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.

The phenotype of an animal cannot be explained entirely by its genes. It is now clear that factors other than the genome contribute to the development and dynamic homeostasis of animals. Two fundamentally important factors are epigenetic regulations and the microbial communities associated with the animal. Unlike the genes and regulatory regions of the genome, epigenetics and microbial composition can be rapidly modified by environmental cues, and may thus represent mechanisms for rapid acclimation to a changing environment. At present, the individual functions of epigenetics, microbiomes, and genomic mutations are largely studied in isolation, particularly for species in marine ecosystems. This leaves significant questions open for how these mechanisms intersect in the acclimation and adaptation of organisms.
The aim of this research is to determine how epigenetic regulations and microbial communities participate in thermal acclimation of a coastal marine species residing in a dynamic temperature environment, and how these non-genetic factors interact with each other. The model species used for this study, the sea anemone Nematostella vectensis, enables us to carry out unprecedented functional experiments to dissect the interactions between microbes and epigenetic mechanisms in the acclimation of the holobiont.
We will first monitor the physiological, transcriptomic, epigenetic and microbial changes associated with thermal acclimation. We will then separate the effects of microbial and epigenetic effects in a series of bacterial transplantation experiments. Finally, we will carry out gene knockdown and over-expression experiments to elucidate the function of host genes in epigenetic regulations and the plasticity of the microbiota. We hypothesize that changes in the microbial community improve the thermal tolerance of the host, and the epigenetic landscape is responding both to shifts in temperature and altered microbial composition.
Studying these interactions will require a concerted effort drawing on the diversity of expertise across our three research groups. Our results will have important consequences for our understanding of the response of marine species to climate change, and more broadly they will shed light on many unanswered questions regarding the role of epigenetic regulations and microbes in animal ecology and evolution.

Mouse and human mutations in the RNA-binding protein Bicaudal-C (Bicc1) are associated with cystic kidneys that are reminiscent of hereditary polycystic kidney diseases (PKD) (Cogswell et al., 2003; Kraus et al., 2012; Maisonneuve et al., 2009). Direct mRNA targets of Bicc1 include adenylate cyclase 6 (AC6) and PKA inhibitor (PKIα), members of the cAMP/PKA signaling pathway (Piazzon et al., 2012), and Ddx5, a gene encoding a RNA helicase of unknown renal function ((Zhang et al., 2013) and unpublished results). In addition, Bicc1 stimulates the transcription and translation of polycystin-2, although these effects are likely indirect ((Tran et al., 2010), and unpublished results). More recently, the Constam lab found that endogenous Bicc1 in kidneys also binds the protein Inversin (Invs), which is mutated in nephronophthisis type 2 patients (Florian Bernet, PhD thesis, unpublished). How this complex is de-regulated and its role in cystic diseases remains obscure. The objective of this project is to develop molecular biology tools to characterize the regulation of Bicc1 activity by Invs and calcium signaling. Novel fluorescent and affinity-tagged versions of Bicc1 and their targeted insertion at the endogenous locus will be used for live imaging experiments, co-localization studies and co-purification of interacting factors to investigate how the de-regulation Bicc1 silencing activity triggers cystic disease. Outcomes of the proposed experiments will help to improve our knowledge of cyst development and to explore new therapeutic avenues.

The acquisition of novel traits is a central pillar in evolutionary biology. Adaptive radiation is recognized as a major process that leads to a rapid diversification of the progeny of a single ancestor into a number of functionally different, genetically isolated populations. Adaptive radiation is proposed to be driven by rapid adaptation to new or underutilized ecological niches that leads to phenotypic diversification and eventually to speciation. Experimental evolution of unicellular prokaryotes can produce adaptive radiation in a controlled environment, but this process and its population dynamics and genetic basis has not been studied in eukaryotes. Here, I propose a novel approach for experimentally inducing adaptive radiation in a eukaryotic model organism (S. cerevisiae). By evolving parallel yeast clones in the simultaneous presence of several, different nutrient sources that cells cannot exploit, I aim to evolve the ancestral form into separate populations, each occupying a different, novel metabolic niche. By barcoding lineages and exploiting next generation sequencing techniques, I plan to reveal the population dynamics and adaptive mutations that allow cells to evolve new metabolic traits. I will evolve both haploid and diploid cells to test the influence of genomic architecture on the radiation process; for example do loss of function mutations drive radiation of haploids, whereas gain of function mutations predominate in diploids, and does niche specialization alter mating preference or reduce the fitness of the products of inter-population matings?

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.

Synchronization in connected populations is routinely encountered in a variety of situations ranging from epidemic outbreaks to species extinction. This research proposal aims to explore the effect of nonlocality and heterogeneity, which are hallmarks of real world ecological and epidemiological networks, on the conditions for synchronization. The proposed research aims to employ experiments as well as computer simulations to better understand the emergence of synchronization in networks of connected populations. The chief goal of the proposed computational model is to construct a ‘phase diagram’ which demarcates regimes corresponding to the presence and absence of synchronization in a three-dimensional parameter space comprising of the migration rate, the degree of nonlocality and the degree of heterogeneity. The second aim is to elucidate the nature of the transition from synchronous to asynchronous behaviour as one of the three parameters is changed. The proposed experiments aim to employ a model bacterial system recently developed in the Gore lab to directly test the model’s predictions. The experiments involve simultaneously growing bacterial cultures and periodically measuring population densities using spectrophotometry and flow cytometry. Migration is facilitated by mixing a fixed fraction of a given culture with its neighboring cultures. Nonlocality and heterogeneity can be tuned by choosing appropriate neighbors for mixing. The extent of synchronization can be quantified directly from the population time series data. Results from these experiments and simulations will be of direct relevance in organizing conservation as well as vaccination programmes.

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.

Retinotopy, the pattern of axonal projections in visual processing centers that preserves the spatial arrangement of photoreceptor (PR) in the retina is a key feature of any complex visual system. I offer to investigate how retinotopy is built in the Drosophila visual system focusing on the medulla neuropile. Medulla neurons are generated sequentially by the Outer Proliferation Center and build 800 columns onto which inner PRs (R7 and R8), also sequentially generated along a posterior to anterior axis in the eye disc by the progression of the morphogenetic furrow, project retinotopically.

To find what are the medulla neurons that support PR retinotopic projections, I will first generate tools to visualize medulla column generation and test by a genetic approach several neuronal populations. I will then determine whether developmental synchrony between the waves of differentiation in the eye disc and medulla is required along the antero-posterior axis for PR retinotopic projection onto medulla columns. I will genetically modulate the speed of both waves in order to desynchronize them and look for retinotopic defects. I will then investigate how those two waves are coordinated. In parallel, I will find genes responsible for dorso-ventral patterning of the medulla by a differential transcriptomic strategy. I will purify ventral medulla neurons by intersectional approaches and compare their expression profile to the entire medulla neuron population.

Completing those three aims will allow me to uncover the developmental rules and signaling pathways responsible for building a complex and immensely precise architecture such as neuronal retinotopic maps.

Enhancers and core promoters are key regulatory elements underlying the precise spatio-temporal regulation of gene expression. Despite recent efforts to map and characterize these elements genome-wide, it is still unclear how their activities are encoded in the genome. Moreover, we are just beginning to unravel the role of the specificity between enhancers and core promoters in transcriptional regulation.
Novel genome-wide activity-based assays for identification of enhancers and core promoters (STARR-seq and its variant) developed in the host lab provide a unique opportunity to quantify sequence-encoded activities in a highly controlled manner. In collaboration with the experimentalists I propose to apply STARR-seq in human cells to measure both enhancer and core promoter activities and assess their specificity. Using these data I will apply sequence analysis and modeling approaches with an aim to establish a quantitative relationship between sequence and activity for both types of elements. I am aiming to reveal differences and commonalities in sequence requirements for a genomic region to act as an enhancer or as a core promoter, allowing me to build a comprehensive model of transcriptional regulation in human. Given the diversity of mammalian core promoters, I will also test whether enhancers and core promoters exhibit mutual preferences and will attempt to uncover sequence determinants underlying such specificity. Finally, using published datasets I will assess how these intrinsic activities are modulated by the endogenous chromatin and sequence context. My results will further our understanding of gene regulatory elements and their interpretation by human cells.

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.

The adult mammalian stomach epithelium is constantly renewed by proliferative isthmus stem/progenitor cells (ISPCs) and maintains its homeostasis under hostile luminal conditions. In the gastric corpus epithelium, differentiated Troy+ chief cells were identified as a novel stem cell population with high plasticity. Interestingly, Troy+ stem cells (TroySCs) can switch between a dormant and active state. TroySCs proliferate very slowly in homeostasis, whereas they rapidly divide upon ISPC loss facilitated by 5-FU treatment. This suggests its role as a reserve stem cell for the ISPC. However, TroySCs are also activated upon parietal cell loss despite the presence of actively cycling ISPCs. Thus, the role of TroySCs still remains vague in homeostasis and regeneration from various injuries. Here, I propose to investigate a potential role of TroySCs, beyond that of the reserve stem cells, by combining state-of-the-art mouse genetics, single cell transcriptome analysis, and mathematical modeling. First, I will characterize the population dynamics of the corpus epithelial cells under homeostasis and regeneration by lineage tracing and single cell analysis in mice. Second, based on the cell population data, I will construct a mathematical model for the corpus epithelium and theoretically investigate the function of TroySCs by perturbing their dynamics. Third, I will experimentally examine the role of TroySCs using in vivo and in vitro functional genetics. This work will reveal an essential role of quiescent stem cells in homeostasis and pathogenesis and shed light on a fundamental question about why quiescent and active stem cell populations coexist in various adult tissues.

Engineering of recombinant pathways in microbial hosts is a powerful tool to provide access to sustainable building blocks for the chemical industry. Such a bottom-up synthesis route has recently been established for monomeric phenylpropanoids. However, the yield and diversity of products obtained are still lagging behind their natural plant biosynthetic pathways. The aim of the herein described project is to explore and develop tools for the reconstitution of plant metabolic pathways in bacterial hosts: namely, tools for the availability of bacterial strains as framework, for protein engineering and for identifying novel pathway enzymes for crucial product tailoring steps.

Therefore, I propose to investigate the applicability of Corynebacterium glutamicum as a bacterial chassis for plant metabolic pathways in general and the phenylpropanoid pathway in particular. I am going to develop genetic tools based on the CRISPS/Cas9 system to allow the fast incorporation and screening of various pathway enzymes and promoter combinations. I furthermore propose to investigate the effect of tethering Cytochrome P450 (P450) enzymes – a typical bottleneck in reconstituted pathways - to their redox partners, on in vivo P450 activity. Lastly, I propose to investigate the correlation of sequence, structure and function of crucial product tailoring O-methyltransferases from various organisms to enable the classification of such enzymes based on sequence homology.

The proposed study will not only increase the efficiency of the synthetic phenylpropanoid pathway but provide tools to further our abilities in manipulating microbial hosts for fermentative production of valuable chemicals.

The biggest challenge in glioblastoma research is to understand the inherent cellular heterogeneity. While much research has been dedicated to glioblastoma stem-like cells (GSCs), a small population of tumor cells that resides at the apex of a differentiation hierarchy and underlies therapy resistance, differentiated glioblastoma cells have not received the same attention.

I hypothesize that glioblastoma is characterized by a previously underestimated extent of cellular differentiation. Dedicated differentiated cell types provide the tumor with a selective advantage, e.g. by promoting angiogenesis and evading the immune system, and by supporting GSCs with essential maintenance and cell division cues. Therefore I propose to accurately define the cellular composition of primary human glioblastoma using microfluidics-enabled transcriptome profiling of thousands of individual cells. Using sophisticated computational methods, this dataset will reveal previously unrecognized cell types, and inform on their roles in tumor formation. Additional epigenetic characterization of tumor cell subpopulations will define cell type specific gene regulatory networks and inform on the molecular consequences of common genetic alterations.

I further hypothesize that tumors of different patients are composed of varying stem-like and differentiated cell types and that cell type frequencies differ between patients. Incorporating the new information on tumor heterogeneity will allow me to redefine glioblastoma subclassification. This will lead to more accurate patient prognoses, and ultimately to the development of subtype-specific therapies and the design of more targeted clinical trials.

The endosomal system is regulated by the interplay of distinct endosomal classes and its interactions with other cytoplasmic organelles within the cell. Identifying the molecular players and mechanisms that regulate the endomembrane system is essential because defects in the system are implicated in human disorders. The previous genome-wide RNAi screen performed in the host lab found numerous metabolic and signaling genes known to be localized to other cellular organelles that affected epidermal growth factor (EGF) and transferrin trafficking, underscoring the importance of inter-organelle communication. However, little is known about the underlying molecular mechanisms. In this proposal, I will perform a focused RNAi screen using a quantitative multiparametric analysis in order to identify factors governing intra-cellular positioning and functional interactions between distinct endosomal classes, such as early and recycling endosomes. I will also search for organelle-specific genes belonging to endoplasmic reticulum, mitochondria, lipid droplets, and peroxisomes that are functioning at the membrane interface with endosomes for inter-organelle tethering and signaling. Finally, I will investigate the physiological function of candidate genes in a primary cell culture system. The project outcome will lead to a better understanding of the endosomal system and the molecular mechanism of inter-organelle communication.

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.

In order to ensure genome stability, DNA repair is highly regulated by the cell division cycle. A major, but largely unexplored question pertains to mechanisms that promote genome stability when DNA damage occurs on segregating chromosomes. My host laboratory discovered that cells suppress the repair of DNA double-strand breaks (DSBs) in mitosis to prevent chromosome segregation errors. These occur as a consequence of repair-mediated telomere fusions. The overarching objective of my project is to address the biological significance of mitotic DSB repair inhibition in vivo by generating a transgenic mouse in which I can conditionally de-suppress DSB repair in mitosis. This system will enable me to identify the tissues and developmental processes sensitive to the genome instability caused by mitotic DSB repair and to test whether inhibition of mitotic DNA repair is a tumour suppression mechanism. In parallel I will elucidate the molecular mechanism that causes the observed telomere fusions. Based on previous results, I hypothesize that the kinase Aurora-B mediates mitotic telomere uncapping through targeting of the telomeric Shelterin complex. I will test whether active Aurora-B localizes to telomeres using a FRET-based activity sensor and identify its target among the Shelterin subunits. Since telomere fusions are enhanced upon exposure to ionizing irradiation, I will also clarify the crosstalk between Aurora-B and the DNA damage response. This project comprises phenotypic animal studies and mechanistic cell based studies and thus represents a major departure from my previous work on the genomics of yeast DNA replication.

Muscle resident stem cells, Satellite Cells (SCs), maintain tissue homeostasis and regenerate skeletal muscles. In the event of an injury or stress, SCs break from quiescence, proliferate and differentiate or self-renew. Metabolic activity controls stem cell proliferation and differentiation in young healthy mice. However, whether metabolic activity is altered during aging in SCs and/or niches is poorly studied. Furthermore, whether cell autonomous or non-autonomous metabolic effects drive age-dependent SC functional decline is completely unknown. Our objective of this proposal is to use metabolic profiling in SCs and their niche during aging to identify a novel stem cell-to-niche communication mechanism. We speculate that upon aging, SCs accumulate lactate that causes a loss of stem cell function. In addition, we speculate that shuttling of lactate, the end product of glycolysis, from muscle fiber and taken up by SCs is a major contributor to the SC metabolic state and functional decline during aging. In this proposal, we will generate 1) metabolic profiles of adult and aged SCs and their niches, 2) in vivo inducible cell-specific genetic mouse models to delete lactate dehydrogenase A (LDHA) from SCs and niche, and 3) in vitro approaches to disrupt lactate signaling between the niche and SCs using lentiviral knockdown constructs targeting lactate transporters (MCT1-4) and receptors (GPR81). We will use muscle regeneration assays to evaluate the role of lactate signaling on stem cell function and tissue repair during aging in vivo. These data will provide novel insights toward stem cell-niche interactions as well as further our understanding of aging biology.