05-31
Project acronym BiomeRiskFactors
Project Discovering microbiome-based disease risk factors
Researcher (PI) Eran Segal
Host Institution (HI) WEIZMANN INSTITUTE OF SCIENCE
Call Details Advanced Grant (AdG), LS2, ERC-2017-ADG
Summary Identifying risk factors for diseases that can be prevented or delayed by early intervention is of major importance, and numerous genetic, lifestyle, anthropometric and clinical risk factors were found for many different diseases. Another source of potentially pertinent disease risk factors is the human microbiome - the collective genome of trillions of bacteria, viruses, fungi, and parasites that reside in the human gut. However, very few microbiome disease markers were found to date.
Here, we aim to develop risk prediction tools based on the human microbiome that predict the likelihood of an individual to develop a particular condition or disease within 5-10 years. We will use a cohort of >2200 individuals that my group previously assembled, for whom we have clinical profiles, gut microbiome data, and banked blood and stool samples. We will invite people 5-10 years after their initial recruitment time, profile disease status and blood markers, and develop algorithms for predicting 5-10 year onset of Type 2 diabetes, cardiovascular disease, and obesity, using microbiome data from recruitment time.
To increase the likelihood of finding microbiome markers predictive of disease onset, we will develop novel experimental and computational methods for in-depth characterization of microbial gene function, the metabolites produced by the microbiome, the underexplored fungal microbiome members, and the interactions between the gut microbiota and the host adaptive immune system. We will then apply these methods to >2200 banked samples from cohort recruitment time and use the resulting data in devising our microbiome-based risk prediction tools. In themselves, these novel assays and their application to >2200 samples should greatly advance the microbiome field.
If successful, our proposal will identify new disease risk factors and risk prediction tools based on the microbiome, paving the way towards using the microbiome in early disease detection and prevention.
Summary
Identifying risk factors for diseases that can be prevented or delayed by early intervention is of major importance, and numerous genetic, lifestyle, anthropometric and clinical risk factors were found for many different diseases. Another source of potentially pertinent disease risk factors is the human microbiome - the collective genome of trillions of bacteria, viruses, fungi, and parasites that reside in the human gut. However, very few microbiome disease markers were found to date.
Here, we aim to develop risk prediction tools based on the human microbiome that predict the likelihood of an individual to develop a particular condition or disease within 5-10 years. We will use a cohort of >2200 individuals that my group previously assembled, for whom we have clinical profiles, gut microbiome data, and banked blood and stool samples. We will invite people 5-10 years after their initial recruitment time, profile disease status and blood markers, and develop algorithms for predicting 5-10 year onset of Type 2 diabetes, cardiovascular disease, and obesity, using microbiome data from recruitment time.
To increase the likelihood of finding microbiome markers predictive of disease onset, we will develop novel experimental and computational methods for in-depth characterization of microbial gene function, the metabolites produced by the microbiome, the underexplored fungal microbiome members, and the interactions between the gut microbiota and the host adaptive immune system. We will then apply these methods to >2200 banked samples from cohort recruitment time and use the resulting data in devising our microbiome-based risk prediction tools. In themselves, these novel assays and their application to >2200 samples should greatly advance the microbiome field.
If successful, our proposal will identify new disease risk factors and risk prediction tools based on the microbiome, paving the way towards using the microbiome in early disease detection and prevention.
Max ERC Funding
2 500 000 €
Duration
Start date: 2019-03-01, End date: 2024-02-29
