Toxoplasma is a common parasite of birds, rodents, and humans during the asexual phase of its life cycle. But, having sex for Toxoplasma is limited to cat intestines. It enters cat when an infected rat or bird is eaten up. This creates an interesting problem because rats do not prefer to be eaten up. Toxoplasma blocks the fear of cats from infected rats. This is often taken to mean that infected rats will approach cat without fear and be eaten up at higher rates. We have no direct evidence for this indirect assumption. We will test this in the first part of this project. Kangaroo Island in Australia plans to fence off one of its parts and exterminate all cats from there. The island is doing so to protect wildlife and to reduce Toxoplasmosis in livestock. From our point of view, this is a golden opportunity to test if Toxoplasma increases predation of rats by cats. We can now compare the survival of infected rats and mice vis-à-vis uninfected rats and mice in the same landscape before and after cat removal. We expect to see more infected animals dying than uninfected when cats are around; and no difference when cats are removed.
While having sex is limited to cats, Toxoplasma can still sustain its asexual life cycle through carnivory or sexual reproduction. The sexual reproduction is exciting because such infections usually have less virulence. They do not kill a host very often as dead hosts do not reproduce to further transmit the parasite. Parasites moving across the food chain, from rats to cats for example, do not have such limitation and often increase virulence. But what happens when an infection is simultaneously transmitted by sexual and going-up-food chain mode? Both paths must trade-off with each other. When cats are plentiful it pays to increase predation (by reducing fear in infected rats) even if it means a bit less of sexual transmission and vice versa. This is a difficult assumption to test directly. The situation in Dudley Peninsula provides a perfect opportunity. We will collect Toxoplasma from bodies of infected rats and mice before and after cat extermination. We will bring these bugs in the lab and ask if cat removal means that the parasite now concentrates more on sexual transmission. That would mean a robust invasion of testes, more pheromones and more liking elicited from uninfected females. This is the second part of this project.

Organ development depends on the integration of local cell-to-cell interactions with long range signalling throughout the body. We will investigate mechanisms by which long-range signalling via the cerebrospinal fluid (CSF) regulate body axis formation and spine curvature. The CSF is produced by the choroid plexus in the brain ventricles and flows down the central canal in the spinal cord. The CSF instructs brain development by delivering age-dependent grow-promoting factors to target cells. CSF circulation also contributes to the curvature of body axis (embryo) and to the spine (juveniles). However, the mechanisms regulating the flow and content of CSF remain poorly understood. Progress has been impeded by a historical lack of tools and challenges inherent to studying fluids in small, developing organisms. The advent of innovative tools and approaches now provides an unprecedented opportunity to overcome previous limitations. The transparency of zebrafish and the accessibility to mouse CSF provide powerful models for testing our driving hypothesis that the physical and biochemical properties of CSF impact body axis formation and spine curvature. We propose an entirely new, interdisciplinary collaboration of three leaders in their field: (1) physicist Francois Gallaire (EPFL, Switzerland), expert in the theory & modelling of complex fluid dynamics; (2) developmental neurobiologist Maria Lehtinen (Boston Children’s, HMS, USA), expert in analysis of the choroid plexus-CSF system; (3) biophysicist Claire Wyart (ICM, France), expert in imaging and sensory physiology in the spinal cord. Our multi-tiered approach will unravel the principal parameters driving CSF composition and flow. We will map CSF flow in the developing fourth ventricle and central canal (Aim 1), elucidate mechanisms regulating protein secretion into the CSF (Aim 2), and investigate mechanisms of active transport of instructive signals along the anteroposterior axis controlling organogenesis (Aim 3). The proposed studies will transform this historically understudied area of neuroscience into a robust field spanning CSF-based signalling in brain and spine. As studies of paracrine signalling and fluid dynamics lag far behind cell-intrinsic studies of signalling, our techniques and concepts should provide a roadmap for future studies of fluid niches throughout the vertebrate body.

The idea of combining man-made and natural systems has fascinated humans for centuries. However, despite the explosion of life science advances, the integration of electronic and biological systems remains woefully underdeveloped. To address this, we will apply principles of Synthetic Biology to develop biological cells controlled by electronic signals.

We propose to create synthetic cellular receptors selectively activated by electrochemically activated peptide. In order to endow the system with the ability to activate a selected ligand:receptor pair in the presence of other polypeptides, we propose to construct peptide-selective bio-electrodes. Electro activation of the peptides decreases their affinity for the electrode and leads to its relocation to the two component cellular receptor that utilizes intramolecular proteolysis to activate transcription of the reporter genes. Using the team’s expertise in protein, cellular and electronic engineering we will design an integrated system where the activation of the reporter expression can be both controlled and monitored using electrode array in a few or even in a single mammalian cell.

This proposed approach enables the construction of a potentially unlimited number of orthogonal electrode/ peptide/receptor systems that allow multichannel information transfer between computing devices and biological cells. While the first embodiment relies on the relatively slow gene expression readout, the same approach can be used to control practically any biochemical process in real time. Such synthetic signaling pathways capable of performing logical operations will exert complex and precise control on cellular biology, leading to a first generation of bioelectronic hybrids.

Plant development and growth are linked to cellular shape changes, which are controlled by genetic programs but also by perception of environmental signals, including mechanical cues. While both genetic regulation and mechanical control of morphogenesis were studied independently, there is a need to explore how cellular shape-associated strain and stress can mechanically regulate gene expression during differentiation. In animals, mechanical stimuli are known effectors of differentiation. They involve propagation of mechanical forces through the cytoskeleton to the nucleus, leading to chromatin remodeling and modification of gene expression. Thus, nuclear envelope proteins that control nuclear shape and transmit forces to chromatin play a key role in rapid triggering of gene expression. In plants, less is known about mechanotransduction from cell surface to the nucleus.
Using a systems biology approach and an interdisciplinary network, we propose to investigate how mechanical cues affecting cellular shaping are sensed at the nuclear envelope to drive chromatin remodeling in Arabidopsis. We will sudy a unique cellular model, the single root hair in an epidermal tissue context, with well-defined morphogenetic programs linked to cytoskeleton and nuclear dynamics. We will analyze root hair formation and growth in WT and mutants affected in either root hair development or nuclear shape. Combining in vivo live imaging and micro-mechanical measurements (rheometry), we will evaluate mechanical properties of cells and nuclei during root hair development and their dependence on cytoskeleton and nuclear dynamics in relation to gene expression. We will also determine how these mechanical, structural and biological properties are modified when a controlled mechanical stress is applied to the root hair cell during development. Our data will highlight proteins involved in mechanosensing, and we will evaluate their interaction with the nuclear envelope network. Live imaging and rheometry data will be correlated to finite element modeling to estimate strain and stress in the system for predicting chromatin remodeling following cellular and nuclear shape changes.
Altogether, this will highlight the molecular networks involved in mechanosensing at the nucleo-cytoplamic interface and reveal how gene expression is robustly regulated during cellular morphogenesis in higher plants.

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.

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.

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.

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.

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.

Perceiving and interpreting our sensory environment feels subjectively effortless, yet, it is one of the computationally most challenging tasks the brain needs to solve. Critically, our brain constantly fuses current sensory input with expectations derived from prior experience in order to be able to reliably interpret our environment in spite of ever-changing conditions, such as lighting, pose, or configuration, making every single experience unique. That prior expectations are constantly shaping our percepts has been well known for over a century from behavioral studies, but how neural circuits in sensory areas of the brain achieve this sensory-prior fusion has remained largely unknown. Progress in several research fields make it possible now to address the neural bases of sensory-prior fusion: novel recording techniques provide an unprecedented opportunity to track the activity of large populations of neurons over extended periods of time; advances in artificial intelligence and machine learning provide powerful new tools to analyse complex data; and advances in computational theories allow us to formulate experimentally testable hypotheses and compare their predictions to data. These techniques are now being used to great effect in sensory neuroscience, but almost exclusively to characterise how sensory input alone impacts neural responses along different stages of the visual processing system of the brain. Our project aims to bring these advances to bear on understanding the effects of prior expectations on neural responses, and their fusion with sensory information. We will rely on complementary approaches that provide insights into different aspects of sensory-prior fusion: experts in mouse experiments and monkey experiments will train complex tasks and record from brain areas that contribute to sensory-prior fusion, while experts in machine learning-based data analysis and computational neuroscience will develop cutting-edge analysis techniques and models to guide experiments and interpret data in a formal theoretical framework. Our project will thus help us understand how a brain that is composed of unreliable components and prone to a variety of perceptual distortions and illusions can efficiently process rapidly changing, cluttered, and noisy scenes to achieve feats such as driving us home safely in busy traffic.

Understanding how out of single cells functional tissues and organs develop is a major challenge of biology. Recent progress allows us to grow organ-like cell assemblies (organoids) from stem cells in vitro. Organoids offer great potential for studying diseases and development. However, in many cases we do not yet understand how these complex tissues emerge out of progenitor stem cells. A common feature in the initial growth phase of many organoid systems is the formation of a polarized epithelial cyst with a single or multiple internal apical lumen. This initial transition into an epithelial cyst establishes a tissue template that on the one hand enables maintenance of progenitor/stem cells (niche) and on the other hand guides the patterning of differentiated cells into a functional tissue. Our aim is to understand how the interplay between proliferation (cell divisions), polarization (epithelial transition) and differentiation (patterning) leads to self-organization of this epithelial progenitor template and how this structure facilitates correct patterning into functional organoids. To this end, we will systematically control and characterize the early growth phase of two organoid systems (pancreatic and neural tube) using microfabrication and micro-patterning approaches. We will quantify evolution of cell shapes, adhesion and cortical forces, apical-basal polarization and differentiation as a function of initial cell contact patterns. This approach will provide the means to find rules how local cell interactions (cell-cell, cell-matrix, cell-lumen) are connected to tissue growth and differentiation. We will then test sufficiency of the hypothetical rules to generate the observed organoid structures using an in silico mechano-chemical model. Taken together, by dissecting the early growth phase of two organoid systems, we aim to uncover the common rules on how progenitors establish a polarized epithelial template, and how this template is then differentially used to generate organ specific differentiation patterns.

Life on earth depends upon the photosynthetic conversion of H2O, CO2 and light into fixed carbon (C) compounds including polysaccharides and lipids, and yet the biosynthesis, regulation and many aspects of the function of the photosynthetic apparatus are still not well understood. A major challenge for photosynthetic organisms is to capture light energy for growth while at the same time eliminating excess absorbed excitation to prevent photodamage, which can be energetically costly and potentially lethal. A major photoprotective mechanism in plants and most algae is qE (quenching energy), a quenching mechanism that dissipates absorbed excitation energy as heat, ensuring survival even under adverse conditions. In the green alga Chlamydomonas reinhardtii (Cr), two LHCSR proteins (Light Harvesting Complex Stress Related; LHCSR1 and LHCSR3) are required for qE function.
The LHCSRs are nucleus encoded, and their expression is governed by transcriptional and post-transcriptional processes that are impacted by CO2, nutrient availability, photosynthetic electron transport (PET), blue light perception and calcium(Ca2+)-elicited signalling. Despite their fundamental importance, mechanisms that regulate LHCSR accumulation are still not well understood and complicated by multiple inputs. For example, our findings demonstrate that LHCSR control is impacted by the metabolism of fixed C compounds. The combined use of physiology, biochemistry, genomics and mathematical modeling will allow us to elucidate transcriptional, post-transcriptional and epigenetic processes that link photosynthesis, C metabolism and photoperception to qE activity, and help establish a systems level view of photosynthetic dynamics.

The complexity of cellular machineries has been forged by the motors of evolution (mutation, natural selection, and genetic drift), with boundaries that are determined by the properties of biological molecules and the biophysical limits of the cell. Our goal in this project is to determine what are the relative contributions of biophysics and evolution in shaping this complexity. Our model of interest is cell signaling, which is rapidly evolving and involves highly interconnected networks of proteins that sense and process signals and make real-time decisions to satisfy cellular needs and promote survival and proliferation. Because typical cells contain from millions to billions of protein molecules, signals can reach out to unwanted proteins in an unspecific manner. How much can evolutionary forces optimize this process so that cells can reach biophysical optimality by minimizing unspecific interactions is currently unknown. This question can be answered neither from physics nor from biology alone, and thus requires a multidisciplinary team. Our international team with expertise in theoretical physics (Gasper Tkacik), evolutionary biology (Christian R Landry) and biochemistry (Judit Villen) is poised address this question. We will generate a mathematical model of signaling network evolution that includes key biophysical and evolutionary driving forces to examine how each contributes to create unspecific signaling interactions in organisms with finite population sizes. This model will guide experiments in which we will manipulate the amount and extent of unspecific interactions and measure its biochemical impacts and its effects on fitness using experiments and bioinformatics data integration to calibrate parameters of the model. In biophysics, it is often assumed that biological systems have reached an optimum attained by natural selection and are only limited by their physical characteristics. Evolutionary biology considers that natural selection works against genetic drift and mutations to bring biological networks near their optimum, which is unknown. Our work between these two fields will reveal how close to the biophysical limits can signaling networks get and how biophysical and evolutionary forces are integrated to shape accurate signal transduction.

Heat produced by living species has been known for centuries but viewed merely as a factor contributing to body temperature. Recent progress in ultra-local thermometry at a cellular scale has challenged this concept. Reports on heat release by active ion channels and pumps and other pioneering experiments and theoretical estimates have fuelled discussion about the significance and the magnitude of endogenous heat. Discoveries of the faster neurite growth aligned with a thermal gradient and heat-pulse induced muscle contractions without Ca2+ influx suggest that cell hot spots may channel signalling and thus contribute to cell and tissue differentiation. We will study the role of heat in three-dimensional cell shaping and differentiation and test the hypothesis that localized heat signals can affect morphology in cells other than neurons. We will aim to resolve the current controversy of intracellular thermometry, the drastic mismatch between theoretical estimates based on near-equilibrium thermodynamics and reported experimental values of temperature rise. We will investigate the signalling activity of artificial hot spots introduced into or close to cells and measure thermal activity of natural hot spots on cell membranes. We will develop a reliable intracellular nanothermometry system and an ultra-local heat-shock trigger-and-measure method to create and control the ultra-local hot spots with light. The method will use a synthetic complex of several nanoparticles, one as a heater and the others as temperature sensors. For the heater, we will use a gold nanorod whose heating can be controlled by the wavelength and polarization of light focussed on the rod. The temperature will also be measured optically, with nano-sized crystals of diamond doped with photoluminescent defects (nitrogen-vacancy centres being the primary candidate fro this role). The expertise of the applicants provides the required synergy between advanced nanotechnology, biophysics and cell biology to achieve these goals. The project starts simultaneously at four nodes and efforts will increasingly integrate as the investigation progresses.

Basic biological processes such as cell migration, tissue morphogenesis, and hearing rely on mechanotransduction, i.e., the conversion of mechanical forces into electrical and biochemical signals that can be used by individual cells or multicellular organisms to survive. Adhesion complexes bearing mechanical force are often needed in mechanotransduction, with several protein families that include integrins and cadherins directly transmitting force signals to sites of transduction. Classical cadherins, key for tissue morphogenesis and integrity, provide calcium-dependent bonds involved in cell-cell contact formation, in signaling to the actomyosin cytoskeleton, and in mechanical stabilization of cell-cell adhesion. Non-classical members of the family are also involved in mechanotransduction, with cadherin-23 and protocadherin-15 forming an adhesive “tip link” essential for the vertebrate senses of hearing and balance. Multiple structural and biophysical studies have elucidated the unbinding, unbending, and unfolding strength of single molecules and adhesive complexes, including those formed by cadherins. However, to the best of our knowledge, nothing is known about how the mechanical properties of adhesion complexes have evolved. Here we aim to study the mechanical evolution of adhesion complexes using inner-ear cadherin tip links as a model system. Tip links initiate sensory perception by directly conveying tension to inner-ear mechanotransduction channels on a microsecond time scale. Fast and effective transmission of mechanical force must be one of the selective factors that dictate the molecular evolution of tip links. We will sequence, synthesize, and study tip-link proteins from diverse extant species and will carry out evolutionary analyses both to reconstruct the sequences of ancestral, “resurrected” tip links, and to identify potentially stronger tip links from species in which positive selection is reported. In parallel, we will use biophysical techniques to determine equilibrium binding affinities and structural properties of modern tip links from various species and ancestral tip links at different evolutionary stages. High-speed force spectroscopy and molecular dynamics simulations will be combined to probe tip link mechanics and strength across species and during evolution. Our interdisciplinary work will provide a unique evolutionary view of adhesion mechanics.

The aim of this proposal is to gain insight into the mechanisms of chromatin reprogramming to totipotency in mammals. Totipotency is the potential of a cell to generate all cell types of an organism including extraembryonic tissues. Whilst induced reprogramming to pluripotency by the Yamanaka factors is relatively inefficient and takes days to weeks, natural reprogramming to totipotency occurs within hours in the one-cell embryo or zygote. How zygotic reprogramming is achieved is poorly understood. We will approach this fundamental question by studying the chromatin state of totipotent cells and their precursors. We will determine how higher-order chromatin organization changes during epigenetic reprogramming in zygotes and primordial germ cells, using both mouse embryos and human/mouse primordial germ cell-like cells. We will use our understanding of the zygotic chromatin state to identify candidate pioneer factors and to test their role in promoting totipotency and genome activation. The results of the project will provide insights into how reprogramming alters genome organization and promotes establishment of a totipotent chromatin “ground state”. This project is led by a strong multi-disciplinary team bringing together expertise in polymer physics (Mirny), ovary organoids (Saitou), biochemistry and single-molecule imaging (Peters) and zygote biology (Tachibana-Konwalski).

Breast cancer frequently metastasizes to bone where it leads to osteolytic bone degradation and poor clinical prognosis. Nevertheless, therapeutic options to interfere with this process are scarce as the underlying mechanisms remain unclear. Most current research focuses on the cellular and molecular signaling underlying bone metastasis, but breast cancer cell interactions with the bone mineral matrix, a composite of collagen fibers reinforced with nanoscale crystals of hydroxyapatite (HA), may be similarly important. However, in the field, there is an ubiquitous lack of (i) high resolution techniques to characterize the multiscale structure of bones as a function of breast cancer progression, (ii) microscopy techniques to identify the underlying changes in bone mineralization pathways in fully hydrated samples, and (iii) model systems to evaluate the functional consequences of varied bone mineral properties on cell behavior largely prevent such studies. Here, we will address these shortcomings and capitalize on the interdisciplinary background of the proposed team in cancer biology and tissue engineering (Fischbach), high resolution structural analysis of hierarchical materials (Fratzl), bone biology and biomineralization pathways (Addadi), and bioinspired materials synthesis (Estroff) to test the hypothesis that breast cancer modifies the hierarchical structure of bones by altering bone mineralization pathways and that the resulting changes in HA nanoparticle characteristics are critical to the pathogenesis of breast cancer bone metastasis. To address this hypothesis, we will pursue three specific aims: Aim 1 will analyze the multiscale structure of bones in mouse models mimicking pre- and post-metastatic stages of breast cancer. Aim 2 will determine the corresponding differences in bone mineralization pathways and Aim 3 will synthesize biofunctional bone-mimetic materials to study the effect of bone mineral matrix properties on tumor and bone cell behavior. This work will broadly impact our understanding of breast cancer bone metastasis and challenge the conventional paradigm of bone metastasis of this disease as solely initiated by cellular and molecular mechanisms. Insights gained from our studies may yield novel therapeutic targets to treat or possibly even prevent bone metastasis in the future.