Project acronym 3DBrainStrom
Project Brain metastases: Deciphering tumor-stroma interactions in three dimensions for the rational design of nanomedicines
Researcher (PI) Ronit Satchi Fainaro
Host Institution (HI) TEL AVIV UNIVERSITY
Call Details Advanced Grant (AdG), LS7, ERC-2018-ADG
Summary Brain metastases represent a major therapeutic challenge. Despite significant breakthroughs in targeted therapies, survival rates of patients with brain metastases remain poor. Nowadays, discovery, development and evaluation of new therapies are performed on human cancer cells grown in 2D on rigid plastic plates followed by in vivo testing in immunodeficient mice. These experimental settings are lacking and constitute a fundamental hurdle for the translation of preclinical discoveries into clinical practice. We propose to establish 3D-printed models of brain metastases (Aim 1), which include brain extracellular matrix, stroma and serum containing immune cells flowing in functional tumor vessels. Our unique models better capture the clinical physio-mechanical tissue properties, signaling pathways, hemodynamics and drug responsiveness. Using our 3D-printed models, we aim to develop two new fronts for identifying novel clinically-relevant molecular drivers (Aim 2) followed by the development of precision nanomedicines (Aim 3). We will exploit our vast experience in anticancer nanomedicines to design three therapeutic approaches that target various cellular compartments involved in brain metastases: 1) Prevention of brain metastatic colonization using targeted nano-vaccines, which elicit antitumor immune response; 2) Intervention of tumor-brain stroma cells crosstalk when brain micrometastases establish; 3) Regression of macrometastatic disease by selectively targeting tumor cells. These approaches will materialize using our libraries of polymeric nanocarriers that selectively accumulate in tumors.
This project will result in a paradigm shift by generating new preclinical cancer models that will bridge the translational gap in cancer therapeutics. The insights and tumor-stroma-targeted nanomedicines developed here will pave the way for prediction of patient outcome, revolutionizing our perception of tumor modelling and consequently the way we prevent and treat cancer.
Summary
Brain metastases represent a major therapeutic challenge. Despite significant breakthroughs in targeted therapies, survival rates of patients with brain metastases remain poor. Nowadays, discovery, development and evaluation of new therapies are performed on human cancer cells grown in 2D on rigid plastic plates followed by in vivo testing in immunodeficient mice. These experimental settings are lacking and constitute a fundamental hurdle for the translation of preclinical discoveries into clinical practice. We propose to establish 3D-printed models of brain metastases (Aim 1), which include brain extracellular matrix, stroma and serum containing immune cells flowing in functional tumor vessels. Our unique models better capture the clinical physio-mechanical tissue properties, signaling pathways, hemodynamics and drug responsiveness. Using our 3D-printed models, we aim to develop two new fronts for identifying novel clinically-relevant molecular drivers (Aim 2) followed by the development of precision nanomedicines (Aim 3). We will exploit our vast experience in anticancer nanomedicines to design three therapeutic approaches that target various cellular compartments involved in brain metastases: 1) Prevention of brain metastatic colonization using targeted nano-vaccines, which elicit antitumor immune response; 2) Intervention of tumor-brain stroma cells crosstalk when brain micrometastases establish; 3) Regression of macrometastatic disease by selectively targeting tumor cells. These approaches will materialize using our libraries of polymeric nanocarriers that selectively accumulate in tumors.
This project will result in a paradigm shift by generating new preclinical cancer models that will bridge the translational gap in cancer therapeutics. The insights and tumor-stroma-targeted nanomedicines developed here will pave the way for prediction of patient outcome, revolutionizing our perception of tumor modelling and consequently the way we prevent and treat cancer.
Max ERC Funding
2 353 125 €
Duration
Start date: 2019-04-01, End date: 2024-03-31
Project acronym ADIMMUNE
Project Decoding interactions between adipose tissue immune cells, metabolic function, and the intestinal microbiome in obesity
Researcher (PI) Eran Elinav
Host Institution (HI) WEIZMANN INSTITUTE OF SCIENCE
Call Details Consolidator Grant (CoG), LS6, ERC-2018-COG
Summary Obesity and its metabolic co-morbidities have given rise to a rapidly expanding ‘metabolic syndrome’ pandemic affecting
hundreds of millions of individuals worldwide. The integrative genetic and environmental causes of the obesity pandemic
remain elusive. White adipose tissue (WAT)-resident immune cells have recently been highlighted as important factors
contributing to metabolic complications. However, a comprehensive understanding of the regulatory circuits governing their
function and the cell type-specific mechanisms by which they contribute to the development of metabolic syndrome is
lacking. Likewise, the gut microbiome has been suggested as a critical regulator of obesity, but the bacterial species and
metabolites that influence WAT inflammation are entirely unknown.
We propose to use our recently developed high-throughput genomic and gnotobiotic tools, integrated with CRISPR-mediated interrogation of gene function, microbial culturomics, and in-vivo metabolic analysis in newly generated mouse models, in order to achieve a new level of molecular understanding of how WAT immune cells integrate environmental cues into their crosstalk with organismal metabolism, and to explore the microbial contributions to the molecular etiology of WAT inflammation in the pathogenesis of diet-induced obesity. Specifically, we aim to (a) decipher the global regulatory landscape and interaction networks of WAT hematopoietic cells at the single-cell level, (b) identify new mediators of WAT immune cell contributions to metabolic homeostasis, and (c) decode how host-microbiome communication shapes the development of WAT inflammation and obesity.
Unraveling the principles of WAT immune cell regulation and their amenability to change by host-microbiota interactions
may lead to a conceptual leap forward in our understanding of metabolic physiology and disease. Concomitantly, it may
generate a platform for microbiome-based personalized therapy against obesity and its complications.
Summary
Obesity and its metabolic co-morbidities have given rise to a rapidly expanding ‘metabolic syndrome’ pandemic affecting
hundreds of millions of individuals worldwide. The integrative genetic and environmental causes of the obesity pandemic
remain elusive. White adipose tissue (WAT)-resident immune cells have recently been highlighted as important factors
contributing to metabolic complications. However, a comprehensive understanding of the regulatory circuits governing their
function and the cell type-specific mechanisms by which they contribute to the development of metabolic syndrome is
lacking. Likewise, the gut microbiome has been suggested as a critical regulator of obesity, but the bacterial species and
metabolites that influence WAT inflammation are entirely unknown.
We propose to use our recently developed high-throughput genomic and gnotobiotic tools, integrated with CRISPR-mediated interrogation of gene function, microbial culturomics, and in-vivo metabolic analysis in newly generated mouse models, in order to achieve a new level of molecular understanding of how WAT immune cells integrate environmental cues into their crosstalk with organismal metabolism, and to explore the microbial contributions to the molecular etiology of WAT inflammation in the pathogenesis of diet-induced obesity. Specifically, we aim to (a) decipher the global regulatory landscape and interaction networks of WAT hematopoietic cells at the single-cell level, (b) identify new mediators of WAT immune cell contributions to metabolic homeostasis, and (c) decode how host-microbiome communication shapes the development of WAT inflammation and obesity.
Unraveling the principles of WAT immune cell regulation and their amenability to change by host-microbiota interactions
may lead to a conceptual leap forward in our understanding of metabolic physiology and disease. Concomitantly, it may
generate a platform for microbiome-based personalized therapy against obesity and its complications.
Max ERC Funding
2 000 000 €
Duration
Start date: 2019-03-01, End date: 2024-02-29
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 AutoCAb
Project Automated computational design of site-targeted repertoires of camelid antibodies
Researcher (PI) Sarel-Jacob FLEISHMAN
Host Institution (HI) WEIZMANN INSTITUTE OF SCIENCE
Call Details Consolidator Grant (CoG), LS9, ERC-2018-COG
Summary We propose to develop the first high-throughput strategy to design, synthesize, and screen repertoires comprising millions of single-domain camelid antibodies (VHH) that target desired protein surfaces. Each VHH will be individually designed for high stability and target-site affinity. We will leverage recent methods developed by our lab for designing stable, specific, and accurate backbones at interfaces, the advent of massive and affordable custom-DNA oligo synthesis, and machine learning methods to accomplish the following aims:
Aim 1: Establish a completely automated computational pipeline that uses Rosetta to design millions of VHHs targeting desired protein surfaces. The variable regions in each design will be encoded in DNA oligo pools, which will be assembled to generate the entire site-targeted repertoire. We will then use high-throughput binding screens followed by deep sequencing to characterize the designs’ target-site affinity and isolate high-affinity binders.
Aim 2: Develop an epitope-focusing strategy that designs several variants of a target antigen, each of which encodes dozens of radical surface mutations outside the target site to disrupt potential off-target site binding. The designs will be used to isolate site-targeting binders from repertoires of Aim 1.
Each high-throughput screen will provide unprecedented experimental data on target-site affinity in millions of individually designed VHHs.
Aim 3: Use machine learning methods to infer combinations of molecular features that distinguish high-affinity binders from non binders. These will be encoded in subsequent designed repertoires, leading to a continuous “learning loop” of methods for high-affinity, site-targeted binding.
AutoCAb’s interdisciplinary strategy will thus lead to deeper understanding of and new general methods for designing stable, high-affinity, site-targeted antibodies, potentially revolutionizing binder and inhibitor discovery in basic and applied biomedical research.
Summary
We propose to develop the first high-throughput strategy to design, synthesize, and screen repertoires comprising millions of single-domain camelid antibodies (VHH) that target desired protein surfaces. Each VHH will be individually designed for high stability and target-site affinity. We will leverage recent methods developed by our lab for designing stable, specific, and accurate backbones at interfaces, the advent of massive and affordable custom-DNA oligo synthesis, and machine learning methods to accomplish the following aims:
Aim 1: Establish a completely automated computational pipeline that uses Rosetta to design millions of VHHs targeting desired protein surfaces. The variable regions in each design will be encoded in DNA oligo pools, which will be assembled to generate the entire site-targeted repertoire. We will then use high-throughput binding screens followed by deep sequencing to characterize the designs’ target-site affinity and isolate high-affinity binders.
Aim 2: Develop an epitope-focusing strategy that designs several variants of a target antigen, each of which encodes dozens of radical surface mutations outside the target site to disrupt potential off-target site binding. The designs will be used to isolate site-targeting binders from repertoires of Aim 1.
Each high-throughput screen will provide unprecedented experimental data on target-site affinity in millions of individually designed VHHs.
Aim 3: Use machine learning methods to infer combinations of molecular features that distinguish high-affinity binders from non binders. These will be encoded in subsequent designed repertoires, leading to a continuous “learning loop” of methods for high-affinity, site-targeted binding.
AutoCAb’s interdisciplinary strategy will thus lead to deeper understanding of and new general methods for designing stable, high-affinity, site-targeted antibodies, potentially revolutionizing binder and inhibitor discovery in basic and applied biomedical research.
Max ERC Funding
2 337 500 €
Duration
Start date: 2019-01-01, End date: 2023-12-31
Project acronym BARINAFLD
Project Using Bariatric Surgery to Discover Weight-Loss Independent Mechanisms Leading to the Reversal of Fatty Liver Disease
Researcher (PI) Danny Ben-Zvi
Host Institution (HI) THE HEBREW UNIVERSITY OF JERUSALEM
Call Details Starting Grant (StG), LS4, ERC-2018-STG
Summary Non-Alcoholic Fatty Liver Disease (NAFLD), a disease characterized by accumulation of lipid droplets in the liver, is the major precursor for liver failure and liver cancer, and constitutes a global health challenge. An estimated 25% of the adult population suffers from NAFLD, but no FDA approved drugs are available to treat this condition. Obesity is a major NAFLD risk factor and weight-loss improves disease severity in obese patients. Bariatric surgeries are an effective treatment for obesity when lifestyle modifications fail and often lead to improvement in NAFLD and type 2 diabetes.
The overreaching objective of this proposal is to combine bariatric surgery in mice and humans with advanced molecular and computational analyses to discover novel, weight-loss independent mechanisms that lead to NAFLD alleviation, and harness them to treat NAFLD.
In preliminary studies, I discovered that bariatric surgery clears lipid droplets from the livers of obese db/db mice without inducing weight-loss. Using metabolic and computational analysis, I found that bariatric surgery shifts hepatic gene expression and blood metabolome of post-bariatric patients to a new trajectory, distinct from lean or sick patients. Data analysis revealed the transcription factor Egr1 and one-carbon and choline metabolism to be key drivers of weight-loss independent effects of bariatric surgery.
I will use two NAFLD mouse models that do not lose weight after bariatric surgery to characterize livers of mice post-surgery. Human patients do lose weight following surgery, therefore I will use computational methods to elucidate weight-independent pathways induced by surgery, by comparing livers of lean patients to those of NAFLD patients before and shortly after bariatric surgery. Candidate pathways will be studied by metabolic flux analysis and manipulated genetically, with the ultimate goal of reaching systems-levels understanding of NAFLD and identifying surgery-mimetic therapies for this disease.
Summary
Non-Alcoholic Fatty Liver Disease (NAFLD), a disease characterized by accumulation of lipid droplets in the liver, is the major precursor for liver failure and liver cancer, and constitutes a global health challenge. An estimated 25% of the adult population suffers from NAFLD, but no FDA approved drugs are available to treat this condition. Obesity is a major NAFLD risk factor and weight-loss improves disease severity in obese patients. Bariatric surgeries are an effective treatment for obesity when lifestyle modifications fail and often lead to improvement in NAFLD and type 2 diabetes.
The overreaching objective of this proposal is to combine bariatric surgery in mice and humans with advanced molecular and computational analyses to discover novel, weight-loss independent mechanisms that lead to NAFLD alleviation, and harness them to treat NAFLD.
In preliminary studies, I discovered that bariatric surgery clears lipid droplets from the livers of obese db/db mice without inducing weight-loss. Using metabolic and computational analysis, I found that bariatric surgery shifts hepatic gene expression and blood metabolome of post-bariatric patients to a new trajectory, distinct from lean or sick patients. Data analysis revealed the transcription factor Egr1 and one-carbon and choline metabolism to be key drivers of weight-loss independent effects of bariatric surgery.
I will use two NAFLD mouse models that do not lose weight after bariatric surgery to characterize livers of mice post-surgery. Human patients do lose weight following surgery, therefore I will use computational methods to elucidate weight-independent pathways induced by surgery, by comparing livers of lean patients to those of NAFLD patients before and shortly after bariatric surgery. Candidate pathways will be studied by metabolic flux analysis and manipulated genetically, with the ultimate goal of reaching systems-levels understanding of NAFLD and identifying surgery-mimetic therapies for this disease.
Max ERC Funding
1 499 354 €
Duration
Start date: 2018-11-01, End date: 2023-10-31
Project acronym bECOMiNG
Project spontaneous Evolution and Clonal heterOgeneity in MoNoclonal Gammopathies: from mechanisms of progression to clinical management
Researcher (PI) Niccolo Bolli
Host Institution (HI) UNIVERSITA DEGLI STUDI DI MILANO
Call Details Consolidator Grant (CoG), LS7, ERC-2018-COG
Summary As an onco-hematologist with a strong expertise in genomics, I significantly contributed to the understanding of multiple myeloma (MM) heterogeneity and its evolution over time, driven by genotypic and phenotypic features carried by different subpopulations of cells. MM is preceded by prevalent, asymptomatic stages that may evolve with variable frequency, not accurately captured by current clinical prognostic scores. Supported by preliminary data, my hypothesis is that the same heterogeneity is present early on the disease course, and identification of the biological determinants of evolution at this stage will allow better prediction of its evolutionary trajectory, if not its control. In this proposal I will therefore make a sharp change from conventional approaches and move to early stages of MM using unique retrospective sample cohorts and ambitious prospective sampling. To identify clonal MM cells in the elderly before a monoclonal gammopathy can be detected, I will collect bone marrow (BM) from hundreds of hip replacement specimens, and analyze archive peripheral blood samples of thousands of healthy individuals with years of annotated clinical follow-up. This will identify early genomic alterations that are permissive to disease initiation/evolution and may serve as biomarkers for clinical screening. Through innovative, integrated single-cell genotyping and phenotyping of hundreds of asymptomatic MMs, I will functionally dissect heterogeneity and characterize the BM microenvironment to look for determinants of disease progression. Correlation with clinical outcome and mini-invasive serial sampling of circulating cell-free DNA will identify candidate biological markers to better predict evolution. Last, aggressive modelling of candidate early lesions and modifier screens will offer a list of vulnerabilities that could be exploited for rationale therapies. These methodologies will deliver a paradigm for the use of molecularly-driven precision medicine in cancer.
Summary
As an onco-hematologist with a strong expertise in genomics, I significantly contributed to the understanding of multiple myeloma (MM) heterogeneity and its evolution over time, driven by genotypic and phenotypic features carried by different subpopulations of cells. MM is preceded by prevalent, asymptomatic stages that may evolve with variable frequency, not accurately captured by current clinical prognostic scores. Supported by preliminary data, my hypothesis is that the same heterogeneity is present early on the disease course, and identification of the biological determinants of evolution at this stage will allow better prediction of its evolutionary trajectory, if not its control. In this proposal I will therefore make a sharp change from conventional approaches and move to early stages of MM using unique retrospective sample cohorts and ambitious prospective sampling. To identify clonal MM cells in the elderly before a monoclonal gammopathy can be detected, I will collect bone marrow (BM) from hundreds of hip replacement specimens, and analyze archive peripheral blood samples of thousands of healthy individuals with years of annotated clinical follow-up. This will identify early genomic alterations that are permissive to disease initiation/evolution and may serve as biomarkers for clinical screening. Through innovative, integrated single-cell genotyping and phenotyping of hundreds of asymptomatic MMs, I will functionally dissect heterogeneity and characterize the BM microenvironment to look for determinants of disease progression. Correlation with clinical outcome and mini-invasive serial sampling of circulating cell-free DNA will identify candidate biological markers to better predict evolution. Last, aggressive modelling of candidate early lesions and modifier screens will offer a list of vulnerabilities that could be exploited for rationale therapies. These methodologies will deliver a paradigm for the use of molecularly-driven precision medicine in cancer.
Max ERC Funding
1 998 781 €
Duration
Start date: 2019-03-01, End date: 2024-02-29
Project acronym BRuSH
Project Oral bacteria as determinants for respiratory health
Researcher (PI) Randi BERTELSEN
Host Institution (HI) UNIVERSITETET I BERGEN
Call Details Starting Grant (StG), LS7, ERC-2018-STG
Summary The oral cavity is the gateway to the lower respiratory tract, and oral bacteria are likely to play a role in lung health. This may be the case for pathogens as well as commensal bacteria and the balance between species. The oral bacterial community of patients with periodontitis is dominated by gram-negative bacteria and a higher lipopolysaccharide (LPS) activity than in healthy microbiota. Furthermore, bacteria with especially potent pro-inflammatory LPS have been shown to be more common in the lungs of asthmatic than in healthy individuals. The working hypothesis of BRuSH is that microbiome communities dominated by LPS-producing bacteria which induce a particularly strong pro-inflammatory immune response in the host, will have a negative effect on respiratory health. I will test this hypothesis in two longitudinally designed population-based lung health studies. I aim to identify whether specific bacterial composition and types of LPS producing bacteria in oral and dust samples predict lung function and respiratory health over time; and if the different types of LPS-producing bacteria affect LPS in saliva saliva and dust. BRuSH will apply functional genome annotation that can assign biological significance to raw bacterial DNA sequences. With this bioinformatics tool I will cluster microbiome data into various LPS-producers: bacteria with LPS with strong inflammatory effects and others with weak- or antagonistic effects. The epidemiological studies will be supported by mice-models of asthma and cell assays of human bronchial epithelial cells, by exposing mice and bronchial cells to chemically synthesized Lipid A (the component that drive the LPS-induced immune responses) of various potency. The goal of BRuSH is to prove a causal relationship between oral microbiome and lung health, and gain knowledge that will enable us to make oral health a feasible target for intervention programs aimed at optimizing lung health and preventing respiratory disease.
Summary
The oral cavity is the gateway to the lower respiratory tract, and oral bacteria are likely to play a role in lung health. This may be the case for pathogens as well as commensal bacteria and the balance between species. The oral bacterial community of patients with periodontitis is dominated by gram-negative bacteria and a higher lipopolysaccharide (LPS) activity than in healthy microbiota. Furthermore, bacteria with especially potent pro-inflammatory LPS have been shown to be more common in the lungs of asthmatic than in healthy individuals. The working hypothesis of BRuSH is that microbiome communities dominated by LPS-producing bacteria which induce a particularly strong pro-inflammatory immune response in the host, will have a negative effect on respiratory health. I will test this hypothesis in two longitudinally designed population-based lung health studies. I aim to identify whether specific bacterial composition and types of LPS producing bacteria in oral and dust samples predict lung function and respiratory health over time; and if the different types of LPS-producing bacteria affect LPS in saliva saliva and dust. BRuSH will apply functional genome annotation that can assign biological significance to raw bacterial DNA sequences. With this bioinformatics tool I will cluster microbiome data into various LPS-producers: bacteria with LPS with strong inflammatory effects and others with weak- or antagonistic effects. The epidemiological studies will be supported by mice-models of asthma and cell assays of human bronchial epithelial cells, by exposing mice and bronchial cells to chemically synthesized Lipid A (the component that drive the LPS-induced immune responses) of various potency. The goal of BRuSH is to prove a causal relationship between oral microbiome and lung health, and gain knowledge that will enable us to make oral health a feasible target for intervention programs aimed at optimizing lung health and preventing respiratory disease.
Max ERC Funding
1 499 938 €
Duration
Start date: 2019-01-01, End date: 2023-12-31
Project acronym CoPathoPhage
Project Pathogen-phage cooperation during mammalian infection
Researcher (PI) Anat Herskovits
Host Institution (HI) TEL AVIV UNIVERSITY
Call Details Consolidator Grant (CoG), LS6, ERC-2018-COG
Summary Most bacterial pathogens are lysogens, namely carry DNA of active phages within their genome, referred to as prophages. While these prophages have the potential to turn under stress into infective viruses which kill their host bacterium in a matter of minutes, it is unclear how pathogens manage to survive this internal threat under the stresses imposed by their invasion into mammalian cells. In the proposed project, we will study the hypothesis that a complex bacteria-phage cooperative adaptation supports virulence during mammalian infection while preventing inadvertent killing by phages. Several years ago, we uncovered a novel pathogen-phage interaction, in which an infective prophage promotes the virulence of its host, the bacterial pathogen Listeria monocytogenes (Lm), via adaptive behaviour. More recently, we discovered that the prophage, though fully infective, is non-autonomous- completely dependent on regulatory factors derived from inactive prophage remnants that reside in the Lm chromosome. These findings lead us to propose that the intimate cross-regulatory interactions between all phage elements within the genome (infective and remnant), are crucial in promoting bacteria-phage patho-adaptive behaviours in the mammalian niche and thereby bacterial virulence. In the proposed project, we will investigate specific cross-regulatory and cooperative mechanisms of all the phage elements, study the domestication of phage remnant-derived regulatory factors, and examine the hypothesis that they collectively form an auxiliary phage-control system that tempers infective phages. Finally, we will examine the premise that the mammalian niche drives the evolution of temperate phages into patho-adaptive phages, and that phages that lack this adaptation may kill host pathogens during infection. This work is expected to provide novel insights into bacteria-phage coexistence in mammalian environments and to facilitate the development of innovative phage therapy strategies.
Summary
Most bacterial pathogens are lysogens, namely carry DNA of active phages within their genome, referred to as prophages. While these prophages have the potential to turn under stress into infective viruses which kill their host bacterium in a matter of minutes, it is unclear how pathogens manage to survive this internal threat under the stresses imposed by their invasion into mammalian cells. In the proposed project, we will study the hypothesis that a complex bacteria-phage cooperative adaptation supports virulence during mammalian infection while preventing inadvertent killing by phages. Several years ago, we uncovered a novel pathogen-phage interaction, in which an infective prophage promotes the virulence of its host, the bacterial pathogen Listeria monocytogenes (Lm), via adaptive behaviour. More recently, we discovered that the prophage, though fully infective, is non-autonomous- completely dependent on regulatory factors derived from inactive prophage remnants that reside in the Lm chromosome. These findings lead us to propose that the intimate cross-regulatory interactions between all phage elements within the genome (infective and remnant), are crucial in promoting bacteria-phage patho-adaptive behaviours in the mammalian niche and thereby bacterial virulence. In the proposed project, we will investigate specific cross-regulatory and cooperative mechanisms of all the phage elements, study the domestication of phage remnant-derived regulatory factors, and examine the hypothesis that they collectively form an auxiliary phage-control system that tempers infective phages. Finally, we will examine the premise that the mammalian niche drives the evolution of temperate phages into patho-adaptive phages, and that phages that lack this adaptation may kill host pathogens during infection. This work is expected to provide novel insights into bacteria-phage coexistence in mammalian environments and to facilitate the development of innovative phage therapy strategies.
Max ERC Funding
2 200 000 €
Duration
Start date: 2019-10-01, End date: 2024-09-30
Project acronym CRISPRsition
Project Developing CRISPR adaptation platforms for basic and applied research
Researcher (PI) Ehud Itzhak Qimron
Host Institution (HI) TEL AVIV UNIVERSITY
Call Details Consolidator Grant (CoG), LS2, ERC-2018-COG
Summary The CRISPR-Cas system has been extensively studied for its ability to cleave DNA. In contrast, studies of the ability of the system to acquire and integrate new DNA from invaders as a form of prokaryotic adaptive immunity, have lagged behind. This delay reflects the extreme enthusiasm surrounding the potential of using the system’s cleavage capabilities as a genome editing tool. However, the enormous potential of the adaptation process can and should arouse a similar degree of enthusiasm. My lab has pioneered studies on the CRISPR adaptation process by establishing new methodologies, and applying them to demonstrate the essential role of the proteins and DNA elements, as well as the molecular mechanisms, operating in this process. In this project, I will establish novel platforms for studying adaptation and develop them into biotechnological applications and research tools. These tools will allow me to identify the first natural and synthetic inhibitors of the adaptation process. This, in turn, will provide genetic tools to control adaptation, as well as advance the understanding of the arms race between bacteria and their invaders. I will also harness the adaptation process as a platform for diversifying genetic elements for phage display, and for extending phage recognition of a wide range of hosts. Lastly, I will provide the first evidence for an association between the CRISPR adaptation system and gene repression. This linkage will form the basis of a molecular scanner and recorder platform that I will develop and that can be used to identify crucial genetic elements in phage genomes as well as novel regulatory circuits in the bacterial genome. Together, my findings will represent a considerable leap in the understanding of CRISPR adaptation with respect to the process, potential applications, and the intriguing evolutionary significance.
Summary
The CRISPR-Cas system has been extensively studied for its ability to cleave DNA. In contrast, studies of the ability of the system to acquire and integrate new DNA from invaders as a form of prokaryotic adaptive immunity, have lagged behind. This delay reflects the extreme enthusiasm surrounding the potential of using the system’s cleavage capabilities as a genome editing tool. However, the enormous potential of the adaptation process can and should arouse a similar degree of enthusiasm. My lab has pioneered studies on the CRISPR adaptation process by establishing new methodologies, and applying them to demonstrate the essential role of the proteins and DNA elements, as well as the molecular mechanisms, operating in this process. In this project, I will establish novel platforms for studying adaptation and develop them into biotechnological applications and research tools. These tools will allow me to identify the first natural and synthetic inhibitors of the adaptation process. This, in turn, will provide genetic tools to control adaptation, as well as advance the understanding of the arms race between bacteria and their invaders. I will also harness the adaptation process as a platform for diversifying genetic elements for phage display, and for extending phage recognition of a wide range of hosts. Lastly, I will provide the first evidence for an association between the CRISPR adaptation system and gene repression. This linkage will form the basis of a molecular scanner and recorder platform that I will develop and that can be used to identify crucial genetic elements in phage genomes as well as novel regulatory circuits in the bacterial genome. Together, my findings will represent a considerable leap in the understanding of CRISPR adaptation with respect to the process, potential applications, and the intriguing evolutionary significance.
Max ERC Funding
2 000 000 €
Duration
Start date: 2019-12-01, End date: 2024-11-30
Project acronym DisConn
Project Neural drivers of functional disconnectivity in brain disorders
Researcher (PI) Alessandro GOZZI
Host Institution (HI) FONDAZIONE ISTITUTO ITALIANO DI TECNOLOGIA
Call Details Starting Grant (StG), LS5, ERC-2018-STG
Summary A rapidly expanding approach to understanding neural organization is to map patterns of spontaneous neural activity as an index of functional communication and connectivity across brain regions. Fostered by the advent of neuroimaging methods like resting-state fMRI (rsfMRI), this approach has revealed that functional connectivity is almost invariably disrupted in severe psychiatric disorders, such as autism or schizophrenia. However, the neural basis of such functional disconnectivity remains mysterious. What drives brain-wide functional synchronization? And are there shared pathophysiological mechanisms leading to impaired large-scale neural coupling?
This project aims to elucidate the neural drivers of macroscale functional connectivity, as well as its breakdown in brain connectopathies. To achieve this goal, I propose a multi-scale perturbational approach to establish causal relationships between specific neural events and brain-wide functional connectivity via a novel combination of rsfMRI and advanced neural manipulations and recordings in the awake mouse.
By directionally silencing functional hubs as well as more peripheral cortical regions, I will provide a hierarchical description of spontaneous network organization that will uncover regional substrates vulnerable to network disruption. I will also manipulate physiologically-distinct excitatory or inhibitory populations to probe a unifying mechanistic link between excitatory/inhibitory imbalances and aberrant functional connectivity. Finally, to account for the hallmark co-occurrence of synaptic deficits and functional disconnectivity in developmental disorders, I will link cellular mechanisms of synaptic plasticity and learning to the generation of canonical and aberrant spontaneous activity patterns. These studies will pave the way to a back-translation of aberrant functional connectivity into interpretable neurophysiological events and models that can help understand, diagnose or treat brain disorders.
Summary
A rapidly expanding approach to understanding neural organization is to map patterns of spontaneous neural activity as an index of functional communication and connectivity across brain regions. Fostered by the advent of neuroimaging methods like resting-state fMRI (rsfMRI), this approach has revealed that functional connectivity is almost invariably disrupted in severe psychiatric disorders, such as autism or schizophrenia. However, the neural basis of such functional disconnectivity remains mysterious. What drives brain-wide functional synchronization? And are there shared pathophysiological mechanisms leading to impaired large-scale neural coupling?
This project aims to elucidate the neural drivers of macroscale functional connectivity, as well as its breakdown in brain connectopathies. To achieve this goal, I propose a multi-scale perturbational approach to establish causal relationships between specific neural events and brain-wide functional connectivity via a novel combination of rsfMRI and advanced neural manipulations and recordings in the awake mouse.
By directionally silencing functional hubs as well as more peripheral cortical regions, I will provide a hierarchical description of spontaneous network organization that will uncover regional substrates vulnerable to network disruption. I will also manipulate physiologically-distinct excitatory or inhibitory populations to probe a unifying mechanistic link between excitatory/inhibitory imbalances and aberrant functional connectivity. Finally, to account for the hallmark co-occurrence of synaptic deficits and functional disconnectivity in developmental disorders, I will link cellular mechanisms of synaptic plasticity and learning to the generation of canonical and aberrant spontaneous activity patterns. These studies will pave the way to a back-translation of aberrant functional connectivity into interpretable neurophysiological events and models that can help understand, diagnose or treat brain disorders.
Max ERC Funding
1 498 125 €
Duration
Start date: 2019-02-01, End date: 2024-01-31
