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 ANTSolve
Project A multi-scale perspective into collective problem solving in ants
Researcher (PI) Ofer Feinerman
Host Institution (HI) WEIZMANN INSTITUTE OF SCIENCE
Call Details Consolidator Grant (CoG), LS8, ERC-2017-COG
Summary Cognition improves an animal’s ability to tune its responses to environmental conditions. In group living animals, communication works to form a collective cognition that expands the group’s abilities beyond those of individuals. Despite much research, to date, there is little understanding of how collective cognition emerges within biological ensembles. A major obstacle towards such an understanding is the rarity of comprehensive multi-scale empirical data of these complex systems.
We have demonstrated cooperative load transport by ants to be an ideal system to study the emergence of cognition. Similar to other complex cognitive systems, the ants employ high levels of emergence to achieve efficient problem solving over a large range of scenarios. Unique to this system, is its extreme amenability to experimental measurement and manipulation where internal conflicts map to forces, abstract decision making is reflected in direction changes, and future planning manifested in pheromone trails. This allows for an unprecedentedly detailed, multi-scale empirical description of the moment-to-moment unfolding of sophisticated cognitive processes.
This proposal is aimed at materializing this potential to the full. We will examine the ants’ problem solving capabilities under a variety of environmental challenges. We will expose the underpinning rules on the different organizational scales, the flow of information between them, and their relative contributions to collective performance. This will allow for empirical comparisons between the ‘group’ and the ‘sum of its parts’ from which we will quantify the level of emergence in this system. Using the language of information, we will map the boundaries of this group’s collective cognition and relate them to the range of habitable environmental niches. Moreover, we will generalize these insights to formulate a new paradigm of emergence in biological groups opening new horizons in the study of cognitive processes in general.
Summary
Cognition improves an animal’s ability to tune its responses to environmental conditions. In group living animals, communication works to form a collective cognition that expands the group’s abilities beyond those of individuals. Despite much research, to date, there is little understanding of how collective cognition emerges within biological ensembles. A major obstacle towards such an understanding is the rarity of comprehensive multi-scale empirical data of these complex systems.
We have demonstrated cooperative load transport by ants to be an ideal system to study the emergence of cognition. Similar to other complex cognitive systems, the ants employ high levels of emergence to achieve efficient problem solving over a large range of scenarios. Unique to this system, is its extreme amenability to experimental measurement and manipulation where internal conflicts map to forces, abstract decision making is reflected in direction changes, and future planning manifested in pheromone trails. This allows for an unprecedentedly detailed, multi-scale empirical description of the moment-to-moment unfolding of sophisticated cognitive processes.
This proposal is aimed at materializing this potential to the full. We will examine the ants’ problem solving capabilities under a variety of environmental challenges. We will expose the underpinning rules on the different organizational scales, the flow of information between them, and their relative contributions to collective performance. This will allow for empirical comparisons between the ‘group’ and the ‘sum of its parts’ from which we will quantify the level of emergence in this system. Using the language of information, we will map the boundaries of this group’s collective cognition and relate them to the range of habitable environmental niches. Moreover, we will generalize these insights to formulate a new paradigm of emergence in biological groups opening new horizons in the study of cognitive processes in general.
Max ERC Funding
2 000 000 €
Duration
Start date: 2018-06-01, End date: 2023-05-31
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 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
Project acronym BioMet
Project Selective Functionalization of Saturated Hydrocarbons
Researcher (PI) Ilan MAREK
Host Institution (HI) TECHNION - ISRAEL INSTITUTE OF TECHNOLOGY
Call Details Advanced Grant (AdG), PE5, ERC-2017-ADG
Summary Despite that C–H functionalization represents a paradigm shift from the standard logic of organic synthesis, the selective activation of non-functionalized alkanes has puzzled chemists for centuries and is always referred to one of the remaining major challenges in chemical sciences. Alkanes are inert compounds representing the major constituents of natural gas and petroleum. Converting these cheap and widely available hydrocarbon feedstocks into added-value intermediates would tremendously affect the field of chemistry. For long saturated hydrocarbons, one must distinguish between non-equivalent but chemically very similar alkane substrate C−H bonds, and for functionalization at the terminus position, one must favor activation of the stronger, primary C−H bonds at the expense of weaker and numerous secondary C-H bonds. The goal of this work is to develop a general principle in organic synthesis for the preparation of a wide variety of more complex molecular architectures from saturated hydrocarbons. In our approach, the alkane will first be transformed into an alkene that will subsequently be engaged in a metal-catalyzed hydrometalation/migration sequence. The first step of the sequence, ideally represented by the removal of two hydrogen atoms, will be performed by the use of a mutated strain of Rhodococcus. The position and geometry of the formed double bond has no effect on the second step of the reaction as the metal-catalyzed hydrometalation/migration will isomerize the double bond along the carbon skeleton to selectively produce the primary organometallic species. Trapping the resulting organometallic derivatives with a large variety of electrophiles will provide the desired functionalized alkane. This work will lead to the invention of new, selective and efficient processes for the utilization of simple hydrocarbons and valorize the synthetic potential of raw hydrocarbon feedstock for the environmentally benign production of new compounds and new materials.
Summary
Despite that C–H functionalization represents a paradigm shift from the standard logic of organic synthesis, the selective activation of non-functionalized alkanes has puzzled chemists for centuries and is always referred to one of the remaining major challenges in chemical sciences. Alkanes are inert compounds representing the major constituents of natural gas and petroleum. Converting these cheap and widely available hydrocarbon feedstocks into added-value intermediates would tremendously affect the field of chemistry. For long saturated hydrocarbons, one must distinguish between non-equivalent but chemically very similar alkane substrate C−H bonds, and for functionalization at the terminus position, one must favor activation of the stronger, primary C−H bonds at the expense of weaker and numerous secondary C-H bonds. The goal of this work is to develop a general principle in organic synthesis for the preparation of a wide variety of more complex molecular architectures from saturated hydrocarbons. In our approach, the alkane will first be transformed into an alkene that will subsequently be engaged in a metal-catalyzed hydrometalation/migration sequence. The first step of the sequence, ideally represented by the removal of two hydrogen atoms, will be performed by the use of a mutated strain of Rhodococcus. The position and geometry of the formed double bond has no effect on the second step of the reaction as the metal-catalyzed hydrometalation/migration will isomerize the double bond along the carbon skeleton to selectively produce the primary organometallic species. Trapping the resulting organometallic derivatives with a large variety of electrophiles will provide the desired functionalized alkane. This work will lead to the invention of new, selective and efficient processes for the utilization of simple hydrocarbons and valorize the synthetic potential of raw hydrocarbon feedstock for the environmentally benign production of new compounds and new materials.
Max ERC Funding
2 499 375 €
Duration
Start date: 2018-11-01, End date: 2023-10-31
Project acronym Ca2Coral
Project Elucidating the molecular and biophysical mechanism of coral calcification in view of the future acidified ocean
Researcher (PI) Tali Mass
Host Institution (HI) UNIVERSITY OF HAIFA
Call Details Starting Grant (StG), LS8, ERC-2017-STG
Summary Although various aspects of biomineralisation in corals have been studied for decades, the basic mechanism of precipitation of the aragonite skeleton remains enigmatic. Two parallel lines of inquiry have emerged: geochemist models of calcification that are directly related to seawater carbonate chemistry at thermodynamic equilibrium. Here, the role of the organisms in the precipitation reaction is largely ignored. The second line is based on biological considerations of the biomineralisation process, which focuses on models of biophysical processes far from thermodynamic equilibrium that concentrate calcium ions, anions and proteins responsible for nucleation in specific compartments. Recently, I identified and cloned a group of highly acidic proteins derived the common stony coral, Stylophora pistillata. All of the cloned proteins precipitate aragonite in seawater at pH 8.2 and 7.6 in-vitro. However, it is not at all clear if the expression of these proteins in-vivo is sufficient for the formation of an aragonite skeleton at seawater pH values below ~7.8. Here using a combination of molecular, biophysical, genomic, and cell biological approaches, we proposed to test the core hypothesis that, unless wounded or otherwise having skeletal material exposed directly to seawater, stony zooxanthellate corals will continue to calcify at pH values projected for the CO2 emissions scenarios for 2100.
Specifically, the objectives of Ca2Coral are to:
1) Use functional genomics to identify the key genes and proteins involved both in the organic matrix and skeleton formation in the adult holobiont and during its larval development.
2) Use a genetics approach to elucidate the roles of specific proteins in the biomineralisation process.
3) Use ultra-high resolution imaging and spectroscopic analysis at different pH levels to elucidate the biomineralisation pathways and mineral precursor in corals in the adult holobiont and during its larval development.
Summary
Although various aspects of biomineralisation in corals have been studied for decades, the basic mechanism of precipitation of the aragonite skeleton remains enigmatic. Two parallel lines of inquiry have emerged: geochemist models of calcification that are directly related to seawater carbonate chemistry at thermodynamic equilibrium. Here, the role of the organisms in the precipitation reaction is largely ignored. The second line is based on biological considerations of the biomineralisation process, which focuses on models of biophysical processes far from thermodynamic equilibrium that concentrate calcium ions, anions and proteins responsible for nucleation in specific compartments. Recently, I identified and cloned a group of highly acidic proteins derived the common stony coral, Stylophora pistillata. All of the cloned proteins precipitate aragonite in seawater at pH 8.2 and 7.6 in-vitro. However, it is not at all clear if the expression of these proteins in-vivo is sufficient for the formation of an aragonite skeleton at seawater pH values below ~7.8. Here using a combination of molecular, biophysical, genomic, and cell biological approaches, we proposed to test the core hypothesis that, unless wounded or otherwise having skeletal material exposed directly to seawater, stony zooxanthellate corals will continue to calcify at pH values projected for the CO2 emissions scenarios for 2100.
Specifically, the objectives of Ca2Coral are to:
1) Use functional genomics to identify the key genes and proteins involved both in the organic matrix and skeleton formation in the adult holobiont and during its larval development.
2) Use a genetics approach to elucidate the roles of specific proteins in the biomineralisation process.
3) Use ultra-high resolution imaging and spectroscopic analysis at different pH levels to elucidate the biomineralisation pathways and mineral precursor in corals in the adult holobiont and during its larval development.
Max ERC Funding
1 499 741 €
Duration
Start date: 2018-01-01, End date: 2022-12-31
Project acronym CANCER-DC
Project Dissecting Regulatory Networks That Mediate Dendritic Cell Suppression
Researcher (PI) Oren PARNAS
Host Institution (HI) THE HEBREW UNIVERSITY OF JERUSALEM
Call Details Starting Grant (StG), LS6, ERC-2017-STG
Summary Recent advances have shown that therapeutic manipulations of key cell-cell interactions can have dramatic clinical outcomes. Most notable are several early successes in cancer immunotherapy that target the tumor-T cell interface. However, these successes were only partial. This is likely because the few known interactions are just a few pieces of a much larger puzzle, involving additional signaling molecules and cell types. Dendritic cells (DCs), play critical roles in the induction/suppression of T cells. At early cancer stages, DCs capture tumor antigens and present them to T cells. However, in advanced cancers, the tumor microenvironment (TME) disrupts the crosstalk between DCs and T cells.
We will take a multi-step approach to explore how the TME imposes a suppressive effect on DCs and how to reverse this hazardous effect. First, we will use single cell RNA-seq to search for genes in aggressive human and mouse ovarian tumors that are highly expressed in advanced tumors compared to early tumors and that encode molecules that suppress DC activity. Second, we will design a set of CRISPR screens to find genes that are expressed in DCs and regulate the transfer of the suppressive signals. The screens will be performed in the presence of suppressive molecules to mimic the TME and are expected to uncover many key genes in DCs biology. We will develop a new strategy to find synergistic combinations of genes to target (named Perturb-comb), thereby reversing the effect of local tumor immunosuppressive signals. Lastly, we will examine the effect of modified DCs on T cell activation and proliferation in-vivo, and on tumor growth.
We expect to find: (1) Signaling molecules in the TME that affect the immune system. (2) New cytokines and cell surface receptors that are expressed in DCs and signal to T cells. (3) New key regulators in DC biology and their mechanisms. (4) Combinations of genes to target in DCs that reverse the TME’s hazardous effects.
Summary
Recent advances have shown that therapeutic manipulations of key cell-cell interactions can have dramatic clinical outcomes. Most notable are several early successes in cancer immunotherapy that target the tumor-T cell interface. However, these successes were only partial. This is likely because the few known interactions are just a few pieces of a much larger puzzle, involving additional signaling molecules and cell types. Dendritic cells (DCs), play critical roles in the induction/suppression of T cells. At early cancer stages, DCs capture tumor antigens and present them to T cells. However, in advanced cancers, the tumor microenvironment (TME) disrupts the crosstalk between DCs and T cells.
We will take a multi-step approach to explore how the TME imposes a suppressive effect on DCs and how to reverse this hazardous effect. First, we will use single cell RNA-seq to search for genes in aggressive human and mouse ovarian tumors that are highly expressed in advanced tumors compared to early tumors and that encode molecules that suppress DC activity. Second, we will design a set of CRISPR screens to find genes that are expressed in DCs and regulate the transfer of the suppressive signals. The screens will be performed in the presence of suppressive molecules to mimic the TME and are expected to uncover many key genes in DCs biology. We will develop a new strategy to find synergistic combinations of genes to target (named Perturb-comb), thereby reversing the effect of local tumor immunosuppressive signals. Lastly, we will examine the effect of modified DCs on T cell activation and proliferation in-vivo, and on tumor growth.
We expect to find: (1) Signaling molecules in the TME that affect the immune system. (2) New cytokines and cell surface receptors that are expressed in DCs and signal to T cells. (3) New key regulators in DC biology and their mechanisms. (4) Combinations of genes to target in DCs that reverse the TME’s hazardous effects.
Max ERC Funding
1 500 000 €
Duration
Start date: 2018-01-01, End date: 2022-12-31
