Project acronym ANTHROPOID
Project Great ape organoids to reconstruct uniquely human development
Researcher (PI) Jarrett CAMP
Host Institution (HI) INSTITUT FUR MOLEKULARE UND KLINISCHE OPHTHALMOLOGIE BASEL
Call Details Starting Grant (StG), LS2, ERC-2018-STG
Summary Humans diverged from our closest living relatives, chimpanzees and other great apes, 6-10 million years ago. Since this divergence, our ancestors acquired genetic changes that enhanced cognition, altered metabolism, and endowed our species with an adaptive capacity to colonize the entire planet and reshape the biosphere. Through genome comparisons between modern humans, Neandertals, chimpanzees and other apes we have identified genetic changes that likely contribute to innovations in human metabolic and cognitive physiology. However, it has been difficult to assess the functional effects of these genetic changes due to the lack of cell culture systems that recapitulate great ape organ complexity. Human and chimpanzee pluripotent stem cells (PSCs) can self-organize into three-dimensional (3D) tissues that recapitulate the morphology, function, and genetic programs controlling organ development. Our vision is to use organoids to study the changes that set modern humans apart from our closest evolutionary relatives as well as all other organisms on the planet. In ANTHROPOID we will generate a great ape developmental cell atlas using cortex, liver, and small intestine organoids. We will use single-cell transcriptomics and chromatin accessibility to identify cell type-specific features of transcriptome divergence at cellular resolution. We will dissect enhancer evolution using single-cell genomic screens and ancestralize human cells to resurrect pre-human cellular phenotypes. ANTHROPOID utilizes quantitative and state-of-the-art methods to explore exciting high-risk questions at multiple branches of the modern human lineage. This project is a ground breaking starting point to replay evolution and tackle the ancient question of what makes us uniquely human?
Summary
Humans diverged from our closest living relatives, chimpanzees and other great apes, 6-10 million years ago. Since this divergence, our ancestors acquired genetic changes that enhanced cognition, altered metabolism, and endowed our species with an adaptive capacity to colonize the entire planet and reshape the biosphere. Through genome comparisons between modern humans, Neandertals, chimpanzees and other apes we have identified genetic changes that likely contribute to innovations in human metabolic and cognitive physiology. However, it has been difficult to assess the functional effects of these genetic changes due to the lack of cell culture systems that recapitulate great ape organ complexity. Human and chimpanzee pluripotent stem cells (PSCs) can self-organize into three-dimensional (3D) tissues that recapitulate the morphology, function, and genetic programs controlling organ development. Our vision is to use organoids to study the changes that set modern humans apart from our closest evolutionary relatives as well as all other organisms on the planet. In ANTHROPOID we will generate a great ape developmental cell atlas using cortex, liver, and small intestine organoids. We will use single-cell transcriptomics and chromatin accessibility to identify cell type-specific features of transcriptome divergence at cellular resolution. We will dissect enhancer evolution using single-cell genomic screens and ancestralize human cells to resurrect pre-human cellular phenotypes. ANTHROPOID utilizes quantitative and state-of-the-art methods to explore exciting high-risk questions at multiple branches of the modern human lineage. This project is a ground breaking starting point to replay evolution and tackle the ancient question of what makes us uniquely human?
Max ERC Funding
1 500 000 €
Duration
Start date: 2019-06-01, End date: 2024-05-31
Project acronym ARBODYNAMIC
Project Coupling dynamic population immunity profiles and host behaviours to arboviral spread
Researcher (PI) Henrik SALJE
Host Institution (HI) INSTITUT PASTEUR
Call Details Starting Grant (StG), LS8, ERC-2018-STG
Summary Arboviruses infect millions of people each year, however, mechanisms that drive viral emergence and maintenance remain largely unknown. A combination of host factors (e.g., human mobility), mosquito factors (e.g., abundance) and viral factors (e.g., transmissibility) interconnect to drive spread. Further, for endemic arboviruses, complex patterns of population immunity, built up over many years, appear key to the emergence of particular lineages. To disentangle the contribution of these different drivers, we need detailed data from the same pathogen system over a long time period from the same location. In addition, we need new methods, which can integrate these different data sources and allow appropriate mechanistic inferences.
In this project, I will use the most globally prevalent arbovirus, dengue virus, as a case study. I will focus on Thailand where all four dengue serotypes have circulated endemically for decades and excellent long-term data and isolates exist, to address two fundamental questions:
i) How do population-level patterns of immunity evolve over time and what is their impact on strain dynamics? I will use mechanistic models applied to historic serotype-specific case data to reconstruct the evolving immune profile of the population and explore the impact of immunity on viral diversity using sequences from archived isolates from each year over a 50-year period.
ii) How do human behaviors, vector densities interact with immunity to dictate spread? I will work with geolocated full genome sequences from across Thailand and use detailed data on how people move, their contact patterns, their immunity profiles and mosquito distributions to study competing hypotheses of how arboviruses spread. I will compare the key drivers of dengue spread with that found for outbreaks of Zika and chikungunya.
This proposal addresses fundamental questions about the mechanisms that drive arboviral emergence and spread that will be relevant across disease systems.
Summary
Arboviruses infect millions of people each year, however, mechanisms that drive viral emergence and maintenance remain largely unknown. A combination of host factors (e.g., human mobility), mosquito factors (e.g., abundance) and viral factors (e.g., transmissibility) interconnect to drive spread. Further, for endemic arboviruses, complex patterns of population immunity, built up over many years, appear key to the emergence of particular lineages. To disentangle the contribution of these different drivers, we need detailed data from the same pathogen system over a long time period from the same location. In addition, we need new methods, which can integrate these different data sources and allow appropriate mechanistic inferences.
In this project, I will use the most globally prevalent arbovirus, dengue virus, as a case study. I will focus on Thailand where all four dengue serotypes have circulated endemically for decades and excellent long-term data and isolates exist, to address two fundamental questions:
i) How do population-level patterns of immunity evolve over time and what is their impact on strain dynamics? I will use mechanistic models applied to historic serotype-specific case data to reconstruct the evolving immune profile of the population and explore the impact of immunity on viral diversity using sequences from archived isolates from each year over a 50-year period.
ii) How do human behaviors, vector densities interact with immunity to dictate spread? I will work with geolocated full genome sequences from across Thailand and use detailed data on how people move, their contact patterns, their immunity profiles and mosquito distributions to study competing hypotheses of how arboviruses spread. I will compare the key drivers of dengue spread with that found for outbreaks of Zika and chikungunya.
This proposal addresses fundamental questions about the mechanisms that drive arboviral emergence and spread that will be relevant across disease systems.
Max ERC Funding
1 499 896 €
Duration
Start date: 2019-01-01, End date: 2023-12-31
Project acronym BactRNA
Project Bacterial small RNAs networks unravelling novel features of transcription and translation
Researcher (PI) Maude Audrey Guillier
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Call Details Consolidator Grant (CoG), LS2, ERC-2018-COG
Summary Regulation of gene expression plays a key role in the ability of bacteria to rapidly adapt to changing environments and to colonize extremely diverse habitats. The relatively recent discovery of a plethora of small regulatory RNAs and the beginning of their characterization has unravelled new aspects of bacterial gene expression. First, the expression of many bacterial genes responds to a complex network of both transcriptional and post-transcriptional regulators. However, the properties of the resulting regulatory circuits on the dynamics of gene expression and in the bacterial adaptive response have been poorly addressed so far. In a first part of this project, we will tackle this question by characterizing the circuits that are formed between two widespread classes of bacterial regulators, the sRNAs and the two-component systems, which act at the post-transcriptional and the transcriptional level, respectively. The study of sRNAs also led to major breakthroughs regarding the basic mechanisms of gene expression. In particular, we recently showed that repressor sRNAs can target activating stem-loop structures located within the coding region of mRNAs that promote translation initiation, in striking contrast with the previously recognized inhibitory role of mRNA structures in translation. The second objective of this project is thus to draw an unprecedented map of non-canonical translation initiation events and their regulation by sRNAs.
Overall, this project will greatly improve our understanding of how bacteria can so rapidly and successfully adapt to many different environments, and in the long term, provide clues towards the development of anti-bacterial strategies.
Summary
Regulation of gene expression plays a key role in the ability of bacteria to rapidly adapt to changing environments and to colonize extremely diverse habitats. The relatively recent discovery of a plethora of small regulatory RNAs and the beginning of their characterization has unravelled new aspects of bacterial gene expression. First, the expression of many bacterial genes responds to a complex network of both transcriptional and post-transcriptional regulators. However, the properties of the resulting regulatory circuits on the dynamics of gene expression and in the bacterial adaptive response have been poorly addressed so far. In a first part of this project, we will tackle this question by characterizing the circuits that are formed between two widespread classes of bacterial regulators, the sRNAs and the two-component systems, which act at the post-transcriptional and the transcriptional level, respectively. The study of sRNAs also led to major breakthroughs regarding the basic mechanisms of gene expression. In particular, we recently showed that repressor sRNAs can target activating stem-loop structures located within the coding region of mRNAs that promote translation initiation, in striking contrast with the previously recognized inhibitory role of mRNA structures in translation. The second objective of this project is thus to draw an unprecedented map of non-canonical translation initiation events and their regulation by sRNAs.
Overall, this project will greatly improve our understanding of how bacteria can so rapidly and successfully adapt to many different environments, and in the long term, provide clues towards the development of anti-bacterial strategies.
Max ERC Funding
1 999 754 €
Duration
Start date: 2019-09-01, End date: 2024-08-31
Project acronym BrainConquest
Project Boosting Brain-Computer Communication with high Quality User Training
Researcher (PI) Fabien LOTTE
Host Institution (HI) INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE
Call Details Starting Grant (StG), PE7, ERC-2016-STG
Summary Brain-Computer Interfaces (BCIs) are communication systems that enable users to send commands to computers through brain signals only, by measuring and processing these signals. Making computer control possible without any physical activity, BCIs have promised to revolutionize many application areas, notably assistive technologies, e.g., for wheelchair control, and human-machine interaction. Despite this promising potential, BCIs are still barely used outside laboratories, due to their current poor reliability. For instance, BCIs only using two imagined hand movements as mental commands decode, on average, less than 80% of these commands correctly, while 10 to 30% of users cannot control a BCI at all.
A BCI should be considered a co-adaptive communication system: its users learn to encode commands in their brain signals (with mental imagery) that the machine learns to decode using signal processing. Most research efforts so far have been dedicated to decoding the commands. However, BCI control is a skill that users have to learn too. Unfortunately how BCI users learn to encode the commands is essential but is barely studied, i.e., fundamental knowledge about how users learn BCI control is lacking. Moreover standard training approaches are only based on heuristics, without satisfying human learning principles. Thus, poor BCI reliability is probably largely due to highly suboptimal user training.
In order to obtain a truly reliable BCI we need to completely redefine user training approaches. To do so, I propose to study and statistically model how users learn to encode BCI commands. Then, based on human learning principles and this model, I propose to create a new generation of BCIs which ensure that users learn how to successfully encode commands with high signal-to-noise ratio in their brain signals, hence making BCIs dramatically more reliable. Such a reliable BCI could positively change human-machine interaction as BCIs have promised but failed to do so far.
Summary
Brain-Computer Interfaces (BCIs) are communication systems that enable users to send commands to computers through brain signals only, by measuring and processing these signals. Making computer control possible without any physical activity, BCIs have promised to revolutionize many application areas, notably assistive technologies, e.g., for wheelchair control, and human-machine interaction. Despite this promising potential, BCIs are still barely used outside laboratories, due to their current poor reliability. For instance, BCIs only using two imagined hand movements as mental commands decode, on average, less than 80% of these commands correctly, while 10 to 30% of users cannot control a BCI at all.
A BCI should be considered a co-adaptive communication system: its users learn to encode commands in their brain signals (with mental imagery) that the machine learns to decode using signal processing. Most research efforts so far have been dedicated to decoding the commands. However, BCI control is a skill that users have to learn too. Unfortunately how BCI users learn to encode the commands is essential but is barely studied, i.e., fundamental knowledge about how users learn BCI control is lacking. Moreover standard training approaches are only based on heuristics, without satisfying human learning principles. Thus, poor BCI reliability is probably largely due to highly suboptimal user training.
In order to obtain a truly reliable BCI we need to completely redefine user training approaches. To do so, I propose to study and statistically model how users learn to encode BCI commands. Then, based on human learning principles and this model, I propose to create a new generation of BCIs which ensure that users learn how to successfully encode commands with high signal-to-noise ratio in their brain signals, hence making BCIs dramatically more reliable. Such a reliable BCI could positively change human-machine interaction as BCIs have promised but failed to do so far.
Max ERC Funding
1 498 751 €
Duration
Start date: 2017-07-01, End date: 2022-06-30
Project acronym CHIC
Project On CHip terahertz frequency Combs
Researcher (PI) Giacomo Scalari
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Consolidator Grant (CoG), PE7, ERC-2016-COG
Summary The terahertz (THz) portion of the electromagnetic spectrum is the junction between optics and electronics. THz is a gate to sensing applications and spectroscopy as well as appealing for material inspection, non-invasive imaging for safety and medical applications and short-range high data rate wireless communication which are being extended to higher frequencies entering the THz range. Optical frequency combs have dominated the scene of laser physics in the last 10 years revolutionizing many fields of optics from metrology to high precision spectroscopy. Optical frequency combs act as rulers in the frequency domain and are characterized by their perfectly equally spaced and coherent modes. An extremely appealing application of optical frequency combs is the so-called dual-comb spectroscopy where multi-heterodyne detection is performed allowing Fourier transform spectroscopy with high resolution, high sensitivity and no moving parts.
The objective of this proposal is to create on-chip, self-referenced frequency combs operating in the spectral region from 1.5-5-5 THz. Two main approaches will be followed: direct generation with THz QC lasers (cryogenically cooled) and room temperature non-linear generation by means of Mid-IR QCL combs. Such devices will be groundbreaking since they will allow high resolution THz spectroscopy and they will pave the way to high-rate local data transmission and coherent communication. We recently demonstrated octave spanning lasing from a THz QCL: this will constitute the foundation of our efforts. The developed combs will be implemented in the extremely powerful dual-comb scheme with innovative on-chip self-stabilization and detection of the multi-heterodyne signals. The self-referencing and the independence from an external detector makes the proposed devices disruptive due to their extreme compactness, intrinsic stability and large bandwidth.
Summary
The terahertz (THz) portion of the electromagnetic spectrum is the junction between optics and electronics. THz is a gate to sensing applications and spectroscopy as well as appealing for material inspection, non-invasive imaging for safety and medical applications and short-range high data rate wireless communication which are being extended to higher frequencies entering the THz range. Optical frequency combs have dominated the scene of laser physics in the last 10 years revolutionizing many fields of optics from metrology to high precision spectroscopy. Optical frequency combs act as rulers in the frequency domain and are characterized by their perfectly equally spaced and coherent modes. An extremely appealing application of optical frequency combs is the so-called dual-comb spectroscopy where multi-heterodyne detection is performed allowing Fourier transform spectroscopy with high resolution, high sensitivity and no moving parts.
The objective of this proposal is to create on-chip, self-referenced frequency combs operating in the spectral region from 1.5-5-5 THz. Two main approaches will be followed: direct generation with THz QC lasers (cryogenically cooled) and room temperature non-linear generation by means of Mid-IR QCL combs. Such devices will be groundbreaking since they will allow high resolution THz spectroscopy and they will pave the way to high-rate local data transmission and coherent communication. We recently demonstrated octave spanning lasing from a THz QCL: this will constitute the foundation of our efforts. The developed combs will be implemented in the extremely powerful dual-comb scheme with innovative on-chip self-stabilization and detection of the multi-heterodyne signals. The self-referencing and the independence from an external detector makes the proposed devices disruptive due to their extreme compactness, intrinsic stability and large bandwidth.
Max ERC Funding
1 999 055 €
Duration
Start date: 2017-03-01, End date: 2022-02-28
Project acronym ChloroMito
Project Chloroplast and Mitochondria interactions for microalgal acclimation
Researcher (PI) Giovanni Finazzi
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Call Details Advanced Grant (AdG), LS8, ERC-2018-ADG
Summary Photosynthesis emerged as an energy-harvesting process at least 3.5 billion years ago, first in anoxygenic bacteria and then in oxygen-producing organisms, which led to the evolution of complex life forms with oxygen-based metabolisms (e.g. humans). Oxygenic photosynthesis produces ATP and NADPH, and the correct balance between these energy-rich molecules allows assimilation of CO2 into organic matter. Although the mechanisms of ATP/NADPH synthesis are well understood, less is known about how CO2 assimilation was optimised. This process was essential to the successful phototrophic colonisation of land (by Plantae) and the oceans (by phytoplankton). Plants optimised CO2 assimilation using chloroplast-localised ATP-generating processes to control the ATP/NADPH ratio, but the strategies developed by phytoplankton are poorly understood. However, diatoms—ecologically successful ocean organisms—are known to control this ratio by exchanging energy between plastids and mitochondria. Is this mechanism a paradigm for optimisation of photosynthesis in the ocean? The ChloroMito project aims to first decipher the mechanism(s) behind plastid-mitochondria interactions. Thanks to a novel combination of whole-cell approaches, including (opto)genetics, cellular tomography and single-cell spectroscopy, we will identify the nature of the exchanges occurring in diatoms and assess their contribution to dynamic responses to environmental stimuli (light, temperature, nutrients). We will then assess conservation of this mechanism in ecologically relevant phytoplankton taxa, test its role in supporting different lifestyles (autotrophy, mixotrophy, photosymbiosis) encountered in the ocean, and track transitions between these different lifestyles as part of an unprecedented effort to visualise ocean dynamics. Overall, the ChloroMito project will alter our understanding of ocean photosynthesis, challenging textbook concepts which are often inferred from plant-based concepts
Summary
Photosynthesis emerged as an energy-harvesting process at least 3.5 billion years ago, first in anoxygenic bacteria and then in oxygen-producing organisms, which led to the evolution of complex life forms with oxygen-based metabolisms (e.g. humans). Oxygenic photosynthesis produces ATP and NADPH, and the correct balance between these energy-rich molecules allows assimilation of CO2 into organic matter. Although the mechanisms of ATP/NADPH synthesis are well understood, less is known about how CO2 assimilation was optimised. This process was essential to the successful phototrophic colonisation of land (by Plantae) and the oceans (by phytoplankton). Plants optimised CO2 assimilation using chloroplast-localised ATP-generating processes to control the ATP/NADPH ratio, but the strategies developed by phytoplankton are poorly understood. However, diatoms—ecologically successful ocean organisms—are known to control this ratio by exchanging energy between plastids and mitochondria. Is this mechanism a paradigm for optimisation of photosynthesis in the ocean? The ChloroMito project aims to first decipher the mechanism(s) behind plastid-mitochondria interactions. Thanks to a novel combination of whole-cell approaches, including (opto)genetics, cellular tomography and single-cell spectroscopy, we will identify the nature of the exchanges occurring in diatoms and assess their contribution to dynamic responses to environmental stimuli (light, temperature, nutrients). We will then assess conservation of this mechanism in ecologically relevant phytoplankton taxa, test its role in supporting different lifestyles (autotrophy, mixotrophy, photosymbiosis) encountered in the ocean, and track transitions between these different lifestyles as part of an unprecedented effort to visualise ocean dynamics. Overall, the ChloroMito project will alter our understanding of ocean photosynthesis, challenging textbook concepts which are often inferred from plant-based concepts
Max ERC Funding
2 498 207 €
Duration
Start date: 2020-01-01, End date: 2024-12-31
Project acronym COMNFT
Project Communication Using the Nonlinear Fourier Transform
Researcher (PI) Mansoor ISVAND YOUSEFI
Host Institution (HI) INSTITUT MINES-TELECOM
Call Details Starting Grant (StG), PE7, ERC-2018-STG
Summary High-speed optical fiber networks form the backbone of the information and communication technologies, including the Internet. More than 99% of the Internet data traffic is carried by a network of global optical fibers. Despite their great importance, today's optical fiber networks face a looming capacity crunch: The achievable rates of all current technologies characteristically vanish at high input powers due to distortions that arise from fiber nonlinearity. The solution of this long-standing complex problem has become the holy grail of the field of the optical communication.
The aim of this project is to develop a novel foundation for optical fiber communication based on the nonlinear Fourier transform (NFT). The NFT decorrelates signal degrees-of-freedom in optical fiber, in much the same way that the conventional Fourier transform does for linear systems. My collaborators and I have recently proposed nonlinear frequency-division multiplexing (NFDM) based on the NFT, in which the information is encoded in the generalized frequencies and their spectral amplitudes (similar to orthogonal frequency-division multiplexing). Since distortions such as inter-symbol and inter-channel interference are absent in NFDM, it achieves data rates higher than conventional methods. The objective of this proposal is to advance NFDM to the extent that it can be built in practical large-scale systems, thereby overcoming the limitation that fiber nonlinearity sets on the transmission rate of the communication networks. The proposed research relies on novel methodology and spans all aspects of the NFDM system design, including determining the fundamental information-theoretic limits, design of the NFDM transmitter and receiver, algorithms and implementations.
The feasibility of the project is manifest in preliminary proof-of-concepts in small examples and toy models, PI's leadership and track-record in the field, as well as the ideal research environment.
Summary
High-speed optical fiber networks form the backbone of the information and communication technologies, including the Internet. More than 99% of the Internet data traffic is carried by a network of global optical fibers. Despite their great importance, today's optical fiber networks face a looming capacity crunch: The achievable rates of all current technologies characteristically vanish at high input powers due to distortions that arise from fiber nonlinearity. The solution of this long-standing complex problem has become the holy grail of the field of the optical communication.
The aim of this project is to develop a novel foundation for optical fiber communication based on the nonlinear Fourier transform (NFT). The NFT decorrelates signal degrees-of-freedom in optical fiber, in much the same way that the conventional Fourier transform does for linear systems. My collaborators and I have recently proposed nonlinear frequency-division multiplexing (NFDM) based on the NFT, in which the information is encoded in the generalized frequencies and their spectral amplitudes (similar to orthogonal frequency-division multiplexing). Since distortions such as inter-symbol and inter-channel interference are absent in NFDM, it achieves data rates higher than conventional methods. The objective of this proposal is to advance NFDM to the extent that it can be built in practical large-scale systems, thereby overcoming the limitation that fiber nonlinearity sets on the transmission rate of the communication networks. The proposed research relies on novel methodology and spans all aspects of the NFDM system design, including determining the fundamental information-theoretic limits, design of the NFDM transmitter and receiver, algorithms and implementations.
The feasibility of the project is manifest in preliminary proof-of-concepts in small examples and toy models, PI's leadership and track-record in the field, as well as the ideal research environment.
Max ERC Funding
1 499 180 €
Duration
Start date: 2019-05-01, End date: 2024-04-30
Project acronym CONNEXIO
Project Physiologically relevant microfluidic neuro-engineering
Researcher (PI) Thibault Frédéric Johan HONEGGER
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Call Details Starting Grant (StG), PE7, ERC-2016-STG
Summary Developing minimalistic biological neural networks and observing their functional activity is crucial to decipher the information processing in the brain. This project aims to address two major challenges: to design and fabricate in vitro biological neural networks that are organized in physiological relevant ways and to provide a label-free monitoring platform capable of observing neural activity both at the neuron resolution and at large fields of view. To do so, the project will develop a unique microfluidic compartmentalized chips where populations of primary neurons will be seeded in deposition chambers with physiological relevant number and densities. Chambers will be connected by microgrooves in which neurites only can grow and whose dimensions will be tuned according to the connectivity pattern to reproduce. To observe the activity of such complex neural networks, we will develop a disruptive observation technique that will transduce the electrical activity of spiking neurons into optical differences observed on a lens-free platform, without calcium labelling and constantly in-incubo. By combining neuro-engineering patterning and the lens-free platform, we will compare individual spiking to global oscillators in basic neural networks under localized external stimulations. Such results will provide experimental insight into computational neuroscience current approaches. Finally, we will design an in vitro network that will reproduce a neural loop implied in major neurodegenerative diseases with physiological relevant neural types, densities and connectivities. This circuitry will be manipulated in order to model Huntington and Parkinson diseases on the chip and assess the impact of known drugs on the functional activity of the entire network. This project will engineer microfluidics chips with physiological relevant neural network and a lensfree activity monitoring platform to answer fundamental and clinically relevant issues in neuroscience.
Summary
Developing minimalistic biological neural networks and observing their functional activity is crucial to decipher the information processing in the brain. This project aims to address two major challenges: to design and fabricate in vitro biological neural networks that are organized in physiological relevant ways and to provide a label-free monitoring platform capable of observing neural activity both at the neuron resolution and at large fields of view. To do so, the project will develop a unique microfluidic compartmentalized chips where populations of primary neurons will be seeded in deposition chambers with physiological relevant number and densities. Chambers will be connected by microgrooves in which neurites only can grow and whose dimensions will be tuned according to the connectivity pattern to reproduce. To observe the activity of such complex neural networks, we will develop a disruptive observation technique that will transduce the electrical activity of spiking neurons into optical differences observed on a lens-free platform, without calcium labelling and constantly in-incubo. By combining neuro-engineering patterning and the lens-free platform, we will compare individual spiking to global oscillators in basic neural networks under localized external stimulations. Such results will provide experimental insight into computational neuroscience current approaches. Finally, we will design an in vitro network that will reproduce a neural loop implied in major neurodegenerative diseases with physiological relevant neural types, densities and connectivities. This circuitry will be manipulated in order to model Huntington and Parkinson diseases on the chip and assess the impact of known drugs on the functional activity of the entire network. This project will engineer microfluidics chips with physiological relevant neural network and a lensfree activity monitoring platform to answer fundamental and clinically relevant issues in neuroscience.
Max ERC Funding
1 727 731 €
Duration
Start date: 2016-11-01, End date: 2021-10-31
Project acronym CTO Com
Project Context- and Task-Oriented Communication
Researcher (PI) Michèle WIGGER
Host Institution (HI) INSTITUT MINES-TELECOM
Call Details Starting Grant (StG), PE7, ERC-2016-STG
Summary Emergence of a large number of distributed decision and control systems (e.g., in health care, transportation, and energy management), combined with increasing demands of traditional communications (e.g., due to multiview videos), create an imminent need for highly improved communication systems. We advocate that—combined with improvements in battery, antenna, and chip technologies—context- and/or task-oriented communication techniques will bring the desired breakthrough. Specifically, context- oriented techniques will greatly improve performance, because future networks have complex infrastructures (with cache-memories, cloud-RANs, etc.) allowing the terminals to collect side-informations about other terminals’ data or signals, and because many distributed decision systems rely on numerous devices with correlated measurements. Task-oriented techniques promise even larger gains, especially in distributed decision systems where decisions take value on a small range, and thus the traditional approach of communicating sequences of observed signals results in a huge overhead.
Information theory, and in particular distributed joint source-channel coding, provides a general framework for designing context-oriented communication techniques. Such a general framework is missing for task-oriented communication. Previous results indicate that creative usages of information theory on its frontier to statistics and decision theory are well-suited for designing task-oriented communication techniques for applications as diverse as coordination of smart devices, distributed hypothesis testing, and clustering of data.
Our goal is to design context- and/or task-oriented communication techniques for these three applications and for cache-aided communication. Besides the high gains that our new techniques bring directly to these applications, the complementarity of our applications and obtained results will facilitate a future general framework for context- and task-oriented communication.
Summary
Emergence of a large number of distributed decision and control systems (e.g., in health care, transportation, and energy management), combined with increasing demands of traditional communications (e.g., due to multiview videos), create an imminent need for highly improved communication systems. We advocate that—combined with improvements in battery, antenna, and chip technologies—context- and/or task-oriented communication techniques will bring the desired breakthrough. Specifically, context- oriented techniques will greatly improve performance, because future networks have complex infrastructures (with cache-memories, cloud-RANs, etc.) allowing the terminals to collect side-informations about other terminals’ data or signals, and because many distributed decision systems rely on numerous devices with correlated measurements. Task-oriented techniques promise even larger gains, especially in distributed decision systems where decisions take value on a small range, and thus the traditional approach of communicating sequences of observed signals results in a huge overhead.
Information theory, and in particular distributed joint source-channel coding, provides a general framework for designing context-oriented communication techniques. Such a general framework is missing for task-oriented communication. Previous results indicate that creative usages of information theory on its frontier to statistics and decision theory are well-suited for designing task-oriented communication techniques for applications as diverse as coordination of smart devices, distributed hypothesis testing, and clustering of data.
Our goal is to design context- and/or task-oriented communication techniques for these three applications and for cache-aided communication. Besides the high gains that our new techniques bring directly to these applications, the complementarity of our applications and obtained results will facilitate a future general framework for context- and task-oriented communication.
Max ERC Funding
1 495 288 €
Duration
Start date: 2017-05-01, End date: 2022-04-30
Project acronym CyberGenetics
Project Cybergenetics: Theory and Design Tools for Biomolecular Control Systems
Researcher (PI) Mustafa KHAMMASH
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Advanced Grant (AdG), PE7, ERC-2016-ADG
Summary We propose to develop a new theory and design tools for the estimation and real-time control of living cells. The control systems designed using these tools will precisely and robustly steer the dynamic behavior of living cells in real time to achieve desired objectives. Cells would be controlled either collectively at the population level, or individually as single cells. The control systems achieving this regulation will be realized either on a digital computer that is interfaced with living cells, or using de novo genetic circuits that are introduced into the cells where they are designed to function as molecular control systems. Our methods will explicitly confront the numerous challenges brought about by the special environment of the cell including nonlinearity, stochasticity, cell-to-cell variability, metabolic burden, etc. The theory and methods developed in this project will thus enable the systematic, rational, and effective feedback control of living cells at the gene level, and will lay the foundation for a new corresponding body of knowledge which we call ``Cybergenetics''. It will also open new research directions in the areas of control theory and estimation.
We also propose to design three cybergenetic control systems, each addressing an important application in biotechnology or therapeutics. In the first, the controller will use light and nutrient supply to precisely regulate gene expression and cell growth in E. coli to achieve high protein and low biomass production rates. The second involves multiple feedback controllers regulating in parallel a large number of single stem cells, and leading to their differentiation to desired fates, e.g. beta cells, with potential for therapeutic applications. Finally, we will engineer into living cells dynamic molecular control systems. Such controllers can be used to monitor physiological variables and secrete biological effectors in a feedback fashion for the treatment of diseases like Type 1 diabetes.
Summary
We propose to develop a new theory and design tools for the estimation and real-time control of living cells. The control systems designed using these tools will precisely and robustly steer the dynamic behavior of living cells in real time to achieve desired objectives. Cells would be controlled either collectively at the population level, or individually as single cells. The control systems achieving this regulation will be realized either on a digital computer that is interfaced with living cells, or using de novo genetic circuits that are introduced into the cells where they are designed to function as molecular control systems. Our methods will explicitly confront the numerous challenges brought about by the special environment of the cell including nonlinearity, stochasticity, cell-to-cell variability, metabolic burden, etc. The theory and methods developed in this project will thus enable the systematic, rational, and effective feedback control of living cells at the gene level, and will lay the foundation for a new corresponding body of knowledge which we call ``Cybergenetics''. It will also open new research directions in the areas of control theory and estimation.
We also propose to design three cybergenetic control systems, each addressing an important application in biotechnology or therapeutics. In the first, the controller will use light and nutrient supply to precisely regulate gene expression and cell growth in E. coli to achieve high protein and low biomass production rates. The second involves multiple feedback controllers regulating in parallel a large number of single stem cells, and leading to their differentiation to desired fates, e.g. beta cells, with potential for therapeutic applications. Finally, we will engineer into living cells dynamic molecular control systems. Such controllers can be used to monitor physiological variables and secrete biological effectors in a feedback fashion for the treatment of diseases like Type 1 diabetes.
Max ERC Funding
2 499 887 €
Duration
Start date: 2017-08-01, End date: 2022-07-31
