Network-topology-induced Fluctuations and Correlation effects in Neuronal Network Dynamics
Host: S. Jamal Rahi
From the perspective of nonlinear dynamical systems, nonequilibrium statistical physics, and scientific modeling, we will briefly describe our recent developments of mathematical methods used in analysis of the dynamics of neuronal networks arising from the brain. We will present some advance in the kinetic theory approach to neuronal network dynamics to include fluctuations and correlation effects induced by network topologies.
From correlations to interactions: how can one solve the inverse Ising problem?
Host: S. Jamal Rahi
Deducing the interactions between the components of a complex system from
the measure of their correlations is an important problem in data analysis
and modelling. In this talk I will review the successes and pitfalls of
various approaches coming from machine learning, statistical inference
and statistical physics. I will in particular present new methods for the
case of strongly correlated systems, for which all algorithms have failed
so far.
In a living cell, gene expression—the transcription of DNA to messenger RNA followed by translation to protein—occurs stochastically, as a consequence of the low copy number of DNA and mRNA molecules involved. Can one monitor these processes in a living cell in real time? How do cells with identical genes exhibit different phenotypes? Recent advances in single-molecule imaging in living bacterial cells allow these questions to be answered at the molecular level in a quantitative manner. It was found that rare events of single molecules can have important biological consequences.
From correlations to interactions: how can one solve the inverse Ising problem?
Host: S. Jamal Rahi
Deducing the interactions between the components of a complex system from
the measure of their correlations is an important problem in data analysis
and modelling. In this talk I will review the successes and pitfalls of
various approaches coming from machine learning, statistical inference
and statistical physics. I will in particular present new methods for the
case of strongly correlated systems, for which all algorithms have failed
so far.
Simple binding reactions: the evo-devo problem and, in particular, the "chromatin accessibility" problem
Host: S. Jamal Rahi
The evo-devo problem: 'Recent' evolution - that which has diversified plants and animals - has been effected with (essentially) a common set of enzymes. Development of a higher organism (eg a human) requires formation of many different structures with different functions, again using common enzymes. In both cases enzymes are directed to specific targets (from among a wide array of possible substrates) by the binding reaction called recruitement. It is easy to see how complex systems have evolved by changes in the surfaces of the recruiters and their targets.
Such concentration-dependent systems can readily go awry. Inhibitors - one form of protection - of various sorts are widely used to suppress basal reactions. Nucleosomes, for example, are widely believed to suppress basal transcription, but the determinants of nucleosome occupancy/positioning along DNA, and to what end, have remained controversial. A new assay reveals that nucleosome occupancy and positioning can be independent variables; that their determinants can be manipulated independently; that a so-called nucleosome-free-region contains instead an unusual nucleosome, held in place by a specific DNA binding protein; and that this unusual structure facilitates binding of the transcriptional activator Gal4.
Statistical physics of ion channels. No life without entropy!
Host: A. Libchaber & N. Arkus
I consider ion transport of a protein ion channel in a lipid
cell membrane. It is known that due to the large ratio of dielectric constants of water filling the channel (81) and of the surrounding lipid (2), an ion placed inside the channel has its electric lines confined in the channel. This should lead to a large electrostatic self-energy barrier and to exponentially large Ohmic resistance of the channel. In other words, one can say that in the channel a pair of positive and negative salt ions is bound by a string with potential energy growing linearly with the distance between them, and, therefore, a large energy is required to break the pair. In this sense, the ion pairs should resemble mesons of two confined quarks. Nevertheless biological channels are well transparent for ions. In order to address this paradox, we study reduction of the electrostatic barrier by a finite concentration of salt in water and/or by immobile charges on the internal channel walls. We show that both types of charges lead to the insulator-metal crossover (elimination of the barrier) with their increasing concentrations. The first one resembles the Mott insulator-metal transition in exciton gas with increasing density of excitons. The second one resembles the Mott transition in a doped semiconductor with growing concentration of impurities. What happens in ion channel is actually very similar to quark de-confinement at large density of mesons in Brookhaven experiments with heavy ion collisions.
Falling Uphill: Acceleration of the Emergence of Bacterial Antibiotic Resistance
Host: S. Jamal Rahi
The phenomenon of rapid emergence of resistance to antibiotics by bacteria is a fundamental problem both for evolutionary biology and in medicine. The role of spatial gradients in accelerating evolution rates has been underappreciated. While the emergence of resistance can occur in a well-stirred test tube of bacteria, there are ways to greatly accelerate the time scale of the process simply by creating very large spatial gradients of stress and populations, as long as the agents are motile. As an example of the role of spatial gradients we have accelerated the emergence of the resistance of the common bacteria 1E. coli to extremely high concentrations of the genotoxic antibiotic Ciprofloxacin to under 10 hours using a carefully designed microfabricated ecology. We show that we understand this process by presenting the initial inoculation number scaling laws of the emergent resistance times, valid down to an initial inoculation of only 100 bacteria. We use whole-genome sequencing techniques to reveal the genetic changes that the bacteria evolved in response to the antibiotic stress gradients within the chip. We believe the principles of rapid emergence of resistance revealed here will be of interest in other examples where rapid changes in drug resistance are observed in heterogenous environments, and in related phenomena such as the evolution of resistance to chemotherapy in oncology.
There comes a time in each of our lives where we grab a thick section of the morning paper, roll it up and set off to do battle with one of nature’s most accomplished aviators - the fly. If however, instead of swatting we could magnify our view and experience the world in slow motion we would be privy to a world-class ballet full of graceful figure-eight wing strokes, effortless pirouettes, and astonishing acrobatics. After watching such a magnificent display, who among us could destroy this virtuoso? How do flies produce acrobatic maneuvers with such precision? What control mechanisms do they need to maneuver? More abstractly, what problem are they solving as they fly? Despite pioneering studies of flight control in tethered insects, robotic wing experiments, and fluid dynamics simulations that have revealed basic mechanisms for unsteady force generation during steady flight, the answers to these questions remain elusive. In this talk I will discuss our strategy for investigating these unanswered questions. I will begin by describing our automated apparatus for recording the free flight of fruit flies and a new technique called Hull Reconstruction Motion Tracking (HRMT) for backing out the wing and body kinematics. I will then show that these techniques can be used to reveal the underlying mechanisms for flight maneuvers, wing actuation, and flight stability. Finally, I will comment on the implications of these discoveries for investigations aimed at elucidating the evolution of flight.
Transcription factors and cis regulatory elements: cis regulatory codes in DNA
Host: S. Jamal Rahi
The interactions between sequence-specific transcription factors (TFs) and their DNA binding sites are an integral part of the gene regulatory networks within cells. My group developed highly parallel in vitro microarray technology, termed protein binding microarrays (PBMs), for the characterization of the sequence specificities of DNA-protein interactions at high resolution. Using universal PBMs, we have determined the DNA binding specificities of >500 TFs from a wide range of species. These data have permitted us to identify novel TFs and their DNA binding site motifs, predict the target genes and condition-specific regulatory roles of TFs, predict tissue-specific transcriptional enhancers, investigate functional divergence of paralogous TFs within a TF family, investigate the molecular determinants of TF-DNA ‘recognition’ specificity, and distinguish direct versus indirect TF-DNA interactions in vivo. Further analyses of TFs and cis regulatory elements are likely to reveal features of cis regulatory codes important for driving appropriate gene expression patterns.
The prevailing framework for the description of activated processes such as conformational changes in macromolecules is to characterize them as the hopping over a free energy barrier associated with the motion of the system along a specific reaction coordinate. Indeed this is the picture underlying classical tools such as transition state theory or Kramers' reaction rate theory, and it has been successful in explaining activated processes in a wide variety of contexts. However, there is mounting experimental evidence that this two-state picture is too simplistic to describe complex biochemical processes such as protein folding, enzyme kinetics, or protein-protein interactions. In this talk, I will review recent data from single molecule experiments and present a series of models with increasing complexity that may explain the experimental findings and elucidate their microscopic origin. These results suggest that the wide range of timescales in the internal protein dynamics profoundly impact their folding pathways and rates.
