Bulletin of the American Physical Society
78th Annual Meeting of the Southeastern Section of the APS
Volume 56, Number 9
Wednesday–Saturday, October 19–22, 2011; Roanoke, Virginia
Session CC: Biophysics and Medical Physics |
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Chair: Ken Wong, Virginia Polytechnic Institute and State University Room: Crystal Ballroom C |
Thursday, October 20, 2011 10:45AM - 10:57AM |
CC.00001: Stochastic Modeling of Regulation of Gene Expression by Multiple Post-transcriptional Regulators Charles Baker, Tao Jia, Rahul Kulkarni New research indicates that post-transcriptional regulators, such as small RNAs (sRNAs), are key components of global regulatory networks. In particular, it has been discovered that these networks often comprise multiple sRNAs which control expression of a critical master regulator protein. However, the regulation of a single protein by multiple sRNAs is not currently well understood and the impact of multiple sRNA on stochastic gene expression remains unclear. To address these issues, we analyze a stochastic model of regulation of gene expression by multiple sRNAs. We derive exact closed form solutions for the regulated protein distribution, including compact expressions for its mean and variance. The derived results provide novel insights into the roles of multiple sRNAs in fine-tuning the noise in gene expression. In particular, we show that, in contrast to regulation by a single sRNA, multiple sRNAs provide a mechanism for independently controlling the mean and variance of the regulated protein distribution. [Preview Abstract] |
Thursday, October 20, 2011 10:57AM - 11:09AM |
CC.00002: Stochastic models of gene expression and post-transcriptional regulation Hodjat Pendar, Rahul Kulkarni, Tao Jia The intrinsic stochasticity of gene expression can give rise to phenotypic heterogeneity in a population of genetically identical cells. Correspondingly, there is considerable interest in understanding how different molecular mechanisms impact the 'noise' in gene expression. Of particular interest are post-transcriptional regulatory mechanisms involving genes called small RNAs, which control important processes such as development and cancer. We propose and analyze general stochastic models of gene expression and derive exact analytical expressions quantifying the noise in protein distributions [1]. Focusing on specific regulatory mechanisms, we analyze a general model for post-transcriptional regulation of stochastic gene expression [2]. The results obtained provide new insights into the role of post-transcriptional regulation in controlling the noise in gene expression. \\[4pt] [1] T. Jia and R. V. Kulkarni, {\it{Phys. Rev. Lett.}},{\bf{106}}, 058102 (2011) \\[0pt] [2] T. Jia and R. V. Kulkarni, {\it{Phys. Rev. Lett.}}, {\bf{105}}, 018101 (2010) [Preview Abstract] |
Thursday, October 20, 2011 11:09AM - 11:21AM |
CC.00003: Regulation by small RNAs via coupled degradation: mean-field and variational approaches Thierry Platini, Tao Jia, Rahul V. Kulkarni Regulatory genes called small RNAs (sRNAs) are known to play critical roles in cellular responses to changing environments. For several bacterial sRNAs, regulation is effected by coupled stoichiometric degradation with messenger RNAs (mRNAs). The nonlinearity inherent in this regulatory scheme implies that exact analytical solutions for the corresponding stochastic models are intractable. Based on the mapping of the master equation to a quantum evolution equation, we use the variational method (introduced by Eyink) to analyze a well-studied stochastic model for regulation by sRNAs. Results from the variational ansatz are in excellent agreement with stochastic simulations for a wide range of parameters, including regions of parameter space where mean-field approaches break down. The results derived provide new insights into sRNA-based regulation and will serve as useful inputs for future studies focusing on the interplay of stochastic gene expression and regulation by sRNAs. [Preview Abstract] |
Thursday, October 20, 2011 11:21AM - 11:33AM |
CC.00004: Utilizing protein networks to determine novel annotations Kenneth Shiao, Jerry Feng, Tina Doan, Andrey Gorin Proteins are a key element of life because they are involved in every metabolic process, yet a majority of proteins remain unannotated. Current chemical and physical annotation methods are inaccurate, inefficient, or expensive. Without proper annotation, understanding of organisms' metabolic pathways is limited. Based on the hypothesis that proteins with similar primary structures have similar characteristics, we theorize that a method for protein annotation can be developed using protein networking, which was previously thought to be useful in determining the evolutionary paths of proteins. A large, diverse database of proteins is used to connect protein fragments by using a preset identity threshold. With this method, unknown proteins are connected to known ones. By observing the number of links to proteins with annotated functions, a likely annotation candidate will be reached. This procedure can potentially facilitate the process of finding more accurate annotations. We have used and validated this approach to annotate putative uncharacterized proteins. Results will be presented at the conference. [Preview Abstract] |
Thursday, October 20, 2011 11:33AM - 11:45AM |
CC.00005: A Model Comparison for Characterizing Protein Motions from Structure Charles David, Donald Jacobs A comparative study is made using three computational models that characterize native state dynamics starting from known protein structures taken from four distinct SCOP classifications. A geometrical simulation is performed, and the results are compared to the elastic network model and molecular dynamics. The essential dynamics is quantified by a direct analysis of a mode subspace constructed from ANM and a principal component analysis on both the FRODA and MD trajectories using root mean square inner product and principal angles. Relative subspace sizes and overlaps are visualized using the projection of displacement vectors on the model modes. Additionally, a mode subspace is constructed from PCA on an exemplar set of X-ray crystal structures in order to determine similarly with respect to the generated ensembles. Quantitative analysis reveals there is significant overlap across the three model subspaces and the model independent subspace. These results indicate that structure is the key determinant for native state dynamics. [Preview Abstract] |
Thursday, October 20, 2011 11:45AM - 11:57AM |
CC.00006: Using blocking peptides to control and analyze the mechanical properties of single fibrin fibers Pranav Maddi, E. Tim O'Brien III, Oleg Gorkun, Michael R. Falvo Fibrin is the main structural protein involved in blood clotting, and exhibits high strength and elasticity. Fibrin study traditionally focuses on fully formed clots, whereas we employ new AFM nanoManipulation techniques to study single fibrin fiber mechanics. We used 4 and 10 residue peptides to interfere with the knob-hole and $\alpha$C interactions involved in fibrin polymerization to evaluate the contribution of each interaction to the fiber's mechanical properties. We varied the concentration of each peptide present during polymerization to find the concentration that inhibited polymerization by half. The presence of either peptide during fibrin polymerization did not affect single fiber breaking strain ($\frac{\Delta L}{L_{0}}$). The breaking force of all treated fibers reduced from 10-50nN to 2-10nN, suggesting treated fibers are thinner or are the same diameter with some inhibition of interactions. Fibers polymerized with the knob-hole targeting peptide visibly lost elasticity after 100\% strain, while fibers polymerized with the $\alpha$C targeting peptide lost elasticity after reaching 150\% strain, suggesting that the knob-hole interactions control single fiber elasticity. [Preview Abstract] |
Thursday, October 20, 2011 11:57AM - 12:09PM |
CC.00007: A biomimetic model for internal fluid transport based on physiological systems in insects Yasser Aboelkassem, Anne Staples Biomimetics is an increasingly important field in applied science that seeks to imitate systems and processes in nature to design improved engineering devices. In this study, we are inspired by insect respiratory systems, and model, analytically and numerically, the air transport within a single model insect tracheal tube. The tube wall undergoes localized, non- propagative rhythmic contractions. A theoretical analysis based on lubrication theory is used to model the problem at low Reynolds number. Results are then validated by performing meshfree computations based on the method of fundamental solutions (MFS). This meshfree numerical approach is then used to investigate the airflow in more complex geometries: a channel with multiple branching segments and various wall contraction regimes. This study presents a new biomimetic mechanism for valveless pumping that might guide efforts to fabricate novel microfluidic devices with improved efficiency that mimic features of physiological systems in insects. [Preview Abstract] |
Thursday, October 20, 2011 12:09PM - 12:21PM |
CC.00008: Locomotion of Paramecium in patterned environments Eun-Jik Park, Aja Eddins, Junil Kim, Sung Yang, Saikat Jana, Sunghwan Jung Ciliary organisms like Paramecium Multimicronucleatum locomote by synchronized beating of cilia that produce metachronal waves over their body. In their natural environments they navigate through a variety of environments especially surfaces with different topology. We study the effects of wavy surfaces patterned on the PDMS channels on the locomotive abilities of Paramecium by characterizing different quantities like velocity amplitude and wavelength of the trajectories traced. We compare this result with the swimming characteristics in straight channels and draw conclusions about the effects of various patterned surfaces. [Preview Abstract] |
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