Diverse physical processes played important roles in the origin of life. I will review the origin of molecular homochirality, the growth of protocell membranes, and potential roles for liquid-liquid phase separation. I will then discuss the concept of functional information and its quantitative relationship with molecular function.

In vivo, the human genome folds into a characteristic ensemble of 3D structures. The mechanism driving the folding process remains unknown. A theoretical model for chromatin (the minimal chromatin model) explains the folding of interphase chromosomes and generates chromosome conformations consistent with experimental data is presented. The energy landscape of the model was derived by using the maximum entropy principle and relies on two experimentally derived inputs: a classification of loci into chromatin types and a catalog of the positions of chromatin loops. This model was generalized by utilizing a neural network to infer these chromatin types using epigenetic marks present at a locus, as assayed by ChIP-Seq. The ensemble of structures resulting from these simulations completely agree with HI-C data and exhibits unknotted chromosomes, phase separation of chromatin types, and a tendency for open chromatin to lie at the periphery of chromosome territories. Although this theoretical methodology was trained in one cell line, the human GM12878 lymphoblastoid cells, it has successfully predicted the structural ensembles of multiple human cell lines. Finally, going beyond Hi-C, our predicted structures are also consistent with microscopy measurements. Analysis of both structures from simulation and microscopy reveals that short segments of chromatin make two-state transitions between closed conformations and open dumbbell conformations. For gene active segments, the vast majority of genes appear clustered in the linker region of the chromatin segment, allowing us to speculate possible mechanisms by which chromatin structure and dynamics may be involved in controlling gene expression. * Supported by the NSF

Living cells contain millions of enzymes and proteins, which carry out multiple reactions simultaneously. To optimize these processes, cells compartmentalize reactions in membraneless liquid condensates. Certain features of cellular condensates can be explained by principles of liquid-liquid phase separation studied in material science. However, biological condensates exist in the inherently out of equilibrium environment of a living cell, being driven by force-generating microscopic processes. These cellular conditions are fundamentally different than the equilibrium conditions of liquid-liquid phase separation studied in materials science and physics. How condensates function in the active riotous environment of a cell is essential for understanding of cellular functions, as well as to the onset of neurodegenerative diseases. Currently, we lack model systems that enable rigorous studies of these processes. Living cells are too complex for quantitative analysis, while reconstituted equilibrium condensates fail to capture the non-equilibrium environment of biological cells. To bridge this gap, we reconstituted a DNA based membraneless condensates in an active environment that mimics the conditions of a living cell. We combine condensates with a reconstituted network of cytoskeletal filaments and molecular motors, and study how the mechanical interactions change the phase behavior and dynamics of membraneless structures. Studying these composite materials elucidates the fundamental physics rules that govern the behavior of liquid-liquid phase separation away from equilibrium while providing insight into the mechanism of condensate phase separation in cellular environments.

Active particles which are self-propelled by converting energy into mechanical motion represent an expanding research realm in physics and chemistry. For micron-sized particles moving in a liquid (``microswimmers''), most of the basic features have been described by using the model of overdamped active Brownian motion [1]. However, for macroscopic particles or microparticles moving in a gas, inertial effects become relevant such that the dynamics is underdamped. Therefore, recently, active particles with inertia have been described by extending the active Brownian motion model to active Langevin dynamics which include inertia [2]. In this talk, recent developments of active particles with inertia (``microflyers'', ``hoppers'' or ``runners'') are summarized including: inertial delay effects between particle velocity and self-propulsion direction [3], tuning of the long-time self-diffusion by the moment of inertia [3], the influence of inertia on motility-induced phase separation and the cluster growth exponent [4], and the formation of active micelles (“rotelles”) by using inertial active surfactants. References [1] C. Bechinger, R. di Leonardo, H. Löwen, C. Reichhardt, G. Volpe, G. Volpe, Reviews of Modern Physics 88, 045006 (2016). [2] H. Löwen, Journal of Chemical Physics 152, 040901 (2020). [3] C. Scholz, S. Jahanshahi, A. Ldov, H. Löwen, Nature Communications 9, 5156 (2018). [4] S. Mandal, B. Liebchen, H. Löwen, Physical Review Letters 123, 228001 (2019). [5] C. Scholz, A. Ldov, T. Pöschel, M. Engel, H. Löwen, Surfactants and rotelles in active chiral fluids, will be published

Understanding the properties of active matter is a challenge which is currently driving a rapid growth in soft- and bio-physics. Some of the most important examples of active matter are at the microscale, and include active colloids and suspensions of microorganisms, both as a simple active fluid (single species) and as mixed suspensions of active and passive elements. In this last class of systems, recent experimental and theoretical work has started to provide a window into new phenomena including activity-induced depletion interactions, phase separation, and the possibility to extract net work from active suspensions. Here I will present our work on a paradigmatic example of mixed active-passive system, where the activity is provided by swimming microalgae. Macro- and micro-scopic experiments reveal that microorganism-colloid interactions are dominated by rare close encounters leading to large displacements through direct entrainment. Simulations and theoretical modelling show that the ensuing particle dynamics can be understood in terms of a simple jump-diffusion process, combining standard diffusion with Poisson-distributed jumps. Entrainment length can be understood within the framework of Taylor dispersion as a competition between advection by the no-slip surface of the cell body and microparticle diffusion. Building on these results, we then ask how external control of the dynamics of the active component (e.g. induced microswimmer anisotropy/inhomogeneity) can be used to alter the transport of passive cargo. As a first step in this direction, we study the behaviour of mixed active-passive systems in confinement. The resulting spatial inhomogeneity in swimmers’ distribution and orientation has a dramatic effect on the spatial distribution of passive particles, with the colloids accumulating either towards the boundaries or towards the bulk of the sample depending on the size of the container. We show that this can be used to induce the system to de-mix spontaneously.

Intrinsically disordered proteins (IDPs), lack of a well-defined folded structure, have been recently shown to be critical to forming membrane-less organelles via liquid-liquid phase separation (LLPS). Due to the flexible conformations of IDPs, it could be challenging to investigate IDPs with solely experimental techniques. Computational models can therefore provide complementary views at several aspects, including the fundamental physics underlying LLPS and the sequence determinants contributing to LLPS. In this presentation, I will start with our coarse-grained computational framework that can help generate sequence dependent phase diagrams. The coarse-grained model further led to the development of a polymer model with empirical parameters to quickly predict LLPS of IDPs. At last, I will show our preliminary efforts on addressing molecular interactions within LLPS of IDPs using all-atom explicit-solvent simulations.