Sporadically, novel and potentially devastating pandemic influenza A viruses (IAVs) are generated through genome reassortment between human and animal co-infecting IAVs. Such pandemic viruses emerge as a consequence of the segmentation of IAVs genome into a bundle made of 8 distinct viral RNAs (vRNAs). However the molecular mechanisms of vRNA intracellular transport and assembly into vRNAs bundles, which are critical for reassortment, remain largely unknown. Our project aims to elucidate these fundamental aspects of IAV life cycle by developing innovative approaches.
We challenge the original model that newly synthesized vRNAs, in the form of viral ribonucleoproteins (vRNPs), are transported across the cytoplasm on Rab11-dependent recycling endosomes. Based on our recent work, we hypothesize that the concomitant transport and assembly of vRNPs is driven by their physical association with remodelled endoplasmic reticulum (ER) membranes and Rab11-dependent transport vesicles distinct from recycling endosomes.
We will set up a cellular system which resembles the natural respiratory tissue targeted by IAVs, while being amenable to simultaneous imaging of the endogenous Rab11 protein and tagged vRNAs. We will develop two cutting-edge and complementary imaging methods: dual-color single molecule fluorescence in situ hybridization (FISH) in live cells for the tracking of distinct vRNAs that diffuse concomitantly, and cryo-Focused Ion Beam combined with electron microscopy in situ hybridization (EMISH) to image individual vRNPs and their transport vesicles at molecular resolution. We will further assess the role of cellular ER-shaping proteins by performing CRISPR/Cas9-mediated knockdowns, and by monitoring changes in the viral-induced remodelling of ER and biogenesis of vRNP transport vesicles by live fluorescence imaging and cellular EM.
The proposed research will require the very close collaboration between three partners with distinct but complementary expertise. The approaches developed jointly are poised to revolutionize our understanding of IAV multi-RNA genome transport and bundling, and thus help in the broader goal of achieving better prevention and treatment of influenza disease. Additionally, the proposed technical developments in live cell FISH and cellular EM, will have impact on other fields of studies well beyond the scope of the proposed project.

Glycolysis is a fundamental energy metabolic pathway which consists of ten enzymatic steps. Unlike the mitochondrion, which is a membrane-bound organelle, glycolytic enzymes are soluble proteins in the cytosol. Based on biochemical evidence, glycolytic enzymes have long been hypothesized to form functional complexes to sustain the rates of glycolysis. This purported complex, called the glycolytic metabolon, was a subject of intense study and debate thirty years ago. Still today we do not yet understand how these purported complexes are organized in cells to sustain local energy metabolism, or their physiological importance. This gap in knowledge results from the fact that when glycolysis was being rigorously examined forty years ago, the techniques did not exist to conclusively answer these questions. The main challenge in addressing these questions lay then, as now, in the ability to both examine the localization of the glycolytic enzymes in living cells, while understanding the biophysical and biochemical mechanisms of their association, and its implications in cellular physiology. We have established a collaboration to address these fundamental questions by making use of our joint expertise in vitro reconstitution and C.elegans physiology, using the energy demands of the C.elegans synapse as a model system.

Plants live in an ever-changing environment which is not always compatible with their survival. A major life threatening condition is drought stress. While most plants can deploy an array of physiological countermeasures to endure remarkable levels of stress, there is a huge variability in the different strategies that plants choose to adopt to deal with drought stress. Many plants evade detrimental stress conditions by activating their reproductive development (flowering) earlier compared to non-stress conditions, a strategy known as drought escape (DE). Notably, even in the most water-rich environments plants face unpredictable dry periods, yet how this information affects the floral network at the molecular levels is unknown.
We will address this question with a blend of molecular and genetics-based approaches. We will leverage known mutants with altered DE to identify candidate mechanisms that are drought sensitive and can act as molecular switch to activate flowering. To comprehensively define DE mechanisms utilized under natural conditions we will assess the variability of the DE response in natural plant populations and in crops, which were selected by human intervention for the different field scenarios. Our targeted large-scale screens will allow us to identify naturally occurring variants in the DE process and decipher the molecular mechanism responsible for DE activation. This information will provide breakthroughs in our understanding of novel regulatory mechanisms that play a role in driving developmental adaptations across extremely variable environmental conditions, their natural genetic variation and the selective forces that maintain such variation in populations, an important aspect for predicting and dealing with the effects of climate change. Finally, because flowering time is a major component of yield potential in crops, the defined mechanisms will help us develop breeding strategies targeted for sub-optimal irrigation scenarios to produce crops with ameliorated performances under drought conditions.

Organisms need strategies to survive when conditions are hard. For mammals, winter is particularly difficult - they have to invest large amounts of energy into keeping warm, while food availability is low. For this reason, many mammals migrate or hibernate. However, what to do if you are too small to migrate long distance, burn your energy fast, and cannot hibernate? The common shrew is such a mammal and has evolved an astonishing strategy: each individual shrinks in winter by up to 20% and then regrows in the spring by about 13%. This size change, thought to allow shrews to survive on fewer resources because of the smaller size and linked lower energy requirements, include not just overall size, but specifically organs that do not usually change size in fully grown animals, such as the brain, heart and liver.
The process of neurological degeneration and regeneration is of great interest, since many central nervous system diseases (e.g., Alzheimer’s, multiple sclerosis) involve degeneration, but ongoing research for therapies to reverse this process has been of limited success. As one of only a few recorded examples of mammalian brain regeneration, understanding how the shrew regrows its brain can accelerate research that leads to future therapies.
To answer the question of how the shrew shrinks and then regrows its brain, we will establish this unusual species as a new model, by studying the biological, molecular, biochemical and genetic processes behind this reversible size change. Besides establishing a database of information that can be mined and researched in years to come to discover the pathways that generate this cycle in the shrew, we will test a metabolic model of neurological change by artificially blocking molecular access to fats. Thus, the cross-disciplinary study of this wintering adaptation may help us understand more about regeneration in mammals in general, and the brain in particular.

To study how nervous systems arise and function, scientists use animal models in which it is possible to integrate research on fundamental processes across different levels of organization from genes to behavior, and from the zygote to the adult. The medicinal leech (genus Hirudo) provides one useful model, because its nervous system is much simpler and easier to work with than vertebrate or mammalian nervous sytems, even though it functions in a similar manner--Hirudo has been used to study phenomena of general importance such as: how glial cells function; how neurotransmitter are released; how synapses form and regenerate; and how neural circuits function to control behavior. Another leech (genus Helobdella) is used to study development and how development changes during evolution, giving rise to kinds of animals over hundreds of millions of years. These two leech species exhibit marked similarities of course, but also some differences. Technical considerations (small embryos for Hirudo; small adults for Helobdella) have made it difficult to integrate these two models, e.g. by applying molecular approaches in Hirudo or to study the adult nervous system in Helobdella. The goals of our project are: 1) to enhance the power of the Hirudo model by introducing newly-developed molecular approaches; 2) to implement approaches in Helobdella that will enable us to unite molecular and cellular approaches to developmental and behavioral neurobiology; 3) to develop new optical techniques for stimulating and recording neuronal activity without exogenous dyes or genetic manipulations.
The intellectual significance of the proposed work is twofold. First, it will enhance our abilities to answer fundamental questions regarding how nervous systems function and development by introducing cutting edge technical approaches to the cellularly simple, physiologically accessible leech models. Of equal importance, it will provide a new evolutionary perspective into neurobiology, by allowing us to examine similarities and differences between leech and other models, including arthropods, nematodes, and vertebrates which have all been evolving separately for more than half a billion years.

The aerial courtship “dance” of mosquitoes has fascinated entomologists for over 150 years. This dance involves highly controlled variations in the frequency and intensity of flight-tones (i.e. sounds generated by the flapping wings) with concurrent changes in flight speed and direction, and enables recognition of conspecifics, display of fitness and transmission of mating interest. However, despite over a century and a half of research, significant knowledge gaps continue to exist in our understanding of this behavior. To decipher this courtship dance, entomologists have to integrate acoustic, energetic and flight information for untethered, free-flying mosquitoes, but the tools that can provide these data have, so far, not been available. In the current project, the two investigators combine their respective expertise in computational biomechanics and acoustics, and behavioral entomology, to generate unprecedented data and insights into the biomechanics and physics of courtship-associated acoustic communication in mosquitoes. In particular, by combining computational modeling with biological assays, the team will generate six-dimensional soundscapes of free-flying mosquitoes engaged in courtship and determine how these soundscapes are actively modified during courtship. We will also estimate for the first time, the energetic costs of courtship and mate-chasing, and the potential constraints this places on courtship behavior. Finally, the team will characterize the degree to which, carefully tailored exogenous sounds can alter and even disrupt courtship. The success of this novel approach could be transformative for future research into comparative auditory mechanisms of communication across a wide range of flying insects. In addition, the insights gleaned here could form the scientific foundation for novel insecticidal/surveillance traps and also lead to environmentally friendly strategies for diminishing mating success in mosquito species that are vectors for malaria, Zika fever and other devastating mosquito-borne diseases.

The overarching goal of this proposal is to investigate the spatiotemporal coding of acetylcholine (ACh) and dopamine (DA) with high-resolution and precision in the striatum using state-of-the-art genetically encoded biosensors combined with modern optics in awake animal imaging. The striatum is crucial for movement, learning and flexible behavior, with striatal DA and ACh both playing key roles in these functions. While the role of DA is relatively well established, the role of ACh in natural behavior still remains enigmatic. Cholinergic interneurons (CINs), the major source of striatal ACh, are involved in processing contextual information that guides flexible behavior. Locally, CINs also exert control over striatal DA release, hijacking DA axons and making them release ACh by activating nicotinic receptors near their terminals. We propose to image the spatiotemporal dynamics of striatal DA and ACh using two-photon microscopy and endoscopy in awake mice engaged in tasks requiring behavioral flexibility. To image DA and ACh simultaneously during behavior we will extend the color-spectrum of DA and ACh biosensors. We will also further optimize the performance of these biosensors to make them suitable for robust in vivo application. Our combined interdisciplinary but complementary expertise – in biosensor engineering, imaging, modelling and behavior – is essential for our aims. We will ensure a coherent, interactive approach by sharing procedures, behavioral tasks, and biosensor technology, with regular planning sessions and feedback of results. A successful outcome of this program will reveal, for the first time, the spatiotemporal coding of neuromodulatory signaling by DA and ACh and how it shapes the function of striatal circuits during flexible behavior. We will also obtain a mathematical understanding of the genesis of the spatiotemporal dynamics. The newly engineered sensors developed in the program will have further broad applications in various biological systems of interest, which will ultimately pave the way toward a more complete understanding of brain function at synaptic, microcircuit, and behavioral levels.

Neuronal circuits store information through the mechanism of synaptic plasticity, a process where synaptic transmission is strengthened or weakened. Long-term potentiation (LTP) is a major form of synaptic plasticity. It requires both activation of CaMKII and subsequent trafficking of receptors and other proteins to the postsynaptic site. Despite extensive research, the causative relationship linking these two processes is still unknown. Here, Hayashi (live imaging and electrophysiology), Zhang (structure biology), and Lucic (cryoelectron tomography) will team up and take a unique minimalist approach to reconstitute synaptic plasticity from purified proteins. We will reconstitute postsynaptic density (reconstituted PSD or rPSD) on a glass substrate using a group of key scaffold proteins (PSD-95, SynGAP, SAPAP, Shank, and Homer) and receptor such as NR2B. Once a key process is found in minimal system, we will test if the same mechanisms work in intact neurons. Finally, we will investigate the persistent modification of the rPSD induced by the activation of CaMKII, which is expected to act as a hub for trafficking of various proteins. The network organization of the resulting complexes in vitro and in situ will be determined by cryo-electron tomography. The final goal of this proposal is to understand the minimum essential machinery for activity dependent delivery of postsynaptic proteins.

We propose to use new tracking technology and computational modeling to determine how vocal communication influences collective behavior in animal societies. Canonical examples of collective movement such as bird flocking and fish schooling involve cohesive groups making short-term decisions in a shared context. However, many animals form stable social groups that coordinate and cooperate over extended time spans, across varying distances, and in diverse contexts. In these stable animal societies, group members must make decisions despite varying access to information and exposure to the costs and benefits of coordinating. Moreover their decisions are likely to be shaped by the long-term social relationships among group members. To achieve coordination in such systems, many species use sophisticated signaling systems, such as vocal communication, that transfer information among group-mates. Animals can flexibly control the vocalizations they produce independent of their movements, resulting in a complex interplay between signaling and movement that ultimately drives group-level outcomes such as collective decisions and coordinated actions.
To understand the mechanisms underlying coordination in animal societies, we will record movements and vocal signals concurrently from all members of wild animal groups at a high resolution, and across varying degrees of spatial dispersion. We will compare three mammal species that face a common set of coordination task, but differ in cohesiveness: meerkats form highly cohesive groups, coatis are moderately cohesive, and spotted hyenas live in fission-fusion societies. In each species, we will 1) fit at least one entire social group in the wild with tags that continuously record fine-scale movements and vocalizations, 2) combine supervised and unsupervised machine learning to identify animal calls and movement states, 3) develop modeling approaches to reveal how animals integrate spatial and acoustic information, how information flows through groups, and how social interactions give rise to collective outcomes, and 4) conduct audio playback experiments to isolate causal factors driving collective dynamics. Combining these approaches with long-term data from field studies will shed light on both unifying features underlying coordination mechanisms across animal societies and differences imposed by distinct constraints.

Octopuses have highly complex brains and are capable of many advanced behaviors that involve cognitive abilities. However, their brains and nervous system evolved completely independently from those of vertebrates, and it is largely unknown how the brains of such seemingly “alien” animals perform vertebrate-like sensory and cognitive functions with this distinct brain organization. In this proposal, we will study how visual sensory information is processed and stored in the octopus memory system. In order to overcome the technical obstacles to achieve this, we will bring together two labs with complementary expertise. The Niell lab studies the visual system of mouse, using calcium imaging of neural activity to understand how cortical circuits perform the computations that underlying visual perception and behavior. The Hochner lab studies learning and memory in the octopus vertical lobe. They have used electrophysiological tools and behavior to show that the vertical lobe is organized in a simple fan-out fan-in architecture and demonstrates robust activity-dependent synaptic plasticity. However, these current experimental methods are not sufficient for understanding how learning and memory networks store sensory features that are likely represented sparsely in the activity of many individual neurons.

Together, we will implement two-photon calcium imaging techniques for the octopus brain, to directly observe how sensory information from the eye is processed and represented in the visual system as it is conveyed into the central brain. We will then measure how this information is stored in patterns of activity across the large population of small neurons in the memory centers of the octopus brain, within a learning paradigm. In other words, we will watch memories being formed from a visual input. We will also perform manipulations that will allow us to determine the role of synaptic mechanisms and neuromodulation that enable this storage and its modulation by reward and punishment signals. The result of this collaborative endeavor will be a comprehensive view of neural information processing, from sensory input to memory formation, in the unique and enigmatic brain of the octopus.

The cerebral cortex is composed of distinct subtypes of neurons organized in circuits allowing high-order functions such as integration of sensory stimuli and sensorimotor transformations. These different neuronal subtypes are connected with neurons located both within and outside of the cortex. Intracortical connectivity is mostly mediated by layer (L) 2/3 neurons, which form synapses with other cortical neurons within and across areas; instead neurons located in L5B project to sub-cerebral targets and are responsible for cortical output.
While the molecular diversity of cortical neurons and their circuit organization is increasingly understood, it is still difficult to genetically manipulate cortical neurons based on which circuits they belong to; the ability to do so would, however, be a critical skill to repair circuits when they are affected by injuries or neurodegenerative diseases. To address this challenge, here we combine our expertise in developmental neurobiology (DJ) and in bioengineering (WL) to develop a strategy to manipulate gene expression in cortical neurons in a circuit-dependent manner. We do so by engineering artificial synaptic contact-dependent signaling cascades to drive new cellular features.
Specifically, we will:
1. Assess the in vitro molecular identity and connectivity of pure populations of L2/3 and L5B cortical neuronal types and manipulate these cellular features by direct reprogramming of L2/3 neurons into L5B neurons (Aim 1).
2. Manipulate gene expression and cellular features of L2/3 neurons in vitro in a synaptic-contact dependent manner by developing a synaptic version of the synthetic notch (synNotch) receptor system (synsynNotch) (Aim 2).
3. Manipulate axonal projections of specific populations of intracortically-projecting neurons in vivo using the synsynNotch system (Aim 3).
Together, these experiments will increase our understanding of the mechanisms controlling cell-type specific circuit assembly and allow us to functionally interrogate this process through circuit-specific manipulation of gene expression.

Protein sequencing remains a challenge for small samples. A sensitive sequencing technology will create the opportunity for single-cell proteomics and real-time screening for on-site medical diagnostics. We will use our expertise of single-molecule protein detection and material sciences to develop novel sequencing tools. In particular, we will use graphene mass sensors to measure the mass of proteins with sub-Dalton sensitivity. Utilizing this high sensitivity, we will measure the mass of protein fragments and identify the sequence of the fragments. We will also apply this method for detecting post-translational modifications of single proteins. Ultimately we aim to achieve sequencing of full-length proteins. This proof of concept will open the door to single-molecule protein sequencing and pave the road toward the development of a new, fast, and reliable diagnostic tool.

The world is characterized by an unequal distribution of resources. To cope, many organisms evolve symbiotic trade partnerships to exchange commodities they can provide at low cost, for resources more difficult to access. Such trade partnerships allow species to colonize extreme environments and survive resource fluctuations. While the ubiquity and importance of trade partnerships has been established, we do not understand the chemical, physical, and environmental stimuli mediating trade strategies, nor how organisms integrate this information to execute trade ‘decisions’. This is largely because of the lack of tools to quantify symbiotic trade across space and time.
Combining biophysics, fluid mechanics, network theory and evolution, we will develop techniques to track, quantify and predict trade strategies in symbiotic networks formed between plants and their arbuscular mycorrhizal fungal partners – a globally ubiquitous trade partnership fundamental to all terrestrial ecosystems. By visually monitoring the trade of nutrients tagged with fluorescent quantum-dot nanoparticles across scales - from within individual fungal hyphae up to complex plant-fungal networks - we will ask: (1) how do oscillatory flow patterns within fungal networks act to regulate fungal trade decisions; (2) can the fungus manipulate its chemistry and physical architecture to maximize nutrient transport and trade benefits; (3) can trade strategies be predicted by environmental stimuli; (4) what is the influence of the external microbiome on trade behaviors.
Using high-resolution video to track fluorescently tagged nutrients within hyphae, we will be the first to test how the fungal symbiont regulates internal flows to mediate trade. We will develop 2D and 3D time-lapse imaging of network topologies to test the factors driving the optimization of fungal transport routes. We will use transformed in-vitro root systems with precisely controlled nutrient landscapes to correlate specific trade strategies with environmental conditions. We will push the frontiers of tracking trade in whole plant mesocosms by growing plant-fungal networks on transparent farming film, characterizing how synthetic microbiomes affect trade strategies. By integrating the state of the art in imaging, fluid mechanics, and ecological manipulations, we will achieve a quantitative and predictive understanding of organismal trade.

Animal mitochondrial DNA (mtDNA) has a higher substitution rate than nuclear DNA, with the accumulation of mtDNA mutations being one of the hallmarks of ageing. This discrepancy in the rates of evolution is partially due to the lack of mismatch repair activities in the mitochondria. Octocorals – a group of cnidarians – have a reduced rate of mitochondrial evolution and encode a MUTS-like protein (mt-MutS) in their mtDNA. Previous analyses suggested that this enzyme was acquired from a virus and has been universally retained among octocoral taxa. Its function, however, remains unknown. The project will combine comparative, structural, and experimental approaches to investigate the function of mt-MutS and to test whether mt-MutS expression results in lower mutation rates in mtDNA and improve heath in ageing. Comparative analysis of octocoral mtDNA will be used to identify distinct mutation patterns among its lineages and correlate them with the changes in mt-MutS. Partial mt-MutS sequences will be used to identify clades with unusual or accelerated rates of mtDNA evolution for additional sampling. Site- and taxa-specific evolutionary rates in mt-MutS will be analyzed to infer functional and structural constraints and to optimize the choice of the mt-MutS for transgenesis. Ancestral sequences of mt-MutS for the nodes of interest will also be reconstructed and analyzed. A structure-function approach will be utilized for in vitro dissection of mt-MutS functions. The full-length proteins from several species and a reconstructed ancestral sequence will be tested for stability and for amenable structure determination. Isolated domains will also be used for high-resolution structural analysis by diverse biophysical techniques to probe molecular details of binding and nuclease activity for understanding and improving function. Finally, we will generate transgenic mice that express a mitochondrially-targeted version of this optimized mt-MutS enzyme to test its effects on mtDNA mutation rate. The transgene construct will be knocked-in to mice by directed Easi-CRISPR template repair or BAC-transgenesis. mtDNA mutation rate analyses in wildtype and mice with enhanced mitochondrial mutation rates will be undertaken. An ageing study on mice expressing mt-MutS will determine if enhanced mtDNA fidelity can positively affect organismal lifespan and healthspan.

Approximately 30% of mammalian genes code for transmembrane proteins, which comprise the majority of signal receptors and transducers. These functions are not solely encoded in protein structure, but are also regulated by the unique physicochemical environment of mammalian membranes. A key unmet challenge is to understand the interplay between the composition of membranes, their collective physical properties, and their resulting effect on protein function. The knowledge gap is especially apparent for mammalian neural tissue, whose membranes are highly enriched in omega-3 polyunsaturated fatty acids (PUFAs), which our bodies do not synthesize. This composition is central to neural function as evidenced by brain lipid alterations in numerous developmental, psychological, and neurodegenerative disorders; however the mechanistic relationships between the brain’s unique lipid composition and neurological functions are unknown. Major open questions are how neuronal function is influenced by the lipid content of the membranes that host neural signal transduction receptors, and how factors like diet and environment can influence those lipid compositions. Here, we assess the paradigm-shifting hypothesis that alterations of neuronal membrane lipid composition affect the signaling in the brain and contribute to the pathogenesis of neurological disorders. Particular emphasis is placed on the role of dietary lipids in modulating membrane composition, and the functional consequences thereof. Breakthroughs in understanding the central role of lipids will emerge from the project’s interdisciplinary crosstalk between detailed comprehensive lipidomics, molecular computer simulations, quantitative cellular biophysics, and molecular neurobiology. We focus on two parallel research streams: pattern-recognition receptors and G protein-coupled receptors, which are here used as representative systems to explore the regulation of neural receptors by lipids in a pipeline involving computational, synthetic, and natural model systems, as well as cultured cells and in vivo studies. As the influence of lipids on neuronal receptor function has so far been almost completely ignored, these studies will generate significant impact. Further, the modulation of membrane composition by diet may provide important translational insights and drug-free therapeutic strategies.

Optical nanostructures are highly organized composites of materials with varying refractive indices (e.g. keratin, melanin and air) that produce some of the brightest colors found in nature through coherent light scattering. How these tissues organise themselves at the nanometer scale to produce colors is poorly understood, despite its fundamental significance to developmental and evolutionary biology and potential to spark advances in the biomimetic design and "green" commercial manufacture of self-assembling optical materials.
We thus propose to use both transcriptomic, laser diffraction and microscopy-based tools of developmental biology to elucidate the mechanisms by which these nanostructures self-assemble in a subsample of birds (Class Aves), a group with incredibly diverse structural colors and mechanisms. Our working hypothesis is that iridescent colors form through depletion-attraction, phase separation and other self-assembly mechanisms. Because most developmental biology is done at larger size scales, testing these hypotheses will require the use and development of methods such as wet cell TEM and in situ laser diffraction analysis to adequately resolve nanometer-scale changes in developing tissue. We will then test these proposed mechanisms using biomimetic approaches that replicate natural conditions as closely as possible (e.g. at room temperature,at biological pH) using natural or semi-natural materials. Use of optical techniques including angle-resolved spectrophotometry and microspectrophotometry will enable us to compare these properties between the natural and synthetic versions. This approach will enable us to not only experimentally test modes of development but also generate and test new materials and/or processes to produce them.
There are three highly innovative aspects to this proposal. First, it attempts to unlock the developmental pathways producing nanostructured tissues. This is a long-standing question with few answers thus far. Second, it uses biomimicry in novel ways to test developmental hypotheses and pushes the technical boundaries of developmental biology by focusing on nanometer-scale organisation of tissues. Finally, the use of biologically realistic chemistry in our biomimetic approaches is a huge leap forward in this field where most work is done at high temperature or with non-biocompatible materials. This work will therefore significantly advance both our fundamental understanding of these materials and the tools to study them and other nanoscale materials.

The OXPHOS system is the only process in animal cells with components encoded by two genomes, maternally transmitted mitochondrial DNA (mtDNA) and biparentally transmitted nuclear DNA (nDNA). The protein products of both genomes have to physically assemble with their counterparts to build functional respiratory complexes. Therefore, variability in the OXPHOS encoded genes is limited by a physical match constraint. This imposes a close-fitting co-evolution of both genomes challenged by the very different mechanism to generate variability for nDNA (by sexual reproduction, mutation and co-existence of two alleles) and mtDNA encoded OXPHOS genes (by mutation, polyploidy and segregation). Since the simultaneous co-existence of alternative mtDNA encoded alleles for OXPHOS proteins has been shown to be detrimental for the organism, we postulate that the co-expression of nuclear encoded alternative alleles may have similar adverse consequences, and that specific regulatory mechanism prevent them. Indeed, random mono-allelic expression is not rare and was suggested for about 30 OXPHOS genes in mice. We postulate that is part of a sophisticated and multi-level system of quality control and functional testing to select for the best combination for providing metabolic plasticity.
Potential regulatory mechanisms are: selective transcription of one allele per cell or selection of the expressed alleles at the import or assembly of the OXPHOS complexes. For testing this hypothesis, we integrate different skills for the analysis of mitochondrial functional and genetics profiling (Enriquez), single cell transcriptomic (Eberwine) and functional and dynamic analysis (Busch) in mouse (Enriquez) and zebrafish (Mercader). If confirmed, we will set the ground for a novel theory of genetic interaction for OXPHOS function. If discarded, the existence of mtDNA and its particular way of inheritance would be necessary to group those genes for which allelic variability is detrimental.

One of the most basic aspects of sleep is that it happens at a particular time of day. Neuroscientists have known for almost half a century that this consolidation requires the suprachiasmatic nuclei of the hypothalamus (SCN); beyond this point, the circuit remains untraced. Equally mysterious, healthy young humans sleep in a single consolidated bout, while infants and older individuals, as well as laboratory mice, can have highly fragmented sleep. Informed by a combined cellular and circuit-based model for slow-wave or “deep” sleep (Forger Group), we propose to trace the signals leading from SCN to cortical slow waves at both physical and molecular levels, and then manipulate them to artificially consolidate sleep. Starting from cortex, aided by a novel “triple-CRISPR” approach to generate knockout mice efficiently in a single generation, we shall examine roles of individual cortical ion channels and the signaling pathways they regulate in creating these slow waves both in vivo and in newly developed whole-brain culture (Ueda Group). This information will be incorporated into a cellular and then a thalamocortical model of slow-wave sleep (Forger Group). In parallel, synaptic tracing in cleared brain, as well as calcium imaging correlation analysis using miniature skull-mounted microscopes, will establish physical and functional connectivity from SCN to cortex (Brown Group), which can also be tested in whole-brain culture (Ueda group). Modeling these data comprehensively and then optimizing this whole-brain model (Forger group), we can predict and test molecular sources of homeostatic and circadian influence upon sleep, as well as combined transgenic and optogenetic strategies to create consolidated bouts of sleep from the normally fragmented sleep of the mouse (Brown and Ueda groups). In this way, by using the power of large-scale quantitative modeling to explore synergies in sleep-dependent signaling, we hope to provide a starting point for novel multimodal therapies with the capacity to fundamentally alter the sleep-wake landscape.

Enhancers are relatively short DNA sequence elements (<1 kb) that determine the timing, location and levels of gene transcription. They harbor specific binding sites for transcription factors (TFs) that control the enhancer. While the necessity of particular TF binding sites (TFBSs) can be assayed with mutations, it is not yet understood which DNA features in an enhancer sequence collectively give rise to the regulatory activity. To identify the molecular determinants that impart a regulatory activity to a DNA sequence element, we have devised a quantitative experimental paradigm and propose to apply statistical analysis and machine learning approaches to the molecular dissection of a model enhancer.
Specifically, we will use a model enhancer driving patterned spatial expression in the wings of fruit flies (Drosophila). First, we will create tens of variants of this enhancer, introducing mutations along its sequence, and describe their regulatory effect. To this end, we will build an automated imaging pipeline to measure the levels and spatial distribution of reporter gene in the wings. The resulting quantitative expression data in a flat tissue will define a morphospace, i.e., a mathematical multidimensional space representing the possible variation of enhancer activity. Second, we will extract DNA feature sets to quantitatively describe molecular variation along the sequence of our mutant enhancers. This will capture structural changes (DNA shape readout), changes in nucleotide sequence per se (DNA base readout), as well as other features (e.g., TFBSs). Third, leaning on dimensionality reduction techniques and machine learning, we will develop predictive models that describe the relationship between DNA features and morphospace. Finally, we will test our predictions of enhancer functionality using synthetic enhancers in transgenic flies. Because enhancers are complex biological objects, we aim with this proposal at developing appropriate mathematical tools to capture the essence of this complexity.
Since this proposal aims at developing a comprehensive mathematical approach to modeling of enhancer functionality, it has the potential to unravel complex molecular mechanisms underlying transcriptional regulation.

We propose to investigate how dietary restrictions (DR) affect aging from a new angle by using social insects as models. Aging is a hallmark of most bilateria and most animals balance their reproduction rate against lifespan. Intriguingly, this trade-off is inverted in reproductive individuals (queens) of social insects (termites, ants, bees). Whereas most studies on aging directly manipulate the lifespan, e.g. of mice or worms or other lab-bred animals, we here propose a radically new approach by employing easily accessible and natural extremely long-lived termite queens as models. Their metabolism, response to DR and fertility will be gauged against genomically identical bu infertile and short lived workers, as well as shorter lived and less fecund queen of a closely related termite species. We will sample termite colonies directly from the field, keep them, expose them to DR and measure their fitness and fecundity. We will examine the role of DR during colony development by sampling transcriptomes, analyzing their epigenetic status, their metabolome and endocrine status and performing in-depth molecular analyses of key molecular components that are known to be implicated in regulating aging and fecundity. Using multiple OMICS methods, reverse genetics, hormonal and dietary administration we will be able to disentangle pathways involved in development of queens and measure the impact of energetic metabolic reprogramming on fitness and reproduction status. Expression patterns and spatio-temporal changes of genetic networks will be used to develop a simple state model. In this model, the metabolic status can be used to predict an individual's trajectory of aging and fecundity depending on its epigenetically imprinted background such as it's caste. Our project thus establishes a new model system for studying the relationship between DR, aging and fecundity, in which the latter two are decoupled and comparison of our model to other model organisms will help understand which dependencies and molecular components have universally conserved interaction partners or phenotypic effects. The project is possible only due to the four participants from three continents, with expertise in dietary research, energy metabolism, field research and social insect genomics.