Bulletin of the American Physical Society
Mid-Atlantic Section 2022 Meeting
Volume 67, Number 20
Friday–Sunday, December 2–4, 2022; University Park, PA, Pennsylvania State University
Session E01: Bio III |
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Chair: Dezhe Jin, Pennsylvania State University Room: Pennsylvania State University Osmond 103 |
Saturday, December 3, 2022 2:00PM - 2:35PM |
E01.00001: Bacterial morphogenesis and growth control in dynamic environments Invited Speaker: Shiladitya Banerjee Bacteria are highly adaptive microorganisms that thrive in a wide range of environmental conditions via changes in cell morphologies and macromolecular composition. How bacterial growth and morphologies are regulated in diverse environmental conditions is a long-standing question. Regulation of bacterial cell size implies cellular control mechanisms that couple bacterial growth and division to the extracellular environment and intracellular composition. In the past decade, simple quantitative laws have emerged that connect cell growth to proteomic composition and the nutrient availability in the external environment. However, the relationships between cell morphology and growth physiology remain poorly understood in dynamic environments. In this talk, I will present our recent work on understanding the physical and biological forces that regulate bacterial growth and morphological adaptation in dynamic changing environments. Specifically, I'll discuss how changes in nutrient environments modulate cell shape, growth, and mechanics to optimize cellular adaptive performance under stress. Integrating quantitative theories with experimental data, we identify mechanistic models underlying cellular growth control and shape regulation, revealing the intimate connections between cell morphology and organismal fitness. In particular, we show how shape changes can provide adaptive benefits in stressful environments. |
Saturday, December 3, 2022 2:35PM - 2:47PM |
E01.00002: Structure-based approach to identifying small sets of driver nodes in biological and biologically-inspired networks Eli Y Newby, Jorge Gómez Tejeda Zañudo, Reka Z Albert In network control theory, driving all the nodes in the Feedback Vertex Set (FVS) by node-state override forces the network into one of its attractors (long-term dynamic behaviors). The FVS is often composed of more nodes than can be practically manipulated in a system. We developed an approach to rank subsets of the FVS on Boolean models of intracellular networks using topological, dynamics-independent measures. We investigated the predictive power of three types of topological measures—centrality measures, propagation measures, and cycle-based measures. Every subset was evaluated on three dynamics-based measures: To Control, Away Control, and the Logical Domain of Influence. After examining an array of biological networks and ensembles of random Boolean networks that resemble biological networks, we found that the FVS subsets that ranked in the top according to the propagation metrics can effectively control the network, indicating a structural underpinning to dynamically important nodes. Consequently, overriding the entire FVS is not required to drive a biological network to one of its attractors, and our method provides a way to reliably identify effective FVS subsets without the knowledge of the network dynamics. |
Saturday, December 3, 2022 2:47PM - 3:22PM |
E01.00003: Long range chromosomal interactions and first passage process in budding yeast Invited Speaker: Lu Bai Chromosomal interaction plays a critical role for nuclear processes including DNA repair, replication, and transcription. One important step during the interaction is the encountering of two chromosome segments, which in statistical physics, presents a first passage problem. Here, we use a novel method developed in our lab, Chemically Induced Chromosomal Interaction (CICI), to study chromosome motion and the first passage dynamics. We show that both random diffusion and cohesin loop extrusion contribute to intra-chromosomal interactions. We also applied polymer physics models to understand the chromosome dynamics. |
Saturday, December 3, 2022 3:22PM - 3:34PM |
E01.00004: Improving Boolean models of biological systems using a genetic algorithm Kyu Hyong Park, Jordan C Rozum, Reka Z Albert The model-checking and improvement process is one of the bottlenecks of model construction. We present a genetic algorithm-based tool that provides a systematic method of comparing a model to various experimental data and creating improved versions. The algorithm starts with a pre-existing model consisting of an interaction graph and a Boolean function for each node. Many offspring models are created that are consistent with the starting interaction graph and optional constraints. Each model is scored based on the agreement of experimental perturbation results (expressed in Boolean form) with the model’s attractors under the same perturbations. The models with the highest score are kept and more offspring are generated from them. Repeated iteration generates models that agree far better with the experimental input than the starting model. |
Saturday, December 3, 2022 3:34PM - 3:46PM |
E01.00005: Revealing context dependence through Partially Observable Markov Model Jiali Lu, Dezhe Z Jin, Sumithra Surendralal, Kristofer E Bouchard Songs of the Bengalese finch consist of variable sequences of syllables. The sequences follow probabilistic rules, and can be statistically described by partially observable Markov models (POMMs), which consist of states and probabilistic transitions between them. Each state is associated with a syllable, and one syllable can be associated with multiple states. This multiplicity of syllable to states association distinguishes a POMM from a simple Markov model, in which one syllable is associated with one state. The multiplicity indicates that syllable transitions are context-dependent. Here we present a novel method of inferring a POMM with minimal number of states from a finite number of observed sequences. We apply the method to infer POMMs for songs of six adult male Bengalese finches before and shortly after deafening. Before deafening, the models all require multiple states, but with varying degrees of state multiplicity for individual birds. Deafening reduces the state multiplicity for all birds. For three of them, the models become Markovian, while for the other three, the multiplicity persists for some syllables. These observations indicate that the auditory system contributes to, but is not the only source of, the context dependencies of syllable transitions in Bengalese finch song. |
Saturday, December 3, 2022 3:46PM - 3:58PM |
E01.00006: Novel Nanoparticle Contrast Agents for Magnetic Resonance Imaging Edward R Van Keuren, Sarah Stoll, Trevor Lyons, Chloe Kekedjian, Christopher Albanese, Olga Rodriguez, Stanley Fricke, Orelle Bulgin Magnetic resonance imaging (MRI) is an important diagnostic tool in both clinical and research environments. In order to improve sensitivity, contrast agents (CAs) are often administered prior to or during imaging sessions. We have developed a number of novel nanoparticle CAs consisting of metal-oxo clusters with high spins (molecular magnets) encapsulated in polymer nanocarriers. The pure clusters show good relaxivities, which can be further enhanced by encapsulation in the polymers. In some cases, values of the relaxivity comparable to or larger than those of commercially available CAs can be achieved. We will report on the contrast enhancement from several of these nanoparticles in both phantom and in vivo images. |
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