List of invited speakers & talk titles

Speakers and titles for 102nd Statistical Mechanics Conference

 Larry Abbott
Title: Controlling Chaotic Activity in Neural Networks
Abstract: Large, strongly coupled neural networks tend to produce chaotic spontaneous activity. This might appear to make them unsuitable for generating reliable sensory responses or repeatable motor patterns. However, this is not the case. Inputs can induce a phase transition, leading to responses uncontaminated by chaotic "noise". Likewise, appropriately trained feedback units can control the chaos, resulting in a wide variety of repeatable output patterns.

Uri Alon
Title: On the Evolution of Modularity

David Bensimon
Title: Single cell physiology

Bill Bialek
Title: How much can we calculate?: Predicting the structure of genetic networks from an optimization principle

David Botstein
Title: A few examples of quantitative issues in biology

G. Bhanot
Title: Scales of selection events-local or genome wide?
Coauthors: Gabriela Alexe, Anupama Reddy, Michael Seiler, Todd Michael, Lee Cronk, Boris Shraiman, Richard Neher, Lane McIntosh, Ajish George, Ravi Sachidanandam, Arnold J Levine, Gyan Bhanot * Joint first authors
Abstract: Cases of hypercholesterolemia are often associated with fat- and cholesterol-rich diets; in spite of this, the Maasai people of East Africa live on a diet consisting mainly of milk, meat and blood and yet, largely avoid hypercholesterolemia and arteriosclerosis, do not suffer from gallstones, have low blood pressures and low rates of cardiac incidents. In the 1970s, radioactively labeled diet studies identified a negative feedback mechanism in the Maasai which maintained cholesterol homeostasis by co-regulating endogenous cholesterol synthesis and dietary cholesterol absorption. These studies suggested, but did not prove, a genetic origin for this phenomenon. The Maasai were also found to have high serum levels of IgA as compared to Caucasians; selected perhaps on account of the pressure to survive in a highly pathogenic environment. Using a number of association significance tests on the recently released HapMap III data, we identified 5,173 polymorphisms that are significantly associated with the Maasai (MKK) samples in the HapMap III dataset compared to all other samples/populations (p-value <10-12). Compared to the distribution of randomly selected polymorphisms in MKK, we found that a subset of 697 polymorphisms formed a clique across all MKK founders with highly significant pair-wise correlation (r2>0.95, Wilcoxon p-value<10-16). A large number of the 5,173 polymorphisms are within or near genes known to be associated with the lipid metabolism pathway. Many are in or close to genes whose dysfunction is known to be associated with arteriosclerosis, coronary artery disease, hypercholesterolemia, hyperlipidemia, hyperlipoprotemia, hypertriglyceridemia, and cardiovascular and metabolic disorders. Many of the other polymorphisms are in regions involving immune system genes. 120 of the 5,173 and 8 of the 697 polymorphisms are located in the human orthologous regions of the "Diet1" locus in mouse strain C57BL/6ByJ (B6By), where polymorphisms are known to induce resistance to diet-induced hypercholesterolemia. Our results strongly suggest that the Maasai have specific genetic alterations compared to other populations in genes involved in metabolic and immune regulation pathways that protect them against hypercholesterolemia and from pathogenic organisms. Such strong selection presumably derives from inbreeding, a relatively small population size, a fat-rich diet, long exposure to a steady but hostile environment, and unusual social customs.

Freeman Dyson
Title: Why Negative Specific Heat is Good for Life

Daniel Fisher
Title: Quantative issues in evolutionary dynamics

Michael Fisher
Title: Biology, Medicine, and Engineering : Roles for Theory ?

Peter Fratzl
Title: Tissue growth and remodelling

Bill Gelbart
Title: What does evolution have to say about our being able to make a virus from scratch?
Abstract: Even though viruses are only arguably alive, they do evolve. And they evolve faster and all-too-often "better" than any living organism (or its immune system). Because they are obligate parasites, depending on their hosts for almost everything, their genomes can be orders of magnitude smaller than those of independent, living, things. Often they involve only a few (i.e., fewer than 10) genes, and consist of just a few components. The first viruses to be reconstituted from purified components were plant viruses consisting of a single RNA molecule and a special number of copies of a single capsid protein that self-organize to form a protective shell for the genome. To date, it has not proved possible to reconstitute an enveloped mammalian virus "from scratch", i.e., to create test-tube conditions for spontaneous self-assembly of the infectious virus from its purified components - RNA genome, virally-encoded capsid protein, lipid bilayer, and virally-encoded membrane proteins. In my talk I describe ongoing efforts to make an enveloped virus without help from its host cell, and discuss what we can learn from our partial successes.

John Hopfield
Title: What is thinking? The dynamics of mental exploration

Mehran Kardar
Title: Thymic Selection of T-Cell Receptors as an Extreme Value Problem
Abstract: T lymphocytes (T cells) orchestrate adaptive immune responses upon activation. T-cell activation requires sufficiently strong binding of T-cell receptors on their surface to short peptides (p) derived from foreign proteins, which are bound to major histocompatibility gene products (displayed on antigen-presenting cells). A diverse and self-tolerant T-cell repertoire is selected in the thymus. We map thymic selection processes to an extreme value problem and provide an analytic expression for the amino acid compositions of selected T-cell receptors (which enable its recognition functions).
A. Kosmrlj, A. K. Chakraborty, M. Kardar, and E. I. Shakhnovich, Phys. Rev. Lett. 103, 068103 (2009). http://link.aps.org/doi/10.1103/PhysRevLett.103.068103

Stefan Klumpp
Title: Transcription of ribosomal RNA - a central task for rapid bacterial growth
Abstract: Synthesis of ribosomes is essential for rapid cell growth and fast growing cells, from bacteria to cancer cells, devote a substantial fraction of their transcriptional activity to making ribosomal RNA (rRNA). Transcription of rRNA is typically characterized by dense traffic of RNA polymerases along the rRNA genes. However, dense traffic is susceptible to traffic jams which may arise inevitably due to stochastic pausing of the polymerases. Theoretical analysis of rRNA synthesis from a "traffic viewpoint" provides a unique perspective towards the physiological constraints and regulatory principles governing ribosome synthesis in bacterial and eukaryotic cells.

Stan Leibler
Title: Selection and survival in microbial populations
Abstract: Synthetic microbial systems present a unique opportunity for a quantitative study of selection in dynamic populations. I will present a short review of some classical arguments in theory of natural selection, in particular of those connected with origins of cooperation. I will show how simple experiments with bacteria could help to make these arguments precise and to "demystify" the whole subject.

This work has been done in collaboration with John Chuang, and Olivier Rivoire.

Raphael Levine
Title: Maximal entropy thermodynamic-like analysis of cell signaling with application to early processes in carcinogenesis
Abstract: Point mutations in the phosphorylation domain of the Bcr-Abl fusion oncogene give rise to drug resistance in chronic myelogenous leukemia (CML) patients. These mutations alter kinase-mediated signaling function and phenotypic outcome. An information theoretic analysis of the correlation of phosphoproteomic profiling and transformation potency of the oncogene in different mutants is presented. The theory seeks to predict the leukemic transformation potency from the observed signaling by constructing a distribution of maximal entropy of site-specific phosphorylation events. The theory is developed with special reference to systems biology where high throughput measurements are typical. We seek sets of phosphorylation events most contributory to predicting the phenotype by determining the constraints on the signaling system. The relevance of a constraint is measured by how much it reduces the value of the entropy from its global maximum, where all events are equally likely. Application to experimental phospho-proteomics data for kinase inhibitor-resistant mutants shows that there is one dominant constraint and that other constraints are not relevant to a similar extent. This single constraint accounts for much of the correlation of phosphorylation events with the oncogenic potency and thereby usefully predicts the trends in the phenotypic output.

Gautam Menon
Title: Stretching Fluctuations and Loop Formation in Short Double-Stranded DNA molecules
Abstract: Many of the physical properties of DNA are well modeled in terms of the mechanics of a homogeneous semi-flexible polymer (the worm-like chain), particularly at scales much larger than the individual base-pair. For very short DNA strands (say 1-20 base pairs), on the other hand, more microscopic atomic-scale descriptions would seem more appropriate. Recent experiments on DNA cyclization and DNA stretching probe a length regime intermediate between these extremes (between 35-90 bp's), providing evidence both for an anomalously enhanced tendency for DNA at this scale to form loops as well as for cooperative stretching fluctuations. Neither of these are explained by conventional approaches based on the worm-like chain model. I will describe our approach to this problem, presenting a comparison of predictions from theory with experimental data, suggestions for new methods of looking at the data itself and a physical picture for the experiments.



Konstantin Mischaikow
Title: A Database Schema for Multiparameter Dynamical Systems

Remi Monasson
Title: Learning in the temporal domain with an integrate-and-fire neuron
Abstract: Twenty years ago E. Gardner showed how statistical mechanics concepts and tools could be used to understand the classification of neural patterns according to their average activity. But what happens if the classification depends on the precise timing of the spikes, and not only the firing rate? I will report some recent results with R. Rubin and H. Sompolinsky on this issue.

Alexander Morozov
Title: Statistical Mechanics of Chromatin Structure
Abstract: Genomic DNA is packaged into chromatin in eukaryotic cells. The fundamental building block of chromatin is the nucleosome, a 147 bp DNA segment wrapped around the surface of a histone octamer. Nucleosomes function to compact DNA and to regulate access to it both by physical occlusion and by providing the substrate for numerous covalent epigenetic tags. We study sequence specificity of intrinsic histone-DNA interactions by using maps of nucleosomes assembled in vitro on genomic DNA. We infer free energies of nucleosome formation with a biophysical model that rigorously takes steric exclusion between neighboring nucleosome particles into account.
Surprisingly, most nucleosomes do not appear to be positioned by periodic dinucleotide distributions or by exclusion of longer sequence motifs such as A-tracts - rather, their locations are simply controlled by the A/T and G/C content of the underlying DNA sequence. A similar sequence signature is observed in nucleosome-free control experiments, likely because intrinsic nucleosome sequence preferences are correlated with those revealed by sonication and micrococcal nuclease digestion assays.

Hong Qian
Title: Nonequilibrium Phase Transition in a Biochemical System: Emerging landscape, time scales, and a possible basis for epigenetic-inheritance
Abstract: We consider a small driven biochemical network, the phosphorylation-dephosphorylation cycle (or GTPase) with a positive feedback. We investigate its bistability, with fluctuations, in terms of a nonequilibrium phase transition based on ideas from large-deviation theory. We show that the nonequilibrium phase transition has many of the characteristics of classic equilibrium phase transition: Maxwell construction, discontinuous first-derivative of the "free energy function", Lee-Yang's zero for the generating function, and a tricritical point that matches the cusp in nonlinear bifurcation theory. As for the biochemical system, we establish mathematically an emergent "landscape" for the system. The landscape suggests three different time scales in the dynamics: (i) molecular signaling, (ii) biochemical network dynamics, and (iii) cellular evolution. For finite mesoscopic systems such as a cell, motions associated with (i) and (iii) are stochastic while that with (ii) is deterministic. We suggest that the mesoscopic signature of the nonequilibrium phase transition is the biochemical basis of epi-genetic inheritance. Michael Schick
Title: "Rafts" as mixtures of lipids and cholesterol; are we still at sea?"

Boris Shklovskii
Title: Self-assembly of viruses

Boris Shraiman
Title: Evolution, Sex and Statistical Mechanics

Eric Siggia
Title: Geometry and Genetics

Eduardo Sontag, Rutgers University
Title: Interconnections in biochemical networks: signaling, impedance, and insulators
Abstract: When analyzing or designing systems made up of interconnected components, it is desirable to be able to predict global behaviors through a bottom-up analysis, based on the knowledge of the behaviors of the individual components together with the interconnection structure. One potential difficulty in such a modular approach is the existence of "retroactivity" effects, which imply that the behaviors of components may change upon interconnection. Indeed, this is a well-appreciated fact in electrical, mechanical, and other engineering fields, and is the reason that "operational amplifiers" are routinely introduced into circuits in order to enforce "unidirectional signal propagation" through insulation from impedance effects. We will discuss how this phenomenon appears in biomolecular systems, analyze their effects on steady state as well as dynamic behavior, and suggest a design of "biological OpAmps" based on enzymatic futile cycles that may play a role in synthetic as well as natural biological systems.

Harry Swinney
Title: Lethal protein produced in response to competition between bacterial colonies
Abstract: We have conducted experiments on neighboring colonies of /P. dendritiformis /bacteria grown on an agar gel [1]. The colonies mutually inhibit growth through secretions that become lethal if the level exceeds a well-defined threshold. Analysis of the secretions reveals the presence of subtilisin (a protease) and a 12 kDalton protein, which we have named Slf (sibling lethal factor). Subtilisin promotes the growth of the colonies, while Slf is lethal. Slf is found to be encoded by a gene belonging to a large family of bacterial genes of previously unknown function. The experimental results are used to develop a model (six coupled PDEs), which predicts that once subtilisin exceeds a threshold, as occurs at the interface between competing colonies, then Slf is secreted into the medium and rapidly kills cells. Laboratory tests yield results in accord with the predictions of the model. The existence in many bacteria of genes encoding homologs of the gene that encodes Slf suggests that the mechanism we observe for self-regulation of colony growth may well occur in other bacteria.
[1] A Be'er, G Ariel, O Kalisman, Y Helman, A Sirota-Mad, HP Zhang, EL Florin, SM Payne, E Ben-Jacob, and HL Swinney, submitted.

Chao Tang
Title: Linking network function and topology

Yuhai Tu
Title: The dissipative nature of adaptation and its thermodynamic cost
Abstract: In this talk, we will first show the dissipative (nonequilibrium) nature of adaptation kinetics in simple biological signaling networks. Next, we will determine the thermodynamic cost for accurate adaptation in E. coli chemotaxis by using a detailed model for its adaptation process. The computed energy requirement reveals the possible chemical energy source that drives adaptation in E. coli chemotaxis. Our analysis uncovers an interesting connection between adaptation and ultrasensitivity, two seemingly opposite but equally desirable functions of biological signaling systems. Finally, we will discuss characteristic signatures of these dissipative systems which may be used to detect the underlying nonequilibrium effects experimentally.

Eric Vanden Eijnden
Title: Navigating through the maze of rare events
Abstract: Rare events such as conformation change of macromolecules, chemical reactions in solution, nucleation events during phase transitions etc. pose challenges both for computations and modeling. At the simplest level, these events can be characterized as the hopping over a free energy barrier associated with the motion of the system along some reaction coordinate. Indeed this is the viewpoint underlying classical tools such as transition state theory or Kramers reaction rate theory, and it has been successful to explain rare events in a wide variety of context. However this picture presupposes that we know or can guess beforehand what the reaction coordinate of the event is. In many systems of interest -- protein folding, enzyme kinetics, protein-protein interactions, etc. -- making such educated guesses is hard if not impossible. The question then arises whether we can develop a more general framework to describe rare events, elucidate their pathway and mechanism, and give a precise meaning to a concept such as the reaction coordinate. In this talk I will discuss an attempt at such a framework and indicate how it can be used e.g. in the context of molecular dynamics simulations to develop efficient algorithms to accelerate the calculations.

Massimo Vergassola
Title: Bacterial chemotaxis as a game against nature
Abstract: Bacteria respond to chemical cues by performing a biased random walk that enables them to migrate towards attractants and away from repellents. Bias is achieved by regulating the duration of the bacterial runs as a function of the history of chemoattractant detections experienced by the bacterium. This time-signal is processed using a time convolution function that can be assayed measuring the response of the bacterium to short pulses of chemoattractant. The convolution constitutes an elementary form of memory, which is encoded at the molecular level by the processes of (de-)methylation and (de-)phosphorilation of the underlying biochemical network. While the latter is being characterized in increasing detail, the evolutionary and functional reasons shaping the chemotactic response remain largely unknown. We shall show that the response observed experimentally emerges from evolution in hostile natural environments as the game-theoretical MaxiMin strategy. In other words, the observed chemotactic behavior is the response that ensures individual bacteria to uptake the largest minimum amount of chemoattractant in any profile thereof.

Geoffrey West
Title: Damage and Repair; Sleep, Aging and Nucleotide Substitution Rates
Abstract: Damage and repair are ubiquitous across all of biology. The network systems that sustain life are typically dissipative, leading to "wear and tear" at all scales. Metabolism fuels repair to combat entropy production, yet is itself dissipative and a major source of damage. These ideas will be discussed in the context of three examples: sleep, aging and nucleotide substitution rates. What sets the scale of our sleep time, our lifespan and our rate of evolution?

Lai-Sang Young, Courant Institute
Spike-time reliability of neural oscillator networks
Abstract: I will discuss the reliability of large networks of coupled oscillators in response to fluctuating inputs. In this talk, intrinsically active neurons are idealized as phase oscillators, and the networks are assumed to be layered, a "layer" being a group of neurons having similar characteristics and driven by the same source. Reliability is the opposite of trial-to-trial variability; a system is reliable if a signal elicits identical responses upon repeated presentations. The effects of network structure, cell heterogeneity and noise on reliability will be discussed. This is joint work with Kevin Lin and Eric Shea-Brown.