Bulletin of the American Physical Society
APS March Meeting 2022
Volume 67, Number 3
Monday–Friday, March 14–18, 2022; Chicago
Session Y31: Biological PhysicsRecordings Available
|
Hide Abstracts |
Sponsoring Units: DBIO Chair: Margaret Cheung, PNNL Room: McCormick Place W-192A |
Friday, March 18, 2022 8:00AM - 8:12AM |
Y31.00001: UNDERSTANDING PROTEIN COMPLEX ASSEMBLY THROUGH GRAND CANONICAL MAXIMUM ENTROPY MODELING Margaret S Cheung Inside a cell, heterotypic proteins assemble in inhomogeneous, crowded systems where the abundance of these proteins vary with cell types. While some protein complexes form putative structures that can be visualized with imaging, there are far more protein complexes that are yet to be solved because of their dynamic associations with one another. Nevertheless, it is possible to infer these protein complexes through a physical model. However, it is often not clear to physicists what kind of data from biology is necessary for such a modeling endeavor. Here, we aim to model these clusters of coarse-grained protein assemblies from multiple subunits through the constraints of interactions among the subunits and the chemical potential of each subunit. We obtained the constraints on the interactions among subunits from the known protein structures. We inferred the chemical potential that dictates the particle number distribution of each protein subunit from the knowledge of protein abundance from experimental data. Guided by the maximum entropy principle, we formulated an inverse statistical mechanical method to infer the distribution of particle numbers from the data of protein abundance as chemical potentials for a grand canonical multicomponent mixture. Using grand canonical Monte Carlo simulations, we captured a distribution of high-order clusters in a protein complex of succinate dehydrogenase with four known subunits. The complexity of hierarchical clusters varies with the relative protein abundance of each subunit in distinctive cell types such as lung, heart, and brain. When the crowding content increases, we observed that crowding stabilizes emergent clusters that do not exist in dilute conditions. We, therefore, proposed a testable hypothesis that the hierarchical complexity of protein clusters on a molecular scale is a plausible biomarker of predicting the phenotypes of a cell. |
Friday, March 18, 2022 8:12AM - 8:24AM |
Y31.00002: Epithelial-to-mesenchymal transition proceeds through directional destabilization of multidimensional attractor Jianhua Xing, Weikang Wang, Dante Poe, Yaxuan Yang, Thomas Hyatt How a cell changes from one stable phenotype to another one is a fundamental problem in developmental and cell biology. Currently biologists tackle this problem mainly through trial-and-error. We established a quantitative experimental-theoretical framework to formulate the problem as transitions between nonequilibrium attractors. With the framework we applied modern reaction rate theories in the field. Specifically a central theoretical concept is the reaction coordinate. With our framework we demonstrated that one can perform transition path analyses on measured multi-dimensional transition paths for a cellular system. |
Friday, March 18, 2022 8:24AM - 9:00AM |
Y31.00003: Cellular organization in lab-evolved and extant multicellular species obeys a maximum entropy law Thomas C Day, Seyed Alireza Zamani Dahaj, Peter Yunker, Raymond E Goldstein, William C Ratcliff, Stephanie Hoehn The prevalence of multicellular organisms is due in part to their ability to form complex structures. How cells pack in these structures is a fundamental biophysical issue, underlying their functional properties. However, much remains unknown about how cell packing geometries arise, and how they are affected by random noise during growth - especially absent developmental programs. Here, we quantify the cellular neighborhood size statistics of two different multicellular eukaryotes: lab-evolved “snowflake” yeast and the green alga V. carteri. We find that despite large differences in cellular organization, the free space associated with individual cells in both organisms closely fits a modified gamma distribution, consistent with maximum entropy predictions originally developed for granular materials. This `entropic' cellular packing ensures a degree of predictability despite noise, facilitating parent-offspring fidelity even in the absence of developmental regulation. Together with simulations of diverse growth morphologies, these results suggest that gamma-distributed cell neighborhood sizes are a general feature of multicellularity, arising from conserved statistics of cellular packing. |
Friday, March 18, 2022 9:00AM - 9:12AM |
Y31.00004: Development of a vessel-on-a-chip model for study of Hb-based artificial oxygen carriers Babak Mosavati Artificial oxygen carries (AOCs) can be used as red blood cell substitutes for transfusion to improve tissue oxygenation. They can be used to reduce transfusion-associated harmful side effects, such as inflammation and immunoreaction from the denoted blood. However, development of effective and safe AOCs to replace physiological human red blood cells (RBCs) is challenging. This work presents oxygen transport in transfusion of artificial oxygen carriers. Hemoglobin based oxygen carriers were synthesized and their performance was tested. A 3D vessel on a chip device was developed to measure the oxygen transport in blood vessel. In this model, each microfluidic chip consists of three channels, a center channel for loading an extracellular matrix (ECM), side by side perfusion channels for endothelium cell cultures. Endothelial cells were seeded on one side of ECM and serum-free medium containing AOCs was added to Endothelial cells channel. The same serum-free medium without Hb was added to another micro channel and Endothelial Cell permeability to Hemoglobin Based Oxygen Carriers was investigated. The response of endothelial layer permeability by comparing the cellular polymersomes vs. acellular HbOCs was tested. Additionally, the mechanical fatigue of AOCs was characterized by subjecting them to cyclic hypoxia and shear stresses at single-cell level. |
Friday, March 18, 2022 9:12AM - 9:24AM |
Y31.00005: Using X-ray scattering to investigate effects of e-cigarette additives on pulmonary membrane structure Alauna Wheeler, Jocelyn Ochoa, Rayner Hernandez Perez, Linda S Hirst Pulmonary surfactant is an important part of the respiratory system. It forms membranes that line the passages inside the lungs. One important function of the pulmonary surfactant is to lower the surface tension at the interface between water and air in the alveoli—or air sacs—of the lungs, preventing alveolar collapse upon exhalation. In 2019 over two thousand people had lung injuries associated with e-cigarette use. Most of these injuries are correlated to the use of certain chemical additives in e-cigarette flavorings. We hypothesize that these chemical additives are changing the structure of the pulmonary surfactant membranes, preventing the pulmonary surfactant from properly functioning to protect the lungs from injury. In this study we use Small- and Wide-Angle X-ray Scattering (SAXS & WAXS) to investigate how the structure of the pulmonary surfactant membranes is altered by the addition of these e-cigarette chemical flavorings. |
Friday, March 18, 2022 9:24AM - 9:36AM |
Y31.00006: Exploring cooperative treadmilling and protrusion growth in fire ant rafts Robert J Wagner, Franck J Vernerey Fire ants (Solenopsis invicta) are well-documented forming buoyant and dynamic aggregations consisting entirely of worker ants when exposed to water. Here, we observe the collective morphogenesis of fire ant rafts docked to stationary, vertical rods. These rafts consist of a condensed, floating, structural network of interconnected ants on top of which a dispersed, pedestrian layer of freely active ants walks. Under these conditions, ant rafts can change their shape substantially and continuously over the span of several hours through cooperative global treadmilling. During treadmilling, these rafts frequently sprout tether-like protrusions from their edges that fire ants can use as land bridges to escape flooded environments. Employing both experimental characterization and an agent-based, numerical model, we here unveil a local set of mechanisms that reproduce the stochastic emergence of these instabilities in the absence of long-range interactions, targeted cues, or external gradients. Furthermore, we demonstrate that simply through the modulation of free ant activity, the model reproduces oscillatory phases of high outwards expansion (exploration) and predominantly inwards contraction (dormancy). These results suggests that collective morphogenesis of this system is strongly mediated by local interactions at the constituent length scale, perhaps providing inspiration for the development of decentralized, autonomous active matter and swarm robotics. |
Friday, March 18, 2022 9:36AM - 9:48AM |
Y31.00007: Will more data rather than more samples improve spectroscopic analysis? Curtis W Meuse, Sabrina Hafiz, Michaela Staab, Kenneth A Rubinson It is well known that the noise on a spectrometric signal will decrease with averaging over time. With contemporary capability for data collection and storage, we can retain and access more information about a signal train than just its average. During the same sampling time, we can record multiple versions of the signal averaged over shorter, equal periods. This is, then, the set of signals over submultiples of the total collection time. With a sufficiently large set of submultiples, the distribution of the signal's fluctuations over the submultiple periods of the data stream can be acquired at each wavelength. We have previously shown that the extreme values of the fluctuation of the signals are usually not balanced (equal magnitudes, equal probabilities) on either side of the mean or median without an inconveniently long measurement time; the data is almost inevitably biased away from the mean indicating benefits from using the median. Here, we explore the use of submultiple data collection to improve multivariate curve resolution – alternating least squares methods to separate the infrared spectra of buffer and protein, objectively, from protein solution spectra. |
Friday, March 18, 2022 9:48AM - 10:00AM |
Y31.00008: An Atomistic Model Of The Human Stratum Corneum: Permeation Through The Long Periodicity Phase. Effect of a pro-penetrant. Christian Jorgensen, Fabien Léonforte, Gustavo S Luengo, Sébastien Gregoire, Bruno Biatry, Peter D Olmsted, Ann Detroyer The stratum corneum (SC) layer of the human skin is the outermost and primary barrier against chemical topical exposure. The ability of a chemical to pass the SC is a key point for risk assessment and development of cosmetic ingredients. From neutron diffraction data, the SC peaks comprise a short periodicity phase (SPP) with a repeat distance of 6 nm, and a long periodicity phase (LPP) with a repeat distance of 13 nm. The LPP captures long-scale dynamics and can be represented as a sandwich model by Bouwstra. |
Friday, March 18, 2022 10:00AM - 10:12AM |
Y31.00009: Asymmetric Branching Scale Factors as Features in Neuronal and Glial Cell-Type Classification Using Machine Learning Methods. Paheli Desai-Chowdhry, Van M Savage, Alexander B Brummer Neurons are connected by complex branching processes - axons and dendrites - that process information for organisms to respond to their environment. Classifying neurons according to differences in structure or function is a fundamental piece of neuroscience. In previous work, we constructed a biophysical theory that establishes a correspondence between neuron structure and function as mediated by principles such as time or power minimization, using undetermined Lagrange multipliers to predict scaling ratios for axon and dendrite sizes across branching levels. Here, we relax the assumption of symmetrical branching in the model to determine asymmetric branching powers that differ across different cell types due to functional tradeoffs. Furthermore, we use scale factors related to asymmetric branching as features in machine learning classification to distinguish between different cell types. We find significant distinctions in the asymmetric scaling ratios between Purkinje cells and motoneurons and between axons and microglia, a specific class of electrically active non-neuronal brain cells. The performance of these classification methods gives us important insights into the correspondence between structure and function across different cell types. |
Follow Us |
Engage
Become an APS Member |
My APS
Renew Membership |
Information for |
About APSThe American Physical Society (APS) is a non-profit membership organization working to advance the knowledge of physics. |
© 2024 American Physical Society
| All rights reserved | Terms of Use
| Contact Us
Headquarters
1 Physics Ellipse, College Park, MD 20740-3844
(301) 209-3200
Editorial Office
100 Motor Pkwy, Suite 110, Hauppauge, NY 11788
(631) 591-4000
Office of Public Affairs
529 14th St NW, Suite 1050, Washington, D.C. 20045-2001
(202) 662-8700