Program

From the periodic firing of neurons to the flashing of fireflies, the synchronization of rhythmic activity plays a vital role in the functioning of biological systems. Synchronization often occurs by global coupling, where each oscillator is connected to every other oscillator through a common mean field. A distinctly different type of transition to synchronized oscillatory behavior is observed in suspensions of yeast cells. Relaxation experiments demonstrate that, slightly below a critical cell density, the system is made up of a collection of quiescent cells, whereas slightly above this density, the cells oscillate in nearly complete synchrony. This type of transition is much like quorum-sensing transitions in bacteria populations, where each member of a population undergoes a sudden change in behavior with a supercritical increase in the concentration of a signaling molecule (autoinducer) in the extra-cellular solution. We have studied large, heterogeneous populations of discrete chemical oscillators (~100,000) to characterize the two different types of density-dependent transitions to synchronized oscillatory behavior. For different chemical exchange rates between the oscillators and the surrounding solution, we find with increasing oscillator density (1) the gradual synchronization of oscillatory activity or (2) the sudden "switching on" of synchronized oscillatory activity. We have also studied spatially distributed groups of excitable particles that diffusively exchange activator and inhibitor species with the surrounding solution. All particles are nonoscillatory when separated from the other particles; however, spatiotemporal oscillations spontaneously appear in groups above a critical size.

A. F. Taylor et al., Science 323, 614 (2009).
M. R. Tinsley et al., Phys. Rev. Lett. 102, 158301 (2009).

In order to understand social systems, it is essential to identify the circumstances under which individuals spontaneously start cooperating or developing shared behaviors, norms, and culture. In this connection, it is important to study the role of social mechanisms such as repeated interactions, group selection, network formation, costly punishment and group pressure, and how they allow to transform social dilemmas into interactive situations that promote the social system. Furthermore, it is interesting to study the role that social inequality, the protection of private property, or the on-going globalization play for the resulting "character" of a social system (cooperative or not). It is well-known that social cooperation can suddenly break down, giving rise to poverty or conflict. The decline of high cultures and the outbreak of civil wars or revolutions are well-known examples. The more suprising is it that one can develop an integrated game-theoretical description of phenomena as different as the outbreak and breakdown of cooperation, the formation of norms or subcultures, and the occurence of conflicts.

Lactase persistence (LP) is common among people of European ancestry, but with the exception of some African, Middle Eastern and southern Asian groups, is rare or absent elsewhere in the world. Lactase gene haplotype conservation around a polymorphism strongly associated with LP in Europeans (213,910 C/T) indicates that the derived allele is recent in origin and has been subject to strong positive selection. Furthermore, ancient DNA work has shown that the 213,910*T (derived) allele was very rare or absent in early Neolithic central Europeans. It is unlikely that LP would provide a selective advantage without a supply of fresh milk, and this has lead to a gene-culture coevolutionary model where lactase persistence is only favoured in cultures practicing dairying, and dairying is more favoured in lactase persistent populations. We have developed a flexible demic computer simulation model to explore the spread of lactase persistence, dairying, other subsistence practices and unlinked genetic markers in Europe and western Asia’s geographic space. Using data on 213,910*T allele frequency and farming arrival dates across Europe, and approximate Bayesian computation to estimate parameters of interest, we infer that the 213,910*T allele first underwent selection among dairying farmers around 7,500 years ago in a region between the central Balkans and central Europe, possibly in association with the dissemination of the Neolithic Linearbandkeramik culture over Central Europe. Furthermore, our results suggest that natural selection favouring a lactase persistence allele was not higher in northern latitudes through an increased requirement for dietary vitamin D.

See the video of the talk.

The lecture will first introduce the general properties of networks helping the understanding of complex system behavior and translating our knowledge of social or technological networks to cellular networks and vice versa aiding cross-disciplinary research and breaking conceptual barriers of thinking.

Link density (the development and dissolution of crowded links) is a key feature of evolving networks. Hubs, modules, and modular overlaps are all reflecting this basic property at various levels of network topology. A novel and integrative modularization method family, the ModuLand method (www.linkgroup.hu/modules.php) revealed a decrease in the overlap of modules in yeast protein-protein interaction networks after stress (Palotai et al., 2008). The disintegration of both inter-modular contacts and modules after the removal of caspase-cleaved proteins from the human interactome was also detected. At the adaptation phase the identification and role of trend-setting creative elements (Csermely, 2008; 2009) will be shown.

The disintegration of the modular structure in stress (during the decrease of system resources) fits well to the series of topological phase transitions of networks (Csermely, 2009) and helps the system by ‘quarantining’ the damage; decreasing noise propagation and allowing a larger independence of various units, thus expanding the response-space. The re-integration of the modular structure after stress offers a chance for learning, adaptation and modular evolution (Csermely, 2008; Korcsmaros et al., 2007). This dual disintegration/reintegration process gives a chance for stress-induced re-juvenilation of aging networks (Kiss et al., 2009), which may well be a key mechanism behind hormesis and stress-conditioning.

Doron Lancet, Aron Inger, Don Armstrong*, Raphael Zidovetzki* and Hamutal Arbel

The lipid world model deals with an alternative scenario for the early evolution of life, which we have implemented in silico through the graded autocatalytic replication domain (GARD) model. In GARD, self aggregating amphiphilic molecules (such as lipids) form assemblies of various molecular compositions, grow through absorption, and split to produce progeny. The information of each aggregate is embodied within its composition (the molecular counts vector), and may be bequeathed with varying fidelity to offspring generated by assembly fission. We have previously demonstrated that when a limited degree of amphiphile in-situ polymerization takes place, there is an increase in the number of attractor-like stationary states, i.e. composomes and their clusters (compotypes). This may be interpreted as enhanced replication fidelity in the presence of larger molecular sizes, constituting a potential path for the appearance of polymer-containing protocells in ways that are independent of polynucleotide templating.
Two major criticisms regarding the GARD model were the paucity of chemical realism in terms of molecular properties of the amphiphiles, and the difficulties in demonstrating an evolution-like process that involves bona-fide assembly selection. We have recently developed R-GARD (Real GARD) in which the constituent molecules possess physicochemical properties and kinetic parameters derived from literature values. We demonstrate that many of the basic properties of GARD, including dynamic changes of composition that involve compotypes are manifested.
In parallel, we explored “classical” GARD simulations (with statistically-selected kinetic parameters), embodying key modifications that allow one to better study selection. For completeness, we examine the transitions from every possible composition to every other. To overcome computational barriers, the simulated GARD in this case has a very small molecular repertoire (NG=6, as compared to the typical NG=100), as well as small pre-split assembly size (2No=8). We pre-compute an all-to-all transition probability matrix based on GARD kinetics, and used this matrix to examine the behavior of a population of GARD assemblies, typically kept at a constant population of 50. Positive selection is implemented either by enhanced the transition probabilities for certain target compositions, or by increasing durability in the constant-population “reactor”. We observe that a significant number of the compositions show a measurable response to selection, manifested as increased population frequency. We now explore parameters governing this imposed selection so as to seek an optimum in the response, while maximizing the resemblance to natural selection in real biological systems.

Phage lambda, a virus that attacks E. coli bacteria, is amongst the simplest organisms that make a developmental choice. An infected bacterial cell goes either into the `lytic' state, where the phage DNA rapidly replicates and eventually kills the cell, or a `lysogenic' state, where the phage goes dormant and replicates along with the cell. Interestingly, phage lambda can count -- the decision depends on how many copies of the phage DNA infect a single cell simultaneously. With a single infection the cell is always killed, while with a double infection the choice between lysis and lysogeny is made more randomly. I will try to explain this behaviour using some simple game theory. For a certain class of games where one has to make choices based on limited information, it is optimal for a single player to use a deterministic strategy, whereas if there are multiple players it may be optimal to use a stochastic strategy. I will argue that this mirrors the shift from the deterministic to the stochastic strategy used by infecting phage when going from single to double infections.

How many molecular species do we have to consider in a systems level model of a living being? Currently, text books and data bases create the impression that there are not so many, e.g., a couple of hundred thousand. Moreover, models of bio-chemical sub-systems of a cell consider usually much less chemical species than these subsystems actually have in reality. The result of this underestimation is that explanations and systems biology tools are mostly species-oriented. In order to answer the question above, we have to clarify what a molecular species is. E.g. we could say that a molecular species is an equivalence class that consists of all those molecules that look the same. Then it appears that there is virtually a (close to) infinite number of species to be considered. Thus, in order to get a better quantitative view of the complexity we need other units to count.

In the second part I will discuss two approaches that might help to cope with this problem. First of all, we have to represent molecular reaction networks implicitly. To illustrate this approach I will use a simple artificial chemistry and "rule-based modeling in space" as an example. In a second step, given an implicitly represented reaction network, we can apply algebraic (or constraint-based) methods to identify
units. Chemical organization theory will be presented as an example.

S. Solomon will unfortunately not be able to attend the symposium. Annick Lesne has been very kind to accept to give a talk.

This talk describes some of the issues that follow from the fact that plants typically live in crowded environments. Such plants compete for limited resources, and these interactions are usually among close neighbours. This is important because local dispersal of propagules, environmental heterogeneity, and local interactions, together generate strong spatial structure in plant communities. So when studying their dynamics, we ought not to adopt the mean-field assumption (pairwise interactions in proportion to spatial average densities), widely used in ecology. Spatial structure is both a cause and an effect of the dynamical processes, with interesting and non-intuitive consequences for the abundance and coexisence of plant species.