Bulletin of the American Physical Society
APS March Meeting 2011
Volume 56, Number 1
Monday–Friday, March 21–25, 2011; Dallas, Texas
Session V38: Focus Session: The Physics of Evolution II |
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Sponsoring Units: DCP DBP Chair: Eugene Shakhnovich, Harvard University Room: A130/131 |
Thursday, March 24, 2011 8:00AM - 8:36AM |
V38.00001: Natural Selection in Large Populations Invited Speaker: I will discuss theoretical and experimental approaches to the evolutionary dynamics and population genetics of natural selection in large populations. In these populations, many mutations are often present simultaneously, and because recombination is limited, selection cannot act on them all independently. Rather, it can only affect whole combinations of mutations linked together on the same chromosome. Methods common in theoretical population genetics have been of limited utility in analyzing this coupling between the fates of different mutations. In the past few years it has become increasingly clear that this is a crucial gap in our understanding, as sequence data has begun to show that selection appears to act pervasively on many linked sites in a wide range of populations, including viruses, microbes, \textit{Drosophila}, and humans. I will describe approaches that combine analytical tools drawn from statistical physics and dynamical systems with traditional methods in theoretical population genetics to address this problem, and describe how experiments in budding yeast can help us directly observe these evolutionary dynamics. [Preview Abstract] |
Thursday, March 24, 2011 8:36AM - 9:12AM |
V38.00002: Understanding Biological Fitness From First Principles Invited Speaker: This abstract not available. [Preview Abstract] |
Thursday, March 24, 2011 9:12AM - 9:48AM |
V38.00003: Geometry Genetics and Evolution Invited Speaker: Darwin argued that highly perfected organs such as the vertebrate eye could evolve by a series of small changes, each of which conferred a selective advantage. In the context of gene networks, this idea can be recast into a predictive algorithm, namely find networks that can be built by incremental adaptation (gradient search) to perform some task. It embodies a ``kinetic'' view of evolution where a solution that is quick to evolve is preferred over a global optimum. Examples of biochemical kinetic networks were evolved for temporal adaptation, temperature compensated entrainable clocks, explore-exploit trade off in signal discrimination, will be presented as well as networks that model the spatially periodic somites (vertebrae) and HOX gene expression in the vertebrate embryo. These models appear complex by the criterion of 19th century applied mathematics since there is no separation of time or spatial scales, yet they are all derivable by gradient optimization of simple functions (several in the Pareto evolution) often based on the Shannon entropy of the time or spatial response. Joint work with P. Francois, Physics Dept. McGill University. [Preview Abstract] |
Thursday, March 24, 2011 9:48AM - 10:24AM |
V38.00004: TBD Invited Speaker: This abstract not available. [Preview Abstract] |
Thursday, March 24, 2011 10:24AM - 10:36AM |
V38.00005: Dynamical Mueller's Ratchet: Population Size Dependence of Evolutionary Paths in Bacteria Dirk Lorenz, Jeong-Man Park, Michael Deem Experimental evolution has recently enabled the complete quantitative description of small-dimensional fitness landscapes. Quasispecies theory allows the mathematical modeling of evolution on such a landscape. Typically, analytic solutions for these models are only exactly solvable for the case of an infinite population. Here we use a functional integral representation of population dynamics and solve it using the Schwinger Boson method. This allows us to compute the first-order correction to the average fitness for finite populations. We will use these results to explain the experimental observations of dynamics of evolution in finite populations. [Preview Abstract] |
Thursday, March 24, 2011 10:36AM - 10:48AM |
V38.00006: At the crossroads of biophysics and evolution: protein robustness and evolvability Wouter Hoff, Masato Kumauchi Proteins consist of only 20 different amino acids with modest chemical reactivity, but perform a breathtaking range of functions. How do proteins achieve such functional versatility? Novel insights are emerging from research at the interface of protein biophysics and molecular evolution. Proteins are robustness against point mutations: most mutations do not abolish function. How can such robustness be reconciled with the effective evolution of protein function? We examine these issues using photoactive yellow protein (PYP), a prototype of the PAS domain superfamily. High-throughput biophysical measurements of active site properties, functional kinetics, stability, and production level on libraries of PYP mutants reveal that almost all mutants retain photocycle activity, but that the majority of substitutions significantly alter functional properties. Thus, PYP combines robustness with evolvability. The data also reveal the mysterious role of the conserved residues that define protein superfamilies: most PAS-conserved residues are required for maintaining protein production. Asn43, the most conserved residue in PAS domains, regulates PYP signaling kinetics. This residue is often substituted by Ser, Asp, and Thr in PAS domains while retaining two side chain hydrogen bonds. Thus, not residue identity at position 43 but the pattern of side chain hydrogen bonds is conserved. [Preview Abstract] |
Thursday, March 24, 2011 10:48AM - 11:00AM |
V38.00007: Deciphering evolutionary instructions for specifying protein fold and function Walraj Gosal, Rama Ranganathan Classical studies show that proteins have evolved to fold into functional native states that are, at best, only marginally stable through weak non-covalent interactions encoded by their primary sequences. How such fold and functional information is stored in a single amino acid sequence remains elusive. Using the statistical analysis of covariation between pairs of amino acids at all positions in a protein, here we identify groups of a few key physically-interconnected residues, which we term sectors. What information about the fold and function is captured by sectors? Using simulated-annealing Monte Carlo, we introduce variation in the sequence of a single member of the PDZ family in a manner that either preserves or disrupts sector correlations. Experimentally we show that function is specifically retained in designed proteins that obey sector correlations, and strikingly, even in the absence of a native state. Thus, we suggest that native-state stability is not a fundamental requirement for function, and is encoded in the sequence in an idiosyncratic manner in the PDZ family. [Preview Abstract] |
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