Bulletin of the American Physical Society
Mid-Atlantic Section Fall Meeting 2020
Volume 65, Number 20
Friday–Sunday, December 4–6, 2020; Virtual
Session D01: Principles of Molecular and Cellular Biophysics: I |
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Chair: Lu Bai, Penn State University |
Saturday, December 5, 2020 9:00AM - 9:36AM |
D01.00001: Thermodynamic Modeling of Genome-wide Nucleosome Depleted Regions in Yeast Invited Speaker: Lu Bai Nucleosome positioning in the genome is essential for the regulation of many nuclear processes. We currently have limited capability to predict nucleosome positioning in vivo , especially the locations and sizes of nucleosome depleted regions (NDRs). Here, we present a thermodynamic model that incorporates the intrinsic affinity of histones, competitive binding of sequence-specific factors, and nucleosome remodeling to predict nucleosome positioning in budding yeast. The model shows that the intrinsic affinity of histones, at near-saturating histone concentration, is not sufficient in generating NDRs in the genome. However, the binding of a few factors, especially RSC towards GC-rich and poly(A/T) sequences, allows us to predict \textasciitilde 66{\%} of genome-wide NDRs. The model also shows that nucleosome remodeling activity is required to predict the correct NDR sizes. The validity of the model was further supported by the agreement between the predicted and the measured nucleosome positioning upon factor deletion or on exogenous sequences introduced into yeast. Overall, our model quantitatively evaluated the impact of different genetic components on NDR formation and illustrated the vital roles of sequence-specific factors and nucleosome remodeling in this process. [Preview Abstract] |
Saturday, December 5, 2020 9:36AM - 10:12AM |
D01.00002: Robotic Mapping and Generative Modelling of Cytokine Responses Invited Speaker: Paul Francois ~An immune response is by essence a collective computation. Starting with the initial activations of few T cells, a complex dance of immune actors self-organize over long time scales. Understanding how and why immune cells communicate with one another to perform this response could be key to a better understanding of personalized medicine and immunotherapy. In collaboration with Grégoire Altan-Bonnet (NIH), we have developed a pipeline to study, decode and model cytokine communications between T cells. I will show how simple machine learning allows to project the complex immune response into a 2D latent space, where immune parameters can be simply deconvolved. Remarkably, this suggests a simple, physics inspired, model of collective communication and computation. The model is highly reproducible in different conditions, and can be applied to different types of immune T cells. I will show how our approach can be used to predict quality of unknown antigen, and how it can potentially help to better estimate success of immunotherapies. [Preview Abstract] |
Saturday, December 5, 2020 10:12AM - 10:48AM |
D01.00003: The size of the immune repertoire of bacteria Invited Speaker: Vijay Balasubramanian Some bacteria and archaea possess an adaptive immune system that maintains a memory of past infections in viral DNA elements called spacers stored in the CRISPR loci of their genomes. This memory is used to mount targeted responses against later threats, but is remarkably shallow: it remembers only a few dozen to a few hundred viruses. I will present a statistical theory of CRISPR-based immunity that quantitatively explains the depth of bacterial immune memory in terms of a trade-off with fundamental constraints of the cellular biochemical machinery. Given known cross-reactive mechanisms of CRISPR interference and primed spacer acquisition, the theory further suggests that the incorporation of phage DNA also creates a significant threat of auto-immunity. I will show that balancing viral defense against auto-immunity predicts a scaling law that relates spacer length and CRISPR repertoire size. Analysis of a publicly available database of microbial genomes shows that this scaling law is realized empirically across prokaryotes, partly through proportionate use of different CRISPR-Cas types in strains carrying multiple loci. Finally, I will demonstrate population-level selection mechanisms that can generate the observed scaling law. [Preview Abstract] |
Saturday, December 5, 2020 10:48AM - 11:00AM |
D01.00004: Study on the Boron Derivatives for Tumor Cell Treatment Using Stereochemical Analysis Sungwon Chung, Richard Kyung Boron Neutron Capture Therapy (BNCT) is an emerging science as a tool in treating cancer. This paper explains the novel structures and stabilities of the boranes based on the molecular orbital theory. A common application for the boranes is the process of hydroboration resulting in the formation of organoboranes. They are important for a potential treatment for cancer known as Neutron Capture Therapy. In this paper, physicochemical effects of commercially used boranes were analyzed using computational simulations. The molecules were observed and analyzed using density functional theory. Such compounds can selectively kill affected cells without being toxic to non-affected cells. Electrostatic potential maps were also used to interpret the activity of the molecules. Molecular editing software was used to measure the optimization energy and the dipole moment of each molecule. Data shows the Octahydrotriborate is very stable and it has a higher boron to hydrogen ratio so that it can deliver more boron to the cancer affected site to perform Neutron Capture Therapy. [Preview Abstract] |
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