Bulletin of the American Physical Society
APS March Meeting 2015
Volume 60, Number 1
Monday–Friday, March 2–6, 2015; San Antonio, Texas
Session J47: DBIO Thesis Prize: Biological Dynamics and Networks |
Hide Abstracts |
Sponsoring Units: DBIO Chair: Vijay Singh, Emory University Room: 217B |
Tuesday, March 3, 2015 2:30PM - 3:06PM |
J47.00001: DBIO Thesis Prize Talk Invited Speaker: Lei Dai |
Tuesday, March 3, 2015 3:06PM - 3:18PM |
J47.00002: Spin glass model for dynamics of cell reprogramming Sai Teja Pusuluri, Alex H. Lang, Pankaj Mehta, Horacio E. Castillo Recent experiments show that differentiated cells can be reprogrammed to become pluripotent stem cells [1]. The possible cell fates can be modeled as attractors in a dynamical system, the ``epigenetic landscape.'' Both cellular differentiation and reprogramming can be described in the landscape picture as motion from one attractor to another attractor. We perform Monte Carlo simulations in a simple model of the landscape [2]. This model is based on spin glass theory and it can be used to construct a simulated epigenetic landscape starting from the experimental genomic data. We re-analyse data from several cell reprogramming experiments [3-6] and compare with our simulation results. We find that the model can reproduce some of the main features of the dynamics of cell reprogramming. \\[4pt] [1] Takahashi and Yamanaka. Cell, 126:663, 2006.\\{ } [2] Alex H. Lang, Hu Li, James J. Collins, and Pankaj Mehta. PLoS Comput Biol, 10:8, 2014.\\{ } [3] Hanna et.al. Nature, 462:7273, 2009.\\{ } [4] Rais et al, Nature 502:7469, 2013.\\{ } [5] Polo et al, Cell 151:7, 2012.\\{ } [6] Fluri et.al. Nat Meth, 9:5, 2012. [Preview Abstract] |
Tuesday, March 3, 2015 3:18PM - 3:30PM |
J47.00003: Collective Calcium Signaling of Defective Multicellular Networks Garrett Potter, Bo Sun A communicating multicellular network processes environmental cues into collective cellular dynamics. We have previously demonstrated that, when excited by extracellular ATP, fibroblast monolayers generate correlated calcium dynamics modulated by both the stimuli and gap junction communication between the cells. However, just as a well-connected neural network may be compromised by abnormal neurons, a tissue monolayer can also be defective with cancer cells, which typically have down regulated gap junctions. To understand the collective cellular dynamics in a defective multicellular network we have studied the calcium signaling of co-cultured breast cancer cells and fibroblast cells in various concentrations of ATP delivered through microfluidic devices. Our results demonstrate that cancer cells respond faster, generate singular spikes, and are more synchronous across all stimuli concentrations. Additionally, fibroblast cells exhibit persistent calcium oscillations that increase in regularity with greater stimuli. To interpret these results we quantitatively analyzed the immunostaining of purigenic receptors and gap junction channels. The results confirm our hypothesis that collective dynamics are mainly determined by the availability of gap junction communications. [Preview Abstract] |
Tuesday, March 3, 2015 3:30PM - 3:42PM |
J47.00004: Microfluidic study of environmental control of genetic competence in Streptococcus mutans Minjun Son, Seyedehdelaram Ghoreishilangroudi, Sang-Joon Ahn, Robert Burne, Stephen Hagen The bacterial pathogen $Streptococcus$ $mutans$ has the ability to enter a transient state of genetic competence in which it can integrate exogenous DNA. It regulates the competent state in response to several environmental inputs that include two quorum sensing peptides (CSP and XIP) as well as pH and other variables. However the interplay of these variables in regulating the competent state is poorly understood. We are using microfluidics to isolate and control environmental inputs and examine how the competence regulatory circuit responds at the single cell level. Our studies reveal that the pH of the growth environment plays a critical role in determining how cells respond to the quorum sensing signals: The response to both peptides is sharply tuned to a narrow window of near-neutral pH. Within this optimal pH range, a population responds unimodally to a XIP stimulus, and bimodally to CSP; outside this range the response to both signals is suppressed. Because a growing $S$. $mutans$ culture acidifies its medium, our findings suggest that the passage of the pH through the sensitivity window transiently activates the competence circuit. In this way a sharply tuned environmental response gives $S$. $mutans$ fine control over the duration of its competent state. [Preview Abstract] |
Tuesday, March 3, 2015 3:42PM - 3:54PM |
J47.00005: Dynamic information routing in complex networks Christoph Kirst, Marc Timme, Demian Battaglia Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how information may be specifically communicated and dynamically routed in these systems is not well understood. Here we demonstrate that collective dynamical states systematically control patterns of information sharing and transfer in networks, as measured by delayed mutual information and transfer entropies between activities of a network's units. For oscillatory networks we analyze how individual unit properties, the connectivity structure and external inputs all provide means to flexibly control information routing. For multi-scale, modular architectures, we resolve communication patterns at all levels and show how local interventions within one sub-network may remotely control the non-local network-wide routing of information. This theory helps understanding information routing patterns across systems where collective dynamics co-occurs with a communication function. [Preview Abstract] |
Tuesday, March 3, 2015 3:54PM - 4:06PM |
J47.00006: Strain induced critical behavior in athermal biopolymer networks Abhinav Sharma, Albert Licup, Robbie Rens, Michael Sheinman, Karin Jansen, Gijse Koenderink, Fred MacKintosh Biopolymer networks exhibit highly interesting mechanical behavior. An instructive model system is that of a network composed of rope-like filaments--zero resistance to compression but finite resistance to stretching. For networks with connectivity below Maxwell point,there is no elastic modulus for small deformations. However,when networks are subjected to an external strain, stiffness emerges spontaneously beyond a critical strain. We demonstrate that the spontaneous emergence of elasticity is analogous to a continuous phase transition. The critical point is not fixed but depends on the geometry of the underlying network.The elastic behavior near the critical point can be described analogous to that of Magnetization in ferromagnetic material near the curie temperature.Surprisingly, the critical exponents are independent of the dimensionality and depend only on the average connectivity in the network.By including bending interactions in the rope network, we can capture the mechanical behavior of biologically relevant networks.Bending rigidity acts as a coupling constant analogous to the external magnetic field in a ferromagnetic system.We show that nonlinear mechanics of collagen are successfully captured by our framework of regarding nonlinear mechanics as a critical phenomenon [Preview Abstract] |
Tuesday, March 3, 2015 4:06PM - 4:18PM |
J47.00007: Pattern Learning, Damage and Repair within Biological Neural Networks Theodore Siu, Kate Fitzgerald O'Neill, Troy Shinbrot Traumatic brain injury (TBI) causes damage to neural networks, potentially leading to disability or even death. Nearly one in ten of these patients die, and most of the remainder suffer from symptoms ranging from headaches and nausea to convulsions and paralysis. In vitro studies to develop treatments for TBI have limited in vivo applicability, and in vitro therapies have even proven to worsen the outcome of TBI patients. We propose that this disconnect between in vitro and in vivo outcomes may be associated with the fact that in vitro tests assess indirect measures of neuronal health, but do not investigate the actual function of neuronal networks. Therefore in this talk, we examine both in vitro and in silico neuronal networks that actually perform a function: pattern identification. We allow the networks to execute genetic, Hebbian, learning, and additionally, we examine the effects of damage and subsequent repair within our networks. We show that the length of repaired connections affects the overall pattern learning performance of the network and we propose therapies that may improve function following TBI in clinical settings. [Preview Abstract] |
Tuesday, March 3, 2015 4:18PM - 4:30PM |
J47.00008: In silico evolution of oscillatory dynamics in biochemical networks Md Zulfikar Ali, Ned S. Wingreen, Ranjan Mukhopadhyay We are studying in silico evolution of complex, oscillatory network dynamics within the framework of a minimal mutational model of protein-protein interactions. In our model we consider two different types of proteins, kinase (activator) and phosphatase(inhibitor). In our model. each protein can either be phosphorylated(active) or unphospphorylated (inactive), represented by binary strings. Active proteins can modify their target based on the Michaelis-Menten kinetics of chemical equation. Reaction rate constants are directly related to sequence dependent protein-protein interaction energies. This model can be stuided for non-trivial behavior e.g. oscillations, chaos, multiple stable states. We focus here on biochemical oscillators; some questions we will address within our framework include how the oscillatory dynamics depends on number of protein species, connectivity of the network, whether evolution can readily converge on a stable oscillator if we start with random intitial parameters, neutral evolution with additional protein components and general questions of robustness and evolavability. [Preview Abstract] |
Tuesday, March 3, 2015 4:30PM - 4:42PM |
J47.00009: Uncertainty of Prebiotic Scenarios: The Case of the Non-Enzymatic Reverse Tricarboxylic Acid Cycle Dmitry Zubarev, Dmitrij Rappoport, Alan Aspuru-Guzik We consider the much discussed hypothesis of the primordial nature of the non-enzymatic reverse tricarboxylic acid (rTCA) cycle and describe a modeling approach that quantifies the uncertainty of this hypothesis due to the combinatorial aspect of the constituent chemical transformations. Our results suggest that a) rTCA cycle belongs to a degenerate optimum of auto-catalytic cycles, and b) the set of targets for the investigations of the origin of the common metabolic core should be significantly extended. [Preview Abstract] |
Tuesday, March 3, 2015 4:42PM - 4:54PM |
J47.00010: Extracting Hidden Hierarchies in 3D Distribution Networks Carl Modes, Marcelo Magnasco, Eleni Katifori Natural and man-made transport webs are frequently dominated by dense sets of nested cycles. The architecture of these networks -- the topology and edge weights -- determines how efficiently the networks perform their function. Yet, the set of tools that can characterize such a weighted cycle-rich architecture in a physically relevant, mathematically compact way is sparse. In order to fill this void, we have developed a new algorithm that rests on an abstraction of the physical `tiling' in the case of a two dimensional network to an effective tiling of an abstract surface in space that the network may be thought to sit in. Generically these abstract surfaces are richer than the plane and upon sequential removal of the weakest links by edge weight, neighboring tiles merge and a tree characterizing this merging process results. The properties of this characteristic tree can provide the physical and topological data required to describe the architecture of the network and to build physical models. This new algorithm can be used for automated phenotypic characterization of any weighted network whose structure is dominated by cycles, such as mammalian vasculature in the organs, the root networks of clonal colonies like quaking aspen, or the force networks in jammed granular matter. [Preview Abstract] |
Tuesday, March 3, 2015 4:54PM - 5:06PM |
J47.00011: Dynamic maintenance of stochastic molecular clusters on cell membranes Andrew Mugler, Martijn Wehrens, Pieter Rein ten Wolde Clustering of molecules on cell membranes is a widely observed phenomenon. A key example is the oncoprotein Ras. Maintenance of Ras clusters has been linked to proper Ras signaling. Yet, the mechanism by which Ras clusters are maintained remains unclear. Recently it was discovered that activated Ras promotes further Ras activation. We show using particle-based simulation that this positive feedback link is sufficient to produce persistent clusters of active Ras molecules via a dynamic nucleation mechanism. The cluster statistics are consistent with experimental observations. Interestingly, our model does not support a Turing regime of macroscopic reaction-diffusion patterning. This means that the clustering we observe is a purely stochastic effect, arising from the coupling of the positive feedback network with the discrete nature of individual molecules. These findings underscore the importance of stochastic and dynamic properties of reaction diffusion systems for biological behavior. [Preview Abstract] |
Tuesday, March 3, 2015 5:06PM - 5:18PM |
J47.00012: Sensing multiple ligands with single receptor Vijay Singh, Ilya Nemenman Cells use surface receptors to measure concentrations of external ligand molecules. Limits on the accuracy of such sensing are well-known for the scenario where concentration of one molecular species is being determined by one receptor [Endres\footnote{\textbf{Phys. Rev. Lett. 103, 158101 (2009)}}]. However, in more realistic scenarios, a cognate (high-affinity) ligand competes with many non-cognate (low-affinity) ligands for binding to the receptor. We analyze effects of this competition on the accuracy of sensing. We show that maximum-likelihood statistical inference allows determination of concentrations of multiple ligands, cognate and non-cognate, by the same receptor concurrently. While it is unclear if traditional biochemical circuitry downstream of the receptor can implement such inference exactly, we show that an approximate inference can be performed by coupling the receptor to a kinetic proofreading cascade. We characterize the accuracy of such kinetic proofreading sensing in comparison to the exact maximum-likelihood approach. [Preview Abstract] |
Tuesday, March 3, 2015 5:18PM - 5:30PM |
J47.00013: Dynamic phases in control and information processing biological circuits Suriyanarayanan Vaikuntanathan Recent work using the mathematical framework of large deviation theory has shown that fluctuations about the steady state can have a particularly rich structure even in extremely simple non-equilibrium systems [Phys. Rev. E. 89, 062108, 2014]. In certain instances the fluctuations can encode the presence of a dynamical phase with properties distinct from those of the steady state of the system. The transition between these two regimes is akin to a first order thermodynamic phase transition. Specifically, it implies an extreme sensitivity of the system to changes in certain sets of parameters. I will show that such dynamical phase transitions can serve as a general organizing principle to understand biological circuits that are involved in information processing and control. I will focus on two specific examples: adaptation control in E. coli chemotaxis and ultra sensitive response of the E. coli flagella motor, to illustrate these calculations. This work also elucidates the role played by energy dissipation in ensuring control and suggests general guidelines for the construction of robust non equilibrium circuits that perform various specified functions. [Preview Abstract] |
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