Program and Abstracts

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Complex biological membrane models: of bending and interfacial catalysis

Lipid bilayer membranes participate in complex membrane trafficking phenomena that require bending. However, despite decades of research into the biophysical basis of the mechanisms behind membrane bending phenomena, we are only beginning to understand their complexity. Our lab has been contributing to the development of experimental techniques to study mechanical consequences of membrane asymmetry generated by peripheral protein binding, as well as by processes that do not require proteins. We will share our recent insight into some of these phenomena.

In a second project we have designed solid supported membrane systems in combination with micro-fluidics and fluorescence readout to characterize the complex reaction kinetics of phosphoinositide (PI) lipid phosphorylation (through the kinase PI3K) and de-phosphorylation (through the phosphatase PTEN). Significant findings have included the evaluation of contributions from allosteric as well as membrane recruitment-based mechanisms to autocatalysis in the hydrolysis of the PI lipid PI(3,4,5)P3 through PTEN, and the finding and characterization of a bistable switch operated by PI3K/PTEN at the membrane.

Proteins: sequences and physics

Proteins and multi-protein complexes play crucial roles in all cellular processes, acting as enzymes, motors, receptors, regulators, and more. The function of a protein is encoded in its amino-acid sequence, and the recent explosion of available sequences has inspired data-driven approaches to discover the principles of protein operation. At the root of these new approaches is the observation that amino-acid residues which possess related functional roles often evolve in a correlated way. In particular, residues that are in contact in the folded protein are correlated.

Methods inspired by statistical physics have enabled successful inference of the three-dimensional structure of proteins and multi-protein complexes, starting from sequences. Recently, we developed related methods to identify which proteins are specific interaction partners, starting from sequence data alone.

Beyond the constraints imposed by folding, sequence alignments have also revealed “sectors” of collectively coevolving amino acids in several protein families. We show that selection acting on any relevant physical property of a protein, e.g. the elastic energy of an important conformational change, can give rise to such a sector. We study the signature of these physical sectors in the covariance matrix of the selected sequences.

Broken detailed balance in living systems

Measuring and quantifying non-equilibrium dynamics is a major challenge in living systems, due to their many-body nature and the limited number of variables accessible in an experiment. We present a method to identify non-equilibrium dynamics based on broken detailed balance. Using this approach, we study active dynamics in flagella, primary cilia, and cytoskeletal networks. What information concerning the system’s non-equilibrium state can be extracted from detecting broken detailed balance? To answer this question, we develop a general, yet simple model of soft elastic networks with a heterogeneous distribution of activities, representing internal enzymatic force generation. With this model, we determine the scaling behavior of non-equilibrium dynamics, including the entropy production rate. Our results provide insight into how internal driving by enzymatic activity generates non-equilibrium dynamics on different length scales in biological assemblies.

Mechanical Structure function properties of subcellular and extracellular networks

Living cells and tissues are highly mechanically sensitive and active. Mechanical stimuli influence the shape, motility, and functions of cells, modulate the behavior of tissues, and play a key role in several diseases. In this talk I will discuss the structure function properties of biopolymer networks in cells and tissues that arise due to the interplay of their mechanical and statistical mechanical properties. I will start with articular cartilage (AC), a soft tissue mainly made of network like extra-cellular matrix. AC covers the ends of long mammalian bones, serving to minimize friction and distribute mechanical loads in joints. It is a remarkable tissue: it can support loads exceeding ten times our body weight and bear 60+ years of daily mechanical loading despite having minimal regenerative capacity. I will discuss the physical principles underlying this exceptional mechanical response and crack resistance in AC, and compare our theoretical predictions with experimental results. The second focus of my talk consists of the dynamic mechanical response of actin networks. Actin is a key component of the cytoskeleton, and is essential to cell growth, division, shape change, and motility. To enable this wide range of mechanical processes and properties, networks of actin filaments continuously disassemble and reassemble via active de/re-polymerization. I will discuss how de/re-polymerization kinetics of individual actin filaments translate to experimentally observed time-varying mechanical properties of dis/re-assembling networks. Understanding the mechanical structure function properties of these systems will provide insights into the dynamic response, toughness, and failure of biopolymer networks in cells and tissues, tissue repair therapies, and design principles for soft robotics.

Exploring cell-biology on a molecular level: Live-cell and quantitative localization microscopy

Our group develops and applies Single-Molecule Localization Microscopy (SMLM) techniques in cell biology—interested in the in situ observation of molecular processes in living cells.

SMLM data is built on single-molecule localizations, and thus allows determining the stoichiometry and molecular architecture of subcellular structures. Here, not only individual proteins can be precisely localized, but the large molecular architecture of multiprotein complexes or the organization of the genome can be targeted in the native cellular environment. This yields detailed quantitative molecular maps that capture these assemblies. In our vision, SMLM imaging thus has the potential to place hundreds of different molecules into assembled three-dimensional structures while maintaining the high spatiotemporal resolution of the present methods, ideally in correlative approaches.

Uniquely, SMLM can be combined with single-particle tracking (SPT) to measure a large batch of statistics on single-molecule dynamics inside living cells. It is thus possible to obtain spatially and temporally highly resolved diffusion maps that combine the multitude of single-molecule trajectories and accordingly unravel possible dynamic heterogeneities and subpopulations.

Behind todays attractive super-resolved images and analyses hides a rather high complexity of in large detail tailored experimental designs for specific organisms and environments. We cannot answer our research questions about the in situ behavior of molecular processes at a single molecules’ spatiotemporal resolution without highly optimized and robust tools—which are still largely missing for most biological research fields, e.g. for microbiology (as most proof-of-principle SMLM studies, are mostly conducted in mammalian cell culture).

In this talk, I will introduce some of our recently developed experimental and analytical tools alongside with our specific biological questions for two main topics: unraveling the molecular architecture and organization of the kinetochore complex regulating chromosome segregation in Schizosaccharomyces pombe and the diverse target detection dynamics of CRISPR Cas systems.

[1] Endesfelder BIOspektrum 2016, 22(2); [2] Virant et al. Int J Mol Sci 2017, 18(7).

Computational modeling of cell decision processes

The complex biochemical circuitry through which cells sense and respond to their environments is tightly interwoven with cell membranes. This coupling seems likely to shape many key features of biological responses to signals, and yet its effects are poorly understood. Mechanistic models of these processes thus offer considerable potential to provide new insights. My group uses computational approaches in collaboration with experimental labs to develop mechanistic models of cell signaling processes.

One of the major challenges in modeling these systems is that the molecular constituents of signaling networks interact in a multitude of ways to form densely connected networks involving hundreds to thousands (and beyond) of distinct biochemical species. Rule-based modeling, an approach my group has helped to develop, addresses this complexity by representing signaling molecules as structured objects whose interactions are governed by rules, which serve as generators of the species and reactions that comprise the network. This approach enables concise and precise encoding of known molecular biochemistry, freeing the modeler from having to explicitly enumerate the large number of possible species and reactions that can arise in such systems. BioNetGen, which is developed and maintained by my group, is one of several rule-based modeling platforms that enable scalable specification and simulation of large-scale models of signal transduction and other biochemical systems. In recent years its capabilities for modeling, simulation, and analysis have been greatly expanded and it has been used to model and gain mechanistic understanding of a number of important signaling processes. Here, in addition to providing a general introduction to rule-based modeling and describing some recent developments, I will present two applications to diverse systems: T cell differentiation in the immune system and dopamine uptake in the nervous system.

Biomimetic remodeling of lipid membranes by curved DNA origami

Biological membranes are dynamic cellular barriers that suffer deformation and bending. Despite huge effort in identifying the physical-chemical fundaments of such phenomena, particular mechanisms and elements are still poorly understood. In order to fill this gap, minimal biomimetic curvature-inducing DNA origami structures, that emulate the characteristics of BAR domain proteins, were engineered [1]. Here, I developed cholesteryl-modified DNA origami scaffolding units of different degrees of curvature and stacking features, that can interact with lipid model membranes and, above all, reproduce the sculpting activity of BAR proteins. Distinctive membrane deformations, such as tubulation, could be triggered at increased scaffold membrane densities, and the shape of those deformations correlated with the intrinsic curvature of the DNA origami nanostructures. Taken together, this novel approach reveals a minimal set of modules and preconditions required for shape-dependent membrane curvature generation (such as degree of curvature, membrane affinity and surface density), opening up exciting perspectives for using DNA origami nanotechnology in the fields of molecular to cellular-scale Membrane Biophysics.

[1] Franquelim HG, Khmelinskaia A, Sobczak JP, Dietz H, Schwille P (2018) Membrane sculpting by curved DNA origami scaffolds. Nat Commun, 9(1): 811.

Flow-generated mobility of proteins can probe membrane properties

A growing body of work describes the tendency of membrane-bound proteins to move in response to flow of the surrounding fluid: the coat proteins of swimming parasites, GPI-anchored glycoproteins on the surface of endothelial cells, and even individual membrane receptors tagged with nanoparticles are able to traverse large distances (many times the length of the protein) across the surface of a living cell membrane. This flow sorting of membrane proteins can occur because while membrane lipids are in a fluid phase, their motion is partially confined by cytoskeletal connections. Similar sorting of lipids or proteins can occur on lipid membranes supported on solid substrates. While synthetic membranes on glass supports are a less heterogeneous environment than a cell plasma membrane, proximity to a solid substrate still results in some dramatic changes in membrane properties, such as individual and collective lipid mobilities and miscibility. We create discrete supported bilayer patches by bursting giant unilamellar vesicles onto glass, to form cell-sized environments in which we can observe the membrane’s response to flow. In this talk I will describe biological membrane flow responses, and also some of the properties of supported bilayers that emerge from observations of our experimental system.

GTP hydrolysis promotes disassembly of the atlastin postfusion complex

Membrane fusion of the endoplasmic reticulum (ER) is catalyzed when atlastin GTPases anchored in opposing membranes dimerize and undergo a crossed over conformational rearrangement that draws the bilayers together. Previous studies have suggested that GTP hydrolysis triggers crossover dimerization, thus directly driving fusion. Here, we make the surprising observations that wild type (WT) atlastin undergoes crossover dimerization prior to hydrolyzing GTP, and that nucleotide hydrolysis and Pi release coincide more closely with dimer disassembly. These findings suggest that GTP binding, rather than its hydrolysis, triggers crossover dimerization for fusion. In support, a new hydrolysis-deficient atlastin variant undergoes rapid GTP-dependent crossover dimerization and catalyzes fusion at an initial rate similar to WT atlastin. However the variant cannot sustain fusion activity over time, implying a defect in subunit recycling. We suggest that GTP binding induces an atlastin conformational change that favors crossover dimerization for fusion and that the input of energy from nucleotide hydrolysis promotes complex disassembly for subunit recycling.

Inferring stresses and forces in active living matter

Measuring experimentally the forces that living organisms produce to move and change shape is challenging. At two different scales, I will propose two new techniques to determine these forces. From the molecular scale—where active forces originate—to the micron scale, thermal agitation makes trajectories erratic, which complicates the inference of these forces. I will show that we can interpret such Brownian dynamics as an information transmission problem, and propose a technique to optimally use microscopy data of single stochastic trajectories to infer active forces. At a larger scale, cells exert forces that are transmitted by the extracellular matrix. I will propose a technique, termed Nonlinear Stress Inference Microscopy, that uses active microrheology to probe such stresses in the extracellular matrix, revealing long-ranged force transmission in these networks.

Modelling membrane-bound cellular organelles with non-equilibrium dynamics

Membrane-bound cellular organelles perform many essential functions, among which the sorting and biochemical maturation of cellular components. Organelles along the secretory and endocytic pathways are strongly out-of-equilibrium structures, which display large stochastic fluctuations of composition and shape resulting from inter-organelle exchange and enzymatic reactions. Understanding how the different molecular mechanisms controlling these processes are orchestrated to yield robust fluxes of matter and to direct particular components to particular locations within the cell is an outstanding problem of great interest for cell biologist, but also for physicists.

In this talk, I will discuss a conceptual model of organelle biogenesis and maintenance that include vesicular exchange (budding, transport, and fusion) and biochemical maturation, i.e. the change of identity of an organelle over time (early to late endosomes, cis to trans Golgi cisternae…). I will show how the non-equilibrium steady-state of an organelle or a network of organelles may be varied in a controlled manner by modifying a limited number of coarse-grained parameters (essentially, the budding, fusion and maturation rates) and discuss the relevance of these results for the structure of the Golgi apparatus.

Building with Active Biofluids: Towards hybdrid bio-mechanical systems

While traditional fluids only flow when acted upon, a remarkable class of biomaterials can spontaneously flow by means of their own internal energy. These “active fluids” comprise a wide range of biological systems that bridge between biological and condensed matter systems due to being intrinsically driven out of equilibrium by internal energy injection from their microscopic elements, such as swimming bacteria or motor protein-microtubule bundles. The typically elongated nature of these active constituents frequently favors nematic alignment; however, their activity disturbs orientational order, continuously creating and annihilating pairs of topological defects. While these defects play a pivotal role in generating disorderly turbulent-like flows, they also have potential for engineering novel applications and understanding morphology when spatiotemporally ordered flow states can be produced.

This talk will describe the transitions between complex ordered flows produced by configurations of “dancing” defects and disorderly active turbulence within microchannels and rotary arrays. The knowledge gained from studying such “living” flows within confining and driven environments is essential for future designs of hybrid bio-mechanical devices that have the potential to work in conjunction with active biological fluids, rather than against them.

Cell membranes resist flow

The fluid-mosaic model posits a liquid-like plasma membrane, which can flow in response to tension gradients. It is widely assumed that membrane flow transmits local changes in membrane tension across the cell in milliseconds. This conjectured signaling mechanism has been invoked to explain how cells coordinate changes in shape, motility, and vesicle fusion, but the underlying propagation has never been observed.

In this talk, I will show that propagation of membrane tension occurs quickly in cell-attached blebs, but is largely suppressed in intact cells. The failure of tension to propagate in cells is explained by a fluid dynamical model that incorporates the flow resistance from cytoskeleton-bound transmembrane proteins. Perturbations to tension propagate diffusively, with a diffusion coefficient ~ 0.024 μm²/s. In primary endothelial cells, local increases in membrane tension lead only to local activation of mechanosensitive ion channels and to local vesicle fusion. Thus membrane tension is not a mediator of long-range intra-cellular signaling, but local variations in tension mediate distinct processes in sub-cellular domains.

Visualization of Host-Pathogen Interactions at Cellular Membranes

Many viruses have evolved protein factors that hijack host cell pathways to promote viral replication and avoid the immune response. One example of great interest to our research group is the Nef protein encoded by HIV-1 and other primate lentiviruses. Nef is a relatively small (25-30 kDa), myristoylated protein that localizes to cellular membranes, where it interacts with a multitude of host cell proteins involved in signal transduction and intracellular trafficking. Non-receptor protein-tyrosine kinases are particularly liable to activation by Nef, which perturbs intramolecular interactions that normally suppress kinase activity. Using bimolecular fluorescence complementation of green fluorescent proteins (BiFC) coupled with confocal microscopy, we have demonstrated that Nef interacts with Src and Tec family kinases in the membrane compartment, resulting in constitutive kinase activation. BiFC has also revealed that Nef forms homodimers, another key part of the kinase activation mechanism. Small molecules that inhibit Nef-kinase signaling pathways show promise as a new class of antiretroviral agents. Working in collaboration with the Lösche laboratory at CMU, we are applying neutron scattering and other biophysical techniques to reveal the structure of Nef in complex with host cell kinases on sparsely tethered lipid bilayers.

How physical constraints mold random motion to create membrane remodeling in health and disease

To live, eukaryotic cells must regulate a complex network of internal membranes which compartmentalize function. The quaternary structures of the individual macromolecules that catalyze topological transformations (i.e. fusion, fission, and poration) between these intracellular membraneous compartments do not immediately suggest their mechanism of action. Work in our lab has focused on using modeling, microscopy, mutations, and self-assembling membranes to investigate these mechanisms. I will discuss one example of each: the membrane fusion that allows the influenza virus to enter a cell, the membrane fission catalyzed by the endocytotic GTPase dynamin, and the poration of the vacuolar and plasma membranes of red blood cells infected with malaria.