ERC FUNDED PROJECTS

The realization of “the internet of things” is inevitably constrained at the level of miniaturization that can be achieved in the electronic devices. A variety of technologies are now going through a process of miniaturization from micro-electromechanical systems (MEMS) to biomedical sensors, and actuators. The ultimate goal is to combine several components in an individual multifunctional platform, realizing on-chip technology. Devices have to be constrained to small footprints and exhibit high performance. Thus, the miniaturization process requires the introduction of new manufacturing processes to fabricate devices in the 3D space over small areas. 3D printing via robocasting is emerging as a new manufacturing technique, which allows shaping virtually any materials from polymers to ceramic and metals into complex architectures. The goal of this research is to establish a 3D printing paradigm to produce miniaturized complex shape devices with diversified functions for on-chip technologies adaptable to “smart environment” such as flexible substrates, smart textiles and biomedical sensors. The elementary building blocks of the devices will be two-dimensional nanomaterials, which present unique optical, electrical, chemical and mechanical properties. The synergistic combination of the intrinsic characteristics of the 2D nanomaterials and the specific 3D architecture will enable advanced performance of the 3D printed objects. This research programme will demonstrate 3D miniaturized energy storage and energy conversion units fabricated with inks produced using a pilot plant. These units are essential components of any on-chip platform as they ensure energy autonomy via self-powering. Ultimately, this research will initiate new technologies based on miniaturized 3D devices.

1 999 968 €

Start date: 2019-09-01, End date: 2024-08-31

When faced with a threat, an animal must decide whether to freeze, reducing its chances of being noticed, or to flee to the safety of a refuge. Animals from fish to primates choose between these two alternatives when confronted by an attacking predator, a choice that largely depends on the context in which the threat occurs. Recent work has made strides identifying the pre-motor circuits, and their inputs, which control freezing behavior in rodents, but how contextual information is integrated to guide this choice is still far from understood. We recently found that fruit flies in response to visual looming stimuli, simulating a large object on collision course, make rapid freeze/flee choices that depend on the social and spatial environment, and the fly’s internal state. Further, identification of looming detector neurons was recently reported and we identified the descending command neurons, DNp09, responsible for freezing in the fly. Knowing the sensory input and descending output for looming-evoked freezing, two environmental factors that modulate its expression, and using a genetically tractable system affording the use of large sample sizes, places us in an unique position to understand how a information about a threat is integrated with cues from the environment to guide the choice of whether to freeze (our goal). To assess how social information impinges on the circuit for freezing, we will examine the sensory inputs and neuromodulators that mediate this process, mapping their connections to DNp09 neurons (Aim 1). We ask whether learning is required for the spatial modulation of freezing, which cues flies are using to discriminate different places and which brain circuits mediate this process (Aim 2). Finally, we will study how activity of DNp09 neurons drives freezing (Aim 3). This project will provide a comprehensive understanding of the mechanism of freezing and its modulation by the environment, from single neurons to behaviour.

1 969 750 €

Start date: 2019-02-01, End date: 2024-01-31

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.

2 000 000 €

Start date: 2019-03-01, End date: 2024-02-29

Arctic sea ice decline is the exponent of the rapidly transforming Arctic climate. The ensuing local and global implications can be understood by studying past climate transitions, yet few methods are available to examine past Arctic sea ice cover, severely restricting our understanding of sea ice in the climate system. The decline in Arctic sea ice cover is a ‘canary in the coalmine’ for the state of our climate, and if greenhouse gas emissions remain unchecked, summer sea ice loss may pass a critical threshold that could drastically transform the Arctic. Because historical observations are limited, it is crucial to have reliable proxies for assessing natural sea ice variability, its stability and sensitivity to climate forcing on different time scales. Current proxies address aspects of sea ice variability, but are limited due to a selective fossil record, preservation effects, regional applicability, or being semi-quantitative. With such restraints on our knowledge about natural variations and drivers, major uncertainties about the future remain. I propose to develop and apply a novel sea ice proxy that exploits genetic information stored in marine sediments, sedimentary ancient DNA (sedaDNA). This innovation uses the genetic signature of phytoplankton communities from surface waters and sea ice as it gets stored in sediments. This wealth of information has not been explored before for reconstructing sea ice conditions. Preliminary results from my cross-disciplinary team indicate that our unconventional approach can provide a detailed, qualitative account of past sea ice ecosystems and quantitative estimates of sea ice parameters. I will address fundamental questions about past Arctic sea ice variability on different timescales, information essential to provide a framework upon which to assess the ecological and socio-economic consequences of a changing Arctic. This new proxy is not limited to sea ice research and can transform the field of paleoceanography.

2 615 858 €

Start date: 2019-08-01, End date: 2024-07-31