Embryonic stem (ES) cells are immortal, yet karyotypically normal cell lines derived from the mammalian blastocyst that can be differentiated into all the lineages of the future embryo. In this proposal, we will address the mechanisms governing cell fate choice in ES cells using a combination of emerging technologies for single cell analysis and mathematical modeling. While ES cells appear morphologically uniform, the advent of sensitive fluorescent reporter lines show that ES cell cultures exhibit dynamic and heterogeneous gene expression that reflects the cell types of the blastocyst from which they are derived. Specifically, undifferentiated ES cell cultures appear to contain at least two populations of cells that are both capable of self-renewal, but poised to differentiate into distinct fates:. One population is primed to become the embryonic lineages or epiblast while the other is primed to become the extra-embryonic primitive endoderm. In the embryo, similar dynamic states exist, but only transiently. As ES cells perpetuate these dynamic states indefinitely, they provide unique experimental access the process of lineage specification. By fully exploiting this model, we can elucidate the molecular mechanism that controls the progress of a cell between primed states and yet prevents them from entering further into differentiation. In both ES cells and embryos, the activation of Erk signaling downstream of Fgf modulates the transition between epiblast and endoderm and can also drive ES cells into differentiation. Is this process of priming and commitment deterministic or stochastic in nature? How does Fgf signaling impact on the fate of individual cells? To answer these questions we take a quantitative approach with single cell resolution. We have assembled a multi-disciplinary team to determine how Fgf signaling acts on these transitions in individual ES cells, how Fgf signaling interacts with the pathways that normally prevent ES cells from differentiating, and explore how key ES cell specific transcription factors affect these Fgf dependent transitions. To achieve those aims, we will exploit new fluorescent reporters that can detect low-level lineage specific gene expression as a tool to identify Fgf-driven transitioning cells. We will develop a novel microfluidics platform to measure variations in fluorescent readouts from these reporters in single cells, under defined Fgf dosage, and in response to perturbations in the Fgf pathway. Microfluidic devices will enable culturing, laser transfection, and time-lapse imaging of single cells in individually addressable growth chambers, allowing for the delivery of different agents combinatorially. The measured dynamic distribution of single cell responses will be correlated with a whole genome expression data. Mathematical modeling will be used to develop a predictive model for the relationship between Erk activation, reversible priming towards endoderm, and endodermal differentiation.

Mechanical stimulation derived from physical activity is critical to the development and regulation of the muscle tissue, whose architecture, enzymatic apparatus and innervation is largely dictated by mechanical demand. Despite the importance of this mechano feed-back process to human and animal (patho)physiology, little is currently known about the molecular mechanisms that mediate it in the cell. Members of the titin-like family of giant proteins (0.7-4 MDa) are now emerging as key mechanotransducers in the sarcomere. These proteins form elastic filaments that are embedded within the sarcoskeletal lattice of myosin-actin motors. They contain conserved kinase domains flanked by mechano-sensitive, regulatory motifs that undergo conformational deformation during myofibril stretch and, thereby, regulate kinase activity. It is believed that mechanical stress leads to kinase activation but, to date, it is unknown how and when these elastic kinases act in the developmental, reformative or atrophic stages of muscle and how they relate to other signalling pathways in muscle. Here, we will address the mechanisms of mechanotransduction in a kinase representative of this family, twitchin kinase from C. elegans, through its atomic and catalytic profiling in vitro under strain-mimicing conditions. We will then use the powerful genetics of C. elegans to engineer transgenic worms carrying in their muscles synthetic cytoskeletal filaments with genetically-encoded fluorescence reporters that will quantitatively report on kinase activation. We will use advanced imaging and data analysis techniques to correlate kinase activation state with the physiological stages of muscle (development/aging), myofibril structure and animal locomotory behaviour. The Overall Objective of this research is to establish the operational, mechanistic principles of this kinase family and use these to assess the physiological significance of their mechanosensing in vivo for muscle development and regulation.

The main aim of this proposal is to understand the cellular and circuit mechanisms that establish spatial coding cellular ensembles in the mammalian hippocampus. The cognitive spatial map theory of the hippocampus posits that internal representations of space are implemented by a sparse subset of 'place cells' that display location-specific firing during spatial navigation, while other neurons remain silent. Moreover, this spatial code is highly dynamic, such that place cells alter their firing properties when the spatial environment changes. The cellular and circuit mechanisms that establish sparsely distributed and dynamic spatial coding schemes in the hippocampus are poorly understood. Longstanding theories posit that the hippocampal inhibitory circuitry plays a central role in the formation and segregation of spatially informative cellular ensembles. If so, the anatomical diversity of local GABAergic interneurons may further promote dynamic organization of place cell assemblies in the population by regulating active dendritic input processing at the subcellular level, which can define the output behavior of principal cells to synaptic excitation in a given environment. Understanding multimodal dynamics in the hippocampus will, therefore, have important consequences for our understanding of how cortical circuits are organized to process and store information. To directly test these hypotheses we will perform multi-level analyses requiring a multidisciplinary approach that brings together experts in neurophysiology, nonlinear optics, molecular genetics and synthetic chemistry.
Our research plan is composed of five tightly integrated projects. 1) Functional population imaging in hippocampal CA1 of behaving mice to determine the fine-scale spatial organization of hippocampal spatial coding ensembles and their dynamic reorganization during controlled changes in the spatial environment and spatial learning. 2) Assessment of multimodal organization and dynamics in synaptic microcircuits of genetically-identified interneurons. 3) Implementation of novel cellular-resolution optical, photochemical and pharmacogenetic techniques for manipulating activity of identified inhibitory circuits in vivo. 4) Dissecting multimodal population and microcircuit dynamics of spatial coding CA1 hippocampal neuronal ensembles using cellular-resolution manipulations in vivo. 5) Measurements and manipulation of subcellular integration of excitatory and inhibitory synaptic inputs in functionally-identified hippocampal CA1 pyramidal cells during spatial navigation and learning.
This project will yield a detailed understanding of the cellular and circuit mechanisms that establish spatial coding ensembles in the mammalian hippocampus. The complexity of this problem necessitates a multidisciplinary and integrated approach.

Dynamic interactions between RNA and proteins are fundamental to gene regulation. To function properly, RNA molecules and associated binding proteins form RNA/protein (RNP) complexes that further assemble into micron-sized RNP bodies, which are involved in many developmental processes. Despite their biological importance, both the precise function of RNP bodies and the biophysical principles governing their mesoscale dynamics, remain enigmatic. An emerging concept is that RNP bodies may represent ATP-dependent liquid-like assemblies of RNA and protein, and that they could thus function as intracellular micro-reactors for efficient RNA regulation. One potential source of an ATP-dependent liquidity is the activity of RNA helicases, a physiologically important class of ATP-hydrolyzing enzymes that are ubiquitous components of RNP bodies. We propose to test the hypothesis that RNA helicases play a central role in the underlying molecular dynamics and structural fluidity of RNP bodies. We will take a multi-scale approach to (1) elucidate the molecular composition of developmentally regulated RNA helicase complexes, (2) determine the molecular mechanisms of RNA helicases in these complexes, and (3) decipher how these dynamic complexes contribute to the assembly and liquid-like biophysical properties of RNP bodies. Our vision is to develop a fundamental understanding of the role of ATPase activity in RNP body assembly, and the physiological consequences for developmental gene expression programs in metazoans.

Slime molds and fungi are ubiquitous components of terrestrial biomes and often grow as dynamic networks. Individuals can reach across multiple hectares of habitat, and for example the “humongous fungus”, Armillaria bulbosa, stretches through 15 hectares of a Michigan forest soil. These organisms function as pathogens, mutualists, and decomposers, and play key roles in biogeochemical cycles and agriculture. Traditionally considered as close relatives of plants, the fungi are now understood as more closely related to animals. Reasonable estimates place the diversity of true fungi at 5 million species; slime molds may range to 2,500 species.
Filamentous slime molds and fungi forage through various substrates for scarce and heterogeneously distributed resources; organisms must dismantle and move resources across vast distances, and then coordinate their use across the individual. How are local patches of food parsed, moved, and integrated to enable an organism to grow as a coherent whole? We hypothesize integration is a function of the internal flows of networks. Communication and growth are likely to be facilitated by the fluids which carry both metabolites and organelles across a network. But different anatomical and functional constraints may facilitate or constrain these flows to a greater or lesser degree. For example, there are no internal partitions within the networks formed by slime molds, but many fungi grow as strings of cells separated by walls, and these walls may limit the movements of cellular structures. While slime molds may actively move large organelles to coordinate the processing of a newly discovered food source, fungi may rely on the passive transport of smaller metabolites. Perhaps communication across fungal networks is less effective than communication across slime mold networks. We aim to understand what organisms do to integrate organismal growth across these different kinds of networks by working with many different species from each of three groups: the acellular slime molds, ascomycete fungi and basidiomycete fungi. Targeting multiple species will enable identification of general properties, and also unique solutions taken by subsets of species. Our approach to organism self-organization involves an international team of a mycologist, a network imaging specialist, and an applied mathematician. The interplay of these disciplines is required to: (i) identify how fluids travel through different kinds of networks, (ii) discover how organisms communicate, and network architectures change, in response to new food sources, and (iii) unravel the different paths by which transport mechanisms and network architectures interact to enable the growth of an individual.

It is becoming increasingly clear that the genomes are pervasively transcribed. Presently, the function(s) of these non-coding RNAs are unknown. We will pursue the hypothesis, based on our preliminary findings, that these transcripts contribute to genome stability. By a next generation sequencing approach we will analyses these transcripts and we will study them in relation to site-specific DNA damage and the activation of local DNA damage response activation.

Resurrecting ancestral proteins can provide fascinating insight into the evolutionary history of molecules, a window on the past revealing how present day adaptive specializations may have occurred. Visual pigments form the first critical step in the phototransduction cascade within the photoreceptor cells of the eye. Some of these pigments, the rod opsins, are known to possess extraordinary adaptations for maximizing photosensitivity under low light conditions, including ultrafast femtosecond photoactivation speeds coupled with remarkable thermal stability. How did such extreme specialization evolve? Ancestral reconstruction approaches have been successful in resurrecting and functionally characterizing a 200 million year old ancestral archosaur rod visual pigment. However, due to the effort and expense associated with laboratory resurrection, this approach is necessarily limited to small numbers of inferred sequences, making the detailed description of important evolutionary transitions and the testing of different evolutionary hypotheses extremely difficult. In this proposal we argue that these difficulties can be overcome by exploiting recent advancements in computational photochemistry that, in principle, allow for the systematic reconstruction of ancient visual pigments in silico. Indeed, it has been recently reported that computer models of visual pigments based on ab initio multiconfigurational quantum chemistry, not only reproduce the changes in ?max values induced by different mutations, but also simulate the effect of the sequence variation on pigment photochemical and thermal activation. Such technology can thus be used to compute the optical and photochemical properties of inferred ancestral sequences, for comparison to modern visual pigments. Here, we propose a research project that integrates, for the first time, the diverse disciplines of ab initio quantum chemistry and ancestral protein resurrection to achieve an unprecedented understanding of the functional divergence of dim-light visual pigments. Accordingly, we will develop and evaluate a computational protocol for the systematic construction of computer models of ancestral pigments. With this technology at hand, large sets of pigments can be screened in silico for interesting functional shifts. These computational investigations will be combined with laboratory investigations of resurrected ancestral pigments focusing on a small number of key targets identified by the quantum chemistry modelling. Our highly innovative combined approach should lead to a better understanding of the evolution of rod visual pigments, and how they achieved their remarkable adaptations for dim light vision.

The ability of animals and humans to learn new tasks is astonishing. How does the brain learn to choose actions that will maximize rewards in a new scenario? Much is known about how we learn to evaluate different stimuli in the environment in terms of how much future reward they predict – this process is thought to depend on learning in the striatum, and on prediction error signals conveyed to the striatum by the neuromodulator dopamine. However, in realistic learning situations the problem is more complex: although our environment consists of a myriad of stimuli, only few are relevant to any specific task. The striatum would be extremely inefficient if it were to learn about all the available stimuli. Indeed, the speed by which we learn new tasks suggests that there are neural processes that identify the task-relevant stimuli and direct learning towards these alone. Here we propose that this function is fulfilled by an understudied neuromodulatory system: the intrinsic striatal cholinergic system. This unique and mysterious system has been implicated in a variety of psychopathologies, including ADHD, schizophrenia and Parkinson’s disease, however, it has been the focus of relatively little scientific research, and as a result the precise function of striatal cholinergic neurons is far from clear. To remedy this, we propose an international multi-disciplinary collaboration that will use a variety of neuroscientific methods to test an overarching hypothesis: that striatal cholinergic neurons provide a “filter”, directing learning towards task-relevant stimuli and away from distractors. We will develop a task that is especially tailored to test this hypothesis, and furthermore, can be used with both humans and animals. This will allow us to use complementary research methods including single cell recordings, optogenetic manipulations, and brain imaging, to provide converging evidence regarding the role of the striatal cholinergic system in learning, and its interaction with dopaminergic processes. Tying all these together will be a computational model of how animals and humans are able to learn in our task, and how different attentional spotlights affect their performance. The proposed project will shed light on a functionally and clinically important neuromodulatory system, with far reaching implications in terms of understanding the neural basis of learning in real-world complex scenarios.

The cells found circulating in blood, including platelets, red cells, and the white blood cells of the immune system are produced continuously throughout our lives. Despite their diverse range of functions, all of these develop from a single progenitor cell type found in the bone marrow. How apparently similar progenitor cells give rise to, and regulate, the tremendous cellular diversity that is required for the blood system to function, is poorly understood. A better understanding of how these blood cells are generated is critical to the development of new therapies for replacement and restoration.
Schumacher’s laboratory has developed the molecular equivalent of ‘bar-coding’, a mechanism to label individual progenitor cells uniquely with a tag that is inherited by all their offspring. This technique enables a much more detailed study of the contribution of individual progenitors to the entire blood system than earlier methods. Complementing this high-level view, members of Schumacher’s team have been developing a methodology for time-lapse imaging of individual progenitors, capturing the patterns of development for family trees of cells and their progeny.
Traditional approaches to extracting family trees from movies have a human study images on a frame-by-frame basis; a costly and time-consuming process. Automated, computer-based extraction is challenging as cells move, change shape and pass under one another. Our approach is to develop a hybrid strategy. Cohen and his computer-engineering laboratory will develop algorithms based on machine learning that automate processing where possible and request human intervention in cases of uncertainty. These algorithms will be packaged into a user-friendly program distributed freely to benefit all scientists.
The data that results from these experimental methods is highly complex. The Hodgkin laboratory, which contains both experimental and theoretical scientists, has a long history of developing mathematical models of biological systems, providing concise, analytic descriptions and using statistical techniques to identify hidden order; their role in this project to interrogate both sources of data and abstract key features. These models will be fed back to Cohen to aid in automated data extraction and forward to Duffy for further investigation.
Duffy’s laboratory consists of experts in mathematical analysis of models. They will collaborate in the statistical analysis of data and perform a stochastic analysis of the best model of the blood system to enable extrapolation and prediction from the model. In collaboration with the Hodgkin laboratory, the most significant findings of this analysis will be fed back to Schumacher’s laboratory to inform further experiments that challenge and refine our understanding.
Ultimately, this grant’s aim is to utilize these new experimental technologies in concert with advanced computer science and mathematics to gain a deeper understanding of the blood system.

The collective behavior seen in assemblies of cells as well as groups of animals is the cornerstone of biological organization and distributed information processing. We propose to bring together two distinct approaches - dynamical self-organization and information-theoretic analyses - to probe how collective behavior emerges in fish groups.
We will base our research on new high-resolution recordings of fish group motion where hundreds of individuals can be precisely tracked for hours. This unprecedented amount of fish trajectory data collected by the Couzin lab, as well as plans to measure new behaviorally relevant quantities (the visual field of the fish, responses to various perturbations like laser pulses, trained individuals, robot-controlled models and virtual interacting fish), will enable us to apply new modeling approaches. Rather than assume an ad-hoc model and tune it to qualitatively reproduce group behaviors, we will use data-driven dimensionality reduction and probabilistic models from neuroscience (from Tkacik and Schneidman labs) to reconstruct the computations that the fish perform to determine their future movement, and to infer how information flows between the group members.
Specifically, we propose:
(i) Using “maximally informative dimensions”, we will ask what combination of the neighbors’ states is most informative about the individual’s future motion. This data-driven approach can infer how the fish integrate the information about neighbors, and how much of this information (in bits per unit time) they collect.
(ii) Using information theoretic measures we will quantify which kind of information (speed, direction, local order), how much of it, and how quickly, propagates beyond the range of the receptive field.
(iii) From these measured quantities we will build bottom-up models of collective behavior, and ask how much information minimally needs to be exchanged to support coherent motion; this can be compared with the measurements in (i,ii) and experimentally tested by decreasing the amount of available information by e.g. lowering the light level.
(iv) We will build top-down models for the whole group directly from data using maximum-entropy and generalized-linear-model approaches. We will look for the least complex interactions between individuals that explain the data and for signatures of hierarchical organization.
(v) We will ask if certain group configurations and geometries are better suited to support the rapid spread of information and generate quick collective responses. This can be tested using perturbation experiments and interpreted in an ecological context.
This research plan pursues the idea that organisms need to actively gather noisy information from their neighbors and the environment to function in a synergistic way across scales. Information theory can be used to quantify the information flows in large new data sets, and to reproduce them consistently in top-down and bottom-up models of collective dynamics.

How animals climb smooth surfaces using adhesive mechanisms is a fundamental biological question. Fibrillar and smooth adhesive structures are observed across a range of animals from insects to lizards, all of which rely upon controllable adhesion to climb, mate, or capture prey. The presence of adhesive hairs in many climbing and clinging organisms in Nature has led biologists to focus on the fibrillar design as the key principle for adhesion-based locomotion. Recent studies by the co-applicants and others suggest that sub-surface and internal structures, particularly with regards to compliance, represent critical ingredients for adhesion. These structures may be essential for the up-scaling of adhesive forces in large animals (e.g., geckos), allowing them to achieve adhesive capacities similar to animals much smaller in mass (e.g., beetles). We hypothesize that the ability for an organism to use adhesion-based climbing depends upon the ratio of an organism’s attachment area to the compliance of the whole system. Specifically, we predict that larger organisms should evolve increasingly stiff sub-surface structures to allow them to use adhesion to climb. We argue that evolutionary changes in the compliance of subsurface structures represent one of the reasons for why animals of different sizes can adhere to surfaces. We test this hypothesis (Fig. 1) through laboratory and field experiments with two groups that have evolved adhesive pads (insects and geckos). We will perform (A) Laboratory studies of subsurface morphology and material properties, (B) Laboratory studies examining effects of compliance on locomotion and adhesion, (C) Field studies examining compliance of surfaces in nature, and (D) Modeling of Subsurface Mechanics and Adhesion Capacity. To accomplish these experiments, our proposal unites three researchers (Irschick, Federle, and Crosby) who bring different expertise to the broader study of adhesion. Irschick is a functional morphologist who has studied how animals perform (jump, run, etc.) in the laboratory and in nature. Federle’s research combines an ecological/evolutionary perspective with a mechanistic and biophysical approach, and Crosby is an expert in materials design and fabrication, especially in the context of soft polymer adhesion and mechanics. Each will conduct different experiments, and will also work together to achieve these different goals. We aim to uncover fundamental scaling laws from insects to lizards by integrating field and laboratory work, and thus our project will provide a critical step in establishing how nature has accomplished adhesion-based locomotion for organisms that range in mass over several orders of magnitude.

The goal of organismal neuroscience is to understand how the circuits of neurons that make up the central nervous system interpret sensory information about the outside world and use that to generate behavior. Implicit in the execution of any behavior is a choice made by the organism, with the nervous system evaluating the costs of that behavior (e.g. effort of movement towards a goal) versus the perceived pay off of the behavior (e.g. reaching a satisfying meal). Behavior is shaped by neural circuits, which are in turn shaped by genetics and by life stage (i.e. different individuals have different genes and experiences, and therefore different neural circuits which consequently will make different choices, but so too will the same animal when it is young vs. old, virgin vs. pregnant, etc.). Progress in neuroscience is hindered by the difficulty of quantitatively measuring the different values that go into choices made by animals in complex, natural settings. Human observers often miss subtle behavioral variance, food or mate choices may involve too many or unknown parameters. Issues of scale arise from time a skilled observed must put into analysis, and the complexity of nervous systems (e.g. 200 billion neurons in a human brain). Open questions include what neural circuits are involved in valuation, and what and how genes shape these circuits. The fruit fly Drosophila melanogaster is a model organism that presents a balance between neurological and behavioral complexity, and approachable simplicity. Drosophila have ~100,000 neurons. They navigate the world using visual, tactile, and chemical cues and make cost-benefit analysis involving the use of limited energy stores to find the best feeding sites, where they eat, mate, and lay eggs. While this provides a rich animal-environment interactions, the flies’ neural circuits and genetics are relatively simple compared to mammals. Recent advances in genetics allow targeting specific neuronal populations in the fly. Advances in machine vision and computation allow high throughput analysis of behaving Drosophila, and advances in mathematics allow sophisticated models to be extracted from large and complex behavioral data sets. We have designed behavioral arenas to enable automated tracking and analysis of fruit flies making choices between food sources of different qualities while avoiding naturalistic obstacles. We aim to combine these experiments with genetic manipulations of specific neuronal circuits to assess the role these circuits play in behavioral decision making. This set up will allow an unprecedented rate of discovery in the neurogenetic underpinnings of behavioral choice in awake, behaving animals presented with quantifiable naturalistic cost and benefit considerations. Finally, we will use this vast cache of behavioral data to create models of neural-circuit driven decision making in Drosophila melanogaster.

To understand and interfere with the stages of the virus life cycle, knowledge of the structural properties of viruses and their assembly intermediates is required. A case in point is the human immunodeficiency virus type 1 (HIV-1), which, despite intense study, still presents challenges coming from a limited knowledge of its architecture and the transformations associated with its passage from the noninfectious immature state to the infectious mature state during the viral life cycle. An intriguing feature of the immature HIV-1 is the sizable gaps in its protein lattice observed by electron microscopy. The origin of the gaps is not understood but they may be important for the timing of release of
the viral particle from the cellular membrane before assembly is completed. We hypothesize that the gaps are unavoidable consequences of the high aspect ratio of the protein subunits constrained to assemble on a spherical shell. The hypothesis represents a new paradigm in virus assembly and will be tested through a multi-pronged interdisciplinary approach including: a) mutagenesis, b) complementary structural studies of immature particles by
cryo-TEM and SAXS, c) theoretical modeling of rod-like subunits spherical assembly, d) directed assembly on templates of various radii.

The vertebrate embryo body is segmented and elongated along the antero-posterior axis. Segmentation of the vertebrate body into vertebrae precursors takes place simultaneously with the extension of the body axis. For the synergistic progression of these two processes, cell behavior and tissue patterning needs to be precisely coordinated. To reach a comprehensive description of the complexity of this system we propose a multidisciplinary project involving biologists, image processing experts and modelers. High-resolution time-lapse imaging of quail transgenic embryos will be used to collect data of the molecular, cellular and tissue dynamics underlying axis formation and patterning with a previously unmatched precision. Analyzed data will be used to build, for the first time, a 4D model integrating morphogenetic and patterning processes. This model will be used to challenge existing and formulate new hypotheses in the field of axis elongation and segmentation. Our collaboration significantly profits in the way that novel in silico predicted properties will be reiteratively challenged experimentally in vivo to feed back and improve our model.

A major goal of neuroscience is to identify neuronal circuits that generate specific animal behaviors. This requires methods to activate specific neurons inside a behaving animal. Opto-genetics combining genetics and visible light to specifically activate or silence neurons satisfies this need, at least partially, and has begun to revolutionize the analysis of neuronal circuitries. However, visible light penetrates tissue poorly requiring piercing an optical fiber into the brain. In contrast, magnetic fields penetrate tissue much more easily. However, development of in-vivo magnetic cell stimulation is hindered because the weak interaction between magnetic fields and biomaterial require a transducer to translate the magnetic signal into a biological stimulus.
We propose a truly contact-less, genetically targetable magnetic field stimulation based on a novel nano-transducer. The transducer consists of super-paramagnetic nanoparticles (MNP) which convert the energy of an applied radio-frequency magnetic field into local heat which opens temperature sensitive ion-channels and activates the neuron.
Major novel aspects of our proposal are (a) local subcellular heating of regions of the cell membrane of genetically selected neurons by targeting MNPs to these places via binding to engineered surface receptors; (b) local temperature determination by fluorescence thermo-sensation; (c) self-assembly driven nano-actuators in form of a MNP array tethered to the temperature sensitive ion-channel; and (d) transfer of bacterial magnetosomes synthesis to eukaryotic cells.
The four objectives of the proposed research are A: develop fast magneto-stimulation of neurons in vitro, B: genetically target the transducer to specific cells and cell areas, C: validate the method in vivo, and D: transfer genes to produce MNP into eukaryotic cells. We will follow an interdisciplinary approach that includes methods from synthetic biology, cell and molecular biology, physical chemistry bacterial genetics, circuit neuroscience, and advanced microscopy and optics.
If successful, this research will lay the foundation of a novel field termed “magneto-genetics”, the remote stimulation of genetically selected cells deep inside the body. The potential reaches beyond neuroscience to other stimulatory cells, i.e. insulin secreting island cells, muscle cells and others.

During development, cells differentiate and form specific adhesive contacts with other cells in order to create tissues. Defects in this process give rise to developmental abnormalities and metastatic cancers. The strength and mechanical properties of cell-cell adhesions govern the mechanical strength and integrity of tissues subject to mechanical stress, such as epithelia. Despite these important physiological outcomes, mechanisms underlying the response of cells to external mechanical forces remain poorly studied. Gaining insight into these mechanisms is crucial to our understanding of normal development, wound healing, disease processes and tissue engineering therapies.The proposed project integrates the expertise of 4 teams, on 3 continents to examine how mechanical forces influence the formation and properties of cell-cell adhesions.
This collaborative project brings together expertise in the design of: (i) devices to accurately measure forces at the molecular and cellular scale (Lim & Ladoux); (ii) nano and micro-fabricated environments (Ladoux); (iii) molecular and cellular tools and (iv) biochemical characterization of molecules in cell-cell contacts (Nelson and Mège). Additionally, the interface between these groups provides a novel training platform for postdoctoral fellows, and undergraduate and graduate students in team building and multi-disciplinary research that crosses boundaries between engineering, biophysics, biochemistry and cell biology. The ability to examine the effects of forces on both cellular and molecular scales offers a powerful way to define the relations between molecular and structural intracellular organization, cell mechanical properties and cell behavior.
The specific goals of the proposal are: 1. Design and validate new tools that enable experimental procedures to be more quantitative in the context of mechanics of cell-cell junctions in epithelial tissues, and develop well-defined microenvironments to control cell adhesion and obtain quantitative measurements of cell behaviors ; 2. Investigate how cells regulate cell-cell junctions in coordination with cytoskeleton dynamics; 3. Investigate the mechano-sensitivity of cadherin-associated proteins at the single-molecule level. These studies will define the mechanisms of tissue cohesion at molecular, subcellular and multicellular scales, and provide a mechanistic framework of the effects of external mechanical forces on epithelial cell-cell contacts.

This project assembles an international team of biologists, mathematicians and engineers to uncover the secrets of the world’s most spectacular animal-built structure: the mound built by the southern African termite Macrotermes. These spectacular structures, long known as the famous “air-conditioned termite mound”, has many new secrets to reveal. The mound does not appear to “air condition” the nest, but is in fact a remarkable organ of extended physiology, essentially the lung for the underground colony. Among the secrets revealed are a novel mechanism for capturing turbulent wind energy to do useful work, and building behavior that is far more sophisticated and complicated than ever realized.
This project seeks to push these new findings into new scientific frontiers, including the physics of using turbulent wind, the largely unexplored biology of the termite brain, and the nature of the collective cognition of the termite colony. From this, we hope to learn new methods for analyzing the adaptation of organisms to their environment, the process of building coherent organs of physiology, new ways to program robot swarms, and perhaps novel ways to exploit wind in climate control of our own buildings.

The last two stages in eukaryotic translation, termination and ribosome recycling, are very distinct from the corresponding, well-characterized stages in bacteria. Thus, eukaryotic termination results from the complex functional interplay between two release factors, eRF1 and eRF3, in which GTP hydrolysis by eRF3 couples codon recognition and peptidyl-tRNA hydrolysis by eRF1, whereas eukaryotic ribosome recycling is mediated by ABCE1, a unique highly conserved member of the ATP cassette family of proteins that contains an iron-sulfur cluster domain, and which does not exist in bacteria. Moreover, in contrast to bacteria, eukaryotic termination and ribosome recycling are intimately linked because eRF1 plays a key role in both processes. Although these two stages of eukaryotic protein synthesis are of major importance in regulation of eukaryotic translation, and are linked to downstream events such as reinitiation and mRNA surveillance, their mechanisms have only recently begun to attract attention. However, future progress in elucidating the molecular mechanism of eukaryotic termination and ribosome recycling is strongly compromised by the lack of structural data. The primary aim of this proposal is therefore to obtain a comprehensive overview of the architecture of defined intermediate states in termination and ribosome recycling and to model the transition between them. To achieve this goal, we shall integrate the complementary expertise of four leading laboratories in cryo-EM, X-ray crystallography, computational biology and functional studies.
The specific aims of the proposed research include: (i) elucidation of the molecular basis for the omnipotent decoding capacity of eRF1 using X-ray studies of modeled eRF1-associated 80S ribosomal complexes containing different stop codons in the A-site, (ii) determination by cryo-EM of the structures of eukaryotic ribosomal complexes corresponding to different stages of termination, from initial ribosomal attachment of release factors through GTP hydrolysis by eRF3 to the final stage corresponding to post-termination complexes containing deacylated tRNA in the P-site, (iii) visualization by cryo-EM of ABCE1 in post-termination complexes and identification of its critical functional interactions with 80S ribosomes and eRF1, (iv) computational analysis and dynamic simulation of ribosomal transition between individual stages in termination and ribosome recycling based on X-ray and cryo-EM results, and (v) functional investigation of the mechanisms of mammalian reinitiation, regarding its importance as a regulatory post-termination event. In summary, the results that are anticipated to emerge from the proposed studies will for the first time provide an integrated structural and mechanistic outline of the last two stages in eukaryotic translation.

Neurodegenerative disorders, including prion diseases, are associated with protein aggregation. Considerable evidence indicates that the extent of neurotoxicity or infectivity of the oligomeric or aggregated proteins is strictly dependent on their structures. The proteins involved in these diseases are conformationally heterogeneous and, according to an emerging view, can switch back-and-forth between functional and various amyloidogenic/prionogenic conformations (strain conformations). Since the various conformations present in these heterogeneous ensembles lead to different aggregated forms, characterizing the monomer conformational space is critical to understand their pathogenecity. However, the characterization of the conformational heterogeneity of monomeric proteins by standard structural biological methods has proven to be extremely challenging. Single-molecule methodologies offer exciting opportunities to increase our understanding of protein conformational equilibrium. This project is aimed at using a novel approach that combines the two main methods for single-molecule manipulation, Optical Tweezers and Atomic Force Microscopy, to map the conformational energy landscapes of a mammalian prion protein (PrP) and yeast prion Sup35 protein, as well as their monomer conformations that promote the aggregation process. Mouse PrP is an ideal candidate for prion conformational studies due to the possibility of creating different infectious conformations in a test tube and of introducing them in mice to develop novel prion diseases. Similarly, the ability of Sup35NM, a prion domain of Sup35, to convert into prion states in a test tube and the possibility of introducing them in yeast, make the yeast prion [PSI+] system uniquely suited to investigate the mechanism by which a single polypeptide (Sup35NM), displaying a heterogeneous ensemble of conformations, can form initial nuclei and misfolds into self-propagating distinct amyloid conformations. The synergic integration of these single-molecule techniques will make it possible to explore conformational properties of both mammalian PrP and yeast prion that are inaccessible to more classical in-bulk ensemble-averaged methods, and to study the nature of the energy surfaces over which these molecules diffuse as they move between their different strain conformations and towards those that are responsible for triggering the aggregation processes and pathogenesis.

Ubiquitination is used by all eukaryotic cells to regulate the localization and turn-over of membrane proteins. Ubiquitination is mediated by ubiquitin ligases. This proposal brings together four researchers working in three continents to characterize a family of such ligases called MARCHs. The MARCHs play major immunoregulatory roles and are anchored to membranes, a unique feature among ubiquitin ligases. Indeed, they recognize their substrates via transmembrane (TM) region interactions, itself a poorly understood phenomenon. We will apply our expertise in immunology, cell biology, proteomics, solution NMR and computation biophysics to fulfill the following aims:

AIM 1: To identify MARCHs substrates

Aim 1.1: We will characterize the expression pattern of MARCH genes in the immune system.

Aim 1.2: We will use label-free quantitative proteomics of plasma membrane (PM) fractions to identify proteins with altered surface expression levels in cells deficient in MARCH 1, 2, 3, 4, 8 or 9 (MARCH substrates).

AIM 2: To characterize the structural basis of MARCH substrate recognition via TM interactions

Aim 2.1: We will determine the role of structural motifs in the TM regions of the MARCHs and their substrates in MARCH-substrate recognition.

Aim 2.2: We will characterize the three-dimensional arrangements of TM regions of the MARCHs and their substrates using solution NMR.

Aim 2.3: We will apply computational modeling to the study of interactions between the TM regions of the MARCHs and their substrates.

Aim 2.4: We will generate chimeric mice with bone marrow retrovirally transduced to express mutant forms of the MARCHs to validate the conclusions of the structural studies in vivo.

The knowledge we will gain with this project will be highly significant at multiple levels. It will contribute to understanding the structural basis of TM-mediated protein-protein recognition and the role of ubiquitination in regulation of membrane protein expression and localization, an activity present in all eukaryotic cells. As the MARCH substrates that we will identify are likely involved in immunoregulation, this project will also be relevant to immunological tolerance and the initiation of immunity. Finally, our project will lead to refinement of strategies for computational modeling of three-dimensional structures of membrane proteins.