Topic: Assembly

Defining profilin function in mammalian actin dynamics and cell behaviour

Klemens Rottner (Helmholtz Centre for Infection Research, Braunschweig) presents evidence that profilin acts as a master regulator of actin filament dynamics essential for cell migration and growth, controlling both formin- and Arp2/3 complex-dependent actin assembly pathways.

Astrocytes: From Metabolism to Cognition

Different brain cell types exhibit distinct metabolic signatures that link energy economy to cellular function. Astrocytes and neurons, for instance, diverge dramatically in their reliance on glycolysis versus oxidative phosphorylation, underscoring that metabolic fuel efficiency is not uniform across cell types. A key factor shaping this divergence is the structural organization of the mitochondrial respiratory chain into supercomplexes. Specifically, complexes I (CI) and III (CIII) form a CI–CIII supercomplex, but the degree of this assembly varies by cell type. In neurons, CI is predominantly integrated into supercomplexes, resulting in highly efficient mitochondrial respiration and minimal reactive oxygen species (ROS) generation. Conversely, in astrocytes, a larger fraction of CI remains unassembled, freely existing apart from CIII, leading to reduced respiratory efficiency and elevated mitochondrial ROS production. Despite this apparent inefficiency, astrocytes boast a highly adaptable metabolism capable of responding to diverse stressors. Their looser CI–CIII organization allows for flexible ROS signaling, which activates antioxidant programs via transcription factors like Nrf2. This modular architecture enables astrocytes not only to balance energy production but also to support neuronal health and influence complex organismal behaviors.

“Open Raman Microscopy (ORM): A modular Raman spectroscopy setup with an open-source controller”

Raman spectroscopy is a powerful technique for identifying chemical species by probing their vibrational energy levels, offering exceptional specificity with a relatively simple setup involving a laser source, spectrometer, and microscope/probe. However, the high cost of Raman systems lacking modularity often limits exploratory research hindering broader adoption. To address the need for an affordable, modular microscopy platform for multimodal imaging, we present a customizable confocal Raman spectroscopy setup alongside an open-source acquisition software, ORM (Open Raman Microscopy) Controller, developed in Python. This solution bridges the gap between expensive commercial systems and complex, custom-built setups used by specialist research groups. In this presentation, we will cover the components of the setup, the design rationale, assembly methods, limitations, and its modular potential for expanding functionality. Additionally, we will demonstrate ORM’s capabilities for instrument control, 2D and 3D Raman mapping, region-of-interest selection, and its adaptability to various instrument configurations. We will conclude by showcasing practical applications of this setup across different research fields.

Investigating activity-dependent processes during cortical neuronal assembly in development and disease

Precise spatio-temporal spike patterns in cortex and model

The cell assembly hypothesis postulates that groups of coordinated neurons form the basis of information processing. Here, we test this hypothesis by analyzing massively parallel spiking activity recorded in monkey motor cortex during a reach-to-grasp experiment for the presence of significant ms-precise spatio-temporal spike patterns (STPs). For this purpose, the parallel spike trains were analyzed for STPs by the SPADE method (Stella et al, 2019, Biosystems), which detects, counts and evaluates spike patterns for their significance by the use of surrogates (Stella et al, 2022 eNeuro). As a result we find STPs in 19/20 data sets (each of 15min) from two monkeys, but only a small fraction of the recorded neurons are involved in STPs. To consider the different behavioral states during the task, we analyzed the data in a quasi time-resolved analysis by dividing the data into behaviorally relevant time epochs. The STPs that occur in the various epochs are specific to behavioral context - in terms of neurons involved and temporal lags between the spikes of the STP. Furthermore we find, that the STPs often share individual neurons across epochs. Since we interprete the occurrence of a particular STP as the signature of a particular active cell assembly, our interpretation is that the neurons multiplex their cell assembly membership. In a related study, we model these findings by networks with embedded synfire chains (Kleinjohann et al, 2022, bioRxiv 2022.08.02.502431).

Versatile treadmill system for measuring locomotion and neural activity in head-fixed mice

Here, we present a protocol for using a versatile treadmill system to measure locomotion and neural activity at high temporal resolution in head-fixed mice. We first describe the assembly of the treadmill system. We then detail surgical implantation of the headplate on the mouse skull, followed by habituation of mice to locomotion on the treadmill system. The system is compact, movable, and simple to synchronize with other data streams, making it ideal for monitoring brain activity in diverse behavioral frameworks. https://dx.doi.org/10.1016/j.xpro.2022.101701

Magnetic Handshake Materials

Biological materials gain complexity from the programmable nature of their components. To manufacture materials with comparable complexity synthetically, we need to create building blocks with low crosstalk so that they only bind to their desired partners. Canonically, these building blocks are made using DNA strands or proteins to achieve specificity. Here we propose a new materials platform, termed Magnetic Handshake Materials, in which we program interactions through designing magnetic dipole patterns. This is a completely synthetic platform, enabled by magnetic printing technology, which is easier to both model theoretically and control experimentally. In this seminar, I will give an overview of the development of the Magnetic Handshake Materials platform, ranging from interaction, assembly to function design.

Investigating activity-dependent processes in cerebral cortex development and disease

The cerebral cortex contains an extraordinary diversity of excitatory projection neuron (PN) and inhibitory interneurons (IN), wired together to form complex circuits. Spatiotemporally coordinated execution of intrinsic molecular programs by PNs and INs and activity-dependent processes, contribute to cortical development and cortical microcircuits formation. Alterations of these delicate processes have often been associated to neurological/neurodevelopmental disorders. However, despite the groundbreaking discovery that spontaneous activity in the embryonic brain can shape regional identities of distinct cortical territories, it is still unclear whether this early activity contributes to define subtype-specific neuronal fate as well as circuit assembly. In this study, we combined in utero genetic perturbations via CRISPR/Cas9 system and pharmacological inhibition of selected ion channels with RNA-sequencing and live imaging technologies to identify the activity-regulated processes controlling the development of different cortical PN classes, their wiring and the acquisition of subtype specific features. Moreover, we generated human induced pluripotent stem cells (iPSCs) form patients affected by a severe, rare and untreatable form of developmental epileptic encephalopathy. By differentiating cortical organoids form patient-derived iPSCs we create human models of early electrical alterations for studying molecular, structural and functional consequences of the genetic mutations during cortical development. Our ultimate goal is to define the activity-conditioned processes that physiologically occur during the development of cortical circuits, to identify novel therapeutical paths to address the pathological consequences of neonatal epilepsies.

Membrane mechanics meet minimal manifolds

Changes in the geometry and topology of self-assembled membranes underlie diverse processes across cellular biology and engineering. Similar to lipid bilayers, monolayer colloidal membranes studied by the Sharma (IISc Bangalore) and Dogic (UCSB) Labs have in-plane fluid-like dynamics and out-of-plane bending elasticity, but their open edges and micron length scale provide a tractable system to study the equilibrium energetics and dynamic pathways of membrane assembly and reconfiguration. First, we discuss how doping colloidal membranes with short miscible rods transforms disk-shaped membranes into saddle-shaped minimal surfaces with complex edge structures. Theoretical modeling demonstrates that their formation is driven by increasing positive Gaussian modulus, which in turn is controlled by the fraction of short rods. Further coalescence of saddle-shaped surfaces leads to exotic topologically distinct structures, including shapes similar to catenoids, tri-noids, four-noids, and higher order structures. We then mathematically explore the mechanics of these catenoid-like structures subject to an external axial force and elucidate their intimate connection to two problems whose solutions date back to Euler: the shape of an area-minimizing soap film and the buckling of a slender rod under compression. A perturbation theory argument directly relates the tensions of membranes to the stability properties of minimal surfaces. We also investigate the effects of including a Gaussian curvature modulus, which, for small enough membranes, causes the axial force to diverge as the ring separation approaches its maximal value.

How do protein-RNA condensates form and contribute to disease?

In recent years, it has become clear that intrinsically disordered regions (IDRs) of RBPs, and the structure of RNAs, often contribute to the condensation of RNPs. To understand the transcriptomic features of such RNP condensates, we’ve used an improved individual nucleotide resolution CLIP protocol (iiCLIP), which produces highly sensitive and specific data, and thus enables quantitative comparisons of interactions across conditions (Lee et al., 2021). This showed how the IDR-dependent condensation properties of TDP-43 specify its RNA binding and regulatory repertoire (Hallegger et al., 2021). Moreover, we developed software for discovery and visualisation of RNA binding motifs that uncovered common binding patterns of RBPs on long multivalent RNA regions that are composed of dispersed motif clusters (Kuret et al, 2021). Finally, we used hybrid iCLIP (hiCLIP) to characterise the RNA structures mediating the assembly of Staufen RNPs across mammalian brain development, which demonstrated the roles of long-range RNA duplexes in the compaction of long 3’UTRs. I will present how the combined analysis of the characteristics of IDRs in RBPs, multivalent RNA regions and RNA structures is required to understand the formation and functions of RNP condensates, and how they change in diseases.

Extrinsic control and autonomous computation in the hippocampal CA1 circuit

In understanding circuit operations, a key issue is the extent to which neuronal spiking reflects local computation or responses to upstream inputs. Because pyramidal cells in CA1 do not have local recurrent projections, it is currently assumed that firing in CA1 is inherited from its inputs – thus, entorhinal inputs provide communication with the rest of the neocortex and the outside world, whereas CA3 inputs provide internal and past memory representations. Several studies have attempted to prove this hypothesis, by lesioning or silencing either area CA3 or the entorhinal cortex and examining the effect of firing on CA1 pyramidal cells. Despite the intense and careful work in this research area, the magnitudes and types of the reported physiological impairments vary widely across experiments. At least part of the existing variability and conflicts is due to the different behavioral paradigms, designs and evaluation methods used by different investigators. Simultaneous manipulations in the same animal or even separate manipulations of the different inputs to the hippocampal circuits in the same experiment are rare. To address these issues, I used optogenetic silencing of unilateral and bilateral mEC, of the local CA1 region, and performed bilateral pharmacogenetic silencing of the entire CA3 region. I combined this with high spatial resolution recording of local field potentials (LFP) in the CA1-dentate axis and simultaneously collected firing pattern data from thousands of single neurons. Each experimental animal had up to two of these manipulations being performed simultaneously. Silencing the medial entorhinal (mEC) largely abolished extracellular theta and gamma currents in CA1, without affecting firing rates. In contrast, CA3 and local CA1 silencing strongly decreased firing of CA1 neurons without affecting theta currents. Each perturbation reconfigured the CA1 spatial map. Yet, the ability of the CA1 circuit to support place field activity persisted, maintaining the same fraction of spatially tuned place fields, and reliable assembly expression as in the intact mouse. Thus, the CA1 network can maintain autonomous computation to support coordinated place cell assemblies without reliance on its inputs, yet these inputs can effectively reconfigure and assist in maintaining stability of the CA1 map.

Building a Simple and Versatile Illumination System for Optogenetic Experiments

Controlling biological processes using light has increased the accuracy and speed with which researchers can manipulate many biological processes. Optical control allows for an unprecedented ability to dissect function and holds the potential for enabling novel genetic therapies. However, optogenetic experiments require adequate light sources with spatial, temporal, or intensity control, often a bottleneck for researchers. Here we detail how to build a low-cost and versatile LED illumination system that is easily customizable for different available optogenetic tools. This system is configurable for manual or computer control with adjustable LED intensity. We provide an illustrated step-by-step guide for building the circuit, making it computer-controlled, and constructing the LEDs. To facilitate the assembly of this device, we also discuss some basic soldering techniques and explain the circuitry used to control the LEDs. Using our open-source user interface, users can automate precise timing and pulsing of light on a personal computer (PC) or an inexpensive tablet. This automation makes the system useful for experiments that use LEDs to control genes, signaling pathways, and other cellular activities that span large time scales. For this protocol, no prior expertise in electronics is required to build all the parts needed or to use the illumination system to perform optogenetic experiments.

Cell assembly activation coordinated by rhythmic oscillation in the prefrontal-ventral striatum-hippocampal network

Network mechanisms underlying representational drift in area CA1 of hippocampus

Recent chronic imaging experiments in mice have revealed that the hippocampal code exhibits non-trivial turnover dynamics over long time scales. Specifically, the subset of cells which are active on any given session in a familiar environment changes over the course of days and weeks. While some cells transition into or out of the code after a few sessions, others are stable over the entire experiment. The mechanisms underlying this turnover are unknown. Here we show that the statistics of turnover are consistent with a model in which non-spatial inputs to CA1 pyramidal cells readily undergo plasticity, while spatially tuned inputs are largely stable over time. The heterogeneity in stability across the cell assembly, as well as the decrease in correlation of the population vector of activity over time, are both quantitatively fit by a simple model with Gaussian input statistics. In fact, such input statistics emerge naturally in a network of spiking neurons operating in the fluctuation-driven regime. This correspondence allows one to map the parameters of a large-scale spiking network model of CA1 onto the simple statistical model, and thereby fit the experimental data quantitatively. Importantly, we show that the observed drift is entirely consistent with random, ongoing synaptic turnover. This synaptic turnover is, in turn, consistent with Hebbian plasticity related to continuous learning in a fast memory system.

Molecular recognition and the assembly of feature-selective retinal circuits

Towards a Theory of Microbial Ecosystems

A major unresolved question in microbiome research is whether the complex ecological patterns observed in surveys of natural communities can be explained and predicted by fundamental, quantitative principles. Bridging theory and experiment is hampered by the multiplicity of ecological processes that simultaneously affect community assembly and a lack of theoretical tools for modeling diverse ecosystems. Here, I will present a simple ecological model of microbial communities that reproduces large-scale ecological patterns observed across multiple natural and experimental settings including compositional gradients, clustering by environment, diversity/harshness correlations, and nestedness. Surprisingly, our model works despite having a “random metabolisms” and “random consumer preferences”. This raises the natural of question of why random ecosystems can describe real-world experimental data. In the second, more theoretical part of the talk, I will answer this question by showing that when a community becomes diverse enough, it will always self-organize into a stable state whose properties are well captured by a “typical random ecosystems”.

Mechano-adaptation in a large protein complex

Macromolecular protein complexes perform essential biological functions across life forms. A fundamental, though yet unsolved question in biology is how the function of such complexes is regulated by intracellular or extracellular signals. For instance, we have little understanding of how forces affect multi-protein machines whose function is often mechanical in nature. We address this question by studying the bacterial flagellar motor, a large complex that powers swimming motility in many bacteria. This rotary motor autonomously adapts to changes in mechanical load by adding or removing force-generating ‘stator’ units that power rotation. In the bacterium Escherichia coli, up to 11 units drive the motor at high load while all the units are released at low load. We manipulate motor load using electrorotation, a technique in which a rapidly rotating electric field applies an external torque on the motor. This allows us to change motor load at will and measure the resulting stator dynamics at single-unit resolution. We found that the force generated by the stator units controls their unbinding, forming a feedback loop that leads to autoregulation of the assembly. We complemented our experiments with theoretical models that provide insight into the underlying molecular interactions. Torque-dependent remodeling takes place within seconds, making it a highly responsive control mechanism, one that is mediated by the mechano-chemical tuning of protein interactions.

Nonequilibrium self-assembly and time-irreversibility in living systems

Far-from-equilibrium processes constantly dissipate energy while converting a free-energy source to another form of energy. Living systems, for example, rely on an orchestra of molecular motors that consume chemical fuel to produce mechanical work. In this talk, I will describe two features of life, namely, time-irreversibility, and nonequilibrium self-assembly. Time irreversibility is the hallmark of nonequilibrium dissipative processes. Detecting dissipation is essential for our basic understanding of the underlying physical mechanism, however, it remains a challenge in the absence of observable directed motion, flows, or fluxes. Additional difficulty arises in complex systems where many internal degrees of freedom are inaccessible to an external observer. I will introduce a novel approach to detect time irreversibility and estimate the entropy production from time-series measurements, even in the absence of observable currents. This method can be implemented in scenarios where only partial information is available and thus provides a new tool for studying nonequilibrium phenomena. Further, I will explore the added benefits achieved by nonequilibrium driving for self-assembly, identify distinctive collective phenomena that emerge in a nonequilibrium self-assembly setting, and demonstrate the interplay between the assembly speed, kinetic stability, and relative population of dynamical attractors.

Edge Computing using Spiking Neural Networks

Deep learning has made tremendous progress in the last year but it's high computational and memory requirements impose challenges in using deep learning on edge devices. There has been some progress in lowering memory requirements of deep neural networks (for instance, use of half-precision) but there has been minimal effort in developing alternative efficient computational paradigms. Inspired by the brain, Spiking Neural Networks (SNN) provide an energy-efficient alternative to conventional rate-based neural networks. However, SNN architectures that employ the traditional feedforward and feedback pass do not fully exploit the asynchronous event-based processing paradigm of SNNs. In the first part of my talk, I will present my work on predictive coding which offers a fundamentally different approach to developing neural networks that are particularly suitable for event-based processing. In the second part of my talk, I will present our work on development of approaches for SNNs that target specific problems like low response latency and continual learning. References Dora, S., Bohte, S. M., & Pennartz, C. (2021). Deep Gated Hebbian Predictive Coding Accounts for Emergence of Complex Neural Response Properties Along the Visual Cortical Hierarchy. Frontiers in Computational Neuroscience, 65. Saranirad, V., McGinnity, T. M., Dora, S., & Coyle, D. (2021, July). DoB-SNN: A New Neuron Assembly-Inspired Spiking Neural Network for Pattern Classification. In 2021 International Joint Conference on Neural Networks (IJCNN) (pp. 1-6). IEEE. Machingal, P., Thousif, M., Dora, S., Sundaram, S., Meng, Q. (2021). A Cross Entropy Loss for Spiking Neural Networks. Expert Systems with Applications (under review).

Tutorial: Cell mimics to study active movements and deformations by actin assembly

Internal structure of honey bee swarms for mechanical stability and division of labor

The western honey bee (Apis mellifera) is a domesticated pollinator famous for living in highly social colonies. In the spring, thousands of worker bees and a queen fly from their hive in search of a new home. They self-assemble into a swarm that hangs from a tree branch for several days. We reconstruct the non-isotropic arrangement of worker bees inside swarms made up of 3000 - 8000 bees using x-ray computed tomography. Some bees are stationary and hang from the attachment board or link their bodies into hanging chains to support the swarm structure. The remaining bees use the chains as pathways to walk around the swarm, potentially to feed the queen or communicate with one another. The top layers of bees bear more weight per bee than the remainder of the swarm, suggesting that bees are optimizing for additional factors besides weight distribution. Despite not having a clear leader, honey bees are able to organize into a swarm that protects the queen and remains stable until scout bees locate a new hive.

Making memories in mice

Understanding how the brain uses information is a fundamental goal of neuroscience. Several human disorders (ranging from autism spectrum disorder to PTSD to Alzheimer’s disease) may stem from disrupted information processing. Therefore, this basic knowledge is not only critical for understanding normal brain function, but also vital for the development of new treatment strategies for these disorders. Memory may be defined as the retention over time of internal representations gained through experience, and the capacity to reconstruct these representations at later times. Long-lasting physical brain changes (‘engrams’) are thought to encode these internal representations. The concept of a physical memory trace likely originated in ancient Greece, although it wasn’t until 1904 that Richard Semon first coined the term ‘engram’. Despite its long history, finding a specific engram has been challenging, likely because an engram is encoded at multiple levels (epigenetic, synaptic, cell assembly). My lab is interested in understanding how specific neurons are recruited or allocated to an engram, and how neuronal membership in an engram may change over time or with new experience. Here I will describe both older and new unpublished data in our efforts to understand memories in mice.

Frustrated Self-Assembly of Non-Euclidean Crystals of Nanoparticles

Self-organized complex structures in nature, e.g., viral capsids, hierarchical biopolymers, and bacterial flagella, offer efficiency, adaptability, robustness, and multi-functionality. Can we program the self-assembly of three-dimensional (3D) complex structures using simple building blocks, and reach similar or higher level of sophistication in engineered materials? Here we present an analytic theory for the self-assembly of polyhedral nanoparticles (NPs) based on their crystal structures in non-Euclidean space. We show that the unavoidable geometrical frustration of these particle shapes, combined with competing attractive and repulsive interparticle interactions, lead to controllable self-assembly of structures of complex order. Applying this theory to tetrahedral NPs, we find high-yield and enantiopure self-assembly of helicoidal ribbons, exhibiting qualitative agreement with experimental observations. We expect that this theory will offer a general framework for the self-assembly of simple polyhedral building blocks into rich complex morphologies with new material capabilities such as tunable optical activity, essential for multiple emerging technologies.

Sonic hedgehog signaling: from neurons to astrocytes during cortical circuit assembly

How the immune system shapes synaptic functions

The synapse is the core component of the nervous system and synapse formation is the critical step in the assembly of neuronal circuits. The assembly and maturation of synapses requires the contribution of secreted and membrane-associated proteins, with neuronal activity playing crucial roles in regulating synaptic strength, neuronal membrane properties, and neural circuit refinement. The molecular mechanisms of synapse assembly and refinement have been so far largely examined on a gene-by-gene basis and with a perspective fully centered on neuronal cells. However, in the last years, the involvement of non-neuronal cells has emerged. Among these, microglia, the resident immune cells of the central nervous system, have been shown to play a key role in synapse formation and elimination. Contacts of microglia with dendrites in the somatosensory cortex were found to induce filopodia and dendritic spines via Ca2+ and actin-dependent processes, while microglia-derived BDNF was shown to promote learning-dependent synapse formation. Microglia is also recognized to have a central role in the widespread elimination (or pruning) of exuberant synaptic connections during development. Clarifying the processes by which microglia control synapse homeostasis is essential to advance our current understanding of brain functions. Clear answers to these questions will have important implications for our understanding of brain diseases, as the fact that many psychiatric and neurological disorders are synaptopathies (i.e. diseases of the synapse) is now widely recognized. In the last years, my group has identified TREM2, an innate immune receptor with phagocytic and antiinflammatory properties expressed in brain exclusively by microglia, as essential for microglia-mediated synaptic refinement during the early stages of brain development. The talk will describe the role of TREM2 in synapse elimination and introduce the molecular actors involved. I will also describe additional pathways by which the immune system may affect the formation and homeostasis of synaptic contacts.

Acoustically Levitated Granular Matter

Granular matter can serve as a prototype for exploring the rich physics of many-body systems driven far from equilibrium. This talk will outline a new direction for granular physics with macroscopic particles, where acoustic levitation compensates the forces due to gravity and eliminates frictional interactions with supporting surfaces in order to focus on particle interactions. Levitating small particles by intense ultrasound fields in air makes it possible to manipulate and control their positions and assemble them into larger aggregates. The small air viscosity implies that the regime of underdamped dynamics can be explored, where inertial effects are important, in contrast to typical colloids in a liquid, where inertia can be neglected. Sound scattered off individual, levitated solid particles gives rise to controllable attractive forces with neighboring particles. I will discuss some of the key concepts underlying acoustic levitation, describe how detuning an acoustic cavity can introduce active fluctuations that control the assembly statistics of small levitated particles clusters, and give examples of how interactions between neighboring levitated objects can be controlled by their shape.

Magic numbers in protein phase transitions

Biologists have recently come to appreciate that eukaryotic cells are home to a multiplicity of non-membrane bound compartments, many of which form and dissolve as needed for the cell to function. These dynamical “condensates” enable many central cellular functions – from ribosome assembly, to RNA regulation and storage, to signaling and metabolism. While it is clear that these compartments represent a type of separated phase, what controls their formation, how specific biological components are included or excluded, and how these structures influence physiological and biochemical processes remain largely mysterious. I will discuss recent experiments on phase separated condensates both in vitro and in vivo, and will present theoretical results that highlight a novel “magic number” effect relevant to the formation and control of two-component phase separated condensates.

Assembly of the neocortex

The symposium will start with Prof Song-Hai Shi who will present “Assembly of the neocortex”. Then, Dr Lynette Lim will talk about “Shared and Unique Developmental Trajectories of Cortical Inhibitory Neurons”. Dr Alfredo Molina will deal with the “Tuneable progenitor cells to build the cerebral cortex”, and Prof Tomasz Nowakowski will present “Charting the molecular 'protomap' of the human cerebral cortex using single cell genomic”.

Non-equilibrium molecular assembly in reshaping and cutting cells

A key challenge in modern soft matter is to identify the principles that govern the organisation and functionality in non-equilibrium systems. Current research efforts largely focus on non-equilibrium processes that occur either at the single-molecule scale (e.g. protein and DNA conformations under driving forces), or at the scale of whole tissues, organisms, and active colloidal and microscopic objects. However, the range of the scales in-between — from molecules to large-scaled molecular assemblies that consume energy and perform work — remains under-explored. This is, nevertheless, the scale that is crucial for the function of a living cell, where molecular self-assembly driven far from equilibrium produces mechanical work needed for cell reshaping, transport, motility, division, and healing. Today I will discuss physical modelling of active elastic filaments, called ESCRT-III filaments, that dynamically assemble and disassemble on cell membranes. This dynamic assembly changes the filaments’ shape and mechanical properties and leads to the remodelling and cutting of cells. I will present a range of experimental comparisons of our simulation results: from ESCRT-III-driven trafficking in eukaryotes to division of evolutionary simple archaeal cells.

Synthetic Structural Biology: Exploiting viral assembly principles as an anti-viral strategy

Cortical interneuron wiring in health and disease

The establishment of synaptic connections is essential for normal brain function, yet the molecular mechanisms responsible for the precise connectivity of specific neural circuits remain largely unknown. Previous work has shown that the assembly of cortical circuits requires specific functions of molecular signalling complexes at different classes of synapses. In this talk, I will describe the molecular logic through which specific pyramidal cell-interneuron circuits are established in the cerebral cortex of the mouse, and how alterations in some of these connectivity motifs might be liked to disease.

Physics of virus assembly

The assembly of a functional neocortex

“LIM Domain Proteins in Cell Mechanotransduction”

My lab studies the design principles of cytoskeletal materials the drive cellular morphogenesis, with a focus on contractile machinery in adherent cells. In addition to force generation, a key feature of these materials are distributed force sensors which allow for rapid assembly, adaptation, repair and disintegration. Here I will discuss our recent identification of 18 proteins from the zyxin, paxillin, Tes and Enigma families with mechanosensitive LIM (Lin11, Isl- 1 & Mec-3) domains. We developed a screen to assess the force-dependent localization of LIM domain-containing region (LCR) from ~30 genes to the actin cytoskeleton and identified features common to their force-sensitive localization. Through in vitro reconstitution, we found that the LCR binds directly to mechanically stressed actin filaments. Moreover, the LCR from the fission yeast protein paxillin-like 1 is also mechanosensitive, suggesting force-sensitivity is highly conserved. We speculate that the evolutionary emergence of contractile F-actin machinery coincided with, or required, proteins that could report on the stresses present there to maintain homeostasis of actively stressed networks.

Mechanical Homeostasis of the Actin Cytoskeleton

My lab studies the design principles of cytoskeletal materials the drive cellular morphogenesis, with a focus on contractile machinery in adherent cells. In addition to force generation, a key feature of these materials are distributed force sensors which allow for rapid assembly, adaptation, repair and disintegration. Here I will describe how optogenetic control of RhoA GTPase is a powerful and versatile force spectroscopy approach of cytoskeletal assemblies and its recent use to probe repair response in actomyosin stress fibers. I will also describe our recent identification of 18 proteins from the zyxin, paxillin, Tes and Enigma families with mechanosensitive LIM (Lin11, Isl- 1 & Mec-3) domains that bind exclusively to mechanically stressed actin filaments. Our results suggest that the evolutionary emergence of contractile F-actin machinery coincided with, or required, proteins that could report on the stresses present there to maintain homeostasis of actively stressed networks.

Physiological importance of phase separation: a case study in synapse formation

Synapse formation during neuronal development is critical to establish neural circuits and a nervous system1. Every presynapse builds a core active zone structure where ion channels are clustered and synaptic vesicles are released2. While the composition of active zones is well characterized2,3, how active zone proteins assemble together and recruit synaptic release machinery during development is not clear. Here, we find core active zone scaffold proteins SYD-2/Liprin-α and ELKS-1 phase separate during an early stage of synapse development, and later mature into a solid structure. We directly test the in vivo function of phase separation with mutants specifically lacking this activity. These mutant SYD-2 and ELKS-1 proteins remain enriched at synapses, but are defective in active zone assembly and synapse function. The defects are rescued with the introduction of a phase separation motif from an unrelated protein. In vitro, we reconstitute the SYD-2 and ELKS-1 liquid phase scaffold and find it is competent to bind and incorporate downstream active zone components. The fluidity of SYD-2 and ELKS-1 condensates is critical for efficient mixing and incorporation of active zone components. These data reveal that a developmental liquid phase of scaffold molecules is essential for synaptic active zone assembly before maturation into a stable final structure.

Neural Stem Cell Lineage Progression in Developing Cerebral Cortex

The concerted production of the correct number and diversity of neurons and glia by neural stem cells is essential for intricate neural circuit assembly. In the developing cerebral cortex, radial glia progenitors (RGPs) are responsible for producing all neocortical neurons and certain glia lineages. We recently performed a clonal analysis by exploiting the genetic MADM (Mosaic Analysis with Double Markers) technology and discovered a high degree of non-stochasticity and thus deterministic mode of RGP behaviour. However, the cellular and molecular mechanisms controlling RGP lineage progression remain unknown. To this end we use quantitative MADM-based genetic paradigms at single cell resolution to define the cell-autonomous functions of signaling pathways controlling cortical neuron/glia genesis and postnatal stem cell behaviour in health and disease. Here I will outline our current understanding of the mechanistic framework instructing neural stem cell lineage progression and discuss new data about the role of genomic imprinting – an epigenetic phenomenon - in cortical development.