Bulletin of the American Physical Society
APS March Meeting 2014
Volume 59, Number 1
Monday–Friday, March 3–7, 2014; Denver, Colorado
Session Q12: Invited Session: Irreversibilty and Entropy Production in Biological Dynamics |
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Sponsoring Units: GSNP DBIO Chair: Jeremy England, Massachusetts Institute of Technology Room: 205 |
Wednesday, March 5, 2014 2:30PM - 3:06PM |
Q12.00001: Roles of Entropic Funnels and Irreversibility in RecA Mediated Homology Recognition Invited Speaker: Mara Prentiss The self-assembly complex systems requiring the correct pairing of more than approximately 3 distinct binding sites faces significant entropic barriers and can suffer from kinetic trapping in conformations containing some correct pairings. If the pairings have energies of the order of the thermal energy kT, then thermodynamic pairing cannot provide the stringencies required for biological systems. It is well known that kinetic proofreading systems can provide much better stringency by including an irreversible step; however, simple versions of such systems fundamentally tradeoff speed and stringency. RecA mediated homology recognition is an example of a system that can provide excellent rapid recognition that can last for days without irreversibility. The combination of speed and stability in the absence of irreversibility depends on the probability that accidental matches extend over of m contiguous binding sites. If the probability decreases sufficiently strongly with m, rapid and efficient homology recognition can occur via a system of checkpoints that limit the number of binding sites that can come in contact, which provides enthalpic and entropic advantages. Increasing the number of contacts requires passing sequence dependent energy barriers. The simplest version of such a system is an initial weakly bound state that is independent of site matching, which is separated from the next conformation by a sequence dependent barrier. The sequence dependent barrier for correct matches must be low enough for the correct match to progress to the next conformation before unbinding from the initial state, whereas the barrier for mismatches must be high enough that it is highly probable that the mismatch will unbind before they pass through the barrier. RecA employs a series of several sequence dependent barriers. The energy gap that reduces the need for irreversibility is the result of the correct pairing having orders of magnitude more contiguous matching sites than the nearest mismatch present in the sample. [Preview Abstract] |
Wednesday, March 5, 2014 3:06PM - 3:42PM |
Q12.00002: Thermodynamics meets information in copolymerization processes Invited Speaker: Pierre Gaspard Copolymers are natural supports of information. This latter is contained in the sequence of monomeric units composing every copolymer. A well-known example is DNA in biology. At the molecular scale, the growth of a single copolymer is stochastic and proceeds by successive random attachments or detachments of monomers continuously supplied by the surrounding solution. The thermodynamics of copolymerization with or without a template shows that fundamental links exist between entropy production and the information content of the copolymer sequence [1,2]. During depolymerization, this information is erased in a way compatible with Landauer's principle [3]. These advances open new perspectives to understand information transmission during DNA replication and, more generally, information processing at the molecular scale in biology and polymer science. \\[4pt] [1] D. Andrieux and P. Gaspard, Nonequilibrium generation of information in copolymerization processes, Proc. Natl. Acad. Sci. USA 105, 9516 (2008). \\[0pt] [2] D. Andrieux and P. Gaspard, Molecular information processing in nonequilibrium copolymerizations, J. Chem. Phys. 130, 014901 (2009). \\[0pt] [3] D. Andrieux and P. Gaspard, Information erasure in copolymers, EPL 103, 30004 (2013). [Preview Abstract] |
Wednesday, March 5, 2014 3:42PM - 4:18PM |
Q12.00003: Talk 4 Invited Speaker: Pankaj Mehta |
Wednesday, March 5, 2014 4:18PM - 4:54PM |
Q12.00004: Reliable cell cycle commitment in budding yeast is ensured by signal integration Invited Speaker: Chao Tang Cells have to make reliable decisions in response to external and/or internal signals that can be noisy and varying. For budding yeast \textit{Saccharomyces cerevisiae}, cells decide whether and when to commit to cell division at the Start checkpoint. The decision is irreversible and has the physiological significance for coordinating cell growth with cell division. The trigger of the Start, the G1 cyclin Cln3 is a dynamic sensor of the nutrient and cellular conditions with low copy number and rapid turnover time. Here we quantitatively investigate how cells process the information from Cln3 to make the Start decision. By using an inducible Cln3 and monitoring the time cell waits before Start transition (G1 length), we find that G1 length is inversely proportional to Cln3 concentration, which implies that Start is triggered when the integration of Cln3 concentration over time exceeds certain threshold. We identify the Start repressor, Whi5 as the integrator. The instantaneous kinase activity of Cln3-Cdk1 is recorded over time on the phosphorylated Whi5, and the decision is made only when the phosphorylation level of Whi5 reaches a threshold. Furthermore, we find that Whi5 plays an important role for coordinating growth and division -- cells modulate Whi5 level in different nutrient conditions to adjust the Start threshold. The strategy of signal integration, which reduces noise and minimizes error and uncertainty, has been found in decision-making behaviors of animals. Our work shows that it is adopted at the cellular level, suggesting a general design principle that may be widely implemented in decision-making and signaling systems. [Preview Abstract] |
Wednesday, March 5, 2014 4:54PM - 5:30PM |
Q12.00005: Maximum entropy, Nonadditive entropies and Biology Invited Speaker: Steve Presse Gibbs once presciently noted that the elegance and simplicity of the principles of statistical physics were worthy of independent development outside of thermodynamics. Biophysical systems --from the single cell to the single protein level-- provide an ideal framework in which to test and apply far-from-equilibrium generalizations of statistical physics. Here we discuss two theoretical topics at the intersection of statistical physics and biology. First, we will describe a recipe for deriving, from first principles, probabilistic equations of motion from limited biophysical single particle tracking data. That is, we will show that maximum entropy principles can be used to determine the most likely statistical weights of trajectories from an ensemble of allowed system trajectories. For instance, using this reasoning, we can show under what circumstances Markov processes and chemical master equations rigorously follow from the data. Second, we will explore the logical implications of using a principle other than maximum entropy to select models (e.g. a model could be a trajectory ensemble in conformational space of a biomolecule) from non-equilibrium biophysical data. In particular, we will show that nonadditive entropy maximization can lead to biophysical models with features that go beyond what is warranted by the data. [Preview Abstract] |
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