Bulletin of the American Physical Society
APS March Meeting 2023
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session Z10: Emergent Behavior in Biological SystemsFocus
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Sponsoring Units: DBIO Chair: James Boedicker, USC Room: Room 202 |
Friday, March 10, 2023 11:30AM - 12:06PM |
Z10.00001: Emergent Spatiotemporal Communication Patterns in Insect Swarms Invited Speaker: Orit Peleg Our world is full of living creatures that must share information to survive and reproduce. As humans, we easily forget how hard it is to communicate within natural environments. So how do organisms solve this challenge, using only natural resources? Ideas from physics, mathematics, and computer science, such as energetic cost, compression, and detectability, define universal criteria that almost all communication systems must meet. We use insect swarms as a model system for identifying how organisms harness the dynamics of communication signals, perform spatiotemporal integration of these signals, and propagate those signals to neighboring organisms. In this talk, I will focus on two types of communication in insect swarms: visual communication, in which fireflies communicate over long distances using light signals, and chemical communication, in which bees serve as signal amplifiers to propagate pheromone-based information about the queen's location. We use behavioral assays and computational methods to develop and test model-driven hypotheses about these model systems and overall bring a deeper understanding of animal communication. |
Friday, March 10, 2023 12:06PM - 12:42PM |
Z10.00002: Nonequilibrium force fluctuations of micro swimmers Invited Speaker: Wylie W Ahmed We investigate the stochastic force fluctuations of micro swimmers in two scenarios: (1) a single swimmer navigating through a passive fluid; (2) a dense suspension of swimmers surrounding a passive tracer. By direct force measurement using optical tweezers we show that the force trajectory of an individual micro swimmer exhibits rich oscillatory dynamics that vary in time. Interestingly, when these highly fluctuating force dynamics are analyzed using the framework of stochastic thermodynamics we recover energy dissipation rates in agreement with time-averaged fluid dynamics studies. For a dense suspension of swimmers serving as an active bath for a passive tracer we observe both shear thinning and thickening, which depends on Peclet number, and enhanced diffusion of our tracer by a factor of 2. We estimate the energy transfer rate from the active bath to the passive tracer. These two scenarios allow us to explore energy exchange between an active swimmer in a passive bath and a passive tracer in an active bath. |
Friday, March 10, 2023 12:42PM - 12:54PM |
Z10.00003: The collective motion and merging of macroscopic bacterial aggregates James Q Boedicker Many chemotactic bacteria generate spatial patterns of cell density. These emergent patterns are the result of the directed movement of cells following chemical gradients self-generated by bacterial metabolic activity. Here we report collective behaviors exhibited by the bacteria Enterobacter cloacae. Enterobacter cloacae spread uniformly within soft agar will eventually form millimeter-sized aggregates of cells. Surprisingly, these aggregates migrate up to several millimeters after formation, sometimes resulting in the merging of two or more clusters of cells. We examined the formation and dynamics of thousands of bacterial clusters that form within large culture dishes, analyzing both the spatial order of the aggregate pattern and the dynamics of aggregate migration. At the microscale, aggregates are composed of immotile cells surrounded by low density regions of motile cells. We understand the collective motion of these aggregates as the result of an asymmetric flux of bacteria at the aggregate boundary. These findings demonstrate how a transient, density-dependent change in motility can lead to the formation of large-scale and dynamics patterns of cell bacteria. |
Friday, March 10, 2023 12:54PM - 1:06PM |
Z10.00004: Spatiotemporal dynamics of metabolite gradients control the emergent morphology of a bacterial colony on hard agar Harish Kannan, Paul Sun, Tolga Caglar, Daotong Ge, Kinshuk Sahu, Jiajia Dong, Bo Li, Terence T Hwa The growth of an E. coli colony on hard agar exhibits robust expansion kinetics and morphology despite the complex interactions between millions of cells experiencing compact confinement under a spatiotemporally varying nutrient gradient. To probe the mechanistic origins of such robust colony characteristics, an agent-based model along with a set of reaction-diffusion equations to model the spatiotemporal dynamics of extracellular metabolites is employed. For colonies grown on glucose minimal medium plates, we find glucose depletion driven by anaerobiosis to be the primary factor contributing to the experimentally observed saturation in vertical expansion, while the excreted fermentation products play a crucial role for cell maintenance at the aerated colony surface. We also establish that the well-known linear expansion of the colony radius is not limited by nutrient. Various physiological factors affecting colony morphology are also characterized. Overall, our study emphasizes that in addition to mechanical interactions, the spatiotemporally varying metabolite gradients and the mode of metabolism of the individual cells determine the emergent morphology and expansion kinetics of the macroscopic colony. |
Friday, March 10, 2023 1:06PM - 1:42PM |
Z10.00005: Mechanical Information Processing by the Actin Cytoskeleton Invited Speaker: Shailaja Seetharaman Adherent cells sense varied mechanical cues; however, the mechanisms by which these input signals are processed to control cell physiological functions is not known. Mechanosensing and force generation in tissues are generally driven by the actomyosin network and adhesion components (focal adhesions and adherens junctions) that control tissue homeostasis. A ubiquitous family of LIM (Lin11, Isl- 1, and Mec-3) domain proteins is associated with mechanotransductive structures, and yet how mechanical information is sensed and processed across a tissue remains elusive. Here, we demonstrate tunability of LIM domain protein localization and function in endothelial cells by altering various intracellular and extracellular mechanical cues such as shear stress, contractility, and matrix rigidity. For instance, Zyxin, which predominantly localizes to stress fibers and focal adhesions, can be redirected to adherens junctions and tricellular vertices by altering matrix rigidity. In addition, we observe that shear stresses experienced by vascular endothelial cells drive the differential localization of Zyxin and FHL2. Functionally, the expression levels and localization of LIM proteins precisely control how cells mechanosense and align in response to shear stress. Altogether, we identify and describe the intracellular and extracellular mechanical cues that trigger the differential localization of LIM domain proteins. Using novel techniques such as photo-proximity spatial profiling of proteins, phosphoproteomics and machine learning, we are exploring the functions and mechanotransduction pathways downstream of the force-dependent tuning of LIM protein localization. |
Friday, March 10, 2023 1:42PM - 1:54PM |
Z10.00006: Graph identification of proteins in tomograms (GRIP-Tomo) Margaret S Cheung, August George, Doonam Kim, Trevor H Moser, James E Evans, Ian Gildea In this study, we present a method of pattern mining based on network theory that enables the identification of protein structures or complexes from synthetic volume densities, without the knowledge of predefined templates or human biases for refinement. We hypothesized that the topological connectivity of protein structures is invariant, and they are distinctive for the purpose of protein identification from distorted data presented in volume densities. Three-dimensional densities of a protein or a complex from simulated tomographic volumes were transformed into mathematical graphs as observables. We systematically introduced data distortion or defects such as missing fullness of data, the tumbling effect, and the missing wedge effect into the simulated volumes, and varied the distance cutoffs in pixels to capture the varying connectivity between the density cluster centroids in the presence of defects. A similarity score between the graphs from the simulated volumes and the graphs transformed from the physical protein structures in point data was calculated by comparing their network theory order parameters including node degrees, betweenness centrality, and graph densities. By capturing the essential topological features defining the heterogeneous morphologies of a network, we were able to accurately identify proteins and homo-multimeric complexes from ten topologically distinctive samples without noise. Our approach empowers future developments to provide pattern mining with interpretability that classifies single-domain protein native topologies as well as distinct single-domain proteins from multimeric complexes within noisy volumes. |
Friday, March 10, 2023 1:54PM - 2:06PM |
Z10.00007: Building differentiable kinetic models to improve yield of finite sized assemblies Adip Jhaveri The self-assembly of protein sub-units into a functional complex is an essential step in several cellular processes like transcription and virion formation. The formation of a functional complex can be carried out in specific pathways that involve a high degree of spatial and temporal organisation. However, the lack of these driving forces can lead to kinetic trapping that can reduce the final yield of the functional complex. In this work we use deterministic reaction simulations to quantify how kinetic trapping regimes can emerge in finite sized assemblies based on topology, size and interaction strengths. These kinetic models allow us to utilize the automatic differentiation technique to maxmize the yield while avoiding erroneous assembly pathways. We show that protein systems can exploit different strategies to avoid traps by introducing different degrees of heterogeneity in the kinetic parameters. Our results further show how certain biological limitations and toplogy of different sized assemblies can lead to emergence of a preferred pathway of assembly. The tuning of kinetic pathways to achieve a higher yield offers a high degree of robustness and flexibility in biological systems without the need to alter topologies or energetics. |
Friday, March 10, 2023 2:06PM - 2:18PM |
Z10.00008: Manipulating polydispersity of lens β-crystallins using divalent cations demonstrates evidence of calcium regulation Michael R Bergman, Leila Deravi One common feature conserved across living systems is the high concentration of crystallin proteins packed within the eye lens. Of the three most common vertebrate subtypes, β-crystallins exhibit the widest degree of polydispersity due to their complex multimerization properties in situ. While the structural complexities of crystallins is one factor that aids in preventing phase-separation within the protein-dense environment, properties which enable vision, it is unclear whether the polydispersity of β-crystallins provides additional function or is a redundant feature in the lens. One proposed function for β-crystallins is calcium-buffering. The lens needs to control calcium to prevent rampant proteolysis by calpains, while balancing protein-protein interactions to maintain tissue transparency. Our combined results suggest that protein-protein and protein-cation interactions are in competition in lens β-crystallins. We assayed hydrodynamic behavior and assembly mechanics of crystallins in different salts and observed altered protein polydispersity in vitro. We used size-exclusion chromatography together with dynamic light scattering and LC-MS/MS to show how divalent cations dissociate β-crystallin oligomers, reducing polydispersity, and shifting protein surface charge – properties that can be reversed when the salts are removed. While the direct, physiological relevance of these divalent cations in the lens is still under investigation, our results support that specific isoforms contribute to a dynamic equilibrium and inherent polydispersity of β-crystallin as an important feature for two aspects of lens function: calcium-regulation and microstructure. The cation-regulating mechanisms of β-crystallin outlined by our results are expected to contribute to the long-lived stability and transparency of the lens. |
Friday, March 10, 2023 2:18PM - 2:30PM |
Z10.00009: Learning and controlling phase separation in complex geometries with differentiable physics Alexander Cohen, Jorn Dunkel, Martin Z Bazant Phase separation is ubiquitous in nature and has recently become a major research interest due to its role in many essential processes in biological cells. While many models have been developed to describe this phenomena, systematic methods to incorporate data into the models and control phase separation are lacking. Here, starting with general theories from nonequilibrium thermodynamics, we write a differentiable physics simulator using adjoint methods for phase separation that can be used in learning, optimization, and control applications. In addition to differentiability with respect to bulk model parameters, the simulation can also be differentiated with respect to boundary condition parameters, time-dependent control parameters, and shape parameters. We utilize this framework to demonstrate how models of phase separation can be learned from noisy data. We also demonstrate optimizing the length of phase boundaries by changing the shape of the simulation domain. Finally, we show how to learn control procedures for boundary conditions in order to manipulate the motion of the separated phases. While we focus on these three specific examples, our approach is general to learning models for phase separation and controlling the dynamics of phase separation for engineering application. |
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