Medulloblastoma is the tumor of the cerebellum and is the most common brain tumor in children with overall survival rates in the range of 60-80 %. The disease is sub-classified in 4 types based on histology, gene expression profiling and demography. Nevertheless, molecular events causing to the disease progression are largely unknown. With the development of the tools enabling high-throughput characterization of genomes, several studies including the ones of the International Cancer Genome Consortium (ICGC) showed the presence of genomic alterations in medulloblastoma patients. Importantly, these studies identified recurrent mutations in genes involved in chromatin regulation, pointing out to a function of epigenetic mechanisms for disease pathogenesis. However, there has not yet been any study investigating the epigenome of medulloblastoma and link potential findings with genomic mutation data to identify regulatory interactions. In my project, I will characterize the epigenome of medulloblastoma subtypes by profiling histone modifications and integrate my findings with existing genomic and transcriptomic datasets to find out the interplay between genetics and epigenetics in medulloblastoma progression. My project is an extension of the ICGC studies and will substantially contribute to the molecular understanding of this disease, which will on the long term be highly beneficial for the diagnosis and treatment of medulloblastoma.

The emergence of synchrony and complex functionality in excitable tissues such as the heart is based on propagation of membrane depolarization from the ion channel, to cell, to tissue, to organ scale. Understanding how these excitable cells initially couple during embryogenesis, adaptively remodel during development and ultimately de-couple during disease is of primary interest in basic science and disease pathogenesis. We hypothesize that tightly regulated mechanical forces transmitted via cell-cell and cell-matrix adhesions are required for the formation and maintenance of electromechanical coupling. To test this we propose to use cardiac muscle as an excitable tissue system and elucidate fundamental mechanobiological mechanisms by (i) building protein-based nanomechanical biosensors that can dynamically probe strain fields during myogenesis and (ii) using these biosensors in two model systems, the developing heart during cardiac morphogenesis in the embryonic chick as an in vivo system and in tissue engineered cardiac muscle derived from murine haploid embryonic stem cells (haES) and human embryonic stem cells (hESC) to selectively probe the effect of targeted adhesion complex knockouts. The haES cells enable conditional knockout of desmosome proteins to determine which are required for formation of a cardiac syncytium, and with the ability to revert back to wild-type provides a test bed to determine if the diseased tissue can remodel to a disease-free state. Further, the use of the nanomechanical biosensors, which can track strain from 10 nm to greater than 200 µm, enables us to determine how the mechanical strain cardiomyocytes impart on the environment changes. These techniques, coupled with an advanced platform for engineering 3D cardiac muscle and measuring contractility, will lead to mechanistic understanding of how genetic changes alter cardiomyocyte cell-cell adhesion, the mechanical strain that they can impart on their environment and ultimately how this impacts gap junction (connexin) coupling into an excitable syncytium with coordinated contraction. Finally, the specific desmosome genes identified with the haES studies will be targeted with siRNA knockdown in hESC-derived, engineered cardiac muscle to elucidate whether the same mechano-sensitive mechanisms regulate formation of an excitable syncytium in human myocardium.

Continuous location estimation is a difficult computational problem. Roboticists grappling with the problem of noisy sensor measurements, changing features in the external world, and novel environments, find that probabilistic representation and inference of locations yields good performance, but storing and updating a single best-guess about location does not. Animals are capable of spatial navigation performance that equals or bests that of mobile robots. Yet our understanding of animal navigation is predicated on the framework of single-hypothesis tracking; there is little exploration of the compelling possibility that the brain’s spatial representations enable probabilistic coding and inference.
In this proposal, we will directly test the general hypothesis that mammals use probabilistic representation and inference for location estimation. We will address this possibility by combining investigation, in mice and humans, with computational models of probabilistic computation on spatial variables. Applying state-of-the art techniques in computational simulation and theory, in vivo electrophysiology and genetic manipulations in mice, and ultra-high resolution neuroimaging and behavior in humans, we will determine if (i) performance of spatial behaviors, (ii) representation of spatial information by place cells, and (iii) high resolution signatures of activity obtained with fMRI, are each consistent with implementation of probabilistic computations. We will in addition seek to obtain the first evidence for molecular mechanisms that control probabilistic computation. Similar experimental paradigms for animals and humans will ensure comparability of our results between species. Implementation of close reciprocal interactions between the three participating laboratories will ensure that the computational modelling studies generate theoretical predictions for the experimental studies, the results of which will in turn help refine the theoretical models.
Taken together, our multidimensional, interactive approach has the potential to provide the first account of the neural mechanisms that allow our brains to perform accurate spatial computations in the face of sensory uncertainty. This will provide a new conceptual framework for investigation of neural circuits underlying navigation and for integration of experimental results obtained in mice and humans.

During cell entry, adenoviruses import their DNA-genome into the nucleus for replication. This is a significant challenge to the virus because the nucleus contains a physical barrier to infection, the nuclear envelope. Traffic into and out of the nucleus is strictly controlled by the nuclear pore complex (NPC). To overcome this restriction, adenoviruses target nuclear pore proteins to dock at the NPC and mediate selective uptake of viral DNA into the nucleus. Additionally, adenoviruses undergo a stepwise disassembly process. This time-controlled gain-of-function process exposes critical viral proteins, facilitates virus-induced nuclear membrane disruption, and weakens the capsid for DNA release at the NPC. Although several studies have identified viral and cellular factors critical for delivery of adenovirus DNA into the nucleus, the structural and functional organization that drives this process is poorly understood. The objective of this proposal is to elucidate the fundamental mechanisms underlying nuclear import of adenovirus DNA. To analyze this process, we will use cutting edge virus imaging technology including cryo-electron tomography, super-resolution microscopy, and total internal reflection fluorescence microscopy. Successful completion of this project will enhance our understanding of the molecular interactions that allow viral DNA to pass through the NPC and may accelerate the design of new antiviral drugs.

To divide, cells need to equally partition their genetic material such that each daughter cell ends up with one complete set of the hereditary information. This requires that one chromosome of each pair is moved to each side of the cell division plane shortly before the two cell halves separate. Failure to do so, results
in genetically unstable cells.
In eukaryotes, chromosome segregation is achieved by the mitotic spindle, whose size, position and shape thus need to be tightly regulated. The complex interplay between spindle mechanics and biochemistry, that allows for this high level of control is so far poorly understood.

We propose to develop a comprehensive theoretical model of the mitotic spindle which captures the interplay between active mechanics and the reaction diffusion advection dynamics of regulatory proteins. This work will provide the theoretical framework to understand how active liquid crystals, such as the mitotic spindle, can compute mechano-chemical signals to self-regulate their size and morphology.

We will use this framework to understand the morphology of metaphase spindles in Xenopus egg extract focusing on the Ran system which is thought to be involved in the spatial organization of many processes required for chromosome segregation and is believed to control microtubule nucleation rates and thus spindle morphology. In particular, this system is thought to ensure the bipolar structure of the spindle,
with the chromosome in the central plane.

Understanding the genetic diversity and population structure of Plasmodium falciparum is fundamental to plan effective strategies for malaria elimination. Inference of the parasite's demographic history will help monitoring changes in the prevalence of pathogen strains and limiting their spread. Here, I propose to exploit large-scale sequencing DNA data from multiple populations of the parasite, to infer the pathogen's geographic origin, timing of first human infection, and colonisation routes.

My first aim is to estimate P. falciparum genetic variation at the individual and population level from publicly available sequencing datasets, by using state-of-the-art statistical methods to account for data uncertainty. I will then adopt a simulation-based approach to reconstruct the ancient demography of P. falciparum. This ecological modelling will borrow from methodologies previously applied to the colonisation of the world by anatomically modern humans. Specifically, I will use spatially explicit Approximated Bayesian Computation techniques to fit a spatio-temporal evolutionary model through a set of summary statistics. The latter will be chosen to summarise the between-strains genetic diversity for all pairs of analysed parasite populations. To enhance power of our inferences, simulations will be conditional to past climate reconstruction.

The information regarding the inferred parasite's evolutionary origin, spread and global colonisation routes will help developing efficient tests for monitoring malaria spread and informing public health interventions.

Speech has long been believed to be a special stimulus for the human auditory system. However, the acoustic features that make it special and the way in which these are processed by the nervous systems during development have so far eluded a unified theoretical framework. Recent results suggest that the category ‘speech’ itself might need to be revised to include other biological communicative sounds, as young infants process primate vocalizations in the same way as speech. Combining our respective expertise in developmental cognitive neuropsychology and computational and systems neuroscience, we seek to elucidate what class of sounds is special for the human auditory system, why they are special and how they are processed in the infant brain at the level of complete networks. We will assess how neural circuitry is reorganized through pre- and postnatal experience from a broad initial auditory sensitivity to a specialization for the vocalization sounds in general, and more specifically for the native language. Our project seeks to explore the developmental mechanisms of specialization of the human brain for speech and communication.
Geffen recently discovered that the auditory cortex of rodents is specialized for processing conspecific vocalizations. Furthermore, in a pilot collaboration with Gervain, Geffen identified an important statistical feature of natural sounds for human perception. In this project, Geffen undertakes statistical sound analysis to determine the essential parameters of different communicative sounds (primate calls, infant cries, native language speech, non-native speech) and, in conjunction with previously developed methods, will construct synthesized stimuli the perception of which will be tested in infants using brain imaging and behavioral methods by Gervain. Geffen will then use Gervain's data to develop a cortical network model of speech and communicative sound processing in the developing human brain. Geffen will estimate the relative information apparent in the different infant brain areas throughout development and correlate it with progressive stages of language development.
The developmental perspective offers a unique window on the initial biological basis of speech and language before experience occurs. Gervain has discovered that newborns are able to detect repetitions in speech and learn structural rules based on them. Using near-infrared spectroscopy (NIRS), she found that the brain areas responsible for this learning partly overlap with language networks in adults, and possibly include Broca’s area. In this project, Gervain will combine behavioral measures with state-of-the-art brain imaging techniques to measure infants’ brain responses at birth and throughout the first year of life to natural and synthesized communication stimuli created by Geffen. NIRS co-registered with electroencephalography (EEG) will be used to identify the brain networks differentially activated by the different sound categories as well as to discern the temporal structure and time scales of the brain responses.

In human cells, RNA Pol III can exist in two distinct-isoforms differing by only a single subunit, POLR3G or POLR3GL, displaying specific expression patterns and assuming partially distinct functions in cell proliferation and differentiation. Thus, RNA polymerase III may have more complex functions and might also contribute to the specific regulation of differential gene transcription, which is at the basis of virtually all fundamental biological processes. Initially identified for its role in cellular transformation, the POLR3G-containing Pol III isoform was found to participate in the regulation of embryonic stem (ES) cell differentiation. Although POLR3G seemed to be expressed only in ES and cancer cells, multiple genome-wide studies reported its accumulation in the liver. Therefore, POLR3G might represent an attractive candidate for the regulation of the stem cell-like behavior of hepatocytes, allowing them to proliferate following liver injury, while retaining their highly specific functions. I shall propose investigations aimed at unveiling the physiological roles of POLR3G and PORL3GL in the liver. To this end I propose to conduct experiments using conditional knock-out mice in various liver regeneration models and ChIP seq assays coupled with transcriptome profiling analysis. Understanding the function and regulation of POLR3G versus POLR3GL may shed light on the roles of different RNA polymerase III isoforms in liver cell proliferation.

Determining how size is controlled is a fundamental question in biology that is poorly understood at the organism, cellular and subcellular levels. Using two frog species that differ in size at all three of these levels, Xenopus laevis and Xenopus tropicalis, my goal is to elucidate genetic and cell biological mechanisms that govern biological size. By generating Xenopus interspecies hybrid embryos and measuring cell and nuclear size throughout development, I will evaluate the role of the genome and egg cytoplasm in cell and embryo size control. Does altering the normal ratio of chromosomes to egg volume change cell or embryo size independent of gene expression? Or do species-specific factors expressed upon activation of the zygote genome influence size scaling? At the subcellular level, scaling factors have been identified that differentially influence the size of the nucleus and mitotic spindle in the two frog species. Utilizing bioinformatics, I aim to identify additional potential novel size control factors that differ between the two species or are expressed in hybrids. To evaluate these scaling factors at the cellular and organism levels, I will alter their expression in embryos and investigate the effects on cell size and development. I will determine if changing the level or regulation of one specific protein is sufficient to alter cell or organism size and if altering the dimensions of subcellular structures affects cell division timing and development. Altogether, this study will provide a combination of general rules and molecular details to describe the means used in nature to control biological size.

Climate change is a key threat to biota globally. Changing temperatures are expected to have particularly strong impact on ectotherms due to their highly temperature-sensitive physiological traits, such as metabolic rate. These traits impact growth and time to reach maturity and govern a species’ life-history. Despite our detailed understanding of these processes under laboratory conditions, there is a paucity of translating laboratory studies into ecologically relevant contexts; the main reason being the difficulty in integrating animal behaviour as a central factor influencing the physiology, energetics and life-history of an individual. Our ability to forecast the implications of changing climates on species’ performance remains therefore limited. This project is set to overcome this difficulty, by integrating a Dynamic Energy Budget (DEB) model with in situ quantification of animal behaviour using novel tagging technology. Our model systems are juvenile elasmobranchs, which use thermally dynamic coastal lagoons as nurseries and are amenable to laboratory and field investigations, allowing the parameterisation of a DEB model. The model will test behavioural scenarios, where two key parameters vary 1) time spent foraging and 2) selection of thermal habitat. The interaction of these parameters will yield a matrix of growth and age at maturity as a function of behaviour. This project will enable us to elucidate the behavioural mechanisms underlying variation in life-history characteristics in response to temperature, laying the foundation to predict the extent of behavioural plasticity required for ectotherms to mitigate declining performance in a changing climate.

One essential element very often missing to explain cell-fate control concerns the spatiotemporal regulation of translation. How does translation at synapses regulate the growth and connection strength of individual synapses during learning process? How does localized mRNA translation contribute to maintaining the pluripotency of stem cells? To address these fundamental biological questions, we propose a multi-disciplinary approach combining tools and concepts from synthetic biology, biophysics and neurobiology. Our strategy is to rationally design functionally controllable RNA-protein (RNP) complexes to spatiotemporally control mRNA translation in living cells. One of the main objectives will be to build synthetic RNPs that can traffic, translate or degrade a mRNA molecule. Our design will integrate magnetic nanoparticles and biological molecules to combine both the functional properties of native RNPs and the capability of being manipulated in space and time using magnetic forces. We hypothesize that local translation in cells often play critical roles in cell-fate decisions, such as the establishment of polarity and regulation of synapse formation and plasticity. However, currently available techniques are limited with their capacity in regulating local translation with spatiotemporal precision. Our new engineering approaches to develop synthetic RNPs in target cells will compensate pre-existing techniques by adding precise spatiotemporal controls. With synthetic RNP-mediated spatiotemporal translational regulatory systems, we will ask fundamental biological questions that are not accessible using current cell biology and ‘omics’ approaches, including: (1) What is the specific role of local translation at a synapse in terms of synaptic plasticity and memory formation and consolidation? (2) Can we control cellular behaviors of stem cells or differentiated cells by providing spatiotemporal gene expression dimensions? The new apporach will allow us to examine the effect of localized mRNA translation in controlling cell-fate behavior for two general cell states including pluripotency of stem cells and differentiated state of neurons. Such approaches will open new directions to better understand how local translation contributes to cell-fate conversion.

A neural circuit adapted for recording and storing representations for unique events and situations faces the related problems of having enough capacity for storing a lifetime of memories, and separating similar but different memory representations. The hippocampus and surrounding cortical areas in the mammalian brain are essential for long term memory. Single unit recordings in rats have shown that hippocampal neurons form a map of a familiar environment, thought to underlie episodic memory formation. The map is stable in a constant environment but may ‘remap’ in response to subtle changes, thought to be the hallmark of a new memory representation of the environment. A network upstream from the hippocampus, located in the entorhinal cortex, contains ‘grid cells’ that do not code for a specific location, but rather a continuous displacement within the environment. Their activity forms a hexagonal pattern that tessellates the ground. Recently, these cells were shown to form individual modules, that independently map the space of the environment.
The question addressed in this proposal regards whether these modules function to increase the capacity for storage in the hippocampus, by changing their activity independently, and thus providing a mechanism of remapping similar but different environmental input. The hypothesis will be tested using large scale multi-unit recordings of the entorhinal and hippocampal neurons in behaving rats, during experimental manipulations targeting individual modules. The project has the potential to explain how an advanced, but simply executed, algorithm may contribute to increase the storage space of independent memories.

The ability to detect light is crucial for humans and animals to adapt to changes in their environment. In humans about 30% of the brain surface is involved in processing light information. Light (photons) is absorbed by photoreceptors, specialized sensory neurons with pigments sensitive to light. Surprisingly, not all photoreceptors stimulate our conscious perception of vision or images. Indeed, some photoreceptors (non-image-forming photoreceptors) are widely present in the animal kingdom, from flies to humans. Image-forming photoreceptors allow animals to get rich information about their environment from the light reflected or emitted from objects, such as size, shape, color, speed and brightness, with high accuracy over space and time. In contrast, non-image-forming photoreceptors measure light brightness to synchronize the day/night cycle with an animal’s inner circadian clock, controlling pupil size and triggering movement toward (or away from) light. Our understanding of non-image-forming photoreceptor functions is largely from studies that genetically block certain functions of non-image-forming photoreceptors in fruit flies and mice. Despite their usefulness, these genetic studies have the potential drawbacks of disrupting neural network and introducing changes that compensate for the blocked functions. In this study we will combine the power of three advanced scientific fields (nanoscience, optogenetics, and neuroscience) to develop tiny particles (nanoparticles) that can be remotely stimulated with infrared light to activate microbial opsins that turn off and turn on non-image-forming photoreceptors in both flies and mice. Studying both flies and mice is important to understanding the functions of non-image-forming photoreceptors in animals at different levels of evolution. Our studies will tackle a fundamental neurobiology question with unprecedented precision. Importantly, our proposal offers a novel opportunity to remotely (wirelessly) activate or inhibit neuronal activity in naturally behaving animals, including those that cannot be easily studied with current methods due to their dark skin/cuticle (such as fruit flies).

The mechanical properties of a tumours environment could induce or supress malignancy, but the nature of such a mechanical cue and how it is detected remains unclear. In vitro, extension of single cells induces a mesenchymal phenotype, providing the intriguing notion that compression could revert malignancy. I will develop a novel tool to mechanically compress, extend and dynamically load both normal and transformed mammary gland acini, cultured in a 3D matrix. Extension and compression induce organisational changes to the matrix, whilst dynamic loading mimics a high tension environment, enabling me to systematically determine the role of distinct mechanical signals on malignancy. I will monitor changes to acinus morphology, rates of cell division and the organisation of the actin cytoskeleton in different loading conditions as indicators of a phenotypic change. Using gene expression profiling I will elucidate the molecular pathway by which cells detect and respond to these conditions. Three actin structures are of interest; stress fibers, junctional and nuclear actin. I will observe concurrent effects on the expression and localisation of the transcription factors Mal/srf, B-catenin and YAP/TAZ to identify the potential pathway. Then, I will examine the role of ancillary proteins to these actin structures with gene silencing to mechanistically determine the molecular sequence of events. These results will provide the first quantitative links between specific mechanical stimuli, mechanosensitive signalling pathways, gene expression, and the induction or reversion of malignancy in a multicellular system.

Malnutrition and a sedentary lifestyle promote cardiovascular and metabolic disorders that nowadays represent the major cause of death in western societies. As there is no pharmacological substitute for a healthy way of life, therapies aim at preventing the onset of metabolic and cardiovascular diseases. Anti-atherosclerotic drugs decrease cholesterol levels to prevent deleterious plaque formation in blood vessels, such as the coronary arteries. Counterintuitively, strong evidence for a positive effect of cholesterol on exercise adaptation and skeletal muscle (SM) function exists: For instance, cholesterol-lowering statin drugs impair endurance exercise adaptation and aerobic metabolism in SM, while dietary cholesterol promotes exercise-induced muscle growth. I hypothesize that either nuclear receptors, the SREBP pathway or acute post-exercise stress response pathways link cholesterol metabolism to SM function. To identify the specific cellular pathway(s) involved in this cholesterol/SM crosstalk, the effects of cholesterol depletion and overload on the exercise adaptation process and muscle function will be comprehensively explored. In order to provide proof-of-principle evidence of how cholesterol affects the SM, I will also develop strategies to overcome the statin-induced inhibition of SM function, e.g. via the pharmacological or genetic modulation of cholesterol-dependent signaling pathways and by biochemical targeting of specific protein/protein interactions. Unraveling the link between cholesterol and SM function should yield major insights into muscle and exercise biology, potentially relevant for the treatment of common human disease.

NAD+ (nicotinamide adenine dinucleotide) is required for redox reactions in various metabolic pathways and is a co-substrate for the sirtuins (SIRT1-7), a family of protein acetylases. Recent data that I have generated shows that protein O-GlcNAcylation is increased in white adipose tissue (WAT) and brown adipose tissue (BAT) during aging. Importantly, Increase in O-GlcNAcylation during aging was reversed by treatment with a molecule that raises intracellular NAD+ levels, nicotinanide mononucleotide (NMN). I intend to investigate role of NAD+, O-GlcNAcylation, and the role of Sirtuins, on adipocyte function and transdifferentiation in the context of aging via the following three aims:. Firstly, the role of NAD+ in regulating O-GlcNAcylation by modulation of flux through the hexosamine biosynthetic pathway (HBP) will be investigated. This is because O-GlcNAcylation depends on the availability of its donor, UDP-GlcNAc, a metabolite synthesized by the HBP that requires metabolites derived from glucose, amino acid (glutamine), fatty acid (acetyl-coA), and nucleotide metabolism. Secondly, I will determine whether sirtuins (SIRT1-7), which are NAD+-dependent deacetylases, regulate O-GlcNAcylation. Sirtuins regulate many important pathways and play a pivotal role in the maintenance of energy homeostasis. We hypothesize that sirtuins may regulate O-GlcNAcylation by changing the activity of OGT and/or OGA, the ability of their substrates to bind, or by changing their expression levels. Lastly, the physiological role of O-GlcNAcylation in the adipose tissue during aging will be evaluated. I intend to identify O-GlcNAcylated proteins which are regulated in an NAD+-dependent manner.

The mammalian cerebral cortex commands all higher order brain functions, including perception, language, emotion and cognition. Our understanding of how a functional cortex is constructed from a set of specific neural stem cells remains however largely fragmentary. The long-term goal of this application is to fill this knowledge gap. As a working hypothesis we propose that the lineage relationship of nascent neurons fundamentally influences the structural and functional assembly of the cortex. To test our hypothesis, we will integrate state-of-the-art experimental, bioinformatics and mathematical modeling approaches to quantitatively analyze the genesis of excitatory neurons and their integration in the developing mouse cortex at the clonal level. First we will systematically trace the lineage trees of cortical excitatory neurons in vivo and at clonal density using the MADM (Mosaic Analysis with Double Markers) technique. Using computational approaches we perform 3D image analysis to map the spatiotemporal progression of individual lineages. Utilizing the unprecedented resolution of experimental MADM datasets, we will delineate the exact cellular events responsible for the step-wise generation of discrete lineages, and develop mathematical models that quantitatively describe progenitor cell behavior at both clonal and population levels. Next, we aim to identify molecular signatures that define individual lineages. Guided by knowledge based on systematic characterization of cortical lineages, we will perform transcriptome analysis to compare and contrast gene expression within individual lineages and across distinct lineages. Comprehensive bioinformatics and statistical algorithms will be employed to uncover potential lineage-specific molecular signatures. Finally, we will holistically determine the structural and functional organization of clonally-related cortical neurons. To this end we will reconstruct individual lineages in the mature cortex, extract their spatial organization principles, and systematically map synaptic connectivity within and across lineages using multi-electrode whole-cell recordings and optical stimulation to reveal functional organization principles. The innovative integration of unique, powerful interdisciplinary approaches promises in-depth insights for understanding mammalian cortical development and function.

One of the wonders of complex life is how cells within an organism, which share an identical complement of genomic DNA, assume a vast array of specialized identities. If the genome is the language of life, then cellular identity lies in the differential interpretation of this genomic language. In this project, we aim to shed light on how transcription factors (TFs), the words in this language, combine in cell type-specific patterns, or grammars, to impart meaningful information and control cellular identity in response to external signaling. Specifically, we aim to utilize computational linguistic tools to build a generative grammar that models how one TF family, the Tcf/Lef (Tcf) family, which is downstream of the pleiotropic Wnt signaling pathway, binds to specific sites in a cell type-specific manner to alter gene expression.
To approach this goal, we will first build a preliminary Tcf grammar rulebook through computational grammatical modeling of a suite of genomic data collected from mouse embryonic stem cells (ESC) and their ESC-derived intestinal endoderm (IE) progeny, extracting grammars that allow Wnt to impart cell type-dependent meanings. Next, we will refine this grammar through analysis of the gene regulatory functions of thousands of automatically designed candidate Wnt-responsive phrases in a pioneering CrispR-based high-throughput assay in both ESC and IE. Through iterative screening and model refinement, we aim to achieve sufficient fluency in Tcf grammar to enable us to design new regulatory DNA sequences with predictable Wnt-dependent activity in vivo and to predictably disrupt Wnt-dependent gene activation by removing specific cofactors. As a proof of concept, one immediate future work is to apply our Tcf grammar in ApcMin intestinal adenoma cells, which have dysregulated Wnt signaling, to predictively disrupt this dysregulated gene regulatory network. The ability to design ab initio new regulatory DNA elements that respond in a cell type-specific manner to external signals opens up new research avenues in diverse disciplines including synthetic biology, regenerative medicine, gene therapy, and systems biology.

In the left hemisphere of the human brain, damage to the ventrolateral frontal (VLF) cortex, which includes a specialized region known as Broca’s area and adjacent precentral motor cortex, leads to speech problems. At the same time, there is an older system playing some as yet unspecified role in vocalization and speech in the dorsomedial frontal (DMF) region, which includes the supplementary motor area, presupplementary motor cortex, and the adjacent cingulate motor areas. Little is known of how these two systems interact anatomically and functionally. In primates that lack speech, such as chimpanzees and macaque monkeys, these regions may be involved in voluntary vocal production. Critically, there is nothing known of how these two systems may or may not have changed during primate brain evolution with increasing selection for language and speech functions in the human lineage. The aim of this interdisciplinary group of scientists is to adopt an evolutionary framework to study the role of these two brain regions in vocalization/speech, their cytoarchitectonic characteristics, and their anatomical and functional connectivity. The multimodal approach proposed here is particularly innovative because it combines comparative cytoarchitectonic analysis in three critical primate species to establish comparable areas. Further, invasive anatomical connection tracing studies that can only be carried out in the macaque monkey will provide totally unambiguous connection data that can then be employed to test predictions about functional and anatomical connectivity in the human and chimpanzee brains using non-invasive procedures including diffusion tensor imaging and resting state functional magnetic resonance imaging. Finally, functional imaging techniques will be used to characterize the VLF and DMF networks in relation to vocal production. This is the first systematic comparative study undertaken in the three most critical primate species for understanding DMF and VLF regions. Each research team brings a unique set of scientific skills and pragmatic strengths that provides for a novel, interdisciplinary effort to advance our understanding of the origins of vocal production and eventually human speech.

Studies on neurodevelopmental disorders have implicated cerebellar function in social interaction, but how the cerebellum regulates social behavior is not well understood. Cerebellar defects cause impaired social interaction and attenuated dopamine release in the prefrontal cortex, suggesting a role for the cerebellum in regulating the rewarding aspect of social interaction. Cerebellar dysfunction also causes defect in social memory. Focusing on these two behaviors, I will attempt to identify cerebellar circuits activated by social interaction by using a mouse line that expresses a drug-inducible fluorescent reporter under the control of the immediate early gene Fos (fosTRAP). This line labels activated neurons throughout the brain during a specified time window, allowing me to identify cerebellar neurons activated during social reward and memory. By using this technique in combination with monosynaptic neural tracing methods I will attempt to identify cerebellar circuits activated during social interaction.

In parallel, I will investigate how synaptic alterations and social environment impact cerebellar circuit activity. Crossing the fosTRAP mouse with ASD mouse models will create mouse lines where neural activity can be assessed in mice with impaired social function, and rearing wild type mice in social enriched environment will be used to assess the role the environment plays in cerebellar circuit activity. I will use these two approaches to verify the importance of the identified cerebellar circuits in social interaction, and to examine how alterations at the synapse and changes in the environment impact circuit activity during complex social behavior.