Although apparently simple, transparency is a complex coloration strategy. Long viewed as exclusively for camouflage (obeying the ‘being invisible to go undetected’ principle), it has recently been proposed to also play a role in communication. While morphological solutions for transparency are diverse, the physical challenges and properties are poorly known, and developmental and biophysical mechanisms at work to build transparent structures remain poorly understood. Previous studies of transparency are sparse and devoted to aquatic organisms, as transparency is frequent in water but extremely rare on land. Furthermore, understanding transparency requires working at the interface between physics, evolutionary biology and developmental biology. We propose an intercontinental collaborative project that aims to elucidate the adaptive functions of transparency in clearwing butterflies and the generative processes leading to modified structures in transparent wings, bridging the gap between development, function and evolution. First, by conducting physical measurements, we will characterize structural, optical, thermal and hydrophobic properties of transparent wings. Notably, we will characterize light transmission efficiency as well as optical patterns, such as iridescence, that may be involved in communication. Second, by examining and experimentally manipulating pupal wings at various developmental stages we will identify the cellular modifications that distinguish transparent areas from opaque areas of the same species and homologous regions between species, and define genetic pathways that underlie these distinctions. Third, by analyzing physical and developmental data in a comparative phylogenetic and ecological context we will reconstruct the evolution of transparency to test functional hypotheses (camouflage, communication, thermoregulation, water repellency) and to assess the contribution of history and selection to the evolution of transparency. This project will bring significant advances in our understanding of animal coloration strategies and terrestrial transparency.

Mapping of dynamic connectomes during fear processing holds promise for transforming our understanding of fear regulation mechanisms and for providing novel insight into the cause of anxiety disorders, in which fear deregulation is the core feature. To achieve this goal, we need to be able to manipulate and record, the activity of single neurons throughout the brain fear circuits in behaving animals. Optogenetics combined with holographic phase shaping enables in vitro and in vivo “all-optical” readout and manipulation of activity in neural circuits with single-spike and single-neuron precision. However, light scattering limits optical imaging and focusing in mammalian brain to shallow depths (<300 µm). Here, we aim at overcoming these limitations by combining the development of new ultratargeted opsins with innovative endoscopy techniques based on emerging concepts of wavefront shaping and wave propagation in complex scattering media. This novel toolbox will be developed through a unique synergetic approach will permit optogenetics and minimally-invasive imaging with single cell precision at unprecedented depths, and will be used to decipher the neural response dynamics underlying the learning and expression of divergent fear responses in the central amygdala circuits in behaving animals.

From the stunning aerial displays of large bird flocks to the collective coordination of human culture, how do the interactions among individuals give rise to such interesting and emergent group behavior, and how are these interactions constructed and controlled within the brain and the body? While collective animal behavior has long fascinated and engaged scientists across disciplines, quantitative studies in three-dimensional environments in which animals naturally live are rare and phenomenological descriptions of collective interactions, on which many models are based, have not previously been connected with their foundation in biological circuits. Here, we propose a novel, cross-disciplinary effort to measure and model the three-dimensional collective dynamics of shoaling in the zebrafish (Danio rerio) and to use genetic, pharmacological and neural perturbations to connect these dynamics to underlying biological mechanisms. We will combine expertise in zebrafish genetics and biology with precision 3D motion tracking and theoretical ideas drawn from statistical physics to quantify and elucidate the interactions that drive such collective motion. We will design a custom apparatus consisting of multiple, fast cameras and image-processing software to capture, with high-resolution in space and time, the simultaneous dynamics of interacting fish in a fully three-dimensional arena. Using this apparatus and leveraging the power of the zebrafish model system, we will quantify the collective dynamics of wild-type shoals and compare them to shoals from zebrafish deficient in their visual and lateral line sensory systems. We will also analyze shoals with disruptions to social neural circuits in the brain, focusing in particular on oxytocin and dopaminergic signaling, using optogenetic imaging. Exploiting this rich abundance of shoaling trajectory data, we will construct maximum entropy and agent-based models of group dynamics, and we will use the parameterization of these models to quantitatively characterize the collective shoaling state and changes of this state between conditions. While shoaling is the focused target of our initial efforts, zebrafish exhibit a variety of social behaviors that can also be studied with our proposed capabilities, both computational and experimental.

The paths we follow when we speak.

The analysis of language processes is traditionally based on discrete, categorical variables, such as noun phrase, suffix or phoneme, quite different in nature from the continuously varying neuronal variables (firing rates, or even spike emission times) that at a microscopic level necessarily underlie them. Forms of analog-to-digital conversion have then to be assumed to link linguistic phenomena, in particular in relation to memory, to cortical network operations. Other memory-related phenomena, however, such as navigation in rodents, are beginning to be understood in detail and to reveal computations that remain analog even at the cognitive level – e.g., the choice of a trajectory in space. Are there analog computations that are relevant to understanding language, in humans?

We address this question at two different scales of complexity. First, in the choice of successive phonemes while uttering a word, which we take to be produced by a well-localized network, perhaps in the left inferior frontal gyrus. It may be envisaged as a continuous trajectory on a ‘phoneme manifold’ which expresses, in the space of all possible vocalizations, the phonological memory of one’s own language(s). We ask how the structure of such a manifold would reflect the statistical learning process with which it is gradually acquired during development, and how it would itself be reflected in the patterns of errors observed when reading aloud. To this end, we shall use network models comprised of individual neuronal units and psycholinguistic tests.

Second, to contrast analog with digital computations within the same paradigm, we consider the memory devices that have culturally evolved to remember extended verbal material, and have crystallized in poetry. Some of them, such as meter, can be thought of as expressing a quasi-continuous trajectory, while others, such as rhyme, are more punctuate and essentially digital. We intend to assess the effectiveness of devices of different nature by manipulating them in network models and in psycholinguistic and EEG experiments involving poetry recall. Since meter and rhyme are embedded in complex constructs including meaning, syntax and other components, which are beyond our scope, we shall represent the whole cortex as a network of Potts units, effectively a model of interacting cortical patches.

The cross-talk between integrin-based adhesions to the extracellular matrix and dynamic microtubules plays a crucial role in cell polarity and migration. Integrin-based adhesions can promote cortical microtubule stabilization in their vicinity. In turn, microtubules can strongly affect the formation and turnover of the adhesion sites. However, the molecular basis of these connections remains enigmatic.
Here, we propose to decipher the molecular chain of events induced by mechanotransduction at integrin adhesions that leads to cortical microtubule stabilization and analyze the morphogenetic impact of this process. To achieve this goal, we will bring together four distinct sets of expertise: cell biology of the cytoskeleton (Akhmanova); structural biology, biochemistry and biophysics of protein-protein interactions (Goult); mechanobiology and single molecule analysis of force dependence of protein-protein interactions (Yan) and genetic analysis of morphogenesis in flies (Tanentzapf).
We will use advanced cell manipulation assays to directly test whether mechanotransduction at adhesions affects microtubule capture and stabilization at the adjacent cortical sites. To uncover the molecular basis of this process, we will focus on a recently discovered connection between a cortical adaptor protein, which constitutes a part of the microtubule stabilization complex, and an adhesion component. At the same time, we will perform experiments, which will allow us to identify and explore additional links between focal adhesions and the microtubule-stabilizing complex, and thus generate a comprehensive functional map of these connections. Given that the investigated proteins are highly conserved, we will combine genetics, imaging and modeling to address their impact on morphogenesis and tissue maintenance in flies. Our work will shed light on how cellular mechanics and cytoskeletal dynamics are integrated at the molecular level.

Our body consists of trillions of cells, which derive from a single fertilized egg. The divisions that generate these cells constitute a genealogical tree, with a single root (the fertilized egg) and trillions of terminal branches (each of our cells). Knowing the shape and branching order of this tree is important because it provides vital information about how we developed; cells that are on the same branch shared the same cell precursors and a common history of developmental decisions. The cell lineage tree of an individual is also important for understanding cancer; its origins and history of colonizing the body.
Discovering the cell lineage of an organism is a huge challenge that has been solved only in the simplest cases. In the nematode worm Caenorhabditis, whose body consists of approximately 1000 cells, the complete cell lineage was painstakingly determined by direct observation of each cell division under the microscope. In larger organisms we can only infer partial cell lineages by direct observation, or through a method called clonal analysis in which genetic marks are used to label the progeny of individual cells. Each of these methods has its limitations. Direct observation is only applicable to transparent, tiny organisms and to events that occur within hours or days. Clonal analysis can inform us about the rough structure of the lineage tree, but its precise branching patterns are unresolved.
Here we propose a new strategy. It is based on the idea that random mutations, which accumulate in cells during the lifetime of an organism, can reveal the structure of its lineage tree: cells belonging to a major branch will uniquely share mutations that occurred in their common ancestors, those that lie together on a finer branch will share additional mutations, and so on. In principle, if a sufficient number of mutations were detected, we could infer the complete lineage tree of the individual. In practice, this approach is limited by our ability to find those rare somatic mutations within the genome of individual cells. Our strategy resolves this problem by relying on two new technologies: a method that allows us to generate mutations at specific sites in the genome, combined with a method for detecting these mutations in the organism, with single-cell precision.

Although potentially of fundamental importance for many phototrophs on Earth, the physiological mechanisms and molecular underpinnings that allow survival over long periods of dark remain a mystery. Diatoms, the dominant oceanic eukaryotic photosynthetic organisms, specifically Fragilariopsis cylindrus (polar pennate diatom with a sequenced genome) and Thalassiosira gravida (representative Arctic centric diatom), will serve as models to characterize the physiological, cellular, genomic, epigenomic, and metabolic state of cells during prolonged darkness and the return of light. Complementary expertise in our team (culturing of polar species, optics, photochemistry, genomics) will allow us to identify key adaptive mechanisms used by diatoms.
Realistic light transitions from fall to early spring will then be simulated to grow F. cylindrus and T. gravida in specially designed bioreactors under stable nutrient and cold temperature conditions. Cellular energy flow and allocation will be monitored before, during and after a simulated 6-month polar night: light absorption coefficients and pigment composition, absorption cross-sections and concentrations of PS1 and PS2, electron production by PS2, redox states of the plastoquinone pool, linear and alternative electron flows, cellular content of electron acceptors, concentrations and activity of RUBISCO, rates of C-fixation, respiration, heterotrophy, and reduction level of storage compounds. F. cylindrus cells will also be examined for their transcriptional and translational activity, and will be subject to transcriptome and metabolome analyses. Mass spectrometry and immunoblotting performed on chromatin will identify major changes in DNA methylation and histone tail modifications. Features of interest will be subject to chromatin immunoprecipitation and DNA sequencing. DNA methylation and histone marks will be aligned to the reference genomes. Chromatin and gene expression states arising in response to prolonged darkness and the return of light will be defined, informing metabolic maps and physiologies. In parallel, organellar structures will be assessed by electron microscopy. Candidate genes encoding key processes for dark survival and recovery will be studied by producing transgenic strains of F. cylindrus, in which these specific genes will be knocked-out.

Filopodia are thin, actin-rich plasma membrane protrusions, which function as sensory organelles of cells. Despite a wealth of information on the physiological functions, the molecular mechanisms underlying their assembly and dynamics are incompletely understood. Filopodia are characterized by high negative membrane curvature and high density of phosphoinositides. Their formation and dynamics are controlled by an array of actin-binding and signaling proteins, many of which interact also with phospholipids. However, the mechanisms and biological roles of these lipid-interactions are largely unknown. We will collaboratively examine the molecular principles of filopodia assembly, with a specific focus on the roles of membrane curvature sensing and phosphoinositide clustering in this process. We will use advanced cell biology methods (genome editing combined with live-cell imaging approaches) to identify the mechanisms by which central filopodial proteins are recruited to these membrane protrusions in cells. Phosphoinositide and curvature sensing properties as well as potential synergetic effects of these proteins will be quantitatively measured by in vitro experiments (optical tweezers, confocal microscopy, FCS) using model membrane systems (membrane nanotubes pulled from Giant Unilamellar Vesicles) with controlled curvature, and also in silico (multiscale simulations) and in vivo with relevant mutant proteins. These computationally efficient simulations are based on systematic coarse-graining methods, in which the molecular resolution is reduced but the effects of key molecular features retained, thus adding insight into the cooperative processes underlying filopodia formation. Such insight will also help to connect the results of the in vivo and in vitro experiments. Finally, once a minimal set of proteins responsible for this synergy will have been identified, we will include actin and reconstruct a synthetic filopodium. Additional positive feedback is eventually expected to take place due to actin polymerizing against the membrane. Thus, by virtue of reconstituted systems, we will aim to identify the essential physical mechanisms underlying the very first steps of filopodia formation.

Macrophages play beneficial roles in protective immunity. However, they also favor the progression of several pathologies when they massively infiltrate diseased tissues. A present challenge in cancer, for instance, is to control macrophage tissue infiltration, which involves the mesenchymal motility. This motility is characterized by the ability of the cell to form protrusive structures called podosomes. A podosome constitutes a submicron core of actin filaments surrounded by a ring of integrin-based adhesion complexes. Our working model postulates a mechanical connection that counterbalances the actin-rich protrusive core by traction at the adhesive ring, likely embodied by acto-myosin contractile cables. Therefore core and cables would form a unique two-module protrusive force generator that balances forces at the level of a single podosome to ultimately contribute to the mechanics of macrophage migration.
Our objective is to build a sound experimental corpus to substantiate this two-module mechanism of force generation and determine its implications for macrophage 3D motility. To this end, we will characterize podosome molecular architecture and formulate its relationship to force generation. Furthermore, we will identify the mechanical role of key podosome components in cell migration.
We assembled a multidisciplinary team that combines cutting-edge expertise in: i) macrophage 3D migration, ii) 3D nanoscale imaging, iii) live super-resolution imaging, iv) cryo-electron tomography technologies allowing resolution of actin filaments within cellular networks, v) measurement of podosome protrusion forces and vi) mechanics of 3D cell migration in custom microfabricated environments.
Our ambitious research plan will deliver the nanoscale localization of podosome molecular components (applicants A1, A3), determine how the architecture evolves along with force dynamics (A2), investigate the mechanics of 3D migrating cells (A4) and reveal the role of podosome components in these uncharted features (A1-4). Thanks to this groundbreaking study, we will articulate mechanical and architectural insights into an integrated portrait of podosomes from the molecular scale up to the biological context of 3D cell migration and thus identify molecular means for the modulation of pathological macrophage tissue infiltration.

Inorganic polyphosphate (polyP) is a biopolymer that serves multiple critical functions in biology. PolyP has been mainly studied in bacteria and shown to be involved in such diverse processes as the bacterial stress response, biofilm formation, plasmid uptake and antibiotic resistance. In comparison, its functions in mammals are significantly less well understood. Even so, polyP has been linked to multiple important physiological phenomena, such as blood clotting, chaperone function, posttranslational protein modification and neuronal signaling.
While in bacteria the enzymes that generate polyP are known (polyphosphate kinases Ppks), the mammalian enzymes remain elusive to date. In fact, we know that polyP is present in different cell types and that it is enriched in different organelles, but we do not know how and where it is made and how it is shuttled. Moving polyP research forward will critically require identification of the elusive enzymes that make and traffic polyP. Currently, a dearth of chemical tools has precluded such deeper insight into mammalian polyP physiology.
Our proposed research will culminate in new technologies required to make, modify, analyze, transport and deliver polyP both ex and in vivo. We will develop and combine multiple novel synthetic approaches to generate a range of modified polyP analogs that are not yet available. Furthermore, we will develop technologies to deliver and release those synthetic analogs in a controlled way outside and inside of cells. Together, these technologies will provide valuable novel insight into how cells make, regulate and distribute polyP. We will use these tools to identify the mammalian enzymes involved in polyP turnover, investigate how polyP levels are affected by other signaling molecules such as inositol pyrophosphates, and try to understand how polyP affects different biological processes. For example, an in-depth evaluation of the role of polyP in blood clotting will be achieved using our novel approaches. These studies will lay the foundation for further research into polyP physiology. By virtue of the combination of synthetic organic chemistry, drug delivery technology, and cell and animal biology, we will be able to develop and apply powerful novel tools dedicated to the elucidation of polyP physiology in mammals.

Although many of the molecules that determine animal body plans have been uncovered in recent years, we still cannot predict the final design of an animal from a diagram of how these molecules interact. This limitation stems in great part from the fact that current technologies to visualize development rely on dead embryos or employ reporter systems that cannot capture the dynamics that underlie developmental processes. Measurements of these dynamics constitute just one step toward predictability; in order to sharpen our understanding, theoretical models that generate quantitative predictions must accompany such measurements. Our interdisciplinary team, which consists of researchers with extensive expertise in developmental biology (Andrew Oates, Francis Crick Institute), the theory and measurement of gene expression (Hernan Garcia, UC Berkeley), and protein engineering (Roberto Chica, University of Ottawa), is uniquely positioned to establish a predictive understanding of the gene regulatory networks that govern vertebrate body plans. We will focus on the segmentation clock in zebrafish, in which the length of body segments is thought to be determined by a network of oscillating genes. We will develop new technology to simultaneously monitor mRNA and protein concentrations in real time during segmentation of the zebrafish embryo. Furthermore, we will develop theoretical models that will leverage this new information to predict how molecular interactions lead to oscillations with a prescribed period and amplitude. These predictions will be tested via the creation of synthetic oscillators with engineered dynamical properties that will be used to generate embryos with altered body plans. We anticipate that these iterations of model and experiment will set the stage for a new paradigm in synthetic biology that enables the rational design of multicellular organisms.

Cells in developing organisms can keep track of time. They use this to make important decisions - for example on when to turn or to stop in the case of migrating axons or cells - without being instructed to do so by signals from other cells in their surroundings. But how such internal clocks work, and importantly, how they are made to be so precise, is still largely unknown. Previous work by one of the participating teams has shown that during the development of the nematode worm C. elegans, the migration of a neuroblast is regulated through the timed expression of a signaling receptor. This system provides a powerful assay to study at single cell level how an internal clock controls gene expression. The three teams will use a unique combination of genetics, evolutionary biology and mathematical modeling to gain detailed insight into the workings of this timing mechanism. They will investigate how timing is mediated at the transcriptional level, how robust this is to environmental variations and how this mechanism has evolved in other nematode species. Importantly, these results will be used in mathematical modeling to gain insight into the underlying regulatory architecture and to make predictions that will be tested in further experiments. Such interplay between experimental and theoretical analysis is a powerful and innovative approach that will enable the three teams to gain deep understanding of how cells measure time.

Vocal learning is a fundamental trait of spoken language and yet the neuro-molecular mechanisms underpinning this trait are poorly understood. The capacity for vocal learning has only been identified in a handful of non-human mammals; cetaceans, elephants and bats. The first evidence for some vocal adaptations in non-human primates is only now emerging. Despite intense interest, these limited experimental options mean that the neural underpinning of mammalian vocal learning has been massively understudied. Some birds, such as parrots, hummingbirds and songbirds, are also vocal learners. Work in songbirds has provided valuable insights, but the evolutionary divergence of avian brain structure is a barrier for direct extrapolation to mammals. Furthermore the lack of a mammalian animal model means that it is unclear whether or not mammals and birds use similar mechanisms during vocal learning. As a result, fundamental questions in the field remain unanswered, such as: how is vocal learning encoded in the mammalian brain, how do neurological and genetic substrates contribute to this trait, and are these mechanisms similar across divergent species?
We will establish bats as an ideal model system because they are mammals that have robustly shown vocal learning and have remarkable capacity for combining vocal phonemes to create new types of vocalisations. Bats can be maintained in laboratory colonies, and there is already a wealth of information regarding the neuroethological mechanisms by which they produce and perceive their vocalizations. We aim to establish bats as the first mammalian model of vocal learning by designing innovative communication paradigms coupled to comprehensive neurological and genetic interrogations. This proposal integrates psychophysical, anatomical, electrophysiological & genetic research in an innovative way to begin to address the encoding of vocal learning in the mammalian brain.
This complementary and coordinated research effort, focuses on a tractable and very promising animal model, addresses a fundamental gap in the field and is likely to significantly advance our knowledge about the origins of vocal learning and ultimately human speech. We believe that this work will have important repercussions across sensory ecology, neuroscience, genetics, evolutionary biology and linguistics.

Humans and monkeys are very good at interpreting intent from other’s body movements and facial expressions. This visual recognition is achieved seemingly effortlessly. This visual recognition is also highly accurate, even though the possible number of body movements and facial expressions is extremely large. While much is now know about the different brain mechanisms involved in the recognition of objects, scenes and faces, little is known on how the visual system recognizes other agent’s intent. We will use functional Magnetic Resonance Imaging (fMRI) in humans and fMRI and single cell recordings in monkeys to identify the neural mechanisms responsible for this recognition. The neuroimaging data will be analyzed using sophisticated machine learning algorithms. These methods of analysis will be used to identify the regions of interest (ROIs) involved in this visual recognition of intent, determine their interaction, and study the image or higher-level features used in each ROI. We hypothesize that, as in object and face recognition, there is a hierarchy of areas with increasing level of abstraction. Finally, we will use the results of our experimental data to derive a neurophysiologically plausible model and optogenetics to test for the causal role of these computations.

Curiosity, defined as the intrinsic desire to know, is among the last unexplored frontiers of higher cognition, and we know very little about its neural mechanisms. We propose to address this question by developing a program for studying curiosity using an integrated empirical/computational approach in humans and non-human primates. We examine the hypothesis that curiosity is a family of mechanisms that evolved to allow animals to maximize their knowledge of the useful properties of the world – i.e., the regularities that exist in the world - using active, targeted investigations. In two experiments, we probe two processes that contribute to curiosity-based exploration. In experiment 1 we examine how agents ascribe value (“interest”) to surprising events, by (1) developing a new behavioral task where children and monkeys make tradeoffs between exploring for sources of reward versus exploring a surprising item, and (2) investigating single-neuron responses related to curiosity-based exploration in cortical areas implicated in the control of attention. In experiment 2 we ask whether subjects show a more sophisticated form of curiosity guided by learning progress – a meta-cognitive tracking of the amount of learning that the individual can make in a task - using new behavioral paradigms where children or non-human primates see a set of symbolic learning problems and freely choose which ones to explore. To quantitatively model curiosity we use the framework of Bayesian Reinforcement Learning, which allows us to infer the agent’s beliefs about the probabilities of various events (rewards, surprises, or learning), the value they place on sampling different events, and how this value depends on the task context. The studies closely integrate the expertise of the 3 member teams in developmental psychology (Kidd), neurophysiology of non-human primates (Gottlieb) and computational modeling of active learning in robotic systems (Oudeyer). Our goal is to develop an integrated theory that (1) incorporates curiosity in established quantitative frameworks of learning and decision making, (2) links it with core cognitive functions such as selective attention, (3) compares its expression in humans and non-human primates, and (4) begins to elucidate its neural mechanisms.

In the brain, the balance between excitation and modulation plays a crucial role in numerous cognitive processes and pathological impairments of this balance may underlie several neurological disorders. Indeed, dysregulations of two neurotransmitter receptor families, glutamate NMDA (NMDAR) and dopamine (DAR) receptors, are believed to play a direct role in the emergence of psychotic disorders such as schizophrenia. Thus, understanding how these two neurotransmission systems communicate is of growing interest. Intensive investigations have identified intracellular and genomic cascades involved in this dialogue. However, the recent discovery that NMDAR and DAR diffuse and physically interact at the surface of neurons profoundly changed our view of neurotransmitter signaling. A major challenge is now to unveil the contribution of DAR/NMDAR complexes in the regulation of living brain circuits. To this aim, we will combine complementary expertise to investigate the surface crosstalk between NMDAR and DAR both in physiological and psychotic disorder contexts, focusing our attention on D1R, D2R, and NMDAR in hippocampal, prefrontal and striatal circuits. We will assess the roles of this dynamic receptor interplay from a multi-scale perspective. We will first investigate the rules of the DAR/NMDAR surface dialogue at the single molecule level by mapping all interaction sites and monitoring receptor distribution and diffusion using multi-color single molecule imaging in vitro and in brain slices at several developmental stages, both in control and in models of schizophrenia. We will then investigate whether the DAR/NMDAR surface crosstalk regulates glutamatergic transmission along the dendritic tree, its impact on NMDAR-dependent plasticity, and its role in dendritic outgrowth and spine maturation during development using two-photon calcium imaging, electrophysiological recording and competing peptides. Finally, we will investigate the influence of the DAR/NMDAR interplay on physiological and pathological network dynamics and behaviors using multi-electrode array recordings, optogenetic release of dopamine, competing peptides and “data-mining” statistics. In conclusion, we will join international forces to shed the first lights on this unexpected dynamic integration level using nanoscopic, macroscopic and mesoscopic approaches.

The oceans are teeming with microbial life, which impacts global biogeochemistry, climate and human health. Omics methods enable us to identify "who is there" and their genetic potential, but understanding how these organisms interact in nature and how they affect biogeochemical processes remains a major open challenge. A crucial component of this puzzle, at the heart of the cycling of nutrients in the biosphere, is the coupling between organisms that fix carbon using solar energy (phytoplankton) and microbes that rely on organic carbon for energy and growth (heterotrophs). The diversity of microbial species and the richness of their metabolism make the problem of predicting how each pair of species will interact impossible to address using traditional approaches. We propose to tackle this challenge through a tightly integrated combination of genome scale modeling and laboratory experiments, to identify genomic traits dictating how environmentally-relevant microbes interact. We will generate a library of ~100 heterotrophic bacteria representing major marine lineages and fully sequence and annotate their genomes. We will implement genome-scale (dynamic flux balance) models of each of these organisms, as well as of four key phytoplankton species, calibrating these models using high-throughput measurements of growth under different conditions. We then grow binary phytoplankton-heterotroph co-cultures in the lab and compare the results with in-silico models of the interacting genomes, studying key interactions in more detail. Recognizing that microbes in the ocean are seldom in steady-state, our work will encompass exponential growth, stationary stage and culture death. Most importantly, missing or incorrectly predicted interactions will give us an opportunity to revisit our models, and suggest the mediation of alternative processes such as allelopathy or other types of chemical signaling. This study will provide the first detailed "roadmap" linking genomic traits (genes and metabolic pathways) and rate measurements with species interactions in environmentally-relevant microbes. Our approach, which - we anticipate - will be embedded in a not-so-distant future in global-scale models of the Earth System, will provide a critical stepping-stone towards predicting how marine microbial systems will evolve in a changing world.

Monomeric actin is readily detectable in the nucleus of mammalian somatic cells. Whether this pool of actin forms filaments has been debated for decades. Recent advancements have established that, indeed, nuclear actin can assemble dynamic filamentous structures in response to external stimuli. However, how nuclear actin filaments exert their biological function remains an unanswered question in cell biology. This is particularly relevant given the highly dynamic nature of nuclear actin filaments, which reside within the intricately organised nucleus that harbours the genome in the form of chromatin. Thus, through this collaboration, we aim to address this by developing and applying novel approaches for optogenetics, advanced cell-imaging and next generation sequencing. Accordingly, we will employ tools to spatiotemporally control nuclear actin filaments with light, and determine their role in regulating chromatin organisation and nuclear structure. Further, we will determine the cell and biological consequences of actin filament-driven chromatin organisation/re-organisation in relation to cell division and cellular reprogramming. By completing these studies, we envisage to advance our understanding of the biological functions of nuclear actin filaments in a manner that will encompass nuclear actin polymerisation as a key mediator of chromatin organisation and regulation. Beyond this, findings from our studies may have translational potential in areas of regenerative medicine, and may delineate new mechanisms that underlie ageing and degeneration.

Like human babies learning speech, young songbirds learn to produce song by imitating adults. Both babies and young birds need to listen to adult vocalizations, extract the relevant information and store it in the brain and then improve their own ‘babbling’ sounds step by step towards the adult version. Experiments on vocal learning have focused mainly on sounds, although sight also seems to play an important role. Babies of only 8 weeks of age already associate speech sounds with the correct mouth position required to make that sound. Moreover, people report that they hear the syllable ‘ga’ when in fact a loudspeaker plays ‘pa’ while a video screen shows the face of a speaker mouthing ‘ka’. This perceptual phenomenon is known as the ‘McGurk' effect. It reveals that sensory information from the ear and eye are integrated in the brain to form a combined, multimodal percept.
Like human speech, birdsong can be heard and seen. Young birds see their fathers moving their beaks while hearing their song. There is substantial evidence to assume that the combined exposure to acoustic and visual cues enhances song learning not only in human but also in bird babies. We aim to uncover the role of this multimodal perception and its underlying neural architecture in vocal learning. Focusing on the zebra finch, the prevalent animal model for molecular, neural and developmental aspects of human speech we will adopt a robotic approach that allows full experimental control over auditory and visual cues.
Simultaneously recording acoustic and visual cues of singing adult birds, we will analyze synchrony between different song elements and the opening and closing of a bird's beak. We will use this to develop a robotic zebra finch that allows us to create matched and mismatched multimodal stimuli. Juvenile birds will be raised with various tutoring regimes to assess the relative roles of unimodal versus multimodal cues, life versus robot cues, and matched versus mismatched cues. Upon reaching adulthood, tutored birds will be tested on their song copy performance (males only), song preference (females only), or discrimination ability (all birds). Finally, we will use a subset of tutored birds to study underlying neural processes by using molecular tools that allow us to pinpoint where in the brain multimodal information is processed and how this is linked to vocal learning.

Neuroscience research using rodents as an animal model relies on the assumption that results should generalize across species to primates and ultimately to humans. However, many brain areas, including the neocortex, have species specific functional organizations. The mouse lemur (Microcebus murinus), the World’s smallest primate, has the potential to become an ideal animal model bridging the gap between rodents and primates. It has most the advantages of the rodent model (small brain size, quick reproduction, relatively short life cycle), but additionally offers the evolutionary closeness of primates. Therefore, the mouse lemur promises to revolutionize the transferability of experimental results from small sized animal models to human applications. In this project, three labs will combine their expertise in primate behavior, in-vivo optical imaging, and cutting edge histology and molecular biology to explore the functional organization of the mouse lemur cortex, as well its behavioral and cognitive capacity. This collaborative project will lay the groundwork to establish the mouse lemur as a novel neuroscience model system.