Most gaseous oxygen (O2) on Earth is produced via oxygenic photosynthesis. However, new evidence indicates that O2 is also produced in permanently dark ecosystems. This so-called “dark oxygen production” (DOP) can proceed via abiotic chemical reactions or via microbial dismutation of chlorite and nitric oxide—metabolisms fundamentally different from photosynthesis. Recent work suggests that microbial DOP is widespread in groundwater ecosystems, yet definitive evidence is lacking to date. Our team has the abilities, instruments, and expertise to provide such evidence and elucidate the origins, processes, and production rates of groundwater O2. We hypothesize that microbial DOP is a globally relevant process in groundwater ecosystems today, and that groundwater aquifers represent model systems to study O2 production and consumption in the deep geologic past, as well as in subsurface ecosystems of other celestial bodies. We propose an international, multi-disciplinary project to provide comprehensive insights into the geochemistry, microbiology, and ecology of DOP. Our combined expertise leverages three key technological advances: (1) triple- and clumped-oxygen isotope analyses, which can unambiguously link O2 to biological DOP origins (led by PI Hemingway), (2) determination of DOP rates and fluxes at unprecedented resolution using nanomolar O2 concentration measurements (led by PI Kraft), and (3) high-throughput analyses of O2-producing enzymes and pathways present in complex communities using genome sequencing and protein mass spectrometry (led by PI Ruff). We will apply these techniques to a sample set from diverse aquifers spanning a broad range of ecosystems in Canada, Finland, Germany, Switzerland, and the USA. We expect several key outcomes. First, we will determine the first ever triple- and clumped-oxygen isotope signatures of DOP by different biotic and abiotic sources, values that are needed to decipher natural signals. Second, we will use stable isotope-labelling to determine rates of microbial DOP in groundwaters, critical measurements that are lacking to date. Finally, we will conduct the first global survey of key microbial lineages and genes to understand the diversity, abundance, and activity of microbes involved in DOP. These insights are crucial to understand groundwater aquifers, which represent Earth’s largest source of drinking water.

It is increasingly clear that microbes can influence host health and fitness. In particular, microbes affect important developmental transitions like metamorphosis in mosquitoes and flowering time. The timing of these transitions is central for organisms responses in changing environments. However, we do not know which microbes alter such traits and how they do it, or whether it is adaptive for the microbes or a consequence of their metabolism. Through integration of life-history models, microbial physiology, community selection, and plant evolutionary ecology, my goal is to understand microbial effects on plant developmental timing. The ultimate goal is to generate predictive models of when are microbes more likely to impact plant development, which microbial functions are involved, and how are these interactions going to change with an increasingly variable environment. One intriguing hypothesis is that since microbes are indicators of environmental and ecological conditions, they can provide accurate information about optimal phenology to the plant hosts while integrating to noisy variation. I will use flowering time in Arabidopsis thaliana as a experimental system to determine how microbial community function might change with changes in temperature. Recently, Dr. Rebolleda-Gomez developed a predictive model microbial community change across temperatures in simple carbon sources. In collaboration with members of the lab, I will extend these models to more complex communities. Using this data I will be able to analyse the information and reliability of changes in microbial functions over time (compared to the temperature series alone) to evaluate the quality of microbes as cues. These mathematical approaches are new to me, but as part of my postdoctoral formation at UCI I will benefit from the expertise in microbial ecology of Dr. Rebolleda-Gomez and time series analyses of Dr. Symons (a close collaborator). Using recently developed theory on community level selection, I will select from different substrates, microbes that significantly affect flowering time and inoculate A. thaliana lines with different flowering plasticity. I will test the effect of such communities in different thermal conditions to determine when and why plants respond to microbes. Using omics approaches, I will characterize from the selected microbial communities the metabolic functions that are associated with either late or early flowering time. Finally, I will incorporate our insights into predictive life-history models to evaluate possible effects of microbes on plant adaptation to climate change. Altogether, this project will allow me to gain insights into the mechanisms by which microbial communities affect plant phenology, and to hypothesize about the evolutionary implications. This fellowship will allow me to learn the mathematical and experimental tools necessary to generate predictive models of microbiome effects on plant development.

Tissue folding is widespread in morphogenesis. It often arises due to geometric frustration associated with growth mismatch. One of the big questions is how organisms take advantage of the local mechanics, differential growth, and physical and geometric boundary conditions of tissues to drive this folding. One such example may be found in the final stages of Drosophila wing development. During metamorphosis, the wing elongates along the body of the fly as a planar sheet before anchoring to the hard cuticle layer encasing it. From 30 hours into metamorphosis up to 96 hours when metamorphosis ends, the wing has grown by more than an order of magnitude in surface area. The wing manages to continue to grow in the confined space over these 66 hours by folding. During this period, as the wing continues to grow, it also becomes thinner and develops more folds. However, the driving mechanism for this folding phenomenon and the level of variability in the shape change across individual wings are not known. We propose to study how the physical and geometric constraints on the wing and the differential growth of the cellular layer and its attached extracellular matrix (ECM) allows the wing to fold. This project will be an incorporation of live imaging in 3D through the highly robust Gal4-UAS system to identify geometric changes to the wing as it develops folds and will require an analysis of 3D-reconstructed images to identify the patterns of shapes that emerge and the recurrence or variability of these patterns across wings of different individuals. A key piece to better understanding the role of this differential growth between the cells and the ECM as well as the constraints on the folding process will involve genetic and physical perturbation of the wings to further study how making alterations to the development of the wing changes its folding pattern. These include using recently developed optogenetic systems to spatially control changes to local cellular growth rates and the use of genetic mutants to examine how the changing the expression level of genes and the distribution of their resultant proteins affect the boundary or growth conditions on the wing and thus affect the folding pattern. We will also examine how the wings unfold at various time points during development by removing the boundary that encases them and watch how they unravel. We expect these experiments and the concurrent analyses will allow us to understand how boundary conditions that confine the wing and the differential growth and material properties between cell and ECM combine to allow the fly to continue to develop its wings under spatial confinement.

The ecology of bacteria is directly tied to the ecology of the mobile genetic elements (MGEs) that infect them. These elements act as parasites or symbionts, spreading horizontally between bacteria and shaping the genetic repertoire of their hosts. MGEs can be beneficial when carrying traits like metabolic pathways, virulence genes, or antibiotic resistance, which allow their host bacteria to thrive in new environments. Yet, they are also costly due to the expression of the encoded genes. Additionally, evidence is emerging of extensive interaction and competition between MGEs. Many MGEs co-circulate in natural bacterial populations and co-carriage within the same bacterial host is common. However, little is known about “coexistence conditions” for MGEs: how can diverse MGEs be maintained in the same population? And how does this affect the bacterial community in which they circulate? We aim to address these questions for plasmids, a type of MGE frequently implicated in the spread of antibiotic resistance. Plasmids commonly code for genes that prevent further infection by similar plasmids (“superinfection”). We hypothesize this naturally leads to non-transitive interactions between plasmids that compete for the same bacterial hosts, and that this can maintain a diversity of plasmids even in the absence of selection for plasmid-borne traits. Non-transitive interactions work like the game “rock-paper-scissors”: each strain both inhibits and is inhibit by other members of the community. Such interactions have been proposed as a prime driver of species diversity, yet experimental realizations thus far remain restricted to bacteriocins or antibiotics, with limited extension to explaining MGE diversity. We intend to study these dynamics in an experimental system using Escherichia coli strains that differ only in their carriage of two competing antibiotic resistance plasmids: (i) “F0” carries no plasmid and grows fast, (ii) “ML” carries a non-conjugative plasmid with medium cost, and (iii) “SC” carries a costly conjugative plasmid and grows slowest. As a result, F0 outcompetes ML due to growth, ML outcompetes SC due to growth and immunity to superinfection, and SC outcompetes F0 since the conjugative plasmid transforms F0 into SC. We will use pairwise and 3-way competition experiments to study the stable states of this system over multiple growth-dilution cycles. By varying parameters of the experiment, like growth rate, dilution, dispersal, and relative costs, we can probe the conditions for plasmid coexistence over a range of scenarios. Mathematical modelling will help scale these transitivity rules to a broad diversity of co-circulating plasmids and predict their influence on the stability of more complex bacterial communities. Understanding such plasmid diversity and maintenance is directly relevant for the study of bacterial colonization and infection of human and animal hosts, as well as the spread of antibiotic resistance.

The evolution of the nervous system is one of the remaining great mysteries of animal evolution. A key step was evolution of the chemical synapse, which enabled the transition from ciliomotor-based movement by diffusive signals to muscle-based locomotion driven by ultrafast localised signals. However, current understanding of this transition is mostly limited to determining the distribution of synaptic genes in early animal genomes, revealing most predate synapses. There are two competing hypotheses for how chemical synapses evolved. The first, termed the “chemical brain hypothesis”, proposes animal behaviour was initially controlled by paracrine cell networks using volume (non-synaptic) signalling. The second, termed the “protosynaptic hypothesis”, proposes that synaptic architecture already existed prior to the origin of true nervous systems, and facilitated some form of directional signalling. To test these hypotheses, we integrate expertise in synaptic dynamics and physiology, functional proteomics, and transgenesis techniques in early animals to uncover how synaptic signalling is achieved in the first animals without synapses (sponges) and those with synapses (cnidarians). To accomplish this, we will reconstruct the ancestral dynamics and localisation of synaptic protein complexes, discover the origins of ultrafast mechanisms for synaptic exo- and endocytosis, and determine the role of electrical potentials in propagating the first synaptic signals. In summary, our study aims to reveal the mechanisms underlying the origin of synaptic transmission with broad implications for the evolution of animal behaviours.

Background: The spatiotemporal organization of T-cell receptors (TCRs) is critical to target cell recognition that underlies a novel class of cancer therapies. While dynamic receptor reorganization was observed in canonical T-cells, less is known about the recognition mechanisms of gamma delta (gd) T-cells, which are emerging as attractive candidates. Specifically, the spatiotemporal organization of their receptors upon immune synapse (IS) formation, their mechanosensitivity, and possibly crucial membrane deformations remain largely unexplored. While high-resolution fluorescence microscopy of T-cells contacting supported lipid bilayers (SLBs) presenting target proteins has been crucial to dissect canonical T-cell organization and signaling, SLBs containing select antigens and adhesion molecules cannot be used to probe gd T-cells as not all factors involved in antigen presentation are known for gdTCRs. Aims: Combining my expertise in membrane biophysics and SLB fabrication on non-rigid substrates with the host’s expertise in biophysics, high-resolution fluorescence microscopy and T-cell immunology, we will reveal the spatiotemporal organization of gdTCRs upon immune synapse formation between T-cells and tumor cell-derived SLBs. In brief, we will: A0. Establish experimental platform - mechanically tunable, tumor cell-derived SLB A1. Map the spatiotemporal (re)organization of gdTCRs upon IS formation A2. Assess effect of surface rigidity on organization of gdTCRs and gd T-cell activation Hypotheses: I conjecture that gd T-cell receptors undergo specific spatiotemporal organization to allow antigen recognition in infection and tumorigenesis. Clustering of TCRs in canonical T-cells and exclusion of phosphatases from the IS amplify the signal from antigen-binding events, but dynamic TCR reorganization in gd T-cells remains unexplored. Intriguingly, receptor organization may interplay with membrane deformation and mechanosensitivity, which may both be critical to T-cell activation. I will study this by modulating support rigidity, with which I have ample experience. Experimental approach: E0: Develop polymer-based supports for fluorescence microscopy. Harvest plasma membrane vesicles from tumor cell cultures. Optimize SLB formation. E1: Total internal reflection fluorescence microscopy - single molecule tracking of synaptic components upon gd T-cell contacting tumor cell-derived SLB. E2: Measure force of gd T-cell–SLB interaction as a function of SLB rigidity using atomic force microscopy-based single-cell force spectroscopy and acoustic force spectroscopy. Conclusions: I will observe the spatiotemporal organization of gdTCRs upon immune synapse formation at the molecular level, gaining insight into their activation mechanism – an unresolved question that has stymied progress in gdT-cell application in immunotherapy. I expect my novel, tumor-cell derived experimental platform to open up a range of new avenues in gdTCR research.

Why do some organisms have shiny colours and others do not? Shiny colours are displayed across a suite of plants and animals, including the flowers of buttercups, orchids and tulips, the wings of butterflies, and the surfaces of beetles. The visual appearance of these organisms is dominated by a flash, which entails a bright pulse of polarised light with a strong angular dependence. The dynamic nature of such “flashy” effects presents a paradox in visual ecology, because although flash effects likely enhance long-range signal visibility, they may undermine the ability to locate objects at close range. This may help explain why colours with a matte appearance prevail in nature, yet the repeated independent evolution of shiny colours implies a fundamental, possibly universal adaptive benefit for signal dynamicity per se. Our project will constitute the most integrative cross-taxon approach to understanding the basis of this adaptive benefit conducted to date. We will achieve an integrative understanding of the ecological significance of flashy colours by: (1) characterising the optical properties of sexually deceptive flowers and relating these to their insect models; (2) quantifying how flower gloss determines the long-distance visibility and short-distance discriminability of flowers to insect pollinators; (3) determining the behavioural significance of flashy colours in insect visual ecology; and (4) elucidating how the insect brain processes bright flashes. Hence, we will trace the full pathway from how such signals are generated to how they ultimately elicit fitness effects in their relevant viewers. This breadth of insight is only possible by integrating our collective expertise in biophysics (van der Kooi), behavioural ecology (Kemp) and neurobiology (Kinoshita), which is precisely why this project promises unprecedented insight into a (literally) brilliant phenomenon that has fascinated researchers for centuries.

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.