Obesity induces chronic inflammation in the intestine and affects the state of non-immune cells such as gut-associated neurons (e.g., enteric and gut-innervating sensory neurons). For example, the intestinal immune system undergoes proinflammatory shifts during obesity, contributing to metabolic dysfunction; while the sensitivity of sensory neurons to satiety-inducing peripheral signals (e.g., distension and nutrients) are disrupted in obese conditions, which leads to food overconsumption. Furthermore, a growing body of evidence has revealed the importance of neuroimmune crosstalk in several pathological conditions, including obesity. Thus, in this proposal, I hypothesize that enteric neuroimmune interactions underlie the cause of multiple obesity-related pathological symptoms, and manipulation of these interactions may critically modulate those symptoms during the development of obesity. To test this idea, first, I will use diverse techniques to characterize the enteric neuroimmune interactions in multiple aspects during the development of diet-induced obesity (Aim 1, 2). With the Victora lab, the Mucida lab (host lab) has recently developed a murine genetic approach that enables the labeling of cell-cell interactions between specific cell types (universal, or uLIPSTIC). I will apply this tool to label the cells interacting with gut-associated neurons during obesity and use flow cytometry to identify the type of labeled immune cells. Next, I will use live imaging and tissue clearing tools in immune cell/neuron double reporter mice (approaches pioneered by the host lab) in lean and obese conditions. I will also use single-cell or single-nuclei RNA-sequencing from the intestinal immune cells and gut-associated neurons, respectively, in lean and obese mice. These approaches will allow us to define the candidate receptor-ligand molecules and gut-associated neuronal subpopulations involved in these interactions. Second, informed by the characterization performed in Aim 1&2, I will investigate the functional consequences of enteric neuroimmune interactions in developing obesity-related symptoms (Aim 3). I will use genetically engineered mice to target ligand-receptor signaling pathways identified in Aim 1 and manipulate gut-associated neuronal subpopulations while monitoring physiological and behavioral parameters related to obesity-related symptoms using metabolic cages. We can also target immune cells that are found to be changed during the development of obesity by using cell-specific depletion strategies. Collectively, by utilizing state-of-the-art approaches, this project will reveal neuroimmune mechanisms possibly modulating obesity-related pathophysiological and behavioral consequences, which is a poorly understood question in this nascent field.

Eukaryotic cells contain multiple mitochondrial genome (mtDNA) copies, which encode proteins required for mitochondrial energy production. Maintaining intact mtDNA is critical for cellular and organismal health and its deterioration has been linked to cellular aging. mtDNA is known to mutate at an elevated rate, but extensive evidence also suggests the existence of processes, acting on cellular and subcellular levels, that eliminate damaged mtDNA thus acting to rejuvenate mitochondria. Yet mtDNA integrity declines during ageing, but the timecourse of its decay and the underlying mechanisms remain largely unknown, because of challenges presented by the complex and quantitative nature of involved phenotypes. This project will address these challenges through a multidisciplinary approach that applies yeast as a model organism and combines novel mtDNA-based reporters, special purpose optofluidic devices and advanced mathematical modelling. Our goal is to understand (a) the link between mtDNA decay and physiological changes associated with the ageing process at the single cell level; (b) the mutational events that drive mtDNA decay with single cell sequence resolution and (c) the processes that facilitate intracellular selection against mutant mtDNA and their role in suppressing mtDNA decay during ageing. Specifically, we will use mtDNA-based fluorescent reporters for mtDNA copy number and expression to infer mtDNA health throughout the ageing process while monitoring the decline of physiological parameters in single cells. To do so, we will develop a novel device that combines optofluidics with advanced fluorescence microscopy to monitor, select and sort single cells during the ageing process and eventually subject them to whole genome amplification and sequencing in a highly parallelized manner to determine mtDNA sequence changes. This will allow us to monitor mitochondrial function and mtDNA variation with cell age and between ancestrally related cell lineages. Resulting data will be analyzed quantitatively with the help of mathematical models of mtDNA propagation within cells, including effects of mutation, selection and random drift, which will enable us to specifically address the role of intracellular purifying selection in extending the mitochondrial healthspan of a cell. Our findings will provide broad fundamental insight into mitochondrial biology.

Social insects can undergo dramatic changes in their physiology and behavior to support the colony. In the ant Harpegnathos saltator (Hs), when the queen dies, workers can transition into reproductive pseudo-queens (gamergates) to re-establish hierarchy in the colony. In the absence of queen pheromones, the young workers engage into a dueling behavior by trading strikes with their antennae. Most workers rapidly abandon the fight (win-lose) but dueling continues for months among the winners (win-win) who become reproductive and share social dominance. These gamergates show dramatic physiological and behavioral changes, lay eggs and cease to perform workers’ duties. They also have a 5X lifespan extension, and their brain is remodeled and shrinks by 20%. This transformation is fully reversible when gamergates are placed back in a queened colony. The goal of this proposal is to understand how the absence of queen pheromones triggers dueling; what the signals are among winning workers that sustain dueling; what brain circuits are affected by sustained dueling to cause changes in behavior. We hypothesize that the neural circuits responding to queen pheromones and controlling their production regulate dueling and the establishment of queen-like behavior. The pheromones normally repress dueling, so their absence in an orphaned colony releases the inhibition, and multiple workers begin dueling. The winning asymmetry appears to be created and maintained not due to the strongest fighters prevailing but due to a signaling imbalance between the animals engaged in duels. We hypothesize that this is achieved through the action of a negative feedforward loop – duelers quickly start producing queen pheromone to repress other duelers – and a positive feedback loop – duelers are more likely to engage in dueling again, possibly due to lowered sensitivity to the pheromones. Dueling further triggers remodeling of the brain circuits that control queen-like physiology and behavior. Aim 1: Track the behavior during win-lose and win-win duels, and measure queen pheromones production on the cuticle and in the producing glands. Aim 2: Generate transgenic lines expressing GCaMP7f or CaMPARI2 in the antennal lobe of the brain to evaluate whether losing and winning workers exhibit different sensitivity to the pheromones. Aim 3: Perform scRNAseq to determine how the gamergate brain changes and which circuits are affected, focusing on homologs of known (female) aggression and egg laying circuitry in flies. Experimental system: The host lab has extensive experience in flies and ants, including a deep knowledge of brain genomics as well as metabolomics of the hemolymph. Genetic manipulations in H.s are also possible. Conclusions: This work will elucidate the molecular underpinning of social conflict that establish a new shared hierarchy in ant colonies, and how molecular memories of social experiences establish long-lasting behavioral traits via brain remodeling.

Mammalian development is an intricate process governed by overlapping and often competing cell fate programmes. Although much of the cell intrinsic transcriptomic machinery and pathways responsible for cellular differentiation is well characterised, the contribution and effect of the surrounding tissue niche(s) toward cell identity acquisition remains poorly understood. This is especially the case when we consider that embryonic macrophages and other immune cells infiltrate many organs early on during tissue specification and develop symbiotically alongside the native cells, increasing the complexity of cellular crosstalk within the niche. Furthermore, our understanding of cellular crosstalk has thus far been restricted to extracellular receptor/ligand interactions, despite increasing evidence that cells might be able to communicate directly via gap junctions, tunnelling nanotubes and extracellular vesicles. Consistently, soluble and membrane-bound ligands alone are unable to fully establish and maintain cell identity of ex vivo cultured cells. In this project, I will focus on pancreatic progenitors and their interactions with the surrounding hematopoietic/immune cells during pancreatic development, in the window of time spanning fate specification and differentiation of distinct pancreatic cell types, such as the acinar and hormone-expressing endocrine cells. Although macrophages and other immune cells represent a large fraction of the embryonic pancreatic microenvironment and are key players in diabetes pathogenesis, they are an often-neglected population and understudied in this context. Single-cell transcriptomics have started to unveil the heterogeneity of these populations, but their functional diversity and potential contribution to tissue niche(s) underlying pancreatic lineage decisions remain unexplored. Utilising in vivo mouse models, human induced pluripotent stem cell models and human fetal tissue together with traditional and spatial transcriptomics, we aim to map the cellular communication network between different sets of hematopoietic/immune cells and pancreatic progenitors. Next, we will explore the possibility of cellular crosstalk beyond traditional receptor/ligand interactions, such as direct cytosolic transfer of mRNA and protein subunits via tunneling nanotubes and extracellular vesicles, and validate the functional relevance of these findings in co-culture experimental set ups. By the end of this project, we will not only have a fuller understanding of how cell-cell communication contributes to the pancreatic tissue niches, but also provide evidence towards a novel and alternate form of intercellular communication via direct cytosolic transfer. Finally, beyond the impact on the development and stem cell biology of the pancreas, this study opens new avenues for understanding mechanisms underlying cell-cell communication and how these processes could go awry in diseases.

During the central nervous system (CNS) inflammation, substantial number of T cells start to infiltrate into CNS and attack the neurons or myelin in several neurological disorders such as multiple sclerosis, suggesting their potent role during CNS inflammation. For T cells to exhibit their effector function, it is necessary to be re-stimulated and regulated in the inflamed region by tissue-resident cells. However, the CNS-resident cells that regulate the effector T cell (Teff) during CNS inflammation are still unclear. Interestingly, recent reports suggest that astrocytes are crucial participants in CNS inflammation. Furthermore, infiltrating Teffs are known to physically contact with astrocytes. Since astrocytes express vast range of immune-regulatory surface molecules such as MHC class II (MHCII), co-stimulatory molecules (B7) and immune checkpoints, it is plausible that astrocytes might utilize those molecules to regulate the infiltrating CNS-reactive Teffs. Based on this idea, we hypothesize that astrocytes contact with Teffs via surface proteins to regulate the Teffs during CNS inflammation.

Cells need to maintain metabolic homeostasis to survive and proliferate. Many biochemical systems have evolved to coordinate levels of cellular metabolites in response to changes in extracellular cues. While we know a lot about regulatory processes involved in cellular metabolite homeostasis, how organelles maintain their metabolite availability is poorly understood. This is particularly relevant for mitochondria, as the major oxidative organelle; but whether mitochondria can sense the levels of metabolites and accordingly regulate their availability is unknown. Studying such compartmentalized metabolite sensing mechanisms is challenging due to lack of technologies to measure and modulate organellar metabolite levels. Recent studies from the host lab discovered SLC25A39 as a mitochondrial transporter for glutathione (GSH), the major antioxidant thiol in mammalian cells. Remarkably, SLC25A39 protein levels are negatively regulated specifically by mitochondrial GSH availability. This observation raises the possibility that mitochondria harbor a sensing system for GSH availability. Building upon these observations, I will identify the mechanism by which mitochondria sense GSH availability and test whether it is required for tumor formation. My first aim is to determine the precise mechanism and molecular players involved in mitochondrial GSH sensing. Using a combination of biochemical tools and genetic screening approaches, I will identify the molecular players and critical domain(s) and residue(s) of the transporter essential for the GSH sensing. Additionally, my preliminary work shows that SLC25A39 expression is associated with poor prognosis and decreased survival of breast cancer patients, and SLC25A39 protein levels are strongly upregulated in breast cancer cells colonizing to the lung compared to those in mammary tumors. Building upon this, my second aim will determine whether mitochondrial GSH availability and its sensing is necessary for breast cancer progression. To test whether mitochondrial GSH sensing is required for metastatic colonization, I will generate mutant forms of the transporter deficient in GSH sensing. In these mouse models, I will determine the precise molecular pathways impacted by mitochondrial GSH loss, resulting in reduced metastasis. To further test the sufficiency of mitochondrial GSH availability for tumor progression, I will also engineer a mitochondrially-targeted bacterial enzyme called GSHf, which produces GSH in specific compartments, and express it specifically in the breast tumor cells. Collectively, these studies will provide a unique opportunity to uncover how mitochondria sense and regulate GSH and how compartmentalized redox sensing shapes breast cancer cell function. This will also provide a proof of principle for potential organellar sensing mechanisms for other metabolites.

Rationale During development, sensory structures change and grow in a way that can impact stimulus perception and motor decision. However, we do not know the mechanisms by which sensorimotor circuits adjust for continuous change to ensure adequate behavioral responses. The lateral line is essential for survival of fishes: it responds to small changes of water flow to adjust body orientation, and to large changes to elicit escape responses. During my PhD in Zoology, I used electrophysiology to study hair cell signaling across a diversity of species. I uncovered a novel mechanism of anion efflux driven signal amplification that depends on the ionic strength of the surrounding water. While my work focused on sensory signaling at the cellular level, I now want to decipher at the organism level how sensorimotor circuits adapt upon change to sensory organs. I discovered the gelatinous encapsulant atop lateral line hair cells, referred to as the cupula, unexpectedly grows in height at a rate of ~12 µm / h in larval zebrafish. A 20-µm increase in cupula height theoretically shifts the detection cut-off frequency of hair cells by an order of magnitude (Van Trump and McHenry 2008). My observation triggers a crucial question: how does the animal accurately detect and adequately respond to flow despite indeterminate growth of its sensors? Specific Aims I will elucidate how the effects of sensor growth on gain are modulated and how motor command neurons ensure adequate behavioral responses: Aim 1. Dissect the mechanisms and kinetics of cupula growth on the entire organism Aim 2. Measure impacts of cupula growth on sensory function and motor output Aim 3. Investigate the peripheral and central mechanisms that adjust sensorimotor gain Central Hypothesis Based on spontaneous activity of the sensor, homeostatic inhibition of neurons in the anterior and posterior lateral line nucleus scales the gain of the sensorimotor circuit. Strategy To test this hypothesis, I will join the lab of Claire Wyart to learn high-throughput behavioral analysis, high speed volumetric population imaging and 3D optogenetics to reveal how the sensorimotor circuit adjust its gain to compensate for the growth of sensory organs: 1) I will monitor the growth of cupulae across neuromasts of the head and tail; 2) I will investigate how cupula size impacts behavioral choice to graded mechanical stimuli; 3) I will investigate by volumetrically imaging of neuronal activity combined with optogenetics in afferent and inhibitory efferent neurons as well as motor command neurons in the brainstem. Conclusion This project will leverage a unique example of sensory change to reveal mechanisms of regulating gain and behavioral output. The HSFP Long-term Fellowship provides an ideal opportunity to reach my long term goal: building a lab using optical and genetic tools to reveal unifying principles of sensorimotor fidelity across aquatic species.

Multicellular organisms gradually develop from a homogenous cell population into well-organized and highly complex shapes. The key concept underlying this developmental process, still far from being fully understood, is self-organization – the emergence of complex well-ordered structures in an autonomous manner. The emerging field of synthetic developmental biology aims to study self-organization by reproducing it “from the bottom up”; that is, engineering cells that don’t usually self-organize to acquire specific and predictable shapes and patterns. While this approach was successful in reproducing simple patterns, its utility in reproducing more complex naturally-occurring developmental processes has yet to be demonstrated. A fundamental step in vertebrate development is the embryonic formation of segments and their corresponding structures along the spine (e.g., vertebrae and ribs). This process is based on a segmentation clock: a self-sustained oscillator with a period of a few hours, which resides in the cells of the embryo’s tail bud. This clock depends on a morphogen gradient that decreases in concentration from the tail tip towards the more frontal areas, until it becomes too low and the clock “arrests”. The phase of the oscillator at the specific time and place of arrest determines the edge of the newly-formed segment. The importance of this strategy goes beyond vertebrate development, as similar mechanisms were suggested in insects, plants, and recently even bacteria. Here, I propose to engineer a segment generator in a tissue-culture setup, based on a design which resembles the natural segmentation clock. As this fundamental and well-studied system consists of several regulatory modules, it can serve as a good model for understanding the emergence of complexity by combination of simple sub-systems. We hypothesize that the module combination will be sufficient to facilitate the emergence of robust segmentation. This will be done by introducing the cells with suitable orthogonal genetic constructs which together will form the regulatory circuits controlling self-organization. Specifically, the design will combine a synthetic oscillator, a short-range cell-cell coupling and longer-range morphogen signaling system. In addition, issues of cell fate commitment and robustness will be addressed. This research is expected to shed new light on the design principles governing segmentation specifically, and developmental processes as a whole. For example, it will allow to address questions such as: What is the relative importance of the different modules? How can the size and number of segments be tuned? How does cell proliferation interact with segmentation? Moreover, expanding the scope of synthetic developmental biology toward complex and modular designs can have immense implications for fields such as tissue engineering and regenerative medicine, where induction of predictable and reproducible self-organization is of essence.

Understanding how infants acquire the meaning of words is fundamental to the study of the human mind. Infants master a considerable vocabulary by year 2, yet, learning word meanings is not a trivial task: labels heard can map on many referents in a complex world. Infants must thus constantly aggregate evidence in such ambiguous contexts. Behavioral methods fall short of tracking semantic processing during learning. Therefore, this process, including infant strategies (whether they put their bets on one candidate to reject/confirm it or slowly accumulate evidence) is still poorly understood. To go further, pediatric tools that can peer into the brain networks supporting word-to-meaning mapping in real time are required. Functional ultrasound (fUS) enables noninvasive and dynamic mapping of brain activity in newborns with little restriction. Here, we will use cutting-edge fUS capabilities to investigate neural correlates of representational changes during word learning in 12 months old infants. We will rely on advanced semantic modeling techniques to decode neural correlates of word representations detected by fUS, track such representational changes in the course of learning and unravel infants’ learning strategies.

Aedes aegypti mosquitoes, the major vector for many important diseases, such as Zika and dengue, exist as two separate subspecies, one domestic and another sylvatic, that differ in their olfactory system. Notably, the adaptation to human blood feeding (anthropophilia) in the domestic subspecies is linked to the expression and specificity of an odorant receptor and correlates with increased ability to acquire and transmit viruses, commonly referred to as vector competence. While evolution of immune modulation by the olfactory system is poorly understood, recent findings in fruit flies have alluded to a role of olfaction in promoting anti-pathogenic immunity. We hypothesize that the olfactory and immune systems are connected in Ae. aegypti mosquitoes and that the changes leading to anthropophilia also affected antiviral immunity, resulting in higher susceptibility to and increased transmission of viral infections. In this proposal, we will use a multi-disciplinary approach to identify and functionally characterize the connection between the olfactory and immune systems in the context of antiviral defenses in Ae. aegypti mosquitoes and in the Drosophila model system. We will further investigate the association between olfactory-linked immune modulation and anthropophilic preferences in Ae. aegypti mosquito subspecies and its consequence for arboviral disease epidemiology. Combining comparative genetic, olfactory, virological and immunological analyses, synthesized in an evolutionary modelling framework, this innovative program of work will address a major gap in our understanding of the impact of environmental odor sensing on the immune system and antiviral defense. As such it will shed new light on the evolution of vector competence in Ae. aegypti and could lead to the development of novel strategies to control the transmission of mosquito-borne viruses.

Single-celled marine algae produce half of Earth’s atmospheric oxygen and are the trophic entry point for life in the ocean. A suite of animal-like ion channels has recently been discovered in members of the red-lineage algae, and has been shown to underlie electrical excitability – the same phenomenon that drives a wide range of sophisticated dynamic behaviors in humans. However, in algae, the full mechanistic basis of this dynamic behavior and its widespread physiological implications remain poorly understood. In this study we aim to determine how ion channels work in concert to produce electrical signals in the red-lineage algae and how these ion fluxes impact the chemistry of the cell. Armed with a quantitative understanding and an ability to simulate electrical behavior we will ask the question: what dynamic behaviors are induced by this excitability? We hypothesize that excitability serves vital roles in marine phytoplankton, including regulating calcification, gene expression, interactions with light, and cell-to-cell communication. We propose that only by understanding membrane excitability within a whole-cell context will we be able to determine how the cellular physiology of unicellular algae results in a wide range of poorly understood phenomena, from exquisite control over intracellular biomineralization, to aspects of population growth affecting global nutrient and carbon cycles. We will take a multidisciplinary approach, integrating mathematical modeling with electrophysiological experiments, pharmacological manipulation, and biochemical approaches, to characterize and explore excitability in two model species of marine algae. The work will be physically split between the electrophysiology lab of McClenaghan at Rutgers University, and the computational microbiology and algal growth laboratory of McClelland at UCL, but will comprise a closely integrated program of work leveraging our contrasting expertise. Our proposed project has the potential to unearth undiscovered behaviors in these organisms, with major ecological, climatic and biotechnological implications.

Prolonged developmental plasticity is a hallmark of plant biology. This feature relies on the function of cell clusters with self-renewal and flexible differentiation capacity, which collectively form different types of “meristems”. It is still unclear if a specific molecular makeup support a “meristematic cell”, and how hundreds of cells within meristematic tissues act in coordination to derive various morphogenetic outcomes. Understanding the cellular- and tissue- level mechanistic principles that underlie specification of the multipotent tissues during early development are crucial to answering these questions. Emerging single-cell methodologies provide an unbiased approach for mapping meristematic processes, but their scalable implementation remain challenging due to the rigid-cell wall, laborious tissue handling and the minute sample size. In addition, moving from instantaneous single-cell profiles to understanding tissue-level dynamics remains non-trivial. Liam Dolan's group is utilizing genetics and modern imaging tools to study the early development of the liverwort M. polymorpha from a single spore. This process, which occurs in isolation and can be massively co-cultured, stands as a unique and accessible model to study how self-organization of a single ancestral cell gives rise to different structures, and in specific to understand how a confined multipotent niche is formed and maintained. We propose to perform in-depth temporal dissection of early spore development and to formulate testable mechanistic hypotheses on the principles that guide formation of plant stem-cell niches and regional specialization of cells in those niches. Given the lack of a comprehensive framework to define meristems or meristematic processes, we speculate those may be non-intuitive and cannot be spelled out a-priory. To achieve this, we plan an initial tri-partite profiling experiment: First, we will utilize recent pipeline (Meir et al, 2021) to derive bulk transcriptomes and images from hundreds of individual sporelings. Second, we will perform single-cell RNA sequencing that will draw an exhaustive manifold of cell states. To understand tissue-level differentiation dynamics, we will de-convolute the single-sporeling bulk transcriptomes based on the single-cell map. This analysis will provide rigorous temporal models for flows between cell states, based on observed data. The resulting model, assisted by spatial reporters that will be derived from it, will be then re-evaluated in perturbed genetic backgrounds. This research will (i) discover the acting cellular states within a minutely sized embryonic-like plant differentiation process that was thus far unreachable, (ii) couple molecular to morphogenetic progression, and (iii) test for mechanistic principles that facilitate initial meristem formation. We speculate such discovery can lead to better understanding of the multi- and pluripotent tissues that support the great developmental plasticity of plants.

Biological systems translate environmental stimuli into behaviour by building efficient internal representations from microscopic interactions. The recent availability of large-scale neural recordings sets the testing ground for new theoretical frameworks describing these mechanisms at a population level. However, these theories are hindered by the challenge of solving complex inverse problems in high dimensions. Statistical physics provides powerful tools to tackle this complexity via simple models, such as pairwise interaction models based on the max-entropy principle, that quantitatively predict experimental data in some settings. However, recent work on the mouse hippocampus shows that these models can fail in describing activity from sparsely sampled populations. Moreover, they have been used primarily to describe the states of networks at single moments in time, where correlations are (necessarily) symmetric; it remains challenging to infer the asymmetric connections that support realistic off-equilibrium neural dynamics. This project aims at filling these gaps by devising new analytic models able to capture the complexity of big neurobiological data and accounting for the hierarchy of neural interactions to grasp the collective nature of information processing in the brain. The central hypothesis is that we do not need a detailed microscopic description of brain activity to explain the underlying physical mechanisms. Instead, we should aim at bridging scales via simplified macroscopic descriptions through the powerful dimensional reduction tools of statistical physics. To this end, I plan to build on my background in machine learning (ML) theory, drawing inspiration from recent advances in modelling realistic inputs and input-output mappings. I aim at integrating statistical physics analyses, such as replica theory, with information-theoretic approaches and ML methods in order to extract the relevant features from data. This approach should lead to data-driven predictive theories deeply intertwined with experiments. Indeed, this project would be based on a synergistic effort with experimental groups at Princeton, where advanced imaging, genetic and electrophysiological techniques are developed to measure the dynamics of neurons in behaving animals. In particular, my host supervisors have established collaborations with experimental groups working on the worm C. elegans, the fruit fly, and mouse hippocampus. To summarise, I seek to develop a physical understanding of the core principles underlying collective phenomena empirically observed in the brain via simple yet insightful models. This new theoretical framework could be applied to investigate how structured neural responses arise from relatively unstructured architectures, to what extent neural codes are low dimensional, and which geometries underlie brain representations. This line of investigation thrives in the promising cross-fertilisation arising between neuroscience and ML.

Microbes synthesize proteins that mediate biochemical reactions, communication, and competition in their environments. DNA sequencing of environmental samples has allowed us to catalog proteins in nature. However, small open reading frame-encoded proteins (SEPs) have been overlooked due to technical challenges. SEPs, despite size, impact vital cell functions and can act as antimicrobial agents or signaling molecules. However, the way in which SEPs evolve and their diversity in the environment are unclear. Considering that life evolved from the ocean, where diversity is influenced by greater environmental variability, we can gain insight into the origins, evolution, and ecological relevance of SEPs through a systematic investigation of ocean microbiomes. Here, I will develop a computational approach to leverage sequence and structural information by machine learning algorithms to identify novel bioactive SEPs in the most extensive genomic resource for ocean microbiomes. Next, by integrating multi-omic data across various spatial and temporal scales, I will conduct an in-depth analysis encompassing the following aspects: 1) Identification of SEP functional clusters within ocean microbiomes; 2) Comparative analysis with other biomes; 3) Examination of genetic and environmental factors influencing SEP evolution; 4) Exploration of co-evolution patterns. Finally, I will verify the antimicrobial efficacy of newly discovered SEPs that could help tackle the looming antibiotic resistance crisis. This project will expand the functional landscape of ocean microbiomes and highlight evolutionary mechanisms of SEPs as ecological modulators. This has the potential to lead to significant discoveries about interactions in microbial communities and to inspire innovative biotechnological applications.

Microbial communities play a central role in ecosystems and make up to 20-30% of the total world biomass. They engage in different types of interactions, from mutualism to competition. Several studies have shown that these interactions are plastic and can change when biotic (e.g. species composition) or abiotic (e.g. nutrients) factors are modified. Manufactured chemicals such as pesticides are a major long-term stress to which microbial communities are exposed. These compounds can be detected in soil, water and even in our body up to years after the exposure and are close to exceed the planetary boundaries. However, it is still unclear how microbial molecular interactions and the genetic composition of microbial consortia evolve during co-adaptation to pesticides at an evolutionary time-scale and how this can be generalised to different communities and conditions. Moreover, emergent properties of microbial consortia such as the rate of pesticides degradation or co-adaptation can not be predicted from the response of single species. In this project, we propose to go beyond single-species adaptive evolution and investigate how microbial species co-evolve during long-term exposure to pesticides. To this aim we will use a combination of bottom-up and top-down approaches evolving artificially-assembled microbial communities and natural ones isolated from soil, water and the human gut. We will expose the selected microbial communities to representative chemicals of a library containing ~1000 pesticides and track how species composition changes during the co-evolution. We will dissect which genomic alterations are responsible for the adaptation during the experiments by performing genome-sequencing of the co-evolved communities and of single strains isolated from them. This approach will enable us to unveil how emerging strains carrying new genetic variants interact with the microbial community and whether these new interactions lead, for instance, to co-adaptation or community collapse. The genomic analysis will be coupled with a metabolomic study of some of the evolved communities to understand how genetic alterations translate in an altered metabolic network. Then, we will evaluate if patterns of polymicrobial convergent co-adaptation emerge across different conditions by comparing replicates of the co-adapted communities. Finally, we will use the evolved communities to assess ecological co-selection when microbial consortia co-adapted to similar or different pesticides are brought together (coalesce). These experiments will tell us how interspecies interactions co-evolve during adaptation to manufactured chemicals and whether co-adapted microbial communities influence each other during community coalescence. This project aims at expanding the frontier of our understanding of co-adaptation of multi-species microbial populations and will provide an unprecedented view of how microbial consortia co-evolve, stabilise and build community resilience.

Background of the proposed research project : To position organelles and transport vesicles and mRNAs inside the cell, cargoes recruit molecular motor proteins that walk unidirectionally along microtubules. Polarised microtubule arrays span the entire cell. Cytoplasmic dynein is the major retrograde motor, while more than a dozen different kinesins transport cargo towards the cell periphery. Active transport in both directions is essential, especially for neurons. Therefore, mutations in molecular motors cause neurological and neurodegenerative diseases. Recent progress, in structural cell biology and biochemical reconstitution experiments, enabled an understanding of how the activity of motors is triggered by binding to cargo adapter proteins. However, how these mechanisms control cycles between autoinhibited and active states of motor proteins in the context of the cell remains to be elucidated. This is particularly interesting for bidirectional motility which enables cargoes to avoid traffic jams on microtubule ends and other obstacles and to rapidly search the cytoplasm for their destination. Central Hypothesis : We hypothesize that cargoes bind to motors of opposite polarities at the same time, and mechanical or biochemical regulatory mechanisms trigger switching the transport direction. This enables efficient cargo transport in either direction, a swift response to obstacles, and efficient redistribution of motors. Aim of the proposed research project : To test this hypothesis, we aim to directly visualize individual molecular motors in cells, obtain their detailed life histories, and understand their engagement with microtubules and cargoes. Specifically, we aim to determine: 1) duration and fraction of time that individual motors bind to a cargo/move along microtubules, 2) how motor life histories change when we deplete/overexpress motor regulators, 3) whether motor engagement is regulated by the cargo. Experimental system : We will tag kinesin-3 KIF1C and dynein with fluorogenic nanobody arrays or inject fluorocube-labelled motors for long-term imaging in human cells using lattice light sheet microscopy. We will co-label cargoes, endosomal markers, or cargo adapters such as Hook3 to which both KIF1C and dynein can bind. From these data, we will extract detailed life histories of single motor molecules and will be able to correlate this to the transport of different cargoes. From the difference in cargo behavior in response to the recruitment of a labeled motor, we aim to infer the total number of active motors on each cargo. Conclusions: Discovering how motors behave in cells is key to understanding the mechanism of fundamentally important transport processes. We will use state of the art technology to establish new single-molecule live cell imaging tools to understand how motors engage with cargoes to bring about their observed motility in a physiological and pathological context.

Schistosomes, the parasitic trematodes which cause the chronic infection schistosomiasis –a major neglected tropical disease affecting more than 200 million people worldwide, have a complex life-cycle involving infection of an aquatic snail intermediate host and a definitive mammalian host. Despite lacking apparent locomotory mechanism, schistosome eggs are able to transit through gastrointestinal tissues into the lumen for excretion, a journey that clearly presents an evolutionary challenge to the parasites. How the eggs are able to translocate in the gut remains unresolved puzzle. In this study, we aim to clarify the migratory mechanism of schistosome eggs from the perspective of tissue mechanics. We posit that anisotropic cell clustering and fibroblast-dependent changes in tissue mechanics following immune reaction to egg deposition may confer a propulsive advantage to the eggs, enabling them to tactfully transit through the host tissues. To clarify the role of fibroblasts in this process, we aim to develop both in vitro and in vivo models, and use them to track fibroblast migration spatiotemporally. First, we will establish a 3D microphysiological system that recapitulates the gastrointestinal tissue where egg migration takes place in vivo. Next, we will deploy the technique of 3D traction force microscopy integrated with atomic force microscopy to map the forces generated around a migrating egg, and correlate them with fibroblast dynamics. Finally, by integrating data from timelapse live cell imaging, cell migration tracking, force mapping, immunological characterization and genetic profiling, we will characterize fibroblasts movement and contractile force generation during granuloma formation and egg migration. Ultimately, we will develop a quantitative mechanistic model of egg migration based on tissue mechanics. Clarifying the egg propulsion mechanism will complement past and on-going biological studies, leading to a better understanding of how schistosomes adapt and exploit the symbiotic relationship with the host to continue their complex life cycle. In addition, since fibroblasts are gaining scientific attention for their role in aiding cancer development, clarifying their role in the propulsion of Schistosoma eggs will deepen our understanding of fibroblast contribution to the development of other diseases such as cancer and tuberculosis (TB).

DNA mutations occur randomly throughout the genome; then natural selection removes mutations from the important regions. This long-standing premise of evolution has been challenged, as studies revealed the mutation occurrence itself varies among genomic loci (mutation bias). Studies using Arabidopsis thaliana have demonstrated that essential genes mutate less, and those genes have distinct chromatin modifications, in particular H3K4me1. This observation leads to a hypothesis; the chromatin modifications that cover the genes locally repress DNA mutations, potentially influencing the genome evolution. However, this hypothesis is untested, and the mechanisms behind mutation bias remain unknown in plants. Here I propose the first two steps and one backup plan on a long road to understanding the mechanisms of mutation bias using model system A. thaliana. As a first step, the causal relationships between chromatin modifications and mutation bias will be experimentally tested. In mutant plants of selected chromatin modifications such as H3K4me1, I will quantify the mutation bias. To this end, I will employ genome sequencing and experimental evolution systems developed by the host researcher. This approach will identify the chromatin modifications (hereafter modification X) responsible for biasing the mutation. In the second step, I will examine the molecular mechanisms of how 'modification X' affects local mutation rates using genetic screening. The screening utilizes the fact that DNA stress is inducible by radiation or drugs, and the plants susceptible to the stress exhibit a scorable phenotype. For example, if the lack of modification X enhances double-strand break(DSB), then the root of the mutant-of-modification-X will be shorter than Wild Type (WT) in the presence of phleomycin, a drug that induces DSB. In the pool of the mutant-of-modification-X, I will screen for the second site mutations that suppress or enhance the DNA-stress-induced phenotype. Characterizing the enhancer and suppressor genes will map out the molecular black box that generates mutation bias. As a backup plan, in case the first step demonstrates any of the tested chromatin modifications have minimal effect on the mutation rate, I will explore the evolutionary universality of the mutation bias phenomena by examining the genomes of other organisms. This approach may provide new insights into the cause of mutation bias. A deeper understanding of the biology underlying mutation biases has the potential to refine our view of mutation’s role in evolution. This study investigates 'chromatin-directed mutation bias hypotheses', providing clarity into how organisms can influence evolution through mechanisms that affect intragenomic variability in mutation rate. New research projects may arise, such as investigating the fate of the genome in the presence of mechanisms to bias mutation and how selection acts on mechanisms that control mutation rates.

Background Mosquitoes are often defined as the deadliest animals on earth for their potential to transmit dangerous pathogens to humans. Aedes aegypti is the prime vector for arthropod-borne viruses such as Dengue (DENV), Zika and Chikungunya. Arboviruses are (re)emerging diseases whose burden on public health is expected to increase concurrently with the global expansion of Aedes aegypti. Arboviruses and mosquitoes share one common target: humans. The transmission of arboviruses depends on the success of infected female mosquitoes in obtaining human blood meals, which they require to reproduce. Prior work has suggested that DENV may manipulate its mosquito host to enhance virus transmission, but this has never been mechanistically investigated. Hypothesis Arboviruses hijack mosquito physiology to promote more aggressive host-seeking and blood-feeding behaviour in mosquitoes, which in turn increases DENV transmission. Viral non-structural proteins may control host gene expression in the mosquito to heighten their sensitivity to humans, increase their motivation to bite, or shift their daily activity timeframes . Aims I will examine the effects of DENV infection on the mosquito brain and sensory systems. How mosquito activity is modified upon infection will be tested, while taking into consideration how the virus affects insect fitness. Molecular changes in gene expression in brain and sensory system will be studied to reveal host-virus interactions. Each individual viral non-structural protein will be functionally tested in-vivo to determine its role in changing mosquito gene expression and ultimately shaping the insect brain and sensory apparatus. Experimental system To test for behavioural changes in DENV-infected mosquitoes, I will take advantage of different behavioural assays: olfactometers, activity monitors and feeding assays. Mosquito survival, fecundity and fertility will be evaluated to quantify the impact of viral infection on the host fitness. Next, I will use RNA and smallRNA sequencing to produce an atlas of differentially expressed genes plus antiviral and regulatory small molecules in infected mosquito brains and antennae. Lastly, I will genetically engineer mosquitoes to express DENV non-structural proteins in brain and sensory neurons in a controlled and reversible way, mimicking a viral infection. This will allow me to make mechanistic linkages between the effect of DENV on gene expression in the host, and subsequent effects on the aggressiveness of the mosquito vector in finding and drinking the blood of human hosts. Conclusion My results will expand our understanding of the complex relationship between mosquito vectors and arboviruses and inform novel methods of vector control. In addition, I will generate transgenic mosquito lines containing single arboviral non-structural proteins: a useful resource for further study on mosquito-virus interactions.

Diverse ethological goals drive species-specific specializations in body morphology, biomechanics, and neural circuitry. However, how these features adaptively coevolve remains poorly understood. As an HFSP Long Term Fellow, I will address this important knowledge gap by comparing the biomechanics, neuroanatomy, and neural dynamics of morphologically and behaviorally divergent species of flies: Drosophila prolongata (‘Dpro’), and its closely-related sister species Drosophila rhopaloa (‘Drho’), and the commonly studied Drosophila melanogaster (‘Dmel’). Dpro males have massively enlarged forelegs (>5 times the volume) relative to Drho and Dmel males. They use these enlarged limbs to perform a species-specific high-frequency leg vibration during courtship. This courtship behavior and limb enlargement may have coevolved via sexual selection. Notably, Dpro males must also use their enlarged forelimbs to perform common behaviors like walking and grooming. Thus, coincident with this morphological adaptation, I hypothesize that during evolution, Dpro males (i) established new neural circuits to control high-frequency leg vibrations, and (ii) adapted existing neural circuits to control walking and grooming with massively enlarged forelimbs. To test these hypotheses, I will develop new transgenic, computational, and microscopy tools. Using these, I will measure and model the relationship between the evolutionary specializations in the body and nervous system of Dpro males. First, I will determine how motor commands have adapted to compensate for the morphological specialization of limb growth. I will quantify these species’ limb movements in 3D and model joint torque dynamics in novel Dpro and Drho neuromechanical simulations. Second, I will identify how motor neuron populations controlling the front limbs–but not middle or hind limbs–may have expanded in Dpro to enable a wider dynamic range of joint torques. I will do this by generating transgenic Dpro and Drho expressing photoactivatable fluorophores and using these for neural circuit mapping. Third, I will discover to what extent a dedicated pool of motor neurons, not present in Dmel or Drho, becomes active during Dpro leg vibrations but not during common walking and grooming behaviors. I will do this by generating transgenic Dpro and Drho expressing indicators of neural activity and imaging motor circuit dynamics during behavior. These studies will reveal fundamental principles of how body morphology and neural circuits coevolve to enable behavioral specializations. Evolutionary and comparative neuroscience is an exciting new research direction for me, my host lab, and the field of motor control. I will learn new experimental approaches and apply them in contexts that are new for my host lab. I envision that comparative studies of neural circuits and behavior will reveal general principles of how nervous systems evolve, pushing the frontiers of both neuroscience and evolutionary biology.