Some four and a half billion years ago, primitive proteins spontaneously phase separated from their environment, like oil from water, to form liquid droplets, which became crucibles for the evolution of the chemical processes that underlie life to this day. This is how the Russian biochemist Alexandr Oparin postulated that life began to evolve, almost a century ago. Very recently, the droplets that Oparin predicted have been discovered and they are composed of molecules resembling the primitive proteins he imagined would have been found in the “primordial soup”. These droplets have been shown to serve a number of important functions and proteins that compose them underlie neurological diseases, including Parkinson’s and Huntington’s diseases and ALS, among others. How many such structures, called non-membrane organelles (or NMO), could exist in the cell and what are their functions? What are the physical rules and chemical information encoded in the sequences of MNO-forming proteins that dictate their unique properties? What happens if NMOs are disrupted? These are the questions we have set out to address in this proposal. The central aim of our proposal is to create a compendium of NMOs in a model of the eukaryotic cell; the bakers yeast. Yeast is an ideal model because it shares many genes with humans, notably those that are most primordial and those that become dysfunctional with age and in diseases such as cancers, and neurodegeneration. We will use massively parallel and automated experimental and computational and theoretical approaches to determine protein sequences that code for their ability to form MNOs of different types and predict the biological function of specific MNOs. We have shown how certain types of cell regulation including gene function and spatial organization of large cell structures depend on NMOs. The compositions of NMOs are surprisingly rich in protein molecules that when mutated, are known to underlie neurodegeneration. We hope to define how these mutant proteins cause dysfunction, perhaps by disrupting the normal functions of NMOs, and what kinds of strategies could re-stabilize them. Finally, the rules of NMO formation and function we elucidate in yeast will allow us to make predictions about similar structures throughout the tree of life, including in humans, ultimately establishing another axis of order that defines life.

In this project, we will provide new insights into the behavioral strategies, biomechanics and motor control animals use to perform complex versatile and adaptive functions and provide novel bio-inspired robot technology for solving complex motor control problems.
Despite the constraints imposed by their miniature brains and bodies, dung beetles are capable of the most impressive
feats of motor control and navigation. Beetles of the species Scarabaeus galenus are able to move large objects – dung balls that can exceed 10 times their own weight – accurately between a food source and their burrow by combining celestial compass orientation with step-counting. In addition, they are able to use their specialized body and legs to dig burrows, manipulate different dung types and move them over different types of terrain (e.g. sand or grass) using a variety of locomotor patterns. How do they achieve these complex versatile and adaptive behaviors when moving over difficult terrain? Our project aims to address this through our integrative approach which combines behavior (EB), biophysical, kinematic and biomechanical analyses (SG) of S. galenus, and computational motor control and robotic modeling (biorobotics, PM).
Research on behavior and neuro-biomechanical functions of insects has, until now, largely dealt with few behavioral modes – like walking, climbing, or navigating – in isolation. We will launch a major research effort aimed at uncovering behavioral strategies, biomechanics, and computational motor control that enable the miniature brains and bodies of insects to effectively generate multiple adaptive behavioral modes. Our behavioral experiments, both in the field and in the lab, will investigate locomotion, navigation, food transportation, and their combination in S. galenus. The data from these experiments will lay the foundation for novel biophysical, kinematic and biomechanical analyses, and computational motor control development. Simultaneously, biomechanical principles underlying the different behavioral modes will be used to shape the behavioral experiments and guide the structural design of robotic modeling. We will develop a biorobotic model that will enable us to test our hypotheses about the relationship between structural and mechanical features and how they interact with motor patterns and neural mechanisms to form complex behaviors.

The ribosome is the universal translation machine, which makes all the proteins in the cell, including its own. Much is known about ribosome structure and assembly pathway. However, cell-free synthesis and assembly of ribosomal proteins and rRNA into functional ribosomes has not been reconstituted, which would be essential for establishing a protein-based self-replicating model system of artificial cells, and provide a new means to develop antibiotics. We will address the challenge of cell-free ribosome biogenesis by combining the reconstitution of E. coli translation from purified components developed by Shimizu and Ueda (PURE system), with the miniaturized on-chip DNA compartments introduced by Bar-Ziv's lab. We address following three questions: i) What are the minimal requirements for cell-free ribosome biogenesis?; ii) How is ribosome biogenesis affected by excluded volume interactions, segregation, and macromolecular gradients in the DNA compartment?; and iii) Can DNA brushes coding for rRNA and ribosomal proteins mimic spatial ‘operons’ and promote efficient assembly coupled to synthesis? For these questions, we will attempt to 1) develop a methodology to label and localize cell-free synthesized ribosomal proteins and rRNA; 2) tailor the PURE system to support cell-free ribosome biogenesis reactions; 3) tailor DNA compartments geometrically to direct ribosome biogenesis and measure synthesis and assembly or ribosomal proteins and rRNA using time-lapse fluorescence microscopy; and 4) develop approaches to resolve, physically and biochemically, new from old ribosomes. The combination of molecular biology and biochemistry with soft matter physics and materials science are expected to provide favorable conditions for in vitro ribosome biogenesis and novel means to separate new from existing ribosomes.

A fundamental challenge in biology is to understand how brain cells change in response to experience and how these changes contribute to memory and establishment of other long-lasting behaviors. Changes in neuronal gene expression are important for memory formation, maintenance and retrieval. Recent advances in genome biology have found that three-dimensional (3D) genome organization—genome topology—is critical for transcriptional regulation. We hypothesize that neuronal genome topology provides special “topology codes” for activity-driven transcriptional modulation in neuroplasticity, and abnormal topology codes contribute to cognitive disorders. This project will examine genome topology and transcriptomics in mouse hippocampus and explore how the dynamics of genome topology contribute to the rapid and highly coordinated transcriptional response during learning and the long-lasting changes in gene expression that underlie memory, epilepsy and other enduring forms of neuroplasticity. Our multidisciplinary team with complementary skills in neuroscience, genomics and bioinformatics will take an integrated approach that includes a novel 3D genome mapping strategy for small numbers of cells (Ruan), advanced genetic labeling and biochemical isolation techniques for transcriptional and epigenomic profiling of neuronal ensembles (Barco), and state-of-the-art, multimodal microscopy for nuclear imaging (Wilczynkski). We will develop and optimize our platform in cultured neurons subjected to different stimuli (Aim 1), and we will examine the 3D epigenomic dynamics of the nuclear response to synaptic activity in two well-established in vivo paradigms: epileptic seizure (Aim 2) and the formation of associative memory (Aim 3). The large volumes of high-quality and multiplex genomic data representing dynamic changes in neurons in response to activation will be integrated by comprehensive computational analysis (Aim 4). Predicted genetic loci that have important roles in chromatin topology and transcriptional regulation will be validated structurally by super-resolution nuclear imaging and functionally by genome editing (Aim 5). The results of this effort will open new chapters in learning and memory and epilepsy research by laying a foundation for understanding the dynamic and topological mechanisms of genome regulation in neuronal plasticity in health and disease.

This work leverages cutting-edge genomic and shape analysis methods to study the evolution of mammalian cooperative societies. Current approaches to studying vertebrate cooperative behavior work in the classical, but mechanism-free, frameworks of behavioral ecology and life history theory. Thus, while cooperation itself is of long-standing interest, we know little about how animals that occupy distinct roles in cooperative societies differ at the molecular level.
Here, we propose to integrate new molecular and computational approaches with a 24-year field study of the most cooperative nonhuman mammal yet described, the meerkat. Like cooperative insects, meerkat societies are characterized by a division of social roles: adults are dominant breeders or morphologically and physiologically distinct helpers, who feed and guard the breeders’ young. However, all helpers retain the capacity to transition to breeder throughout life. Meerkats thus present an exceptional opportunity to study alternative phenotypes in cooperative societies. We will first investigate how helpers and breeders are differentiated at the gene regulatory level, including whether steroid hormone signaling generates these differences. Second, we will test social role-driven differences in growth and immune defense. We will track growth by developing computational geometry-based approaches to perform 3D skeletal reconstructions from X-ray data and immune defense using experimental pathogen challenges. Finally, we will test the hypothesis that the competing demands of growth, reproduction, and immune defense create “competition” at the transcriptional level, which is resolved differently by helpers and breeders. Our experiments will not only quantify phenotypic transition-associated trade-offs, but also identify the genes and pathways that mediate them.
The methods required for these analyses either do not exist or will need to be generalized to field studies for the first time. Thus, this study requires collaboration across behavioral ecology, genomics, immunology, and computational image analysis. Together, it will contribute a powerful model for applying modern tools to long-standing puzzles in evolution and behavior. It will also yield new insight into the molecular changes involved in the evolution of cooperative societies—a subject of fascination and controversy for almost two centuries.

Human mobility is made possible by skeletal muscles, a voluntary tissue under the control of the central nervous system. Upon injury or insult, skeletal muscle regenerates to restore its form and function. Muscle regeneration requires an adult stem cell population termed satellite stem cells (SCs) that reside in a specialized ‘niche’ atop the sarcolemma of multinucleate myofibres and ensheathed by a proteinaceous matrix. Most of the time SCs are quiescent; a state characterized by inactivity. Injury induces SCs to activate and produce committed progenitors called myoblasts that fuse into multinucleate myofibres. In the present state of our knowledge, SC activation is an essential and intriguing process that is not well understood. Although SC activation is tightly controlled in the body, when SCs are removed from the body and studied in two-dimensional culture, activation is the default state. This observation points to the enticing possibility that physical or structural aspects of the three-dimensional tissue microenvironment might contribute to the spatial and temporal control of SC activation. In particular, we hypothesize that injury rapidly alters the SC niche mechanical stress profile and that this serves to engage intracellular mechanisms that tip the balance in favor of SC activation over quiescence by directly altering transcriptional activity in a highly localized manner. The Gilbert (Canada) and Betz (Germany) labs share a common interest in resolving the impact of mechanical stresses on cellular fate, and the Darzacq (USA) is driven by a curiosity as to how the nuclear environment imposes on the fundamental rules of gene regulation. By joining efforts in an international collaboration, we aim to (a) define the mechanical stresses (e.g. compressive, shear) exerted on SCs in resting and regenerating niches and (b) determine the molecular implications of niche mechanics as they relate to the SC transcriptome in the native niche, for the first time. We will integrate our three distinct experimental approaches – SC cell and molecular biology (Gilbert), quantitative biophysics (Betz), and high resolution single molecule imaging of transcription factor binding and nascent transcript activity (Darzacq), to conduct a collaborative study and achieve a holistic understanding of the earliest events that evoke SC activation in the native niche.

The current Zika virus epidemic attracted public attention to the problem of mosquito-borne viral infections. Vector control is an essential element to prevent disease transmission due to the absence of arbovirus-specific drugs and limited availability of vaccines. Historical vector control methods such as the use of insecticides and environmental control are facing challenges due to the wide spread of insecticide resistance throughout natural mosquito populations and the complexity of breeding site elimination in the modern urban environment. Novel genetics-based strategies are emerging as promising complement to historical mosquito control methods. One idea is to genetically-manipulate the vectors so that they become unable to support pathogen infection, replication or transmission. The development of these novel transmission-blocking interventions requires in-depth insights into how mosquito vectors interact with and transmit arboviruses. It is thought that the immune system influences the efficiency by which mosquitoes transmit specific viruses. Recently, a novel immune response was identified that recognizes viral RNA and breaks it down into small fragments. In this project, the investigators will study whether mosquitoes from different locations across the globe differ in this immune response. Moreover, they will analyze how these differences influence transmission of the epidemic Dengue and Zika viruses. The multi-disciplinary research team includes experts in mosquito evolution and genomics, entomology, and virology, allowing a complementary approach to address the research aims. The proposed project will have immediate and profound implications for public health and may lead to novel mosquito control strategies.

What underlies the ability to count and where did it come from? This project tests the broad hypothesis that the ability to represent the number of objects in a set (numerosity) has an evolutionarily conserved neural basis, and identifies the cell and molecular processes involved using multidisciplinary analysis in zebrafish. Although a wide range of species are able to estimate numerosities, only in primates has a neural mechanism homologous to humans’ been demonstrated and the underlying cellular processes are unknown. Using automated operant conditioning we train zebrafish to perform numerical tasks and identify lines of fish with differential abilities (e.g. mutants in candidate genes identified from human studies generated using CRISPR). We use 2 photon light sheet imaging of neural activity as wildtype and mutant larvae discriminate numerosities to identify circuits involved. Behavioural analysis will establish the ontogeny and extent of zebrafish’ numerosity. Genetic analysis tests the hypothesis that numerosity has an evolutionarily conserved basis. Neural imaging will test the hypothesis that “number neurons” exist in fish as in primates and indicate the circuits involved.

Our proposal is aimed at discovering the molecular mechanisms underlying the remarkable force-sensing and responsive properties of cellular attachment to the extracellular matrix. Many proteins contribute to the intracellular machinery that links the cytoplasmic domains of the transmembrane integrin adhesion receptors to the actomyosin contractile apparatus within the cell. These integrin adhesion complexes (IACs) provide a paradigm for a distinctive class of subcellular protein complex. Rather than assembling a structure of fixed stoichiometry (e.g. ribosome, centriole) via exclusive interactions, evidence is emerging that IACs engage a dynamic set of heterogeneous interactions that evolve from IAC initiation through maturation to achieve their signaling and mechanical functions.
Thus, we hypothesize that a key feature of IACs is their ability to exchange multivalent interactions between components, so changing their composition in response to diverse inputs, including force, developmental history and location within the organism. We have selected a few pivotal components of the IACs as the focus for our project: namely talin, kindlins, the IPP sub-complex (integrin-linked-kinase (ILK), PINCH, parvin), and vinculin.
To test this hypothesis we will combine Giannone's expertise in live single protein tracking and super-resolution microscopy with Brown's expertise in Drosophila developmental genetics. First we will advance existing methods to achieve the challenging task of quantitative super-resolution imaging within IACs in living tissues. Second, we will develop new tools to image interacting proteins, study their dynamic behavior and alter the interactions. Discovering the regulation of IAC rearrangement will greatly improve our understanding not only of mechanisms mediating Integrin adhesion but also of dynamic macromolecular protein complexes.
By bringing together the contrasting approaches of the two applicants we will gain an exceptional view of how the molecular machinery at integrin adhesion sites has evolved to be able to respond diverse environments and activities within the organism. We anticipate that this will lead to an understanding of general principles directing the progressive formation of macromolecular complexes.

The X-ray free-electron laser (XFEL) promises the study of systems that cannot be crystallized and the ability to follow the evolution of structures undergoing reactions or other dynamic processes, overcoming limitations of crystallography (which requires crystals) and cryo-electron microscopy (which requires cooled samples). Both of those methods are fundamentally constrained by the problem of radiation damage, which sets a limit to the exposure that can be tolerated by the sample. The XFEL breaks this limit with very intense and brief X-ray pulses that are shorter than the time atoms can move on the atomic scale, even though the sample is ultimately vaporized. This enhanced dose tolerance has been well demonstrated by high-intensity experiments using protein nanocrystals, where diffraction patterns are collected at many thousands of times higher exposures than is possible otherwise. However, even at these extreme intensities, the diffraction signal of non-crystalline objects is low, comparable to the achievable signals of biological molecules in cryo-electron microscopy (cryo-EM).
We propose to develop radically new methods to image single uncrystallized biological molecules at atomic resolution by XFEL diffraction of nano-engineered samples. By attaching DNA origami structures to the sample we obtain stronger signal than from the molecule alone. The structural information of the sample is built up from millions of diffraction patterns from such samples, collected one at a time at the repetition rate of the XFEL. These patterns can only be fully interpreted to give a three-dimensional (3D) structure of the molecule if they are individually registered to each other in all three orientations (similar to cryo-EM). The flexibility of DNA nanotechnology will be exploited to build structures that align in a flowing jet or orient on a membrane substrate such as graphene. The unknown rotation of the object about the alignment axis will be obtained from signatures based on the designed DNA structure. In addition to boosting the diffraction signal and orienting the molecule, the known DNA origami structure provides a holographic reference to phase the aggregated diffraction intensities and give the 3D electron density map. Our general-purpose technique will be applied to obtain atomic resolution imaging of biological molecules that do not readily crystallize.

When plants and animals grow they often develop patterns, such as the spiral arrangement of leaves around a stem or the overlapping pattern of scales on a snake. Some of these patterns are controlled by genes acting to shape the cells, and these patterns have been well studied. However, many biological patterns arise simply from physical forces. These patterns depend on the chemistry of the materials that plants and animals are made of, and on the forces that arise as these materials grow. We hypothesise that a single set of rules governs this mechanical pattern formation, and that these rules will relate to how tissues grow, what they are built of, and how stiff they are. By defining and understanding these rules we will be able to explain a great deal of the diversity of living organisms.
We have chosen to study the formation of a particular type of pattern – buckling, or wrinkling, of layers of the skin. Our team comprises a plant biologist, who will study buckling of the petal surface of Hibiscus trionum, an animal biologist, who will study buckling of the skin of corn snakes, and a polymer engineer, who will model buckling in artificial systems and generate rules and predictions. The two biologists will test these predictions in their different models, and the team will work iteratively to refine the models. The two biologists will also share tools and techniques to enable them to measure the same properties of their different systems.
Our findings are poised to provide new understanding of the universal principles that apply to life, and specifically growth processes in both plants and animals. They will help evolutionary biologists to explain the great diversity of plant and animal form, and will underpin many future applications in which engineers use bioinspiration to generate new materials and structures.

Sophisticated alien-like systems in squids, octopuses, and other cephalopods capture the human imagination, and are of growing research interest. Some represent unique innovations, like dynamic camouflage, high pressure jet propulsion, and stretchable arms with tasting suckers that grip. Other features are convergent traits that are surprisingly similar, but molecularly different, from familiar biological systems in ourselves and our vertebrate cousins, including large brains, sophisticated eyes, and a muscular heart that drives a high pressure circulatory system. Parallel evolution of these complex systems in cephalopods and vertebrates is likely due to an ancient evolutionary competition to dominant as large, active swimming, visual predators in early oceans, causing both groups to engineer their own genetic, cellular, anatomical and physiological solutions to similar environmental challenges. This matchless competition profoundly shaped complexity in both lineages, and offers researchers today an extraordinary and uniquely powerful opportunity to distill basic principles and reveal novel solutions of how to make a brain, complex eyes, and a heart with sophisticated cardiovascular regulation. Here, through detailed comparisons between cephalopods vs vertebrates, together with state-of-the-art technologies, we will decipher mechanisms and uncover alternative solutions: how to design a circulatory system with rhythmic heartbeats?
To characterize, reverse engineer and control novel types of circulatory systems, powerful genetic tools will be developed. We will establish, for the first time, targeted genome editing and light-based genetic tools to control activity in the world’s smallest cephalopod - the pygmy squid Idiosepius – a novel revolutionary model for biomedicine. Second, using this transparent marine organism, we will produce a genomic portrait of the entire circulatory system at single-cell resolution. Finally, with real-time imaging technologies and sophisticated genetic controls, we will develop new ways to regulate, not one, but three cephalopod hearts and their pacemakers. As a result, our international team will transform the pygmy squid into a cephalopod ‘lab rat’, and discover fundamental principles that led to the origins of high-pressure circulatory systems, providing new materials and ideas for synthetic biology and bioengineering.

For a cell to maintain protein homeostasis (proteostasis) extensive networks of components are needed to safeguard and rapidly correct unwanted proteomic changes. The performance of these proteostasis networks may be reduced under stress and during aging, which results in misfolding of proteins, their aggregation and/or loss of functionality. Such instability of the proteome manifests in age-dependent neurodegenerative diseases, like Alzheimer’s and Parkinson’s and other medical disorders.
Currently there is a shortfall of capacity to quantitatively measure how well the networks maintaining proteostasis operate. The central objective of this project is to build a new biosensor system that can quantitatively measure how efficiently proteostasis is managed. We will probe proteostasis in space (i.e. spatially inside mammalian cells) and over time in mammalian cells as well as in the whole organism context using an animal model (the nematode) that is ideal for the study of age-dependent changes in proteostasis. Success in this central objective will enable us to measure the latent buffering capacity of the quality control networks under normal and stressed conditions. In turn this will enable us to gain insight into how cells respond dynamically to stresses, how resilient cells are to such stresses, and how quality control systems become degraded or overwhelmed in disease contexts and upon ageing.
Our team bridges four disciplines needed to bring this system to light. Hatters (Australia) brings experience in biosensor design and molecular biology. Ebbinghaus (Germany) is the co-inventor of a temperature jump microscope, which will be employed to extract in-cell kinetic and thermodynamic folding information about the biosensor that will be used to understand proteostasis efficiencies. Dickson (United States) is a computational expert in protein-chaperone interactions and will build coarse-grained models of proteostasis. Nicholas (Australia) has experience in nematode biology to implement the biosensors in the nematode to study proteostasis upon ageing.
Our specific goals are to:
1. Build a biosensor and mathematical framework that can measure proteostasis buffering capacity in living cells.
2. Define the proteostasis buffering capacity within different organelles of mammalian cells.
3. Quantitate proteostasis changes upon ageing in a nematode model.

According to the World Health Organization, about 600 million people around the world are obese. Not only does obesity affect developed countries, it is also becoming a major problem for low and middle-income countries. Obesity results from an increased accumulation of lipids within adipose tissue. Triglycerides are stored in lipid droplets, ultimately leading to adipocytes (ADs) hypertrophy, altered hormonal release and adipose inflammation. Hence, obesity contributes in a major way to the burden of diabetes and cardiovascular diseases (metabolic syndrome).
Growing evidence indicates that static stretching promotes adipogenesis, possibly relevant to sedentary lifestyle, while dynamic stretching or vibrations, as occurring for instance during exercise, have the opposite effect. Altogether, these observations suggest that mechanical force has a major impact on the ability of ADs to accumulate lipids, with differential responses to specific types of mechanical stress. ADs are characterized by a unique ability for volume expansion upon triglyceride accumulation, increasing their size by more than 30-fold with a marked enhancement in effective cell stiffness. Consequently, within adipose depots, hypertrophic ADs generate a mechanical stress transmitted to resident cells. We postulate that a positive mechanical feedback loop acts in the process of adipogenesis and influences hormonal production. Using a combination of transdisciplinary approaches, including soft matter physics, cell biology, biophysics, physiology, pharmacology and clinical observations we will investigate the molecular basis of adipose cells mechanosensitivity. Important questions need to be addressed: What are the mechanical forces at play in adipose tissue? Can we measure tension generated within adipose depots in vivo? How is mechanical stress transduced at the molecular level in adipose cells? Does mechanical stress impact hormonal production and adipose inflammation? We will investigate the functional role for candidate mechanosensors, including the mechanosensitive ion channel Piezo1, the adhesion molecules integrins/talins, as well as the nuclear protein lamin-A in adipose plasticity and function. In conclusion, we will provide novel insights into the mechanobiology of adipose tissue, with expected practical perspectives for the treatment of obesity.

The purpose of this proposal is to recreate an ancient living system, an organism that uses RNA catalysts, ribozymes, as part of its translation apparatus. We will achieve this grand goal by progressively reintroducing ribozymes into cellular metabolism, ultimately replacing protein enzymes. To this end, Hiroaki Suga will develop novel ribozymes, Flexizymes, that can charge tRNAs with amino acids. Andy Ellington will adapt Flexizymes for use in cells, and replace cognate aminoacyl-tRNA synthetases. Michael Jewett will adapt Flexizyme charging to an orthogonal ribosome that can specifically utilize Flexizymes. Both Ellington and Jewett will hand organisms containing Flexizymes and orthogonal ribosomes to Philippe Marliere for high-throughput evolutionary adaptation and optimization. Ultimately, this will result in the creation of an organism that serves as a doppelganger for ancient living systems in transition from an RNA to a protein world. This ribo-organism will be unique in that it will have two translation apparatuses operating side-by-side, one of which has the normal complement of cellular machinery, and one of which has Flexizymes, orthogonal tRNAs, an orthogonal ribosome, and a new genetic code. We will initially carry out our goals by altering the machinery for the incorporation of histidine, but eventually expand the genetic code to unnatural amino acid analogues of histidine, 1,2,4-triazole-3-alanine (T3A) and alpha-hydroxy histidine (AHH), in order to highlight potential biotechnology applications. The incorporation of these new amino acids into the genetic code, both as 21st amino acids (via suppression) and in competition with an existing amino acid, histidine (via missense incorporation), should serve as a modern experimental surrogate for the ancient establishment of the genetic code. This project is also notable for its broad interdisciplinary flavor, in that it spans from a chemist (Suga) to a biochemist (Ellington) to a bioengineer (Jewett) to an evolutionary biologist (Marliere). Each individual field touches on the other, but the overall arc traverses a much broader swath of science and technology than would otherwise be possible. The intermingling of distinct cultures is also apparent in the scope of the work, which for the first time attempts multi-scale evolutionary optimization of an entire cellular sub-system, translation.

Life involves a myriad of inter-related chemical processes, almost none of which would proceed at adequate rates without the assistance of enzymes. Enzymes are “Nature’s catalysts”, accelerating the rates of these reactions by up to ~20 orders of magnitude, thus making life as we know it possible. No consensus has yet emerged about the ultimate origin of the "catalytic power" of enzymes, with a rather wide variety of hypotheses put forward over the years. In addition, the limitations in our understanding of enzyme catalysis are highlighted by our inability to reproduce the catalytic power of the best naturally occurring enzymes in any human made catalyst (including de novo designed enzymes); as Feynman famously pointed out, "What I cannot create, I do not understand". This lack of a definitive understanding in the origins of enzyme catalysis is most likely related to the fact that natural enzymes are the complex outcome of natural selection operating over vast expanses of time in an evolutionary process that may be determined to some extent by contingency. Here, we posit that an in-depth understanding of the catalytic power of enzymes will only be possible when we have at our disposal a procedure that routinely reproduces the emergence of new functions from non-catalytic (or minimally catalytic) scaffolds in the laboratory. Therefore, during the course of this project, we will:
1) use phylogenetic analysis to reconstruct sequences of ancestral proteins from a structure having high potential to serve as a scaffold for generating novel functionalities;
2) prepare the encoded proteins in the lab and test them not just experimentally but also computationally for the biophysical and biochemical properties that confer high evolvability on a protein scaffold;
3) synthesize very large libraries of up to ten trillion (10E13) variants using highly evolvable ancestral proteins as scaffolds;
4) use ultra-high-throughput in vitro and in vivo methodologies to screen these libraries for non-natural functions;
5) use both experimental and multiscale modeling tools to characterize the resulting de novo enzymes for the biophysical, biochemical and structural features relevant for efficient catalysis;
6) use the above characterization to test different hypotheses about the evolutionary and molecular origin of enzyme catalysis.

Autophagy is a ubiquitous process of eukaryotic cell biology, which occurs by the formation and growth of the isolation membrane (IM). The IM engulfs bulk cytosol or targets such as protein aggregates, damaged organelles, and invading pathogens. The IM closes to become the autophagosome, fuses with the lysosome, and its contents are degraded. More than 40 Atg proteins are dedicated to autophagy, thus the “parts list” is known. How the autophagosome initiates, grows, and closes, using these parts is a world-class mystery. We propose to use biochemical reconstitution, cell imaging, and computational biophysics to dissect the uptake of the intracellular pathogen Salmonella (“xenophagy”) and so reveal the physical basis of autophagosome formation. In one major model, derived from yeast data, the IM nucleates from several small vesicles that then fuse into a sheet. The sheet grows by fusion of more small vesicles. In another model, derived from mammalian cell data, the IM is extruded out of a domain of the endoplasmic reticulum (ER). We propose to resolve which of these mechanisms is operative, by reconstituting autophagosome formation, and by directly imaging the process both in vitro and in cells using real-time super-resolution imaging. We will then move beyond distinguishing between these qualitative models, to a quantitative, biophysical paradigm. The arrival, departure, copy numbers, and structures of the relevant protein complexes on and off membranes will be determined in vitro and in vivo. Changes in membrane shape will be correlated with these parameters. These will be input to a computational model accounting for membrane physical properties and protein structures. The complexity of this system, with 10s-100s of copies of more than 40 different proteins, operating on a time scale of minutes and a length scale of two microns, makes this one of the most complex systems to be tackled with such biochemical and biophysical detail.

This project will investigate locomotion control in undulatory animals and transitions between different environmental media. It will test the idea that a single control principle could explain different modes of locomotion in vertebrate and invertebrate animals for different morphologies in different environmental media (water and ground). The control principle is based on “sensory synchronization” of local neural oscillators. It merges ideas from central pattern generators and from sensory-driven locomotor models. We postulate that flexible motor patterns for body-limb coordination during swimming, crawling and walking can be obtained in a distributed network of neural oscillators that rely to a large extent on (multimodal) sensory feedback signals for synchronization. In other words, we postulate that the synchronization between oscillations in body and limbs, and hence the generation of gaits, is due to mechanical interactions of the body with the environment and the resulting sensory signals more than to direct neuronal (or central) coupling between the involved neuronal oscillators. We also postulate that many observed features of various gaits are due to changes in the environment rather than to changes in the descending commands.
This idea and related predictions will be tested by investigating Polypterus (a walking fish), salamander, and centipede locomotion. These three species represent a diversity of life that has overcome the problems associated with neuro-control in amphibious environments. Our research tools combine animal locomotion studies, neuromechanical simulations, and robotic experiments. The neuromechanical simulations and the robots will play an essential role in decoding the complex interplay between central pattern generators, sensory feedback, the musculoskeletal system, and the different environments. The interdisciplinary approach will allow us to investigate whether the same control principle could not only facilitate adaptations to growth, lesions, perturbations, and different environments during the lifetime of the animal, but also to evolutionary adaptations (e.g. changes of ecological niches and of morphologies) in particular the transition from aquatic to terrestrial environments in vertebrates and invertebrates, a key step in evolution.

To understand how cellular machineries work, we typically rely on reconstituted systems that often do not represent the complexity existing in vivo. We lack innovative methods to describe protein-protein interactions at high-resolution, specially the very transient ones, in their physiological environment. Chromatin is a good example of a system whose complexity cannot be fully reconstituted in vitro. Indeed chromatin is regulated by hundreds of chromatin remodelling enzymes and hundreds of possible combinations of histone post-translational modifications (PTMs) and variants. This complexity cannot be fully reconstituted in vitro.
We propose a novel combination of synthetic biology, mass spectrometry and high-resolution imaging to define the molecular details of how proteins function on chromatin in their physiological environment at high resolution. The challenge is to use photochemical traps installed by genetic code expansion in histones of living cells to “freeze” interactions of proteins bound to chromatin, especially the very transient ones that could be disrupted or missed by conventional purification or bulk chemical cross-linking. The trapped protein-chromatin complexes will be analysed by cryo-electron microscopy. By mass spectrometry we will map the interactions between remodelers and histones in vivo and we will quantitatively describe all chromatin PTMs associated to specific remodelers. This way, we will be able to analyse the spatio-temporal activity of chromatin-bound complexes at high-resolution at specific time points or upon specific stimuli.

The spectacular manoeuvres of flocking birds and schooling fish are among the most dramatic and mysterious sights in the natural world. How can hundreds or thousands of individuals coordinate their movements so perfectly, behaving almost as a single super-organism? The answer to this puzzle began to be uncovered through mathematical models showing that collective order can emerge as a by-product if all individuals within a group follow simple rules to align with and stay close to their neighbours. However, unlike the simulated agents in these models, real animals are not identical, and can differ both in their individual characteristics and in their relationships with one another. A group’s composition is therefore likely to affect its overall structure and cohesion as well as its ability to reach consensus decisions when responding to the environment. Understanding these effects has important implications, from determining how animal groups respond to threats, to mitigating the impacts of crop pests, managing crowd safety and developing intelligent systems in robotics. We will use mixed-species flocks of rooks and jackdaws (birds of the crow family, or corvids) to understand the effects of group composition on collective behaviour in nature. Combining field experiments with cutting-edge imaging and computational techniques, we will produce 3D reconstructions of the movements of every bird within flocks of varying composition and examine how a flock’s composition affects its structure and movements, and its responsiveness when avoiding or mobbing predators. Are more homogeneous groups better able to respond as a coherent unit, or does diversity enhance group responses as in human social institutions? Our 3D reconstructions will also allow us to determine the fine-scale internal structure of flocks. Do corvid flocks, like human crowds, contain sub-groups, reflecting flock members' social preferences? Finally, we will use our data to understand how individuals' flight decisions are influenced by who their neighbours are. By building mathematical models based on these measurements and testing the models using flocks of robot-controlled drones, we can find out how local interactions and social preferences among neighbours generate both internal sub-structure and collective order in complex societies.