Life depends on the faithful transmission of genetic information. DNA must be accurately replicated and segregated during cell division. Cancer cells evolve due to accumulation of multiple, successive mutations within a cell lineage that result in changes in cell growth, proliferation, and survival. The selection for multiple, successive mutations favors the evolution of genetic instability (defects in DNA replication, repair, and chromosome segregation), which increases the rate of mutation. However, it is not clear how genetic instability arises and evolves. Cataloging the genetic rearrangements present in cancer cells does not allow us to re-capitulate the contribution of individual mutations to the development of genetic instability. Instead, I propose to study the evolution of genetic instability over time in a yeast model of cancer. I will evolve cells to escape growth suppression, which is analogous to the selection for loss of tumor suppression by the inactivation of genes that guard against genetic instability or unintended cell growth and proliferation. The level of genetic instability will be monitored as cell lineages will undergo several rounds of selection, and instability-associated mutations will be identified by whole-genome sequencing. To quantify the direct function of these mutations in generating instability, we will re-introduce them in a non-evolved ancestor strain. With this strategy, I aim to uncover early mutations that cause genetic instability and generate genetic fingerprints that can be used to identify the causes of genetic instability. By selecting in diploids, I will be able to identify dominant instability-causing mutations, which may be more relevant to cancer than the classical loss-of-function candidates. Due to the conservation of basic cell biology, I expect that our results will be relevant to understand genetic instability in humans.

Non-apoptotic cell death (NACD) is now recognized as tightly regulated forms of cell death, although the molecular mechanisms driving the underlying processes remain to be unveiled. Compelling evidence suggests that NACD sub-routines require oxygenated lipids as critical signals, demanding many questions to be answered: What are the enzymatic mechanisms involved in the formation of oxygenated lipids? Which of these lipid species play an active role in NACD signaling and what are these roles? Are they triggers and/or executors? And what are the targets? Lipid chemistry is remarkably diversified, harboring unlimited opportunities for a refined and meaningful signaling, but, at the same time, this diversity represents a major technical challenge for experimental studies. Here, we propose an analogy between language and biology to address this challenge in an interdisciplinary framework combining experimental and computational studies. Assisted by computational tools developed originally for language applications we plan to decipher the unspoken oxi-lipidome language as follows: Step 1) Identifying the words: We hypothesize that oxygenated lipids formed during different processes of cell death are analogous to words. To define the list of words relating to different forms of NACD, we will generate oxi-lipidome profiles using distinct cell death triggers and well-defined genetic models. Their analysis will yield a modulatory profile used to provide a signature for different cell death modes; Step 2) Deriving a lipidome dictionary: Oxidized-(phospho)lipid (oxi(P)L) heat maps as generated in Step 1 will lay the basis to characterize prominent differences between normally functioning and death-destined cells. This will lead to the identification of potential NACD oxi(P)L signals that will undergo further scrutiny through the language-inspired bioinformatics “filters”. Rational synthesis of the thus defined types of informative phospholipids will be thoroughly analyzed in the context of their interactions with target proteins known to shape the oxi-lipidome. Step 3) Deciphering the meanings of lipid words: In an iterative process integrating predictions and experimentation, we will study the interaction of many lipids with specific proteins and interactions that a specific lipid can undergo with many proteins using computational classification techniques also used in language analysis. Using biophysics and biochemistry techniques we will validate predicted covalent versus non-covalent interaction of the oxi(P)L-protein interfaces. The libraries of oxi-lipids created in step 2 will be delivered to specific intracellular destinations and tested for their signaling role in NACD pathways. Conclusively, knowledge gained by this comprehensive and highly multidisciplinary approach will provide intriguing insights on how the oxi-lipidome could emerge as a tremendous reservoir of yet unrecognized information.

We will investigate host and pathogen DNA sequence coevolution and multigenerational inheritance of epigenetic changes during plant-fungus interactions. Verticillium dahliae, an economically important vascular wilt pathogen that can infect numerous plant species and exhibits differential host virulence, will be studied as it adapts to infect Arabidopsis thaliana. The project will carry out experimental coevolution and track not only phenotype evolution but also genome, methylome, transcriptome, and small RNA changes using next generation whole-genome sequencing technology. The experiments will investigate genome stability and dynamics of epigenetic marks during pathogen evolution, plant evolution, and their coevolution by comparing data gathered prior to, during, and following their serial interactions across multiple generations. The experiments will identify specific genes and mechanisms that allow a broad host-range pathogen to gain increased infection efficacy on an initially marginal host, and characterize genome-wide changes in the pathogen. Simultaneously, host genome stability and host epigenetic changes in the face of pathogen attacks will be characterized. These experiments should offer an exciting view of the role and mechanisms of genome plasticity and epigenetic dynamics during host-pathogen adaptation.

All living organisms must organize their DNA within the confines of the cell. This is achieved by a combination of “passive” factors (e.g. cell size and shape) and “active” processes (e.g. DNA folding proteins). While much is known about how DNA is organized in higher organisms, we still have little understanding of the DNA folding processes that drive chromosome organization and compaction in bacteria. Given the abundance of these organisms, and their impact on human activity, this represents a startling gap in our knowledge. In recent years nano-scale cell imaging, large-scale genomic techniques, and mathematical/physical modeling of biopolymers have emerged as new tools to study DNA biology. In this program we bring together these approaches to facilitate precise dissection of bacterial chromosome structure. Thus, in a collaborative effort between theory and experiment, we will test and expand models to describe bacterial genome organization.

Blood-oxygenation-level-dependent functional magnetic resonance imaging (BOLD-fMRI) has emerged as the cornerstone of noninvasive brain mapping in recent years. This technique measures neuronal events indirectly by detecting associated changes in a mixture of cerebral blood flow (CBF), cerebral blood volume (CBV) and cerebral metabolic rate of oxygen consumption (CMRO2). Although BOLD contrast is widely used as a surrogate marker for neural activation, to date, there is no clear demonstration of how neurons and astrocytes, the two different cell populations in brain, generate this functional signal. This limitation seriously confounds MRI data interpretation for both basic research and clinical applications.
In this project, we seek to dissect the neuronal and astrocytic components of BOLD signal using pharmacogenetic and optogenetic fMRI. We propose to use two different yet complementary genetic tools based on (i) Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) and (ii) light-activated photosensitive proteins (microbial opsins) for selective modulation of neuronal/astrocytic activities. Continuous arterial spin labeling (CASL) technology will be used for simultaneous acquisition of BOLD and CBF data before, during and after optogenetic stimulation of one of the two cell populations while the other will be pharmacogenetically silenced. We hypothesize that selective optical excitation and chemical inhibition of genetically defined cell populations will provide the first direct evidence of how BOLD signal is generated in vivo, what it actually represents and finally, put the long-lasting debates on BOLD contrast mechanism to rest.

The precise adjustment of the floral transition is controlled by external and internal cues. In the temperate cereals wheat and barley, flowering is induced by long-days and vernalization. VRN2, a long-day flowering repressor with no homologs in Arabidopsis, is repressed by vernalization and plays a central role in preventing flowering during the fall. However, even nonvernalized winter wheat plants flower after long periods at room temperature. Interestingly, VRN2 is also downregulated during plant development. This suggests that plant age could induce flowering, probably through the control of VRN2. Recent studies indicated that miR156 and its targets, the SPL transcription factors, constitute a conserved mechanism to control age-dependent processes in plants. Here I propose to study the role of the SPL genes in the control of VRN2 expression and cereal flowering by age. First, I will obtain and characterize mutants for SPLs using a tetraploid wheat TILLING population, in particular looking for mutations that eliminate the regulation of the SPLs by miR156. Also, I will knock-down and overexpress miR156 through a transgenic strategy in barley. Then, I will integrate the SPLs into the known flowering network by crossing the SPL mutants with available mutants for different flowering genes, and by performing detailed studies of gene expression. Finally I will screen barley landraces and varieties for polymorphisms in the SPL family to test their potential adaptative value. Results from this study will increase our understanding of the mechanisms involved in the regulation of flowering and can contribute to engineering improved varieties adapted to changing environments.

We aim to explore the emerging paradigm that transposable elements (TEs) could be sensors of bacterial stress, and that their reactivation could contribute to a transgenerational and adaptive memory of the immune response through heritable changes, either epigenetic (heritable modulation of nearby-genes expression) or genetic (restructuration of the genome and creation of new regulatory networks via transposition). This project comprises two aims. First, we want to test if the modulation of defense gene expression, through epigenetic modifications at nearby TEs, can be inherited to the progeny. As a first step towards answering this question, we will determine whether the DNA methylation changes previously observed in the course of the immune response, and other related epigenetic marks, can be passed to and mitotically maintained in Arabidopsis stem-cells (precursors of the germ cells), then propagated in the plant to the next generation, thereby contributing to transgenerational immune priming. Second, we want to set-up a reporter system to analyze the pattern of somatic transpositions in a plant challenged with bacteria and to isolate the rare individuals that display the transgenerational memory of transposition events. In fact, transposition upon environmental challenge has not been much studied experimentally so far in plants due to the lack of appropriate tools. We propose that there is a timeframe during which transposons can be reactivated upon bacterial challenges and our system should allow us to unravel the conditions for transposition, the specific tissues/cell types and the frequency of their occurrence as well as their transgenerational inheritance.

Although locomotion may seem effortless, it relies on spinal circuits producing complex patterns of muscle contractions. Spinal cord central pattern generator circuits (CPGs) produce motor output autonomously as a result of descending commands from the brain and modulations caused by internal physiological cues. The cerebrospinal fluid (CSF) constitutes a fascinating interface through which chemical cues produced in the brain can reach neurons within the entire central nervous system. Located along the central canal, CSF-contacting neurons (CSFns) project a ciliary tuft into the CSF and an axon into the spinal cord. These mysterious cells were identified in over 200 species of vertebrates by Kolmer and Agduhr who hypothesized that they could act as a proprioceptive sensory neuron. The difficulties of labeling and accessing these cells have prevented the characterization of their sensory physiology or specification. However newly developed tools and experimental approaches in zebrafish provide us with a unique opportunity to overcome these technical challenges. The transparency of zebrafish at early stages makes it a powerful system for identifying neurons by their morphology and for investigating and manipulating neuronal activity of specific cells in the intact animal. Using an optogenetic approach, Dr. Wyart and colleagues discovered that CSFns could strongly modulate the activity of spinal CPGs. In this proposed project, the Delmas, Lewis and Wyart labs will combine expression profiling, channel physiology, behavioural analysis and loss-of-function assays to elucidate how CSFns are specified and how they sense chemical and mechanical cues in the CSF. The Lewis lab has pioneered the use of FAC sorting and transcriptome analysis to identify genes expressed in distinct subtypes of spinal neurons. The Delmas lab has unraveled the functions of channels underlying chemo- and mechano-sensation in mammals. The Wyart lab has combined optical and physiological approaches to identify the functions of CSFns. Together we will establish how genetic networks specify these cells and unravel the molecular mechanisms by which CSFns are physiologically activated in vivo and contribute to behaviour.

How genetic and epigenetic mechanisms control proper gene expression is a fundamental unresolved problem. At the sequence level, enhancers regulate transcription in a cell-type- and cell-state-specific manner. On top of enhancer sequence, dynamic DNA methylation and histone modification processes have been correlated with transcription regulation. The host lab has provided the first indication that histone modification patterns can be used for enhancer annotation. However, mechanisms of enhancer regulation by chromatin modification are not completely understood, mostly due to the inability of targeted reprogramming of epigenome. Here I will develop tools which enable us to targeted edit the epigenome in human cells(Aim 1). In hESC, I will express fusion proteins containing mutant Cas9(dCas9, lacking nuclease activity) and chromatin modifying enzymes, which can be guided to target DNA sequence by sgRNA to edit chromatin modifications. Next, I will study the role of enhancer-like chromatin modification in gene regulation and cell fate determination(Aim 2). I will create H3K4me1 modification near NKX2-5 locus in hESC, a master regulator of cardiac progenitor cells, followed by monitoring changes in NKX2-5 expression, histone modification and cell fate. I will also study if chromatin modifications play a causative role in enhancer activity and transcription(Aim 3). The chromatin modifications on OCT4 enhancers in hESC will be reprogrammed by CRISPR/Cas9 system. I will then perform a rigorous genomic analysis to study the dependency between chromatin modification, OCT4 enhancer activity and hESC pluripotency. Using these data, I will explore the role chromatin modifications in enhancer regulation. I expect this project will have a major impact on the understanding of functional human epigenome and on developmental biology. The developed CRISPR/Cas9 system will be widely applicable in epigenetic studies in other model systems.

Autophagy, the process whereby cells degrade their own components, is essential for normal cell function and mammalian development, and also has been implicated in numerous human diseases. Autophagy involves a wide array of protein-protein interactions, including a large number involving ubiquitin, ubiquitin-like proteins and various adaptor modules. The ability to target and disrupt these protein-protein interactions would enable dissection of the molecular details of autophagy, which would greatly enhance our basic understanding of the process and could lead to the identification of targets for therapeutic intervention. This project will develop and apply a toolkit of protein-based modulators to explore the roles of distinct molecular networks in autophagy. We will first identify protein interaction interfaces, and subsequently, will use computational design and combinatorial protein engineering to develop high affinity sensors or inhibitors that can function in live cells. Structural studies will be performed to determine the molecular basis of their action. These tools will then be used in vivo settings, using variety of cell and mouse models, to monitor and control physiological and pathophysiological autophagy processes.

Adaptation to environmental change is required for species to be successful, however the potential and rate at which this takes place is unclear. In addition, recent studies have highlighted the importance of ‘extended genotype’ features as factors influencing a wide variety of adaptive phenotypes. This project aims to determine the genetic basis of environmental adaptation and to investigate extended genotype factors as both a cause and consequence of the adaptation process using natural populations of the model cereal Brachypodium distachyon. First, the project will aim to determine the genetic architecture of DNA methylation variation within natural populations. As DNA methylation may lead to phenotypic changes, the genetic loci regulating methylation may be closely associated with the variability of adaptive traits such as flowering time and growth rate. Second, allelic variation in DNA methylation (epialleles) will be examined to determine if they are causal, and directly associated with adaptive traits and extended genotype variation. Methylation variation will be assessed within both inbred populations and samples selected from across globally diverse environments to determine if there are specific regions of the epigenome that vary or have become fixed within their respective populations. Beyond this, both inbred and diverse allopolyploid lines will be assessed to determine the impact of genome duplication on both DNA methylation and adaptive trait variation. These experiments will allow for genome-scale analyses of the extended genotype across natural and synthetic B. distachyon lines to determine the underlying basis of adaptation ability in harsh environments.

The processing and encoding of external stimuli is essential for all life forms to react appropriately to environmental cues. When animals move, however, they activate their own sensory systems. Expectations about self-generated sensory input and its subtraction from the total input are essential for accurate sensory processing. Organisms have optimized a solution for distinguishing between self-generated and external stimulations by involving a descending (efferent) neural pathway that modulates ascending (afferent) activity. Mechanosensory hair cells, for example, are subject to feedback regulation by cholinergic efferent neurons that originate from several nuclei in the brainstem. The present research proposal aims at understanding how efferent neurons control mechanosensory processing.
Fishes and amphibians have a superficial and accessible mechanosensory system, the lateral line, which circumvents many of these problems. The lateral line serves to detect hydromechanical variations around the animal’s body and controls two characteristic behaviors: the stereotypic fast escape responses to sudden mechanical input, and complex and highly variable obstacle avoidance and rheotaxis. The simplicity of the lateral line in the zebrafish larva makes it a particularly powerful experimental model system.
Versatile recent technological developments suggest that efferent/afferent interactions in the zebrafish lateral line can be interrogated using a combination of pharmacological and genetic manipulations of neural circuits in vivo, intravital structural and functional imaging of neuronal ensembles, and fictive behavioral paradigms. Combining the knowledge and strength of each group, we will be able to clarify efferent/afferent interactions and lay the foundations to further ask how the nervous system adjusts its sensitivity to discriminate between external- and self-stimulation. This collaborative project is based on molecular studies of efferent neurons, in toto visualization and manipulation of the zebrafish lateral line, and zebrafish neurophysiology, functional imaging and behavior.

The tumor microenvironment is becoming appreciated as a determinant factor in cancer development. Pancreatic cancer is supported by its tumor-associated stroma, including protection from the effects of chemotherapy. The use of genetically modified mouse models is at the heart of pancreatic cancer research, as they mimic well most of the features of the human disease. Accordingly, pancreatic tumors developed in mouse models are highly abundant with stromal components and resist conventional chemotherapy. Connective tissue growth factor (CTGF) is a critical component of the tumor-associated stroma in pancreatic cancer, and was shown to mediate anti-apoptotic signals and oppose chemotherapy effects. This research is aimed to investigate the roles and mechanism of action of CTGF in supporting pancreatic cancer survival, and identify other stromal components that may facilitate the malignant process. To discern the contribution of the pancreatic stromal compartment to tumor progression, we will use a newly-established ex-vivo system for growing mouse pancreatic epithelial cells in 3D matrix that keeps their natural conformation and biological features. Co-culturing pancreatic epithelial organoids with pancreatic stromal cells, such as PSCs, will provide an elegant and clean system to study CTGF signaling, and other survival signals that promote pancreatic malignancy. We will further expand this system to allow the growth of human pancreatic cancer cells in order to dissect signaling pathways that are most relevant to this deadly human disease.

Endogenous heterogeneity in isogenic T-cells renders individual cell activation unreliable. Accordingly, cytokine based cell to cell communication is necessary to proofread individual cell response and achieve a reliable self/non-self discrimination at the population level. Current attempts to understand cytokine-cell networks either neglect their dynamics or address dynamics of the average cell only, neglecting the full distribution. Our aim is to understand the dynamics of cell to cell cytokine communication in heterogeneous clonal populations at the distribution level.

To properly study cytokine and T cell population dynamics it is not enough to make precise measurements of cytokine concentration and T cell activation; a mathematical model that manifests the dynamics is required. Furthermore, since genetic perturbations cannot be used to understand immune response in human patients, it is of utmost clinical relevance to create a quantitative model of cytokine communications and how different cytokine perturbations impact lymphocyte differentiation.

We conjecture that the cytokine receptor distribution affects the cell fate decision. If true, we will test whether different sub-groups within the distribution carry different cell fates, eg. short-lived effector vs. long-lived memory cell. We will test these hypotheses by designing in vitro cultures of primary cells that mimic in vivo immune distributions. We propose to build a computational model of the distribution dynamics and variability of T cell regulation. We will use this model to test and validate experimentally diverse perturbations of collective T cell regulation with the goal of optimizing immunotherapies.

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.