Bulletin of the American Physical Society
APS March Meeting 2019
Volume 64, Number 2
Monday–Friday, March 4–8, 2019; Boston, Massachusetts
Session P64: Systems Biology and Stochasticity in Biological Networks |
Hide Abstracts |
Sponsoring Units: DBIO Chair: Po-Yi Ho, Harvard University Room: BCEC 259B |
Wednesday, March 6, 2019 2:30PM - 2:42PM |
P64.00001: The effects of the circadian clock on cell cycle regulation in cyanobacteria Po-Yi Ho, Ariel Amir The circadian clock affects the timing of cell divisions in cyanobacteria such that cells tend not to divide near dawn or dusk. The mechanism underlying the coupling between the clock and division remains unclear. We developed a phenomenological model that captures the single-cell statistics of the timing of cell divisions in the cyanobacteria Synechococcus elongatus. The model reproduces experimental results for both the wildtype and a clock-deletion mutant, in constant as well as periodic environments. We further study, within the model, how coupling division to the clock may affect the fitness of the population as a whole. |
Wednesday, March 6, 2019 2:42PM - 2:54PM |
P64.00002: Molecular search for a target with a conformational change: First passage time approach Jaeoh Shin, Anatoly Boris Kolomeisky The process of a molecule search for its target is ubiquitous in Nature. During the process, the molecule is often moving in complex inhomogeneous environments with random transitions between different dynamic modes. A notable example is transcription factors searching for target sequences on a DNA. Here we study the search dynamics with stochastic transitions between two conformations in a one-dimensional lattice. Using the first passage time approach, we explicitly analyze the mean search time for arbitrary system parameters. We found that there are several dynamic regimes in the search dynamics, which are determined by the relative values of the relevant length scales in the system. Moreover, the search time can be minimized by the combination of two different modes. Intriguingly, a recent analysis of hOGG1 protein shows that the protein moves on a DNA in the optimal parameter range. Additionally, we construct a general dynamic phase diagram. |
Wednesday, March 6, 2019 2:54PM - 3:06PM |
P64.00003: Timing in single cells: fundamental limits and mechanisms for noise suppression Ruoshi Yuan, Jiawei Yan, Glenn Vinnicombe, Johan Paulsson Precise timing can be advantageous in many biological processes, whether to coordinate events in the cell cycle, determine the duration of cell states, or create reliable rhythms. However, it can be hard to achieve because chemical reactions often produce exponentially distributed waiting times for individual events even when the rates are perfectly constant. Here we develop mathematical theories to dissect classes of timing mechanisms in single cells -- derive fundamental limits and optimal strategies, and how simpler and realistic circuits would approach the optimal. For some broad but naturally occurring distributions, the noise is limited by the inverse quartic root of the average number of states, and even that requires intricate mechanisms. We discuss how known synthetic and natural genetic timers appear to employ these mechanisms to create precise rhythms or accurate multigenerational cell fate decisions. |
Wednesday, March 6, 2019 3:06PM - 3:18PM |
P64.00004: Non-steady-state dynamics and growth optimization of scalable flux networks Wei-Hsiang Lin, Edo Kussell, Christine Jacobs-Wagner Exponential growth naturally arises in many biochemical, cellular, ecological and economic flux networks. While the majority of mathematical models focus on balanced, steady-state growth, the general existence criteria for a stable long-term growth rate remains unclear. Here, we introduce a theoretical framework by connecting ergodic theory to the long-term behavior of flux networks. We investigate the convergence of exponential growth rate for a broad class of nonlinear flux networks, constructed by scalable flux functions. |
Wednesday, March 6, 2019 3:18PM - 3:30PM |
P64.00005: Temporal precision of molecular events with regulation and feedback Shivam Gupta, Sean Fancher, Hendrik Korswagen, Andrew Mugler Cellular events such as cell migration, division, and cell differentiation rely on precise timing. Molecular events inside cells are highly stochastic, and yet cells trigger events with high timing precision. We explore the effect of gene regulatory networks on first passage timing precision. We devise a method to find the global regulation function between the regulator and target gene which optimizes the timing precision. This method can be applied to a range of networks involving two genes such as regulation by an external species combined with autoregulatory feedback on the target gene itself. We confirm that feedback alone is not helpful in increasing timing precision. However, if a regulator is present then the combination of feedback and regulation is more beneficial than regulation alone. Specifically, higher timing precision is achieved by positive feedback when the regulator is high and negative feedback when the regulator is low. Our results are relevant to experimental gene regulatory systems where high timing precision is crucial, such as neuroblast migration during Caenorhabditis elegans development. |
Wednesday, March 6, 2019 3:30PM - 3:42PM |
P64.00006: Fluid effects in spatial gradient sensing Nicholas Licata The ability to measure shallow gradients in a chemical concentration plays an important role in a number of cellular processes, from chemotaxis to wound healing and development. Berg and Purcell were the first to demonstrate that diffusion sets a fundamental physical limit to the accuracy with which a cell can measure chemical concentrations. There is a growing body of physical literature concerning many aspects surrounding cellular concentration sensing. This includes the effects of receptor cooperativity, cellular shape and memory, and collective effects in multicellular sensing. Notably absent from this list is the role of fluid flow. In this talk, we discuss the problem of a low Reynolds number spherical squirmer directly sensing spatial gradients in concentration. By constructing a renormalization group improved solution of the appropriate advection-diffusion equation, we derive physical limits to the accuracy of spatial gradient sensing by swimming cells. At small Péclet number, advection is a singular perturbation in the problem. As a result, the sensory limits differ qualitatively from the case of pure diffusion which neglects the effects of fluid flow. |
Wednesday, March 6, 2019 3:42PM - 3:54PM |
P64.00007: From structural to temporal and spatial hierarchies in
heteroclinic networks Hildegard Meyer-Ortmanns, Maximilian Voit We construct heteroclinic networks from generalized Lotka-Volterra equations of winnerless competition. Our heteroclinic orbits connect saddle-fixed points characterized by the temporary survival of single species. By an appropriate choice of rates in the predation matrix we implement a structural hierarchy in the attractor space that consists of iterated heteroclinic cycles of heteroclinic cycles. This induces a hierarchy in time scales that amounts to iterated oscillatory modulations of fast oscillations on slower time scales. We indicate how the temporal hierarchy translates to spatial scales by coupling these heteroclinic networks on a spatial grid. Our concrete realization then leads to rock-paper-scissors games, played on several scales simultaneously. Applications of this kind of heteroclinic dynamics are transient neuronal dynamics in the brain, possibly related to the binding problem, and chunking dynamics, or transient dynamics in ecological systems with games played in parallel on the scale of individual species as well as of populations and metapopulations. |
Wednesday, March 6, 2019 3:54PM - 4:06PM |
P64.00008: The Mechanosensory Hair Bundles of the Inner Ear Distinguish Sinusoidal Forces from Noise Best When They Oscillate Spontaneously but Remain on the Verge of Quiescence Daibhid O Maoileidigh, Joshua D Salvi, Jim Hudspeth Hair bundles are the sensors that detect mechanical stimuli in the hearing and balance organs of vertebrates. Because these sensors are mechanically active, they often exhibit limit-cycle oscillations. A general theory of active hair-bundle dynamics predicts that a bundle's behavior may be controlled by its mechanical load. We confirm these predictions experimentally by employing a feedback system to change the mechanical load of individual hair bundles. In experiments, we observe that a noisy bundle’s average displacement and entrainment in response to frequency-detuned sinusoidal forcing peak when the bundle spontaneously oscillates near supercritical or subcritical Hopf bifurcations. Owing to two distinct mechanisms intrinsic to the bifurcations, we also observe stochastic resonance in a bundle’s displacement and entrainment, which can be eliminated by changing the bundle’s operating point. Because the mechanism for stochastic resonance depends on the bifurcation type, noise allows us to distinguish the two kinds of Hopf bifurcation. The results detailed here apply to all detectors possessing a Hopf bifurcation. |
Wednesday, March 6, 2019 4:06PM - 4:18PM |
P64.00009: Trade-off between organelle number and size fluctuations suggest that a limiting pool of building blocks biophysically constrains organelle biogenesis Kiandokht Panjtan Amiri, Asa Kalish, Luke Nadell, Shankar Mukherji One of the hallmarks of the eukaryotic cell is its organization into distinct spatial compartments known as organelles, that mediate processes critical to cellular function. While the regulation of the abundance and size of organelles plays a profound role in the function and health of a cell, very little is known about the biophysical underpinnings of organelle size regulation. To achieve mechanistic insight into organelle size regulation, we examined three general limits of a comprehensive mathematical model of organelle growth, in which growth either occurs at a constant rate, is regulated by a negative feedback process, or is constrained by a limiting-pool of building blocks. Experimentally, we tested our model on lipid droplets and peroxisomes, two key organelles in cellular lipid metabolism, using quantitative confocal fluorescent microscopy to obtain joint probability distributions of organelle number and size at a single cell resolution. Statistical analyses of our models over a large parameter space and comparison to mutant strains of yeast are consistent with a limiting-pool of organelle building blocks biophysically constraining the size of lipid droplets and peroxisomes. |
Wednesday, March 6, 2019 4:18PM - 4:30PM |
P64.00010: Consequences of noise in bacterial communication Ghazaleh Ostovar, James Boedicker Bacterial quorum sensing is a phenomenon associated with secreting signaling molecules called autoinducers into the extracellular environment. Individual bacteria can regulate gene expression by detection and response to autoinducers. On the other hand, gene expression which involves a series of biochemical interaction is a stochastic process. Noise in gene expression can lead to emergence of different subpopulations with distinct behaviors within an isogenic population of bacteria.We model the case in which production of an exoenzyme under quorum sensing regulation can increase the growth rate of individuals. This exoenzyme, representing a public good, can freely diffuse into the environment and breakdown a substrate. We verify under what conditions heterogeneity in communication networks and division of tasks between two different phenotypes are metabolically beneficial for the whole population. We show the optimum initial ratio of these two subpopulations depends on the energetic cost associated with each task and the benefit provided by the trait. |
Wednesday, March 6, 2019 4:30PM - 4:42PM |
P64.00011: Optimal control of aging in complex networks Eric Sun, Thomas Michaels, L Mahadevan Aging is a shared process of biological and technical systems. As structural and organizational complexity increases, the phenomenon of aging--the progressive increase in the probability of death or decay--arises as an emergent property. A key question is how to maximize longevity of an aging system at minimal cost of maintenance and intervention. Here, we answer this question using optimal control theory and machine learning on a network model of aging. We derive and numerically validate optimal protocols for repair that emerge from a balance between maximizing system healthspan and minimizing the overall cost of repair. These protocols may motivate the design of rational strategies for delaying aging in complex systems. |
Wednesday, March 6, 2019 4:42PM - 4:54PM |
P64.00012: Integrating epigenetics to construct gene regulatory networks Abhijeet Sonawane, Kimberly Renee Glass The biological processes that drive cellular function can be modeled by a complex network of interactions between regulators (transcription factors) and their targets(genes), summarized by gene regulatory networks (GRNs). The cell’s “epigenetic state” governs the potential targeting of genes by influencing chromatin accessibility. However, integrating such information to construct GRNs remains a challenge. Here, we develop an approach SPIDER using epigenetic information (DNase-I Seq data) and message-passing algorithm to estimate networks between transcription factors and genes in multiple cell lines. We validate our predictions against public ChIP-Seq data. SPIDER was more accurate, in predicting GRNs that other methods that integrate epigenetics compared to existing methods and improved detection of cell-line specific interactions in respective GRNs. SPIDER was also able to identify indirect interactions when putative motifs are absent in the regulatory region of genes, but with ChIP-Seq evidence of regulation. The epigenetically-informed GRNs from SPIDER can be used to identify targets of key regulators, or regulators of important genes from an experiment, in the given context of the cell-type. |
Wednesday, March 6, 2019 4:54PM - 5:06PM |
P64.00013: Kinetic PDE models of cell size control: size blow-up and evolution of growth rate Mingtao Xia, Thomas Chou We derive kinetic equations for the distribution of cells in age, size, and added size after birth. These kinetic PDE models incorporate timer, sizer, and adder mechanisms of cell division. After properly constructing cell division rates, we show that an sizer-adder PDE model can lead to diverging cell sizes, particularly if the distribution of daughter cells immediately after birth is broad. The kinetic models are also extended to include growth rate correlation between successive generations. As the population evolves, so does the distribution of cellular growth rates. Representative numerical solutions to our PDEs will be presented. |
Wednesday, March 6, 2019 5:06PM - 5:18PM |
P64.00014: Exploiting a Percolation Transition for the Clustering of Noisy Gene Expression Data Steffen Werner, Tom S Shimizu, Greg Stephens Gene expression largely determines the fate of individual cells and ultimately influences development and behaviour of entire organisms. Thus, the ability to assess the abundance of mRNA intermediates of gene expression on a genome-wide scale (down to single cell resolution) promises to revolutionize our understanding of biological processes. While the collection of such data is rapidly growing thanks to experimental innovations, researchers face the challenge of identifying meaningful patterns and often need to discriminate subtle signals from a high noise floor. Here, we describe a density-based clustering approach that takes advantage of a percolation transition generically arising in random data to help discriminate meaningful patterns of variation from noise. The method allows clustering parameters to be defined by statistical properties of the data itself, thus obviating arbitrary parameter choices or detailed knowledge of experimental noise sources. By applying this approach to data from single cells to whole organisms, we reveal known as well as unknown modules of co-regulated genes. |
Wednesday, March 6, 2019 5:18PM - 5:30PM |
P64.00015: Dynamical network formation of C. elegans Ken Nagai, Hiroshi Ito, Takuma Sugi Ordered collective motions are ubiquitous among locally interacting living beings. Experimental systems have been developed for non-living self-propelled particles, bacteria, and mammalian cells on a substrate, but there have been no experimental systems of multicellular organisms, which have much more complex behaviours, with various controllable parameters over a wide range. |
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