Memory is typically treated as representing past experiences, including salient events and stimuli. A key purpose for the retention of these memories is to provide predictive information that guide the animal’s future behavior - where it will go and what it will do. However, the world is rarely static, and memory therefore requires continuous updating from sensory information. While sensation and memory have been well studied separately in tightly constrained tasks, little is known about how they interact to enable complex behaviors. This proposal aims to understand how these three processes – behavior, sensation, and memory – predict each other while animals freely move within an environment, and how these predictions are altered based on an animal’s experience and the predictability of its environment.
We will test three general hypotheses about the interactions between sensation, memory and behavior: (1) Memory evolves from being learnt from (i.e. instructed by) sensation and behavior in a novel environment, to being predictive of (i.e. instructing) sensation and behavior in a familiar environment. (2) The direction of predictability between processes (i.e. which process instructs another) are dynamic and can be manipulated by changing the context of the environment. (3) The direction of predictability is dependent on the predictability of the environment, with memory instructing sensation and behavior for predictable features, but sensation instructing the other processes for unpredictable features.
We will test these hypotheses in an environment with static (predictable) and mobile (unpredictable) features. We will combine long-term recordings from large populations of neurons in the visual cortex and the hippocampus of freely moving animals, high-resolution behavioral measurements, and statistical modeling of neural and behavioral dynamics. Our experiments will provide unprecedented measurements of the neural representations that underlie natural behavior. They will show how these animals, and potentially ourselves, use representations of the past to predict the future.

Sequences of place cells, hippocampal neurons active when a subject enters a particular location, encode spatial trajectories while navigating a given environment. During periods of restful wakefulness and non-REM sleep, condensed sequences corresponding to prior navigation recur during sharp-wave-ripple events in the hippocampus, the disruption of which disturbs memory. Enabled by the use of large-scale neural imaging, recent work has revealed that these sequences are in fact composed of multiple discrete neural assemblies connected together. Understanding such assembly activity during various behaviors is critical as they may represent the basic unit upon which memories are encoded. However, the functional organization of the microcircuits, including assembly activity, recruited during REM sleep (REMs) remains unknown despite the recently confirmed role for REMs in the formation of spatial memory. The goal of the research outlined in this proposal is to address this issue using large-scale neural imaging in the hippocampus of fully habituated head-fixed mice. Specifically, this research aims to investigate the occurrence and characteristics of neural assemblies during REMs under baseline conditions as well as following learning of a spatial task. As a final step, local microcircuits within the hippocampus will be manipulated optogenetically during REMs following spatial learning in order to probe for a direct relationship between place cell (assembly) activity during REMs and subsequent memory performance. Cumulatively, these experiments will provide a novel characterization of the recruitment and mechanistic role of neural assemblies in the hippocampus during REMs.

Non-invasive transcranial stimulation and imaging of targeted neurons deep in brain are a central goal of neurobiology and related engineering science. Optical techniques, such as imaging and optogenetics, have revolutionized experimental neuroscience but are limited by the inability of visible light to penetrate deep into brain tissue. Here I propose an approach for transcranial near-infrared (NIR) deep brain stimulation and imaging by taking advantage of upconversion nanoparticles (UCNPs). UCNPs are lanthanide-doped nanocrystals unique in their ability to absorb tissue-penetrating NIR light and convert into emission in both visible and NIR spectral ranges. First, I will demonstrate UCNP-mediated optogenetics for deep brain stimulation, where UCNPs will be employed to convert transcranial NIR irradiation into visible emission to stimulate rhodopsin-expressing neurons in mouse brain. Second, I will develop blood-brain barrier-crossing UCNPs for targeted imaging of molecular markers in deep brain. For proof of concept, UCNPs will be conjugated to curcumin, a specific binder to beta amyloid - a molecular marker of Alzheimer’s disease, therefore allowing transcranial imaging of amyloids by UCNPs’ NIR emission. Finally, I will integrate the dual functions of UCNPs in deep brain imaging and stimulation, by taking advantage of their simultaneous NIR and visible emission, to achieve transcranial diagnostic imaging and optogenetic treatment of neurological diseases in model mice. The new techniques developed here will allow for non-invasive brain stimulation and imaging without the need for implants, and hold potential for next-generation remote neural therapeutics.

The human brain gains much of its computational abilities from the trillions of connections made between cells by synapses. Molecular changes in synapses (a process called synaptic plasticity) are considered to underlie learning and memory. An important component of the synapse is the postsynaptic density (PSD). This specialized structure has been studied extensively to understand its function, in particular because >100 neurologic disorders (such as autism spectrum disorder and schizophrenia) have been associated with PSD dysfunction. Information regarding the overall molecular architecture of the PSD, however, is largely incomplete, in part because the PSD is extremely complex, containing hundreds of individual components connected in a dense network. The PSD is also highly dynamic and asymmetrical—two properties that render protein structural analyses challenging. While solving the structure of the entire PSD seems insurmountable, half of the PSD’s mass is composed of only ten classes of linker proteins. We hypothesize that these highly-abundant proteins form a molecular scaffold, a network we term the ‘postsynaptic scaffold’ (PSS). We aim to develop an approach we call the ‘Thermophile-Assisted Postsynaptic Architecture Strategy’ (TAPAS) to solve the PSS structure. Given the delicate nature of proteins, structural biologists like to work with resilient, temperature-resistant proteins that can be obtained from thermophilic organisms. For brain-derived proteins, there is one animal known to be comfortable at temperatures >50 °C: a worm that lives on hydrothermal vents in the Pacific Ocean. We plan to sequence this worm’s genome (Alvinella pompejana) to find the PSS proteins that it shares with humans. We will determine the structures of the thermophilic proteins by X-ray crystallography. As much of the PSS architecture consists of filamentous structures that do not crystallize, we will use cryo-electron microscopy to define these larger structures. Finally, we will integrate several other methods (biochemical, proteomic, bioinformatic and advanced electron tomography methods) to build a model of the overall PSS. Achieving this ambitious goal will inform studies into learning and memory, lead to new treatments for devastating brain disorders, and help explain how the synapse contributes to human cognition.

Pattern recognition receptors (PRRs) of the innate immune system recognize structures that are shared by a large group of microbes. Originally posited as the initiators of immunity recognizing pathogen-associated molecular patterns (PAMPs), it was realized that PRRs also detect structures on symbionts which were therefore termed microbe-associated molecular patterns (MAMPs). In addition to initiating inflammation, MAMPs are also involved in the maintenance of symbiosis and in the development and regulation of the immune system. Given the very large microbiota resident in the intestine, a significant amount of intestinal MAMPs penetrates the circulation and modulate diverse aspects of immunity and physiology. For this project, we have developed a transgenic mouse system to control the expression and delivery of a MAMP into the host and assess its impact on immunity and physiology. We will assess the molecular mechanisms governing MAMP detection in the host and impact on development of immunity both basally to maintain homeostasis and during disease. As early life exposure of MAMPs likely modulates effects later in life, we will determine if fetal and neonatal exposure to MAMPs imprints the host. Moreover, as the penetration of MAMPs into the host is normally controlled by the innate immune system, we will use transgenic mice lacking this compartment to assess how innate immunity modulates physiology through the control of MAMPs. We thereby aim to determine the impact of MAMPs on the host, and the threshold levels of MAMPs beyond which immunity and physiology cross into pathology. This study will open the way for the use of MAMPs as modifiers of human physiology.

While microbial pathogens evolve during infection to adapt to the human environment and overcome antibiotic treatments, little is known about how adaptation is affected by other co-infecting species. Recent advances in whole-genome sequencing and phenotyping of microbial pathogens derived from human hosts during infection reveal that bacterial pathogens can diversify quite rapidly within a single patient, accumulating mutations that allow them to adapt to challenges presented by the human environment, as well as to overcome antimicrobial treatments. Yet, pathogens within the human body often do not evolve alone. Indeed, many complex infections, especially long-term chronic infections, involve multiple co-infecting pathogenic species within the same patient. In such polymicrobial infections, interactions between pathogens can determine virulence and alter the nature of evolutionary adaptation for each species. As an HFSP Fellow, I will investigate how interspecies interactions influence pathogen evolution in patients. First, I will focus on the cystic fibrosis lung, a canonical site of polymicrobial infections. Second, I will expand to a wide range of infections, leveraging clinical data from >2 million patients. This research will improve our ability to predict how pathogens will evolve in the human body and to design new strategies to thwart their evolution.

The recent discovery of 7-deazapurine bases in bacterial and bacteriophage DNA revealed an unexpected interplay between RNA and DNA modification pathways. In phages, these hypermodified bases could play major roles in pathogen-host interactions, DNA replication, DNA-packaging into capsids, gene expression and bacteriophage evolution. Using a combination of genetic, biochemical and sequencing approaches, our objectives are to discover i) how widespread is this phenomenon, ii) the exact pathway(s) leading to the incorporation of these alternative bases into DNA, iii) the “raison d’être” for these modified bases, and iv) if this phenomenon arose as an offensive or as a defensive tool.
To characterize the distribution of 7-deazapurine bases in bacteriophages DNA, we will use several approaches including comparative genomics, mass-spectrometry analysis of modified bases, high-throughput sequencing of restriction endonuclease resistant environmental virome samples, and genome sequencing of phages infecting a wide range of bacterial hosts. This will generate a collection of diverse, sequenced and partially characterized phages that will be made publicly available via deposition in the Félix d’Hérelle Reference Center for Bacterial Viruses. Biochemical, molecular biology and genetic studies will be performed on phages harboring a variety 7-deazapurine variants to elucidate these novel DNA modification pathways. We will also study the role(s) played by the DNA modifications in phage biology, with a particular emphasis on understanding their potential role in overcoming host defences or in facilitating phage-mediated destruction of unmodified host DNA. In addition to classical biochemical, genetic and omics methods, third generation sequencing (PacBio and Nanopore) technologies will be exploited. These can already detect simple DNA modifications, like methylation, but we will combine machine learning with the sequencing of phage DNA molecules containing specific 7-deazapurines to expand the range of detectable DNA modifications. Although the scope of this project is limited to deciphering the role of 7-deazapurines in bacteriophage DNA, our results could spark developments of new genome editing tools and increased knowledge on gene regulation and epigenetics that may some day change paradigms in human health.

Proteins in the cell can undergo liquid-liquid phase separation (LLPS), forming liquid droplets - the so-called “non-membranous organelles”. The Michnick group has shown that protein liquid droplets generate work to drive membrane invagination in clathrin-mediated endocytosis. I propose an entirely new role for protein liquid droplets in membrane biology: protein transmembrane transport. My studies will focus on exploring a molecular-level mechanism of protein import from the cytosol to the peroxisome lumen, a mysterious process that occurs without the need of proteins being unfolded. Although this process is crucial to peroxisome biogenesis, its mechanisms remain unknown, due to lack of evidence of detectible transmembrane channels in these organelles. The Michnick group has evidence that two of the proteins involved in peroxisome protein translocation (Pex5 and Pex13) have both transmembrane domains and sequences that favor LLPS. My hypothesis is that these proteins form liquid droplets inside the peroxisome membrane (i.e. between the lipid bilayer leaflets), which would act as a conduit for transmembrane protein transport. After being recognized by a C-terminal peroxisome-targeting sequence, the cargo proteins could then dissolve in the droplet and emerge on the other side of the membrane. My studies will employ the budding yeast S. cerevisiae and will mainly use genetic manipulation with super-resolution and electron micrographic methods to characterize liquid droplets. Further spectroscopic and biophysical methods (e.g. fluorescence recovery after photobleaching, FRAP) will be used to assess protein dynamics inside the droplets and transmembrane protein transport.

Enzymes catalyze molecular transformations in living systems while being pushed and squeezed by other biomacromolecules. This molecular crowding generates excluded volume effects that result in large quantitative consequences on the rates and the equilibria of enzymatic activity by molecular mechanisms that are not yet fully elucidated. To recreate these features, we propose packing tens to hundreds of enzymes within bacteriophage capsids to create nanoreactors (NRs). Our nanoreactors allow control over packing density, protein environment, and boundaries at the nanoscale. Regulation of these conditions is key for understanding in vivo enzyme behaviour, and facilitating metabolic engineering efforts. We will focus on the mevalonate (MVA) isoprenoid pathway, which, despite demanding enzymatic cascade reactions, is widely used for production of industrially useful biochemicals. Limitations may be related to the lack of proximity between partner enzymes, unfavourable interactions under molecular crowding conditions, and/or unfavourable molecular ratios between cascade enzymes. Here we pursue an integrated study to produce materials where MVA enzyme packing and stoichiometry are controlled to mimic the complexity of the intracellular environment. The kinetics of enzymes within NRs will be measured using both ensemble and single-molecule techniques. The enzymatic activity of single nanoreactors will be monitored using a combination of atomic force and fluorescence microscopies, which will allow the in situ study and manipulation of single NRs in real time to provide individualized details not accessible with averaging ensemble approaches. These studies will be supported by multiscale modelling of the crowded enzyme environment. Our experiments will reveal the optimum biophysical conditions for maximizing metabolic flux in the MVA pathway. Further, designed NRs will be assembled and assessed within living cells. Our project has both fundamental and applied aims. First, to understand how crowding affects enzymes at the nanoscale, including metabolite diffusion and protein conformational changes. Second, to improve the biosynthesis of isoprenoids in biological and industrial systems.

Epithelial collective cell migration (CCM) is important in biological processes such as organ development, tissue maintenance and tissue repair. CCM usually occurs on curved surfaces such as that found in blood vessel walls and intestinal villi. However, current CCM research are still conducted on flat surfaces. This is due to lack of techniques to fabricate tubular and spherical microstructures resembling that of organs as well as difficulty in observing and measuring the collective dynamic behaviour of cells on these surfaces. Nevertheless, recent studies are beginning to show that cells do behave differently on curved surfaces. However, these studies were mainly focused on single cells, as such, there is limited insight into CCM which involves complex interactions among multiple cells.
Here, we claim that curved surfaces can significantly influence CCM. As such, we propose to systematically study CCM on such surfaces to better understand their underlying mechanisms. Our project will combine distinct but complementary scientific expertises coming from biology, biophysics and engineering. We aim to: 1) Develop novel techniques in fabricating different, well-defined curved geometries such as tubular and spherical surfaces with nano-patterns; 2) Identify biomolecules and proteins involved in CCM on curved surfaces; 3) Develop computational models to perform 3D imaging and analysis so as to better monitor and measure complex tissue dynamics; and 4) Develop a universal theory to better explain and unify experimental observations.
Together, the unique combination of these different approaches will enable us to better understand the fundamental mechanisms and impact of surface curvature on cell behaviour and tissue organization. These will shed light on related biological functions such as in organ development and tissue repair, as well as contributing towards better tissue engineering or regenerative medicine applications.

In mammalian development, a zygote gives rise to three germ layers and ultimately hundreds of cell types. How a single genome drives the cell fate decisions underlying development remains one of the most intriguing questions in biology. Extensive work over recent decades has identified some 'master regulator' transcription factors (TFs) that specify certain lineages upon expression, e.g. MYOD for muscles. However, for many lineages the TFs and regulatory regions governing cell type specification remain in the dark. In addition, the sequence of events that leads to open and TF-bound chromatin at developmental enhancers is unknown. These cell fate decisions inherently occur in heterogeneous cell populations, making them difficult to study with bulk techniques. The ability to simultaneously measure changes in chromatin accessibility and gene expression in each of many single cells, coupled to cell lineage information, would provide unprecedented insights into mammalian development. Here I propose to develop and apply such single-cell ‘co-assays’ using mouse embryoid bodies (EBs) as a model system. This will allow me to identify the TFs and regulatory regions involved in early mammalian lineage specification. I will then genetically perturb candidate genes and characterize the effects on lineage establishment. In addition I propose a systematic screen to identify lineage-specifying TFs that serve as ‘pioneer factors’, capable of accessing binding sites in previously closed chromatin. The approach developed in this easily accessible and perturbable system will provide unique insights into intricate biological processes in the future, from in vivo mouse development to disease.

The primary sequence of mRNA transcripts contains essential regulatory information in the form of internal chemical adducts, coined the epitranscriptome. Groundbreaking studies of N6-methyladenosine (m6A), by us and others, revealed that this abundant mRNA modification participates in many aspects of the mRNA life cycle to affect cellular, developmental and disease processes. It does so primarily through recruitment of specific binding proteins that channel modified transcripts to various processing pathways and fates. I recently identified a new mRNA modification, N1-methyladenosine (m1A), which occurs on thousands of human and mouse transcripts. It is strongly enriched at the 5’UTR and positively correlates with translation. These distinct features, together with its evolutionary conservation and dynamic nature, suggest a fundamental role in gene expression. The objective of this proposal is to establish the function of m1A in mRNA metabolism, focusing on 5’UTR and translation, and delineate the mechanisms through which it is executed. Aim 1 will systematically identify m1A-binding proteins that will be characterized to expose pathways controlling methylated transcripts. Aim 2 will functionally interrogate the effect of individual 5’UTR m1A sites on translational output in vitro and in vivo (now made possible by method advancement in my lab allowing robust mapping of m1A with single-base precision). Aim 3 will combine results of Aim 1 and 2 to mechanistically dissect the combination of factors and sequence features required for translation initiation. This study is expected to expose a new and central player in translation regulation affecting thousands of genes.

As intracellular, obligate parasites viruses rely on a diversity of strategies to survive. Some, like most RNA viruses, cause acute “hit-and-run” infections and require large susceptible host populations. Others, mostly DNA viruses, persistently infect their hosts. Morbilliviruses, like measles virus (MV) and canine distemper virus are examples of RNA viruses that can cause persistent infections. The exceptional circumstances which converge to drive RNA virus persistence remain unclear, since these viruses need to replicate continually in vivo. Bats are evolutionary and ecologically unique mammals standing out in their ability to tolerate viral infections. We recently showed that bats host major mammalian paramyxoviruses and described an ancient morbillivirus in vampire bats. This discovery provides a unique opportunity to explore RNA virus persistence in an important reservoir host that has high rates of contact with humans and domestic animals through its blood feeding habits. The primary objective of the proposed research is to unravel fundamental mechanisms that govern morbillivirus persistence and understand the consequences for immunity and infection. We hypothesize that within-host persistence in canonical morbilliviruses is a vestigial relic of a more common strategy that evolved in bats. Research activities comprise a multidisciplinary program involving investigations of natural and experimental infection of bats, reverse genetics to resurrect viruses from infectious clones, comparative studies of canonical morbilliviruses and hosts together with investigation of pathobiology and immunity underpinned by mathematical modeling. Existing materials, a unique field network for long-term monitoring vampire bats, novel approaches and critical insights from systematic field and laboratory studies make this project both exciting and feasible. This study represents an unusual integration of approaches and ideas from disease ecology, evolutionary biology and synthetic biology. We expect this fusion to resolve fundamental knowledge gaps in our understanding of how RNA viruses persist in hosts; a critical component for the understanding of rare disease manifestations, the consequences of viral persistence on the host immune system and for identifying patterns in risk of virus transmission between species.

Cells achieve reproducible outputs while relying on intrinsically stochastic molecular processes. In plants, cell division orientation is accurately predicted before mitosis by a microtubular ring, the preprophase band (PPB), through an unknown mechanism. Using high-throughput microscopy, quantitative image analysis, biomechanics and stochastic modeling, we will investigate how the stochasticity of microtubule (MT) self-organization is used, or filtered out, during PPB formation to sense temporal, geometric and mechanical cues in order to generate a robust placement of cell division planes. In short, we will test whether the PPB acts as a macromolecular mechanosensor. Using statistical mechanics such as Monte Carlo, event-based modeling and mean-field theory, we will assess how stochasticity leads to distinct dynamical states for MT arrays. We will develop biophysical models of dynamic MTs in 3D cells to explore how stochastic MTs self-organize into PPBs and how spatiotemporal cues modulate that process. Using the Arabidopsis shoot apical meristem, we will identify correlations between MT array dynamics, PPB behavior, cell shape, growth and mechanics, cell cycle progression, and cell division plane from statistically representative sample involving hundreds of dividing cells. To challenge the robustness of PPB and cell division in vivo and in silico, we will globally and locally increase variability in these cell parameters with mutants (MT dynamics, wall mechanics, cell cycle, mechanotransduction), inducible lines, mosaics, and micromechanical perturbations. Last, we will unravel the molecular mechanism processing molecular stochasticity to channel cell divisions: we will investigate how the TTP (TON1-TRM-PP2A) complex, a key regulator of PPB formation in connection with the cell cycle, contributes to generate reproducible divisions by monitoring MT self-organization, integrating geometric, mechanical and temporal cues. Implications of this project go beyond cell division robustness: while many cellular pathways are adapted to respond to rapid and discontinuous changes, we expect here to unravel mechanisms managing slow and continuous signals, like shape, growth or tissue-stress. We will also gain insight into the mathematical properties of stochastic extended objects like microtubules, and we will propose a mechanism for cells to perceive directional cues.

Protecting genome integrity from environmental stresses is essential for the stable propagation of genetic information from stem cells to their daughters. The most important significance of this work is to add to our basic knowledge of how some cell types, especially neural stem cells, are able to cope with ionising radiation damage better than other cells. The two main aims of this project are to identify the cell-autonomous mechanism of radiation resistance in neuroblasts and to determine the non-cell autonomous role of the stem cell niche in neuroblast resistance. To pursue both aims, I will use a combination of confocal microscopy with molecular markers, cell-type specific genetic manipulations, genetic screens and in vitro stem cell cultures. Using the power of fruit fly genetics to get at some of the underlying mechanisms for neural stem cell radiation resistance may also help to provide us with tools for manipulating the resistance process in many different cell types. The findings of this project will have long-term implications for improving our understanding of how stem cells react to challenging environments and the inputs they receive from their niche.

Ribonucleoprotein (RNP) granules are "membraneless organelles" found in eukaryotic cells. Common to RNP granules is enrichment of RNA-binding proteins harboring intrinsically disordered domains of low sequence complexity (LC) that may self interact, stabilizing granules via liquid-liquid phase separation (LLPS). Importantly, several LC domains of stress granule (SG) proteins are aggregation-prone and associated with inclusions observed in many neurodegenerative diseases. Although the constituent proteins and RNA are being enumerated by mass spectroscopy and sequencing approaches, and the ~100 nm-scale features are being resolved by fluorescence microscopy techniques with improving resolution, a fundamental conformational/physical-chemical understanding of structures and protein-protein interactions stabilizing SGs remains to be directly interrogated. Our goal is to observe with, residue-by-residue detail, the protein-protein interactions and structural changes caused by disease-causing missense mutations in human SGs both in vitro and in cells. Using the well-studied protein FUS to benchmark our spectroscopic tools and the SG marker and nucleator TIA-1 as a focal point, we will provide the first analysis of protein secondary structures and stabilizing interactions in granules. We will apply in-cell vibrational and Förster resonance energy transfer (FRET) imaging combined with NMR spectroscopy to determine the molecular details of LC domain structure in LLPS assemblies in vitro and SGs in cells. By examining disease-associated variants known to form intracellular aggregates or impair SG dynamics, we will probe the underlying physico-chemical protein changes underlying disease-associated SG biophysical changes. Our novel molecular toolbox and experimental protocols to probe protein structure in cellular (and in vitro) SGs will be immediately applicable to other RNP granules and phase separated structures and their disease-associated changes.

Muscles are producing the active forces that enable all our voluntary body movements. The cellular components of muscle are called muscle fibers and are very large cells that can be several centimeters in length in humans. Inside all muscle cells are millions of tiny molecular machines, called sarcomeres that produce the active forces of muscles. These sarcomeres are arrayed in highly regular long chains called myofibrils that span from one muscle end to the other. This arrangement ensures that the force produced by the myofibrils is transmitted to the connected tendons and bones at the muscles ends. The highly regular periodic organization of the myofibrils results in the cross-striated appearance of skeletal muscles under the microscope.
We assembled an international team of researchers from France, USA and Germany to study how myofibrils are built during muscle development. For this we combine two different experimental model systems, the fruit fly Drosophila muscles and human muscle cells generated in vitro from stem cells, together with mathematical modeling of myofibril assembly. Our starting hypothesis is that mechanical forces, which are generated early during muscle development, are an important factor for the polymerization of myofibrils. We will test this hypothesis in fly as well as in human muscles produced in vitro by following the localization of sarcomeric protein components with high-resolution microscopy techniques. We will measure when a sarcomeric protein pattern can be first detected and how this pattern is refined. These data will be used to generate a computer model that can produce periodic sarcomere-like structures that are linked together from homogenous components. We will further measure the strength of mechanical forces present during myofibril formation in fly muscles in vivo and in human muscles in culture. Finally, we aim to modify these forces and to observe the effect of these manipulations on the developing muscles and myofibrils. These data will be used to produce a refined computer model of myofibrillogenesis. Together, our research should lead to a better understanding of how the contractile apparatus of human muscle is built, which could eventually be helpful to treat muscle injuries or aged dependent myopathies.

Organisms must innovate to survive. While adaptation often occurs via mutations in existing proteins or through protein domain shuffling, evolution sometimes must invent functional proteins de novo. Such proteins can arise when organisms acquire the ability to express a short open reading frame encoding a peptide of benefit. Although nearly a third of the genes in many genomes are predicted to have emerged de novo, the mechanisms and constraints governing gene birth remain mostly elusive. During my post-doctoral studies, I will use the molecular, biochemical, and next-generation sequencing-based approaches that are fully accessible in the Laub lab to study how genes emerge during evolution and become integrated into cellular processes. I will develop an approach that explores the link between environmental challenges, existing cellular systems, and de novo gene birth – a largely uncharted area. Specifically, I will (i) screen for beneficial and deleterious randomized protein sequences under various conditions, (ii) characterize those sequences to reveal the molecular mechanisms behind their cellular effects, and (iii) generate models that identify and predict the potential functions of natural de novo genes. This project will provide insight into how cellular innovation arises and how the existing complexities of the cell shape such innovation.

Neuronal activity consists of electrical transients on the millisecond timescale. Recently developed genetically encoded voltage indicators (GEVIs) have potential to record optically those transients in thousands of neurons simultaneously. Despite great efforts and improvements on the GEVIs, many technical challenges must be overcome for GEVIs to being used in large-scale recordings in live animals. Here, we propose to develop and implement new imaging modalities to enable recordings of voltage dynamics from neuronal networks in layer 2/3 of the mouse cerebral cortex in vivo. As a voltage indicator, we will use a recently developed Archaerhodopsin mutant, called 'NovArch', offering optical sectioning by nonlinear activation. We will use protein engineering to further improve trafficking of NovArch to minimize background fluorescence, and we will co-express it with an actuator to allow for simultaneous optical stimulation. We also plan to develop a microscope specifically optimized for voltage imaging in vivo. It will contain adaptive optical elements to direct optical excitation to the two-dimensional cell membranes where the GEVIs reside, thereby minimizing illumination of non-signal-bearing regions of the sample. This approach will provide high signal levels, while minimizing light scattering and photodamage. We will use this novel microscope to map neural activity in cortical sensory circuits under conditions of sensory stimulation in vivo. The recordings will probe the precise activity levels, sub-threshold voltage dynamics, and intercellular correlations in activity of genetically defined neurons. These data will aid in constraining models of cortical function.

Microtubules form the basic structure, and transport systems in cells, responsible for fundamental processes including cell division, and hence are important drug targets for diseases including cancer, with common taxane-based drugs having them as their biological target of action. Broadly, one of the mysteries of cell biology is the basic set of properties involved in the seed and growth of microtubules and the processes underlying how these systems are initiated. New avenues for controlling cell development and division, possibly related to anticancer treatments will come with a fundamental understanding of the basic mechanisms that lead to unusual switching behavior – dynamic instability. After decades of studies, both in cells and in reconstituted systems there are many open questions about this fascinating behavior. The major bottleneck in exploring microtubules is that the process of seeding is short-lived and the molecular species are structurally very small making standard microscopy observations very difficult, especially for capturing dynamics. In situ liquid cell transmission electron microscopy (LCTEM) has the potential to solve this crucial problem. To enable these kinds of experiments, the microtubule growth, and concentration need to be optimized for confinement within the liquid-cell. Imaging conditions need to be optimized to maximize contrast (as biological systems produce very low contrast under electron beam). We contend that LCTEM experiments replicating naturally occurring nucleation, growth, shrinkage, and re-growth process of microtubules and quantitative image analysis would offer us unique insights into their formation and reorganization.