PML nuclear bodies (NBs) are involved in the regulation of key nuclear pathways but their biochemical function in nuclear metabolism is unknown. In this study PML NB assembly dynamics were assessed by live cell imaging and mathematic modeling of its major component parts. We show that all six nuclear PML isoforms exhibit individual exchange rates at NBs and identify PML V as a scaffold subunit. SP100 exchanges at least five times faster at NBs than PML proteins. Turnover dynamics of PML and SP100 at NBs is modulated by SUMOylation. Exchange is not temperature-dependent but depletion of cellular ATP levels induces protein immobilization at NBs. The PML-RARα oncogene exhibits a strong NB retention effect on wild-type PML proteins. HIPK2 requires an active kinase for PML NB targeting and elevated levels of PML IV increase its residence time. DAXX and BLM turn over rapidly and completely at PML NBs within seconds. These findings provide a kinetics model for factor exchange at PML NBs and highlight potential mechanisms to regulate intranuclear trafficking of specific factors at these domains.

We demonstrate how a single-celled organism could undertake associative learning. Although to date only one previous study has found experimental evidence for such learning, there is no reason in principle why it should not occur. We propose a gene regulatory network that is capable of associative learning between any pre-specified set of chemical signals, in a Hebbian manner, within a single cell. A mathematical model is developed, and simulations show a clear learned response. A preliminary design for implementing this model using plasmids within Escherichia coli is presented, along with an alternative approach, based on double-phosphorylated protein kinases.

BackgroundWe suggest a new type of modeling approach for the coarse grained, particle-based spatial simulation of combinatorially complex chemical reaction systems. In our approach molecules possess a location in the reactor as well as an orientation and geometry, while the reactions are carried out according to a list of implicitly specified reaction rules. Because the reaction rules can contain patterns for molecules, a combinatorially complex or even infinitely sized reaction network can be defined.For our implementation (based on LAMMPS), we have chosen an already existing formalism (BioNetGen) for the implicit specification of the reaction network. This compatibility allows to import existing models easily, i.e., only additional geometry data files have to be provided.ResultsOur simulations show that the obtained dynamics can be fundamentally different from those simulations that use classical reaction-diffusion approaches like Partial Differential Equations or Gillespie-type spatial stochastic simulation. We show, for example, that the combination of combinatorial complexity and geometric effects leads to the emergence of complex self-assemblies and transportation phenomena happening faster than diffusion (using a model of molecular walkers on microtubules). When the mentioned classical simulation approaches are applied, these aspects of modeled systems cannot be observed without very special treatment. Further more, we show that the geometric information can even change the organizational structure of the reaction system. That is, a set of chemical species that can in principle form a stationary state in a Differential Equation formalism, is potentially unstable when geometry is considered, and vice versa.ConclusionsWe conclude that our approach provides a new general framework filling a gap in between approaches with no or rigid spatial representation like Partial Differential Equations and specialized coarse-grained spatial simulation systems like those for DNA or virus capsid self-assembly.

The mammalian cell nucleus contains a variety of organelles or nuclear bodies which contribute to key nuclear functions. Promyelocytic leukemia nuclear bodies (PML NBs) are involved in the regulation of apoptosis, antiviral responses, the DNA damage response and chromatin structure, but their precise biochemical function in these nuclear pathways is unknown. One strategy to tackle this problem is to assess the biophysical properties of the component parts of these macromolecular assemblies in living cells. In this study we determined PML NB assembly dynamics by live cell imaging, combined with mathematical modeling. For the first time, dynamics of PML body formation were measured in cells lacking endogenous PML. We show that all six human nuclear PML isoforms are able to form nuclear bodies in PML negative cells. All isoforms exhibit individual exchange rates at NBs in PML positive cells but PML I, II, III and IV are static at nuclear bodies in PML negative cells, suggesting that these isoforms require additional protein partners for efficient exchange. PML V turns over at PML Nbs very slowly supporting the idea of a structural function for this isoform. We also demonstrate that SUMOylation of PML at Lysine positions K160 and/or K490 are required for nuclear body formation in vivo.We propose a model in which the isoform specific residence times of PML provide both, structural stability to function as a scaffold and flexibility to attract specific nuclear proteins for efficient biochemical reactions at the surface of nuclear bodies.MCS code: 92C37

DEF-like and GLO-like class B floral homeotic genes encode closely related MADS-domain transcription factors that act as developmental switches involved in specifying the identity of petals and stamens during flower development. Class B gene function requires transcriptional upregulation by an autoregulatory loop that depends on obligate heterodimerization of DEF-like and GLO-like proteins. Because switch-like behavior of gene expression can be displayed by single genes already, the functional relevance of this complex circuitry has remained enigmatic. On the basis of a stochastic in silico model of class B gene and protein interactions, we suggest that obligate heterodimerization of class B floral homeotic proteins is not simply the result of neutral drift but enhanced the robustness of cell-fate organ identity decisions in the presence of stochastic noise. This finding strongly corroborates the view that the appearance of this regulatory mechanism during angiosperm phylogeny led to a canalization of flower development and evolution.