SUMOylation stabilizes sister kinetochore biorientation to allow timely anaphase

During mitosis, sister chromatids attach to microtubules from opposite poles, called biorientation. Sister chromatid cohesion resists microtubule forces, generating tension, which provides the signal that biorientation has occurred. How tension silences the surveillance pathways that prevent cell cycle progression and correct erroneous kinetochore-microtubule attachments remains unclear. Here we show that SUMOylation dampens error correction to allow stable sister kinetochore biorientation and timely anaphase onset. The Siz1/Siz2 SUMO ligases modify the pericentromere-localized shugoshin (Sgo1) protein before its tension-dependent release from chromatin. Sgo1 SUMOylation reduces its binding to protein phosphatase 2A (PP2A), and weakening of this interaction is important for stable biorientation. Unstable biorientation in SUMO-deficient cells is associated with persistence of the chromosome passenger complex (CPC) at centromeres, and SUMOylation of CPC subunit Bir1 also contributes to timely anaphase onset. We propose that SUMOylation acts in a combinatorial manner to facilitate dismantling of the error correction machinery within pericentromeres and thereby sharpen the metaphase-anaphase transition

Discrete Modeling of Lattice Systems: The Concept of Shannon Entropy Applied to Strongly Interacting Systems

Discrete modeling is a novel approach that uses the concept of Shannon entropy to develop thermodynamic models that can describe fluid-phase behavior. While previous papers have focused on reviewing its theoretical background and application to the ideal-gas model as one limiting case for fluid phases, this paper addresses its application to lattice models for strongly interacting condensed phase systems, which constitute the other limiting case for fluids. The discrete modeling approach is based on the discrete energy classes of a lattice system of finite size, represented by a distribution of discrete local compositions. In this way, the model uses the same level of discretization as classical statistical thermodynamics in terms of its partition functions, yet avoids (1) a priori averaging of local compositions by utilizing a distribution, and (2) confinement to systems of infinite size. The subsequent formulation of the probabilities of discrete energy classes serves as the basis for introducing the concept of Shannon information, equivalent to thermodynamic entropy, and for deriving the equilibrium distribution of probabilities by constrained maximation of entropy. The results of the discrete model are compared to those derived from Monte Carlo simulations and by applying the Guggenheim model of chemical theory. We point out that this applicability of discrete modeling to systems of finite size suggests new possibilities for model development